Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Annex II Feasibility Study

Safeguarding communities and their physical assets from climate induced disasters in Timor Leste

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

TABLE OF CONTENTS

Table of Contents ...... 2 1. Executive Summary ...... 1 2. Climate risk profile of Timor Leste ...... 3 2.1 Geographical Context ...... 3 2.2 Climate ...... 4 2.3 Socio-economic conditions overview ...... 5 2.4 Main socio-economic indicators ...... 6 2. 5 Incomes, assets and poverty ...... 8 2.6 Non-petroleum Sub-Sectors ...... 8 2.7 Geographic isolation and public services: water supply, irrigation, connecting roads and bridges...... 10 2.8 Climate change in Timor Leste ...... 15 2.8.1 Expected Climate Change ...... 15 2.8.2 Climate Change Impacts ...... 34 2.8.3 Impact on Water Resources ...... 34 2.8.4 Impact on Soil Erosion ...... 34 2.8.5 Impact on Agriculture ...... 34 2.8.6 Impact on coast ...... 36 2.8.7 Impact on infrastructure ...... 36 2.8.8 Exposure to climate-induced natural hazards ...... 39 2.8.9 Exposure to High/Very High Hydro-meteorological hazards ...... 41 2.9 Socio-economic risk assessment ...... 44 2.10 Prioritization of municipalities for intervention ...... 58 3. The most vulnerable municipalities and sucos ...... 59 3.1 Underlying causes of vulnerability ...... 59 3.2 Livelihood pressures on land: land use, deforestation due to logging and fuelwood...... 60 3.3 Livelihood pressures and financial vulnerability ...... 61 3.4 Exposure to hazards: threats to lives and assets ...... 63 3.5 Gender issues and vulnerability of other social groups (ethnic minorities) ...... 68 4. Status of current government policies, programmes and investments to address infrastructure deficiencies and community resilience; ...... 71 4.1 INDC (relevant priorities) ...... 71 4.2 NAPA ...... 72 4.3 Strategic Development Plan 2011-2030 (SDP): ...... 73 4.4 Other government strategies and policies ...... 73 4.5 Relevant Forestry Policies and laws ...... 81 5. Government Institutional arrangements and capacity for DRR and CCA ...... 88

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

6. Institutional Arrangements and capacity in Infrastructure Development ...... 93 6.1 Main investment programmes (both planned and under implementation) in large and small- scale infrastructure ...... 93 6.2 International Climate resilience projects ...... 95 6.3 Capacity Assessment of Government ...... 96 7. Main baseline programmes in agroforestry ...... 104 7.1 Review of Agroforestry Sector ...... 104 7.2 Government-led Agroforestry Interventions ...... 104 7.3 Non-Government-led Agroforestry Interventions ...... 104 7.4 Other relevant projects and initiatives ...... 106 8. Good practices, field evidence and lessons for scale-up ...... 109 8.1 Strengthening the Resilience of Small Scale Rural Infrastructure (SSRI) and Local Governance Systems to Climate Variability and Risks ...... 109 8.2 Background ...... 109 8.3 Main project objectives: ...... 109 8.4 Expected Project Outcomes ...... 110 8.5 Description of project implementation ...... 110 8.6 Water Supply Systems ...... 112 8.7 Rural access roads and bridges...... 122 8.8 Reservoirs and Irrigation systems ...... 129 8.9 River Embankments/flood defences ...... 133 8.10 Some Lessons Learned ...... 134 8.11 Project Current and Potential Impacts ...... 135 9. Gaps, barriers and needs for scaling up good practices for transformative change ...... 137 9.1 Policy and Legislation ...... 137 9.2 Technical Capacity – National Institutions ...... 137 9.3 Technical Capacity – Sub-national Institutions ...... 138 9.4 Financial Capacity ...... 139 9.5 Theory of Change...... 142 9.6 Project Logical Framework ...... 147 10. Proposed interventions towards achieving resilience of communities and safeguarding their physical and economic assets in the face of climate change ...... 156 10.1 Project objective, outputs and impacts ...... 156 10.2 Proposed GCF Project Outputs ...... 156 11. technical Feasibility and approaches of proposed interventions ...... 171 11.1 Proposed Multi-hazard, risk and vulnerability mapping methodology ...... 171 11.2 Risk and Vulnerability Modelling and Mapping ...... 184 11.3 Detailed Data Requirements ...... 186 11.4 Economic Loss and Damages current practice and feasibility of proposed technologies 191

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

11.5 The Desinventar database ...... 197 11.6 Sector Data Availability ...... 199 11.7 Development of an asset inventory database ...... 201 11.8 DRMapp ...... 201 11.9 A Cost model for DRMapp ...... 202 11.10 Review of Drone technology ...... 204 11.11 Climate Proofing Infrastructure in the 6 target municipalities – feasibility and methodology ...... 208 11.12 Agro-forestry and reforestation for catchment management and infrastructure climate proofing and protection ...... 232 11.13 Delivery mechanism of Agroforestry Intervention (considering financial and sustainability options) ...... 239 11.14 Detailed set of activities for Agroforestry Social Business development ...... 241 11.15 Estimated Project Cost of the Agroforestry and reforestation Intervention ...... 242 12. Knowledge Management, Learning and strategic communication ...... 243 12.1 Introduction ...... 243 12.2 Connecting people to information and knowledge ...... 243 12.3 Connecting People to People ...... 245 12.4 Institutional KM improvement ...... 248 12.5 Developing and embedding KM tools and practices ...... 249 13. project impact evaluation ...... 250 14. Conclusion ...... 252 15. Annexes ...... 256 Annex 1- Development indicators for Timor leste ...... 257 Annex 2 – List of Climate Resilience Projects Funded by International Agencies ...... 259 Annex 3 - Review of Existing hazard modelling and Mapping for Timor Leste ...... 262 Annex 4 - Data availability for hazard and risk modelling and mapping for Timor Leste ...... 270 Annex 5 - Map of proposed infrastructure projects ...... 272 Annex 6 – Maps showing catchments in which agro-forestry will be implemented ...... 273 Annex 7 – Infrastructure beneficiary sucos by municipality ...... 277 Annex 8 – Prototype climate proofing design of small-scale rural infrastructure units for timor leste 281

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

5. LIST OF FIGURES Figure 2-1: Map of Timor-Leste ...... 3 Figure 2-2: Elevation of Timor-Leste ...... 4 Figure 2-3: Flow diagram of the existing PDID process for selection of infrastructure projects .. 14 Figure 2-4: Flow diagram of the existing PDID process for implementation of infrastructure projects ...... 15 Figure 2-5: Monthly mean temperature at 11 climate stations in Timor Leste (Source, INC) ...... 17 Figure 2-6: Monthly rainfall based on average at 36 stations in Timor Leste (Source, INC) ...... 18 Figure 2-7: Patterns of Monthly rainfall in Timor Leste based on cluster analysis (Source, INC) 19 Figure 2-8: Comparisons of seasonal cycles of rainfall in Timor-Leste calculated from every 30- years monthly rainfall climatology with 10-years interval based on CRU TS 3.1 dataset (Source, INC) ...... 19 Figure 2-9: Decadal trend of mean annual rainfall over Timor-Leste based on CRU TS 3.1 ...... 20 Figure 2-10: Time series of seasonal rainfall over Timor-Leste taken from CRU TS 3.1 (1901- 2009 periods) ...... 21 Figure 2-11: Time series of seasonal rainfall over Timor-Leste taken from CRU TS 3.1 (1901- 2009 periods). (Source, INC) ...... 22 Figure 2-12: Spatial correlations of area-averaged monthly rainfall anomalies in Timor-Leste with sea surface temperature anomalies in the Indo-Pacific region ...... 22 Figure 2-13: Patterns of onset of the rainy seasons in Timor-Leste based on the result of cluster ...... 23 Figure 2-14: Patterns for the end of the rainy seasons in Timor-Leste based on the result of cluster ...... 23 Figure 2-15: Variability and trend of onset and end of the wet season over Timor-Leste (area- averaged) during 1951-2007 periods. Calculations are based on the methodology used by Liebmann et al. (2007). Daily rainfall data from Aphrodite was used for calculating the onset and end of the wet season and red dash-line is the end of Julian day (365) and the value beyond this red dash-line represents the Julian day of the following year...... 24 Figure 2-16: Trend of mean sea level rise from observed multi-mission satellite altimetry during October 1992 – November 2009 (units in mm/year; left), and projected increase of sea level based in the future based on the average of current trends (units in mm; right)...... 25 Figure 2-17: Seasonal rainfall differences in Timor-Leste based on the output of RCM projected for 2050 (mean value of 2041-2060 periods) and 2070 (mean value of 2061-2080 periods) relative to the 1981-2000 baseline (in %). Source, INC) ...... 27 Figure 2-18: Seasonal rainfall differences in Timor-Leste based on GCM ensembles under the SRES A1B scenario projected for 2050 (mean value of 2041-2060 periods) and 2070 (mean value of 2061- 2080 periods) relative to the 1981-2000 baseline (in %) ...... 28 Figure 2-19: Seasonal rainfall differences in Timor-Leste based on GCM ensembles under the SRES A2 scenario projected for 2050 (mean value of 2041-2060 periods) and 2070 (mean value of 2061- 2080 periods) relative to the 1981-2000 baseline (%)...... 29 Figure 2-20: Seasonal rainfall differences in Timor-Leste based on GCM ensembles under SRES B1 scenario projected for 2050 (mean value of 2041-2060 periods) and 2070 (mean value of 2061- 2080 periods) relative to the 1981-2000 baseline (%)...... 30 Figure 2-21: Projections of monthly mean temperature anomalies in Timor-Leste based on the multi-model ensemble mean under four RCP scenarios and SRES A1B scenario...... 31 Figure 2-22: Changes in the spatial patterns of rainfall types in Timor-Leste based on the 20 GCMs multi-model ensemble projection under four RCP scenarios at three different future periods, i.e. in 2011-2040, 2041-2070 and 2071-2100...... 32 Figure 2-23: Projected changes of total area at different rainfall types ...... 33 Figure 2-24: Exposure of Dwellings to all high/very high hydro-meteorological hazards ...... 42 Figure 2-25: Exposure of rural roads to high/very high intensity floods and landslides ...... 42 Figure 2-26: Exposure of main roads to high/very high intensity floods and landslides ...... 43 Figure 2-27: Exposure of water sources to high/very high hydro-meteorological hazards ...... 43 Figure 2-28: Exposure of all crops to high/very high hydro-meteorological; hazards ...... 44

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Figure 2-29: Flood Hazard map ...... 45 Figure 2-30: Landslide Hazard map of Timor-Leste ...... 50 Figure 2-31 Erosion Susceptibility Map ...... 53 Figure 6-1: Number of projects by municipality between 2011-2017 ...... 95 Figure 9-1: Theory of Change of the project ...... 144 Figure 11-1: Timor Leste weather station ...... 180 Figure 11-2: Emera Road #2 (E-RR-02) (new proposed road in red) ...... 219 Figure 11-3: The existing road condition along the proposed road for E-RR-02 ...... 219 Figure 11-4: illustrates the existing road condition along the proposed road for E-RR-02...... 219 Figure 11-5: Completed Reservoir installation in Ermera...... 222 Figure 11-6: The flood plain at Gegrama, Ermera Municipality ...... 228 Figure 11-7: Floodplain at Suco Mehara, Lautem ...... 228

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

1. EXECUTIVE SUMMARY This feasibility report details the approach to climate change adaptation to safeguard vulnerable rural communities and their physical and economic assets from climate change induced disasters. Access to climate resilient rural infrastructure which support the lives and livelihoods of the poorest communities of mono culture, small-holder farmers in Timor Leste, has been worsening in the past years as a result of increasing climate variability, and the resulting increased hazards from floods, flash floods, landslide, soil erosion and prolonged droughts which destroy infrastructure. Communities are faced with risks of isolation, livelihood vulnerability and increasing exposure to impacts of climate variability and extreme events that will only accelerate without urgent adaptation investment at a required scale.

Increasing climatic variability and unpredictability, particularly in relation to rainfall and extreme weather events, presents a significant risk to the lives and livelihoods of rural people in Timor Leste. Those living in the remote interior of the country as well as in coastal areas are highly exposed. Approximately 70 percent of Timor-Leste’s 1.2 million people who live in rural areas are highly vulnerable to climate change. Impacts of intensified extreme events on critical rural infrastructure which damage and degrade assets, particularly water supply infrastructure, drainage, embankment and river protection structures, and community level feeder roads and bridges leave the rural population without the basic services and in full isolation.

The project objective is to safeguard vulnerable communities and their physical and economic assets from climate change induced disasters and aims to address institutional, financial and legislative barriers and shift the baseline scenario towards climate resilience through two main outputs:

Output 1 - Climate risk reduction and climate-proofing measures for small-scale rural infrastructure are implemented to build the resilience of vulnerable communities in six priority districts; Output 2 - Climate risk reduction and climate-proofing measures for small-scale rural infrastructure are implemented to build the resilience of vulnerable communities in six priority districts

The project proposes to invest in climate proofing of small scale rural infrastructure to address the adaptation challenge. The proposed investments in the 6 target municipalities targets the most vulnerable, which are highly susceptible to the main hydro-meteorological disasters, of floods and flashfloods, landslide, erosion and droughts due to their topography, intensifying land degradation and increasing climate variability and addresses the government’s current investment deficit in essential small scale rural infrastructure, perceived higher cost of investing in climate proofing, and the need to protect these infrastructure from intensifying hazards.

The project will first, strengthen capacities of mandated institutions to assess and manage the risks of climate induced hazard extremes, embed new skills, innovative methods and technologies in risk identification and mitigation and improve availability of climate risk information. Second, the project will invest in small-scale rural infrastructure to ensure their resilience to climate change induced extreme hazards, by scaling up proven successful adaptation methods and technologies in climate proofing rural infrastructure against climate-induced hazards. GCF funds will be used to improve engineering skills and practices for climate proofing of rural infrastructure that are essential for the reduction of prevalent social vulnerabilities and widespread economic disparities. Third, the project will invest in ecosystem protection and management that is conducive to a long-term resilience of the target communities and their physical and economic assets. The project will enable land use and livelihoods that benefit from agro-forestry and forest products and contribute to forest rehabilitation and maintenance. The project thus will support landscape restoration and land stability as an investment to climate risk reduction and long-term resilience.

The project impact potential is high, with 175,840 direct beneficiaries (15% of total population) of climate proofed infrastructure, 300 ha of reforested and rehabilitated land, up to $203 Million of avoided damages and losses from single hazardous events. The project will ensure a fundamental

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I change in how infrastructure development is done, by ensuring climate resilience in the design, construction and maintenance, by improving capacities for undertaking climate hazard and risk assessment, improved access to climate risk information and development and embedding of standards for designing climate resilient infrastructure which will include the use of innovative best practice approaches such as bioengineering. The project ensures sustainable development, by protecting natural capital through eco-system based adaptation approaches for long-term resilience of infrastructure and increased resilience to climate change. The project will also ensure sustainable development through the enhancement of policy and enabling environment by supporting cross-sector climate policy, standards and guidelines, and long-term investment planning and financing for climate resilient infrastructure development. The project meets the needs to the recipients by addressing the underlying need for climate resilient infrastructure to link isolated communities, improve access to resources, and reduce poor land use practices which place livelihood pressures on the land exacerbates exposure to climate-induced hazards. The project is aligned with national adaptation priorities including climate change and DRR policies as well as strategic development plans and further ensures country ownership through strong stakeholder and community engagement. The embedding of climate resilience into the development of infrastructure and eco-system based catchment management approaches ensures long-term cost effectiveness and efficiency by reducing maintenance costs and increasing service life of infrastructure.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

2. CLIMATE RISK PROFILE OF TIMOR LESTE

2.1 Geographical Context

The island of Timor sits at the south-eastern end of the archipelago of volcanic islands, the Banda Arc, running eastwards from the Indonesian island of Bali. Timor-Leste occupies the eastern half of the island and is a relatively small country with an area of 14,954 km2. This includes the main land area of 13,989 km2, Oecusse enclave of 817 km2, Atauro Island of 140 km2 and Jaco Island of 8 km2. Administratively, Timor-Leste is comprised of 13 Districts including Oecusse enclave, 65 Administrative posts and 442 sucos or villages.

The topography, particularly of the mainland, is comprised of hills and mountain ranges and is dominated by a massive central mountainous backbone rising to approximately 3000 meters and dissected by deep valleys (Figure 2-2). On the northern side, the mountains extend almost to the coast, but on the southern part the mountains taper off some distance from the coast, which provides areas of coastal plain. Approximately 44% of the territory has slope of more than 40%.

Figure 2-1: Map of Timor-Leste

The island of Timor represents the active accretion of the Banda volcanic arc to the Australian continental margin. Hence Timor has been gradually uplifting over time. This has geomorphologically, resulted in very steep slopes representing the equilibrium between geological uplift and erosion. It has also resulted in exceptionally high sediment loads in the rivers leading to extensive and thick alluvial fans and flood plains along river courses and across the coastal plains. The geology of Timor-Leste is mainly limestone and coral.

Studies involving height variations and measurements of uplifted Quaternary reefs and post orogenic sediments undertaken by Kaneko et. al. (2007) reveal that Timor is rising at a rate of 5 to 10 mm per year. As almost half of Timor’s land has a slope of 40° or more reflecting this steep equilibrium, classic soil profiles have not developed across much of the central spine of the island.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Soils are characterised by shallow rocky soils that are alkaline, not particularly fertile, do not store water well, and are easily eroded. In addition, the very high temperatures cause soil nutrients to decompose faster than they accumulate, which further exacerbates the soils’ erodibility. The most fertile soils are found in river valleys, flat lands, and along the southern coastal plains.

Forest remains the largest land use/cover category in the country, occupying about 50% of the total land area1. The second largest is grassland and shrubs occupying about 27% of the total land area. The remaining are bare land, rice fields and dry farms covering approximately 3.3%, 2.8% and 1.5% of total land respectively while settlement covers only 0.2% of the total land area.

Figure 2-2: Elevation of Timor-Leste

2.2 Climate

Timor-Leste’s climate is influenced by the Asian monsoon system. There are two distinct rainfall patterns: the northern monomodal rainfall pattern, which produces a 4–6 months wet season beginning in December that affects most of the northern side of the country and tapers to the east; and the southern bimodal rainfall pattern, which produces a longer (7–9 month) wet season with two rainfall peaks starting in December and again in May, which affects the southern side of the country. Annual rainfall is very low along the northern coast of East Timor (<1000 mm y-1), low to moderate throughout the central and elevated areas (1500–2000 mm y-1), and moderate (>2500 mm y-1) in high altitude areas. In common with most tropical locations, intense downpours of rainfall are common.

1 The Food and Agriculture Organization of United Nations's Global Forest Resources Assessment (2005 & 2010) and the State of the World's Forests (2009, 2007, 2005, 2003, 2001)

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

There is little seasonal variation in temperature with monthly mean temperatures varying by no more than 3oC between the coolest months of July and August to the warmest months of October and November. Diurnal (daily) temperature variations range from 7oC to 13oC. Temperature decreases with altitude: for example, in Maubisse, which is 1400 m above sea level, the mean monthly temperature is approximately 17oC in July and 24oC in November, compared with Liquica, which is 25 m above sea level and where the mean monthly temperature is approximately 25oC in August and 31oC in February.

Variability in East Timor’s climate is significantly influenced by the El Niño Southern Oscillation, which in El Niño years changes the timing and volume of rainfall. In some places, such as Ainaro and Lautem, annual rainfall is up to 50% less than average in El Niño years. In others, such as Baucau and Oecussi, annual rainfall in El Niño years is greater than average. In all places El Niño suppresses rainfall in the January–March wet season, with some places experiencing only 25% of the rainfall usually received in these months. In general, the wet season is delayed by 2 to 3 months in El Niño years, with implications for crop planting and food security. In the year following an El Niño, rainfall can be higher than the annual average, with implications for flooding.

2.3 Socio-economic conditions overview

Timor Leste is among the youngest countries in the world that gained independence only in 2002. It is a least developed country, a post-conflict society with a fast-growing population that remains dependent upon subsistence agriculture. Approximately 70 percent of Timor-Leste’s 1.06 million people live in badly serviced rural areas. Low agricultural production combined with a lack of access to markets and inputs contributes to high food insecurity, particularly in rural areas. 74 percent of the rural population suffers moderate and severe food insecurity.2 Annual food deficits also contribute to malnutrition rates, especially for children and women, which have been among the highest in the world.3 From an economic standpoint, inflation remains high and with an estimated 61.5 percent of the population under the age of 25, lack of viable employment and income generation opportunities continues to present a challenge and risk for the youth population.

Baseline: Since gaining independence in 1999, Timor-Leste has faced great challenges in rebuilding its infrastructure, strengthening the civil administration, and generating jobs for young people entering the work force. This pervasive infrastructure deficit keeps the rural population in isolation, lacking access to basic public services and deprived of mobility and economic opportunities. A network infrastructure is crucial for the functioning of today's economy and society, notably infrastructure for energy (e.g. grids, power stations, pipelines), transport related fixed assets, such as roads and bridges and water supply (such as, water supply pipelines, reservoirs, waste water treatment facilities and irrigation canals). They are sets of interconnected networks of physical infrastructure which facilitate the production and distribution of goods and economic services, and form the basis for the provision of basic social services. There are considerable gaps in this network infrastructure in Timor Leste, hindering service delivery, growth and economic development. In fact, many country assessments for Timor Leste recognise a direct correlation between the high incidents of poverty and significant gaps in infrastructure.4 It therefore comes as no surprise that the government’s priority investments are directed towards addressing the current infrastructure deficit that is considered the major binding constraint for socio-economic development. It is critical however that climate change impacts are duly addressed as to ensure that these foundational investments and associated services are durable in support of local development and long-term resilience.

2 Food and Nutrition Security Task Force. Ministry of Agriculture and Forests Algis Map. Dili, January 2012. 3 World Bank, Country Partnership Strategy, op.cit. 4 USAID, Country Development Cooperation Strategy, 2013-2018. 4 Food and Nutrition Security Task Force. Ministry of Agriculture and Forests Algis Map. Dili, January 2012. 4 World Bank, Country Partnership Strategy, op.cit. 4 USAID, Country Development Cooperation Strategy, 2013-2018.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Rural populations of Timor Leste are highly exposed to a number of hazards including flash floods, landslides, soil erosion, coastal flooding and drought, due to unfavorable terrain, socio-economic factors and intensification of these climate-induced hazards over time. In addition, anthropogenic factors such as poor, non-climate-resilient design and application of infrastructure construction standards and the limited investment in operation and maintenance, are exacerbating exposure and resulting in the failure of small scale rural infrastructure, which is essential to the development of rural communities. Impacts include isolation of communities when roads and bridges are damaged by localized extreme events, contamination of unprotected water sources, reduction in yield of water supply sources due to droughts, flooding of communities due to inadequate or failing flood defences. In addition, the institutional and financial capacity of Local Administrations and communities to adapt to the situation is weak. This includes the ability of municipality planning officials, engineers and decision makers to identify areas that are critically vulnerable to climate hazards, to draw the links between ecosystems management and infrastructure development, and to identify, appraise, prioritize, design, cost and ‘budget in’ greater resilience measures. There is also a weak ability to understand and address gender and climate change related development and equity issues at local level.

2.4 Main socio-economic indicators

Timor-Leste has a UN Human Development Index of 0.595 and ranks 133 out of 188 countries, which puts Timor-Leste in the medium human development category. Between 2000 and 2014, Timor-Leste’s HDI value increased from 0.468 to 0.595, an increase of 27.1 percent or an average annual increase of about 1.73 percent. However, when discounted for inequality, the current HDI of 0.595 falls to 0.412, a loss of 30.7 percent due to inequality in the distribution of the HDI dimension indices. Annex 1 lists the main UNDP (2015) human development indicators for Timor Leste5.

Population and demographics The total population is 1.2 Million, with 70% of the population living in rural areas. Life expectancy is 68.2 years which is an increase of 33.8 years on the life expectancy in 1980. Population is concentrated in the westerns part of the country, and in Dili and Baucau – the two cities.

Economy Since gaining independence in 1999, Timor-Leste has faced great challenges in rebuilding its infrastructure, strengthening the civil administration, and generating jobs for young people entering the work force. The development of offshore oil and gas resources has greatly supplemented government revenues. This technology-intensive industry, however, has done little to create jobs in part because there are no production facilities in Timor-Leste, although there are plans to develop domestic processing capacity.

The government has focused significant resources on basic infrastructure, including electricity and roads. Limited experience in procurement and infrastructure building has hampered these projects. The underlying economic policy challenge the country faces remains how best to use oil-and-gas wealth to lift the non-oil economy onto a higher growth path and to reduce poverty.

Domestic product is $2.3 Billion (based on 2011 purchasing power parity), with 1.65% of GDP coming from Foreign Direct Investment and remittances 9.4% of GDP. Gross national income per capita is $5,362.50 (2011 purchasing power parity) with development assistance at 6% of GNI. Of note, and related to the poverty indicators is the Domestic credit provided by financial sector (% of

5 http://hdr.undp.org/en/countries/profiles/TLS

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

GDP) of -53.6%. The negative value for Timor Leste indicates a weak and unstable domestic financial framework and this is reflected in a very limited access to finance.

Poverty and Inequality In Timor-Leste 64.3% of the population (694,000 people) are multidimensionally poor while an additional 21.4 percent live near multidimensional poverty (231, 000 people). The breadth of deprivation (intensity) in Timor-Leste, which is the average of deprivation scores experienced by people in multidimensional poverty, is 50.1%. The multidimensional poverty headcount is 29.4% points higher than income poverty. This implies that individuals living above the income poverty line may still suffer deprivations in education, health and other living conditions.

Gender The Gender Development Index, based on the sex-disaggregated Human Development Index, defined as a ratio of the female to the male HDI, measures gender inequalities in achievement in three basic dimensions of human development: health (measured by female and male life expectancy at birth), education (measured by female and male expected years of schooling for children and mean years for adults aged 25 years and older); and command over economic resources (measured by female and male estimated GNI per capita). Timor Leste has a GDI of 0.868, indicating inequality for females against the three main indicators. Labour force participation is less than 40% overall, with only 24.6% of females making up the labour force compared to 50% of males. Only 56.6% of the school-age population receives secondary education and adult Literacy is 58.3%.

In rural Timor-Leste, the burden of agricultural work, coffee harvesting and caring for home gardens is generally shared between men and women. However, domestic responsibilities such as child- rearing, cooking, cleaning and overall family wellbeing, reflects traditional gender roles. This implies that women’s vulnerabilities to climate change and disaster, while similar to men, include specific additional concerns such as: • Access to water and firewood; • destruction of and damage to the home gardens; • damage to seeds; • hindered access to markets and hence sale of products/ generation of cash; • diseases and access to clinics; and • closing of schools. • Post-disaster health care

In Timor-Leste, women are often excluded from certain activities due to customary norms or lack of capital and ownership arrangements that confer all rights to men in the family. Women hold very few leadership positions within the districts. In cases where women do participate in local level planning, they are in the minority. An important aspect of gender mainstreaming in Timor-Leste is therefore to increase involvement of women in formal and informal decision-making processes.

Employment According to UNHDR 2015 Statistical Annex Timor Leste is 1.7 times below the average employment rate for developing countries and 1.9 times below the rate for the region. This trend is magnified when the gender disaggregate data is examined with the rate of employment among TL females being 2.5 times less than the regional average while males are 1.6 times below the rate of employment regionally. The working poor is 66.9% compared to the regional average of 23.8%. Youth unemployment is in line with the average for developing countries at 14.8%, but below the regional average of 18.6%, but this may mask the fact that a larger than average percentage of the potential Timor Leste work force is comprised of the youth (Population median age of 16.9 years). 50% of employment is in agriculture while 40% is in services.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

2. 5 Incomes, assets and poverty

Despite being an oil rich country, Timor-Leste is still one of the poorest countries in the Asia-Pacific region as the development indicators show. Its economic performance since gaining independence from Indonesia in 2002 has been fragile, characterized by slow-moving investment of aid funds and oil revenues. The country is set to benefit from the commercial exploitation of its petroleum and natural gas reserves and in June 2005, the National Parliament of Timor-Leste unanimously approved the Petroleum Fund (PF) law following public consultation (IMF, 2009). This PF law was aimed at effectively managing and investing oil revenue in the country’s development after exploitation of these resources ends.

Oil and gas contributes about 90% of total budget revenue for the country (IMF, 2011). In addition, oil wealth is estimated at US$24.3 billion or US$22,000 per capita (IMF, 2011). Furthermore, Timor- Leste’s petroleum fund balance was US$4.2 billion in 2008 and US$5.4 billion in 2009, and in 2010 this fund reached US$6.9 billion. The Fund held assets of $16.5 billion, by December 20146. The development of offshore oil and gas resources has greatly supplemented government revenues, but has done little to create jobs due to the lack of production facilities in Timor-Leste with gas currently being piped to Australia for processing.

With regards to non-petroleum GDP for the country, sectors of Industry and Services together with Agriculture including its sub sectors forestry and fishery are the two main sectors that dominate Timor-Leste’s economy.

2.6 Non-petroleum Sub-Sectors

In terms of share of non-petroleum GDP, sub-sectors such as industry and services and agriculture, forestry and fishery are the dominant sub-sectors that contribute to Timor-Leste’s GDP. The industry and services sector contributed approximately on average 55% of non-petroleum GDP between 2009 and 2012, compared to an average of 20% by the agriculture sector in the same period7. In addition, the percentage of share of non-petroleum GDP for public administration, defence, education, human health and social work activities is 20%.

While unemployment statistics in a largely agrarian and informal economy are difficult to ascertain, it must be admitted that in a country like Timor-Leste, informal sector activities are essential for income generation, particularly for those living in rural areas (i.e. > 70% of the population). Hence, with more than 50% or people formally employed in the agricultural sector (see Table 0-1) and with an even larger percentage of the population reliant on subsistence farming, and therefore engaged in the informal agricultural sector, the agriculture sector is perhaps the most important non-oil sector for Timor Leste.

Agriculture

Agriculture dominates economic activities in Timor-Leste (IV Constitutional Government Program, 2007-2012). It is subsistence agriculture with low inputs and outputs, and comprises crops and livestock, fisheries and forestry. It is estimated to employ more than 75% of Timorese people. Staple crops are maize, rice, and cassava with sweet potato, potato, mung bean, peanut and soya bean being widely grown in farmlands on steep slopes. The exception to this is the rice crop, which is mostly found on flat areas or terraces on moderate slopes. Cash tree crops such as coffee, coconut and candlenut are important and are grown on specific slopes and bands of elevations. For example, coffee plants are found in cool high elevation areas in some districts such as Ermera,

6 https://www.cia.gov/library/publications/resources/the-world-factbook/geos/tt.html 7 INC

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Aileu and Ainaro, while coconut plants are found in the coastal areas of some districts such as Baucau and Viqueque.

Farming in Timor-Leste is heavily dependent on rainfall patterns and therefore highly vulnerable to changes in rainfall quantity and timing. Land preparation takes place during the dry period e.g. from July to November followed by cultivation of maize, cassava, sweet potatoes and grain legume crops in around mid-November when the wet season starts. Maize crops are harvested around February. From February to May, farmers start to prepare paddy fields for rice cultivation. The rice crop is harvested between May and August. Production of crops is very low compared to other countries. For example, rice production in Timor-Leste is less than 2 ton/ha compared to 4.5 ton/ha in Indonesia (IV Constitutional Government Program, 2007- 2012). Average maize yield recorded in 2006, 2007 and 2008 were 1.8, 1.6 and 1.7 ton/ha, respectively. These yields are very low compared to hybrid variety yields of 6 ton/ha in irrigated fields in East Java and 5 ton/ha in dry land production in South Selves (Swastika et al. 2004). Low crop yields are considered to be due to low quality of seeds, and low or no inputs of fertilizers8.

Coffee is the most important of the commercial export tree crops grown in Timor-Leste. A recent estimate showed that more than 57% of the production area (53,816 ha based on 2009 observation) is in Ermera (IV Constitutional Government Program, 2007-2012). Coffee production ranges from 0.23 to 1.4 ton/ha. Annual income from coffee production is up to US$ 200 and this provides 90% of growers’ income. The main exporting venue for Timorese coffee production is the United States of America (USA). Net exported weight of coffee was 7.7 ton with a value of US $6,889.00 in 2004 and this increased to 8,328 ton with a value of US$ 12,492,134.00 in 2009. This figure shows that coffee production provides a significant income after oil and gas. The other advantage of growing coffee is that coffee plantations and their shade legume trees e.g. Paraserianthes falcataria (albizzia), Casuarina sp. and Leucaena spp. also play an important role in protecting soil from erosion.

Livestock is one of the most important sources of farmers’ income in Timor-Leste, and the contribution of this sector to the country’s non-oil GDP is estimated at US$ 4.6 million with an increase of 10.2% annually (MAFF, 2004).

Forestry

Forest cover currently comprises 48.4% of the total land area of Timor Leste. A recent study from a Japanese team indicated that there has been significant reduction in Timor- Leste’s forest cover for the period between 2003 and 2010 where more than 180,000 ha of forest were estimated to have been lost. Deforestation was found to be widespread in all districts for both dense and sparse forests. Reduction in dense forest coverage is especially rampant in Lautem, Viqueque, Bobonaro and Manufahi districts.

Many of the forests in Timor-Leste are thought to have been heavily affected by human intervention and there is a lack of measures to halt and reverse these activities. Recently, fragmented forests (mosaic land uses) are observed to be widespread in Viqueque, Baucau, Manufahi, Liquiça and Covalima, most likely a direct result of patch clearing for shifting cultivation. The two latest inventory studies conducted with the Japanese expert team and the forest inventory study in Bobonaro and Covalima (2008 and 2009) confirmed what has always been thought to be the condition of forests in Timor-Leste.

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Fisheries

The annual potential catch of fish is expected to be about 116,000 tonnes/year, but up until 1988, catches were only 3.5% (3000 tonnes) of this potential (Gutteres, 2003). Further, the economic value of exported fish could be up to US$ 5 million and fishing licenses US$ 15 million, these figures would contribute 5% to the country’s GDP.

Despite the country’s wealth of coastal and marine resources, limiting factors such as weakness of fisheries legislation and regulations, lack of monitoring systems, and inadequately resourced institutions to control and protect these resources, present challenges for the country to protect and use these resources for the benefits of the people of Timor-Leste. For instance, there was an estimated loss of US$ 36 million per year due to illegal fishing in the country9.

2.7 Geographic isolation and public services: water supply, irrigation, connecting roads and bridges.

A central pillar of the GoTL’s Strategic Development Plan (2011-2030) is the building and maintenance of core and productive infrastructure to enable Timor-Leste to develop economically and socially. The scale and cost of addressing the infrastructure deficit, however is large.

Roads and Bridges An extensive and well maintained road network is essential to connect communities, promote rural development, industry and tourism, and provide access to markets. Roads are the primary mode of transport and allow development and the delivery of resources to urban as well as rural areas. They are critical to most other sectors and support the delivery of community services, health care and education. Timor-Leste has an extensive system of national, regional and rural roads that provide access to the rural areas where 70% of the population lives. The network is generally constructed to the Indonesian pavement standard of 4.5 metres width (narrow by international standards) with lined masonry drains and two lane steel truss bridges. The Timor- Leste road network should comprise of 1,426 km of national roads that link districts to each other, 869 of district roads that link district centres with 3,025 km of sub-district and rural roads that provide access to villages and the more remote areas. The national road network comprises two coastal roads along the north and south coasts and five roads crossing the country and connecting with the two coastal roads. There are around 456 bridges in the road network.

Due to a lack of maintenance, the road network is deteriorating, with around 90% of national roads in poor or very poor condition with only 10% in fair condition, and over 90% of district roads in poor condition. Road construction and maintenance in the interior of Timor-Leste is particularly challenging due to mountainous terrain and because of high levels of mud and water as well as several natural hazards such as floods and landslides, resulting in many parts of the country being regularly isolated when roads and bridges become impassable, blocked or are completely washed away. Lack of investment in road maintenance often results in the need for emergency repairs, which is an expensive method of managing a road network. The poor state of the roads is increasing transport costs and impeding economic growth and the reduction of poverty at national, regional and local levels. Regional agriculture and industrial development are particularly affected by the state of our roads. Poor roads also result in very poor safety for all road users.

Given the extent and state of the road infrastructure, the GoTL’s priority is to rehabilitate and repair existing roads to maintainable standards to secure the road network currently in place. As the economy expands, investment in new roads will be required.

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GoTL Strategy and Actions for Roads and Bridges According to the SDP 2011-2030, Timor-Leste will undertake substantial and long-term investment to provide a road network which supports equity in national development, facilitates the transport of goods at a reasonable price, allows for the delivery of government services and promote agriculture and the growth of the private sector. This would be achieved through:

1. Delivery of a comprehensive roads maintenance program 2. Rehabilitation of all existing road to an international standard by 2020 3. Construction of 3,200 linear metres of new bridges to provide all-weather access on major routes within five years and the remainder of national and district roads by 2030. 4. Rehabilitate all rural roads to a minimum standard by 2015 (surfacing works using asphaltic material and minor shoulder works, drainage and slope protection) 5. Building the road infrastructure required to support the development of the south coast 6. Establishment of national ring road standards and establish a ring road to these standards by 2030.

The SDP prioritizes national and district roads and bridges and its programme of rehabilitation and construction is heavily supported by development partners (US$500 million over the next five years in the form of loans) such as World Bank and Asian Development Bank but these are mainly focused on national and district road projects. The SDP expenditure on roads and bridges for the period 2008-2013 was USD 253.6 Million and the target for 2014-2019 is USD 516.3 Million.

A World Bank review of the SDP10 stated that if all roads in Timor-Leste were rehabilitated to 'good' or 'fair condition', it would have a sufficiently extensive road network system to keep the economy moving forward smoothly for several years. However, in order to sustain the road network as a major asset base, a larger share of the national budget (1.09 times the non-oil expenditure) would need to be allocated for road maintenance. The review questioned the socio-economic development objectives and expected economic growth (such assessments are lacking in the SDP) to support the level of rehabilitation and construction outlined in the SDP. The review also highlighted that the maintenance requirements (currently lacking) to support this level of upgrades is onerous and not explicitly detailed in the SDP.

Water Supply

The two most significant causes of infant and child mortality in Timor-Leste – lower respiratory infection and diarrheal disease – are directly related to a lack of water supply and poor sanitation and hygiene. Investment in sanitation is an investment in health, education, the environment and poverty reduction. Improved sanitation typically yields about $9 worth of benefits for every $1 spent, based on a reduction in direct and indirect health costs, better education, improved water supply and increases in tourism.

The percentage of the population with access to an improved drinking source (either piped water, protected well or hand pump, tanker or bottled water) increased from 48% in 2001 to 66% in 2010. While the percentage of the population with access to improved sanitation facilities (pit latrine with slab, ventilated improved pit latrine or a pour/flush septic tank or pit) was 39% in 2010. In rural areas, 57% for rural areas has access to improved drinking water and 25% have access to improved sanitation facilities based on the 2010 Census. Springs are the main water source for the

10 Timor-Leste public expenditure review: Infrastructure: A joint ministry of finance and world bank review of the quality of infrastructure spending in Timor-Leste, focusing on roads, irrigation and electricity (file:///C:/Projects/TL%20GCF/70%20Documents/71%20Docs%20in/Reference%20docs/A_Joint_Ministry_of_Finance_an d_World_Bank_Report_on_Timor-Leste_Public_Expenditure_Review_Infrastructure.pdf)

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I rural eastern part of the country and the second main source in the rural central and western areas. For more than a third of Timorese families, access to water is ten or more minutes away. The main source of drinking water in urban areas is from household taps (42%). In rural areas, the main source of drinking water is from a well or spring (25%). Water shortages are common in many areas in the dry season.

Timor-Leste also has problems with drainage and storm water pollution in Dili and district centres. Waste and contaminants lie on the streets or in dried-up streams before being carried to the sea with the rain. In Dili during the wet season, many sections of drainage channels become blocked with solid waste, kankung and sediment, leading to flooding and dangerous levels of pollution.

Major water supply and sanitation projects have been carried out, but lack of operating and maintenance capacity has led to difficulties in sustaining them.

GoTL Strategy and Actions for Water Supply According to the SDP (2011-2030), the strategy for improving water supply and sanitation is based on achieving the following Millennium Development Goals by 2020: • 75% of Timor-Leste’s rural population will have access to safe, reliable and sustainable water • 40% of rural communities will have significantly improved sanitation facilities • Installation of approximately 400 water systems for 25,000 rural households in the next five years (at 80 systems per year) • Construction of community owned latrines • Provision of technical expertise and supervision for communities • Recruitment of 80 sub-district water and sanitation facilitators for sucos • Major investment in rehabilitating and extending irrigation systems and improving water storage in rural areas.

Irrigation

During the Portuguese colonial era, numerous small-scale communal irrigation systems were developed, using simple irrigation technology that relied on water supplies from small springs and run-off from mountain-sides. During the Indonesian occupation, free-intake river diversion irrigation schemes were constructed on the larger rivers, such as the Beikala scheme on the lower reaches of the Caraulun River.

After Independence, donors funded a series of Agriculture Rehabilitation Projects (ARPs) in the period from 2000 to 2008, mainly involving small-scale communal irrigation schemes, in addition to one larger ex-Indonesian scheme named Caraulun. In addition, a series of irrigation plans and designs were developed and analyzed during the period the ARPs were implemented, including pre-construction economic appraisals based on Economic Internal Rate of Return (EIRR) for a number of projects which showed negative EIRR, particularly of large irrigation schemes. These negative EIRRS have been largely ignored and schemes already rehabilitated and subsequently upgraded.

GoTL Strategy and Actions for irrigation To achieve food security, Timor Leste is aiming to increase the area of irrigated rice by 40% (from 50,000 hectares to 70,000 hectares) by 2020 (SDP 2011-2030). This would require significant investment in rehabilitating and extending irrigation systems and improving water storage.

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The existing irrigation systems are generally non-functional, due to a lack of maintenance and to damage to water intake channels. According to the SDP, the following strategic actions will be taken: 1) A comprehensive irrigation scheme inventory will be commissioned to identify existing schemes that can be enlarged and new schemes that could be developed. 2) Sources to feed existing and proposed irrigation schemes will be identified to support any expansion of farmland which will depend upon building new irrigation schemes that can survive the dry season. Storage systems will be developed to capitalize on rainy season excess rainfall and store for use in the dry season. 3) A large dams feasibility study will be conducted and, if large dams prove feasible, careful planning and investment in dams will be made to ensure that adequate water is available all year round for irrigation. 4) Dam pilot projects will be conducted to test the potential for reservoirs or small dams for smaller schemes in appropriate locations: in most cases, further upstream in water catchments. 5) Groundwater pilot projects will be conducted to find and prove groundwater. This will involve drilling 20 tubewells, mostly in the lowland and semi lowland areas, to identify future good locations and developing criteria for further development where findings are successful.

Expenditure on Infrastructure

In Timor-Leste, expenditure on infrastructure is implemented through three windows, these being line ministries’ Consolidated Fund of Timor-Leste (CFTL) budgets; the Infrastructure Fund; and the District Integrated Development Plan (PDID), a district development program which includes the construction of small-scale infrastructure projects with budgets of less than US$500,000. Line ministries’ CFTL budgets are used to execute all projects that have budgets to a value of less than US$1 million and which are expected to be completed within a year. The Infrastructure Fund, a multi-year fund that was established in 2011, is used to execute large projects with budgets to a value in excess of US$1 million and which are expected to take more than one year to complete. The main goal of the PDID is to develop the domestic private sector, with its secondary goals being to create an increased number of employment opportunities in rural areas and to provide high quality infrastructure demanded by the local population in these areas.

The focus on expenditure through the Infrastructure Fund is justified on the grounds that since its establishment in 2011, more than 85% of the total value of expenditure on infrastructure in Timor- Leste there has been implemented through this window. In addition, all of the large-scale infrastructure development projects listed in the SDP will be implemented through the Infrastructure Fund. Therefore, understanding the constraints on the execution of the SDP plan requires a strong knowledge of the institutions which govern this fund and the associated processes. From the viewpoint of the line ministries, the establishment of the Infrastructure Fund and supporting institutions involved several changes in the way larger projects were proposed, procured and monitored. Under the new system, line ministries continued to be responsible for proposing and justifying large projects. However, the Major Projects Secretariat (MPS) became responsible for undertaking an ex ante analysis of project proposals and for the presentation of this analysis to the Budget Review Committee (BRC) and the Council for Management of the Infrastructure Fund (CAFI). In the case of a number of proposed projects, including several proposed projects for the development of the irrigation sector, the MPS has concluded that the economic returns from the proposed project are not sufficiently high to justify the investment and that the project should not be approved. Although such projects have still been approved, the establishment of the Infrastructure Fund has meant that project proposals are subject to more intense scrutiny. The MPS also reports on the rate of progress and outcome of projects implemented through the Infrastructure Fund.

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Implementation of Rural Infrastructure The funding and implementation of rural infrastructure is done via the Planning and Implementation of District Development Investment Plan (formerly PDID now PDIM). The following is a description of the processes of selection and implementation of PDIM projects.

PDIM project selection process 1. At the level of the sucos, 3-4 projects are proposed annually from each suco, with sucos chiefs submitting proposals to Administrative Post Administrator 2. At the level of administrative post, the projects from all sucos (2-9 proposals depend on how many sucos in one AP and based on Suco Development Plan) are reviewed and loosely prioritized through discussions with suco chiefs. At this level, AP staff undertake initial feasibility studies during the review process. 3. All project proposals are then sent to municipality level where they are assessed against standard criteria and ranked. 4. Ranked projects are sent to the national level where budgets are set and the ranked projects that fit within the budget are ear marked for implementation.

Figure 2-3: Flow diagram of the existing PDID process for selection of infrastructure projects

PDIM Project Implementation Process

1. Once projects are approved for funding a verification team comprising personnel from municipality and administrative post undertake a site visit. Verification involves surveys aimed at confirmation of the number of beneficiaries and presumably technical measurements for the works to be done. 2. A feasibility study is then done by municipality engineers. 3. Design is then undertaken by the municipality engineers. 4. The BOQ is developed and the tender, procurement and contract process follows. The Municipality evaluates bids. Some of the challenges identified by municipalities in the procurement process include long timeframes between tender and contracting, lack of engineering expertise in contractor teams (although CVs for engineers are often submitted), 5. Once the contractor is engaged, the implementation starts and AP monitors the construction through the Community Development Officer (CDO). The CDO generally is not a qualified engineer with the capability to technically monitor the work, but relies on reports from the community on their level of satisfaction with the work. Some of the challenges that have been identified by municipalities and AP’s is the lack of expertise and resources (personnel, transportation, and equipment for monitoring engineering works) to properly monitor construction works.

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6. On completion, the work is verified by a team comprising municipality administrative post staff. Consultations with municipalities, APs and sucos found that there are sometimes issues identified only on completion at the final verification stage and although the contractor has up to 6 months after completion to address any issues (and 10% of the fee is withheld for this purpose), some of these issues can be avoided with better contractor management, monitoring of works and technical input and monitoring throughout implementation.

Figure 2-4: Flow diagram of the existing PDID process for implementation of infrastructure projects

The current PDIM process currently does not include climate risk considerations in the identification, prioritization, design or implementation of projects apart from those undertaken by donor-funding such as the UNDP SSRI project which is aiming to embed climate risk considerations into the PDIM process.

2.8 Climate change in Timor Leste

2.8.1 Expected Climate Change Projections cited in the reports of Intergovernmental Panel on Climate Change (IPCC), including those of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) project notable changes in the region’s climate for the future. In Timor-Leste, temperature is expected to increase by 0.3–1.2 °C by 2030 and 0.8–3.6 °C by 2070. Rainfall is predicted to decrease in the dry season and increase in the wet season with overall rainfall increasing by 7–13% by 2050. Extreme rainfall events such as tropical cyclones are expected to decrease in frequency but increase in intensity. Furthermore, an increase in rainfall is predicted for areas of high altitude. For example, the mountainous districts are projected to experience higher increase in rainfall during the wet season. In addition, sea level is expected to rise by between 9 and 76 cm by the year 2100.

First National Communication Timor- Leste completed its Initial National Communication (INC) in June 2014, under the United Nations Framework Convention on Climate Change (UNFCCC) which recognizes two possible major impacts of climate change including (a) a shift in seasonal and latitudinal precipitation patterns, and (b) an increase in the frequency and scale of extreme weather events.

Based on historical climate data and the results of climate scenarios, generated with Regional Climate Model (RCM) using the A1B emission scenario, and with 20 Global Circulation Models (GCMs) using new emission scenarios, Representative Concentration Pathways (RCPs), the following conclusions have been reached: • In the longer term, annual mean temperature over Timor-Leste has increased consistently with a rate of about 0.016°C per year. It is very likely that temperatures in Timor-Leste will

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continue to increase. Prior to the 2040s, the mean temperature anomalies in Timor-Leste are expected to increase by up to as much as 1°C for all emission scenarios. Post 2040s, the rate of increase will vary based on different scenarios. For the high emission scenario (RCP8.5)11 the increase in temperature relative to current conditions may reach 3°C by 2100, while for the low emission scenario (RCP2.6)12 it may increase by up to 0.5°C • Historically, the sea level surrounding the main island of the country has risen at about 5.5 mm/year. Over 100 years, the sea level rise may reach 76 cm. Based on the Pacific Climate Change Science Program (2011); Pacific Ocean acidification has also been increasing in Timor-Leste’s waters. It will continue to increase and threaten coral ecosystems. • Historical data suggests that during the 20th century and early 21st century, there were already some shifts in the peak of the wet season. In the future, the wet season onset may be delayed by about 20 days from the current climate pattern, while dry season onset will be delayed by as much as 11 days depending on the period and emission scenarios. Thus, in some areas the length of the wet season would shorten. • Extreme rainfall events are projected to become fewer but more intense as a result of decreasing numbers of tropical cyclones albeit with stronger intensity (Pacific Climate Change Science Program 2011). • Decreases in rainfall are projected in some parts of the country, as well as changes in its seasonal distribution, with respect to the 1981-2010 conditions. For example, the drier area on the northern coast of the country (annual rainfall less than 1000 mm) will expand in the future. • The water balance suggests that the area with a duration of water deficit period (LDP) of more than 8 months will expand while the area with LDP<5 months will shrink

Historical Climate Change in TL:

Based on historical rainfall and temperature record, the region is divided into three different climatic zones, i.e. (i) north coast region, characterized by average mean temperature of more than 24 0C, annual rainfall amount less than 1500 mm, with a dry season lasting for around five months; (ii) mountainous region, characterized by average mean temperature less than 24 0C, annual rainfall amount more than 1500 mm and dry season lasting for four months; and (iii) South coast region, characterized by average mean temperature more than 24 0C, annual rainfall amount of about 2500 mm, and dry season lasting for only three months (Kirono 2010).

Temperature: The climatology of monthly mean temperatures in Timor-Leste varies across different areas (Figure 2-5). Based on the climatology of mean temperatures of 11 climate stations located in different altitudes, the highest monthly mean temperature generally occurs during the peak of the rainy season when the optimum solar radiation occurs and there is intensive heating the surface. During the wet season, the mean temperature ranges from around 20°C to 30°C. During the dry season, the temperatures are lower, ranging from 16°C to 27°C.

11 The RCP8.5 combines assumptions about high population and relatively slow income growth with modest rates of technological change and energy intensity improvements, leading in the long term to high energy demand and GHG emissions in absence of climate change policies 12 The RCP2.6 emission and concentration pathway is representative of the literature on mitigation scenarios aiming to limit the increase of global mean temperature to 2°C

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Figure 2-5: Monthly mean temperature at 11 climate stations in Timor Leste (Source, INC)

In general, the country has experienced an increase of mean annual temperatures with an annual rate of increase of 0.016°C per year. Within the last decade, there has been a decreasing trend in the annual mean temperature of about -0.026°C per year (Figure 2-3). However, this downward trend could be related to the pause in global surface temperature rise due to the substantial role of decadal variability in the Pacific (Met-Office 2013). Meehl et al. (2011) suggested that the pause might also relate to the capacity of the deep ocean below 300 m in absorbing heat during the recent cooling periods. However, in the long term the effect of increasing greenhouse gases in the atmosphere in causing global warming is apparent.

Rainfall: In general, the rainfall pattern in Timor-Leste is strongly characterized by the Australian Monsoons. The peak of the rainy seasons usually occurs in January or February around 250 mm in average, and the dry seasons appear in July to October with the lowest rainfall average around 25 mm (Figure 2-6).

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Figure 2-6: Monthly rainfall based on average at 36 stations in Timor Leste (Source, INC)

Rainfall patterns in Timor-Leste vary from the driest area in the northeastern part to wetter areas in the western part of the country. There are five dominant rainfall types found in the country based on the PCA-cluster analysis of monthly rainfall climatology (Figure 2-7). The differences between these types are mostly found in the amount of their wet season rainfall. The Type 1 rainfall region represents areas in the western part of the country with the highest rainfall during wet season, especially in February and March, reaching around 400 mm in average. The Type 2 rainfall region is also located in the western part adjacent to the Type 1 location. In the Type 2 region, the characteristic Monsoonal rainfall is dominant with the rainfall peak reaching around 275 mm, especially in December, January and February. The Type 3 rainfall region has a peak rainfall around 225 mm and is found adjacent to the north coast region, running from the west to the east of the main region as well as in the separated region in the west. The southwestern part of the country also has the same Type 3 characteristic. The Type 4 rainfall region is located mainly in the centre of the country with a rainfall peak lower than the previous types, i.e. around 175 mm. The north coast region is predominantly characterized by Type 5 rainfall. It has the lowest rainfall compared to the other four rainfall types. The peak of wet season rainfall in a Type 5 area is not more than 150 mm.

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Figure 2-7: Patterns of Monthly rainfall in Timor Leste based on cluster analysis (Source, INC)

Rainfall Trends Long-term rainfall variability in Timor-Leste contributes to the change in rainfall climatology over different periods. This is shown by the comparison of the monthly rainfall climatology in different 30-year periods with ten-year intervals (Figure 2-6). The changes of rainfall climatology are mostly apparent in December, January, March and May, indicating an increase of rainfall during the rainy season. In contrast, there are no considerable changes found in the dry season, particularly in July, August and September.

Figure 2-8: Comparisons of seasonal cycles of rainfall in Timor-Leste calculated from every 30-years monthly rainfall climatology with 10-years interval based on CRU TS 3.1 dataset (Source, INC)

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Timor-Leste experienced rainfall changes during the 20th century and in the beginning of the 21st century. The rate of decadal trend of annual rainfall climatology in Timor-Leste is estimated at around 6.4 mm/decade (Figure 2-7). The rates of decadal rainfall trends are different for each season (Figure 2-8). A consistently increasing trend is found only in DJF season with the rate around 7.156 mm/decade. A similarly increasing trend of decadal rainfall is also found in SON with a rate of 0.4 mm/decade, but with the tendency of a downward trend after 1951-1980 climatology (see Figure 2-8). In contrast, the downward trends of decadal rainfall are shown in MAM and JJA seasons. These long-term downward trends are mostly due to dominant decrease of rainfall within the last few decades in those two seasons.

Figure 2-9: Decadal trend of mean annual rainfall over Timor-Leste based on CRU TS 3.1

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Figure 2-10: Time series of seasonal rainfall over Timor-Leste taken from CRU TS 3.1 (1901-2009 periods)

Rainfall Variability The annual rainfall amounts in Timor-Leste are also different each year and show a strong inter- annual variability associated with annual increases or decreases in rainfall that link to possible extreme climate events such as drought and flood. The considerable signs of rainfall variability with very little long-term trends are shown in the seasonal rainfall time series in Figure 2-9. Many studies have shown that the El-Nino Southern Oscillation (ENSO) could significantly affect rainfall variability in the Maritime Continent region (Aldrian; Susanto 2003; Aldrian et al. 2003; Boer; Faqih 2004; Faqih 2010; Hendon 2003). Similar to many countries within the region, rainfall variability in Timor- Leste is also strongly affected by ENSO. Figure 2.10 shows the spatial correlations between sea surface temperature anomalies (SSTa) in the Indo-Pacific region with the area-averaged rainfall anomalies in the country based on different time lags. Consistent negative correlations at different time lags are found in the central tropical Pacific, indicating considerable influence of ENSO to the rainfall variability in Timor-Leste. The ENSO signal impacting rainfall variability could be identified from the previous 3 months of SSTA data in the central Tropical Pacific, providing potential uses of SSTA data for seasonal climate predictions. Based on the same figure, it is suggested that rainfall variability in the region is not strongly influenced by the climate drivers in the Indian Ocean, especially the Indian Ocean Dipole (IOD) event since the correlations for the SSTA in the western and eastern parts of the Indian Ocean with rainfall anomalies are not significant.

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Figure 2-11: Time series of seasonal rainfall over Timor-Leste taken from CRU TS 3.1 (1901-2009 periods). (Source, INC)

Figure 2-12: Spatial correlations of area-averaged monthly rainfall anomalies in Timor-Leste with sea surface temperature anomalies in the Indo-Pacific region

Onset, End and Length of the Seasons

The season onsets are important especially for agricultural and water resource management. The onset of the wet season in Timor-Leste usually occurs in early November to early December with different timing across different regions. The advance or delay of the onset could reach around 15 days in respect of the mean onset date. Figure 2-13 shows the spatial pattern for the average timing of the wet season onset across different areas in Timor-Leste. The usual timing for the onset of the dry season is early to mid-April each year. However, due to the impact of climate drivers affecting climate variability, the onset could shift earlier or later with standard deviations up to 28 days from the mean onset date.

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Figure 2-13: Patterns of onset of the rainy seasons in Timor-Leste based on the result of cluster

Figure 2-14: Patterns for the end of the rainy seasons in Timor-Leste based on the result of cluster

The variability of the onset of both dry and wet seasons are clearly shown in the time series plot (Figure 2-14). The onset of the dry and wet seasons in Timor-Leste are analyzed using gridded observed data from Aphrodite Dataset (Yatagai et al. 2012). The methodology for these calculations follows the onset definition used by Liebmann et al. (2007). The length of both dry and wet seasons can also be seen from Figure 2-13 based on the combination of the onset of those two seasons. The onset of the dry and wet seasons in Timor-Leste indicates strong variability with a relatively slow rate of decreasing trends, i.e between -0.15 and -0.17 days per year for the dry and wet season, respectively. The strong variability is consistent with the period of climate events, especially ENSO, as shown from the strong deviations during the El Niño and La Niña year. The onset of the wet season tends to delay (advance) during a strong El Niño (La Niña) year. This occurs similarly for the end of the wet season (the dry season onset), but with some exceptions, depending on the El Niño (La Nina) intensity and duration. For example, the end of the wet season came earlier in 1982 at the beginning of El Niño event which was followed by the delay of onset within the same year. Meanwhile, in the 1972/73 El Niño event, the dry season onset came earlier in 1974 not long after the delay of the onset in 1973. The differences in the responses of the onset and end of the rainy season to ENSO behavior may influence the length of the wet season in the

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I country. As a result, the relationship between the length of the wet season and ENSO is potentially lower than the relationship of onset and end of the wet season with ENSO.

Figure 2-15: Variability and trend of onset and end of the wet season over Timor-Leste (area-averaged) during 1951-2007 periods. Calculations are based on the methodology used by Liebmann et al. (2007). Daily rainfall data from Aphrodite was used for calculating the onset and end of the wet season and red dash-line is the end of Julian day (365) and the value beyond this red dash-line represents the Julian day of the following year.

Variability of onset and end of the wet season within the Maritime Continent region, including Timor- Leste, is strongly affected by climate drivers in the Indo-Pacific region, especially ENSO. Since ENSO is the representation of climate phenomenon as a result of coupled air-sea interactions, it is acceptable and common to select one of many atmospheric and ocean variables in order to measure and identify ENSO behavior. A common variable used as an indicator of ENSO is sea surface temperature anomalies (SSTA). Analysis shows that the onset is strongly correlated with SSTA both in local (negative correlations) and in remote areas in the central tropical Pacific Ocean (positive correlations). Negative correlations over the local sea indicate that warm (cold) SSTA in the local area may increase (decrease) the heat flux transferred to the atmosphere through evaporations associated with more (less) intense convections that could bring advance (delay) of the wet season onset in the country. In contrast, positive correlations found in the central Tropical Pacific Region lead to an indication where warm (cold) SSTA in the region associated with the El- Niño (La-Niña) event is associated with the onset of the dry and wet seasons.

The areas of local SSTA that are significantly correlated with the onset are clearly shown in July and areas with significant correlations extend to August, September and October. This is in contrast with the correlations with SSTA in remote areas over the central tropical Pacific Ocean, where the most significant correlations are found in June and become weaker in the following months, i.e. July, August and September. The correlations become higher again for SSTA in October but with significant correlations in areas that shift from the central to the eastern part of the Tropical Pacific Oceans. Based on this finding, it can be concluded that the length of the wet season is not significantly correlated with the SSTA in the Tropical Pacific Oceans but that the onset is significantly correlated.

Sea Level Rise Based on the trends of sea level obtained from satellite altimetry data (referred to as multi-mission, see Figure 2-16), there were increasing trends of sea level rise surrounding Timor-Leste. The rate of SLR was found to be higher in the south coast (≥5.5 mm/year) than in the north (<5.5 mm/year) (Figure 2-16; left). On average, the rate of sea level rise surrounding the main island of the country

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I based on multi-mission satellite altimetry is around 5.5 mm/year. Assuming that this rate is linearly consistent to the future (2010-2100), the sea level in the region is projected to increase around 50 mm by 2100 (Figure 2-16; right).

Figure 2-16: Trend of mean sea level rise from observed multi-mission satellite altimetry during October 1992 – November 2009 (units in mm/year; left), and projected increase of sea level based in the future based on the average of current trends (units in mm; right).

Future Climate Change The study of climate change in the country has been performed in several studies (Barnett et al., 2003; Barnett et al., 2007; Katzfey et al., 2010; MoI, 2010). Barnett et al. (2003) summarized future climate projections in the country by using nine GCMs of the IPCC’s Third Assessment Report (TAR). The study projected that mean temperature in the country will increase around 0.3-1.2 0C by 2030 and around 0.8-3.6 0C by 2070. It is also expected that the wet season rainfall in November-April will slightly increase or decrease by 2030 (± 8%) and will increase to 20% by 2070. This is in contrast with the rainfall change in May-July (the second wet season for the southern part of Timor-Leste and the beginning of the dry season in the north) that shows a considerable decrease reaching 30% by 2030 and continuing to decrease to 80% by 2070. Similar rainfall changes are expected to occur during August-October.

Another climate change study was conducted by Katzfey et al. (2010). Although this study was specifically intended for Indonesia, some of the results can be used to show climate changes in Timor-Leste. The study was based on dynamical downscaling using CSIRO CCAM with the output of six GCMs. The simulations were performed with 60 km x 60 km grid resolution for selected periods between 1971 -2000 for baseline periods, and two periods for future projections under the SRES A2 scenario, i.e. 2041-2060 and 2081-2100. The study projected that the maximum and minimum temperature will increase from 1 to 2°C and 1 to 1.5°C in 2081-2100 respective to the 1971-2000 baseline. The annual rainfall is expected to decrease around 0.1 to 1 mm/day, with the most considerable decrease projected for March-April-May (MAM). In addition, MoI (2010) recently conducted another climate change study for the country. This study utilized 17 GCMs outputs divided into three future periods in 2020, 2050 and 2080 with relative baseline periods in 1961- 1990. The result of analysis suggests that the mean temperature is expected to increase by around 0.8°C by 2020, 1.5°C by 2050 and 2.2°C by 2080. Meanwhile, rainfall is projected to change with a 2% increase in the average by 2020, 4% by 2050 and 6% by 2080.

Projections of IPCC AR4 CMIP3 Models with SRES Scenarios

Temperature The changes in temperature in the future were assessed for Timor-Leste based on the output of Regional Climate Model 3 (RegCM3) by comparing the mean temperature difference in the future (2041- 60 and 2061-80 periods) based on their departure from the current baseline (1981-2000 period). The projection is based on the SRES A1B scenario. It was clearly shown that mean temperatures are expected to increase in the future. This is consistent with future projections of

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I mean temperatures for other countries as indicated in many studies. The mean temperatures during the 2041-60 and 2061- 2080 periods are expected to increase from the current temperature between 1.5°C and 1.8°C and between 2.1°C and 2.7°C respectively.

Rainfall In the future, the rainfall in Timor-Leste is expected to change. Figure 2-17 demonstrates the change of seasonal rainfall in the future respective to the 20th century baseline for the country. The analyses performed in these figures are based on the output of RegCM3 simulations under the SRES A1B scenario. The seasonal rainfall climatology in Timor-Leste is expected to increase in some or all parts of the country especially from wet to dry seasons (DJF, MAM and JJA). The most considerable increase is expected to occur in JJA during the 2041-60 period. During the transition period, the seasonal rainfall climatology in SON is predicted to be drier than the historical baseline, especially in the 2061-80 period. In general, the seasonal rainfall climatology in the region will be much wetter during 2041-60 than 2061-80 periods.

In addition to the analysis of seasonal rainfall projections from RegCM3, the INC compared the patterns of seasonal rainfall differences simulated by RegCM3 with the map of proportion stating the agreement of GCMs in projecting the change of seasonal rainfall in the future. This analysis only compares the projection results under SRES A1B scenario (Figure 2-18) since only the RegCM3 model is simulated under this scenario. The seasonal rainfall difference is stated as a percentage (%) and is calculated by subtracting the seasonal climatology of future rainfall projection from the current baseline, and by dividing the result with the baseline in order to define the change in percentage. The proportion maps of GCMs are calculated by identifying the ratio of GCMs that have similar agreements in projecting the change of seasonal rainfall climatology in the future. The range of proportion values is from 0 to 1. The higher (lower) the value indicates that more (less) GCMs agree with the increase of seasonal rainfall climatology in the future. If the value is in the middle of the range (0.5), it indicates that half of the models agree with the increase of seasonal rainfall, while the other half of the models agree with the decrease. This may also indicate that there might be no change of seasonal rainfall in the future.

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Figure 2-17: Seasonal rainfall differences in Timor-Leste based on the output of RCM projected for 2050 (mean value of 2041-2060 periods) and 2070 (mean value of 2061-2080 periods) relative to the 1981-2000 baseline (in %). Source, INC)

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Figure 2-18: Seasonal rainfall differences in Timor-Leste based on GCM ensembles under the SRES A1B scenario projected for 2050 (mean value of 2041-2060 periods) and 2070 (mean value of 2061- 2080 periods) relative to the 1981-2000 baseline (in %)

The GCMs proportion in projecting the rainfall change in Timor-Leste seems to be inconsistent with the patterns of seasonal rainfall differences projected by RegCM3. The ensemble model only shows similar agreement with the RegCM3 patterns during MAM in 2041-60 and SON in both 2041-60 and 2061-80 periods. The GCM ensemble projections under different scenarios, i.e. SRES A2 and B1, can be seen in Figure 2-19 and 2-20, respectively.

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Figure 2-19: Seasonal rainfall differences in Timor-Leste based on GCM ensembles under the SRES A2 scenario projected for 2050 (mean value of 2041-2060 periods) and 2070 (mean value of 2061- 2080 periods) relative to the 1981-2000 baseline (%).

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Figure 2-20: Seasonal rainfall differences in Timor-Leste based on GCM ensembles under SRES B1 scenario projected for 2050 (mean value of 2041-2060 periods) and 2070 (mean value of 2061- 2080 periods) relative to the 1981-2000 baseline (%).

Sea Level Rise Previously, the future SLR projection was calculated by using the trend of observed historical altimetry data. In this subsection, the resultant trend from multi-mission satellite data is combined with the future projections of six GCMs data and their ensemble (2010-2100 period) under the SRES A1B scenario. On average, the sea level surrounding Timor-Leste is expected to increase around 0.76 meters by 2100.

Projections of IPCC AR5 CMIP5 Models with RCP Scenarios

Temperature The area averaged monthly mean temperature anomalies calculated from the multi-model ensemble of CMIP5 GCMs with four RCP scenarios as well as from CMIP3 GCMs with the SRES A1B scenario are shown in Figure 2-21. From these projections, it is found that there are no significant differences in the range of the trends prior to year 2035. The mean increase of temperature for Timor-Leste to 2035 is expected not to exceed 1 °C. The projection shows that the difference in the increase of mean temperature trends across different scenarios will be more considerable after the year 2035. The increase in the temperature anomalies will range from 0.5°C to around 3.5°C by 2100 based on the lowest range scenario (RCP2.6) into the highest range scenario (RCP8.5), respectively. For the SRES A1B scenario, the increase of mean temperature

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I will be around 2°C by 2100 from the current baseline. This value is in between of RCP6.0 and RCP8.5.

Figure 2-21: Projections of monthly mean temperature anomalies in Timor-Leste based on the multi-model ensemble mean under four RCP scenarios and SRES A1B scenario.

Rainfall Changes of Rainfall Types The spatial patterns of rainfall in Timor-Leste are expected to change in the future. This is shown by the changes in the total area of each rainfall type as shown in Figure 2-22 and Figure 2-23. Consistent decreases are found at all periods in the RCP2.6 scenario for total rainfall area in Type 1, 2 and 4, with the decrease reaching 10% of the current total area. Similar consistent decreases for the same rainfall types are also found in the RCP6.0 scenario but only during the 2041- 2070 and 2071-2100 periods with the decreases less than 8%. The decreases of total area having Type 1, 2 and 4 rainfall regions contribute to the increase of total area having Type 3 and 5 rainfall regions. In the RCP4.5 scenario, the changes of total rainfall area across different rainfall types are varied at different periods. The highest increase is found in the Type 1 rainfall region during the period 2011- 2040, reaching a more than 20% increase. Such an increase contributes to the decrease of areas having Type 2, 3 and 5 rainfall.

Changes of Monthly and Seasonal Rainfall Climatology Timor-Leste is projected to experience some changes in monthly and seasonal rainfall climatology in the future, as has already happened in the past. Unlike the change of monthly rainfall climatology in the past where the changes were mostly found in the wet season, the future projections indicate that the change of rainfall will be expected to occur in the dry season and the transition of the season, especially from July to October in the 2011-2040 and 2071-2100 periods. The rainfall increases during those months may reach more than 10% of the current rainfall baseline. In 2041- 2070, more rainfall is expected during transition periods in March, April and May, as well as in September. Meanwhile, rainfall is projected to decrease in June and July during that period. Based on the consensus of 20 CMIP5 GCMs, it can be seen that in 2011-2040 and 2041-2070 under RCP2.6 scenario, the models agree that the wet season rainfall in the DJF season is expected to decrease compared to the current baseline. Within the same scenario, the models agree that there will be an increase in MAM rainfall, especially during the 2041-2070 and 2071-2100 periods. For the JJA and SON periods, there is only around 0.5% probability that rainfall will increase in all periods, except for the SON rainfall in 2041-2070 where most models agree that the season will experience a rainfall decrease (Figure 2-23).

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Figure 2-22: Changes in the spatial patterns of rainfall types in Timor-Leste based on the 20 GCMs multi- model ensemble projection under four RCP scenarios at three different future periods, i.e. in 2011-2040, 2041- 2070 and 2071-2100.

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Figure 2-23: Projected changes of total area at different rainfall types

Under the RCP4.5 scenario, different projections’ results on future rainfall show that dry season rainfall is expected to increase in the future, especially during the 2011-2040 and 2041-2070 periods. Most models agree that the season will experience a rainfall decrease over some areas in the country. Especially for this season and time periods, most models under the RCP6.0 scenario project an increase of rainfall. Under the highest range scenario (RCP8.5), the models mainly show a nearly fifty-fifty change of agreement, indicating a very low consensus in projecting future seasonal rainfall in Timor-Leste. This is similarly found in other RCP scenarios. The only clear agreement of the model is the consensus in projecting an increase of future rainfall in Timor-Leste under the RCP8.5 for the MAM season during the 2011-2040 and 2041-2070 periods.

Changes of the Dry and Wet Season Onsets

Based on the projections of the future onset of the dry and wet season using statistical downscaling methods, Timor-Leste is projected to experience some changes to the average timing of the seasonal onset in the future. Most of the timing of the dry season onset in the country will be shifted. In the current period, most of the regions in Timor-Leste experience the dry season onset in early April with variability of around 19 days. In the future, some of the country will have delays until mid- April with an average variability that could reach around 28 days of advance and delays of the onset due to climate factors driving rainfall variability. The changes of the timing of dry season onsets will vary, depending on future periods and scenarios. Unlike the changes of the means and variability of the dry season onset, the changes to the wet season onsets in Timor-Leste are expected to be consistent across different periods and scenarios. The projections show that the wet season onsets will shift from early to end of November in most of the regions, with some regions shifting to mid November. Although there is a consistent shift especially from early November (Region 1) to end of November (Region 4), the variability of future timing of the wet season onsets will be smaller as indicated by smaller standard deviations from 14 to only 4 days. The changes in the characteristics

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I of the dry and wet season onsets will slightly influence several important sectors in the country, especially the agriculture and water resource sectors.

2.8.2 Climate Change Impacts Most climate-induced disasters in Timor-Leste are localised and periodic, with resultant serious impacts upon local communities. Major hazards include flash floods, droughts, landslides and destructive winds. 76% of the of the population have been personally affected by these disasters. The communities living in areas with difficult road accessibility and low capacity to respond to disasters are generally the worse affected. Most of the rural population is dependent on agriculture for their livelihood. In Timor-Leste, agriculture employs 64% of the labour force and contributes 26.5% of the GDP. With this high level of dependence on agriculture, even low intensity disasters will add significantly to their vulnerability and increased food insecurity.

2.8.3 Impact on Water Resources Climate change could result in a drier dry season, wet season’s characterised by fewer but more intense events, and El Niño events, which result in delayed rain and less rain, may become more severe. These changes may exacerbate existing problems with drought, floods, and water quality. A drier dry season would increase vulnerability to drought because of high year-to-year rainfall variability combined with minimal water resource infrastructure. Lack of water in the dry season is already common, particularly on the northern side of the island, affecting agricultural production. Drought in 2001 to 2002, and the late arrival of the wet season in 2002 to 2003 resulted in an estimated 34% decline in maize production between 2002 and 2003 (22). As a result, 110 000 people were identified as needing food aid, particularly in the drier maize producing districts of Aileu, Ainaro, Ermera, and Liquica. East Timor is also prone to flooding, especially on the southern side of the country. Cova Lima, Manufahi, and Viqueque each receive more rainfall than northern districts, and experience two wet seasons each year. Intense rainfall events often cause flooding in these places. For example, unseasonal rains in June 2003 resulted in intense flooding and associated landslides in Manufahi and Cova Lima, which affected 778 families and caused damage to 74 houses and 610 ha of rice paddy. The severity of these flooding events is most probably exacerbated by upland farming practices that causes soil erosion, and the damage caused by landslides downstream is also a function of deforestation. Water Resources infrastructure such as water storage, water supply and flood defence infrastructure are lacking in rural areas and climate change will increase vulnerability of existing infrastructure and the requirement of additional and more resilient infrastructure.

2.8.4 Impact on Soil Erosion Clearing of vegetation occurs as part of maize production in highland areas, but is also a legacy of the use of defoliants during Indonesia’s war against the Timorese in the late 1970s, harvesting of forest resources during the period of Indonesian occupation, and changes in energy availability since the Indonesian withdrawal in 1999 and the subsequent removal of the subsidy on kerosene that existed under Indonesian rule, resulting in firewood becoming a cheaper source of fuel and a viable means to earn cash income for rural communities. In addition to these anthropogenic factors, climate change may exacerbate soil erosion.

2.8.5 Impact on Agriculture Widespread use of slash and burn agriculture coupled with poor agricultural and catchment management practices has led to deforestation and soil erosion, which have resulted in increased intensity of runoff from the country’s mostly steep terrain, causing significant soil erosion, increased incidence of landslides and flash flooding and low soil fertility for crop production. These vulnerabilities will be exacerbated under climate change due to the changes in the intensity, frequency and seasonality of rainfall and temperature described above. Potential areas for the establishment of new agricultural areas (expansion) will become more limited. Increasing cropping

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I intensity will be more difficult without supporting irrigation water. In some areas of the north coast of Timor-Leste, even planting crops once a year is not possible. Changes in climate would result in a reduction of maize yield between 5% and 20% from the current yield depending on climate scenarios. Crop failures due to extreme climate events may also increase. Agriculture is the most important socioeconomic sector in East Timor, accounting for approximately 75% of employment. Given the heavy reliance on subsistence agriculture to survive, the population is therefore vulnerable to shocks such as floods and droughts which lead to crop failures. Dependence on the agricultural sector means that climate change impacts can be far-reaching given that the capacity to adapt is low. Overall, a potential loss equivalent to 6.7% of combined gross domestic product (GDP) per year by mid-century due to climate change impacts, is expected.

Maize is the most abundant and accessible crop, making it the most important source of food supply in East Timor and is grown in shallow soils on steep slopes using shifting cultivation practices involving burning existing vegetation and planting seeds in the ashes. It is estimated that up to 20% of the country is burned each year for maize production. Limited land in mountainous areas, means that fallow periods are short, resulting in declining yields which are further exacerbated by soil erosion and nutrient depletion, both of which will increase with climate change. Most agriculture, including maize is unirrigated, making it vulnerable to drought and irregular rainfall.

Rice is the second most important food crop in East Timor in terms of volume produced and a key indicator of food security, with areas producing at least one rice crop per year being more food secure that those that cannot. Two crops are produced mainly in the southern part of the island where there are two rainfall peaks in the wet season, while in the north only 1 peak is possible to less rice is produced. In general, the second crop only accounts for 10% of total production, with the bulk of production coming from single crops irrigated by rain-fed flooding. However, economic loss and physical damage to rice is mainly from flooding in extremely wet years.

Irrigation is a critical input for rice production. Of 498 sucos, 286 have irrigation of some kind, and these roughly correspond to the areas that produce at least one rice crop per year (30). However, most of these systems operate in the wet season only, there being insufficient water in the dry season and no significant water storage systems for year-round irrigation of crops. Approximately 10 000 ha of irrigation rice systems are still damaged and require rehabilitation. The areas that produce a single crop each year, and which account for the bulk of rice production, may be sensitive to climate change, particularly if rainfall in the wet season decreases. All rice crops in flood prone areas may experience reduced production in the future because of increased flood events, while increased temperature may result in increased evaporation of water from paddies.

Coffee is the most important cash crop in East Timor, accounting for approximately 90% of foreign exchange. Some 25 000 families derive a significant proportion of their income from coffee production, and a further 15 000 families derive a small portion of income from it. However, the real price of coffee declining due to overproduction, commodity dependence, and increasing concentration of power in the hands of a few agribusinesses in the supply chain, thus shifting income from producers to traders. Coffee requires an average annual rainfall of some 2000– 3000 mm y1 and relative humidity of 70%–90% (3). It also requires a distinct dry season for flowering and ripening of berries (3). For these reasons, coffee is grown in the northern and southern highlands, and is a major crop for most sucos in Aileu, Ainaro, Ermera, Liquica, and Manufahi. Rising temperatures and increased rainfall may alter humidity at lower altitudes where coffee is grown and shift the altitude band favorable for coffee production upward. Increased rainfall in the dry season may also have an adverse effect on flowering and ripening of berries.

In summary, climate change has direct and indirect effects on crop production and the socioeconomic circumstances of Timor-Leste.

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2.8.6 Impact on coast A sea level rise of 76 cm may result in increased shoreline erosion, saltwater intrusion into freshwater aquifers, salinization of drinking and agricultural water. Coastal flooding and coastal erosion may increase impacting infrastructure such as buildings and roads, agricultural activity and may increase shoreline retreat. Parts of the main road from Dili to Com via Baucau run close to the water’s edge. The main port at Dili would be at increased risk as well as the new port and oil industry infrastructure at Suai. In some places, such as Oecussi, neap tides can cause inundation of settled and farmed areas with seawater, which suggests that such places are vulnerable to rising sea levels.

2.8.7 Impact on infrastructure The impact of climate-induced hydrometeorological hazards on Timor Leste, based on existing national-scale hazard maps and detailed socio-economic data on hazard receptors - people, property, agriculture and infrastructure (roads and bridges and water supply) - has been undertaken.

The assessment is based on the % of the overall risk nationally, that each municipality accounts for, for each receptor (dwellings, rural roads, main roads, water sources, and agriculture). It also looks at the risk with and without coping capacity taken into consideration and is done for baseline and climate change (CC) scenarios.

The impact of all hazards has been shown to increase under climate change and, the severity of impact is dependent on the ability of communities to cope with hazards under climate change. The following tables show the likely increase in % of each municipality at the highest risk from the main hazards, under baseline and climate change scenarios, without consideration of the capacity of communities to cope and an index of the severity of the impact, when coping capacity is taken into account. The analysis shows that the increase in the areas affected as well as the number and length of key infrastructure affected, increases for all municipalities and for all hazards. In most cases, at least doubling in percentage terms.

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Table 2-1: Impact of Landslides on receptors

Impact of Landslide Hazard Agriculture Water Supply Sources Houses Main Roads Rural Roads Municipality Coping Index Baseline CC CCCC Index Baseline CC CCCC Index Baseline CC CCCC Index Baseline CC CCCC Index Baseline CC CCCC Index Aileu 3 18.14% 87% 2.07 0.00% 75.00% 2.25 35.14% 89.03% 1.62 55.23% 97.87% 1.28 32.80% 88.12% 1.66 Ainaro 2 48.44% 80% 0.63 0.00% 60.00% 1.20 51.71% 79.63% 0.56 59.17% 74.24% 0.30 38.27% 71.83% 0.67 Baucau 3 4.23% 29% 0.73 0.00% 25.00% 0.75 5.47% 26.57% 0.63 9.63% 26.62% 0.51 6.99% 38.15% 0.93 Bobonaro 1 19.19% 34% 0.15 23.08% 51.28% 0.28 33.69% 63.79% 0.30 34.24% 61.04% 0.27 41.84% 69.65% 0.28 Covalima 2 0.57% 3% 0.06 0.00% 18.52% 0.37 4.97% 22.77% 0.36 12.08% 46.03% 0.68 7.44% 34.15% 0.53 Dili 2 0.30% 15% 0.29 0.00% 29.41% 0.59 2.28% 19.33% 0.34 18.35% 51.37% 0.66 10.99% 60.99% 1.00 Ermera 3 57.52% 80% 0.67 57.14% 71.43% 0.43 65.49% 86.63% 0.63 54.83% 65.83% 0.33 64.57% 89.24% 0.74 Lautem 2 0.93% 12% 0.23 0.00% 6.67% 0.13 1.37% 14.57% 0.26 1.97% 20.60% 0.37 0.10% 13.62% 0.27 Liquica 1 2.09% 8% 0.06 33.33% 50.00% 0.17 37.44% 77.12% 0.40 42.72% 58.89% 0.16 31.37% 78.74% 0.47 Manatuto 1 0.89% 7% 0.07 3.85% 3.85% 0.00 9.80% 37.68% 0.28 15.15% 50.48% 0.35 6.84% 47.93% 0.41 Manufahi 1 4.11% 26% 0.22 0.00% 6.67% 0.07 13.45% 52.64% 0.39 16.99% 31.91% 0.15 12.50% 46.82% 0.34 Viqueque 2 2.96% 20% 0.33 0.00% 12.50% 0.25 6.25% 32.43% 0.52 9.21% 27.80% 0.37 11.96% 48.89% 0.74 Grand Total 13.28% 33.43% 9.78% 34.19% 22.25% 50.18% 27.46% 51.06% 22.14% 57.34%

Table 2-2: Impact of Floods on receptors

Impact of Flood Hazard Agriculture Water Supply Sources Houses Main Roads Rural Roads Municipality Coping Index Baseline CC CCCC Index Baseline CC CCCC Index Baseline CC CCCC Index Baseline CC CCCC Index Baseline CC CCCC Index Aileu 3 43.27% 64.17% 0.63 0.00% 0.00% 0.00 15.47% 39.50% 0.72 18.52% 35.97% 0.52 22.98% 52.28% 0.88 Ainaro 2 15.24% 37.46% 0.44 0.00% 0.00% 0.00 8.02% 24.54% 0.33 16.79% 36.75% 0.40 16.21% 35.74% 0.39 Baucau 3 23.40% 47.13% 0.71 21.08% 21.08% 0.00 11.21% 31.41% 0.61 23.09% 48.91% 0.77 13.83% 37.54% 0.71 Bobonaro 1 32.26% 58.26% 0.26 6.16% 8.18% 0.02 20.87% 43.44% 0.23 23.32% 47.01% 0.24 25.21% 49.36% 0.24 Covalima 2 37.49% 63.20% 0.51 13.49% 13.49% 0.00 22.53% 49.67% 0.54 27.24% 49.22% 0.44 29.12% 54.86% 0.51 Dili 2 35.63% 62.76% 0.54 0.00% 0.00% 0.00 30.10% 56.16% 0.52 27.50% 57.48% 0.60 27.76% 56.59% 0.58 Ermera 3 25.82% 46.26% 0.61 0.00% 0.00% 0.00 14.31% 37.67% 0.70 19.26% 39.45% 0.61 19.84% 42.33% 0.67 Lautem 2 25.44% 50.67% 0.50 24.99% 46.94% 0.44 16.75% 42.70% 0.52 24.29% 50.57% 0.53 20.19% 47.19% 0.54 Liquica 1 43.91% 68.50% 0.25 6.87% 19.60% 0.13 23.39% 55.56% 0.32 23.13% 53.72% 0.31 29.23% 56.17% 0.27 Manatuto 1 40.02% 64.73% 0.25 0.00% 8.61% 0.09 21.11% 43.33% 0.22 28.39% 52.19% 0.24 30.71% 57.03% 0.26 Manufahi 1 34.22% 59.70% 0.25 0.00% 36.20% 0.36 22.89% 49.29% 0.26 25.06% 49.91% 0.25 30.28% 57.13% 0.27 Viqueque 2 29.35% 54.91% 0.51 0.00% 0.00% 0.00 30.90% 54.11% 0.46 24.52% 51.21% 0.53 20.51% 44.16% 0.47 Grand Total 32.17% 56.48% 6.05% 12.84% 19.80% 43.95% 23.43% 47.70% 23.82% 49.20%

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Table 2-3: Impact of Erosion on receptors

Impact of Erosion Hazard Agriculture Water Supply Sources Houses Municipality Coping Index Baseline CC CCCC Index Baseline CC CCCC Index Baseline CC CCCC Index Aileu 3 61.49% 98.72% 1.12 46.31% 100.00% 1.61 42.20% 96.48% 1.63 Ainaro 2 57.03% 94.68% 0.75 17.25% 75.21% 1.16 45.17% 90.07% 1.35 Baucau 3 10.84% 73.56% 1.88 0.00% 78.92% 2.37 9.97% 52.42% 1.27 Bobonaro 1 11.99% 88.09% 0.76 0.00% 74.79% 0.75 14.01% 74.69% 1.82 Covalima 2 0.38% 85.17% 1.70 5.49% 80.53% 1.50 13.94% 79.81% 1.98 Dili 2 1.87% 77.66% 1.52 0.00% 100.00% 2.00 3.95% 68.85% 1.95 Ermera 3 31.66% 85.10% 1.60 11.19% 90.84% 2.39 51.38% 92.93% 1.25 Lautem 2 26.31% 80.56% 1.09 8.56% 61.16% 1.05 10.67% 63.50% 1.58 Liquica 1 0.71% 87.66% 0.87 0.00% 81.77% 0.82 28.76% 91.19% 1.87 Manatuto 1 9.17% 60.64% 0.51 0.00% 69.94% 0.70 18.29% 77.77% 1.78 Manufahi 1 23.69% 88.07% 0.64 46.53% 68.81% 0.22 28.52% 87.54% 1.77 Viqueque 2 35.48% 90.08% 1.09 15.66% 27.81% 0.24 20.01% 75.93% 1.68 Grand Total 22.55% 84.17% 12.58% 75.82% 23.91% 79.26%

Table 2-4: Impact of Droughts on receptors

Impact of Drought - Dry season Agriculture Water Supply Sources Houses Municipality Coping Index Baseline CC CCCC Index Baseline CC CCCC Index Baseline CC CCCC Index Aileu 3 100.00% 100.00% 0.00 100.00% 100.00% 0.00 94.97% 100.00% 0.15 Ainaro 2 83.96% 100.00% 0.48 49.58% 100.00% 0.13 78.42% 100.00% 0.43 Baucau 3 0.00% 100.00% 3.00 0.00% 100.00% 1.00 0.00% 100.00% 3.00 Bobonaro 1 41.93% 100.00% 1.74 45.26% 100.00% 0.16 28.01% 100.00% 0.72 Covalima 2 0.00% 100.00% 3.00 0.00% 100.00% 1.00 0.34% 100.00% 1.99 Dili 2 0.00% 100.00% 3.00 0.00% 100.00% 1.00 0.08% 100.00% 2.00 Ermera 3 100.00% 100.00% 0.00 100.00% 100.00% 0.00 100.00% 100.00% 0.00 Lautem 2 0.00% 85.77% 2.57 0.00% 68.15% 0.32 0.00% 81.29% 1.63 Liquica 1 100.00% 100.00% 0.00 81.11% 100.00% 0.01 95.49% 100.00% 0.05 Manatuto 1 31.14% 100.00% 2.07 30.66% 100.00% 0.33 55.43% 100.00% 0.45 Manufahi 1 77.37% 100.00% 0.68 32.61% 100.00% 0.31 85.23% 100.00% 0.15 Viqueque 2 7.34% 100.00% 2.78 0.00% 100.00% 1.00 7.09% 100.00% 1.86 Grand Total 45.14% 98.81% 36.60% 97.35% 45.42% 98.44%

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

2.8.8 Exposure to climate-induced natural hazards Vulnerability to natural disasters and climate change is a function of exposure, sensitivity and adaptive capacity (IPCC, 2001; IPCC, 2012). Vulnerability reduction in the context of disaster risk reduction involves seeking opportunities to reduce exposure, reduce sensitivity and increase adaptive capacity. Exposure to climate change is, to a large extent, determined by geographical location. The most obvious way of reducing exposure to climate-related disasters is to avoid promoting settlements and economic development in identified high-risk areas and in some cases, to retreat from such areas through relocation of infrastructure and population resettlement. In practice, these options may be politically difficult to promote, especially the latter. Infrastructure- and ecosystem-based options are also available to reduce exposure.

More frequently, interventions in the field of disaster risk reduction and hazard management address vulnerability through enhancement of adaptive capacity, through a combination of activities which may include education and awareness raising, promotion and enabling of livelihoods that enhance climate change adaptation, access to essential services, access to information and technology (e.g. forecasting and early warning systems), infrastructure building, ecosystem and natural resource management, and institutional capacity building. The best approaches normally involve taking an integrated approach which encompasses all of these types of interventions.

Geographically, Timor-Leste is exposed to several kinds of natural hazards, which include frequent events such as tropical cyclone, riverine flooding, drought, and landslides as well as rarer events such as earthquakes and tsunamis. The most prominent and frequent hazard types in the country’s recent history include floods, landslides, and drought (prolonged dry spells). These events typically have negative impacts on domestic food production that can be affected by such hazards, which in turn impacts the population which is heavily reliant on subsistence farming. Additionally, natural hazards can cause substantial damage to the country’s fragile infrastructure and buildings which deteriorate over time by exposure to natural hazards (i.e. slow on-set hazards, coupled with poor maintenance) as well as injury and fatality to residents when natural hazards occur as disasters or high intensity events. Table 2-5 and Table 2-6 summarise the actual hazards that have been experienced in Timor-Leste and their impacts since 1992 as recorded in the Desinventar damage and losses database. It shows that flooding affects the most number of people and property with drought and landslide second. The table on damages is sparsely populated which is perhaps a reflection of lack of collected data on hazard impact rather than a lack of damages and losses.

The exposure of rural communities to climate-induced disasters within Timor-Leste’s is exacerbated by un-favourable socio-economic conditions, limited access to infrastructure and services and limited adaptive capacity and resilience to enable effective response to or recovery from such disasters, which further deepens their deprivation. Women are notably at risk because of their comparatively limited education, income and ability to influence decision-making.

The majority of disaster management activities in Timor-Leste are limited to ad hoc disaster response undertakings driven by immediate needs. The capacity to manage disaster preparedness is particularly weak, especially when it concerns understanding and addressing larger area-based challenges such as land use changes, watershed deterioration, destructive agricultural practices and deforestation.

The impacts of climate change are expected to exacerbate damage to rural infrastructure and increase economic losses incurred at the national and local community level. Adaptation to climate change will require improved routine maintenance, emergency repair, and rehabilitation of infrastructure, but perhaps more importantly, the building of climate resilient infrastructure to withstand climate-induced hazards.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Table 2-5:Reported hazard event and impacts based on data recorded in the Desinventar Damages and Losses Database

DROUGHT FLOOD LANDSLIDE RAINS STRONG WIND Houses Houses Houses Houses Houses Houses Houses Houses Houses Houses Municipality No Deaths Affected Damaged Destroye No Deaths Affected Damage Destroyed No Deaths Affected Damag Destroy No Deaths Affected Damaged Destroyed No Deaths Affected Damaged Destroyed AILEU 7 0 10 8 2 2 0 16 0 0 43 1 92 99 4 AINARO 8 0 906 310 5 5 0 36 0 0 41 0 1,575 1,419 38 BAUCAU 18 13 289 286 0 5 0 44 0 0 1 0 1 0 1 85 1 226 176 28 BOBONARO 6 5 27 28 8 1 0 10 0 0 1 15 0 45 127 39 1 159 88 63 COVALIMA 27 3 5,476 5,312 658 7 0 41 0 0 1 0 27 27 0 26 1 7 117 0 DILI 1 0 8,502 0 0 106 2 3,473 3,597 12 15 0 145 0 0 35 1 279 105 9 ERMERA 9 4 164 168 0 8 0 12 0 0 119 5 530 460 14 LAUTEM 27 15 709 336 36 3 6 2 6 6 2 6 141 216 145 78 1 396 321 141 LIQUICA 10 0 179 98 6 6 0 91 35 0 MANATUTO 14 2 1,553 486 0 9 0 103 0 0 12 0 19 22 1 MANUFAHI 26 0 3,597 2,150 21 2 0 4 0 0 92 0 521 522 3 OECUSSE 6 0 73 73 0 2 0 2 0 0 123 0 218 148 62 VIQUEQUE 23 0 603 603 49 1 0 0 0 0 71 0 427 408 20 Grand Total 1 0 8,502 0 0 287 44 17,059 13,455 797 60 6 415 6 6 5 21 169 288 273 770 11 4,540 3,920 383

Table 2-6: Damages based on data recorded in Desinnevtar Damages and Losses database

DROUGHT FLOOD LANDSLIDE RAINS STRONGLength WIND Length of Length of Length of of Length of Raods Damage Raods Raods Raods Damaged Raods Damages Damaged Damaged Damages d Land Damaged Damages Damaged Damaged Damaged Damag Damages District Land (ha) Damaged (m) ($) Land (ha) (m) ($) (ha) (m) ($) Land (ha) (m) Damages ($) Land (ha) ed (m) ($) AILEU - - - 0 0 - 0 ------0 AINARO - - - 0 0 - 0 ------0 BAUCAU - - - 0 0 - 0 - - 0 - - - - 0 BOBONARO - - - 0 0 - 0 ------2,000 COVALIMA - - - 32 0 - 40 - - 17 - - - - 0 DILI - - - 0 0 - 0 ------0 ERMERA - - - 0 0 - 0 ------0 LAUTEM - - - 27 25 - 0 - - 0 - - - - 0 LIQUICA - - - 0 0 ------0 MANATUTO - - - 0 0 - 0 ------0 MANUFAHI - - - 0 0 - 0 ------0 OECUSSE - - - 0 0 - 0 ------0 VIQUEQUE - - - 180 0 - 0 ------0 Grand Total - - - 239 25 - 40 - - 17 - - - - 2,000

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

2.8.9 Exposure to High/Very High Hydro-meteorological hazards The exposure to climate-induced hydrometeorological hazards in Timor Leste has been assessed, based on existing national-scale hazard maps and detailed socio-economic data on hazard receptors - people, property, agriculture and infrastructure (roads and bridges and water supply).13

Dwelling Units subject to high/very high hazards Based on the analysis of existing hazard maps, it would appear that drought risk has the biggest impact on dwellings in 6 of the 12 municipalities, with exposure to erosion and landslide risk showing equal significance, while strong winds and floods appear less significant. Hence, drought is widespread in Aielu, Ainaro, Ermera and Liquica but negligible in Baucau, Covalima, Dili and Lautem. Ainaro is significantly exposed to landslide and strong wind. It should be noted, however, that the flood hazard maps used were for flooding to only 6 catchments. Hence the data is skewed as demonstrated by the fact that the most commonly recorded hazard is flooding (Table 2-5 above).

Table 2-7: Exposure of Dwellings to all high/very high hydro-meteorological hazards

13 Note: Irrigation infrastructure data was not available so it is not included in the analysis.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Figure 2-24: Exposure of Dwellings to all high/very high hydro-meteorological hazards Rural Roads subject to High/very high flood and landslide hazard

% All rural roads (km) subject to High or Very High Floods and Landslides

Municipality Flood Landslide Aileu 22.98% 32.80% % km of All Rural Roads subject to High or Very High Flood Ainaro 16.21% 40.66% and landslide Hazard Baucau 13.83% 6.99% Bobonaro 25.21% 46.26% Covalima 29.12% 7.44% Dili 27.76% 10.99% 80.00% Ermera 19.84% 72.79% 60.00% Lautem 20.19% 0.10% Liquica 29.23% 32.14% 40.00% Manatuto 30.71% 6.84% 20.00% Manufahi 30.28% 12.50% 0.00% Flood Viqueque 20.51% 11.96%

Flood Landslide

Figure 2-25: Exposure of rural roads to high/very high intensity floods and landslides

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Almost three quarters of All rural roads are exposed to High/Very high Landslide hazard in Ermera with Ainaro, Bobonaro and Ainaro significantly exposed. Between approximately 20 to 30% of all rural roads are exposed to high/very high flood hazard.

Main Roads subject to High/very high Flood and landslide hazard

% Main roads (km) subject to High or Very High Floods and Landslides

Municipality Flood Landslide Aileu 18.5% 55.2% % Km of Main Roads subject to High/Very High Flood Ainaro 16.8% 64.1% and Landslide hazard Baucau 23.1% 9.6% Bobonaro 23.3% 37.3% Covalima 27.2% 12.1% Dili 27.5% 18.4% 100.0% Ermera 19.3% 87.3% 80.0% 60.0% Lautem 24.3% 2.0% 40.0% Liquica 23.1% 43.2% 20.0% Manatuto 28.4% 15.2% 0.0% Flood Manufahi 25.1% 17.0% Viqueque 24.5% 9.4%

Flood Landslide

Figure 2-26: Exposure of main roads to high/very high intensity floods and landslides

The majority of Main roads in Aileu, Ainaro and Ermera are subject to very high/high landslide hazard with between approximately one fifth to one quarter of all main roads subject to high/very high flood hazard.

Water Sources subject to High/very high hydro-meteorological hazard

% Water Sources (number) subject to High or Very High Hazards % Water Sources (beneficiaries) subject to High or Very High Hazards

Municipality Flood Drought Erosion Landslide Municipality Flood Drought Erosion Landslide Aileu 0.0% 100.0% 25.0% 0.0% Aileu 0.0% 100.0% 46.3% 0.0% Ainaro 0.0% 40.0% 20.0% 0.0% Ainaro 0.0% 49.6% 17.2% 0.0% Baucau 25.0% 0.0% 0.0% 0.0% Baucau 21.1% 0.0% 0.0% 0.0% Bobonaro 7.7% 25.6% 0.0% 25.6% Bobonaro 6.2% 45.3% 0.0% 25.2% Covalima 18.5% 0.0% 7.4% 0.0% Covalima 13.5% 0.0% 5.5% 0.0% Dili 5.9% 0.0% 0.0% 0.0% Dili 0.0% 0.0% 0.0% 0.0% Ermera 0.0% 100.0% 42.9% 71.4% Ermera 0.0% 100.0% 11.2% 100.0% Lautem 17.8% 0.0% 4.4% 0.0% Lautem 25.0% 0.0% 8.6% 0.0% Liquica 16.7% 66.7% 0.0% 33.3% Liquica 6.9% 81.1% 0.0% 31.0% Manatuto 7.7% 34.6% 3.8% 3.8% Manatuto 0.0% 30.7% 0.0% 17.8% Manufahi 6.7% 80.0% 40.0% 0.0% Manufahi 0.0% 32.6% 46.5% 0.0% Viqueque 12.5% 12.5% 25.0% 0.0% Viqueque 0.0% 0.0% 15.7% 0.0% Figure 2-27: Exposure of water sources to high/very high hydro-meteorological hazards

All or most water sources and all or most of their beneficiaries in Ermera are subject to high or very high drought and landslide hazard. All Aileu’s sources and beneficiaries are subject to high/very high drought. Some 80% of Manufahi’s water sources are subject to high or very high drought hazard.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

All Crops subject to high/very high meteorological hazard % All Crops (Hectares) subject to High or Very High Hazards

Municipality Flood Landslide Strong Wind Aileu 43.3% 18.1% 15.74% % Ha of Crop Production subject to High/Very Ainaro 15.2% 49.2% 81.33% High Hazard Baucau 23.4% 4.2% 4.81% Bobonaro 32.3% 23.7% 17.66% Covalima 37.5% 0.6% 5.25% 100.0% Dili 35.6% 0.3% 0.80% Ermera 25.8% 72.9% 50.07% 50.0% Lautem 25.4% 0.9% 7.96% 0.0% Flood Liquica 43.9% 2.1% 0.00% Manatuto 40.0% 0.9% 0.00% Manufahi 34.2% 4.1% 1.49% Viqueque 29.3% 3.0% 0.00% Flood Landslide Strong Wind

Figure 2-28: Exposure of all crops to high/very high hydro-meteorological; hazards

Up to a third of all Municipalities are subject to high/very high flood hazard with over 50% of Ermera crops exposed to high/very high landslide and strong wind hazard. Almost 50% of crops in Ainaro are subject to high/very high landslide hazard with strong wind high/very high hazard affecting over 80% of Ainaro crops.

2.9 Socio-economic risk assessment

This section presents the outcomes of an assessment of the risks posed by each hazard on receptors, where risk is comprised of two components – Likelihood or probability of occurrence and impact or consequence of the occurrence. The risk assessment is based on the % of the overall risk nationally, that each municipality accounts for, for each receptor (dwellings, rural roads, main roads, water sources, and agriculture). It also looks at the risk with and without coping capacity (CCS) taken into consideration and is done for baseline and climate change (CC) scenarios. Municipalities are also ranked from 1 to 13 in terms from highest risk municipality to lowest. The final analysis is based on the ‘riskiest’ municipalities which uses a combined risk score for all hazard for each receptor.

2.9.1 Flood Risk

Flood is one of the most common disasters in Timor-Leste, resulting from a combination of heavy monsoon rain, steep topography and widespread deforestation. There are three types of flooding in Timor-Leste namely: (1) flash flooding that occurs when high intensity seasonal rainfall occurs on steep slopes; (2) riverine flooding that occurs when water accumulates in lowland or upland flood plains and river banks have insufficient capacity to contain the flow resulting in an overflow of the river and (3) Urban or pluvial flooding when urban drainage system have insufficient capacity to accept high intensity rainfall which results in surface water flooding in paved areas (mainly in Dili and Baucau).

For the purposes of this feasibility study (and to overcome the fact that the existing national flood hazard map was done for only 6 catchments), an indicative national flood hazard map has been derived for the whole of Timor-Leste, based on Topographic Wetness Index which is a measure of the likelihood of an area being flooded, based on slope, flow direction and flood accumulation parameters derived for the grid cells within the catchment. It is indicative only and does not fully

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I represent flood hazard which would also be influenced by amount and type of precipitation, soil, geology and land use. However, it is a reasonable starting point in the absence of any more comprehensive flood hazard mapping14. Figure 2-29 is the resulting indicative flood hazard map. It should be noted that this indicative flood map does not assign return period (or probability) to flooding and only approximates fluvial flood risk.

Figure 2-29: Flood Hazard map

Flood Risk – Baseline and climate change assessment

Under climate change and with coping strategy taken into account flooding has greatest impact on houses in Dili, main roads, rural roads, cropland and rice plantations in Baucau and water sources in Lautem. It is important to note that when coping capacity is not considered flooding has the greatest impact on houses in Dili, rural and main roads in Lautem, cropland in Cova Lima and Rice plantations in Baucau.

14 Note: A UNDP study in 2012 derived flood (and other) hazard maps for 6 highest risk catchments (where flooding had been experienced in the past) which did not provide national coverage and therefore could not be used.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Flood Risk to Dwelling Units Flood Risk to Main roads Flood Risk to Cropland Total Risk Score Total Risk Score Municipality Baseline Rank Total Risk Score Total Risk Score Municipality Baseline Rank Total Risk Score Total Risk Score Municipality Baseline Rank Baseline CCS Wetness Ind CCS No CCS Baseline CCS No CCS Wetness Ind CCS No CCS Baseline Baseline No CCS (Area) CCS No CCS 17712 5% 1968 2% Aileu 7 12 46 0% 11 1% Aileu 12 12 6392 6% 710 2% Aileu 6 9 8703 2% 2901 3% Ainaro 8 11 557 4% 54 5% Ainaro 9 9 1736 2% 579 2% Ainaro 10 10 72783 19% 8087 7% Baucau 2 6 2236 14% 127 12% Baucau 2 2 28225 27% 3136 10% Baucau 1 4 8255 2% 8255 7% Bobonaro 9 5 1306 8% 98 9% Bobonaro 5 6 2869 3% 2869 10% Bobonaro 8 6 32958 9% 10986 10% Covalima 4 2 1574 10% 112 10% Covalima 4 4 22518 22% 7506 25% Covalima 2 1 106329 28% 35443 32% Dili 1 1 309 2% 54 5% Dili 11 10 223 0% 74 0% Dili 12 12 63090 16% 7010 6% Ermera 3 8 495 3% 50 5% Ermera 10 11 13553 13% 1506 5% Ermera 4 8 25551 7% 8517 8% Lautem 6 4 4231 27% 184 17% Lautem 1 1 8960 9% 2987 10% Lautem 5 5 7679 2% 7679 7% Liquica 10 7 779 5% 81 8% Liquica 7 7 480 0% 480 2% Liquica 11 11 4274 1% 4274 4% Manatuto 12 10 1288 8% 107 10% Manatuto 6 5 3346 3% 3346 11% Manatuto 7 3 6134 2% 6134 6% Manufahi 11 9 702 5% 75 7% Manufahi 8 8 1865 2% 1865 6% Manufahi 9 7 30420 8% 10140 9% Viqueque 5 3 1941 13% 125 12% Viqueque 3 3 14459 14% 4820 16% Viqueque 3 2 383888 100% 111394 100% 15464 100% 1080 100% 104626 100% 29877 100% Total Risk Score Total Risk Score Municipality Climate change Rank Total Risk Score Total Risk Score Municipality Climate Change Rank Total Risk Score Total Risk Score Municipality Climate Change Rank Climate Change CC/ No CCS Wetness Ind CCS No CCS Climate Change CC/ No CCS Wetness Ind CCS No CCS Climate Change CC/ No CCS (Area) CCS No CCS 38016 5% 4224 2% Aileu 7 12 206 3% 23 1% Aileu 8 12 11193 6% 1244 2% Aileu 6 10 20799 3% 6933 3% Ainaro 8 11 338 5% 113 5% Ainaro 6 9 3732 2% 1244 2% Ainaro 9 9 2244 31% 249 12% Baucau 1 2 165159 21% 18351 8% Baucau 2 4 54545 28% 6061 11% Baucau 1 3 192 3% 192 9% Bobonaro 10 6 16485 2% 16485 7% Bobonaro 9 6 5379 3% 5379 10% Bobonaro 8 6 631 9% 210 10% Covalima 5 4 65574 8% 21858 10% Covalima 4 2 40120 20% 13373 24% Covalima 2 1 196812 25% 65604 30% Dili 1 1 310 4% 103 5% Dili 7 10 406 0% 135 0% Dili 12 12 137430 17% 15270 7% Ermera 3 8 902 13% 100 5% Ermera 3 11 28232 14% 3137 6% Ermera 3 8 54198 7% 18066 8% Lautem 6 5 1078 15% 359 17% Lautem 2 1 16828 9% 5609 10% Lautem 5 5 15372 2% 15372 7% Liquica 10 7 163 2% 163 8% Liquica 11 7 833 0% 833 2% Liquica 11 11 8502 1% 8502 4% Manatuto 12 10 199 3% 199 9% Manatuto 9 5 5866 3% 5866 11% Manatuto 7 4 12132 2% 12132 5% Manufahi 11 9 145 2% 145 7% Manufahi 12 8 3446 2% 3446 6% Manufahi 10 7 55440 7% 18480 8% Viqueque 5 3 733 10% 244 12% Viqueque 4 3 26214 13% 8738 16% Viqueque 4 2 785919 100% 221277 100% 7142 100% 2102 100% 196794 100% 55066 100% Flood Risk Rural Roads Flood Risk to Water Sources Flood Risk - Rice Total Risk Score Total Risk Score Municipality Baseline Rank Total Risk Score Total Risk Score Municipality Baseline Rank Total Risk Score Total Risk Score Municipality Baseline Rank Baseline CCS CC/ No CCS Wetness Ind CCS No CCS Baseline CCS No CCS Wetness Ind CCS No CCS Baseline Baseline No CCS (Area) CCS No CCS 57 6% 6 3% Aileu 5 11 38214 1% 4246 2% Aileu 6 7 8967 5% 996 2% Aileu 5 8 36 4% 12 5% Ainaro 7 10 1518 0% 506 0% Ainaro 10 10 776 0% 259 1% Ainaro 12 12 319 35% 35 16% Baucau 1 1 28278 1% 9806 5% Baucau 7 4 105608 55% 11734 29% Baucau 1 1 23 3% 23 10% Bobonaro 8 4 171029 5% 7976 4% Bobonaro 3 5 5218 3% 5218 13% Bobonaro 6 3 67 7% 22 10% Covalima 4 5 699162 19% 34604 17% Covalima 2 2 1384 1% 461 1% Covalima 8 10 15 2% 5 2% Dili 10 12 942 0% 314 0% Dili 11 11 1132 1% 377 1% Dili 10 11 212 23% 24 11% Ermera 2 3 0 0% 0 0% Ermera 12 12 23057 12% 2562 6% Ermera 3 6 102 11% 34 15% Lautem 3 2 2589417 69% 124685 61% Lautem 1 1 11915 6% 3972 10% Lautem 4 4 13 1% 13 6% Liquica 12 9 88869 2% 13917 7% Liquica 5 3 859 0% 859 2% Liquica 11 9 14 2% 14 6% Manatuto 11 8 95321 3% 6287 3% Manatuto 4 6 2912 2% 2912 7% Manatuto 7 5 18 2% 18 8% Manufahi 9 6 21654 1% 2349 1% Manufahi 8 8 1374 1% 1374 3% Manufahi 9 7 45 5% 15 7% Viqueque 6 7 2145 0% 715 0% Viqueque 9 9 28630 15% 9543 24% Viqueque 2 2 922 100% 223 100% 3736549 100% 205405 100% Total Risk Score Total Risk Score Municipality Climate Change Rank 191831 100% 40267 100% Total Risk Score Total Risk Score Municipality Climate Change Rank Climate Change CC/ No CCS Wetness Ind CCS No CCS Total Risk Score Total Risk Score Municipality Climate Change Rank Climate Change CC/ No CCS Wetness Ind CCS No CCS 1043 7% 116 3% Aileu 5 11 Climate Change CC/ No CCS (Area) CCS No CCS 114642 10% 12738 3% Aileu 4 7 487 3% 162 4% Ainaro 7 10 15496 4% 1722 2% Aileu 5 8 4554 0% 1518 0% Ainaro 10 10 4349 30% 483 13% Baucau 1 2 1482 0% 494 1% Ainaro 11 12 136242 12% 15138 4% Baucau 3 5 410 3% 410 11% Bobonaro 8 4 204335 56% 22704 30% Baucau 1 1 14853 1% 14853 4% Bobonaro 7 6 1303 9% 434 11% Covalima 4 3 9374 3% 9374 12% Bobonaro 6 3 146061 13% 48687 13% Covalima 2 2 300 2% 100 3% Dili 10 12 2365 1% 788 1% Covalima 9 10 2826 0% 942 0% Dili 11 11 3235 22% 359 9% Ermera 2 6 2020 1% 673 1% Dili 10 11 0 0% 0 0% Ermera 12 12 1690 12% 563 15% Lautem 3 1 41771 12% 4641 6% Ermera 3 6 671175 58% 223725 60% Lautem 1 1 270 2% 270 7% Liquica 12 8 22917 6% 7639 10% Lautem 4 4 28881 3% 28881 8% Liquica 5 3 289 2% 289 8% Manatuto 11 7 1480 0% 1480 2% Liquica 12 9 18861 2% 18861 5% Manatuto 6 4 371 3% 371 10% Manufahi 9 5 5127 1% 5127 7% Manatuto 7 5 7047 1% 7047 2% Manufahi 8 8 716 5% 239 6% Viqueque 6 9 2410 1% 2410 3% Manufahi 8 7 6435 1% 2145 1% Viqueque 9 9 14463 100% 3798 100% 53848 15% 17949 24% Viqueque 2 2 1151577 100% 374535 100% 362624 100% 75002 100%

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Based on available hazard and risk mapping the economic damages incurred from each hazard has been assessed.

Flooding economic damages

To calculate economic damages from flooding, depth data is required which is not provided by the Topographic Wetness Index. However, the UNDP flood hazard maps which were done for the 6 highest risk catchments for flooding, includes depth information for different return periods. This data has been used to assess flood economic damages by municipality and my rural and urban sucos. Table 2-8 shows that the overall annual average damages for the municipalities which fall within the 6 UNDP prioritized sub-catchments is $ 2.046 Million and the highest damages, as would be expected, would be sustained in Dili, the capital, which would account for 57% of all damages. Manatuto has the second highest flood damages and accounts for a third of all flood damages.

Table 2-8: Annual Average Flood Damages for the municipalities within the 6 UNDP prioritized catchments

TOTAL AAD AILEU $ 11,562 1% AINARO £ 25,403 1% BAUCAU £ 10,910 1% BOBONARO $ 66,766 3% COVALIMA $ 14,219 1% DILI $ 1,165,531 57% ERMERA $ 23,425 1% LAUTEM $ 491 0% LIQUICA $ 54,164 3% MANATUTO $ 673,660 33% $ 2,046,131 100% 6 Catchments from UNDP 2012

In rural areas $7.9 Million in damages would be incurred for the 1 in 100 year flood and would affect 34 sucos in the 6 priority catchments (Table 2-9). In urban areas, the total damages for the 1 in 100 year event would be $13.16 Million. Almost twice, covering 7 sucos.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Table 2-9: Damages and Annul Average Damages for rural sucos with the 6 UNPD prioritized catchments

Flooding Rural Areas Annual Average % Rp10 Rp50 Rp100 Damage ($) contribution Suco No Amount No Amount No Amount Aculau 47 $ 101,237.03 47 $ 106,693.74 106 $ 163,563.66 $ 21,207 2.7% Ailili 11 $ 30,201.96 26 $ 69,564.38 44 $ 135,041.56 $ 13,173 1.7% Ainaro 2 $ 762.63 5 $ 2,391.70 $ 164 0.0% Aiteas 26 $ 65,541.53 26 $ 72,066.45 143 $ 411,492.71 $ 26,223 3.3% Atabae 1 $ 195.94 21 $ 19,063.85 44 $ 71,192.30 $ 4,573 0.6% Cassa 52 $ 14,558.73 225 $ 102,135.59 240 $ 189,975.93 $ 17,519 2.2% Comoro 159 $ 150,467.31 269 $ 391,604.27 325 $ 728,064.31 $ 71,890 9.2% Dare 16 $ 18,740.38 22 $ 30,805.62 27 $ 50,386.52 $ 5,725 0.7% Daudere 1 $ 62.39 $ 2.50 0.0% Fahilebo 1 $ 62.39 1 $ 195.94 1 $ 195.94 $ 29 0.0% Fatisi 27 $ 35,862.75 36 $ 68,758.69 41 $ 89,512.29 $ 11,562 1.5% Funar 1 $ 62.39 $ 2.50 0.0% Gugleur 22 $ 32,645.39 $ 1,306 0.2% Guiþo 28 $ 44,452.04 $ 1,778 0.2% Hataz 5 $ 10,801.17 5 $ 12,673.27 104 $ 289,242.04 $ 13,250 1.7% Iliheu 103 $ 324,038.80 233 $ 766,814.87 $ 59,836 7.6% Lacumesac 4 $ 3,849.24 4 $ 5,348.27 13 $ 14,997.49 $ 1,274 0.2% Leolima 31 $ 25,353.22 34 $ 45,010.28 33 $ 48,575.09 $ 7,262 0.9% Liho 3 $ 1,189.37 25 $ 17,505.97 18 $ 14,574.46 $ 2,218 0.3% Lissadila 3 $ 7,072.70 5 $ 10,122.47 50 $ 86,957.79 $ 4,743 0.6% Ma'abat 36 $ 77,718.40 95 $ 263,744.35 103 $ 358,791.40 $ 41,975 5.3% Purugua 49 $ 97,374.32 83 $ 191,924.38 252 $ 478,109.32 $ 41,266 5.3% Raimea 39 $ 59,852.68 49 $ 83,208.65 58 $ 93,445.23 $ 14,219 1.8% Rairobo 1 $ 195.94 3 $ 3,299.26 $ 142 0.0% Sau 436 $ 1,219,345.17 543 $ 1,593,812.26 812 $ 2,682,153.91 $ 311,697 39.7% Serelau 1 $ 2,490.34 1 $ 2,800.28 1 $ 2,800.28 $ 489 0.1% Suro-Craic 1 $ 669.03 2 $ 2,490.34 2 $ 4,999.56 $ 458 0.1% Tapo/Memo 1 $ 2,490.34 $ 100 0.0% Tibar 2 $ 3,586.82 2 $ 4,398.55 2 $ 5,801.26 $ 807 0.1% Uaigae 5 $ 12,677.93 13 $ 19,660.29 30 $ 34,382.64 $ 3,779 0.5% Ulmera 1 $ 866.23 1 $ 700.24 1 $ 2,720.60 $ 215 0.0% Uma Caduac 61 $ 59,432.71 131 $ 264,427.61 247 $ 669,995.59 $ 53,570 6.8% Vatuboro 116 $ 211,711.38 133 $ 245,660.32 157 $ 314,784.70 $ 45,286 5.8% Vemasse 14 $ 9,993.43 24 $ 20,383.30 72 $ 119,458.19 $ 7,112 0.9% Total $ 2,221,048 $ 3,969,561 $ 7,913,433 $ 784,850 100.0%

Table 2-10: Damages and Annul Average Damages for urban sucos with the 6 UNPD prioritized catchments

Flooding Urban Areas Annual Average % Rp10 Rp50 Rp100 Damage ($) contribution Suco No Amount No Amount No Amount Ailili 1 $ 866.23 1 $ 1,219.88 1 $ 1,219.88 $ 202 0.0% Comoro 1,262 $ 2,476,018.08 2,160 $ 5,608,705.92 2,997 $ 11,482,610.30 $ 1,087,889 82.3% Dare 1 $ 298.63 $ 27 0.0% Ma'abat 9 $ 32,302.60 73 $ 254,564.40 86 $ 227,912.72 $ 33,642 2.5% Purugua 1 $ 4,338.41 $ 174 0.0% Sau 254 $ 836,532.31 307 $ 1,105,726.44 307 $ 1,450,259.50 $ 199,352 15.1% Vemasse 1 $ 102.13 1 $ 102.13 1 $ 102.13 $ 18 0.0% Total $ 3,345,821 $ 6,970,617 $ 13,166,443 $ 1,321,304 100.0%

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

In addition to this, flood damages were calculated based on the indicative flood maps for all of Timor-Leste, by assessing the value of property and incomes affected by moderate and high severity flooding (i.e. because only an extent map is available, it is not possible to derive flood depth/damage data so it is assumed that if flooded, then a property is damaged to the full value). While this represents a possible over-estimation of damages that would occur (or rather the upper limit of damages, should the extreme event result in total devastation), it provides a look at the relative damages between municipalities.

Table 2-11: Economic damages that would occur due to moderate and high flood events

Moderate and High Rice Areas % Rice Areas No of Value of Water WS Irrigation Service Area Rank Municipality Total Pop'n Total Male Total Female Crop Income IS Beneficiaries Impacted (ha) Impacted Properties Property Damage Supply Beneficiaries System (ha) 1 Baucau 2,087.73 47.01% 1,083 6,011 3,160 3,147 2,075,327 76,623 1 952 17 2,357 2,408 2 Viqueque 1,746.41 52.45% 1,415 7,053 3,698 3,755 509,927 108,227 1 - 8 5,709 1,465 3 Bobonaro 984.70 62.09% 1,151 6,184 3,317 3,355 1,672,655 87,731 6 803 3 216 470 4 Lautem 719.12 48.78% 1,272 6,779 3,462 3,669 2,301,196 96,120 13 18,822 7 337 435 5 Manatuto 540.64 64.55% 584 3,351 1,767 1,664 1,135,483 47,912 4 1,562 12 890 850 6 Ermera 456.96 56.33% 1,005 6,002 3,264 3,082 2,450,995 69,513 1 - 4 644 478 7 Manufahi 258.44 66.55% 900 4,995 2,683 2,456 1,322,823 68,676 2 715 1 200 200 8 Aileu 176.92 64.51% 289 1,820 957 895 605,359 21,925 - - 4 168 177 9 Liquica 157.06 67.69% 1,222 7,444 3,940 3,720 1,997,989 98,422 4 2,448 1 200 20 10 Covalima 81.54 66.43% 1,631 8,238 4,291 4,291 2,039,998 135,443 5 3,675 3 801 310 11 Dili 70.18 62.17% 5,063 32,824 17,643 16,973 19,696,211 212,675 1 - - - - 12 Ainaro 48.80 52.36% 361 1,975 1,035 1,028 447,677 28,261 - - - - - Grand Total 7,328.51 53.48% 15,976 92,676 49,217 48,035 36,255,640 1,051,528 38 28,977 60 11,522 6,813

Table 2-11 shows that a total of $36.26 Million in damages, 1.05 Million in crop income losses and $6.84 Million in total income losses is possible under moderate and high severity flood events. In addition, 38 water supply sources, and 6,813 ha of irrigated land will be impacted. 53.47% of rice areas will be affected.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

2.9.2 Landslide Risk

Landslides induced by flooding are reported to be one of the most common disasters in Timor- Leste. The country experienced large-scale landslides in many mountainous areas, especially in Liquiçá district, due to heavy rains brought by La Niña weather patterns from December 2007 to April 2008. A landslide in Bobometo village of Oekusi destroyed at least 2 hectares of local farmland and forced the evacuation of 15 families living around the affected area. In Timor-Leste, high occasional rainfall, steep slopes, high weathering rates and slope material with low shear resistance or high clay content are the main preconditions for landslides. Apart from their potential to cause casualties and damage, landslides can also cause major disruption to the fragile road network, isolating communities for long durations. Deforestation, vegetation destruction by fire or other sources and inappropriate agricultural activities in Timor- Leste have contributed to creating conditions that make areas prone to landslides.

The UNDP landslide hazard maps (Figure 2-30) show spatial distribution of susceptibility zones. The range of zones are very low to very high. The UNDP national landslide hazard map has been integrated with receptor socio-economic data to assess landslide risk, damages and losses and climate change impact has been included.

Figure 2-30: Landslide Hazard map of Timor-Leste

Landslide risk – baseline and climate change assessment Under climate change and with coping capacity taken into account, landslides have the greatest impact to house and water sources in Viqueue, main and rural roads and cropland in Ermera, and rice plantations in Baucau.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Landslide Risk to Dwelling Units Landslide Risk to Main Roads Landslides Risk to Cropland Total Risk Score Total Risk Score Municipality Baseline Rank Total Risk Score Total Risk Score Municipality Municipality Baseline Rank Total Risk Score Total Risk Score Municipality Baseline Rank Baseline CCS Baseline No CCS CCS No CCS Baseline CCS Baseline No CCS Wetness Ind CCS No CCS Baseline CCS No CCS CCS No CCS 633690 11% 70410 4% Aileu 3 7 5460 16% 607 7% Aileu Aileu 2 6 21531 4% 1781 3% Aileu 6 10 217551 4% 72517 5% Ainaro 7 5 2990 9% 997 12% Ainaro Ainaro 4 3 22104 4% 2433 4% Ainaro 5 9 933345 16% 103705 7% Baucau 2 3 4832 14% 537 7% Baucau Baucau 3 8 97298 19% 9426 16% Baucau 2 2 42030 1% 42030 3% Bobonaro 11 10 1135 3% 1135 14% Bobonaro Bobonaro 8 2 16349 3% 4435 8% Bobonaro 7 6 231969 4% 77323 5% Covalima 6 4 2142 6% 714 9% Covalima Covalima 5 4 41955 8% 13711 23% Covalima 3 1 535920 9% 178640 11% Dili 4 2 749 2% 250 3% Dili Dili 9 12 468 0% 155 0% Dili 12 12 273294 5% 30366 2% Ermera 5 11 11666 35% 1296 16% Ermera Ermera 1 1 251334 50% 3150 5% Ermera 1 8 215676 4% 71892 5% Lautem 8 6 1523 5% 508 6% Lautem Lautem 7 10 10075 2% 3358 6% Lautem 8 7 26327 0% 26327 2% Liquica 12 12 540 2% 540 7% Liquica Liquica 11 7 913 0% 751 1% Liquica 11 11 42599 1% 42599 3% Manatuto 10 9 694 2% 694 9% Manatuto Manatuto 10 5 5787 1% 5462 9% Manatuto 10 5 53876 1% 53876 3% Manufahi 9 8 354 1% 354 4% Manufahi Manufahi 12 11 6697 1% 5997 10% Manufahi 9 4 2457231 43% 819077 52% Viqueque 1 1 1592 5% 531 7% Viqueque Viqueque 6 9 25059 5% 7880 13% Viqueque 4 3 5663508 100% 1588762 100% 33678 100% 8162 100% 499570 100% 58538 100% Total Risk Score Total Risk Score Municipality Climate change Rank Total Risk Score Total Risk Score Municipality Municipality Climate Change Rank Total Risk Score Total Risk Score Municipality Climate Change Rank Climate Change CC/ No CCS CCS No CCS Climate Change CC/ No CCS Wetness Ind CCS No CCS Climate Change CC/ No CCS Wetness Ind CCS No CCS 882450 10% 99714 4% Aileu 3 7 7617 16% 846 7% Aileu Aileu 3 9 39571 4% 10103 3% Aileu 6 9 392337 5% 130779 5% Ainaro 7 5 4130 8% 1377 11% Ainaro Ainaro 4 3 50449 5% 23371 6% Ainaro 5 5 1330338 15% 152754 6% Baucau 2 4 8555 17% 951 8% Baucau Baucau 2 7 192021 21% 34263 9% Baucau 2 2 75963 1% 75963 3% Bobonaro 10 9 1672 3% 1672 13% Bobonaro Bobonaro 8 1 31846 3% 23794 6% Bobonaro 7 4 459648 5% 153216 6% Covalima 6 3 3505 7% 1168 9% Covalima Covalima 5 4 88285 9% 29794 8% Covalima 3 3 650655 8% 234789 9% Dili 4 2 1201 2% 400 3% Dili Dili 9 12 917 0% 307 0% Dili 12 12 543159 6% 60351 2% Ermera 5 11 14141 29% 1571 13% Ermera Ermera 1 2 425039 46% 204482 54% Ermera 1 1 314052 4% 105036 4% Lautem 8 6 2862 6% 954 8% Lautem Lautem 6 6 23414 3% 7805 2% Lautem 8 10 45207 1% 45207 2% Liquica 12 12 805 2% 805 6% Liquica Liquica 11 10 1955 0% 1739 0% Liquica 11 11 68421 1% 68421 3% Manatuto 11 10 1121 2% 1121 9% Manatuto Manatuto 10 5 12318 1% 11884 3% Manatuto 10 8 93873 1% 93873 4% Manufahi 9 8 600 1% 600 5% Manufahi Manufahi 12 11 12997 1% 12063 3% Manufahi 9 7 3804780 44% 1291500 51% Viqueque 1 1 2790 6% 930 8% Viqueque Viqueque 7 8 51501 6% 17797 5% Viqueque 4 6 8660883 100% 2511603 100% 48998 100% 12395 100% 930311 100% 377402 100% Landslide Risk to Water Sources Landslides Risk to Rice Total Risk Score Total Risk Score Municipality Baseline Rank Total Risk Score Total Risk Score Municipality Baseline Rank Landslide Risk - Rural Roads Baseline CCS Baseline No CCS CCS No CCS Baseline CCS No CCS CCS No CCS Total Risk Score Total Risk Score Municipality Baseline Rank 46719 1% 5191 0% Aileu 8 33 Baseline CCS Baseline No CCS CCS No CCS 31513 5% 2551 3% Aileu 5 8 38718 1% 12906 1% Ainaro 9 29 14699 15% 1633 8% Aileu 3 5 4461 1% 658 1% Ainaro 7 12 257643 6% 28627 2% Baucau 3 24 4118 4% 1373 7% Ainaro 4 7 335834 51% 32950 36% Baucau 1 1 197542 4% 197542 15% Bobonaro 4 16 17158 18% 1906 10% Baucau 2 4 13863 2% 8549 9% Bobonaro 6 4 3019 3% 3019 15% Bobonaro 7 3 29976 1% 9992 1% Covalima 10 31 2472 0% 790 1% Covalima 11 11 3519 4% 1173 6% Covalima 6 10 54 0% 18 0% Dili 12 35 2963 0% 978 1% Dili 10 10 1221 1% 407 2% Dili 10 15 1576548 35% 175172 14% Ermera 2 17 151949 23% 4568 5% Ermera 2 5 43575 45% 4842 24% Ermera 1 2 197415 4% 65805 5% Lautem 5 19 31890 5% 10118 11% Lautem 4 3 1807 2% 602 3% Lautem 9 16 58910 1% 58910 5% Liquica 6 20 1115 0% 1100 1% Liquica 12 9 1840 2% 1840 9% Liquica 8 10 16005 0% 16005 1% Manatuto 11 26 3836 1% 3801 4% Manatuto 8 6 974 1% 974 5% Manatuto 12 16 52061 1% 52061 4% Manufahi 7 23 3703 1% 3321 4% Manufahi 9 7 1026 1% 1026 5% Manufahi 11 16 1981455 44% 660485 51% Viqueque 1 13 74150 11% 21906 24% Viqueque 3 2 3555 4% 1185 6% Viqueque 5 15 4453046 100% 1282714 100% 657750 100% 91289 100% 96511 100% 19981 100% Total Risk Score Total Risk Score Municipality Climate Change Rank Total Risk Score Total Risk Score Municipality Climate Change Rank Total Risk Score Total Risk Score Municipality Climate Change Rank Climate Change CC/ No CCS CCS No CCS Climate Change CC/ No CCS Wetness Ind CCS No CCS Climate Change CC/ No CCS CCS No CCS 73800 1% 8232 0% Aileu 11 33 58049 4% 15323 4% Aileu 5 6 21352 15% 2372 8% Aileu 3 20 77385 1% 25803 1% Ainaro 8 26 10129 1% 4482 1% Ainaro 7 9 5963 4% 1988 7% Ainaro 5 22 365874 5% 40770 2% Baucau 7 24 663601 49% 114469 29% Baucau 1 2 29484 21% 3276 11% Baucau 2 18 266520 4% 266520 14% Bobonaro 3 17 29582 2% 24272 6% Bobonaro 6 4 4294 3% 4294 14% Bobonaro 7 17 39840 1% 13320 1% Covalima 10 31 5219 0% 1786 0% Covalima 11 12 6069 4% 2023 7% Covalima 4 21 39 0% 21 0% Dili 12 35 5866 0% 1968 0% Dili 10 11 1931 1% 644 2% Dili 10 32 2588148 38% 287604 15% Ermera 2 16 338886 25% 145408 36% Ermera 2 1 57936 41% 6437 21% Ermera 1 14 263166 4% 87738 5% Lautem 5 20 64565 5% 22204 6% Lautem 4 5 3703 3% 1234 4% Lautem 8 28 103755 2% 103755 5% Liquica 4 18 2593 0% 2573 1% Liquica 12 10 2699 2% 2699 9% Liquica 9 19 8756 1% 8709 2% Manatuto 8 7 1616 1% 1616 5% Manatuto 12 25 21354 0% 21354 1% Manatuto 9 28 73269 1% 73269 4% Manufahi 6 23 7095 1% 6585 2% Manufahi 9 8 1678 1% 1678 6% Manufahi 11 24 146557 11% 52586 13% Viqueque 3 3 5795 4% 1932 6% Viqueque 6 23 2937285 43% 979383 51% Viqueque 1 13 1340898 100% 400364 100% 142522 100% 30194 100% 6810435 100% 1907769 100%

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Landslide economic damages

Economic damages due to high and very high intensity landslide could reach $186.6 Million to properties and $13.4 Million to total income lost. In addition, 1,042km of roads, 14,250 road beneficiaries, 15 water supply sources and 1,767 ha of land are at risk of damages.

Table 2-12: Economic damages due to high and very high severity landslides

High and Very High Rice Areas % Rice Areas No of Value of Water WS Irrigation Service Area Rank Municipality Total Pop'n Total Male Total Female Total Income IS Beneficiaries Impacted (ha) Impacted Properties Properties Supply Beneficiaries System (ha) 1 Ermera 1,344.38 60.87% 15,810 92,706 48,372 48,390 72,268,973 5,427,855 5 2,707 10 1,159 925 2 Bobonaro 569.30 13.05% 6,476 34,960 18,245 18,875 29,190,738 2,182,926 10 2,470 3 403 495 3 Baucau 484.94 4.13% 1,179 5,546 2,784 3,002 4,823,712 349,263 - - 7 456 474 4 Viqueque 311.10 4.13% 886 4,009 2,076 2,205 3,644,073 264,343 - - 1 78 112 5 Aileu 105.64 18.86% 2,619 16,618 8,733 8,309 17,202,702 853,882 - - 1 82 50 6 Ainaro 92.12 32.50% 5,342 31,946 16,651 16,391 23,462,455 1,729,281 - - 4 1,103 636 7 Lautem 56.89 1.44% 163 761 379 414 668,679 48,462 - - - - - 8 Manufahi 42.46 4.29% 1,222 7,293 3,859 3,578 5,706,831 431,405 - - - - - 9 Manatuto 3.97 0.19% 708 4,810 2,479 2,451 4,625,122 208,601 1 3,223 - - - 10 Covalima 3.84 1.22% 624 3,349 1,702 1,775 2,551,167 184,671 - - - - - 11 Liquica 1.71 0.28% 4,336 25,404 13,166 13,038 18,763,473 1,384,913 4 3,867 - - - 12 Dili 1.08 0.30% 688 4,645 2,443 2,346 3,658,884 286,644 - - - - - Grand Total 3,017.44 8.62% 40,053 232,047 120,889 120,774 186,566,807 13,352,244 15 9,560 16 2,122 1,767

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

2.9.3 Erosion Risk The UNDP/CARE 2015 erosion susceptibility map has been integrated with receptor socio- economic data to assess erosion risk, damages and climate change impact has been included.

Figure 2-31 Erosion Susceptibility Map

Erosion Risk – baseline and climate change assessment

Under climate change and with coping capacity considered, erosion has the greatest impact to houses in Ermera and water sources in Lautem.

Erosion risk to Dwelling Units Erosion Risk - Water Sources Total Risk Score Total Risk Score Municipality Baseline Rank Total Risk Score Total Risk Score Municipality Baseline Rank Baseline CCS Baseline No CCS CCS No CCS Baseline CCS Baseline No CCS CCS No CCS 277128 12% 30792 6% Aileu 3 10 362205 29% 40245 11% Aileu 1 4 125496 5% 41832 8% Ainaro 6 6 18501 1% 6167 2% Ainaro 10 11 456039 19% 50671 9% Baucau 2 4 104823 8% 11647 3% Baucau 4 8 51489 2% 51489 9% Bobonaro 9 3 24511 2% 24511 7% Bobonaro 9 6 107766 4% 35922 6% Covalima 7 8 226800 18% 75600 21% Covalima 3 2 237024 10% 79008 14% Dili 4 2 12726 1% 4242 1% Dili 11 12 829980 35% 92220 17% Ermera 1 1 76806 6% 8534 2% Ermera 5 9 91218 4% 30406 5% Lautem 8 11 298347 24% 99449 27% Lautem 2 1 41734 2% 41734 8% Liquica 10 7 32922 3% 32922 9% Liquica 8 5 22523 1% 22523 4% Manatuto 12 12 43544 3% 43544 12% Manatuto 6 3 32065 1% 32065 6% Manufahi 11 9 7450 1% 7450 2% Manufahi 12 10 132843 6% 44281 8% Viqueque 5 5 42927 3% 14309 4% Viqueque 7 7 2405305 100% 552943 100% 1251562 100% 368620 100% Total Risk Score Total Risk Score Municipality Climate change Rank Total Risk Score Total Risk Score Municipality Climate Change Rank Climate Change CC/ No CCS CCS No CCS Climate Change CC/ No CCS CCS No CCS 472959 11% 52551 5% Aileu 4 11 609768 25% 67752 9% Aileu 2 5 213075 5% 71025 7% Ainaro 6 7 35352 1% 11784 2% Ainaro 10 11 946377 21% 105153 10% Baucau 2 3 218214 9% 24246 3% Baucau 4 8 100026 2% 100026 10% Bobonaro 9 4 51498 2% 51498 7% Bobonaro 9 6 207801 5% 69267 7% Covalima 7 8 456048 19% 152016 21% Covalima 3 2 492390 11% 164130 16% Dili 3 1 25452 1% 8484 1% Dili 11 12 1382535 31% 153615 15% Ermera 1 2 147663 6% 16407 2% Ermera 5 9 184014 4% 61338 6% Lautem 8 9 612531 25% 204177 28% Lautem 1 1 74697 2% 74697 7% Liquica 10 6 68121 3% 68121 9% Liquica 8 4 42678 1% 42678 4% Manatuto 12 12 92544 4% 92544 13% Manatuto 6 3 57630 1% 57630 6% Manufahi 11 10 12759 1% 12759 2% Manufahi 12 10 250371 6% 83457 8% Viqueque 5 5 91197 4% 30399 4% Viqueque 7 7 4424553 100% 1035567 100% 2421147 100% 740187 100% 53

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Erosion economic damages

The total potential economic damages from moderate and high severity erosion is just under $10 Million with 140 water supply sources, and 50,693 ha of land affected. 80.98 % of rice areas are affected representing 133,422 households.

Table 2-13: Economic damages due to moderate and high severity erosion

Moderate and High Rice Areas % Rice Areas No of Water WS Irrigation Service Area Rank Municipality Total Pop'n Total Male Total Female Crop Income IS Beneficiaries Impacted (ha) Impacted Properties Supply Beneficiaries System (ha) 1 Baucau 8,842.48 75.31% 11,287 55,917 29,166 29,527 926,347 3 3,565 105 8,137 11,307 2 Viqueque 7,001.45 92.94% 10,777 51,739 27,205 27,790 872,821 3 1,964 31 16,565 6,743 3 Bobonaro 3,788.92 86.86% 13,205 69,795 36,808 37,947 1,057,241 22 7,345 24 3,259 5,987 4 Lautem 3,234.70 81.82% 7,487 38,875 19,786 21,009 596,699 25 24,526 39 2,024 2,374 5 Ermera 1,648.07 74.62% 19,282 113,013 59,017 58,772 1,486,786 6 2,459 14 1,543 1,167 6 Manatuto 1,062.74 50.84% 5,666 34,869 18,200 17,725 461,450 19 12,696 42 4,136 4,979 7 Manufahi 892.27 90.17% 7,781 45,274 23,908 22,598 611,033 13 1,359 10 4,497 6,136 8 Aileu 554.01 98.88% 7,210 45,338 23,814 22,780 591,802 4 9,169 9 474 377 9 Liquica 518.01 84.82% 10,500 62,132 32,220 31,928 856,116 11 10,215 7 1,507 916 10 Covalima 283.22 89.89% 9,559 48,750 25,294 25,168 781,795 18 21,936 16 6,281 5,505 11 Dili 276.75 76.60% 21,640 140,557 75,756 72,897 937,432 12 1,414 1 20 75 12 Ainaro 248.24 87.59% 9,028 52,776 27,648 26,936 718,804 4 1,535 14 3,945 5,128 Grand Total 28,350.86 80.98% 133,422 759,035 398,822 395,077 9,898,326 140 94,618 312 52,388 50,693

2.9.4 Drought Risk

Timor-Leste has been experiencing a rapidly worsening drought during the winter season especially in the northern areas (CRM, 2009). Historical records indicate that Timor-Leste has experienced El Niño-related droughts in the past. During the period of 2002-2003, and most recently in 2015-16. El Niño-related drought affects almost all of Timor-Leste. In 2006, the El Niño Southern Oscillation (ENSO) caused delays in the typical wet season throughout the country for more than one month. In addition, the rainfall pattern remained erratic and dry spells were reported in some areas until late February 2007. That year there were serious negative impacts on agricultural production due to the late onset of the rainy season and erratic rainfall pattern. There was a 30% drop in production in 2007 which is attributed to drought (FAO/WFP, 2007). In 2015 and 2016, El Niño resulted in water and food shortages across the country causing crop failure, limited production, reduced family income with 78% of the population affected by food and water shortages, the death of 70,000 livestock and an additional 70,000 reported sick. Limited supply of water has led to a significant gap in cereal production for two consecutive years and the ongoing drought is putting a critical pressure on the limited resources of rural households.

In an El Niño year, rainfall is not only diminished but the onset of the rainy season is delayed as well (Dolcemascolo, 2003). Because of this, studies of drought in time and space are essential. It is also important to study the probability of having a consecutive dry period during the growing season of a crop. Drought susceptibility has been mapped based on the probability of occurrence of droughts at different severity levels (i.e. moderate, severe, and extreme and moderate to extreme) in the 24 stations.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Drought Risk – baseline and climate change assessment

Under climate change and with coping capacity considered, drought has the greatest impact to houses in Ermera and water sources in Aileu. Given most agriculture is ‘backyard’ subsistence agriculture, it is reasonable to use impact of droughts on dwellings as a proxy to impact on the backyard subsistence agriculture that much of the rural communities rely on.

Drought economic damages

The economic damages that would be incurred in a high and very high severity drought event is $12.5 Million for crop income, with 193 water supply sources affected, and 62,808 ha of land. 98.63% of rice production areas are at risk from high and very high drought which will affect 172,403 properties and nearly the whole population of Timor-Leste.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Table 2-14: Economic damages due to drought hazard

High and Very High Rice Areas % Rice Areas No of Water WS Irrigation Service Area Rank Municipality Total Pop'n Total Male Total Female Crop Income IS Beneficiaries Impacted (ha) Impacted Properties Supply Beneficiaries System (ha) 1 Baucau 15,109.90 100.00% 21,522 111,816 58,244 59,372 1,686,066 4 4,517 163 14,642 18,873 2 Viqueque 12,203.80 100.00% 14,212 68,227 35,839 36,932 1,145,812 8 7,063 40 17,420 8,173 3 Bobonaro 7,592.47 100.00% 17,689 93,595 49,151 50,564 1,383,925 39 9,821 18 2,789 5,370 4 Covalima 5,986.01 100.00% 11,959 61,345 31,798 31,691 938,707 27 27,240 19 6,675 5,962 5 Ermera 5,283.14 100.00% 20,754 121,666 63,558 63,292 1,603,770 7 2,707 14 1,543 1,167 6 Lautem 5,233.06 85.77% 9,597 51,147 25,937 27,506 718,617 29 27,328 46 1,956 2,222 7 Manatuto 4,502.91 100.00% 7,270 44,516 23,211 22,585 588,718 26 18,152 54 4,824 6,093 8 Manufahi 2,937.37 100.00% 8,890 51,758 27,272 25,838 697,066 15 1,975 11 5,997 8,332 9 Ainaro 1,346.93 100.00% 10,027 58,172 30,410 29,730 799,111 5 2,041 15 3,970 5,199 10 Aileu 956.68 100.00% 7,468 46,950 24,686 23,576 612,700 4 9,169 9 474 377 11 Liquica 943.70 100.00% 11,513 68,167 35,322 34,973 936,941 12 12,492 7 1,507 916 12 Dili 415.55 100.00% 31,502 202,833 109,381 105,484 1,348,646 17 1,414 2 70 125 Grand Total 62,511.51 98.63% 172,403 980,192 514,809 511,543 12,460,079 193 119,402 398 61,867 62,808

2.9.5 Multi-hazard Assessment of receptor risk

A multivariate analysis has been undertaken to determine the combined effect of all hazards on key receptors. This provides a picture of the infrastructure and receptors most vulnerable to natural hazards under baseline and climate change conditions and taking coping capacity into account.

Dwellings For dwellings, the riskiest municipalities for both the baseline and climate change scenarios are Baucau, Ermera, Dili and Aileu respectively. The result reflects the density of population in these municipalities and the depth of poverty and hence lack of coping capacity. In addition, given that dwellings can be considered as a proxy to subsistence agriculture, the combined risk reflects the likely combined risk to the ability of communities in these highest risk municipalities to cope with, and recover from hydrometeorological hazards.

Ranking of Dwellings affected by Hazards Ranking of Dwellings affected by Hazards Climate Change Baseline with Standard Combined Standard Combined with Coping Flood Landslide Drought Erosion Wind Mean Rank Deviation Rank Coping Capacity Flood Landslide Drought Erosion Wind Mean Rank Deviation Rank Capacity Aileu 7 3 3 3 4 4.0 1.7 4 Aileu 7 3 3 4 4 4.2 1.6 4 Ainaro 8 7 5 6 5 6.2 1.3 7 Ainaro 8 7 6 6 5 6.4 1.1 7 Baucau 2 2 2 2 1 1.8 0.4 1 Baucau 2 2 2 2 1 1.8 0.4 1 Bobonaro 9 11 9 9 9 9.4 0.9 9 Bobonaro 9 10 9 9 9 9.2 0.4 9 Covalima 4 6 7 7 6 6.0 1.2 6 Covalima 4 6 7 7 6 6 1.2 6 Dili 1 4 4 4 3 3.2 1.3 3 Dili 1 4 4 3 3 3 1.2 3 Ermera 3 5 1 1 2 2.4 1.7 2 Ermera 3 5 1 1 2 2.4 1.7 2 Lautem 6 8 8 8 7 7.4 0.9 8 Lautem 6 8 8 8 8 7.6 0.9 8 Liquica 10 12 10 10 10 10.4 0.9 10 Liquica 10 12 10 10 10 10.4 0.9 10 Manatuto 12 10 12 12 12 11.6 0.9 11 Manatuto 12 11 12 12 12 11.8 0.4 12 Manufahi 11 9 11 11 11 10.6 0.9 11 Manufahi 11 9 11 11 11 10.6 0.9 11 Viqueque 5 1 6 5 8 5.0 2.5 5 Viqueque 5 1 5 5 7 4.6 2.2 5

Roads

Rural roads in Baucau and Ermera are at highest combined risk from the combination of flooding and landslide hazards, followed by Aileu and Ainaro under baseline and climate change conditions. Main roads in Baucau are also at highest combined risk followed by Lautem, Cova Lima, Viqueue and Ermera under baseline conditions and climate change conditions. Ainaro main and rural roads show increased risk under climate change.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Ranking of Main Roads affected by Hazards Ranking of Main Roads affected by Hazards Climate Change Baseline with Standard Combined Standard Combined with Coping Flood Landslide Mean Rank Coping Capacity Flood Landslide Mean Rank Deviation Rank Deviation Rank Aileu 12 2 7.0 7.1 8 Capacity Ainaro 9 4 6.5 3.5 6 Aileu 8 3 5.5 3.5 6 Baucau 2 3 2.5 0.7 1 Ainaro 6 4 5.0 1.4 4 Baucau 1 2 1.5 0.7 1 Bobonaro 5 8 6.5 2.1 6 Bobonaro 10 8 9.0 1.4 9 Covalima 4 5 4.5 0.7 3 Covalima 5 5 5.0 0 4 Dili 11 9 10.0 1.4 11 Dili 7 9 8.0 1.4 8 Ermera 10 1 5.5 6.4 5 Ermera 3 1 2.0 1.4 2 Lautem 1 7 4.0 4.2 2 Lautem 2 6 4.0 2.8 3 Liquica 7 11 9.0 2.8 10 Liquica 11 11 11.0 0 11 Manatuto 6 10 8.0 2.8 9 Manatuto 9 10 9.5 0.7 10 Manufahi 8 12 10.0 2.8 11 Manufahi 12 12 12.0 0 12 Viqueque 3 6 4.5 2.1 3 Viqueque 4 7 5.5 2.1 6

Ranking of Rural Roads affected by Hazards Ranking of Rural Roads affected by Hazards Climate Change Baseline with Standard Combined Standard Combined with Coping Flood Landslide Mean Rank Coping Capacity Flood Landslide Mean Rank Deviation Rank Deviation Rank Aileu 5 3 4.0 1.4 3 Capacity Ainaro 7 4 5.5 2.1 5 Aileu 5 3 4.0 1.4 3 Baucau 1 2 1.5 0.7 1 Ainaro 7 5 6.0 1.4 6 Baucau 1 2 1.5 0.7 1 Bobonaro 8 7 7.5 0.7 8 Bobonaro 8 7 7.5 0.7 8 Covalima 4 6 5.0 1.4 4 Covalima 4 4 4.0 0 3 Dili 10 10 10.0 0.0 9 Dili 10 10 10.0 0 9 Ermera 2 1 1.5 0.7 1 Ermera 2 1 1.5 0.7 1 Lautem 3 9 6.0 4.2 7 Lautem 3 8 5.5 3.5 5 Liquica 12 8 10.0 2.8 9 Liquica 12 9 10.5 2.1 11 Manatuto 11 12 11.5 0.7 12 Manatuto 11 12 11.5 0.7 12 Manufahi 9 11 10.0 1.4 9 Manufahi 9 11 10.0 1.4 10 Viqueque 6 5 5.5 0.7 5 Viqueque 6 6 6.0 0 6

Water Sources

Water Sources in Lautem, Baucau, Aileu and Ermera are at highest risk from the combination of flood, landslides, droughts, and erosion under baseline conditions. Water sources in Lautem, Aileu, Liquica and Cova Lima are at highest risk under climate change. It should be noted that the risks to individual hazards is very different in different municipalities and this should be considered during the design of intervention measures in specific municipalities.

Ranking of Water Sources affected by Hazards Ranking of Water Sources affected by Hazards Baseline with Climate Change Standard Combined Coping Standard Combined with Coping Flood Landslide Drought Erosion Mean Rank Deviation Rank Capacity Flood Landslide Drought Erosion Mean Rank Deviation Rank Capacity Aileu 6 8 1 3 4.5 3.1 3 Aileu 4 11 2 5 5.5 3.9 3 Ainaro 10 9 10 6 8.8 1.9 10 Ainaro 10 8 11 11 10 1.4 11 Baucau 7 3 5 2 4.3 2.2 2 Baucau 3 7 5 8 5.8 2.2 5 Bobonaro 3 4 9 9 6.3 3.2 7 Bobonaro 7 3 10 6 6.5 2.9 7 Covalima 2 10 3 7 5.5 3.7 5 Covalima 2 10 4 2 4.5 3.8 2 Dili 11 12 11 4 9.5 3.7 11 Dili 11 12 12 12 11.8 0.5 12 Ermera 12 2 4 1 4.8 5.0 4 Ermera 12 2 6 9 7.3 4.3 9 Lautem 1 5 2 8 4.0 3.2 1 Lautem 1 5 3 1 2.5 1.9 1 Liquica 5 6 7 10 7.0 2.2 8 Liquica 5 4 9 4 5.5 2.4 3 Manatuto 4 11 6 12 8.3 3.9 9 Manatuto 6 9 8 3 6.5 2.6 7 Manufahi 8 6 13 10 9.3 3 10 Manufahi 8 7 12 11 9.5 2.4 11 Viqueque 9 1 7 7 6 3.5 6 Viqueque 9 1 8 5 5.8 3.6 6

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

Agricultural Land

Agricultural land is assessed based on the combined effect on cropland, rice and orchards. Baucau Viqueue, Ermera, and Cova Lima are the municipalities worst affected by flooding landslides and wind, under both baseline and climate change conditions. It should be noted, however, that analysis of the individual crops show different ranking of impact by hazards which will be considered when considering intervention measures targeted in different municipalities

Ranking of All Crops affected by Hazards Ranking of All Crops affected by Hazards Climate Change Baseline with Standard Combined Standard Combined Flood Landslide Wind Mean Rank with Coping Flood Landslide Wind Mean Rank Coping Capacity Deviation Rank Deviation Rank Capacity Aileu 6 6 7 6.3 0.6 5 Aileu 6 4 7 5.7 1.5 5 Ainaro 10 5 5 6.7 2.9 7 Ainaro 10 7 5 7.3 2.5 7 Baucau 1 2 2 1.7 0.6 1 Baucau 1 1 2 1.3 0.6 1 Bobonaro 8 7 8 7.7 0.6 8 Bobonaro 7 8 8 7.7 0.6 8 Covalima 2 3 3 2.7 0.6 3 Covalima 4 5 3 4.0 1 4 Dili 12 12 12 12.0 0 12 Dili 11 11 12 11.3 0.6 11 Ermera 4 1 1 2.0 1.7 2 Ermera 3 2 1 2.0 1 2 Lautem 5 8 6 6.3 1.5 5 Lautem 5 6 6 5.7 0.6 5 Liquica 11 11 11 11.0 0 11 Liquica 12 12 11 11.7 0.6 12 Manatuto 7 10 9 8.7 1.5 9 Manatuto 8 9 9 8.7 0.6 9 Manufahi 9 9 10 9.3 0.6 10 Manufahi 9 10 10 9.7 0.6 10 Viqueque 3 4 4 3.7 0.6 4 Viqueque 2 3 4 3.0 1 3

2.10 Prioritization of municipalities for intervention

Based on the risk assessment conducted and extensive consultations with central and local government partners, the following municipalities have been identified as the most vulnerable to hydrometeorological hazards and target municipalities where the GCF funds will be used for direct interventions: Baucau, Ermera, Aileu, Viqueue, and Lautem. Liquica is also included for strategic and political reasons. Liquica, which is at high risk from flooding and landslides only and for two receptors (houses and agriculture) only, and therefore did not rank within the top 6, has been included as it represents a municipality with significant deficit of flood protection infrastructure and will address one of the hazards with the greatest and most frequent impact on communities.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

3. THE MOST VULNERABLE MUNICIPALITIES AND SUCOS

3.1 Underlying causes of vulnerability

Due to its geographical location, topography and socioeconomic conditions, Timor-Leste is considered to be one of the top 10 countries most at risk of disaster (9th rank). Together with the other 10 countries, the vulnerability and susceptibility of Timor-Leste is high, with a significant lack of coping capacity and adaptive capacity.

The Asian Development Bank undertook a vulnerability assessment at the village (suco) level, and found that there are 61 villages categorized as being vulnerable to very vulnerable to climate change based on high levels of exposure and sensitivity and low adaptive capacity. In this study the level of exposure, sensitivity and adaptive capacity of the sucos are represented by socio economic and “biophysical condition”. The study found that the most vulnerable sucos are mainly located in the western part of the country. The study, however, did not make use to hazard information and is based mainly on living standards in the sucos which is used as an indication of vulnerability. Living standards at the suco level was assessed using the asset information of the 2010 Population and Housing Census and deriving a vulnerability index based on the sum of the number of weighted household assets.

The ADB vulnerability index includes an infrastructure index, which is a simple average of indexes of the share of households with electricity, improved water, and improved sanitation. Access to infrastructure is a key factor in the ADB vulnerability assessment. It was found that access to infrastructure is higher in sucos with higher living standards, and there is a large gap in access between groups. Of the 89 sucos with the lowest living standards, the average share of households with electricity is only 3%. This compares with an average share of 66% in the 89 sucos with the highest living standards. Access to improved water and improved sanitation is also much higher in sucos with living standards. The study found that there is a large gap between the Dili district and other districts, and the concentration of the sucos with the highest living standards in or close to Dili or district centers. The sucos with the lowest living standards are concentrated in Baucau, Lautem, Mantauto, Oecussi, and Viqueque and districts.

This asset-based vulnerability index is a measure of development outcomes and opportunities for development. However, the ADB analysis did not explicitly examine the impact of hazards in identifying the municipalities and sucos most vulnerable to climate change. The analysis undertaken in the previous section provides this additional analysis which has enabled a more appropriate prioritisation of municipalities for intervention to address the threats posed by climate- induced hazards.

In Timor-Leste, more than 40% of the population are defined as being below the poverty line. Globally, climate change has high impacts on furthering poverty prevalence. A key component of vulnerability in Timor Leste is the persistence of poverty, which leads to survival strategies and livelihoods that increase exposure to climate-induced risks.

Climate change will make it increasingly difficult to achieve and sustain development goals. This is largely because climate effects on poverty remain poorly understood, and poverty reduction strategies do not adequately support climate resilience. Ensuring sustainable development in the face of climate change requires action on six fronts: investing in a stronger climate and poverty evidence base; applying knowledge of development effectiveness to address adaptation needs; supporting nationally derived, integrated policies and programmes that address both climate risk reduction and poverty reduction; including the climate-vulnerable poor in developing strategies; and identifying how mitigation strategies can also reduce poverty and enable adaptation.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I

3.2 Livelihood pressures on land: land use, deforestation due to logging and fuelwood.

Land degradation in Timor-Leste is mainly caused by deforestation, unsustainable agricultural practices, recurring wildfires on grass-covered mountain slopes, over grazing, illegal cutting of important tree species and demographic pressures. Currently approximately 50% or about 742,000 ha of Timor-Leste is forested, none of which is protected under IUCN categories I-V. The forestry sector in Timor-Leste is particularly poorly developed and forest cover is currently decreasing at 1.7% annually, one of the highest rates in Asia. The domestic demand for building poles and sawn wood for construction and furniture has increased and the consumption of fuel wood alone has contributed to a decline in forest cover which has direct implication for land erosion and land degradation. Current wood harvest and primary processing practices using chainsaws are extremely wasteful and inefficient, capturing only an estimated 15% of the volume grown. Current Government fees and permit/licencing procedures are inefficient and do not provide a conducive business environment for the sector. Until now, the Ministry of Agriculture, Forestry and Fisheries (MAFF) has focused mostly on forest management and reforestation, and there has been no large- scale programme to support the long-term development of the commercial forestry sector due to the immediate focus on food security and agriculture production.

Around 80% of Timor Leste’s population relies on rain-fed subsistence mono-culture farming for food and livelihoods, with the majority of farmers involved in mono-culture crops, the most important of which are coffee, rice, and maize. Agricultural outputs are low due to challenging topography characterised by very steep slopes and limited cultivable land areas, limited access to improved technologies, irrigation, quality seeds and fertilizers. Most of TL’s population is engaged in upland farming in the form of shifting cultivation, with each family occupying 1– 2 hectares across 2 –3 farm areas. The cultivation period lasts for about 3 years and the land is abandoned thereafter. This results in land and watershed degradation and loss of biodiversity. In addition, the practice of slash and burn farming and cutting of timber is resulting in encroachment into the forest.

Poor management of land degradation and livelihood challenges leading to poor land management, have led to the steady increase in natural hazards at the catchment scale, which has been manifested in increased runoff rate and quantity of flood water runoff, decreased infiltration of rainfall into already steep land, resulting in increased drought risk, increased soil erosion and landslide risks. These hazards, which are also intensifying due to climate change are placing additional pressures on already poor infrastructure within catchments, resulting in infrastructure failure (e.g. washing away of bridges and roads, failure of flood defences, siltation of water sources, increased demands for water supply and irrigation infrastructure), increased cost of maintenance and rehabilitation of infrastructure and shorter service life of infrastructure.

Livelihood challenges leading to over-exploitation of land and forestry resources are increasing land degradation. Hence communities living within the catchments of rural infrastructure are inadvertently contributing to the degradation of catchment and hence increasing the risks to rural infrastructure.

While there is a Forestry Policy which is promoting an integrated landscape-based approach to sustainable forest resources management through the implementation of conservation and environmental protection measures, the production of wood and non-wood forest products for national economic development, which meets the needs of poor and vulnerable people who depend on the forests for survival, there is little funding for the implementation of the policy and plans and little evidence of sustainability of measures already being taken.

Key to reducing land degradation, and its impacts is the implementation of sustainable livelihoods for communities which will lead to the reduction of poverty, based on community participation in all aspects of forestry and developing a private sector business environment that addresses livelihood pressures on the land. The government also recognises this approach as outlined in its commercial

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I agro-forestry plan, however there is a lack of comprehensive government funding for implementation of the plan.

Current strategies supporting climate resilience do not address the root causes of rural communities exploitive and destructive land-based livelihood practices. Key to reducing land degradation and its impacts is the implementation of sustainable livelihoods for communities, that will allow communities to engage in economic activities which enhance the forests and discourage harmful land use practices.

Community induced vulnerabilities such as the livelihoods pressures resulting in land degradation and deforestation threatens the sustainability of the investment made on the small-scale infrastructure. Promoting environmentally protective economic activities in target areas of the infrastructure development, help in realizing direct economic opportunities in infrastructure development which will ensure communities develop vested interest in protecting and owning the infrastructure. Most small businesses in any economy, but especially in an economy that is in its early decades of existence or post crisis establishment such as Timor-Leste, operate below what is described as their production possibility or capabilities. However, transforming subsistence farmers in rural economies to a real productive sector faces many challenges and impediments including: • Limited labour and business skills • Low Productivity due to primitive agricultural practices • Limited infrastructure, communications, transportation, to connect rural producers to market • Unfavourable regulatory environment for micro and small business initiatives • Limited access to business capital for start-up businesses

3.3 Livelihood pressures and financial vulnerability

Rural access to finance in Timor Leste

A key livelihood challenge of rural communities is a lack of access to finance to enable them to engage in activities that will protect the land and forests and hence have a positive impact on the catchment ecosystems and hence infrastructure. There is also a lack of business skills in the identification of business opportunities and the management of the business.

In Timor Leste, access to finance is among the lowest in the world. The formal financial system is still limited in outreach and consists essentially of the banking system: three commercial banks, each an overseas branch of a foreign institution, and one local institution operating with a limited banking license. Each of these serves distinct but limited market niches within the broader population. Regulatory and supervisory functions for the banks are performed by the Banking and Payments Authority (the BPA).

There are no non-bank financial institutions subject to BPA supervision and there is no insurance company serving Timor-Leste, nor any leasing finance entities. Beyond the formal, regulated, institutions, there are microfinance institutions (MFIs), savings and loan cooperatives, and pawnshops. While MFIs are of limited significance in dollar terms, they have succeeded in reaching between a fifth and a quarter of poor households. There are also informal mechanisms to provide financial services.

Timor-Leste has a low ratio of micro, small and medium enterprises (MSME) to 1000 people when compared to other countries, making the case for SME promotion for livelihood improvement, poverty reduction and job creation.

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Table 3-1: Key Indicators for Banking Sector in Timor Leste

The private sector currently comprises mainly contractors reliant on government grants. The legal framework for private sector financing (land law, solvency and bankruptcy law etc.) is not yet in place in Timor Leste and presents additional barriers to finance.

In rural areas, land cannot be used as collateral because there is no land law in place for individual land holders (new Land law recently finalised but not enacted). There is a desire from the commercial banks to move away from collateral-based or security-based loans to cash-flow based loans (partly to overcome the lack of collateral), which will require strong business plans and entire route to market for the proposed enterprise.

For one of the major commercial banks, BNCTL, less than10% of loans are currently in rural areas. They lack the physical infrastructure to service rural communities (although they provide some mobile services (vans) and there are currently plans to open physical branches in key locations to reach sucos. Mobile phone banking is also being developed to target rural communities).

Interest rates are currently 6-40% for micro-credit (few hundred to thousand dollars) and generally less than 10% interest rates can be obtained by respected borrowers. In rural areas, lending is to small agricultural business, and small market stall vendors. Field staff in mobile units do informal education in financing and business diversification when they are out on field. (e.g. coffee growers receive advise), and the bank also provides some limited formal financial literacy and business management through programmes.

SME’s are the backbone of economy and more robust and resistant to economic shocks and reduces risk to bank and provides some confidence to borrowers. With the development of SMEs, the income of the population in the lower end of the income ladder will typically rise hence reducing income inequality and poverty; it is important to note that SMEs development is a poverty reduction intervention targeting economically active poor so minimum productivity ability is a pre-requisite. The biggest positive development in the financial services landscape of Timor-Leste was the recent drafting of the Financial Sector Development Master Plan (FSDMP), which comprehensively lays down the central bank’s vision for the development of the sector in Timor-Leste.

Infrastructure Poor infrastructure is a major barrier to accessing markets and rural economic development. MSMEs and cooperatives have indicated a desire to work together with government to improve infrastructure that is necessary for economic activities in rural areas (clean water, energy, communications, roads, and design of policy for transport system). There is insufficient infrastructure and support in transportation, storage, quality, increasing yields, and appropriate technology – all of which greatly hinder the country’s ability to scale‐up and use potential resources within Timor‐Leste. The poor transportation system and lack of electrification make production and

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I distribution very costly in Timor‐Leste. The inadequate communication system affects information flows including market related information.

3.4 Exposure to hazards: threats to lives and assets

Water Supply

Based on 2010 Census data, nearly a quarter (23%) of the rural population use a public tap, followed by protected well or spring (16%), with only 15% accessing piped water (to yard or house).

Between 1995 and 2011 access to water supply in rural areas has more than kept pace with population growth. However, according to the Joint Monitoring Programme (JMP) of WHO and UNICEF in 2011 rural residents accounted for the 92% of people nationally that did not have access to improved water supply. Access to improved water is fairly equitable, with 43% of the rural population in the lowest wealth quintile having access, and 77% in the highest quintile. This is due to government policy that focuses on public standpipes and considers this an appropriate level of service. Piped connections to individual households remain at a low level of 14%, with only 3% of the poorest rural quintile having access to individual house connections, and 28% among the richest quintile. Given its population growth rate of 2.4% per annum, if Timor-Leste is to meet its Strategic Development Plan vision for 2030—which aims for all citizens to have access to clean water, particularly in rural areas, there will need to be more intensive support and scaling up of water supply infrastructure, and importantly, financing of maintenance of rural water supply schemes to extend scheme life span and achieve the nation’s rural water supply targets. The 2020 target is for 80% of rural households to have access to improved water supply requires about 34,000 people per year in rural areas to gain access to improved water supply between 2011 and 2020. This is more than three times the average number of people (10,700 people) who gained access on an annual basis between 1995 and 2011.

An analysis of the service delivery pathway for water and sanitation undertaken by World Bank15, showed that Timor-Leste performs adequately in the ‘enabling’ phase of service delivery due to the presence of policy guidelines, national and subsector targets, and relatively clear institutional roles. However, budgets for water supply and sanitation were found to be unpredictable and fluctuate considerably from year to year. The assessment also found that budget prioritisation, allocation and expenditure of funds, and execution for major capital works, as well as community participation (particularly for remote communities where service delivery is challenging) needed improving. The assessment also found performance in sustainability, particularly regarding maintenance, needed to be improved.

Sustainability is poor due to a lack of funding to pay for water supply operations and maintenance, and no clear strategy to effectively support operations and maintenance in the rural sector. With improved operations and maintenance, water supply systems could last longer, save on replacement costs, and be a more cost-effective investment.

In addition, there is a shortage of human technical capacity throughout the full project cycle of WSS projects, contributing to low levels of service delivery and low sustainability. Importantly, in the design of water supply project, no account is taken of hydrometeroloogical hazards. Hence sizing of systems is based primarily on demand rather than in-depth analysis of sources, particularly risk to supply from drought. This is largely due to limited available data on hydrometeorological variables. With its limited water resources, Timor-Leste has a significant number of water systems which rely on spring catchments and ground water sources that are recharged by rainfall. Shifting

15 Service Delivery Assessment - Water Supply and Sanitation in Timor-Leste – Turning Finance into Services for the Future, International Bank for Reconstruction and Development/The World Bank April 2015

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I rainfall patterns and other potential effects of climate change could have serious impacts on water supply systems including availability of water resources in general. In addition, water sources need protection from other hazards such as erosion (that can cause pollution of sources), landslides (that can cause damage to infrastructure) and floods (that can cause pollution of sources and damage to infrastructure). As shown in Table 2-1 to Table 2-4, under climate change water supply sources will be at risk from hydrometeorological hazards to the following extent: Landslides – 34.2%; Floods – 12.84%; Erosion – 75%; Droughts – 97.35%.

There is also no consideration of potential multiple uses of water sources and no coordination, leading to illegal use and overuse of water sources e.g. for irrigation. There is a need for a coordinated approach between government agencies and integrated catchment management. However, there are no plans or budgets for addressing climate change risk and implementing risk reduction strategies at local level.

The World Bank service delivery assessment identified the following priority action areas for rural water supply:

• Establish clear policies and define government and community responsibilities for O&M of rural water systems. • Ensure budget is available for technical support systems for O&M services of community- managed schemes. • Increase functionality of water supply schemes by a) improving the spare parts supply chain, b) increasing numbers and skills of technical staff in districts, and c) professionalizing management of rural water supply through contracting of NGOs and the private sector. • Make district budgets transparent to show water supply funding from DNSA, decentralized projects, development partners and NGOs. • Finalize community engagement processes to improve community involvement in water supply scheme development and operation, and harmonize approaches with decentralized projects. • Develop and enforce legislation that is sensitive to traditional customs to protect springs and other water resources from illegal use.

The report concludes that sufficient budget is probably available to meet the SDP (2011-2030) rural water supply targets, but only if attention is given to operations and maintenance to ensure the water supply schemes continue to function.

Without this attention to sustainability, progress towards targets will begin to fall behind. Funds for preventive maintenance, major repairs (beyond the capacity of local communities) and technical support services to community-managed schemes need to be included in annual budgets. At the same time, a funding line would need to be established to allow for replacement of rural water assets at the end of their economic lifespan, as such replacement costs are normally not covered through rural water tariffs.

Climate resilient designs, consideration of all hydro-meteorological hazards and their likely intensification under climate change, and greater attention to O&M will increase life span and functionality of assets, requiring less future investment in replacement of schemes and saving money in the long run.

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Irrigation

The driver for irrigation schemes in Timor-Leste is rice production. The government strategy on the development and rehabilitation of irrigation schemes has been justified on the basis of the need to increase rice products to safeguard flood security.

A World Bank review of the SDP (2011-2030) highlighted the following issues:

1) The analyses completed to determine the economics of growing irrigated rice only focus on rice producing (first crop), as in most situations the supply of irrigation water in the dry season is insufficient for second crops, and there are no markets for surplus rice (defined as rice production over and above that required for general household subsistence). 2) Timor-Leste’s current irrigation strategy has not and will not generate acceptable returns on investment in the sector. Investment costs are very high and marginal rates of return are low, due to very low yields and cropping intensities, and low farm-gate prices. Hence, focusing exclusively on investments in irrigation hardware (river diversion weirs) and not on investments in complementary software (farmer services, production inputs and market support) is unsustainable as it will not facilitate the production of a sufficiently large volume of rice to justify the large investments in physical infrastructure, nor will it result in reduced dependency on imported rice to feed the nation. 3) It is much cheaper to import rice (at an average cost of US$660 per metric ton) than to grow rice ($1,000 per metric ton), and there are few incentives for farmers to increase domestic production16. In addition, sectoral policies, such as the subsidization of rice for consumption, conflict with sectoral support initiatives that aim to increase the volume of domestic rice production. 4) The MAFF’s current and planned budgets for the operations and maintenance of irrigation schemes are much smaller than those needed to maintain and operate the asset stock adequately. The MAFF annual budget just for the maintenance of irrigation systems will need to increase to approximately US$16.6 million by 2020, up from US$2.0 million in 2013, and an annual operational budget of approximately US$21.2 million by 2020. 5) The current strategy for the development of irrigation systems has not been guided by these early experiences. Timor-Leste’s irrigation strategy continues to be based on the rehabilitation of large, damaged irrigation schemes with little Government support for two essential and complementary packages, consisting of farmer support (production inputs and training) and marketing support (public sector rice purchases). 6) Current irrigation planning has not considered the impact of climate change and land degradation on sustainable supplies of irrigation water which has resulted in increased seasonal flooding and reduced basal stream flows to the point where only one crop of rice can be grown each year in some areas. Furthermore, climate change has not been factored into the economic assessments on which the irrigation strategy is based. 7) The current WBRD irrigation strategy is very expensive to implement, with associated construction costs of around US$10,000 per hectare and maintenance costs of approximately US$250 per hectare per year. In addition, it neglects the needs of non-rice growing families.

The WB review found that in the period from 2003 to 2013, US$82 million had been invested by donor and government in the rehabilitation of a number of large irrigation schemes, but only resulted in modest increases in levels of rice production, thus confirming the previously predicted

16 See also: Young, Philip. 2013. Impact of Rice Imports on Rice Production in Timor-Leste. Commissioned Study for the Seeds of Life program, Ministry of Agriculture and Fisheries, Dili, Timor-Leste.

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I negative EIRRs. The review found that only small community based irrigation schemes have generated acceptable EIRRs, suggesting that the irrigation strategy to support increased rice production is best achieved through these small community-based schemes. It recommends that the more cost-effective irrigation strategy would involve the use of TWSPS to supply supplementary wet and dry irrigation season water, together with the implementation of the current river WBRD irrigation strategy. A Seeds of Life review found that the proposed use of river diversion irrigation schemes will cost about $38.40 million per year ($480Mt) more than an alternative approach based on tube-wells and the use of small pumps, plus more intensive use of production inputs and marketing services. Seeds of Life Review also concluded that the economic cost of growing rice in Timor-Leste would be less than the cost of importing rice; about $440/Mt compared with $660/Mt using TWSPs systems, and by using an intensive “rice- bowl” approach to irrigated rice production, rather than the current scattered “every district must have irrigation approach” would also reduce the cost of growing irrigated rice.

Table 3-2: MAFF’s Irrigation Development Plans and Required Maintenance and operations Budget (2013 – 2020)

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Table 3-3: Plans for Irrigation Development – Areas to be irrigated (ha)

Based on these conclusions, the WB review recommended that the strategy for the development of the irrigation sector into the future should be based on the following steps:

1) The development, funding, implementation, and monitoring of the impact of improved software packages for selected existing WBRD systems;

2) The introduction and testing of TWSP irrigation systems in selected non-irrigated areas, with measures to monitor outcomes and impacts;

3) The introduction of TWSP systems into existing WBRD systems following testing and a positive determination regarding the TWSP system’s technical, financial and economic viability, especially for dry season crop production; and

4) Following the development of rice markets and domestic rice price increases, together with increases in the level of production of non-rice crops, the introduction of an irrigation service fee, tested for welfare effects, to recover some of MAFF’s irrigation operations and maintenance costs.

The WB review findings also confirm that irrigation infrastructure development strategy should consider the impact of climate change and land degradation on sustainable supplies of irrigation water to reduce seasonal flooding and increase stream base flows to increase productivity. It also needs to factor climate change into the economic assessments on which the irrigation strategy is based.

Roads

The Roads for Development Program (R4D) is the leading rural roads program in Timor-Leste, supporting the development of the rural roads sector in the country. R4D is aligned with the Government of Timor-Leste’s Strategic Development Plan 2011- 2030 and the Programs of the Constitutional Government. R4D is implemented by the Government of Timor-Leste (GoTL) through the National Directorate of Roads, Bridges and Flood Control (DRBFC) in the Ministry of Public Works, Transport and Communications (MPWTC).

The overall goal of the program is that women and men in rural Timor-Leste are deriving social and economic benefits from improved road access. The first Phase of the Program from March 2012 to March 2017 was co-funded by Governments of Australia (GoA) with a contribution of AUD 36 million for capital investments and technical assistance provided by the International Labour Organization (ILO), whilst Government of Timor-Leste (GoTL) contributed USD 20 million for physical road works and the provision of resources for staffing and operational costs.

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A total of 138 km of core rural roads have been rehabilitated by R4D. Continuous routine maintenance systems have also been established with approximately 400 km of rural roads being maintained using trained Community Maintenance Groups. A 5-year (2016 - 2020) Rural Roads Master Plan and Investment Strategy (RRMPIS) was developed by R4D to provide a framework for the development of the rural roads sector in Timor-Leste.

During phase I the program included the development of systems and standards for planning, delivering and monitoring investments in the rural road sector in Timor-Leste. Comprehensive social and environmental safeguards frameworks were also developed and operationalized.

During phase I training was provided to 882 staff of contractors and 345 Government staff. Training was provided on planning, procurement, implementation and management aspects of rural roads rehabilitation and maintenance works.

The R4D program also contributed to key socio-economic benefits to rural communities in Timor- Leste. Rehabilitation and routine maintenance projects created short term employment opportunities for local labour generating approximately 611,000 labour days of work with 25 percent of these days for women.

Impact studies conducted during Phase I found that following rehabilitation the roads not only had year-round motorable access, but that travel times had been reduced by 50 percent. Access to services also improved along rehabilitated roads, including 24-hour ambulance service and mobile health services.

Agreements have been signed for the implementation of a 4-year Phase 2 from 1 April 2017 to 31 March 2021. The Government of Australia will continue to support the technical assistance provided by the ILO, but all physical works will be funded by the Government of Timor-Leste.

The name “R4D” will now be used to refer to the program implementing physical works within the Ministry, while the ILO technical assistance team will be referred to as the Roads for Development Support Program or “R4D-SP”. While the technical support provided by the ILO technical assistance team during Phase I supplemented MPWTC-DRBFC’s implementation capacity, support provided by R4D-SP team during R4D Phase II will ensure a gradual transfer of rural roads implementation responsibility to the MPWTC–DRBFC. Technical assistance provided by R4D-SP team will focus on capacity development of government and private sector stakeholders.

3.5 Gender issues and vulnerability of other social groups (ethnic minorities)

Women play an important role in Timor-Leste’s rural communities, in particular, in agriculture as cultivators, laborers and family workers. However, women face significant barriers and inequalities in terms of access to and control over resources such as land, capital and credit as well as access to agricultural inputs and technology, training, information and marketing services to enable full participation in social and economic life in rural communities. Women and girls in Timor-Leste are particularly vulnerable to food insecurity and consequently they suffer from malnutrition which leads to high rate of maternal, infant and child mortality (Seeds of Life III, 2010). Women’s ability to attain food security through higher agricultural productivity is disproportionally affected by their low social empowerment, weak community influence and lack of control over and access to income, resource and information (Seeds of Life III, 2010) as well as isolation due to the lack of mobility and basic infrastructure. Eliminating gender gaps in rural communities is thus paramount to achieving productive rural communities in Timor Leste.

While considerable progress has already been made in addressing inequalities through legislation, policy development, institutional mechanisms, and raised public awareness since 2002, the

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I strategic national development plan recognizes that much more remains to be done. Some of the challenges or women, particularly rural women, are as follows:

Causes of Gender Inequality in Timor-Leste

Timor-Leste is a patriarchal society in which social norms and cultural values influence gender roles. Men are responsible for household decision making and are major income earners in the formal economy. However, in most rural households, women also share the role of providing for their families through their contributions to agriculture, fisheries, and raising livestock, in addition to their traditional raring child and home keeping responsibilities.

Religious and cultural values reinforce male authority and restrict the choices available to women and girls. Cultural practices that perpetuate gender inequality have included polygamy and bride price, as well as customary principles relating to property rights, inheritance, and succession to traditional offices. Conservative religious attitudes about gender roles and reproductive health, has resulted in limited use of contraceptive methods.

There is discrimination, particularly against women, in the economic, social, political, and legal arenas and a lack of mobility, particularly in rural areas prevents women from having access to information including informal information networks information networks.

Along with high fertility, limited access to health services, safe water, and improved sanitation facilities increase the risk of maternal and child mortality.

Hunger and poor nutrition is a serious public health concern, with 27% of women aged 15–49 being malnourished. Malnourished women have a greater risk of obstructed labour, of dying from postpartum haemorrhage, and of experiencing illness. In 2009–2010, more than half of Timorese children (58%) suffered from chronic malnutrition. There is no significant difference in malnutrition between girls and boys, but malnutrition is much higher among children in rural than urban areas.

Lack of access to clean drinking water and appropriate sanitation remains a health risk, especially in rural areas: 75% of rural households have poor or no sanitation facilities and 43% continue to rely on unimproved sources of water.

Women’s access to education, economic opportunity, and decision making

The Law on the Election of the National Parliament ensures that 1 in every 3 candidates is a woman, thus ensuring women’s representation in politics. However, this does not guarantee their political influence. Women’s share of decision-making roles at the highest levels of government— as ministers, vice ministers, and secretaries of state rose narrowly from 13% in 2007 to 18% in 2012.

While women are achieving great equity at the national level, they have almost no voice at the local level, where decisions of the greatest relevance to rural women are made. Almost all of the 442 suco (village) and 2,336 aldeia (hamlet) chiefs are men (98%) and there has been little change over the last decade.

Women’s share of managerial jobs across both the public and private sectors is low. Only 16% of public service directors and chiefs are women (2013), while in the private sector 29% of chief executives and directors are women.

In rural areas, work to produce food for household consumption and unpaid care work in the home—the types of work typically done by women—are not counted as employment. Excluding

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I these forms of work, gender gaps in labour force participation are significant: 50% of men are classified as being in the labour force (or economically active) compared with only 24.6% of women.

Women are more likely than men to be in vulnerable employment, which tends to lack stable income and benefits. This is particularly so for rural women: 87% of working rural women are in vulnerable jobs compared with 54% of urban women. The rate is also high among rural men (78%) compared with urban men (37%).

The distribution of employed women and men by industry indicates that other than the primary industry, women are concentrated in wholesale and retail trades and in education, health, arts, and others, which is a broader variety of industries than men are engaged with.

Gender segregation is also found in technical and vocational training programs attended by women and men. The majority of women (56%) tend to enrol in administration, finance, and information technology training programs, whereas men are enrolled in more technical programs such as construction and auto-mechanical skills training.

Access to financial services is crucial for economic empowerment, especially for women, who tend to have less access and control over significant assets. Improving banking services and microfinance programs, as well as cash transfers, can play an important role in helping women generate income and manage financial resources while contributing to economic development. Land legislation remains unresolved, but new laws have been drafted that intend to promote gender equality in land ownership.

Hence, pronounced gender discrimination largely remains a problem in Timor-Leste, with women sparsely involved in decision-making groups and largely found in the bottom layers of informal sectors. GoTL has taken a firm position to eradicate gender inequalities, having acceded to the Convention on the Elimination of All Forms of Discrimination against Women (CEDAW) and gender equality written into Timor-Leste’s constitution. Having pledged to pursue gender mainstreaming in national programmes, the government has established the office of the Secretary of State to encourage gender equality in ministries and is seeking to achieve 30% of women representation in key decision-making groups.

Under the Local Government Support Programme (LGSP), women have been encouraged to get involved in district assemblies as well as subdistrict assemblies and committees, yet their status and standing pales sharply in comparison with men. This is further exacerbated by an inability to convey their thoughts appropriately, caused by inexperience, traditional views on women’s roles and meetings conducted at faraway places. LGSP lacks a plan for gender mainstreaming, which does nothing about discrimination due to gender and highlights why gender issues are not brought up in major policy and legislative documents.

The full Gender Assessment and Action Plan is provided in Annex XIII(c) of the funding proposal.

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4. STATUS OF CURRENT GOVERNMENT POLICIES, PROGRAMMES AND INVESTMENTS TO ADDRESS INFRASTRUCTURE DEFICIENCIES AND COMMUNITY RESILIENCE;

4.1 INDC (relevant priorities)

According to Timor Leste’s INDC priority adaptation measures will be focused on reducing adverse effects of climate change, promote sustainable development and reduce poverty, by employing strategies and plans across all sectors. Priority adaptation measures include:

Adaptation measures will be focused on reducing the adverse effects of climate change, promote sustainable development and reduce poverty. These measures will build on existing strategies and plans across all sectors within Timor-Leste including the National Priorities process. Priority adaptation measures proposed by Timor-Leste are:

Food Security: Reduce vulnerability of farmers and pastoralists to increased drought and flood events by improving their capacity to plan for and respond to future climatic conditions and improve national food production. • Develop integrated agroforestry and watershed management including climate change dimensions. • Based on existing national action plans on sustainable land management, implement integrated, sustainable land management promoting fixed/permanent agriculture, reduced burning, reduced erosion, and increased soil fertility. • Reforestation of degraded land to prevent landslides and provide a sustainable fuel wood source in priority areas with high vulnerability to climate-related risks. • Improve physical infrastructure/civil engineering and natural vegetation methods to prevent landslides in hill sites, roads and river banks. • Education and awareness and conduct a pilot demonstration on sustainable agriculture and forest management that increases resilience and reduces climate-related impacts of shifting cultivation and unsustainable upland farming practices.

Water Resources: Promote Integrated Water Resource Management (IWRM) to guarantee

• Build climate proofed and environmentally sustainable infrastructure to protect water sources (springs, streams, wells, etc.) to provide safe water access for food production, sanitary uses, ecosystems and industry development. • water supplies during climate change extreme event periods. • Enhance government and community strategies to respond to drought exacerbated by climate change. • Create and enhance water harvesting model (capture and storage), water distribution system and management system at all levels to avoid water shortages due to climate change. • Control of quantity of water use by industry, and water pollution control standardization including coffee processing waste management in a climate change context.

Natural Disasters: Improve institutional and staff capacity in the disaster sector in relation to climate change induced disasters. • Establish early warning systems in areas identified as vulnerable to disasters such as floods and storms. • Integrate of climate risk information into traditional disaster risk reduction and management.

Forests, Biodiversity and Coastal Ecosystems Resilience:

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• Maintain mangrove plantations and promote awareness raising to protect coastal ecosystems from impacts of sea level rise. • Include ecosystem management in national planning to develop sustainable, ongoing programme, nurseries and community awareness development - 1st year assessment, 2nd year plan, 3rd year implementation and maintenance.

Physical Infrastructure: Improve regulations and standards for climate-resilient infrastructure. • Review existing laws, regulations and standards to enhance CC-resilience of critical infrastructure. • Pass new legislation to strengthen and guarantee national development through improved regulation, quality of materials, adapted building codes and practices and law enforcement.

National Institutional Capacity Development for Climate Change: • Strengthen the mandate of the cross-sectoral national climate change team to improve coordination and engagement. • Establish a Climate Change Unit with necessary staffing and budget to engage in and support national policy development and programming activities. • Capacity development support for key non-governmental institutions in low emissions and climate resilient development planning, including national NGOs and research/educational institutions. • Develop a national climate change strategy and action plan. • Promote sub-national capacity development for improved adaptation planning and implementation. • Strengthen national hydro-meteorological department to collect, compile, analyze and disseminate climate-related data.

4.2 NAPA

The Government of Timor-Leste has proposed nine programs under the NAPA (National Adaptation Plan of Action-2010) which cover all the above key adaptation actions. The nine programs are as follows: 1. Building resilience of rural livelihoods to ensure national food security. 2. Promotion of Integrated Water Resource Management (IWRM) to guarantee water access to people in the context of increasing climate risks. 3. Enhancing capacity of the health sector to anticipate and respond to changes and reduce the vulnerability of populations at risk from expansion of climate related diseases. 4. Improving institutional, human resource and information management capacity in the disaster management sector in relation to climate change induced risks at national, district and community levels. 5. Restoration and conservation of mangrove ecosystems and awareness raising to protect coastal ecosystems exposed to sea level rises. 6. Improved strategic planning, institutional frameworks and methodologies to promote sustainable, integrated livestock production under changing climate conditions. 7. Review and revise legislation, regulations and standards to enhance climate change resilient infrastructure. 8. Support to the ambitious national poverty reduction target (Timor-Leste Strategic Development Plan 2011-2030) in relation to the expected increased storm intensity at sea by improving capacity to forecast and adapt offshore oil and gas infrastructure to withstand strong storms and waves. 9. National Institutional Capacity Development to build and enhance Timor-Leste’s capacity to coordinate and integrate climate change into strategic planning in moving towards sustainable development and poverty reduction.

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4.3 Strategic Development Plan 2011-2030 (SDP):

The SDP emphasizes infrastructure development and recognizes infrastructures as one of the three pillars of the strategic and sustainable development vision of the country. Though there is no explicit mention of climate proofing the infrastructures, the SDP highlights the need to build infrastructure such as roads and bridges which have better designs and engineering considerations that can withstand the impacts of landslides and erosions. SDP also highlights the need to cut down on the maintenance costs, particularly emergency repair costs.

SDP proposes considering inclusions of drainage in the construction of roads and bridges to make these infrastructures resilient to climate risks. Moreover, the SDP identifies climate risk zoning and environmental and climate risk sensitivities as the key aspects to be considered for the National Planning Framework.

Deficiency: • “The current National Strategic Development Plan for Timor-Leste (2011 to 2030) does not specifically identify disaster risk management as a theme. However, if the protection of strategic development goals is a target, then the integration of disaster risk reduction into actions aimed at achieving those goals must also be a major priority.”17 • Although implied, there is no clear mention of the need to climate proof or the benefits of doing so to reduce the high maintenance costs (which are not explicitly considered in the SDP). • SDP mentions that the priorities and programmes for development of road infrastructures and drainages will be detailed in the respective master plans. However, there is no linkage between the need to development of the “sustainable” infrastructures to the climate change priorities and local level planning and budgeting.

Other deficiencies the SDP have already been highlighted in earlier discussions on specific infrastructure development plans.

4.4 Other government strategies and policies

This section discusses the institutional arrangements for DRR and CCA and relevant policies as they relate to climate resilience of communities and infrastructure.

4.4.1 Environmental Basic Law, 2011 Provides the framework for environmental policy and the guiding principles for the conservation and protection of the environment and for the preservation and sustainable use of natural resources in order to promote the quality of life of the country's citizens.

The Environmental Basic Law under Article 34 explicitly mentions Climate Change. Article 34 states that

“the State shall implement the measures necessary for climate change adaptation and mitigation in terms of reducing greenhouse gas emissions into the atmosphere and/or their removal by sinks and minimizing the negative effects of the impacts of climate change on biophysical and socioeconomic systems”.

Though there is no direct mention of the climate change impacts and interventions directly contributing to climate change adaptation or mitigation, the Environment Basic Law has priorities such as sustainable natural resource management, prevention of degradation of forest and land,

17 Draft DRM Policy

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I sustainable management of water resources which contribute to the climate change adaptation measures. In addition, the Environmental Basic Law prescribes “strategic environmental assessment identifying, describing and assessing any significant effects on the environment and ensuring the integration of environmental concerns into the decision-making procedure”.

The Law mandates environment sector and hence the law to have sectoral considerations, particularly with land use, energy, agriculture, industries, water resources, forest, transport, fisheries, telecommunication and tourism.

Similar to the provisions made in the Draft Revised DRM Policy and Draft National Climate Change Policy, Environmental Basic Law clearly indicates the need for Environmental Fund to ensure routine and adequate financing for conservation, protection and management of the environment.

The other noteworthy aspects of Environmental Basic Law include introduction of economic instruments, environmental accounting system and provision and access to environmental information.

4.4.2 National DRM Policy (draft) Guided by the SDP vision, the Ministry of Social Solidarity was established as a focal entity to manage and reduce the disaster risks.

One of the mandates of the National Disaster Management Directorate is to “integrate climate change into all disaster policies, programs and management activities”. And by the virtue of the nature of DRM, climate change and climate induced disasters become an integral part of the DRM approaches and interventions. Hence, among all the policies and plans, the one on DRM is expected to have close correlation with the climate change.

In this regard, the Draft DRM Policy complements the National Action Plan for Adaptation (NAPA), developed in 2010 and, in the implementation of DRM actions, will ensure consistency with the NAPA through supporting:

• The development and implementation of immediate and urgent project based activities to adapt to climate change and climate variability; • Increased awareness of climate change impacts and adaptation activities in communities, civil society and government; and • Contributing to a road map for the State Secretariat for Environment to follow in working across all climate change vulnerable sectors to assist the integration of adaptation concerns into policies, strategies, programmes and activities.

The Draft DRM Policy underscores the need for robust, systematic and reliable climate data to make informed decisions on DRM and the linkages between the climate change adaptation measures and DRM measures.

The alignment and complementarity with climate change actions and priorities are made visible through the objectives and priorities in the DRM Policy, such as:

• DRM Policy will “create an integrated national capacity to identify, assess and monitor disaster risks (including hazards, vulnerabilities, exposure levels and economic effects together with prevailing capacities), including the effects of climate change”. • DRM Policy will “promote development planning and programming into which disaster risk management is integrated along with climate change adaptation.

At the institutional level, the DRM Policy recognizes the need for harmonizing the sectoral priorities and more so in respect of climate change adaptation and mitigation. The Policy recommends

Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I establishment of inter-sectoral, inter-ministerial commission for DRM in which the climate change related issues are proposed to be led by the MCIE. For better coordination and avoiding any overlaps, the Policy clearly mentions about the need for a “Climate Change Adaptation and Disaster Risk Management Task Force to enable joint actions to be taken by the climate change functionaries of the Climate Change Directorate in the Ministry of Commerce, Industry and Environment and representatives from the NDMD. It will be the responsibility of the Task Force to develop content for the DRM and Climate Change Adaptation agendas that seeks to maximise the full potential of both institutions”.

The current draft DRM policy focuses on “implementing a programme aimed at the reduction and/or elimination of these risks over time through actions that are part of development planning and programming, while at the same time maintaining a readiness through adequate preparedness, enabling a timely and effective response when disasters occur. The policy further recommends that the programme is developed taking account of the limitations on resources and capacities availability and is implemented in a cost-effective way to ensure adequate returns on investments.”

To ensure that the disaster risk management aspects are well integrated into different levels of planning, budgeting and execution of local and national development, DRM policy proposes key areas of intervention including a) Risk assessment and identification; Preparedness and Response Planning; and c) DRM communication.

Proposed areas of intervention under Risk Assessment and Identification are • improved risk assessment and mapping, • access to assessment data to all stakeholders in disaster risk management, • comprehensive disaster Damage and loss data management to provide tools for analysis, planning and programming alongside risk assessment

DRM Policy acknowledges that bottom up DRM planning and preparedness is equally important as the transboundary (across the administrative boundaries of sucos and APs) coordination and planning.

“It is clear that disasters do not respect administrative boundaries and therefore it is important that preparedness plans, particularly at the national level, provide for the necessary coordination that may be required if a disaster affects, for example, more than one municipality. One way of ensuring that this overlap of administrative boundaries is addressed is through the use of the declaration of disaster whereby a senior political official (often the Prime Minister or Deputy Prime Minister) can declare a state of disaster, such a declaration initiating access to a wider set of resources and capacities than would be appropriate for a disaster situation contained within the administrative boundaries of just one municipality. An official declaration of disaster can also identify the rights of those affected and those who are responding, including volunteers, as well as the roles of elements such as the private sector in assisting the operation.”

Proposed interventions under the DRM Preparedness catering to mitigation of climate risks are: • Comprehensive End-to-end Multi-Hazard Early Warning, wherever feasible, covering hazard identification, information generation, analysis, dissemination, communication and response planning and implementation. Early warning will be as community-based as possible and involve the dissemination of information that leads to decision-making and action. However, there must be the full involvement of all levels, national to local, to ensure effective communication. • Preparedness Plans at Both National and Sub-National Levels, particularly related to areas of high disaster risk, indicating the mechanisms for readiness in case of disaster impact.

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• Contingency Plans for Different Types of Hazard, Especially in Areas of High Disaster Risk, these contingency plans covering specific response actions related to different hazards, focusing on municipalities and below. • Standard Operating Procedures, which detail the roles and responsibilities of individuals and organisations in preparedness and response as well as coordination arrangements. • Needs, Damage and Loss Assessment Procedures and Formats, to be conducted after disaster impact through the creation of relevant assessment formats and templates.

Similarly, the key proposed interventions under Disaster Risk Reduction priorities are: • Integration of Disaster Risk Reduction into Development Planning and Programming. Even though disaster risk management is not a themed priority in the National Strategic Development Plan for Timor-Leste (2011 to 2030), every effort will be made to ensure that mechanisms are created to enable this to happen both at the national and the local levels. • Development of Community Resilience in the Face of Disaster Risks a High Priority. The more at-risk communities can identify and address the disaster risks that they must face the more effective disaster risk management programming will be. • Opportunities in Development Programming to Protect Lifelines, Infrastructure and Public Utilities that are in areas at risk from disasters that might be triggered by natural hazards - roads and bridges, electricity and water supplies, schools and health facilities.

Considering the fact that the proposed DRM Policy proposes a more holistic approach to disaster risk management by integrating climate resilience into the development and planning processes, the policy recommends revising the current institutional mandates of NDMD. It suggests that:

• “fundamentally, the names of the key institutions should be changed from covering "Disaster Management" to covering "Disaster Risk Management”. Thus, the existing National Disaster Management Directorate should be changed to the National Disaster Risk Management Directorate (NDRMD) to reflect the focus of the national programme.” • “The government of Timor-Leste should take steps to establish a Climate Change Adaptation and Disaster Risk Management Task Force to enable joint actions to be taken by the climate change functionaries of the Climate Change Directorate in the Ministry of Commerce, Industry and Environment and representatives from the NDMD. It will be the responsibility of the Task Force to develop content for the DRM and Climate Change Adaptation agendas that seeks to maximise the full potential of both institutions. Joint action will utilise the resources available to both institutions and will promote the avoidance of duplication.”

Deficiencies: • Though DRM Policy tries to integrate climate change adaptation and links DRM to development, the policy does not adequately address the important aspects of mainstreaming climate resilience and disaster risk reduction into the development plans. • Institutional arrangement to ensure bottom up planning is not addressed adequately. • Does not address the need and importance of DRM financing to facilitate integration of preparedness into sectoral priorities. • Does not mention the climate risk land use mapping and its importance in DRR • Does not make strong linkage between the L&D database and the informed and evidence based DRR and DRM • There are not strong linkages drawn between DRR as a concept with the sectoral priorities and sectoral policies and programmes.

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• DRM Policy puts emphasis on clarifying the concepts and ideas rather than giving policy guidance on how to set DRR and DRM priorities and how to mainstream DRR and DRM into the development agenda. • Sustainable development and livelihood aspects seem to be missing from the policy purview.

4.4.3 DRM Law (draft): The objectives of disaster risk management are to: 5. Prevent the risk of disasters and their respective occurrence; 6. Reduce the risk of disasters and mitigate their effects, in the event of disaster occurrence; 7. Rescue and assist affected people; 8. Protect public and private property; 9. Support the restoration of normality in the lives of people affected by disasters.

The DRM Law details the institutional arrangements and other logistical aspects of DRM. With regards to the DRM priorities on the technical front, it identifies the need to conduct climate risk assessments, integration of DRM into the municipal level planning process, communication and inter-ministerial coordination mechanisms.

Under Article 32-Development Programmes and Plans, the DRM law spells out the means of integrating DRM into the municipal planning processes as follows:

1. Development plans and programs should integrate the disaster risk prevention, namely forecasting, realistically, the risk of current disasters and ensuring that actions, plans and development projects do not generate disaster risks in the future. 2. In relation to the preceding number, the Municipal Planning Agencies, are responsible for collecting data related to the needs of communities, in particular concerning the risks of disasters detected in order to prepare local development plans and projects based on disaster risk management, in addition to ensuring that the proposed local development plans and projects do not create or exacerbate future disaster risks, including risks arising from climate change. 3. Municipal Planning Agencies should plan the concentration of activities and population centers in low disaster risk areas, construction in areas not susceptible to flooding or other locally detected disaster risks and development activities that do not exacerbate the risks of identified disasters. 4. The planning and construction of vital supply lines, namely the supply of water and electricity as well as the construction of major roads and public buildings, including schools and hospitals, should ensure disaster risks are identified to mitigate any damage that may result from the occurrence of disasters.

Other Articles dedicated to technical aspects include article on Early Warning, Preparation of Disaster Preparedness Plan, Disaster Response Plan, and Recovery.

Deficiencies: • The DRM Law is not guided by the principles of integrating DRM and DRR interventions into the national and local level planning and programming. • Though a separate article is dedicated for the DRM and Development Plans, there is no linkages drawn between the municipal development plans and the disaster preparedness plans and how these planning processes need to be evolve in a coordinated manner at the national as well as sub-national levels

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• The Law does not emphasize the need for database management systems and the institutional roles and responsibilities on managing the database. It only mentions risk assessments. • The Law does not spell out the need for budgetary allocations in the sectoral annual plans to ensure that the Articles outlining DRR can be implemented.

The core principles of current Community-Based DRM (CBDRM) include community participation, priority for vulnerable people, consideration for indigenous knowledge and above all integration of DRM into the local development planning process and multi-sectoral and multi-disciplinary approach.

CBDRM Pilot Project is centred around the community – and the entire project cycle is driven by the community members. In the course of planning, budgeting and implementation, the level of integration of DRM and CC into the sectors is determined by the nature of selected intervention. The selected sucos (26 sucos in the phase 1) prepare Mid-term (spanning 3 years) and annual plans. The plans thus prepared consist of a) risk sensitive spatial planning and b) socio-economic, environmental issues and structural issues of the selected sucos. These mid-term plans function as the Master Plan for these sucos and become integral part of the climate and DRM responsive PNDS.

Integration of DRM and CC is ensured as an integral part of the PNDS preparation process. According to the manual, sectoral authorities and non-government partners need to be identified depending upon the selected project interventions and adequately consulted. Under the provisions outlined under the Integrated Planning and Partnerships, emphasis is given for the integration of sectoral programmes and priorities into the Suco planning process under the active leadership of the Chefe Suco. To strengthen the integration and ensure actualization of the integrated plans, the manual suggests signing an MoU between the community and the concerned institution(s). The integration process includes the construction of climate resilient infrastructures by integrating DRM and CCA measures into the structural projects.

4.4.4 National Climate Change Policy (draft) National Climate Change Policy intends to provide policy guidance to mainstream climate change into the development policies and prioritizing climate resilience in the development plans.

An important aspect of the policy is that it emphasizes the need for mandatory budgetary allocations in the annual budget cycle of the line ministries to ensure climate resilient development.

The Policy has specific sections on Infrastructure, Loss and Damage and Disaster Risk Management and Decentralization to emphasize the integration of climate resilience into different levels of governance as illustrated below:

Climate Resilient Infrastructure 1. Promote climate resilience and climate proofing approaches and concepts in the small, medium and large scale infrastructures. 2. Identify and map all the appropriate and effective climate proofing measures that have been practiced in the country and in the region. 3. Commission a comprehensive Cost-Benefit Analysis to assess the benefits and losses incurred by the climate and climate induced disasters and integrating climate resilient options into the infrastructure development designs.

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4. Integrate climate resilience aspects into the Environmental Impact Assessment (EIA) regulations and introduce provisions to make the EIA mandatory for all the infrastructure development activities. 5. Develop Climate Risk Zone Map disaggregated by key climate risks to guide the infrastructure development projects. 6. Identify the most climate vulnerable communities and the underlying factors contributing to their vulnerability and recommend appropriate infrastructure development priorities such as access to water, irrigation canals, road, health facilities among others to help enhance community resilience. 7. Develop the capacity of technical teams responsible for designing, approving, commissioning and implementing infrastructure development projects in the government as well as private sector to integrate climate resilience and environmentally friendly options into their work. 8. Integrate climate resilience into the existing monitoring and evaluation templates used by the government authorities such as Ministry of Public works, Transport and Communication.

Loss and Damage 1. Collaborate with existing vulnerability assessments, natural disaster risk assessments and complement the information on existing and potential loss and damage incurred by the climate change disaggregated by type of loss and damage, sector and region. 2. Prepare a repository of data and information on the existing and potential loss and damage disaggregated by sector, magnitude, gender, and geography. 3. Establish a Task Force led by the Multi-Stakeholder Committee for Climate Change specifically for Loss and Damage.

Disaster Risk Management 1. Make provisions of updating climate risks and vulnerability zones in collaboration with the NDMD to prepare risk sensitive land use planning 2. Implement Risk Sensitive Land use Plan to ensure that the human settlements, and infrastructures are not built in the climate risk or disaster prone areas. 3. Collaborate with Ministry of Social Solidarity to develop local level disaster risk reduction action plan that can be used to prioritize and implement disaster risk management interventions at the community level. 4. Integrate disaster risk management aspects into the local development plans and budget allocation guidelines. 5. Coordinate with national and sub-national level disaster operating units and centres to help make informed decisions. 6. Integrate early warning mechanisms and early recovery mechanisms into the livelihood enhancement programmes such that there is an integrated approach to managing disaster risks at the community level. 7. Create platform for better coordination and collaboration between climate change adaptation and disaster risk management interventions. 8. Make provisions of community shelters to evacuate people at risk during the event of climate induced disasters. 9. Promote integrated watershed management aspects, sustainable infrastructure development and community-based approach to disaster risk management.

Access to finance

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1. Collaborate with Ministry of Finance to conduct an assessment to find out the existing public climate expenditure at the national and sub-national level. 2. Prepare a monitoring framework to assess the existing climate financing received and utilized to meet the adaptation priorities identified in the NAPA. 3. Conduct an assessment to identify appropriate climate financing mechanism. 4. Identify medium term and long term climate action plan and climate financing projections. 5. Establish a nationally appropriate climate financing mechanism such as Climate Fund/Trust Fund to mobilize public, private, vertical and bilateral climate funds to finance medium and long term climate action plan. 6. Make provisions to generate climate finance from the carbon trade. 7. Promote carbon offset mechanisms to generate climate fund. 8. Develop climate fiscal framework to promote climate responsive planning, budgeting, expenditure and tracking of public, private, bilateral and multilateral climate funds. 9. Make provisions to plan and allocate at least 70% of the national climate finance for the community based climate resilience and climate-related activities. 4.4.5 National Water Resources Management Policy (Draft, March 2017) The objective of the draft NWRM Policy (2017) is to promote the coordinated planning, development and management and protection of the nation’s water resources, in order to optimize social, economic and cultural benefits without compromising the sustainability of essential water dependent ecosystems and the environmental benefits which those ecosystems provide for people.

The policy envisages that all people will have access to adequate, reliable and sustainable sources of water for their vital human needs and for subsistence farming, that water resources management will be integrated, equitable, sustainable and will optimize the socio-economic and environmental outcomes from water for the benefit of all Timor-Leste’s citizens and that water dependent ecosystems are protected enhanced where they have been degraded.

The GoTL Priorities are: • To make water governance and water resource management integrated, transparent and accountable • To promote water resources management through community participation and access to water • To promote Sustainable Management of Water Resources • To ensure adequate financial resources for effective implementation of water resources management plan • To establish data management systems, monitoring and evaluation mechanisms and knowledge management system for informed planning and decision making

A key guiding principle of the draft policy is the need for adaptive water resource management in to address climate change. It states:

“Adaptive water resources management: there is a need to promote the development of knowledge, flexibility and forward thinking in policies, plans, programs and actions, in order to be able to adapt these when needed in response to new data and information on changes in socio- economic conditions and changes in climate and environmental conditions”

The policy acknowledges the nexus between climate change impacts on water resources and the vulnerability of the water infrastructure. The strategies to adapt to climate change include: • build environmentally sustainable infrastructure to protect water sources, streams and hand dug wells and water boreholes

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• enhance government and community strategies to respond to drought that is exacerbated by climate change • create and enhance water harvesting and storage capabilities and a water distribution and management system that can ameliorate water shortages due to climate change • control water use by industry and commerce and control pollution to protect water resources

In addition to the recommendation on the government mechanisms, the policy also calls for enhancing adaptive capacity and coping mechanisms at the individual level. Some of the ways the Policy recommends enhancing adaptive capacity include:

“the development of adequate monitoring networks, so that data and information are available to facilitate adaptive water resources management and public water supply planning.”

The Policy clearly mandates the need for better data management system in support of making informed decision on the vulnerability of the water resources, public water supply plans and the protection of the investments made on the water resource infrastructure.

Aligned with the overall objective, guiding principles and focus on the climate-resilient water resource management system, the Policy Implementation Priorities in the short and long term have integrated watershed management plans and database management and strong monitoring mechanisms to ensure sustainable water resource management.

In support of the principles and strategies outlined in the Draft NWRM Policy (2017), the GCF project will provide hazard mapping of droughts, floods and all hydrometeorological hazards which impact on water resources at the watershed management level, and will provided the basis for water resources planning in the future. Furthermore, the project is developing climate proofing approaches for designing, constructing and maintaining water infrastructure which will be elaborated in guidance documents and manuals. These activities will therefore directly contribute to the government priorities of safeguarding water resources and water infrastructure.

The project will develop a database (SDI) for all CC, hazard risk and vulnerability data as well as an infrastructure asset management database, of which water infrastructure will be a component, enabling a systematic and portfolio-risk-management approach to management and maintenance of water (and other) infrastructure. This will partially contribute to the database management that the WR policy has prioritized.

4.5 Relevant Forestry Policies and laws

The objectives of the Revised National Forest Policy (Draft, March 2017) are:

• effective protection of the ecological integrity and biological composition of not less than 70 percent of the area of forests by 2030. • to produce 50 percent of the nation’s sawn timber supply from locally grown forest plantations by 2050 for building construction, furniture manufacture and other uses of timber • long-term sustainable conservation of watersheds not later than 2035 in order to maintain and enhance natural water flows, to maintain high water quality and to minimise flooding and the erosion of rock and soil • harmonious and effective participation of forest communities and other private sector groups with the Government by the end of 2025 • development and maintenance of a private sector-based business environment for profitable forest ownership and the management, production, utilisation and marketing of forest products, especially for the alleviation of poverty amongst rural communities.

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• develop managerial, technical and administrative capacity and to maintain and develop forestry sector institutions in order that all forest policy objectives and specific programmes will be effectively designed, implemented, managed, monitored and adapted based on lessons learned from implementation

The Revised Draft National Forest Policy emphasizes the integration of conservation, protection and management of forest resources. Though the linkages have been drawn with allied sectors such as watershed management, agriculture, biodiversity, land use management and cross cutting aspects such as capacity development and climate change, these linkages are not very strong. The Policy Instruments that have been identified to facilitate implementation of the Policy are: • Community Based Management of Forests and Watersheds • Participatory Reforestation and Land Restoration • Forest Conservation and Protection • Market and Enterprise Development • Extension, Training, Research and Information • Incentives, Valuation and Monitoring

Direct reference to climate change is made under the Policy Instrument of the Forest Conservation and Protection and climate change adaptation under the Community based management of forests and watershed, forest resource based market and enterprise development and the participatory reforestation and land restoration. The linkages drawn to the control of land degradation, sustainable land use management, combating desertification, reforestation and climate vulnerability assessment with focus on forest resources and forest management also have strong climate change adaptation and mitigation connections.

The Revised Forest Policy focuses on the forest resources management, but given the strong impact of forest management on climate change and vice versa – climate change adaptation, climate change mitigation, climate finance (carbon sequestration) and the forest based economy have potential to enhance community’s coping mechanism.

In addition, the activities mentioned and the policy instruments identified have cross over to the existing climate change portfolio and the national climate change priorities. The draft National Climate Change Policy has identified Forestry sector as one of the pillar sectors for longer term climate change adaptation and mitigation goals. The priorities and the strategies identified in the draft National Climate Change Policy have been addressed mainstreamed, to some extent, into the Revised Forest Policy.

Moreover, the components of capacity building, monitoring and evaluation of the implementation, incentives and valuation of the sustainable forest management mechanisms are linked to the climate change adaptation. In Timor-Leste, emissions from Forests was 14% in 2010 as per the Initial National Communication. Hence, the measures identified to conserve and protect forest coverage would directly impact the national greenhouse gas emissions and hence will have direct impact on the climate change mitigation measures.

MAF’s Strategic Development Plan 2014-2020 (MAF SDP) was developed based on the priorities for the agriculture, fisheries and forestry sectors outlined in the Timor-Leste National Strategic Development Plan 2011-2030. MAF SDP's main objectives are to: (i) focus on agricultural and rural development which supports small farmers and promotes improved markets in order to reduce poverty; (ii) ensure food and nutrition security, and sovereignty; and (iii) promote economic growth and employment in rural areas, and thus across the nation.

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The Government’s National Priorities for 2017 were announced in July 2016 by the Prime Minister, and include: Agriculture (combating hunger and malnutrition); health; education; water and sanitation; basic infrastructure and the elections. To monitor achievements, the GoTL, adopted the new UN Sustainable Development Goals (SDGs) and has integrated SDG goals, indicators and targets into all Government planning and budgeting for 2017.

MAF commenced in 2015 a review of the National Forest Law with support from the Food and Agriculture Organisation (FAO) and is currently developing a long-term forestry investment plan to diversify from the largely oil-dependent economy, which is a strong signal of the renewed priority being placed in the development of the forestry sector.

Furthermore, in June 2016 the GoTL sent to the National Parliament the draft new Land Law18. While this initiative is commendable, notably given the urgency for the agro-forestry to have a modern legal framework giving more security and ownership to local assets (i.e. land and trees), there are concerns regarding the low level of consultations with rural communities. Customary rights are mentioned in the new proposed Land Law but there is a lack of provision on how communities’ rights will be protected and how to create an enabling environment that would sustain agro-forestry development in the country.

Table 4-1: Extract from the summary of the MAF SDP. Most relevant programmes are highlighted in green

Specific Objectives per Sub program 1.1: To enhance the contribution of 2.1. To develop and implement safety 3.1: To establish a functional, clear and 4.1: To review the organizational structure, agricultural research to sustainable agricultural standards and quality control assurance accountable policy and legislative governance mechanisms and modalities of production, food and nutrition security and across crops, livestock, fisheries, and framework and capacity for policy analysis operation to ensure that MAF and related 5.1: Sustainable natural resources poverty reduction. forestry products and implementation. agencies are functioning as relevant modern management and utilization. 3.2: To ensure coordination and 1.2: To increase farmers’ access to relevant responsibilities are undertaken in a coherent 4.2: To develop and implement a manpower information, knowledge, and technology 2.2: To promote access and use of high manner leading to improved implementation development and capacity strengthening 5.2: Increase the knowledge, protection and through effective, efficient, sustainable and quality inputs, planting, and stocking and management of sector policies and policy strategy and program to enhance the utilization of the bio-diversity within Timor- decentralized extension services. materials, and fishing equipment. programs. productivity of MAF staff. Leste. 3.3: To establish and maintain a functional agricultural statistics system providing 4.3: To develop and implement a 2.3: To promote diversification and value timely & appropriate information to sector knowledge management and communication 5.3: Development and dissemination of 1.3: To reduce losses through improved control addition activities within the sub sectors stakeholders, and assisting with MAF strategy to facilitate effective environmentally friendly agricultural of pests, vectors and disease. along the value chain. planning and management. decisionmaking and accountability. industry practices.

1.4: To develop water resources for 3.4: To develop capacity for improved agricultural production on the basis of 2.4: To provide the necessary rural market decision-making in planning, and budgeting sustainable irrigation, water for livestock and infrastructure including appropriate processes by providing accurate and up-to- 4.4: To develop and implement an M&E 5.4: Promote the conservation of national aquaculture. structures to improve post-harvest losses. date climate information and analysis. strategy. and cultural heritage. 1.5: To increase the use of labor productivity 3.5: To develop the necessary early warning 4.5: To review the HR policy and practices enhancing technologies including appropriate 2.5: To promote collective marketing, and and weather monitoring systems to help to provide the necessary skills and mechanization and other farm management support to Farmer Groups and Farmers’ mitigate the impact of, and adapt to, climate incentives to enhance the performance of related practices. Associations. variability. MAF’s staff. 1.6: Accelerate production of selected strategic enterprises on the basis of specialization and 2.6: To promote private sector engagement 4.6: To develop and implement a agro-zoning. in input supply and product marketing. partnership strategy for MAF 4.7: To develop and implement a resource mobilization strategy to ensure adequate and sustainable funding for MAF.

18 Land Law is a particular issue in Timor Leste which prevents a number of basic and key societal functions to run efficiently. Including designation of protected areas, use of land as collateral for access to finance.

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4.5.1 Agricultural Policy and Strategic Framework (Draft) - Towards Nutrition- Sensitive, Climate Smart Agriculture and Food System The objective of the Draft Agricultural Policy and Strategic Framework is to ensure an overall development of the agricultural sector in Timor-Leste through:

• Improved availability and access to nutritious, diversified foods and food security of the rural population and increased self-reliance and resilience to climate change and natural disasters; • Increased farmers’ linkages to markets opportunities through inclusive and efficient value chain development, income generation, as well as improved community and private sector participation in all sub-sectors; • Increased rural incomes and decent employment especially for the youth; • Gaining revenue from commodity export and by substituting imports. • Sustainable management and use of natural resources including land, forests, marine and biodiversity to provide environmental, social and economic benefits to the Timorese people; • Improved agricultural sector institutional development for an enabling environment and support services.

The policy vision is that by 2030 Timor-Leste will have a climate resilient, sustainable, and prosperous agriculture sector that produces locally grown nutritious foods, eliminates food insecurity and poverty and improves the living standards of the Timorese people.

The agriculture sector is one of the sectors which is most affected by climate change and the sector which more than 70% of the rural population relies upon for subsistence as well as income value. As in most of the developing and least developed countries where the industrial development is limited or negligible, agriculture forms the one of the largest contributors of greenhouse gases. Initial National Communication (INC 2014) has indicated that Agriculture was responsible for 65% of the national GHG emissions in 2010. Though this correlation has not been strongly drawn in the Policy, there are sections that have references and inferences to the climate change.

While addressing the challenges that Agriculture as a sector is facing at the national level, climate change was identified as one of the key factors. Lack of coherence among the policies and the inter-sectoral coordination have also been identified as the challenges in developing agriculture sector. However, in an account of successful stories, climate smart agriculture, agroforestry, water harvesting methods and other smart agriculture techniques have been identified as the underlying contributors.

The Policy makes a visible remark that the government must consider the existing challenges and success stories and accordingly reorient the upcoming Agriculture Policy. In this regard, the Policy indicates that

“The Government will therefore reorient the agricultural and rural development policies that resets incentives and lowers the barriers to the transformation of food and agricultural systems. Particular attention shall be given to supporting low-income smallholder farmers in strengthening their capacity to manage risks and adopt effective climate change adaptation strategies.”

In addition, climate change has been considered as one of the Guiding Principles of the Policy which indicates that climate change has been integrated well into the development of the Policy. The Guiding Principles - Factoring Climate change, resilience and environmental sustainability says that “focusing policy instruments on the sustainability of the use of natural resources (land and soil, water and ecosystems) with the future generation in mind while increasing agricultural production, marketing and other human activities in the agricultural sector.”

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Even though climate change was identified as one of the challenges and one of the guiding principles, the policy interventions and strategies don’t draw much linkage to the climate resilient agricultural practices, and the ways of reducing GHG emissions through implementation of climate smart agriculture.

One of the interesting aspects of the Policy is the list of indicators that would measure the level of penetration and implementation of the Policy. Among other indicators, the Policy mentions ‘access to finance for the farmers and the access to credit at an interest rate lower than 5%’. The other indicator is ‘the development of value chain ensuring that the agricultural development provides market access and ensures that the investments have shorter rate of return’.

Among other key focus areas, the Policy exerts emphasis on the need to have a Land Reform, develop market and create competitive niche for the local products to attract and retain the farmers into the sector and importance of supporting infrastructure such as irrigation.

4.5.2 National Action Programme (NAP) to Combat Desertification The goal of the NAP is to ensure that the management of agricultural, forest and other terrestrial lands of Timor-Leste is done in a sustainable manner to contribute positively to the environmental, economic and social well-being of the nation. The overall objective of the NAP is to lay out priority actions towards controlling factors contributing to and mitigation of the effects of land degradation in Timor-Leste in an integrated manner as pre-requisite for forging sustainable livelihoods of the people of Timor-Leste.

Specific Objectives include:

• Effective implementation of sustainable agriculture and forestry through provision of effective incentive and regulation • Effective water resource management • Expansion in woodland areas to achieve biodiversity conservation and increase carbon storage capacity to help tackle global warming • Sustainable management of the land to maintain its local landscape character and responsive to ecosystem requirements • Restoration of damaged lands and good management of soils, to reduce soil compaction and erosion • Prosperous agriculture and forestry that provide for the nation’s food security and improved nutrition • Self-reliant rural communities through improved productivity, increased income and employment opportunities • Sufficient economic returns of crops to cover investment in sustainable land management • Good understanding of the implications of taking gender issues into consideration to combat land degradation • Better understanding of sustainable land management and its importance to rural economy • Improved quality of life through better environment, availability of high quality, locally produced food and improved access to clean and abundant water

The NAP prioritized the following:

Land degradation prevention through:

• Poverty Alleviation Programmes • Public Education and Awareness • Improvement of the legislative framework and policies for sustainable land management

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Land degradation mitigation through: • Land Degradation Inventory and Monitoring • Monitoring and mitigating the impact of climate variability

NAP to Combat Desertification was developed under one of the three Rio Conventions – UN Convention to Combat Desertification. In this regard, there is correlation with the overall global warming impact, and the strategies and action plan to prevent and mitigate land degradation.

Increasing forest cover and vegetation cover through agriculture, forestry, agro-forestry related programmes is at the core of the NAP. These strategies of preventing and mitigating land degradation contribute to livelihood of the communities and also to the overall economy as well.

Moreover, these practices have direct linkage with the climate change mitigation and adaptation. Under the Land Degradation Mitigation, the NAP explicitly mentions about the role of climate change and need to monitor and mitigate the impact of climate variability. Hence to guard the land degradation preventive measures, mainly the agriculture and forest practices, and also the lives and assets of vulnerable people, the NAP identifies the following as important interventions:

• Establishment of early warning systems for disaster preparedness • Empower local community for disaster management • Carry out targeted research on climate variability related to land degradation • Monitoring the impact of drought and promote research on drought resistant-crops • Develop country’s scientific and technical capacity to assess and monitor the state of • climate induced degradation of the land.

Since NAP crosses over the agriculture and forestry interventions to prevent land degradation, there is an overlap between NAP and the sectoral policies on Agriculture and Forest. Similarly, the interventions and priorities identified by the NAP in relation to mitigating the impact of climate change and variability are closely linked with the disaster risk management rather than climate change adaptation. Considering the fact that underlying driver for deforestation and degradation of forest leading to larger land degradation problem is fuel wood, the NAP puts an emphasis on the need to develop rural renewable energy to cut down dependence on fuelwood. In this regard, the NAP in an implicit way draws linkage with climate change mitigation.

The NAP identifies the National Directorate for Environment as one of the six focal institutions to implement its interventions.

4.5.3 National Biodiversity Strategic Action Plan (NBSAP) The NBSAP envisages that by 2020, Timor-Leste’s biodiversity and ecosystems are conserved and wisely used by all sectors, providing food security and contributing to poverty eradication and improved quality of life of Timorese people.

At the onset, the NBSAP mentions that the Strategy and Action Plan is closely aligned with the NAPA and other aspects of climate change commitments of which Timor-Leste is a party.

Considering that the health and wellbeing of biodiversity is dependent to a large extent on climate change and its adverse or favourable effects, NBSAP gives emphasis and mentions climate change and the importance of mitigating its negative impacts.

NBSAP is valid until 2020 and among its key strategies mentions promotion of climate resilient ecosystems through a better management of protected areas, which will consequently reduce threats to biological diversity.

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Acknowledging the huge challenges and threats facing climate change, NBSAP recommends to adopt “a proactive approach and investments in disaster prevention, mitigation, preparedness and response would reduce disaster risks and contribute to biodiversity conservation”.

Similarly, NBSAP takes an account of the NAPA priority areas and identifies linkages with the relevant sectors which have direct impact on the improvement of biological diversity in Timor-Leste.

In addition to the thematic linkages, NBSAP makes a conscious effort to underscore the priorities related to institutionalization of climate change sector identified in the SDP, for e.g. Centre for Climate Change and Biodiversity.

NBSAP in its medium-term strategy envisions implementation of at least 70% of the activities and programmes identified in the NAPA in 2011.

NBSAP prioritizes Climate Change by identifying climate resilient ecosystems as one of the Priority Strategies.

NBSAP mentions and accounts for the importance for the climate and climate induced disasters related interventions to increase coping capacity such as:

• Adaptation of climate resilient agriculture infrastructures to protect agriculture from fluctuations in rainfall. • Early warning systems and mechanisms of DRR through a better mechanism of losses and damages accounting tools

Considering NBSAP’s focus on biodiversity, some of the sections reiterate the methods, mechanisms and strategies of the sectoral mandate such as forests, agriculture, marine ecosystem, among others.

In the absence of the National Climate Change Policy, NBSAP relates the climate change and its impact to the climate induced disaster risk management.

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5. GOVERNMENT INSTITUTIONAL ARRANGEMENTS AND CAPACITY FOR DRR AND CCA The following institutions have some responsibility for DRR or CCA or for the implementation and maintenance of infrastructure, in particular rural infrastructure.

Table 5-1: Main institutions involved in DRR and CCA

Stakeholder Role in DRR and CCA Ministry of Commerce Industry and o Lead government agency on climate change policy, and Environment, legislation National Directorate for Climate Change Centre for Climate Change and Biodiversity

MSA, National Directorate for Local o Lead agency with responsibility for local governance reform Administration o Lead agency implementing PDIM and PDNS projects o Investment fund release to focus Districts based on approved climate resilient plans; M&E Districts o Liaise with MCIE on embedding climate risk information in infrastructure design o Support standardization of climate resilient designs, evidence- based policy influencing and up-scaling o Organize awareness raising and training events

Ministry of Social Solidarity, National o National Disaster Management Directorate (NDMD) and the Disaster Management Directorate (NDMD) National Disaster Operation Centre (NDOC) are responsible for and the National Disaster Operation providing disaster risk management coordination and technical Centre (NDOC) support to the government and communities in Timor-Leste

MPW, National Directorate for Water o Collaborate on climate resilient design approaches, designs and Resources and BESIK sustainable O&M for rural water, sanitation and hygiene sector o Standardization of designs and climate resilient policy development

MPW, Roads 4 Development o Design of roads, road drainage structures and other related small infrastructure works; o Standardization of designs and climate resilient policy development o Technical capacity development for communities and LAs Municipalities o Implementation of PDIM and PDID projects, responsible for local Development Commissions planning, Strategic Municipality Plans, budgeting and LA staff infrastructure development o Implement municipal investment plan: develop annual climate- resilient investment plans, determine budgets, implement climate resilient small scale infrastructure and ecosystem services o Standardization of infrastructure designs, up-scaling of good practice to whole Municipality Plans and evidence-based policy influencing

Communities and Local decision o Provide local knowledge; support stakeholders acquire adequate makers understanding of local realities and facilitate development of practically feasible solutions

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Ministry of Commerce, Industry and Environment (MCIE)

Three national directorates have been established – National Directorate for Climate Change (NDCC), National Directorate for Planning control and Environmental Impact (NDCPEI), National Directorate of Pollution and Biodiversity (NDPB). NDCC – is mainly focused on international climate change activities, NDCPEI (planning application) and NDPB have input to biodiversity impact assessment of infrastructure projects. The role of MCIE includes the development of methodologies for addressing climate risk in all sectors and collaboration on bioengineering methods. The NDPEI directorate is responsible for EIA – project categorisation and signoff of projects based on successful EIA. MCIE EIA and environmental safeguarding of infrastructure projects. The GEF, GCF and UNFCC focal points and Designated National Authority for Timor Leste also sit with the MCIE.

One role of the NDCC is to attend and cooperate on any regional, international meetings on climate change. To share how they meet COP requirement and challenges, act on Designated National Authority as head of CDM committee (clean development mechanism), Implementing HPMP (Phase out management plan for HFC). Under UNFCC NDCC coordinate with other agencies to prepare NAPA in collaboration with UNDP (GEF). NDCC undertook the Initial National Communication (INC) and is currently undertaking the SNC Project.

Centre for Climate Change and Biodiversity (CCCB)

The CCCB was established by UNTL and MCIE with support from the SSRI Project on behalf of UNDP in 2014 through the provision of technical assistance, equipment, training, and access to experts in climate policy. The Centre is managed by the UNFCCC focal point and UNPD provides a fulltime key technical assistant to the centre.

The work of the CCCB is to build capacity and provide training, expert advice and support to practitioners and policy makers on Climate Change. The Centre is ensuring the sustainability of capacity building in the areas of climate change through the provision of products that enhance the long-term management of climate risk data (data bases have been designed and established to collect, collate and disseminate climate change information). CCCB has created a website and provided access to data and information. CCCB is also sharing skills by sharing lessons learned during training and workshops. CCCB is also involved in public awareness raising and training of staff from other ministries dealing with climate change, including the Ministry of Social Solidarity (responsible for Disaster Risk Reduction (DRR), trained in risk mapping), MSA, and MCIE (NDCC), Ministry of Agriculture and Fisheries, Ministry of Public Works, Transport and Communications, meteorology and physics university departments. The Centre has been an important partner during the process of development of policy for Climate Change Adaptation (CCA) and Climate Change Mitigation undertaken by the SSRI project.

The CCCB has been instrumental in the collection, systematization and dissemination of climate risk information at community level, provision of training to practitioners and policy makers, identification and coordination of climate change related research, and establishment of links to international organisations involved in climate change. In November 2014, the CCA Technical Working Group led by NDCC, MCIE hosted the 1st International conference on Climate Change Adaptation.

One challenge identified by the CCCB head is that cooperation among shareholders is still relatively weak and there is no key focal point from each stakeholder organization/department for involvement in the working group.

Ministry of State Administration

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MSA is responsible for infrastructure at all levels and their main role is to guarantee the local development and good governance through decentralisation of functions. PDIM and PNDS processes are the main mechanisms by which this decentralisation is achieved. Community driven programmes using the PDIM process are therefore of importance to MSA and fully aligned with the strategy of decentralisation for local level rural economic development, and with the Strategic Development Plan 2011-2030 which includes the opening of rural roads to all hamlets, and actively promoting revegetation and reforestation to protect the forests.

MSA recognises the benefits to rural communities of the climate resilient approach to the development of small scale rural infrastructure and sees the sustainability of the approach.

MSA is taking the lead on embedding climate change in infrastructure with the Secretary of state for MSA personally acting as the focal point from MSA to discuss with other line ministries e.g. Ministry of Social Solidarity and Ministry of Agriculture and Fisheries through regular meetings where relevant updates are provided and information shared on planning and implementation policies. MSA is undertaking advocacy for bottom up planning through information sharing from CCCB and other platforms.

Ministry of Social Solidarity – National Disaster Management Directorate

The National Disaster Management Directorate (NDMD) and the National Disaster Operation Centre (NDOC) are organisations within the Ministry of Social Solidarity. NDMD is responsible for providing disaster risk management coordination and technical support to the government and community in Timor-Leste. NDMD has the following responsibilities: • Acting as Timor-Leste’s centre for disaster risk reduction activities and knowledge, collecting information, monitoring overseas developments and proposing developments for incorporation into the national disaster risk reduction system; • Developing strategies in disaster risk reduction including preparedness and response plans and procedures and assisting in district planning; • Establishing and sustaining links to risk assessment and monitoring in the region, and interpreting and providing warning and strategic planning in relation to developments that may affect Timor-Leste; • Acting as the contact point for initial reports of emergencies and disasters in conjunction with the DOC; • Coordinating disaster risk management including scheduling of regular meetings of actors and stakeholders; • Organising and leading multi-sector damage and needs assessment teams during response when necessary; • Developing and conducting public information and awareness programs in cooperation with other relevant agencies; • Developing disaster risk reduction and emergency response training programs in conjunction with relevant partners; • Maintaining and developing a National Disaster Risk Management Information System; • Developing or identifying the sources of baseline data for use in disaster preparedness and response activities; • Maintaining, reviewing and developing the National Disaster Risk Management Policy (NDRMP) and advising on other sector and development policies, strategies and legislation related to disaster risk management; • Administering a national regional strategic stockpile of disaster response assets. The National Disaster Operation Centre (NDOC) was established to function on a 24-hour basis operated by well-trained personnel equipped with communications equipment, a secure power supply and disaster proof structures. The functions of the NDOC are as follows: • Monitor and analyse national and international disaster risk information • Provide Early Warning communications

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• Coordinate and report on multi-sector government and partner operations to assist Timorese communities to effectively prepare for, mitigate, respond to and recover from disaster situations • Provide effective information for the NDMD, Ministry of Social Solidarity, and the InterMinisterial Disaster Management Committee to make informed decisions for the management of disaster and crisis risk management • Coordinate disaster risk management simulated operations and lessons learned exercises on priority and developing risks • Assist in the development of multi-agency standard operating procedures for dealing with all major hazards, risks and disasters • Develop information systems including a national hazard risk atlas, data base and other geographical information systems (GIS) • Develop disaster early warning, evacuation and safety systems, at community, district and national levels (National DRM Policy, 2015)

An important element of the NDOC organisation are the focal points. There is a focal point in every district, and this focal point is in most occasions the first point of contact when disasters occur. Also, the focal point oversees communicating with the NDOC headquarters, coordinating the response and assessing local risks.

National Directorate for Water

The national directorate for water is responsible for policy, planning, execution, organisation and monitoring of all water systems implemented by government and also all government partners. All agencies, NGOs who work on water supply system activities must work directly with the directorate for Water and Sanitation.

Before installation of any water supply system the directorate has two activities that must be implemented regarding community action plan. First, for community action plan related to socialization, consultation at community level, all beneficiary groups must be consulted. Second for community action plan related to conducting survey, design involves technical staff from municipality, facilitator for water and sanitation in Administrative Post and also representatives from the community (male and female). For monitoring and maintenance, the technical staff from municipality and Facilitator for water and sanitation in Administrative post form the GMF (Grupo Maneja Fasilidade/ Group for Maintenance of Facility) are involved. According to the policy for water there are two categories, for urban area responsible for maintenance by technical staff in Municipality and in rural area by the community (GMF). To do the maintenance in rural areas the community must contribute, about 0.50 – 1.00 USD, depending on their capacity and in concordance with the community. Before installation any water supply, technical staff in municipality are engaged in measuring water flow (the water debit, water volume and take GPS point measurements). The National Directorate for Water also provides the Guidelines for GMF.

Department for Watershed Management

The department for watershed management provides three services including management of watersheds; mangrove and coastal areas and water flow services. At the moment, they have agreement (MoU) with the government of Indonesia (Department of Forestry and Industrial Crops) to conduct rapid survey in 3 points watersheds in border (Mota masin in Covalima Municipality, Nunura in Bobonaro Municipality and Tono in Oecussi Municipality). The directorate works closely with donor organisations working on catchment management activities. The permanent nursery in Maubara provides seedlings and distributes to communities for such projects.

The Directorate of National forestry is principal counterpart on implementation of projects involving catchment management agro-forestry and reforestation. The Directorate of National forestry play an important role in watershed management and reforestations in catchment areas in order to

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Ministry of Agriculture, Forestry and Fisheries (MAF)

MAF is the government institution mandated for the development of the main rural sectors and for coordinating rural development. MAF has personnel at all levels ranging from national to local and is working with farmers, other government agencies, the private sector and development partners. MAF, therefore, has established coordinating mechanisms at all levels for harmonizing functions, planning and implementation and for monitoring progress of achievements in rural development.

The organizational structure and governance of the Ministry is stipulated under Decree Law No. 4/2004 on the Structure and Rules of the Ministry of Agriculture, Livestock, Fishery and Forestry. This decree was revised by the enactment of Decree Law No. 18/2008 (19 June 2008). Although the Government has changed from the IV Constitutional Government to the V Constitutional Government, the current structure of MAF remains, based on the Decree Law 18/2008.

The Ministry is currently headed by a Minister and assisted by a Vice Minister, a Secretary of State for Forestry, a Secretary of State for Fisheries, and a Secretary of State for Livestock.

The Director General (DG) is supported by 12 National Directorates and 13 District Directorates. The nine Technical National Directorates are responsible for the development of the various subsectors, including planning, monitoring and policy development, administration and finance, and regulatory services. The development, implementation and administration of programs and activities is predominantly a National Directorate responsibility. The District Directorates consists of three Departments: Agricultural Extension, Technical Services Support; and Administration and Programs.

The current priorities of MAF are guided by the National SDP (2011-2030). Increased productivity and self-sufficiency are the major focus of the agricultural development component of the SDP.

Since the launch of the Policy and Strategy Strategic Framework (2004), sub-sector policies have been developed by MAF for forestry, fisheries, food security and quarantine. Policies for livestock production, agricultural extension and agro-chemicals are in the last stages of development. The National Agricultural Extension Policy (NAEP) provides a framework for the establishment of a new national public and free agricultural extension service. The Gender Policy (2005) focuses on the need to achieve equality between men and women in the access to, and control over, the process of development and benefit-sharing in both the organizational and programmatic aspects of MAF. The Food Security Policy treats food security as a cross-sectoral and multi-level issue involving stakeholders from the household to national levels. This policy addresses issues related to access, availability, stability and effective utilization of food.

MAFF recognises that intensive and extensive agriculture production systems lead to environmental consequences and that long-term climate change has its own consequence on the environment as well as on agricultural production. Climate change leading to extreme weather events creates changes in geographical production patterns as well as deterioration of the natural resource base due to water scarcity and rising temperatures. Crop yield losses due to the increased risk of drought, floods and cyclone events, and the intensities with which they occur is inevitable. MAF advocates research and development efforts which can play a significant role in responding to the challenges of climate change as well as mitigating and adapting to climate-related production risks.

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6. INSTITUTIONAL ARRANGEMENTS AND CAPACITY IN INFRASTRUCTURE DEVELOPMENT

6.1 Main investment programmes (both planned and under implementation) in large and small-scale infrastructure

Large scale infrastructure development The SDP (2011-2030) outlines the key large scale infrastructure to be implemented under each type of infrastructure. Table 6-1 shows that government expenditure on roads and bridges has doubled in absolute terms, but only increased slightly in percentage (of total budget) terms between 2008-2013 and 2014-2018. Both irrigation and water and sanitation have increased substantially in absolute terms, and increased in percentage terms over the period.

Table 6-1: Summary of government expenditure by infrastructure type 2008 to 2013 compared to 2014-

2018 Small-scale infrastructure development - PDIM19 and PNDS investment plans, trends and priorities The two tables below show the number of projects implemented under the PDIM and PNDS investment plans since 2011, under which small scale infrastructure is implemented. It shows that the number of projects peaked in 2012, within the first year of the SDP and budgetary allocation for PDIM peaked in 2014 at $76.9 Million and has substantially reduced since, with only $10.7 Million allocated for 2017. Similarly, PNDS peaked in 2015 at 17.7 Million with only $400,000 allocated for 2017. Figure 6-1 shows that Baucau has had the largest number of PDIM and PNDS projects implemented since 2014 and the largest number of projects overall, which perhaps reflects the density of population, high infrastructure deficit and low coping capacity (hence higher need). The number of projects implemented under PDIM and PNDS is substantially reduced to 44 in 2017 compared to 695 at its peak in 2012. This drastic reduction in funding of rural infrastructure reflects the government’s prioritisation of large scale infrastructure and mega projects at the expense of small scale infrastructure.

19 Formerly PDID

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It should be noted that originally the PDIM budget was annually planned and spent. However, the PDIM legal framework has been recently amended in 2016 in line with the deconcentrating/decentralization program that allows re-appropriation of the unspent budget. This new amendment allows administrative units to carry funds beyond the year of allocation. The decision on this appropriation is through consultation between the administration unit. The municipal and the line ministries responsible for the program to the following year.

Table 6-2: List of Projects implemented under the government's PDIM and PNDS investment plans from 2011-2017

List of PNDS and PDID Project Implemented during 2011 - 2017 Number of project by year No Municipality Total 2011 2012 2013 2014 2015 2016 2017 2011 2012 2013 2014 2015 2016 2017 1 Aileu 25 41 46 33 33 9 0 187 2 Ainaro 23 50 39 25 35 21 0 193 3 Baucau 41 56 44 53 67 61 23 345 4 Bobonaro 29 62 39 53 47 39 3 272 5 Covalima 44 59 37 36 31 18 2 227 6 Dili 51 56 74 23 47 8 5 264 7 Ermera 29 65 56 52 58 30 3 293 8 Lautem 48 47 31 36 39 15 2 218 9 liquica 38 40 52 29 25 12 1 197 10 Manatuto 42 38 41 34 28 20 2 205 11 Manufahi 28 54 30 31 28 20 1 192 12 Oecusse 31 64 37 26 15 12 0 185 13 Viqueque 29 63 32 36 41 22 2 225 Total 458 695 558 467 494 287 44 3003

Table 6-3: Budgetary allocation of PDIM and PNDS projects for 2011-2017

Budgetary Allocation for PDID and PNDS project 2011 - 2017 2011 2012 2013 2014 2015 2016 2017 Total PDD: $ 44.3 M PDD: $ 64.5 M PDID: $ 71.5 M PDID: $ 76.9 M PDID: $ 2 PDIM: $ 2 PDIM: $ 10.7 $ 319 M 8.3 M 3 M M PDL: $ 3.5 M PDL: $ 6.2 M PNDS: $ 6.5 M PNDS : $13.6 M PNDS: $ 1 PNDS $ 10 PNDS: $ 400,0 $ 58 M 7.8 M M 00.00 Total $ 377 M Total Allocation for PNDS,PDID projects from 2011 - 2017: 377M

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Figure 6-1: Number of projects by municipality between 2011-2017

6.2 International Climate resilience projects

Table 6-44 below summarises the funding from International Agencies in climate resilience infrastructure projects in Timor Leste while Annex 2 lists the projects that have been implemented or are in implementation which include climate resilience.

Table 6-4: Total cost for climate resilience project funded by International Agencies registered in TL state Budget from 2014 - 2017

Total cost for climate resilience project funded by Interntional Agencies registered in TL state Budget from 2014 - 2017 2014 $3,677,494.49 24.98% 2015 $3,906,264.28 26.53% 2016 $4,303,389.12 29.23% 2017 $2,836,023.00 19.26% Total $14,723,170.89 100%

Climate resilient infrastructure projects are implemented mainly by international funding agencies with few, if any, government-funded schemes including climate resilience measures. International climate resilience project totalled $14.72 Million USD and showed in increasing trend from 2014 to 2016, and a decrease in 2017 due to incomplete data (only for the first half of 2017).

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6.3 Capacity Assessment of Government

A National Capacity Development assessment was undertaken from which the National capacity development Framework (NCDFM)20 prioritises important and urgent capacity development interventions that will strengthen the overall management and administration of Municipalities will be developed. By enhancing Municipalities’ service delivery to their local communities, it enables them to achieve the goals set for their development plan and to contribute towards building the nation of Timor Leste. The NCDFM is a five to seven-year strategy.

Local government capacity A consolidation of institutional capacity assessment was conducted, largely based on selected project evaluations from UNCDF, UNDP and the Asia Foundation, focused on local governments. This section provides a summary of findings relevant to institutional capacity for the development of rural infrastructure.

Timor-Leste still faces huge limitations in its human resource capacity despite enhancements to local governments’ capacities in managing local development funds (especially local planning, budgeting, procurement, implementation of small-scale infrastructure and monitoring). Apart from the sanctioning of municipality laws which will help further UNDP-UNCDF’s local governance initiatives, local government capacities need long-term expansion plans in order to run independently in the future.

• Local government officials demonstrate poor administrative and technical capacities in managing local development grants. District officials report weaknesses in technical capacities to: o assess proposals; o ensure performance standards; o conduct safety, environmental impact and cost-effective evaluations of proposals; and o monitor local development projects. • There was a shortage of technical staff in districts, such as architects and structural engineers, to oversee planning and supply projects with professional certification and technical approval. Given the rising trend in local development grants, which leads to increased demand for technical expertise, lone support from the local governance programme will be unable to fulfil what is required.

• LGSP has established systems which allow citizens to be more involved in prioritising local development project proposals. Informed local community participation is still in its infancy however, with obstacles in the way of establishing local government’s legal framework and constitutional structure. Although LGSP has brought about many enhancements, much more progress is required to set up working decentralized mechanisms and build required capacities for participatory planning, implementation and monitoring of local development projects and service delivery. Timor-Leste’s problems in advancing decentralized local government and boosting service delivery mirror the reality in similarly post-conflict, transitional nations. The speed and order of decentralization reforms have to consider capacities and institutional structures necessary for effectual local government.

• Timor-Leste is Still Largely Centralized. Successful decentralization requires delegation of funds, functions and functionaries:

20 National capacity development framework for strengthening municipalities to build community resilience in Timor Leste, UNDP 2017

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o According to the constitutional structures of local government, this means transferring administrative and legislative powers to varying degrees, revenue raising and taxation powers as well as medium-term expenditure frameworks and budgeting. o Delegation of functionaries will inevitably lead to establishing nuclei of district-level public servants (or at lower levels of administrative units). o Finally, there needs to be a clear understanding of how revenues will be shared between national and district-level governments.

• However, Timor-Leste is still largely centralized: o Resource generation, taxation, revenue administration and financial expenditure allocations are under the purview of ministries in the capital city. Sucos receive small financial resources from GoTL and do not have the legal authority to create revenue, make local laws, buy goods and services or enter into contracts. Fines can be collected for local usage; however, these are frequently small sums. Sucos and sub-units, aldeias, are considered community structures reporting to the Ministry of State Administration, not local government units. o Local level service delivery is fundamentally controlled by respective line ministries, with instructions passed down through district sectoral officials who are appointed and held accountable by the ministries, not local governments. o Timor-Leste officials are trained by CSC and appointed centrally by different ministries; there is no distinction of national, district and sub-regional officials. District administration is usually made up of a district administrator and a deputy district administrator aided by officers in charge of development, finance, general staff, human resources and social economy. There are also sectoral officials from line ministries such as agriculture, education, health, police, public works, land and property, water and sanitation and others. o As a result, programs like the Local Development Programme (LDP) and the Integrated Decentralized Development Programme “only represent steps towards a partial and somewhat controlled delegation of expenditure management to local levels.” (UNDP, 2014). Each suco council can only approve five local development project proposals each year, with block grants of approximately $60 per person. A district committee selects LDP projects for tendering and awarding, with line ministry sectoral officials and three members from each suco council. Ultimately, it is the national government who retains majority of the decision-making with regards to tendering, fund disbursement, monitoring and planning.

• Key Findings of LGSP: o there is a need to further improve community level service users’ participation with regards to planning, oversight and accountability. The policy and implementation capacities of national decentralisation champions are limited when measured against the scale of challenges confronting them. o planning at district or sub-district level is basically about prioritising projects, without long-term implications or area-based dimensions. Primarily, plans concentrate on clinics, drinking water supply and schools and, apart from irrigation and roads, negligible notice is granted to economic services. o Structurally sound infrastructure has been delivered, clear benefits to local communities, including the poor who express deep gratitude for the services provided. However, operations and maintenance arrangements with local participation are not established and basic supporting amenities like water supply and toilets are absent. o Long term sustainability of infrastructure, service delivery and the local governance system. Selected pilot districts are laying the foundations for institutional sustainability. However, for infrastructure sustainability, there is a

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need for local level operations and management organisations to be used. Economic and environmental sustainability have not been addressed by LGSP.

• Managing Agro-Biodiversity for Sustainable Livelihoods o Timor-Leste's rich agricultural species diversity (agro-biodiversity, ABD) faces challenges from over-intensive use and evolving agricultural practices. At governmental level, there is lack of understanding on how agro-biodiversity contributes to sustainable agricultural production and climate change adaptation, with little resources assigned to consider this issue. GIZ project Managing Agro- Biodiversity for Sustainable Livelihoods in Timor-Leste hopes to tackle this via i. “Protecting the rich agro-biodiversity by promoting its sustainable management ii. Developing and applying agricultural practices that preserve and promote agro-biodiversity, particularly in cocoa farming” (GIZ, 2017) o The Ministry of Agriculture has laid foundations for agro-biodiversity in the National Directorate for Community Development and Agricultural Extension, which is gaining importance at all levels. A national campaign for rice encouraged farming methods as well as usage of local varieties, which protects biodiversity. There is also a group-learning model for farmers to exchange their farming knowledge. i. National University of Timor-Leste's faculty for agriculture has received and is updating an index of varieties and species being cultivated, with State Secretariat for Environment receiving updates for inclusion in 2014's national biodiversity report. The farmers' groups who are involved in the project maintain registrations of their own plants and are beginning to try out farming methods like composting to protect biodiversity. ii. Farmers are cultivating demonstration fields where local varieties are grown and farming best practices are experimented. Extension specialists assist farmers in growing cocoa amongst current fields for bananas, coconuts, maize and vegetables. This has a positive effect on spurring training for farmers' groups and extension specialists. iii. State Secretariat of the Ministry of Commerce, Industry and Environment has created a directorate to safeguard biodiversity, with a holistic progress monitoring system put in place when executing the National Biodiversity Action Plan. The project has provided the services of a specialist to assist the State Secretariat in additional requirements in monitoring and evaluation iv. MSS, MAFF and MCIE: Functional capacities, knowledge and skills, and institutional arrangements

Technical Capacity Needs based on Focus Group Discussions with MASS, MAFF & MCIE

The following table highlights the functional and technical capacity gaps identified from MSS, MAFF, and MCIE. These are primarily gaps in knowledge and skills which can be addressed through training courses addressing the gaps.

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Technical Capacity Development Activities and Training Courses in Climatic Risk Analysis, Disaster Risk Reduction (DRR) & Disaster Risk Management (DRM)

A comprehensive list of recommended key capacity development activities and training courses is drawn up based on the technical capacity development needs identified above. This list acts as a reference for both current and future capacity development activities and training for municipalities. Different priorities are set for each ministry corresponding to differences in gaps identified:

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Capacity Development Needs for Small Scale Infrastructure Contractors

Across the board, 1) municipality management and administration and 2) municipality work systems and processes were found to be the two foundational capacities that require the most urgent development in municipalities. Furthermore, these provide the base from which further capacity development activities can be built on and fully developed. As such, it is recommended that key functional capacity development activities to be initiated in 1) municipality management and administration and 1) municipality work systems and processes.

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Municipality Climate and Disaster Risk Monitoring and Evaluation

The following table highlights the technical capacity gaps identified from the focus group discussions and interviews with 249 respondents (12% women, 88% men) comprising municipal staff, local community, sub-regional offices and small scale infrastructure contractors from Dili, Ermera, Lautem, Liquica, Baucau, Ainaro, Viqueque, and Covalima. Broadly speaking, each technical capacity gap identified requires two phases:

• Setting up/enhancing of a climate risk and disaster monitoring and evaluation (M&E) system • Training municipal staff in the use of said M&E system

In addition, each system has different outputs (e.g. data to be captured, reports to be generated) that requires different technical skills training for capacity to be fully developed. As these systems require both technical and functional capacities and training to be developed first in the municipalities, they are given a rating of Priority 3 i.e. to be developed once foundational skills and capacities are in place

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7. MAIN BASELINE PROGRAMMES IN AGROFORESTRY

7.1 Review of Agroforestry Sector

The practice of Agroforestry is not new in Timor-Leste. Just like in other countries, the cultivation and combination of trees and agricultural crops has long been considered as a traditional practice but did receive much attention and distinction. A good example of a century-old practice is Coffee- based Agroforestry System in Ermera where Albizia21 takes the role as shade trees and coffee as the agricultural component. Another example are vegetable farmers who are using live-fence system, instead of dead branches and palm mid-ribs, using Ai-Gamal (Glicidia sepium) to protect their crops from free grazing animals.

What is still missing in the general picture of the Agroforestry Sector in Timor-Leste is the element of MANAGEMENT and the very essence of recognizing the environmental benefits as well as goods and services of practicing it.

Below are the on-going interventions of the government and its partners in support of this sector.

7.2 Government-led Agroforestry Interventions

The MAF-Ministry of Agriculture and Fisheries (and Forestry) is the primary arm of the government responsible for coordinating all programs and projects related to Agriculture, Forestry and Watershed Development. With the passage of Deconcentration Law, it has gained more support from Municipal Local Government (MLG) with the Municipal Agricultural Offices (MAOs) taking the helm of implementing the frontline services.

Unlike other ministries, the MAOs have Extension Workers deployed in almost all the villages or Sucos of Timor-Leste These government workers represent the MLGs in all community meetings, supervised the implementation of agricultural and forestry projects and activities. They also provide free Technical Assistance (TA) to individual farmers and groups and assist the MAF Development Partners (DPs) in coordinating and implementing their programs and projects.

7.3 Non-Government-led Agroforestry Interventions

The DPs of MAPs are also continuously implementing their versions of various Agroforestry interventions of in Timor-Leste. Following are some of the prominent interventions of selected DPs.

World Vision World Vision introduced in 2010 the Farmer Managed Natural Regeneration (FMNR) techniques in the municipality of Aileu. It has also expanded its area coverage in the municipality of Bobonaro in 2012. The FMNR technology originates from Africa particularly in the country of Ethiopia. It is still an Agroforestry system in the sense that it is also promoting the integration of trees in the farm. In FMNR, natural regenerants trees growing inside the agricultural farm (also known as “wildlings”) are freed from competition from less economically viable species of plants. FMNR project also introduced tree production and alley cropping using Ai-gamal as hedgerow and farm live-fence.

21 A genus of about 150 species of mostly fast-growing subtropical and tropical trees and shrubs in the subfamily Mimosoideae of the family Fabaceae. The genus is pantropical, occurring in Asia, Africa, Madagascar, America and Australia, but mostly in the Old World tropics. In some locations, some species are considered weeds. They are commonly called silk plants, silk trees, or sirises

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JICA-CBNRM JICA-Community-Based Natural Resource Management (CBNRM) project in the municipality of Aileu started in 2012. The project is promoting Participatory Land Use Planning (PLUP) for establishing local policies -through Tara-Bandu22 - to support the CBNRM activities. Agroforestry interventions promoted by the project includes establishment of Soil and Water Conservation Measures (SWC), Terracing, Alley cropping using Multi-purpose trees such as Ai-gamal and Lamtoro and reforestation.

JICA is also implementing the Laclo Watershed Management project (various upland pilot projects on the target locations/villages in Manatuto, Aileu, Dili, Ermera municipalities territory).

USAID’s Avansa Agrikultura Project The USAID’s funded Avansa Agrikultura Project started in 2015 and covers selected Sucos in the municipalities of Dili, Aileu, Ermera, Ainaro, and Bobonaro. Though the project is more focused on horticulture value chain, it is also implementing various Agroforestry Intervention activities as a component of one of its objectives: Promoting Natural Resource Management and the practice Sustainable Production Practices. Some of the Agroforestry Interventions it has introduced so far Home-Gardens with tree components, Sloping Agricultural Land Technologies (SALT)23 and SWC. All these interventions are still currently on going.

Gobal Climate Change Alliance (GCCA) EU, GIZ and Camoes are implementing various Agroforestry-based activities as part of the GCCA Program. The project activities include the promotion of agriculture and soil and water conservation practices that are nutrient sensitive and the establishment of a network of potential Agroforestry species nurseries located in strategic location of the upper catchments of Loes and Seical watershed.

GIZ has been implementing the project ‘Global Climate Change Alliance’ (GCCA-TL) in Timor Leste since 2013. The Global Climate Change Alliance program in Timor-Leste is increasing resilience through reforestation practices by improving the capacity of vulnerable communities to cope with climate change effects through the sustainable management of their natural resources and improvement on their livelihood. The project addresses key issues of the high dependence on subsistence agriculture, mountainous topography, food insecurity, high rate of deforestation and degradation of the natural resources, the coping mechanisms of rural communities and the effects of climate change. The project has improved capacity of the Agriculture and Land Use Geographic Information System (ALGIS) to collect, analyse and sharing agro-met data (10 out of 12 ALGIS weather stations (AWS) are operational, Monthly edition of MAF Agro-meteorological Bulletin based on ground data. Awareness raising at community level emphasizing the need to implement agriculture and (agro) forestry activities for adaptation were undertaken and community replication and implementation of adapted practices in agriculture and (agro) forestry (7 new climate sensitive livelihood activities were implemented, facilitated by the establishment of 42 agro forestry nurseries, producing 127, 901 seedlings of 33 different species. The GIZ programme is continuing until 2018 and has been implemented in Ermera and Liquica.

WithOneSeed In 2012, the WithOneSeed project and the Australian Agroforestry Foundation started making its intervention in Suco Baguia, in the municipality of Baucau. The group initiated and offered a Master Tree Growers Course- to train potential tree growers. Their project also led to the formation of the Baguia Tree Cooperative, engaging 251 subsistence farmers who have planted 40,093 trees so

22 A centuries-old form of community law and order which can include regulations on human interactions with the environment, interactions with each other and interactions with animals,” 23 A modified Alley cropping technology that originates from the Philippines

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Coffee Cooperative of Timor-Leste (CCT) CCT is one of the oldest farmers’ cooperative in Timor-Leste providing technical support to farmers who are engaging into coffee production. As compared with other coffee producing countries, Timor-Leste are still using the variety that of coffee that requires shades hence considered also as an Agroforestry intervention having met the requirement of the tree and agricultural crop combination. CCT has already diversified and currently engaged into another shade-loving crop- Cacao.

7.4 Other relevant projects and initiatives

Other organisations actively implementing agro-forestry programmes in Timor Leste are as follows:

1. Seeds of Life Program (Fini ba Moris): Seeds of Life (SoL) is a program within the Timor Leste Ministry of Agriculture and Fisheries (MAF). SoL is funded collaboratively by MAF and the Australian Government, through Australian Aid and the Australian Centre for International Agricultural Research (ACIAR). So far they have been working with Laclo (Manatuto district) and Raimoco (Lospalos district) watershed areas. Basically, their activities engage with target community (villages) in the up-land with particular activities. SoL maintains a core focus on increasing yields by selecting and distributing improved varieties of superior genetic quality. It also has a secondary focus on analysing and developing strategies to overcome climate variability and change; improving agronomic practices to reduce weed burdens and increase soil fertility; reducing post-harvest storage losses and improving input supply arrangements for seed.

SoL maintain a wide network of automatic weather stations. Most of their automatic stations have no telemetry capabilities yet, but an upgrade of this system is taking place and four of their stations are now sending data automatically. All the information from the automatic stations is being sent to NDMG which maintains a database with information from all the different weather stations in the country.

2. UNDP Indonesia CO, responsible for project on the biomass project for East Timor: local contents on the fuel woods sources and demands were made by the agro forestry and livelihoods Specialists. Particularly Dili as high demand for the fuelwood and all the neighboring districts of Dili are main supplier for the fuelwood.

3. Shoreline Protection Project, UNDP Timor Leste Country Office. Location covers mostly south coast region include; Suai, Same and Viqueque coastal zones and their community.

4. Partnership for sustainable Agro-forestry (PSAF) between Timor Leste, the European Union and Germany and will be between 2017 and 2021. EU and German Government have agreed with the GoTL to support the development of smallholder-based agro-forestry farming systems, which include food and cash crops (and where suitable, livestock) to ensure short-term returns to farmers (increased incomes) and improved food security and nutrition; and in the longer-term, increased income from cash crops, and improved forest protection and management. In addition, the agroforestry approach will assist with farm product diversification, and have a positive effect on long term ecosystem services and biodiversity. This time-phased approach to rural development through the promotion of

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agro-forestry systems will enable farmers to address multiple short-term objectives, whilst working towards the development of diversified and climate resilient assets in the form of tree and timber crop plantations. Economic opportunities in rural areas can help mitigate migration to urban areas which is a potential source of conflict. The rehabilitation and maintenance of rural roads will have an evident impact on market development for agroforestry products (wood and non-wood). It will improve rural communities' access to all other services (health, education) as well. At the same time, it will allow building capacities of local construction companies and communities and increase incomes (through the high intensity labour works strategy).

PSAF will pay particular attention to the environment by limiting the cutting of trees not planted for commercial purposes, supporting improved forest management and reforestation, and producing fuelwood as by-product from agro-forestry systems. The programme will actively promote the positive environmental effects of using agro-forestry systems, such as habitat functions, and reduced soil erosion and water pollution. Furthermore, the programme will support the implementation of the Convention on Biological Diversity (CBD) and the achievement of respective Aichi targets by using agroforestry systems.

5. ETADEP, Terracing (Aileu, Remexiu, Dare, Laulara, Manatuto, Ermera, etc.).

6. CARE INTERNATIONAL. CARE in Timor-Leste focuses on long-term sustainable development projects in agriculture and disaster risk reduction, education, community health and nutrition, capacity building, urban community outreach and peace-building, rural infrastructure and employment, and women’s participation and gender equality.

7. WorldFish: Involved in aquiculture activities (hatchery, capacity building, assists traditional fishermen in Atauro (rumpong), stock assessment on the south coast and mud crab). Future plans include sea cucumber project. A hatchery is being installed in Vemasse in Baucau district to distribute the fingerlings fish to the selected community. Main donors for the World Fish include: Norway, New Zealand Aid and …

8. Directorate of Fisheries Department: their priority programs and actions (activities) on the coastal areas promoting livelihoods sources for the coastal community.

9. KOICA Timor Leste: KOICA’s plan to establish an Aquiculture Training Centre (ATC) in Maubara, Liquica district. Currently in the preliminary assessment stages. The ATC main focus will be to train young fishermen as Training of Trainers (TOT) to be selected from entire territory. The subjects for the ATC main will covers how to produce the fish and minor segment on the marketing. For the future potential training partner’s, government have indicated two potential universities (UNTL and UNITAL).

10. Kmanek Trading: Kmanek Trading started business in East Timor in 2007. Initially the company start with horticulture. 1) Horticulture. The company’s orientation is Go Green or 100 percent organic - a project sponsored by USAID. Beneficiaries of the project includes approximately 500 rural families. Typically, price for the vegetables vary on their size (big, medium and small) for example for the big sizes costs $10 per kg. Basically, vegetables price is based on consensus among local farmers and the Kmanek Trading, since local farmers must compensate for the seeds and technical assistance from the company

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throughout the cultivation period; 2) Aquiculture (fish farming) initiated in 2011 including species; mud crab (wild catch) and hatchery. Target locations; Vemasse, Liquica, Beco- Zumalai and Same which was implemented by ACI-VOCA.

11. ALGIS - Ministry of Agriculture and Fisheries: The Agriculture and Land-use Geographic Information System (ALGIS) is an institution within the Ministry of Agriculture and Fisheries (MAF). ALGIS was established by FAO and issues monthly reports about climatological conditions for agricultural purposes. ALGIS has 12 automatic weather stations in Timor Leste, information from which is collected and used to climate variable reporting. ALGIS collaborates with NDMD/NDOC during disasters, especially during flood and fire disasters. They coordinate the response from a village point of view, undertaking assessment of the community needs and providing relief. ALGIS also seems to send information about rainfall during the rainy season, although how this is accomplished and what type of information is shared is unclear.

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8. GOOD PRACTICES, FIELD EVIDENCE AND LESSONS FOR SCALE-UP

8.1 Strengthening the Resilience of Small Scale Rural Infrastructure (SSRI) and Local Governance Systems to Climate Variability and Risks

8.2 Background

The institutional and financial capacity of Local Administrations and communities in Timor Leste to adapt to climate change and its impact on people, agriculture and infrastructure is weak. This includes the ability of municipality planning officials, engineers and decision makers to identify areas that are critically vulnerable to climate hazards, to draw the links between ecosystems management and infrastructure development, and to identify, appraise, prioritize, design and ‘budget in’ greater resilience measures. There is also a weak ability to understand and address gender and climate change related development and equity issues at local level.

The climate induced problem that the SSRI project is seeking to address is that Local Administrations, particularly in drought prone areas and areas vulnerable to extreme rainfall events, are finding it increasingly difficult to supply and maintain critical small scale rural infrastructure for rural communities, leading to measurable reductions in household income as well as increased food insecurity and health issues. The project is also seeking to address climate induced threats caused by the slowly decreasing protective and water storage functions of ecosystems due to over-exploitation of forest and coastal areas resulting in rapid deforestation.

The LDCF-funded UNDP SSRI Project focuses on supporting Ministry of State Administration (MSA ) and Ministry of Commerce, Industry and Environment (MCIE) to implement climate resilient rural infrastructure projects in a socially and environmentally acceptable manner as well as to develop institutional and human capacity at national and sub-national level (local community and Municipalities) to integrate climate resilience into the planning and implementation of District Development Investment Plan (PDIM) projects.

SSRI supports integrating climate change issues into Municipality and local level planning and implementation of PDIM projects in a manner that makes them withstand risks and impacts of climate change. SSRI is being implemented in three Municipalities - Baucau, Ermera and Liquica - which represent the diversity of key climate variability risks and vulnerabilities, which the project aims to address. They combine relatively high population densities with relatively poor areas, vulnerable flood-prone coastal conditions and landfall prone vulnerable mountainous terrain and areas with a projected increased drought period with areas of high groundwater vulnerability. The vast majority of the population in the selected municipalities depends on unprotected gravity-fed water sources is used for both domestic use and important subsistence, and in some cases, cash crop production.

8.3 Main project objectives:

Critical small scale rural infrastructure is climate-resilient designed and implemented through participatory approaches and strengthened local governance systems, reflecting the needs of communities vulnerable to increasing climate risks.

The overall goal of the project is to safeguard development benefits for rural communities from future climate change induced risks, which is in line with and underpinned by, several important policies and strategies governing Timor-Leste’s national development and its specific response to climate change.

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8.4 Expected Project Outcomes

GEF-LDCF funds are being used by the Government of Timor Leste to address these barriers through 3 components.

Outcome 1: Policy makers and the public in Timor Leste are aware of critical climate risks to rural (infrastructure) development and are systematically being informed on up to date evidence-based information on climate hazards through vulnerability assessment and cross government coordination mechanisms. LDCF grant requested: USD 430,000 and Co-financing: USD 12,577,384.

Outcome 2: Local Administrations integrate climate risks into participatory planning, budgeting and standards of small scale rural infrastructure development. LDCF grant requested: USD 573,610 and Co-financing: USD 12,579,523.

Outcome 3: Small scale rural infrastructure made resilient against climate change induced risks (droughts, floods, erosion and landslides) in at least the 3 Districts or Municipalities of Liquiça, Ermera and Baucau (Physical Investment Component). The Ministry of State Administration is to act as the lead partner from the government of Timor Leste as well as responsible party for the investment component (Component 3). LDCF grant requested: USD 3,366,390 and Co-financing: USD 23,174,128.

8.5 Description of project implementation

In Timor-Leste 70 percent of its 1.1 million people live in rural areas. Many of its communities are in mountainous and coastal areas that are highly vulnerable to climate risks such as floods, droughts, erosion and landslides. These conditions have made it difficult to develop basic infrastructure, such as roads and water supply systems, directly impacting both community livelihoods and national development goals.

The UNDP Timor-Leste Strengthening the Resilience of Small Scale Rural Infrastructure and Local Government Systems to Climatic Variability and Risks (SSRI) Project has been collaborating and working closely with national and local administrations to increase the climate resilience of rural infrastructure for communities that are most vulnerable to extreme climate events and climate risks, particularly in the three municipalities of: Ermera, Baucau and Liquiça.

SSRI project funded by GEF LDCF and implemented by UNDP in collaboration with MSA and MCIE can be described as a pilot intervention of how climate resilient and adaptable infrastructure can benefit the country. It provides the foundation and ground work for advancing the initiatives and works that were piloted in the three selected municipalities of Baucau, Ermera and Liquica and for expanding into other vulnerable communities.

While the project has been developing the capacity of these communities and local administrations to integrate climate resilience into the development of local infrastructure. One of the Government’s primary objectives for the SSRI project is to mainstream climate change resilience into national policies and strategies for local level planning so that these lessons can be replicated and applied to all municipalities across the country.

The approach of planning, developing and implementing climate resilient rural infrastructure differs from the business-as-usual approach. The new way of thinking – planning and implementing takes into consideration the potential existing and future climate change and climate variability risks and actively seek ways of addressing them through adaptability and resilience of the infrastructure.

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Project implemented by the UNDP SSRI project are selected from the annual Municipality Investment Plan (PDIM – Planu Investimentu Municipal). The project selection process involves reviewing the Municipality Investment Plans (PIM) and projects implemented focus mainly on four categories of infrastructure namely: i. water supply systems, ii. rural access roads and bridges, iii. reservoirs and irrigation systems, iv. stabilizing river banks/flood protection.

Building climate resilient rural infrastructure comprise of several interventions and measures as follows: 1. Engineering designs and structural measures a. Improved Design – improved and appropriate designs, choice of materials, technical specifications, cost-effective, efficient and sustainable designs. b. Quality improvement – continuous improvement in the processes and products of the project being implemented. This also include improvement in construction and methodology. For example, in the case of masonry drains and irrigation channels, traditionally the side wall were constructed first before the installation of the base slab. However, with improvement of the construction by completing the base slab first and then the side walls this has led to improvement in the service life of the structure and its resilience particularly where there are high risks of erosion and landslides.

2. Slope stabilization – combination of gabions with bioengineering approaches to address landslides and erosion

3. Soil-bioengineering interventions - the use of vegetation, either alone or in conjunction with civil engineering structures such as small dams, wall and drains to manage water and debris thereby reducing instability and erosion on slopes. Some typical bio - engineering methods include the following: − Grass Planting using common species such as vetiver and elephant grass − Shrub and Tree Planting − Brush Layering, palisades − Check dams using locally available materials

4. Capacity Development - training and capacity development of local authorities and municipality technical staff, local contractors, suco (village) councils and community. One example is the ongoing engagement and capacity development of the contracting companies at regular monthly construction site meetings which is being done for the first time for PDIM projects by the SSRI project. It was found to be very beneficial to address issues arising during the implementation of the projects. Involvement of the local leaders and technical staff from the municipality also helped to quickly resolve issues arising and therefore provided additional benefits such as reduced implementation risks and delays.

5. Strengthening existing and/or developing new guidelines, manuals and technical specifications for planning, development and implementation of small scale rural infrastructure. For example, the technical specifications use for road rehabilitation and construction is in process of being improved to include the various soil bioengineering approaches which is now an integral aspect of rural road construction. SSRI project is collaborating with other entities such as the Ministry of Public Works R4D program and on the national bioengineering working group platform to first share all the lessons

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learned on the bioengineering interventions undertaken on the rural infrastructure projects (particularly on the rural roads) and aims to influence the review and revision of the technical specifications to be used also for implementation of PDIM projects.

6. Extensive community consultation – the engagement and involvement or community, beneficiaries and all relevant stakeholders at all stages of the planning, development and implementation of the physical infrastructure projects have significantly aided the process of implementation.

During the planning process and prior to implementation, the project beneficiaries and community members were engaged in a consultative process. The proposed project is presented to the community where all concerns can be raised and addressed prior to commencement of implementation. Issues such as adequacy of designs, functionality when project is completed, sustainability, operation and maintenance, and land ownership were some critical issues that were raised and addressed at many of these consultations.

These consultations also form part of the Environmental and Social Safeguard assessments that were conducted for all the projects and the reports that were prepared and submitted to the Ministry of Commerce Industry and the Environment. EIA assessment and reports for the project were done in accordance with the Environmental Licensing Decree Law No. 05/2011 of 9 February. This is also the first time that EIA assessment conducted and reports compiled for PDIM projects. According to the National Director for EIA and Pollution Control and Chief of Department for EIA at the MCIE, it is expected that PDIM projects in the future can follow this process and comply with the requirements of the relevant Decree Law. 7. Sustainability and Maintenance – absence or lack of adequate resource allocation for maintenance and operation of rural infrastructure have led to reduced service life, failure and in some instances complete loss of the infrastructure asset. It is therefore imperative that the issue of post-construction operation and maintenance to ensure sustainability of the project is taken into consideration earlier in the development stages and that mechanisms are put in place to address this. For the SSRI project, all the rural roads were merged with the Ministry of Public Works annual maintenance program after its completion. For the water supply projects, the existing mechanism of establishing and supporting Facility Maintenance Groups (GMF) were followed as per the existing guidelines of the water and sanitation Department of the Ministry of Public Works.

8.6 Water Supply Systems

1. Clean water installation project in Aldeia Uatu-ua, Suco Gariuai, Baucau Municipality

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The construction of water intake structure/tank, 60 m3 galvanized reservoir, and 7 public taps, and installation of 1.475 km transmission mains and 2.1 km distribution pipes has provided clean water for more than 2,380 people in the village.

2. Clean water installation project in, Suco Ossoala, Baucau Municipality

Suco Ossoala is a very remote community located in Municipal Authority Baucau.

The project entails the construction of water intake structure, installation of 20 m3 galvanized water tank, two 5.5 m3 distribution tank, and construction and rehabilitation of a total of 13 (6 newly constructed and 7 rehabilitated) public taps, and installation of 5 km transmission mains and 2 km distribution pipes, benefitting more than 665 people.

During the official inauguration of this project on 22 February 2016 in Baucua Municipality, H.E Secretary of State, Mr. Samuel Mendonca encouraged persons in attendance particularly officials of the Government present at the ceremony to apply the initiatives and activities undertaken by SSRI into other Government’s programmes. Mr. Mendonca further added that although SSRI projects are implemented on a small scale, it has significant positive impacts for protecting our infrastructure and the environment. “SSRI project interventions not only provide water, fix roads or

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I provide irrigation systems, but works by combining the physical infrastructure with other softer solutions to provide protection from climate events such as landslide, flooding and erosion”.

UNDP, MSA and MCIE commissioned rural water supply project in Suco Ossoala as part of climate resilient small scale rural infrastructure project in Timor-Leste. http://www.tl.undp.org/content/timor_leste/en/home/presscenter/pressreleases/2016/02.html

3. Wailia water source protection in Suco Bahu, Baucau Municipality

The protection includes construction of corrugated roofing covering to water source and sealing of crack on wall of spring box, benefiting 34,820 people in the municipality.

4. Clean water well in Suku Maumeta and Lauhata, Bazartete administrative post, Ermera municipality

Commencement : August 10, 2016 Completion : January 10, 2017 Value : $ 29,902.25 Contractor : Colikai Unipessoal Lda Deign life : 10 years

Scope of Works - Construction of 3 water well with 5 m depth, hand pump, washing place and protection house. - Gabion wall protection to - Bio-engineering (trees planting) Direct beneficiaries of the project - Total beneficiaries: 1,386 (Female: 689, Male: 697) - Number of Aldeias - 4

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Some challenges during the project implementation − Difficult to procure materials on time, also the limited technical and financial capacity of company which the project had to work closely with the company to get the job done. − Limited participation from some of the community members despite being involved in the stakeholders’ consultation. This also resulted in one of the initial locations for the public well had to be relocated from the planned initial design

Three water wells with 5 meters depth, hand pump, housing unit with washing facilities provided for the beneficiaries, and vegetated gabion embankment constructed to protect wells and structure from inundation and erosion, providing clean water for more than 1,386 beneficiaries.

5. Clean water installation project in Aldeia Leirema, Suco Ailelo of Hatolia administrative post, Ermera Municipality

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More than 490 people are benefitted with the construction of water intake structure, 20 m3 concrete reservoir and 16 public taps, and installation of 2.75 km transmission mains and 2.5 km distribution pipes.

6. Clean water installation project in Aldeia Gnutur, Suco Leimea Kraik of Hatolia administrative post, Ermera Municipality

More than 450 beneficiaries with the construction of water intake structure, 20 m3 concrete reservoir and 8 public taps, and installation of 5.2 km transmission mains and 1.5 km distribution pipes.

7. Clean water installation project in aldeia Bura, Suco Talimoro of Ermera administrative post, Ermera Municipality

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More than 930 people are benefitted with the construction of water intake structure, 20 m3 concrete reservoir and 9 public taps, and installation of 0.2 km transmission mains and 3.2 km distribution pipes.

8. Water supply installation project in Suco Lauala, Ermera Municipality

Commencement : 26 September 2016 Completion : December 26, 2016 Total Value : $94,969.50 Contractor : Lost Angel Unipessoal Lda Deign life : 15 years (with routine maintenance) and reservoir/tank comes with manufacturer’s warranty of 20 years

Scope of Works - Construction of water intake structure/tank, galvanized reservoir – 80 m3, and 16 public taps - Installation of transmission mains – 3.75 km and distribution pipes – 2.75 km Direct beneficiaries of the project - Total beneficiaries: 1,270 (Female: 518, Male: 752) - Number of Aldeias – 2

Some challenges during the project implementation − Difficult access to site of the water source posing challenges for the company to mobilize construction materials − Inclement weather (rainfall) affected the implementation of planned activities by the company in project site − Delay in shipment of the pre-fabricated galvanized water tank 80 m3 from the manufacturer in Australia resulting in late arrival and consequently delay completion of the project

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Through the construction of the water intake structure and 80m3 galvanized reservoir, installation of 6.5km of transmission and distribution pipelines, water is brought from reservoir to 16 public taps, providing clean and more efficient water supply for more than 1,400 beneficiaries.

“We feel very happy, because in the past we used to go very far to get water, but now the clean water is near, we feel very happy for the authority to have given us clean water” said Bendita de Jesus Salsinha, who lives in Suco Lauala.

“In the past, we don’t plant vegetables, we always buy them. We don’t plant vegetables because there is no water, therefore we are going to use the water to plant vegetables, to cook and drink. We have the obligation to take care of the water supply system and taps, so that the system will last for long time and for the next generation.” she further added.

Apart from addressing the challenges posed by climate change such as drought this project provides other benefits to the people in this remote village in Ermera. Mr. Jose Martinho dos Santos, President of Ermera Municipal Authority, expressed thanks for SSRI Project and hopes that UNDP will continue to support water projects to schools and health posts in the future. “Community in Lauala should take care of the maintenance of this water system,” he urged participants from Lauala. “The new and clean water supply could also minimize the malnutrition problem.”

Publication: News Story on UNDP: http://www.tl.undp.org/content/timor_leste/en/home/ourwork/environmentandenergy/successstori es/new-water-supply-system-bringing-clean-water-to-1400-people-in-l/

Video on YouTube: https://youtu.be/GLmflX54lIU

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9. Clean water supply installation project in Suco Poetete, Ermera Administrative post, Ermera Municipality.

Commencement : August 23, 2016 Completion : December 31, 2016 Value : $92,889.76 Contractor : Hamutuk Hatutan Unipessoal Lda Deign life : 15 years (with routine maintenance) and reservoir/tank comes with manufacturer’s warranty of 20 years

Scope of Works - Construction of water intake structure/tank, galvanized reservoir – 60 m3, and construction of 7 public taps - Installation of transmission mains – 3.6 km and distribution pipes – 450 meters Direct beneficiaries of the project - Total beneficiaries: 1,175 (Female: 615, Male: 560) - Number of Aldeias - 3 Some challenges during the project implementation − Difficult access to site the site particularly the water source posing challenges for the company to mobilize construction materials and complete the works in a timely period − Inclement weather (rainfall) affected the implementation of planned activities by the company in project site especially in Ermera when there is usually raining every day in the afternoon period

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10. Clean water installation project in Aldeia Aimera ulu, Suco Hatolia, Ermera Municipality

Commencement: August 23, 2016 Completion : December 31, 2016 Value : $74,642.15 Contractor : Ele Nisi Eto Unipessoal Lda Deign life : 15 years (with maintenance of system. Manufacturer’s warranty for the galvanized reservoir is 20 years)

Scope of Works - Construction of water intake structure/tank, galvanized reservoir – 60 m3, and 11 public taps - Installation of transmission mains – 1.475 km and distribution pipes – 2.1 km

Direct beneficiaries of the project - Total beneficiaries: 1,008 (Female: 499, Male: 509) - Number of Aldeias – 2

Some challenges during the project implementation − Inclement weather (rainfall) and poor condition of access road resulting in difficulty for the company to mobilize construction materials and therefore affected the implementation of planned activities by the company in project site. This resulted in delay in completion of the project.

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With the construction of water intake structure, and installation of 60 m3 galvanized reservoir, and 11 public taps, and installation of 1.475 km transmission mains and 2.1 km distribution pipes, clean and efficient water supply is provided to more than 1,000 people in the village.

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Table 8-1: Sanitation facilities / methods of private households at GCF target municipalities of Timor Leste24

Status of Open Defacation Free (ODF) (meaning that all people in all households have Proportion of flush & latrine toilets access to toilet. ODF is part of the implementation of PAKSI Administrative Private (Action Plan for Community Post and Suco Households Sanitation and Hygiene) of the Ministry of Health (MoH)). Source: Total Total No facility https://www.communityledtotals flush % % % latrine & others anitation.org/country/timor-leste- toilet

east-timor Declared 'Open Defecation Free’ (ODF). 92 percent of all Aileu 7,598 2593 34% 4,436 58% 569 7% households in Aileu Municipality have a toilet. Baucau 22,976 6152 27% 13,497 59% 3,327 14% Officially declared ‘Open Ermera 20,671 5601 27% 11,680 57% 3,390 16% Defecation Free’ (ODF) on 22 Feb 2019 Expected to declare 'Open Lautem 12,050 2965 25% 5,458 45% 3,627 30% Defecation Free' (ODF) in November Officially declared ‘Open Liquica 11,885 3,557 30% 6,142 52% 2,186 18% Defecation Free’ (ODF) on 30th April 2019) Expected to declare 'Open Viqueque 15,297 2,585 17% 5,753 38% 6,959 45% Defecation Free' (ODF) in November

8.7 Rural access roads and bridges

1. Construction of bridge, culverts and roads in Suco Leguimea, Ermera villa Post Administrative, Ermera Municipalities

24 Open Defecation Free – ODF means that all people living in a municipality exclusively use toilets rather than defecating in public places. The ODF team, together with municipality ODF secretariat team, monitor and encourage people to build toilets for themselves, Suco Councils verify ODF. (Source: https://www.wateraid.org/au/articles/liquica-announces-open- defecation-free-status?fbclid=IwAR1Zvz8ZGhnwAxi0t8MVTXJj3JXyhSfPNEFNTj8hJxKv16-ECuBKYShMZcIAs CLTS is progressing and more households are having sanitation installations the data will be verified and updated at the inception stage of the project

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The bridge construction, including construction of box culverts, pipe culverts, 269 m3 gabions, 467 m3 drainage structure, retaining wall, 18.37 m3 plum concrete work and 510 m3 gravelling to improve road access and provide benefit to more than 1,050 people.

This project commenced in 2015 and while experiencing delays in implementation, the project was substantially completed in January 2017.

While for SSRI projects, funds are not allocated for maintenance beyond end of the defects liability period and when the project of issued with the “Final Completion” certificate to the contractor, all the roads rehabilitated and/or constructed were included in the maintenance plan and with budgetary allocation by the Ministry of Public Works R4D program. This is also an important lesson learned and best practice that can be replicated on other PDIM rural road infrastructure projects to ensure sustainability and longevity of the projects implemented.

Publication: TIMOR-LESTE: STAY CONNECTED Reducing Climate Risks, Building the Future https://undp-adaptation.exposure.co/timorleste-stay-connected

Stay Connected in Timor-Leste: Reducing Climate Risks https://www.youtube.com/watch?v=Tt4Ts5O8LQQ&feature=youtu.be

2. Road rehabilitation of Nunulete Darulema 1.6 km in Maubaralisa administrative post in Liquica municipality

Commencement : June 2015 Completion : January 31, 2017 Value : $ 119,841.97 Contractor : Ambou Unipessoal Lda Deign life : 15 years

Scope of Works - Plum concrete work for slopes with gradient > 15% = 418 m3

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- Side drains and concrete retaining walls structure = 130.42 m3 - Gabion wall installation =210 m3 - Causeway – two units - Box culverts – two units - Bio-engineering (check dam, grass planting, trees planting) Direct beneficiaries of the project - Total beneficiaries: 1078 - Number of Aldeia - 2 Some challenges during the project implementation − Inclement weather (rainfall) affected the implementation of planned activities by the company in project site − Initial delays in implementation of the project by the company because of limited technical and financial capacity. The project worked closely with the contractors and national and municipality counterparts to ensure that the works were successfully completed

The existing road to Nunulete-Darulara was eroded due to lack of maintenance and also because of the impact of extreme climate events causing erosion and landslide. Particularly during the rainy season access to the road is the most difficult for community due to slippery and inaccessible road in the steep sections which in some instances have been eroded because of the extreme amount of water flowing through the roadway without side drains and drainage structures and the type of surfacing.

Because of these conditions of the roads, safety for road users and accessibility to communities and their homes are significantly affected, mainly by the effects of climate change. There are all indications that debris and sediments flow from highland areas and are deposited on the lowlands. During community assessment, the people in the area reported that, vehicles are reluctant to go to the Aldeia due to slippery and unstable surface and the deplorable condition of the road. The problem is further compounded by lack of resources allocated for maintenance that is affecting community livelihood, socio-economic and cultural activities.

This project was identified under the SSRI project to address this problem and hence preserve this vital link, so that the social and economic livelihood of the people will be improved. In addressing these issues, the following measures were undertaken:

• Bio-engineering, the planting of live vegetation along steep slopes to prevent landslides and erosion. • Construction and rehabilitation of drainage structures with adequate and improved designs. • Plum concrete/hard surfacing for sections of road with steep slopes particularly with gradient greater than 15% • Combination of these measures at some locations including construction of masonry side drains to cater for increase water discharge during periods of extreme rainfall • Merging the completed road into the Ministry of Public Works R4D maintenance program to ensure that annual and routine maintenance will provide sustainability of the road

3. Road rehabilitation of Dato Darulete 1.678 km in Liquica vila administrative post in Liquica municipality

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The road rehabilitation, including construction of 418 m3 plum concrete, 528 m3 gravelling, drainage structure and bio-engineering work (check dam, grass and trees planting) will provide better access and benefit more than 15,300 people in four villages.

4. Rehabilitation of 2.77 Km of road in Buruma from Wamutu to Afatalakai and Waimatame, Suco Buruma, Baucau Municipal Authority

Commencement : 16 August 2016 Completion : 24 Value : $ 171,028.68 Contractor : Strive Unipessoal Lda Deign life : 10 years

Scope of Works - Stone masonry for Retaining wall and drainage 650 m3 - 5 units of pipe culvert and 2 units of box culvert - Construction of plum concrete 183.6 m3 - Gabions installation 162 m3 - Construction of causeway – 7.2 m3 - Graveling to road surface in sections with slope less than 10% gradient - Bioengineering component is sections at risk from landslide Direct beneficiaries of the project - Total beneficiaries: 4,705 (Female: 2,518, Male: 2,187) - Number of Aldeias – 3 Some challenges during the project implementation − Inclement weather (rainfall) affecting the implementation of planned activities by the company in project site. − Section of the road at risk from landslide was very challenging for company to complete the gabions installation in a timely manner

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− Delay in procurement of materials by the contracting company resulted in delay implementation and completion of the project.

The road rehabilitation, including construction of 650 m3 masonry retaining wall and drainage structures, concrete surfacing in the steep sections that are susceptible to erosion and washing away during extreme rainfall and gravelling done to other sections of the road and for new sections, including gabion installation and bioengineering intervention at sections that are at risk of collapsing from potential landslide, with benefits to more than 4,700 people and providing improved livelihood and economic activities in the community.

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Mr. Liborio Freitas – Chief of Buruma Village says that this new road provided by UNDP SSRI Project will boost agriculture, fishing and tourism in Buruma village.

Mr. Timotio Ernesto da Silva – Beneficiary in Buruma Village says “now the road condition is good and has helped us, because the car and motor bike accessible to drop our local products such as tomatoes, and make our work lighter. Before the road is not rehabilitate is very far because we must bring tomato to main road by foot and now we can sell our local product in the local market.

Publication:

News Story on UNDP Website: Better road improves livelihood of Buruma people http://www.tl.undp.org/content/timor_leste/en/home/ourwork/environmentandenergy/s uccessstories/better-road-improves-livelihood-of-buruma-people/

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Video on YouTube: https://youtu.be/1ezrzw9TgGI

5. Construction of low-water crossing and road rehabilitation in Suco Manusae, Hatolia Administrative Post, Ermera Municipality

Commencement : August 23, 2016 Completion : 15 % completed at July 31 - Ongoing Value : $ 137,152,44 Contractor : Hauhei Unipessoal Lda Deign life : 20 years (with regular and routine maintenance)

Scope of Works - Construction of concrete causeway – 16 meters - Gabions installation 48 m3 - Length of low-water crossing/bridge is 12 meters with 6 No. 0.6 meter pipe culverts and reinforced concrete slab - Road rehabilitation with plum concrete on steep slopes with > 15% gradient and gravelling for other sections Direct beneficiaries of the project - Total beneficiaries (direct and indirect): 24.285 (Female: 12,150, Male: 12,135) - The low-water crossing which is an innovative design for Timor-Leste will provide linkage between two Sucos comprised of 3 Aldeias. Some challenges during the project implementation − Difficult access to project site of the bridge because of continuous rainfall in the location throughout the first half of 2017 and the road condition in a very deplorable and inaccessible for mobilizing plant and equipment and transporting materials to site. − Continuous rainfall affected the implementation of planned activities by the company in project site base on this the construction of the initial design of a

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reinforced concrete bridge across the river. This could not have been implemented because of the continuous high water in the river and the capacity of the construction company with the limited time available before SSRI project comes to an end. − To accelerate the implementation of the project and to ensure that the contractor can deliver the project for the community, the scope of works for the project was revised and instead of a high span RC bridge the low-water crossing was designed for implementation with rehabilitation of the road.

6. Road rehabilitation of Taltabi-Kutulau 1.6 km, Bazartete administrative post, Liquica Municipality

The road rehabilitation, including 242.4 m3 plum concrete work, 793.35 m3 graveling, constructing 96 m3 gabion wall, box culvert and 13.5 m3 side drain, and bio-engineering work (check dam, grass and trees planting) will benefit more than 1,070 people and improve their livelihood.

8.8 Reservoirs and Irrigation systems

1. Construction irrigation scheme in Lacoliu, Quelicai administrative post of Baucau Municipality

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Water is collected from three intake sources and piped into a reservoir. The water is then stored and/or channeled to the fields to be irrigated. In addition to the construction of 225 m3 of check dams and 550 meters of irrigation channel, benefiting more than 3,960 people in three sub-villages.

2. Continuation of irrigation scheme (377 m) at Suco Lacoliu, Administrative Post, Baucau Municipalities

The construction of 377 meters irrigation channel, installation of 70 m3 gabions and implementation of complementary soil bioengineering interventions along the lined channel area provided benefits to more than 50 hectares of farmlands and directly and indirectly to more than 1,700 people in four sub-villages.

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3. Water source protection and irrigation scheme in Suco Uailili, Baucau Municipal Authority

Commencement : 16 August 2016 Completion : 31 March 2017 Value : $ 90,632,87 Contractor : Zeca Gariuai Unipessoal Lda Deign life : 15 years

Scope of Works − Rehabilitation retaining wall in water source – 47 meters − Construction of masonry irrigation channel of 576 m3 with length 800.20 m − Gabions installation for erosion control at source – > 100 m3 − 10 units check gate installation along the irrigation channel for water management and control − Bioengineering component/planting trees/grass to protect the retaining wall and erosion along gabion wall in the water source area Direct beneficiaries of the project − Total beneficiaries: 3,537 (Female: 1,711, Male: 1,826) − Number of Aldeias – 5 − Farmers: 15 − Number of hectares of farmlands: 10.30 ha

The existing farmlands in the area were being irrigated by means of a traditional earthen channel that was been used to convey water through an unlined irrigation channel from the water source and it was in existence since around 1995. Some sections of the channel were destroyed in 1997 and there has been no maintenance resulting in inefficient and unreliable water supply to farmlands. Farmlands located almost 500 meters to 1 km away could also not been cultivated because of inadequate water supply. At the water source, the community has been experiencing irregular and intermittent supply of water and contamination at the water source because of erosion and cattle coming every day to drink water at the source.

Photo: Irrigation Channel before and after construction, Suco Uailili Baucau Municipality

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Photo: Agia Water Source and Uailili Irrigation Scheme, Suco Uailili Baucau Municipality

The SSRI project intervention include the rehabilitation of 47 linear meters of masonry retaining and base slab at the water source, construction of irrigation channel 576 m2 with length 800.20 meters and over 100 cubic meters of gabions, and installation of 10 check gates for water management and control. The total coverage area for paddy fields is 10.3 hectares, and this intervention will benefit more than 3500 persons from five sub-villages with improved and efficient water supply for farmlands, clean water supply for domestic purposes and consumption, improved washing facilities and increased agricultural production and activities.

New farmlands more than 1 km away from the water source can now be cultivated since the lined irrigation channel conveying water along the farmlands. The water source is now protected from contamination with the cattle having a separate area for drinking and erosion of the banks has been addressed with the installation of gabions and rehabilitation of the masonry retaining wall. New and improved washing facilities has been constructed and more community members are using the facilities because of its convenience including significant number of women and children. There is now more reliable and clean supply of water for all activities including agriculture, cattle, and domestic purposes. Water is also collected by water tankers daily and transported to other villages and communities for domestic consumption and used for construction related activities and other uses. This project has contributed to several of the SGGs including 2 and 6.

Beneficiary - Mr. Amancio Fernando Freitas – Farmer in Suco Uailili “In that moment water is very scarce, but when the project came we feel much better...it makes our lives better, during the daylight we make beds for our plants such as cassava, corns etc. Now we feel very happy because we have plenty of water”.

Excerpts from interview with Minister of State Administration, H.E Dioniso Nabo Soares

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“This example in Baucau Municipality the project on water and sanitation and irrigation that was introduced to improve the irrigation system, and making sure the flow of water can go from the spring itself to the areas of cultivation of course, this has brought a new technology into the way people who have been traditionally used to work on their rice field and so on could profit more, and could benefit more from the water itself. And the fact that it also facilitates water and can be irrigated from time to time without having to wait like before on season - because of the dry season and the wet season. But with this irrigation system, it can of course help the water itself to be irrigated throughout the year and that would help a lot for the community to double the harvest and that would have an impact on the livelihood as well.

Also, making them understand about the climate change itself has brought some changes to how the spring is producing water but you can really save the water in such a way that’s why you can use throughout the whole year”.

Publication: Video on YouTube can be accessed at https://youtu.be/LGvfH9bGtZ4

8.9 River Embankments/flood defences

1. Kakae River embankment and gabion wall for flood protection in Suco Lisadilla of Maubara administrative post, Liquica Municipality

Commencement : June 2015 Completion : October 2015 Value : $133,418.25 Contractor : Luzeri Unipessoal Lda Deign life : 15 years

Scope of Works − 3-layer gabion wall of 435-meters length, earthen embankment behind gabion wall − Bio-engineering (planting vetiver grass, bamboo trees and gamal plants) Direct beneficiaries of the project − Total beneficiaries: 2,959 − Number of Aldeia – 2

During the rainy season, the entire community is at risk from flash flood and inundation because of high water level in the river. When flooding occurs, houses, schools, farms, water and sanitation services are considerably affected. The community is mainly vulnerable because of their geographic location; the land is lowland and relatively flat with the river cutting through the community. Previous recurring flooding have had extensive impact on the community’s social, economic and cultural activities. The situation has also been exacerbated because the community is unable to mitigate the effect of flooding and recovery can take very long after any typical flooding event. Despite the attempt by the community to construct a diversion for the flowing river, by raising the banks using traditional approaches, the result has been futile. Because of the flooding, the ecosystems, properties and resources were being destroyed.

In 2015 SSRI project undertook the implementation of the project intervention identified in the Municipality Investment Plan to address this recurring problem facing the community. The aim of the project intervention is to build on the existing coping mechanism initiated by the community to

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The project designed and constructed a three-layered 435 meters long gabion wall with a vegetated earthen embankment to protect more than 2,950 people from flooding. The complementary soil bioengineering including planting such as vetiver grass, bamboo trees and gamal planting on the earthen embankment that was constructed to support the gabion walls.

“Now, we are not worry anymore about floods because the gabion can protect us.” said Mr. Mateus Salvador, a Teacher of a Primary School located near the river. “This should be implemented in other villages too.”

Publication: TIMOR-LESTE: STAY CONNECTED Reducing Climate Risks, Building the Future https://undp-adaptation.exposure.co/timorleste-stay-connected

Mateus Salvador: “Now, we are not worry anymore about floods…” http://www.tl.undp.org/content/timor_leste/en/home/ourwork/environmentandenergy/successstori es/Disaster-Prevention/

8.10 Some Lessons Learned

1. Community Action Management Planning (CAMP). PDIM projects implemented by local contractors on behalf of MSA often suffer from a lack of community participation and ownership of both the process and product. If involved at all, the community’s participation is often limited to the provision of paid labour. For infrastructure to be taken care of, to be maintained and to last, more intense community involvement (through community consultations and dialogue) is necessary. Therefore, it is suggested to include the CAMP processes as part of the entire PDIM project implementation process. SSRI project has developed and using a methodology on all the SSRI supported projects and later can be replicated on other PDIM projects.

2. Fostering Community Ownership – Community ownership is a key factor to the success of climate resilient SSRI projects. The SSRI team has worked extensively with local authorities and beneficiaries to create the spirit of community ownership of the project. One particularly successful approach to engaging communities has been the participatory approach through Community Action Management Planning, where the designs for all projects are presented to the community before implementation. Relevant issues and

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related concerns raised by the beneficiaries are looked at and if these can be addressed within the budget and scope of the project, then the design is reviewed and revised accordingly to accommodate and address the community concerns.

3. Environmental Impact Assessment (EIAs) and Social Safeguards – Notwithstanding climate change impacts, implementation of infrastructure projects will have both positive and negative impacts on the environment and people’s social wellbeing. The likely positive and negative impacts (if any) need to be identified and assessed, avoided or mitigated. Therefore, SSRI aims at mainstreaming Environmental Impact Assessment and social safeguards into the PDIM process and guidelines thereby ensuring that all PDIM projects, have an environmental management plan to address potential negative consequences to the environment and people’s wellbeing.

4. Bio-engineering incorporation into designs and BoQs. As part of the measure to reinforce the resilience of infrastructure against climate variability impact and stabilise the watershed and landscape, SSRI supported infrastructure projects have included in the designs and BoQs the soil bio-engineering component as appropriate. This involves selection and planting species appropriate for different purposes such as water source protection, soil protection, river banks protection, slope stabilisation and agroforestry purpose species. The aim is to include bio-engineering features eventually into standard PDIM project implementation procedures.

5. Maintenance and sustainability – Even newly constructed small scale infrastructure is vulnerable to extreme rainfall events, causing erosion, landslides and flash floods. Due to this it is important that there is a strategy for harmonisation of the PDIM infrastructure into a maintenance programme and there is regular budget allocated for maintenance and enhancing the service life of the project. One example from SSRI is that all the roads constructed are harmonised with the maintenance programme under the Ministry of Public Works/ILO Rural Roads Master Plan for Timor-Leste.

8.11 Project Current and Potential Impacts

Impact on physical and financial assets The impacts of the SSRI project on rural communities includes enhancement of the value and derived benefits from existing community assets such as land, water, livestock and livelihoods, increased capacity of local communities to exploit potential economic opportunities and to develop stronger links with the markets and external partners, through the infrastructure improvements provided by the project. Efforts to strengthen local level organizations in the implementation of similar projects in the future is a key impact of the project and is evident by the local capacity to implement and use new climate resilient measures in the long-term. It is likely that the project has contributed to food security, livelihood enhancement and health and safety improvements where it has directly intervened.

The project is therefore having significant impact on the physical assets of rural communities through the implementation of structural measures that address climate risks. This impact is likely to be long-lived and will contribute to the advancement of socio-economic situation of the communities that use these infrastructure assets.

Environmental Impact Environmental degradation is very often a manifestation of poverty and the struggle for survival by the rural poor, and contributes to non-resilience to climate change and increased risk from climate- related disasters. The project has contributed to rehabilitation of the environment (particularly of

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There are many examples of positive environmental impacts of the project to date including the use of bioengineering techniques that reduce environment risks, catchment revegetation, water source protection (health impacts).

Impact on Institutions, policies, and the regulatory framework Existing institutions, policies and regulatory frameworks significantly influence the lives of the rural poor. Supporting the capabilities of existing national, and especially local public institutions in servicing the rural communities and reorienting the existing policies of institutions in favour of the poor is an increasingly expected result of development projects and is an expected outcome of this project. This encompasses the change brought about in sectoral and national policies affecting the rural communities and their exposure. In addition, the degree of decentralization, which allows decision making to be taken at the local level, is also a relevant consideration and important to this project.

The project is attempting to strengthen the PDIM process. The long-term impact of this institutional strengthening will result from the intervention in the process by the end of the project. This has the potential to truly embed climate risk considerations and resilience into the planning design and construction of small scale rural infrastructure. In general, the project efforts have already raised awareness to climate risks (through component 1), built some capacity to address these risks and demonstrated how to implement climate resilient infrastructure (component 3). A key area of focus needs to be the embedding of climate risk considerations into sector policy, and the project should leverage the evidence it can gather from the SSRI projects inform the wider policy framework. A detailed institutional capacity assessment has been undertaken at the end of the SSRI project and a long-term capacity development and training plan has been developed. This has been recently completed and the findings form the basis form the basis of the capacity development outputs to be undertaken for the GCF project.

Impact on Social Capital and Empowerment At community level the project is building capacity to identify climate risks and to identify climate resilient projects in the future. Thus, empowering communities and helping them to adapt to climate change. The project is contributing to gender empowerment by reducing time it takes for chores to be done by women (e.g. fetching water) and providing access to better hygiene and health through the supply of drinking water.

Impact on Food Security Water supply projects have added benefits for subsistence farming as water supply systems are not only being used for drinking water, but for ‘kitchen’ gardens for subsistence too. In addition, road stabilisation projects provide access to markets (both directions) and links communities thus allowing for greater trade and cooperation. With regard to food security, the irrigation projects at have the potential to provide increased annual productivity and yield to the communities that will have more secure water availability for their rice production.

Impact on Gender The project through the community engagement has sought to reflect the gender differentiated aspects of climate risks using single gender working groups when undertaking community-based risk mapping and disaggregated the data collected by gender.

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9. GAPS, BARRIERS AND NEEDS FOR SCALING UP GOOD PRACTICES FOR TRANSFORMATIVE CHANGE

9.1 Policy and Legislation

Incomplete policies, standards and regulations to govern climate resilient infrastructure development for the basic public services:

The policies and laws governing climate change are established, such as draft National Climate Change policy and DRM Policy as well as some sectoral policies that include consideration of climate change. However, there remains regulatory and legislative limitation in implementation of the climate change interventions prescribed in these draft policies. Moreover, there remains, several deficiencies and gaps in the enabling environment, which govern the implementation of infrastructure, which need to be addressed in order to embed climate resilience into the design, construction and maintenance of small scale rural infrastructure. National Disaster Risk Management Policy adopted in 2008, commits both the sectoral ministries and local communities, including suco (village) and aldeia (sub-village) chiefs to engage in both ex post and ex ante risk reduction. This policy covers a shift from traditional crisis response management to disaster, conflict, and climate change risk management. However, it remains too broad and is not guided by locally-specific information. In the absence of rigorous hazard and risk mapping as well as a damage accounting system, it is difficult to identify, plan, cost and budget for risk reduction investments, especially in relation to physical infrastructure. Furthermore, sector ministries and local administrations are not guided by detailed operation protocols to effectively implement disaster risk reduction and climate resilience measures. Thus, the infrastructure that is being built may increase levels of exposure and risks of adverse impacts.

9.2 Technical Capacity – National Institutions

Limited technical capacity to engineer climate proofing measures to infrastructure:

Climate risk information is currently lacking in Timor-Leste, which limits the ability of the relevant institutions to undertake climate change adaptation and disaster risk management activities in a comprehensive or consistent manner. Climate-induced hazard, risk and vulnerability maps are essential for the assessment of current and future hazards, for the identification of receptors such as infrastructure, people and agriculture at risk, and for the design of hazard management solutions that fully accounts for climate change. There is currently no definitive or accurate hazard and risk mapping for Timor-Leste and existing national scale hazard maps are of a broad-brush nature and do not provide the level of technical detail on which to base comprehensive climate risk adaptation and disaster risk management. The strategic assessment of risk to population, infrastructure, economic activity and to future development under conditions of climate change is a government priority to support and guide municipalities to wisely and rationally manage risk exposure to acceptable levels. The Climate Change and Biodiversity Centre (CCCB) under the Ministry of Commerce, Industry and Environment (MCIE) was established with a mandate to provide climate information services across all government institutions to facilitate climate responsive policies and decision-making. It is housed at the National University of Timor-Leste and benefits from the available research and administrative resources. However, such capacities remain nascent at this newly established institution.

The National Disaster Management Department (NDMD) sits within the Ministry of Social Solidarity (MSS) and requires comprehensive and robust hazard mapping as well as loss and damage data management systems to effectively fulfil its DRM mandate. In line with regional good practice, the Disinventar database is currently used for the collection, storage and analysis of Loss and Damage information and is the primary Disaster Risk Management Information System (DRMIS). Current

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I data collection uses a multi-sector hazard template to collect georeferenced information on the different hazards for different sectors including agriculture, infrastructure, education, health, preparedness and pre-disaster data and Loss & damage data which covers the post-disaster data. However, data collection is not systematic due to limited budgets, lack of modern data collection equipment and technologies and difficulty in accessing remote areas where disasters are sometimes concentrated. Hence the current DRMIS is not well populated and is underutilised as a result. MSS has started extending the DRMIS data on vulnerability through an ongoing UNDP project (Dili to Ainaro Road Corridor). However, there is a need for a systematic and sustainable approach to loss and damage data collection and updating and for a longer-term strategy.

A key requirement of loss and damages data collection is the knowledge of the location and condition of infrastructure and assets (or receptors) that are likely to be impacted by hazards and disasters. Undertaking comprehensive infrastructure asset inventory, asset condition inspection and asset management have not been systematically done in Timor-Leste, but the GFE-funded UNDP project - Small Scale Rural Infrastructure (SSRI) project – has started systematically collecting locational and condition data of all infrastructure at risk from climate hazards using methods that can be extended and incorporated into an infrastructure asset management system with further systematisation.

Technical capacity for compiling and analysing climate data for informing DRM practice – such as producing risk and vulnerability maps and forecast bulletins – is nascent. Much of the meteorological and forecasting data for informing climate risk and vulnerability are only available from regional centres such as the Regional Integrated Multi-Hazard Early Warning System for Africa and Asia (RIMES) or the Australian Bureau of Meteorology. Data products focused on Timor- Leste are not available. Planning institutions are therefore limited to inadequate and out-dated knowledge when planning for future climate change scenarios and climate-induced disasters. Neither are there innovative technologies for risk assessment (e.g. UAV drone technology for ground truthing and risk mapping, tracking changes in water flow through GPS coordinates, etc.) available or used. Moreover, DRM practitioners at the national and sub-national levels are not able to use seasonal and long-term forecasts of climatic conditions to inform probabilistic assessments of risks posed by climate-induced disasters to infrastructure and livelihoods. Without such risk assessments, tailored measures for disaster and climate risk management cannot be developed. Specifically, with respect to: i) climate risk assessments; ii) vulnerability assessments; iii) Physical Damage and Economic loss assessments; iv) training needs assessments; v) economic valuations that underpin different sectoral, national and subnational plans; and vi) contingency planning. Without these necessary skills, it will not be possible for effective planning and implementation of climate change adaptation to support important infrastructure in Timor-Leste. National Disaster Management Directorate’s capacity to manage disaster preparedness is particularly weak, especially when it concerns understanding and addressing larger area-based challenges such as land use changes, watershed deterioration, destructive agricultural practices and deforestation that create conditions for the evolution of hazards.

9.3 Technical Capacity – Sub-national Institutions

Weak institutions at the municipal and village level to plan, implement and maintain network infrastructure under the changing climate:

Already weak institutional functions and capacities are even weaker at district / municipal and village (suco) level. All stages of PDIM planning from the point of suco level prioritization, and reviews at administrative post and municipal levels and then clearances at the Ministries of State Administration and Strategic Planning and Investment through their joint technical committee must embed climate risk reduction criteria for decision-making. The PDIM manual currently do not include detailed guidelines for climate resilient infrastructure development. Furthermore, engineering skills and knowledge of climate proofing know-how is nearly non-existent. Equipment,

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Verification, Evaluation and Supervision (EVAS) engineers that support village and municipal infrastructure development investments under the Ministry of State Administration require targeted training in climate proofing, related technical engineering manuals and enforceable codes and standards to apply and adhere to. There is no Standard Operating Procedures (SOP) for infrastructure use and maintenance that considers emerging conditions of climate change. Spatially expressed risk information at various timescales is not available to the PDIM planners and engineers to reference their siting decisions, choices of construction materials and engineering designs in response to existing vulnerabilities and projected risks. Necessary skills in the use of Geographical Systems (GIS) to enable the use of hazard and risk mapping data is missing at municipal level. Climate risk informed PDIM and PNDS is critical for climate resilient development of local communities and infrastructure services.

9.4 Financial Capacity

Limited financial capacities or finance options for climate resilient community and infrastructure development at sub-national level:

When planning and implementing infrastructure investments through municipal / district and village development planning mechanisms broader landscape and ecosystem functions are not considered as a viable strategy to safeguard the investments. In both the short- and long-term, investments in ecosystems can protect and sustain built infrastructure and human livelihoods. However, the allocation of development resources in Timor-Leste is focused on physical infrastructure. Consequently, the value of watershed management approaches to climate risk management is overlooked. The local planning process does not consider management of watersheds, especially where areas requiring management are larger than individual sucos (villages). In such cases, watershed management activities would not be considered in the suco plans nor be brought up to the district plans. In addition, the Department of Forestry has a limited budget for reforestation and watershed management activities. As a result, there is a limited implementation of landscape stabilisation, erosion control, sediment control and drainage control. Neither are there financial incentives for local communities to rehabilitate degraded watersheds and adopt land-use and livelihood practices that contribute to sustainable management of land and watershed forests. Thus, substantial areas of land have been cleared of vegetation in Timor Leste and under-utilized. At least 30 percent of land area is suitable for tree growing. However, this potential is not used to stabilize the land, reduce hazard risks to the communities and infrastructure and unravel socio-economic potential of community agro-forestry. Furthermore, current PDIM and PNDS do not have funding criteria or requirement to embed additional cost of climate proofing of infrastructure. These only follow the annual investment planning cycle and are not conducive to embed long term adaptation objectives. However, there are policy requirements to integrate climate and disaster risk management into these decentralized planning mechanisms that requires adequate enforcement capacities.

The Strategic Development Plan for Timor-Leste (SDP 2011-2030) outlines the government’s strategy for implementation of infrastructure to be built over the 20-year period. Government expenditure on roads and bridges has doubled in absolute terms, but only increased slightly in percentage (of total budget) terms between 2008-2013 and 2014-2018. Both irrigation and water and sanitation have increased substantially in absolute terms, and increased in percentage terms over the period. The roads and bridges prioritised for government expenditure are mainly national and regional roads, which leaves a major deficit in investment in rural roads and bridges.

Rural Infrastructure have been implemented via the decentralised PDIM and PNDS schemes, which are centrally funded but managed and implemented at the municipal level since 2011. Government investment in rural infrastructure under the PDIM and PDNS processes, has been steadily decreasing over the past 4 years and is currently less than 1/10 of its peak value in 2012, due to a change in government priorities and a focus on national and regional infrastructure rather

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I than rural small scale infrastructure. In addition to reduced government budgets, there is a reluctance to invest perceived higher costs into climate resilient infrastructure. On average 429 projects have been implemented annual under PDIM between 2011 and 2016 but the number of project being implemented under PDIM in 2017 is 44.

Currently, climate resilient small-scale infrastructure is being implemented only on a donor-funded project basis and on IFI-funded large scale (national) projects, where climate resilience is linked to donor financing requirements. However, there remains a shortfall which is leaving rural communities exposed, under-developed and unable to respond to climate change risks. As a result, there is no consistent approach to implementing climate resilient infrastructure and no evidence of government-funded projects (rural or national) implementing climate resilience measures due to the perceived additional cost in including climate resilience. SSRI project is the only project which has sought to embed climate resilient methods within the planning process by influencing the PDIM and PDNS processes to include climate risk considerations in the identification, design, implementation and maintenance of rural infrastructure. The SSRI project has resulted in many successful examples of implemented climate resilient infrastructure and provides several good-practices and lessons learned, which can be scaled up to further embed climate resilience into the systematic planning and implementation of small-scale rural infrastructure.

Land degradation, Catchment Management and livelihood pressures In addition to the climate induced hazards impacting rural infrastructure, land degradation due to poor land management practices is intensifying hazards in the catchments upstream of rural infrastructure, further endangering the infrastructure.

Livelihood challenges leading to over-exploitation of land and forestry resources and increasing land degradation, means that communities living within the catchments of rural infrastructure are inadvertently contributing to the degradation of catchment and hence increasing the risks to rural infrastructure.

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These barriers combined hinder the development of particularly vulnerable communities and their physical and economic assets in the face of climate change. The proposed project strategy takes a barrier-removal approach and delivers the following outputs and impacts.

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9.5 Theory of Change

Timor-Leste is investing in the development of its infrastructure, but not with a focus or pace that meets the urgent development needs of more than 70% of its population which lives in rural areas.

The underlying causes of the current baseline conditions is that, firstly there is a lack of climate risk information for undertaking climate risk-informed sectoral planning and decision-making of rural infrastructure and all sectors that impact on the resilience of rural infrastructure. This is due to limited financial, technical and human capacities to undertake hazard, risk and vulnerability assessment and limited ability to assess the socio-economic damages and losses that can occur due to hazards and to use such information in prioritizing CCA and DRR activities. Secondly, the sectoral legislative and enabling environment does not currently take a risk-informed cross-sectoral approach to addressing and incorporating climate change considerations which has resulted in poor spatial planning land use water resource management and disaster risk management. All of which are integral to the planning and development of climate resilient infrastructure.

Government investment in infrastructure development, thus far, has been focused on larger scale infrastructure leaving a large deficit in essential rural infrastructure. The limited investment in rural infrastructure has been reducing since the establishment of the PDIM and PNDS rural planning processes, since 2012. In addition, the investment in rural infrastructure has been based on design methods which do not take climate change into consideration despite the already observed trends of increasing susceptibility to hydrometeorological hazards, which have already resulted in loss of critical infrastructure, loss of livelihoods and increased exposure to hazards. Furthermore, infrastructure development thus far has not taken account of the current requirement for maintenance nor future requirements under climate change, and does not allocate sufficient budgets for maintenance, Unstainable and environmentally deleterious rural livelihoods have resulted in significant land degradation of all catchments in TL and will increase exposure of people, and infrastructure to climate-induced hazards, and will further impact rural livelihoods.

In order to achieve transformational change, the project will address the underlying lack of climate risk information for undertaking climate risk-informed sectoral planning and decision-making of rural infrastructure and all sectors that impact on the resilience of rural infrastructure by improving the financial, technical and human capacities to undertake hazard, risk and vulnerability assessment, to assess the socio-economic damages and losses that can occur due to climate-induced hazards and to use such information in prioritizing CCA and DRR activities. This will be done through the introduction of modern methods and technologies for hazard and risk assessment and mapping, supported by standards and guidelines that enable systematic use of climate risk information in the design and implementation of infrastructure and the management of climate-induced hazards in the future. Engineering capacities will be enhanced, through the introduction of new methods of designs, materials and technologies that are locally appropriate and will include innovations such as bio-engineering methods. The project will strengthen the sectoral legislative and enabling environment to take a risk-informed cross-sectoral approach to addressing and incorporating climate change considerations into spatial planning land use and water resource management and disaster risk management. All of which are integral to the planning and development of climate resilient infrastructure. The project will address the underlying limited and declining investment in rural infrastructure through the PDIM and PNDS rural planning processes, and the perceived higher cost of including climate resilience into infrastructure development by embedding infrastructure investment planning by the introduction of evidence based cost benefit analysis into design methods which takes climate change into consideration and identifies current and future requirements for maintenance under climate change, identifies cost of climate proofing as well cost of maintenance. In addition, the project addresses the effects of unstainable and environmentally deleterious rural livelihoods that

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I have resulted in significant land degradation of all catchments in TL and which increase exposure of people, and infrastructure to climate-induced hazards, and will further impact rural livelihoods. In addressing catchment management, the project is further building resilience into infrastructure development and reducing the long-term cost of infrastructure maintenance.

Figure 9-1 presents the Theory of Change of this project and demonstrates how the current barriers can be removed through the project activities to achieve transformational change in infrastructure development which will result in increased resilience to infrastructure and the built environment, as well as increased resilience and enhanced livelihoods of the most vulnerable people, communities and regions of Timor Leste.

In summary, with GCF funding the lack of climate risk information for CCA and DR will be addressed, the sectoral policy and legislative framework will be strengthened by embedding climate change considerations into all sectors that impact the resilience of infrastructure, CCA and DRR, and institutional capacity at central and local level will be built to enable long-term use of climate risk information, methods and tools in the planning and investment in rural infrastructure, and in the development of CCA and DRR activities. Furthermore, livelihood pressures that lead to land degradation will be addressed through the introduction of climate smart agro-forestry and reforestation in catchments within which infrastructure will be developed thus providing essential over-arching eco-system ased protection for the infrastructure, reduced maintenance requirements in the long-term and reduced exposure of communities and their assets to climate induced hazards. The preferred solution provides the clear link between activities that are seeking to address CCA and DRR (as per the new CC and DRM laws) and the development of rural infrastructure (as per the SDP). The preferred solution will bring about transformative change in the way in which Timor- Leste plans and develops rural infrastructure in the future and will safeguard infrastructure and livelihoods.

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Figure 9-1: Theory of Change of the project

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Preferred option with GCF Project

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9.6 Project Logical Framework

H.1.2. Outcomes, Outputs, Activities and Inputs at Project/Programme level

Target Assumptions Means of Verification Expected Result Indicator Baseline (MoV) Mid-term (if Final applicable) Project/programme Outcomes that contribute to Fund-level impacts outcomes A5.0 Strengthened institutional A 5.1 # of Institutional and Gazette of Register of Outdated Mid-term – 6 national Government commitment to embed climate risk and regulatory systems for regulatory systems that improve regulations, register of sectoral policies, regulations, information in sectoral policies and legislation climate responsive planning incentives for climate resilience institutional guidelines for revised methodologies Political will to implement relevant legal- and development and their effective implementation methodologies and infrastructure and guidelines for CR regulatory reform and to establish cross- guidelines development infrastructure adopted sectoral CC platform that do not Mid-term – 6 national include policies, regulations, climate risk revised methodologies consideration and guidelines for CR s infrastructure adopted A7.0 Strengthened adaptive A7.1: Use by public-sector services Monitoring and Evaluation Mid-term - 100 staff in Government commitments to secure adequate capacity and reduced exposure staff of Fund supported tools, reports at mid-term and MSA, MSS and MAF in O/M of relevant software and databases are to climate risks instruments, strategies and final central and local fulfilled on a continuous basis both during the activities to respond to climate government using new project implementation and afterwards change and variability tools and technologies Capacities built across relevant agencies Final - 200 staff in MSA, through the project are maintained and MSS and MAF in central periodically updated and local government using new tools and technologies

A7.0 Strengthened adaptive A 7.2 # of males and females Project baseline, mid- 33,000 Mid-term – 75,000 There is continued commitment and uptake of capacity and reduced exposure reached benefitting from climate- term and end term beneficiaries beneficiaries direct the information by targeted communities in the to climate risks resilient infrastructure. surveys in 3 of the beneficiaries (51% male, project target 49% female) of the 31

municipalities climate resilient where SSRI infrastructure assets has been Final - 175,840 direct implemented beneficiaries (51% male, 49% female) of the 130 climate resilient

infrastructure assets

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Gender-sensitive field Mid-Term - Total direct surveys undertaken within and indirect beneficiaries: the targeted sub- 261,000 (51% males, 49%

catchments and districts. female) beneficiaries Final - Total direct and indirect beneficiaries: 522,000 (51% males, 49% female) beneficiaries

Project/programme Outputs that contribute to outcomes outputs 1. Climate risk information is 1.1 # of hazard risk maps and Project reports, Coarse 4 sets of national hazard Government commitments to secure adequate developed, monitored and information developed and evaluation reports, site resolution maps covering all of Timor O/M of relevant software and databases are integrated into policies, adopted/ embedded into sectoral observations, databases, UNDP Leste for floods, landslide, fulfilled on a continuous basis both during the regulations and policies and legislations monitoring and risk indicative erosion and drought (to be project implementation and afterwards assessment products national completed before mid- Capacities built across relevant agencies institutions to inform hazard maps term) through the project are maintained and climate resilient small- for 4 major periodically updated scale rural infrastructure hydromet Relevant government agencies cooperate on planning and hazards the development of hazard maps (MSS, MAF, management MCIE, MPWTC etc.). Government commitment to embed climate risk information in sectoral policies and legislation Political will to implement relevant legal- regulatory reform and to establish cross- sectoral CC platform 2. Climate risk reduction and 2.1 # of infrastructure units built to Project reports, 13 units per 13025 climate resilient Political will to revise PDIM and PNDS climate-proofing new climate resilient standards evaluation reports, site year non- infrastructure units processes to include CR considerations measures for small-scale observation, databases, climate (mid-term – 31 Effective embedding of CR infrastructure rural infrastructure are construction supervision proofed 20 roads; 11 water supply design standards at municipal level and asset inspection infrastructure units; Government commitment to long-term implemented to build the reports, monitoring and in each of the investment in CR infrastructure resilience of vulnerable risk assessment products 6 target Final – 130) Government commitment to implementation of communities in six priority municipalities 38 water supply units, 25 long-term catchment agroforestry and districts Irrigation system, 20 flood reforestation strategy introduced by project protection units. 47 Rural Agroforestry introduced to local communities roads. will lead to alternative sustainable CR 2.2 # Hectares of agroforestry Project reports, Deforestation Mid-term – 75 hectares livelihoods that lead to reduced land implemented in target evaluation reports, site rate of 1.16% Final – 300 hectares degradation infrastructure catchments observation, databases, per year Government commitments to secure adequate construction supervision O/M of 130 infrastructure units are fulfilled on a and asset inspection

25 49% of assets will be implemented using government co-financing

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reports, monitoring and continuous basis both during the project risk assessment products implementation and afterwards Capacities built across relevant local government organisations through the project are maintained and periodically updated Relevant government agencies cooperate on development and implementation of CR infrastructure (MSS, MAF, MCIE, MPWTC etc.). Activities Description Inputs Description This activity includes data generation and analysis, modelling, Setting up of the project GIS (SDI system), engagement of production of hazard, risk and vulnerability mapping and related national expert, travel-related costs, data review and data training and capacity, This activity will develop risk modelling modelling inputs, GIS work, printing and production of and actionable risk information production capacities by reports and maps; project management. implementing the following: Data gathering and organisation into project GIS (SDI 1.1.1. Establish a project Spatial Data Infrastructure (SDI) and system), various data gathering, physical (e.g. topographic provide project GIS support throughout. and geological) surveys. Survey teams (contractors) Input will include cost of local and international experts, MSS staff, travel-related costs, GIS work, printing and production of reports and maps; project management. Flood hazard and risk maps will be developed in line with international best practice. Accurate digital elevation models 1 International and 1 national (DEM) in the form of LiDAR will be used for all modelling. GIS consultant to develop and Topographic survey of rivers through high risk areas will be establish SDI, undertaken. Historical hydro-hydrometric data for all Timor 1.1. Develop and deliver Consultants, Contractors, Leste required for all hazard and risk assessments will be climate risk knowledge and Training, Workshops and utilized. vulnerability mapping to all conferences Training workshops for MSS practitioners sectoral institutions Input will include cost of local and international experts,

travel-related costs, cost of international experts.

Development of the risk and vulnerability surveying tool.

Engagement of teams to undertake socio-economic surveys Input will include cost of local and international experts, travel-related costs, cost of international experts. Development of the GIS-based risk and vulnerability modelling tool based on hazard data, physical data (receptor data), socio-economic data from new survey methods Training of MSS and municipality staff in socio-economic survey tools (workshops) and engagement of teams to undertake socio-economic surveys 1.1.2 Data gathering, data digitisation systematization, storage Data gathering and organisation into project GIS (SDI and analysis within the SDI GIS system for use in hazard and system), various data gathering, physical (e.g. topographic 2x Consultants for surveys, risk analyses to support the hazard and risk modelling and and geological) surveys. Survey teams (contractors) TOT Training. mapping. Undertake detailed surveys for all hazard modelling

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Purchase of software for Purchase of modelling software for hydrological (flood and 1.1.3 Procure modelling software, databases, hardware for hazard, risk and vulnerability drought), hydraulic (flood), erosion modelling multi-hazard modelling to be embedded in MSS modelling and mapping

Input will include cost of local and international experts, 1.1.4 Using the most appropriate modelling techniques, International and national MSS staff, travel-related costs, GIS work, printing and establish numerical models for flood modelling, landslide and consultants to provide TA to production of reports and maps; project management. erosion and drought for all major river basin in TL based on undertake hazard, modelling Flood hazard and risk maps will be developed in line with surveys of the physical characteristics of the river basins. and mapping. international best practice. Accurate digital elevation models Produce high resolution hazard maps (DEM) in the form of LiDAR will be used for all modelling. Topographic survey of rivers through high risk areas will be undertaken. Historical hydro-hydrometric data for all Timor Leste required for all hazard and risk assessments will be utilized. 1.1.5 Deliver training in hazard modelling to at least 20 Training workshops for MSS practitioners practitioners at national and local government level and identify Training, TOT training. long-term training needs

Input will include cost of local and international experts, 1.1.6 Develop and codify methods and tools for undertaking Socio-economic vulnerability travel-related costs, cost of international experts. socio-economic surveys to collection necessary information to survey methods and tool Development of the risk and vulnerability surveying tool. fully map the socio-economic conditions of the rural poor within development the catchment; Using the methods developed, undertake detailed socio-economic surveys for 6 target municipalities in TL Engagement of teams to undertake socio-economic surveys Socio-economic vulnerability 1.1.7 Undertake socio-economic and vulnerability assessment surveys to fully map existing vulnerability within TL

Input will include cost of local and international experts, 1.1.8 Develop a GIS-based tool to integrate various spatial travel-related costs, cost of international experts. socio-economic data with the hazard maps, perform Development of the GIS-based risk and vulnerability vulnerability assessment, produce vulnerability maps which will Development of risk, modelling tool based on hazard data, physical data include damages and loss of life estimates and to test risk vulnerability, and CBA tool (receptor data), socio-economic data from new survey management interventions options. Tools, methods, guidelines methods and procedures for recording disaster events, undertaking post- event surveys

Training of MSS and municipality staff in socio-economic Training in socio-economic 1.1.9 Develop and deliver a training programme in socio- survey tools (workshops) and engagement of teams to modelling methods and tools economic modelling methods and tools to MSS staff undertake socio-economic surveys 1.2. Establish a database This activity includes strengthening systems for monitoring and system for monitoring and recording climate induced disaster events. Estimation of the Hover Drones x 6 (1 per pilot recording information on economic damages caused by climate change induced events Municipality) Fixed wing Drone climate induced damages in and establish a database management system to monitor x 1. including training and order to inform climate risk damages over time. spare parts

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1.2.2 Review of existing damage and loss databases and International and national Includes collection of asset register datasets, validation, accounting technologies (Disaster Risk Management Portal, consultants to develop and data cleansing, conversion. Development of mobile GIS- SIGAS accounting system, and Desinventar database). implement a harmonized and based asset condition inspection methods and tools. Development and implementation of a harmonized and unified unified damage and loss International and national expert inputs for development of damage and loss recording and accounting system in the form recording and accounting asset management system and engineer link to unified of a Disaster Risk Management Application (DRMApp) which system in the form of a damage and loss database. Input from MSS to the will provide a real-time system to all tracking the observation Disaster Risk Management development in introduction of guidelines. data, verification data and compensatory responses, including a Application (DRMApp), International and national expert inputs for development of Metadatabase to collate and track disparate reporting. development of electronic asset management system and engineer link to unified Available at National sub-national and municipal and suco level. (online, mobile handheld damage and loss database. DRMapp will include development of electronic (online, mobile proformas etc.) and manual Input from MSS to the development in introduction of handheld proformas etc.) and manual damage and loss damage and loss recording guidelines. recording templates templates

1.2.3 Develop and implement an infrastructure asset Procurement of asset Training of MSS, MSA and municipality staff in asset management system linked to Damage and loss database. management system. condition inspection. International expert inputs to train Introduce asset inspection guidelines, methods and approaches Collection of asset register MSS staff on asset management system and damage and 1.2.4 Develop and deliver a training programme in damage and loss database datasets, validation, data loss and asset management methods and tools to MSS staff cleansing, conversion.

Development of mobile GIS- based asset condition inspection methods and tools. International and national expert inputs for development of asset management system and engineer link to unified damage and loss database. Input from MSS to the development in introduction of guideline. Training (D&L, asset management system)

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1.3 Refine ordinances, regulations and associated This activity includes developing enabling conditions to create Development of a climate change strategy for gender in the codes and standards to an enforceable policy framework for climate resilient small-scale Consultants, Contractors, context of prioritization of small scale infrastructure enable climate proofing infrastructure development. This will be delivered by Training, Workshops and development. small-scale rural implementing the following: conferences infrastructure 1.3.1 Develop Gender Responsive Climate Change Strategy International and national and Action Plan which encompasses the priorities endorsed in experts. Extensive the national documents as indicated in the upcoming National stakeholder consultations Climate Change Policy.

1.3.2 Review and revise all standards, guidelines and International and national experts. Extensive stakeholder Review and revise standards, specifications for rural infrastructure, encompassing both consultations guidelines for rural technical and functional standards to respond to climate risk infrastructure reduction requirements, based on international best practices.

Develop and embed climate resilience measures into a 1.3.3 Input to the development of the Rural Roads Master Plan International and national rural resilient roads plan & Investment Strategy 2016–2020 to help embed climate experts. Roads Department resilience measures into road master planning. (4RD) staff

1.3.4 Input to the development of a National Water Supply Development of a plan for resilient rural water supply Policy and Strategic Plan to provide the medium to long-term vision for the sector and to provide a framework for the International and national institutional arrangements, overall operation and management experts. MPWTC staff of DNSA and coordination with other sectoral agencies and partners, to ensure that climate resilience approaches are embedded in the policy and strategy for water supply

1.3.5 Develop guidelines and SOPs for all infrastructure Develop guidelines for embedding climate resilience International and national investments to be carried out under the municipal (PDIM) and measures into PDIM and PDNDS rural infrastructure plans experts. MPWTC, training of village (PNDS) development plans to make these plans climate municipality staff responsive

International and national Develop plan for capacity building for climate resilient rural 1.3.6 Develop a capacity building plan and roadmap for national experts. infrastructure and regional authorities to integrate new policies, plans and strategies and guidelines into PDIM and PNDS. This would include the development of tools that will be needed for International and national implementation and enforcement of new methods and experts. guidelines for CR infrastructure development planning and implementation Training 1.3.7 Implement capacity building and training based on CDP for national and regional authorities

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Provide training on climate and disaster risk management 1.3.8 Support the National Institute for Public Administration (INAP) to implement Disaster Risk Management Training Training Manual, which has recently been launched by Ministry of Social Solidarity and INAP. 2.1 Climate risk reduction This activity includes the Introduction of climate risk screening Consultants, Contractors, Development and codification of detailed methodologies for measures for small-scale methods and embed climate risk reduction criteria across PDIM Training, Workshops and incorporating CC considerations into risk assessments, rural infrastructure are fully and PNDS planning and decision-making cycle. Under this conferences, materials and strategies, policies and plans for all infrastructure relevant integrated into the planning activity the project will provide step-by-step guidelines for goods sectors using international best practice. and budgeting cycles of climate risk reduction measures for all categories of small-scale Village and Municipal rural infrastructure through PDIM manual – CAMP; Community- development plans based management and maintenance – GMF manual, KAM – municipal procurement guidelines and administrative post and the Ministerial Technical Committee review checklists. The following will be implemented: 2.1.1 Develop step-by-step guidelines for climate risk reduction measures for all categories of small-scale rural infrastructure Consultants to provide TA for (water supply, road and bridges, irrigation, flood defences) development of step-by-step through PDIM manual – CAMP; Community-based guidelines for climate risk management and maintenance – GMF manual, KAM – reduction measures for all municipal procurement guidelines and administrative post and categories of small-scale rural the Ministerial Technical Committee review checklists infrastructure through PDIM

2.1.2 Train team of technical staff of Equipment Verification, Training, Workshops and Training Evaluation and Supervision (EVAS) to determine the likelihood conferences and consequences of risk in relation to asset (infrastructure exposure and vulnerability). Their skills to engineer climate resilient designs and apply various methods of bioengineering (e.g. by use of local vetiver plants to stabilize the slopes and gabion structures) will be developed

2.1.3 Provide technical assistance to Administrative Post (AP) Training and technical TA staff in prioritizing projects at this level and in undertaking an assistance to AP staff in appropriate level of feasibility studies on which to base climate- climate resilient project risk informed project prioritization. prioritisation and feasibility studies 2.1.4 At municipal level, introduce climate risk criteria into the Training and technical TA and municipal engineering input using new CBA prioritization process, and include other methods of measuring assistance to municipality staff methods for project prioritization. benefits of projects based on the introduction of appraisal-led project prioritisation using socio-economic cost-benefit analysis Detailed CBA of 130 infrastructure projects methods and tools to be developed under Activity 1.1. Undertake detailed CBA for 130 prioritised infrastructures projects in 6 target municipalities. Provide capacity development to enhance the ability to undertake engineering

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feasibility studies and incorporate climate-risk considerations into technical feasibility

2.1.5 Introduce investment feasibility considerations, socio- Training and technical International and local experts economic cost-benefit analysis, optioneering and options assistance to municipality staff appraisal methods as well as environmental impact assessment that integrate climate change impact scenarios, to strengthen the feasibility process, safeguard investments and optimize engineering solution. Develop long-term municipality investment plans for PDIM and PNDS 2.1.6 At the detailed design level, technical assistance will be Training and technical International and local experts provided to introduce climate change considerations into design assistance to municipality staff of infrastructure to ensure that they will accommodate likely changes of environmental variables (frequency and intensity of occurrence) expected with climate change. Environmental impact assessment (EIA) will be introduced at the detailed design stage, in line with international good practice

2.1.7 Train municipality engineers in the new climate-risk Training and technical Training informed infrastructure detailed design methods and include assistance to municipality staff specific training in the design of bio-engineering methods relevant to Timor Leste. Bioengineering training will be done through technical assistance and by providing dedicated trainings on bio-engineering.

2.1.8 Introduce processes for pre-qualifying contractors, based Training and technical Development of pre-qualification criteria, training of on specific criteria such as certification in prior trainings on assistance to municipality staff contractors in CR methods implementation of climate-resilient projects, experience of implementing climate-resilient projects, experience of contract management of such climate-resilient projects and access to engineering expertise aligned with the types of climate resilient measures to be built into infrastructure (such as bioengineering methods) 2.2 Implementation of This activity will carry out the investment component as part of Detailed design, procurement Engineering inputs to detailed design, procurement and climate-proofing measures the decentralized investment programmes of PDIM and NPDS and implementation of 130 implementation of 130 infrastructure schemes (TA, for small-scale rural and will embed climate resilient practice. Small-scale rural infrastructure including TA of municipal input, international experts, community infrastructure infrastructure in the target districts and villages will be climate international and national engagement, bill of quantities development, procurement proofed. experts, community process, construction supervision, construction hand over) 2.2.1 Detailed design and construction of 130 CR infrastructure engagement, preparation of bill projects of quantities development, input to procurement process, construction supervision, construction hand over. Safeguards expert (international consultant) for implementation of the ESMF

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Procurement and implementation/construction infrastructure units (multiple contracts) Procurement of services for O&M for years 3-6 of project implementation (multiple contracts) Purchase of six motorbikes and 4 vehicles in support to project implementation, 2 DSLR camera and other related communication equipment International and national consultants National experts for oversight and supervision - (2 engineers @ $114096) = $228,192

2.3 Supporting catchment This activity includes scaling-up climate resilient catchment Consultants, Contractors, International and local experts providing assistance to MAF management and management in order to reduce the exposure of communities Training, Workshops and to develop strategy. MAF central and local government input rehabilitation measures to and their physical assets, such as rural infrastructure, to conferences, materials and to development of strategy, Capacity Building, Site enhance climate resilient climate-induced hazards. The following will be implemented: goods Assessment and Planning infrastructure and 2.3.1 Develop agroforestry and reforestation strategy for communities infrastructure sub-catchments Techncial Assistance to MAF

2.3.2 Implement agroforestry and reforestation strategy for infrastructure sub-catchments Local Labour for land Seedling Production, Land Preparation and Out-Planting, preparation, planting etc. Monitoring and Reporting, Farmer Registration, Farm Maintenance of agro-forestry Registration, Product Registration (if the farmers decide to plantations go purely organic), Tree Registration and Certification Purchase of seedlings

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10. PROPOSED INTERVENTIONS TOWARDS ACHIEVING RESILIENCE OF COMMUNITIES AND SAFEGUARDING THEIR PHYSICAL AND ECONOMIC ASSETS IN THE FACE OF CLIMATE CHANGE

10.1 Project objective, outputs and impacts

The climate induced problem that the project is seeking to address is that Local Administrations, particularly in the areas vulnerable to extreme hydrometeorological events, are finding it increasingly difficult to supply and maintain critical small scale rural infrastructure for rural communities, leading to measurable reductions in household income as well as increased food insecurity and health issues. The project is also seeking to address climate induced threats caused by the slowly decreasing protective and water storage functions of ecosystems in particularly vulnerable catchment areas.

The project objective is to safeguard vulnerable communities and their physical and economic assets from climate change induced disasters. The proposed project aims to address the above barriers and shift the baseline scenario towards climate resilience.

The project will first, strengthen capacities of mandated institutions to assess and manage the risks of climate induced physical damages and economic losses. GCF funds will be used to embed new technical skills, improve availability of risk information and create effective response mechanisms. Second, the project will invest in small-scale rural infrastructure to ensure their resilience to climate change induced hazards. GCF funds will be used to improve engineering skills and practices for climate proofing of rural infrastructure that are essential for the reduction of prevalent social vulnerabilities and widespread economic disparities. Investments in roads & bridges will address community isolation that is critical to overcome during the extreme climate events and disasters; water supply and irrigation will address risks of changing water availability patterns and especially drought events; drainage and flood protection will create water flow control and flood risk management infrastructure. These infrastructure units will be established as the means to address adaptation deficit where the social vulnerabilities and exposure to climate risks are particularly high. The project will utilize municipal finance mechanisms (e.g. municipal investment plans) to address the increasing costs of infrastructure development under the conditions of climate change. As discussed above, the need of infrastructure investment over the coming decades is enormous in Timor- Leste. Climate change does not alter that need, but may increase its cost. With GCF funding financial mechanisms to absorb such costs will be established. Third, the project will invest in livelihoods and land use management that is conducive to a long-term resilience of the target communities and their physical and economic assets. The project will enable land use and livelihoods that benefit from agro-forestry and forest products and contribute to forest rehabilitation and maintenance. The project thus will support landscape restoration and land stability as an investment to climate risk reduction and long-term resilience.

The following complementary outputs will be delivered: 1. Policies and institutions strengthened to enable climate resilient small-scale rural infrastructure development and climate risk reduction in the particularly vulnerable communities; 2. Climate resilient small-scale rural infrastructure deployed to benefit 175,840 people across six priority districts.

10.2 Proposed GCF Project Outputs

Output 1: Policies, regulations and institutions strengthened to enable climate resilient small- scale rural infrastructure development and climate risk reduction in the particularly vulnerable communities.

This output will address the gaps in policy, regulations, and institutional capacity to deliver climate resilient small-scale infrastructure. It will do so by addressing gaps in the climate risk knowledge base through the

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I development and introduction of hazard, risk and vulnerability assessment and mapping methods, technologies and tools, and capacity development within the main central government institutions involved in climate change adaptation and disaster risk management. Climate-induced hazard, risk and vulnerability maps are essential for the assessment of current and future hazards, for the identification of receptors such as infrastructure, people and agriculture at risk, and for the design of hazard management solutions that fully accounts for climate change. There is currently no definitive or accurate hazard and risk mapping for Timor-Leste and existing national scale hazard maps are of a broad-brush nature and do not provide the level of technical detail on which to base comprehensive climate risk adaptation and disaster risk management. The strategic assessment of risk to population, infrastructure, economic activity and to future development under conditions of climate change is a government priority to support and guide municipalities to wisely and rationally manage risk exposure to acceptable levels. The project, under this output will also address gaps in the legislative and policy framework by supporting the elaboration of policies, legislation, guidelines and standards to embed climate change considerations across all sectors relevant to infrastructure development and facilitating the dissemination and sharing of the common and definitive climate risk information which all sectors will need to embed climate risk considerations into their functions. The Climate Change and Biodiversity Centre (CCCB), established under the SSRI project, has a mandate to provide climate information services across all government institutions to facilitate climate responsive policies and decision-making and to undertake capacity building of government practitioners. The project intends to build the capacity of the CCCB to embed necessary skills training (ToT) for long-term sustainable delivery of the key aspects of the capacity development plan.

Activity 1.1. Climate risk knowledge base developed and climate information services developed and delivered to all sectoral institutions.

GCF Intervention: The GCF project will help develop and deliver climate services such as climate hazard and risk and vulnerability assessments, cost-benefit assessments for adaptation solutions and related training to responsible public servants across mandated institutions. The capacity of National Institute for Public Administration (INAP) is being developed to provide DRR and CCA related training to all the public servants. UNDP with MSS has developed DRM Training Manual consisting of 14 modules which is being reviewed to be included into the INAP’s regular training material. Project will provide targeted support to INAP in enhancing its DRR and CCA capacity, to enable the institution to function as one of the strong training institutes in the country.

The hazard and risk maps, will be used for risk-informed decision-making for all aspects of development and risk management in the future. Uses will include development planning for zoning of development activity away from high hazards areas to avoid physical damages to people, property and losses to economic activity, as the basis for the development of multi-hazard early warning system, development of emergency preparedness and response plans, raising public awareness and improving community preparedness. Importantly the hazard maps will provide the basis for the management of climate-induced hydrometeorological hazards across all sectors, in Timor-Leste now and in the future.

The project will also develop a bespoke GIS-based socio-economic risk model as a tool for risk assessment, cost-benefit analysis and the identification and appraisal of climate resilient intervention measures for strategic planning in the future. The hazard maps to be developed will be used in combination with infrastructure (bridges, roads and buildings), land use (settlements, agriculture, grazing lands, and conservation areas), property and socio-economics data, to model the socio-economic impacts of each hazard and produce vulnerability maps. This vulnerability map, based on the accurate hazard mapping of the current situation will form the baseline. Large hydrometeorological events in Timor-Leste often results in losses to infrastructure, particularly roads and water supply, losses to agriculture and damage to property, along with concomitant social effects associated with loss of potable water and agricultural productivity. The baseline model will form the basis of future appraisal-led disaster risk management and risk-informed infrastructure planning. Central government DRM, CCA and infrastructure practitioners will be trained in the use of the hazard and risk models developed and importantly, capacity will be built to enable the

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I updating and maintenance of the models. Municipality engineers will also be trained in the use of the models for appraisal-led infrastructure planning.

Local field officers and village youth leaders will be trained in surveying techniques including the use of global positioning systems (GPS) to undertake topographic surveys which will be required to produce flood risk maps and other community-based mapping for development, calibration and validation of the hazard maps. GPS will also be effectively used to record the coordinates of the infrastructure (as part of the asset mapping and asset management to be introduced in Activity 1.2) on the GIS hazard maps to inform planning and budget allocations. Series of technical staff training in climate risk modelling, mapping and vulnerability, Cost Benefit Analysis (CBA) and project appraisal techniques, specifically in relation to infrastructure planning and development, and climate-induced disaster risk management, will be delivered.

Sub-Activities: 1.1.1. Establish a project Spatial Data Infrastructure (SDI) and provide project GIS support throughout. 1.1.2 Data gathering, data digitisation systematization, storage and analysis within the SDI GIS system for use in hazard and risk analyses to support the hazard and risk modelling and mapping. Undertake detailed surveys for all hazard modelling 1.1.3 Procure modelling software, databases, hardware for multi-hazard modelling to be embedded in MSS 1.1.4 Using the most appropriate modelling techniques, establish numerical models for flood modelling, landslide and erosion and drought for all major river basin in TL based on surveys of the physical characteristics of the river basins. Produce high resolution hazard maps 1.1.5 Deliver training in hazard modelling to at least 20 practitioners at national and local government level and identify long-term training needs 1.1.6 Develop and codify methods and tools for undertaking socio-economic surveys to collection necessary information to fully map the socio-economic conditions of the rural poor within the catchment; Using the methods developed, undertake detailed socio-economic surveys for 6 target municipalities in TL 1.1.7 Undertake socio-economic and vulnerability assessment to fully map existing vulnerability within TL 1.1.8 Develop a GIS-based tool to integrate various spatial socio-economic data with the hazard maps, perform vulnerability assessment, produce vulnerability maps which will include damages and loss of life estimates and to test risk management interventions options. Tools, methods, guidelines and procedures for recording disaster events, undertaking post-event surveys 1.1.9 Develop and deliver a training programme in socio-economic modelling methods and tools to MSS staff

Activity 1.2. Loss and damage accounting methods and database established.

GCF Intervention: The GCF project will provide loss and damage data collection and accounting technologies and establish loss and damage database management approaches. These improved loss and damage systems will provide evidence for budgeting and implementation of climate risk reduction measures, specifically in relation to community infrastructure services. Such accounting system will help demonstrate that benefits of avoided loss and damages can outweigh costs of climate proofing and risk reduction. The manual and digital templates, including the detailed guidelines and training for the MSS field officers on how to record loss and damage data will be developed. This will also include a mobile application to record the loss and damage data and transmit to the central server in real time. Use of UAV technology / drones will be introduced to map out current hazard risk conditions effectively at the catchment scale. Risk profiling of such accuracy and scale will underpin the planning and implementation of risk reduction measures in hazardous and densely populated areas. Series of trainings will be conducted on data management and analysis and data management standards and protocols will be introduced. Data sharing protocols (e.g. through CliDE) will be put in place at all data holder Ministries and Directorates. This activity will provide the profile of current risks and a means of systematically recording loss and damages realised in actual events. It will also help in the immediate aftermath of disasters in recording loss and damages for needs assessment and compensation. Drone technology will be useful in mapping extent of current hazard conditions and in expediting the assessment of loss and damages and need, following disasters.

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The database in Timor Leste contains some 1,600 records from 2001 to the present but it is not well managed. Risk Management Application will be developed for the storage, analysis and management of disaster data.

Relevant inputs and reports will be managed on a simple real time system available to all tracking the observation data, verification data and compensatory responses, and to collate and track disparate reporting. The benefits would be: rapid and simple access to data; single data storage database; shorter lead times from data requests to delivery; improved feedback through standard reporting; better ownership and accountability; transparency; Data quality control; faster resource allocation (to affected area); costs savings for rapid assessment teams; reduced operational costs for Loss and Damage data collection and storage; on demand data both to and from District and sub District data from NDOC.

Currently the cost of Disaster Risk management including an average of 10 to 15 rapid assessments per year is around USD 600,000 rising to USD1.5 million if site mobilisation and other items are factored in. It is estimated that the Risk Management Application will cost approximately $500,000 to develop and will provide long-term savings and efficiencies.

The GCF project will also build on the asset locational and condition survey methods developed under the SSRI project and will establish an asset management database on which to base loss and damage monitoring of infrastructure. It will introduce asset inspection guidelines, methods and approaches, and will train MCIE, Ministry of Social Solidarity (MSS), Ministry of Public Works (MoPW) national and municipality staff in the use and maintenance of the datasets, and in condition inspection. In addition, the asset management database will be used for planning, costing and prioritisation of asset maintenance using principles of portfolio risk assessment. MSS will have responsibility for this activity.

Sub-Activities: 1.2.1 Procure 6 Drones and deliver (how many) user training 1.2.2 Review of existing damage and loss databases and accounting technologies (Disaster Risk Management Portal, SIGAS accounting system, and Desinventar database). Development and implementation of a harmonized and unified damage and loss recording and accounting system in the form of a Disaster Risk Management Application (DRMApp) which will provide a real-time system to all tracking the observation data, verification data and compensatory responses, including a Metadatabase to collate and track disparate reporting. Available at National sub-national and municipal and suco level. DRMapp will include development of electronic (online, mobile handheld proformas etc.) and manual damage and loss recording templates 1.2.3 Develop and implement an infrastructure asset management system linked to Damage and loss database. Introduce asset inspection guidelines, methods and approaches 1.2.4 Develop and deliver a training programme in damage and loss and asset management methods and tools to MSS staff

Activity 1.3. Ordinances, regulations and associated codes and standards defined to climate proof small-scale rural infrastructure.

GCF Interventions: The GCF project will prepare a set of revised standards, guidelines and specifications for rural infrastructure, encompassing both technical and functional standards to respond to climate risk reduction requirements. The guidelines and SOPs for all infrastructure investments to be carried out under the municipal (PDIM) and village (PNDS) development plans will be developed. Trainings for the technical personnel and groups of engineers to enable a full compliance with the revised standards and codes will be delivered. GCF will support the development of the Rural Roads Master Plan & Investment Strategy 2016 – 2020 to help embed climate resilience measures into road master planning. GCF will support the development of a National Water Supply Policy and Strategic Plan to provide the medium to long-term vision for the sector and to provide a framework for the institutional arrangements, overall operation and

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I management of DNSA and coordination with other sectoral agencies and partners, to ensure that climate resilience approaches are embedded in the policy and strategy for water supply. Existing technical specifications will be reviewed to address the climate change resilience aspects of the specifications. Existing guidelines and manuals will be reviewed and strengthened thereby providing guidance for technicians and engineers to develop and design projects that are adaptable and resilient climate change. In the case of small irrigation schemes, the guidelines would have to be developed from scratch. The existing Standard Method of Measurement (SMM) developed by Agency of National Development (AND) will be reviewed to ensure that it incorporates climate resilient design considerations, such as physical parameters and appropriate choice of materials. Other relevant and related standards that are in use in the construction will also be developed e.g. soil-bioengineering standards for infrastructure projects in Timor- Leste. Once developed, engineers will be fully trained in the use of the new specifications, guidelines and manuals. This activity will be coordinated by MCIE and will involve all sectors for which guidelines, regulations and codes and standards will be developed to ensure sector specificity and ownership. Training will be to relevant technical staff from all sectors.

Sub-Activities: 1.3.1 Develop Gender Responsive Climate Change Strategy and Action Plan which encompasses the priorities endorsed in the national documents as indicated in the upcoming National Climate Change Policy 1.3.2 Review and revise all standards, guidelines and specifications for rural infrastructure, encompassing both technical and functional standards to respond to climate risk reduction requirements, based on international best practices. 1.3.3 Input to the development of the Rural Roads Master Plan & Investment Strategy 2016–2020 to help embed climate resilience measures into road master planning. 1.3.4 Input to the development of a National Water Supply Policy and Strategic Plan to provide the medium to long-term vision for the sector and to provide a framework for the institutional arrangements, overall operation and management of DNSA and coordination with other sectoral agencies and partners, to ensure that climate resilience approaches are embedded in the policy and strategy for water supply 1.3.5 Develop guidelines and SOPs for all infrastructure investments to be carried out under the municipal (PDIM) and village (PNDS) development plans to make these plans climate responsive 1.3.6 Develop a capacity building plan and roadmap for national and regional authorities to integrate new policies, plans and strategies and guidelines into PDIM and PNDS. This would include the development of tools that will be needed for implementation and enforcement of new methods and guidelines for CR infrastructure development planning and implementation 1.3.7 Implement capacity building and training based on CDP for national and regional authorities 1.3.8 Support the National Institute for Public Administration (INAP) to implement Disaster Risk Management Training Manual, which has recently been launched by Ministry of Social Solidarity and INAP.

Output 2. Climate resilient small-scale rural infrastructure deployed to benefit 175,840 across five priority districts.

Under this output, the GCF project will work closely with the municipal and village level government investment programmes into the small scale rural infrastructure development through its PDIM and PNDS mechanisms at administrative sub-national-level, to climate proof the local infrastructure investments for geographic focus areas across all sectors of water supply, flood defences, roads and bridges, and irrigation. Actual physical investments will be accompanied by the development of essential capacities and setting- up institutional and procedural systems required for scaling up climate resilient approaches to infrastructure development in the country. This output builds upon the SSRI project considering the lessons learned while deepening the level of intervention in the municipal and village development planning processes (PDIM and PNDS) to fully embed climate resilience into infrastructure design, implementation, construction and maintenance. It will do so via the development of manuals, guidelines and specifications using climate risk information and methods developed in Output 1, for all stages of the rural infrastructure planning and implementation, and by building capacity at the local level for implementing these new methods. Using the new approaches, the project will directly fund the implementation of climate resilience measures to

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I infrastructure to be rehabilitated or built within the six priority municipalities of Baucau, Ermera, Aileu, Viqueque and Lautem and Liquica following PDIM and PNDS priorities.

Activity 2.1. Village and Municipal development plans (PDIM and PNDS) fully integrates climate change risk considerations into their annual planning and budgeting cycle for small scale rural infrastructure.

GCF Intervention: The project will introduce climate risk screening methods and embed climate risk reduction criteria across PDIM and PNDS planning and decision-making cycle. It will provide step-by-step guidelines for climate risk reduction measures for all categories of small-scale rural infrastructure (water supply, road and bridges, irrigation, flood defences) through PDIM manual – CAMP; Community-based management and maintenance – GMF manual, KAM – municipal procurement guidelines and administrative post and the Ministerial Technical Committee review checklists. A team of technical staff of Equipment Verification, Evaluation and Supervision (EVAS) will be trained to determine the likelihood and consequences of risk in relation to asset (infrastructure exposure and vulnerability). Their skills to engineer climate resilient designs and apply various methods of bioengineering (e.g. by use of local vetiver plants to stabilize the slopes and gabion structures) will be developed.

It will embed the systematic use of climate hazard and risk information (to be developed under Activity 1.1) in the PDIM project identification process to provide a more comprehensive, robust and evidence-based means of identifying projects at suco level. The GCF project will provide technical assistance to Administrative Post (AP) staff in prioritizing projects at this level and in undertaking an appropriate level of feasibility studies on which to base climate-risk informed project prioritization. At municipal level, the GCF project will also introduce climate risk criteria into the prioritization process, and include other methods of measuring benefits of projects based on the introduction of appraisal-led project prioritisation using socio- economic cost-benefit analysis methods and tools to be developed under Activity 1.1.

Capacity development will be provided to enhance the ability to undertake engineering feasibility studies and will include incorporate climate-risk considerations into technical feasibility, introduction of investment feasibility considerations, introduction of socio-economic cost-benefit analysis, optioneering and options appraisal methods as well as outline environmental impact assessment, to strengthen the feasibility process, safeguard investments and optimize engineering solutions.

At the detailed design level, technical assistance will be provided to introduce climate change considerations into design of infrastructure to ensure that they will accommodate likely changes of environmental variables (frequency and intensity of occurrence) expected with climate change. Environmental impact assessment (EIA) will be introduced at the detailed design stage, in line with international good practice and will ensure that the potential impacts of the project are identified and examined at the detailed design (and not only at the early scoping stage before the actual works are designed as is currently done or after completion when it is too late) and that mitigation measures can be built into the design. Importantly, the project will train municipality engineers in the new climate-risk informed infrastructure detailed design methods and will include specific training in the design of bioengineering methods relevant to Timor Leste. Bioengineering training will be done through technical assistance and by providing dedicated training on bio-engineering.

In order to enhance the ability of infrastructure construction contractors to implement climate-resilient construction, the GCF project will introduce processes for pre-qualifying contractors, based on specific criteria such as certification in prior trainings on implementation of climate-resilient projects, experience of implementing climate-resilient projects, experience of contract management of such climate-resilient projects and access to engineering expertise aligned with the types of climate resilient measures to be built into infrastructure (such as bioengineering methods). The GCF project will seek to embed such training of contractors into appropriate centralised contractor training courses.

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The GCF project will strengthen the monitoring capacity at Administrative Post (AP) level through the provision of appropriate engineering expertise during implementation. To truly build capacity within the process, this will be done by training existing AP staff to undertake project monitoring and to provide the resources to do so including additional/complementary monitoring to be done by the GCF project as technical assistance.

The project will support the development of the following manuals and guidelines for Sustainable Climate- resilient Rural Infrastructure Projects in Timor-Leste (SCRIPT)

1. Manual/guidelines for the design and construction of rural road infrastructure – in collaboration with MSA, Ministry of Public Works and ADN 2. Manual/guidelines for the design and construction of small irrigation schemes – in collaboration with Ministry of Agriculture, Ministry of State Administration 3. Manual/guidelines for the design and construction of rural water supply infrastructure – in collaboration with Ministry of Public Works

Guidelines and Technical Specifications Technical specifications for rural infrastructure will be reviewed and revised to improve the quality and adaptability of the construction to climate change for the various types of rural infrastructure.

The Technical Specifications forming part of the contract documents for the design and construction of roads, bridges and drainage structures would include specific sections for the various elements such as excavation, gravel, concrete, masonry works, drainage, retaining-walls etc.

There will be a review of the specifications for inclusion of section/chapter on climate adaptation features/elements of the road, bridge and drainage infrastructure for e.g. scour-checks, check-dams, rip- raps, gabions, soil-bioengineering etc.

The project will review existing specifications which need to be revised and improved to respond to the changing climate and existing conditions in the ground e.g. the design for retaining walls, specification for the strength of concrete for the various applications and for reinforced concrete, masonry, etc.

Existing Guidelines and technical specifications for water supply systems will be reviewed and enhanced to include climate resilient design.

Sub-Activities: 2.1.1 Develop step-by-step guidelines for climate risk reduction measures for all categories of small-scale rural infrastructure (water supply, road and bridges, irrigation, flood defences) through PDIM manual – CAMP; Community-based management and maintenance – GMF manual, KAM – municipal procurement guidelines and administrative post and the Ministerial Technical Committee review checklists 2.1.2 Train team of technical staff of Equipment Verification, Evaluation and Supervision (EVAS) to determine the likelihood and consequences of risk in relation to asset (infrastructure exposure and vulnerability). Their skills to engineer climate resilient designs and apply various methods of bioengineering (e.g. by use of local vetiver plants to stabilize the slopes and gabion structures) will be developed 2.1.3 Provide technical assistance to Administrative Post (AP) staff in prioritizing projects at this level and in undertaking an appropriate level of feasibility studies on which to base climate-risk informed project prioritization. 2.1.4 At municipal level, introduce climate risk criteria into the prioritization process, and include other methods of measuring benefits of projects based on the introduction of appraisal-led project prioritisation using socio-economic cost-benefit analysis methods and tools to be developed under Activity 1.1. Undertake detailed CBA for 130 prioritised infrastructures projects in 6 target municipalities. Provide capacity development to enhance the ability to undertake engineering feasibility studies and incorporate climate-risk considerations into technical feasibility

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2.1.5 Introduce investment feasibility considerations, socio-economic cost-benefit analysis, optioneering and options appraisal methods as well as environmental impact assessment that integrate climate change impact scenarios, to strengthen the feasibility process, safeguard investments and optimize engineering solution. Develop long-term municipality investment plans for PDIM and PNDS 2.1.6 At the detailed design level, technical assistance will be provided to introduce climate change considerations into design of infrastructure to ensure that they will accommodate likely changes of environmental variables (frequency and intensity of occurrence) expected with climate change. Environmental impact assessment (EIA) will be introduced at the detailed design stage, in line with international good practice 2.1.7 Train municipality engineers in the new climate-risk informed infrastructure detailed design methods and include specific training in the design of bio-engineering methods relevant to Timor Leste. Bioengineering training will be done through technical assistance and by providing dedicated trainings on bio-engineering. 2.1.8 Introduce processes for pre-qualifying contractors, based on specific criteria such as certification in prior trainings on implementation of climate-resilient projects, experience of implementing climate-resilient projects, experience of contract management of such climate-resilient projects and access to engineering expertise aligned with the types of climate resilient measures to be built into infrastructure (such as bioengineering methods)

Activity 2.2. Municipal finance made available for a design and deployment of climate resilient infrastructure at a scale that benefit 175,840 people, 15% of the country population.

GCF Intervention: Climate resilient infrastructure will be deployed in the priority sub-sectors of rural roads & bridges, water supply & irrigation and drainage and flood protection (protective gates, gabions, including bio-engineering). The project will develop evidence-based engineering manuals and construction codes and standards to guide the EVAS engineers that provide design and construction supervision services to PDIM and PNDS. The project will device and deploy performance-based top-up grants to finance climate- resilient features of target infrastructure units (e.g. divertors, drainage canals, reinforcements etc.) and related risk reduction measures and thus absorb additional cost of climate proofing. As a long-term solution to address the additional cost of climate proofing the project will develop long-term village and / or municipal investment plans to leverage private sector finance into the climate resilient investments. In relation to this, the project will support local municipalities to establish financial and loan repayment capacity to contribute to the PDIM and PNDS investment plans. Municipal investment plans will be developed using the cost- benefit and appraisal-led feasibility methods to be introduced in Activity 1.1 for all municipalities. However, at present, only Baucau municipality will be able to access private sector finance through top-up grants based on different status of the municipalities. However, it is possible that, in the future, other municipalities will be able to access private sector finance directly. Investment planning will, none-the-less, be a key investment planning tool for accessing public sector financing for all municipalities.

Based on the municipal level climate change risk and vulnerability assessment undertaken in the feasibility Study, the project will target implementation of climate resilient infrastructure projects in the 5 municipalities worst affect by multiple hazards. The 5 worst affect municipalities were Baucau, Ermera, Aileu, Viqueque and Lautem. In addition, Liquica, which is at high risk from flooding and landslides only and for two receptors (houses and agriculture) only, and therefore did not rank within the top 6 has been included as it represents a municipality with significant deficit of flood protection infrastructure and will address one of the hazards with the greatest and most frequent impact on communities.

A total of 130 infrastructure units at the cost of $25.66 Million USD has been identified, (SSRI project investments were used as a reference for costing, per unit cost, including base cost for construction to be covered from municipal funds and climate proofing cost to be covered from GCF funds). PDIM and PNDS implementation has averaged 493 infrastructure units and $54 Million USD per year between 2011 and 2016 nationally. Over the 5 years of infrastructure implementation PDIM and PNDS investments in the 6

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I target municipalities will be $12.5 Million (including $12.5 Million in government co-financing). Hence PDIM and PNDS co-financing will cover 49% of the GCF investment in infrastructure.

These proposed infrastructure projects will directly benefit 19,751 households or 175,840 people26. This represents 14.65% of the population.

Table 0-1: Number of infrastructure units by type that can be implemented under the GCF project

No. of Total No. of beneficiary Length Irrigation Costs Scheme Type Projects households (km) area (ha) (USD)

Irrigation 25 8,374 54.18 3,700.30 3,681,687

Flood Protection 20 1,758 14.15 3,429,150

Rural Roads 47 5,459 216.94 14,791,488

Water Supply 38 4,084 127.49 3,755,925 Total 130 19,751 25,658,250

A cost-benefit analysis has been conducted on all 130 projects and the projects have been ranked and prioritised based on their internal rates of return (IRR) and the number of associated beneficiaries, into high, medium and low priority (dark to light blue cells in Table below) which will dictate the order or priority in which they will be implemented during each implementation year. This is to ensure that the highest priority projects benefitting the most people will be done first. The IRR calculation includes the cost of maintenance (periodic and annual) that would be required over a 20-year lifespan of the infrastructure.

Roads projects are the most expensive accounting for 57% of total project costs (and 36% of the number of projects), with only 34% of all roads projects falling in the high and medium priority categories. This is mainly a reflection of high maintenance costs associated with roads despite the large benefits that road projects will bring to rural communities. For example, without maintenance included in the IRR calculation, 84% of roads fall within the high and medium priority categories. It is also a reflection of the isolation of some communities that will benefit from the roads such that the beneficiary numbers of some of the schemes are low compared to the overall cost. However, it is specifically to relieve the isolation of communities that many of these road projects are needed and to enable economic activity which will lift communities out of poverty and climate-induced vulnerability. It also points to the need to ensure a proper maintenance strategy for roads to capitalise on the gains that will be made from climate proofing them. It is likely that climate proofing will reduce maintenance costs, so the values used reflects the reduced maintenance that climate proofing will provide, balanced against the need for increased maintenance with worsening climate-induced hazards that will be incurred.

26 The number of direct beneficiaries of the 130 infrastructure projects/interventions alone is 119, 498. Complementary catchment management activities have been estimated to result in an additional 56,342 direct agro-forestry beneficiaries. This gives a total number of direct beneficiaries of 175,840 beneficiaries of Output 2.

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Water supply schemes have the two highest proportions of projects in the high and medium categories (91%) which reflects the relatively low capital and maintenance costs, compared with the numbers of beneficiaries, as well as the socio-economic gains that will be realised by rural communities. 66% of irrigation projects fall in the high and medium priority categories.

Flood protection measures show only a small proportion of high and medium priority projects (20%) and this is in large part, due to the very small numbers of beneficiaries, agricultural land and property that can be protected by individual flood defences. It is likely that flood risk management strategies which do not only include infrastructure, will need to be examined and the right combination of structural and non- structural measures identified. It is also noted that activities in Output 3 which will address land degradation will have attendant benefits on flood management, but the cost-benefit of these have been assessed separately (see Output 3).

Year 1 Year 2 Year 3 Year 4 Year 5 Total % All Projects 376,944.34 915,436.26 1,857,797.12 1,857,797.12 376,944.34 5,384,919.20 21% 434,314.48 1,054,763.74 2,140,549.94 2,140,549.94 434,314.48 6,204,492.59 24% 984,818.67 2,391,702.49 4,853,749.18 4,853,749.18 984,818.67 14,068,838.20 55% Total 1,796,077.50 4,361,902.50 8,852,096.25 8,852,096.25 1,796,077.50 25,658,249.99 100%

Rural Roads 153,644.34 373,136.26 757,247.12 757,247.12 153,644.34 2,194,919.20 15% 197,734.63 480,212.67 974,549.24 974,549.24 197,734.63 2,824,780.40 19% 684,025.17 1,661,203.99 3,371,266.93 3,371,266.93 684,025.17 9,771,788.20 66% Total 1,035,404.15 2,514,552.93 5,103,063.29 5,103,063.29 1,035,404.15 14,791,487.80 100%

Irrigation System 78,400.00 190,400.00 386,400.00 386,400.00 78,400.00 1,120,000.00 30% 91,468.12 222,136.85 450,807.14 450,807.14 91,468.12 1,306,687.37 35% 87,850.00 213,350.00 432,975.00 432,975.00 87,850.00 1,255,000.00 34% Total 257,718.12 625,886.85 1,270,182.14 1,270,182.14 257,718.12 3,681,687.37 100%

Water Supply 134,750.00 327,250.00 664,125.00 664,125.00 134,750.00 1,925,000.00 51% 106,233.74 257,996.22 523,580.56 523,580.56 106,233.74 1,517,624.82 40% 21,931.00 53,261.00 108,088.50 108,088.50 21,931.00 313,300.00 8% Total 262,914.74 638,507.22 1,295,794.06 1,295,794.06 262,914.74 3,755,924.82 100%

Flood Control 10,150.00 24,650.00 50,025.00 50,025.00 10,150.00 145,000.00 4% 38,878.00 94,418.00 191,613.00 191,613.00 38,878.00 555,400.00 16% 191,012.50 463,887.50 941,418.75 941,418.75 191,012.50 2,728,750.00 80% Total 240,040.50 582,955.50 1,183,056.75 1,183,056.75 240,040.50 3,429,150.00 100%

This preliminary project identification, outline scoping and cost-benefit analysis will be refined during the project and will be based on the detailed hazard mapping, and utilise the robust cost-benefit assessment and appraisal-led methods and tools to be introduced by the project under Output 1. In refining the assessment, the viability each scheme be determined and additional criteria used to ensure that the most beneficial schemes are implemented as priority. The $25.66 Million (including $12.5 Million government co-financing) budget is therefore an upper limit of capital costs that the project will cover in implementing these infrastructure schemes.

Maintenance Costs

The cost of maintenance over the life of the asset is high for some types of infrastructure such as roads. For all infrastructure projects identified maintenance over the first 10 years of asset life is $7.2 Million, and over the 20-year service life of the asset, is $29.4 Million. The rural roads identified account for $5.9 Million and $23.6 Million of 5-year and 20-year maintenance costs which is more than 80% of maintenance costs of all infrastructure. In some cases, the maintenance cost over the assumed 20-year asset life span or

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I even shorter term can exceed the capital cost of the schemes. There is a need to gain a better understanding of maintenance costs as part of longer-term asset management, and the project will examine approaches such as the use of linear depreciation methods, which allows for changes in the distribution of depreciation over time. In the presence of inflation and climate change, the use of different depreciation methods would yield different real (adjusted) maintenance costs. It will also allow for the inclusion of detailed socio-economic considerations in the benefits of the infrastructure, such as the economic losses if the infrastructure is lost, disruption due to maintenance, or attendant impacts on access to essential services such as health and education.

Investment Planning

As discussed above, currently the PDIM and PNDS do not have funding criteria or requirement to embed additional cost of climate risk reduction to physical and economic assets and there is currently no understanding of the investment requirements for climate proofing infrastructure due to the lack of climate- risk information and methods on which to base such investment planning.

To address this barrier, the project will develop and implement new approaches to investment planning to ensure that infrastructure investment including annual and periodic maintenance which can be met in the long-term and will include climate proofing. Approaches will include: • Embedding climate proofing in the PDIM and PNDS project identification and screening processes from village level project identification through to project feasibility, design and costing • Identification of financing models for investment maintenance costs (e.g. of community-based scheme that involve the use of tariffs or in-kind contributions to establish municipal maintenance programmes (e.g. GMF as being done on SSRI) or engagement of private sector in infrastructure maintenance financing). • Development of municipal infrastructure investment plans based on risk-informed project designs, including maintenance, and costs-benefit analysis based on CBA methods and models to be introduced in Activity 1.1 • Use of municipality investment plans for technical justification for central budget allocation to cover investment and maintenance cost of climate resilient rural infrastructure utilising the climate proofing methods introduced by the project. • Project will provide evidence of the long-term need for maintenance to safeguard infrastructure investments and will assist government in identifying and prioritising financing, based on the principles of portfolio risk assessment (PRA) and associated cost-benefit analysis. Furthermore, the CBA tools to be developed by the project will be embedded in municipality as a standardised requirement for developing annual infrastructure investment plans.

Using the asset management database to be introduced in Activity 1.2, the project will develop essential processes for infrastructure asset management including, maintaining a systematic record of individual assets (costs, original service life, remaining useful life, physical condition, repair and maintenance consistency); developing a defined program of planned maintenance of infrastructure including repair and replacement; and implementing and managing information systems (e.g., updating Geographic Information Systems on which the system will be based) based on surveys.

Climate Proofing Approaches Based on experience of the SSRI, GCF funds will be used to build climate resilience into infrastructure using several different approaches depending on the type of infrastructure. Hence the GCF funds will be used to provide the climate resilience additionality benefit to infrastructure projects to be built through the planned government infrastructure development. For Water Supply systems, the climate-resilience approach will include:

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a. identification of sources at risk from reduced supply due to droughts, and calculating requirements for upgrading sources and extending dependability of supply b. Protection of water sources from pollution by revegetating land around sources, formalising informal sources (putting in pipes and collection/storage systems to enhance environmental protection and supply dependability) c. Installation of standpipes in villages and connection to existing sources

For Roads and Bridges, the climate-resilience approach will include: d. Rehabilitation of bridges that are usually washed away in the rainy season using climate resilient materials, and protection of bridge openings with bioengineering methods (e.g. Vetivier grass) in combination with sustainable structural measures such as gabion baskets. e. Vegetation of road corridors with bioengineering material such as Vetivier grass. f. Re-sizing of road drainage systems that accommodate flows, taking account of climate change flows. g. Engagement of local communities in the vegetation of road embankments, as well as for wider catchment re-forestation to protect road works

For Flood defences, the climate-resilience approach will include: h. Development of flood management intervention measures on a catchment scale, which takes account of current risks upstream and downstream of affected communities under existing and climate change scenarios, thus ensuring that flood defences are not built in isolation and without consideration for impacts upstream and downstream of defences. i. Building of flood defences to protect communities currently at risk using bioengineering methods to protect flood embankments from erosion. j. Design of flood defences to flood levels and lengths that take account of climate change k. Consideration and design of non-structural flood management measures such as wetland- creation, floodplain storage areas and small-scale multi-use dams which provide flood storage as well as water supply benefits to communities. l. Use of check dams to control erosion and runoff

For Irrigation systems, the climate-resilience approach will include: m. Formalisation of existing, or construction of new irrigation schemes which include water storage systems to store water for use in the dry season and mitigate against drought with benefits to water efficiency and stability of supply for crop production. The designs will be based on climate risk from drought as well as detailed socio-economics assessment of likely benefits to local agricultural production from the constructions of new irrigation systems.

For all projects, soil bioengineering interventions will be used and would include, but will not be limited to the following: - Vegetated check-dams - Vegetated Brushwood Retaining Wall - Vegetated Bamboo Retaining Wall - Vegetated Loose Stone Check Dams - Live spurs/stakes - Palisades

The type of interventions would depend on the soil characteristics, topography, gradient, weather pattern, hydrology etc.

Cost of Climate-Proofing Infrastructure

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In Bhutan, the cost of building in climate resilience into roads projects is estimated to add 15-25% to the total project costs27. However, the additional costs would nullify in 7 to 9 years due to lower maintenance costs over the long-term, climate resilient roads would be much cheaper than conventional roads. Under the SSRI project, 3 climate resilient rural road rehabilitation projects were implemented in 2016 at an average cost of around $63,658 per kilometre ($493,225/7.748 km). The investment for the complementary soil bioengineering interventions was between 3– 5 % of the contract cost.

Assuming a value of 10% of the cost, it can be estimated that the additional cost of climate-proofing roads is 1,474,152 or $6,890 per km.

For water supply systems, the total investment cost per capita under the SSRI project was $75/person and provides approximately 15 years’ service life. Considering only the total investment cost this yields a simple average of $5.00 per person per annum for 12.775 m3 @35 litres/person/day which works out to approximately = $0.39 per cubic meter per year at constant supply. Since most of these systems are gravity-fed, operational expenses are minimal, as are maintenance costs. Hence the proposed GCF project will provide 10.3 Million cubic meters per year of constant supply. This represents a guaranteed water supply in areas where there is currently no or irregular supply, and where clean supply is at risk from drought, erosion, flooding and landslides.

Under the SSRI project, 2 irrigation schemes were implemented, covering 110 ha of irrigated land, at a total cost of $294,613.67 and 5,238 beneficiaries. It is estimated that the annual rice production for areas producing single crop per year is 1.5 MT per ha on average. The proposed GCF project could therefore result in 5,550 Mt per ha per year more rice production. This represents a more stable rice production in areas where variable production is being exacerbated by drought risk. Sub-Activity:

2.2.1 Detailed design and construction of 130 CR infrastructure projects

Activity 2.3. Supporting catchment management and rehabilitation measures to enhance climate resilient communities and infrastructure.

Degraded catchments increase the vulnerability of built infrastructure to physical damage during extreme events like floods, and increases maintenance costs while ecologically stable catchments enhance built infrastructure. The catchment is therefore the eco-system unit within which critical processes must be managed in order to minimise the impact of climate change on the built environment. Hence, strategic investment in ecologically healthy and functioning catchments, is needed to lengthen the life of built infrastructure and reduce or delay the need for additional built infrastructure – often with significant cost savings. It is more cost effective to rehabilitate the ecosystems concerned than to keep repairing or replacing the built infrastructure. Well managed ecologically healthy catchments, can also support a range of livelihoods thus supporting economic sectors, directly and indirectly28.

This output will scale-up climate resilient catchment management to reduce the exposure of communities and their physical assets, such as rural infrastructure to climate-induced hazards. This will be achieved by addressing the catchment scale land degradation caused by anthropogenic activity and exacerbated by climate change, which is leading to intensification of the hazards and deterioration of infrastructure. Even with the climate proofing approaches to be introduced and implemented, it will still be necessary to

27 National Environment Commission, Royal Government of Bhutan, Technology Needs Assessment and Technology Action Plans for Climate Change Mitigation, Kingdom of Bhutan, March 2013 28 A study from the CGIAR research program on Climate Change, Agriculture and Food Security (CCAFS) found from a survey of over 700 households in East Africa that at least 50% of those households had begun planting trees on their farms in a change from their practices 10 years ago resulting in reduction in the effects of climate change by helping to stabilize erosion, improving water and soil quality and providing increased crop yields.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I implement catchment rehabilitation and management to re-establish proper catchment ecosystem functions in order to safeguard infrastructure and climate proofing investments from long-term climate change impacts. This will have the added benefit of reducing the cost of climate proofing and maintenance of infrastructure in the future. The project will lift human and livelihoods pressures that are being placed on the land, which contributes to its degradation and hazard evolution, by identifying and implementing agroforestry measures, including community agro-forestry, that will lead to direct re-forestation of the catchments and improve livelihoods to the communities which ensure land use practices that contribute to overall risk reduction and long term climate resilience.

The project employs catchment management adaptation strategy that includes rehabilitation of hazardous areas by providing climate risk information and the actual on-the-ground methods for landscape restoration. It will also include the community mobilization and sensitization to agro-forestry opportunities for resilient community development. The livelihood challenges are low income and employment opportunities, single crop farming, limited land holding, and limited access to finance, markets, business knowledge, technology and technical-know how. The project will address some of these livelihood pressures by supporting the development of agro-forestry strategies, including the identification of appropriate climate resistant varieties, full route to market analysis for all introduced agro-forestry species, This ecosystem-based adaptation will be implemented at the catchment level.

The GCF project will work with the Ministry of Agriculture and fisheries (MAF) and the National Directorate for Forestry and Agri-business (which comes under MCIE) to develop catchment rehabilitation strategies including agro-forestry strategies for upstream catchments of target infrastructure. The project will develop strategies and actions of catchment rehabilitation, including selection of tree species, methods of rehabilitation and maintenance that are fully informed by the hazard maps to be developed under Activity 1.1. It will delineate the priority hazardous areas for a phased rehabilitation strategy. It will assist in the identification of plant species that will provide the soil, water and nutrient protection properties needed to address degradation of catchment. Several varieties of tree species have already been identified, among them falcataria moluccana, a fast-growing tree that is typically cultivated for timber; Acacium mangium that is increasingly being used for agroforestry projects for its nitrogen fixation properties, but also for shadow it creates for other trees, such as wild coffee. It is a resistant tree, and can be productive in low fertility soils with poor moisture content. Casurina and Toona Sureni are also used for their timber and fast burning properties. Teak, mahogany, sandalwood and coconut have also been identified as resistant and with high livelihood value. The agro-forestry potential of these species has been assessed as significant both internally and internationally. The project will assist MAF and MCIE in developing the long-term strategy and planning for agro-forestry as catchment rehabilitation strategy for ecosystem-based adaptation.

Actual catchment rehabilitation works will be conducted in the catchment areas that are particularly hazardous across the target districts and require reforestation in order to stabilize the soil, arrest erosion and degradation that exposes the community and physical assets to climate change risks. The proposed catchment management will involve convergence of existing government reforestation programmes with collective action by the community. The project will support the MAF directorates on forestry and watershed management to undertake a phased approach to catchment rehabilitation while focusing on highly hazardous areas of high exposure to climate risk. Such climate risk informed prioritization will be based on hazard modelling and mapping of a range of climate change scenarios. Based on hazard risk information developed during the feasibility study 200 hectares of state-owned land has been identified for reforestation/catchment management schemes. The project will work with the MAF to design and deliver this support to their existing reforestation and catchment management schemes in the 6 target municipalities which contain 19 sub-catchments in total. This is in line with MAF SDP (2011-2030) objective 3.4 which aims ‘To develop capacity for improved decision making in planning and budgeting processes by providing accurate and up-to-date climate information and analysis. As part of rehabilitation efforts agroforestry will be used as an important element of catchment management. The MAF forestry and MCIE agribusiness experts will engage with community leaders to facilitate the formation of cooperatives for sustainable agroforestry.

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Cooperatives can be an important mechanism to facilitate and support the development of agro-forestry in the rural areas. This is a key strategy under the Government’s Strategic Development Plan (SDP) 2011‐ 2030 for economic and rural development. As of September 2011, the number of cooperatives in Timor‐ Leste had reached 92, with more than 10,000 members affiliated in 13 municipalities. The growth in cooperatives is largely a result of a government program that provides equipment and production means to cooperatives. This support focuses on building human resources and institutional capacity, as well as providing in‐kind subsidies to eligible cooperatives.

At the local level, and based on the agro-forestry strategies to be developed, the project will support farmers in identifying suitable community agro-forestry opportunities. It will do this by identifying agriculture associations and cooperatives which will serve to facilitate individual members or groups in developing community-based agro-forestry. These associations will also serve to provide technical and logistical guidance to farmers and will be organised by type of agro-forestry (e.g. coconut growers association) and by geography (e.g. on an Administrative post level, to provide logistical support to farmer, e.g. with regards to transporting goods to market) and will include women’s associations, leveraging on already established such associations and building on previous and existing government initiatives, as well as youth organisations. The associations and cooperatives could also serve as a quality control assurance body for products. The project will work with the MAF to design and deliver this support to their existing reforestation and catchment management schemes in the 6 target municipalities.

The project will support rural communities to implement agroforestry on their lands and, in so doing, will enhance catchment management adaptation strategy.

Based on the 10 sucos with the highest vulnerability to soil erosion in the 6 target municipalities, it is estimated that 23,412 households face potential crop losses due to erosion of $1.9 Million USD in total. Assuming agro-forestry will be promoted in areas such as these, the potential number of beneficiary households is 208,367. It is estimated that approximately 100 ha of privately owned land belonging to these households currently under threat from land degradation, will be used to establish agro-forestry within the target, priority sub-catchments. The hectares of land to be rehabilitated has been calculated based on number of households currently at risk from erosion and who are currently likely to be losing crop yields because of the combined effect of catchment degradation and climate change exacerbated hazard risks. The best proven approach is to target communities and incentivise them to engage in agro-forestry (i.e. such households are likely to engage as they currently have a problem with loss of crops due to intensified hazards and degradation of their land). The communities thus identified will be supported to implement climate resilient livelihoods that are conducive to resilient catchment management and climate risk reduction. In addition, reforestation and agro-forestry will be implemented on approximately 1200ha of land with co-financing from MAF in the target watersheds.

The main benefit of the catchment-based approach is that it addresses the livelihood pressures of communities within the catchments where key infrastructure is being developed, and at the same time helps to protect the infrastructure from climate-induce hazards through the re-establishment of critical eco-system functions.

Sub-Activities:

2.3.1 Develop agroforestry and reforestation strategy for infrastructure sub-catchments 2.3.2 Implement agroforestry and reforestation strategy for infrastructure sub-catchments

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11. TECHNICAL FEASIBILITY AND APPROACHES OF PROPOSED INTERVENTIONS

11.1 Proposed Multi-hazard, risk and vulnerability mapping methodology

A review of existing hazard mapping for Timor Leste is provided in Annex 3. The existing hazard mapping is of a broad-brushed nature and does not provide the level of detail required to develop risk knowledge on which to base detailed risk reduction measures such as climate-proofing of infrastructure, disaster risk reduction measures etc. This section describes the methodologies, data requirements and feasibility of implementing multi-hazard modelling and mapping for Timor Leste, which will provide climate risk information of the appropriate level of detail and accuracy. The discussion is focused on the hazard and risk modelling methods to be adopted, and while it includes some discussion about the modelling software packages to implemented, it does not prescribe software packages to be used at this stage, as a more indepth assessment of data availability, data quality, user requirements and specific skill levels, is required and this will be done in the early stages of project implementation. Annex 4 details the datasets that are available for undertaking hazard and risk modelling and assessment for Timor Leste.

Hazard, risk and vulnerability modelling and mapping Hazard and vulnerability maps are essential for the assessment of current and future hazards and the design of hazard management solutions that fully accounts for climate change considerations and the identification of receptors such as infrastructure at risk. The strategic assessment of risk to population, infrastructure, economic activity and to future development under conditions of climate change is a government priority to support and guide municipalities to wisely and rationally manage risk exposure to acceptable levels. GCF resources will be used to introduce modelling technologies to develop hazard maps under current and climate change conditions for the whole country and for all hazards. The hazard and risk maps, will be used to make risk-informed decisions for all aspects of development and risk management in the future. This will include zoning of development activity away from high hazards areas to avoid physical damages to people and property and losses to economic activity. In addition, the hazard maps will be used as the basis of the multi-hazard early warning system to be developed in the future and will be used by national and local authorities, and communities in the development of emergency preparedness and response plans, and could be used in the establishment of different financial risk transfer mechanisms, and for raising public awareness and improving community preparedness. The visual maps will benefit decision makers and all involved in natural hazard risk management at national and local level. It will also enable government and donor agencies to better focus their efforts in dealing with hazards in the basin in the future. Importantly the hazard maps will provide the basis for the management of climate-induced hydrometeorological hazards in Timor Leste now and in the future.

The project will also develop a bespoke GIS-based socio-economic risk model as a tool for risk assessment, cost-benefit analysis and climate resilient intervention measures for strategic planning in the future. The hazard maps to be developed will be used in combination with infrastructure (bridges, roads and buildings), land use (settlements, agriculture, grazing lands, and conservation areas), property and socio-economics data, to assess the socio-economic impacts of each hazard and produce vulnerability maps for the river basin. This vulnerability map, based on the accurate hazard mapping of the current situation will form the baseline.

In order to develop vulnerability maps, the bespoke GIS-based risk model will be used to integrate various spatial socio-economic data with the hazard maps, and produce vulnerability maps which will include economic losses and damages and loss of life estimates. Large hydrometeorological events in Timor Leste often results in losses to infrastructure, particularly roads and water supply, losses to agriculture and damage to property, along with concomitant social effects associated with loss of potable water and agricultural productivity. The baseline socio economic appraisal will concentrate on these and other sectors.

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The implementation and maintenance of modelling systems and the full adoption of the new technologies to be introduced, will require technical capacities in all areas of hazard and disaster risk management to ensure the long-term sustainability of the system.

Some technical skills and competencies exist in governmental and non-governmental institutions in areas that contribute to risk reduction and disaster management and emergency response. There are good capacities to elaborate long-term development policies, strategies and plans in various sectors. This however is mostly the case at central level, rather than decentralized levels (regional, municipal and local).

While technical expertise exists in various sectors and for specific technical areas, awareness and knowledge of hazard modelling and risk reduction concepts and practices is the area for improvement. Technical capacities related to hazard identification, risk identification and assessment, prevention, risk reduction, risk mitigation, risk transfer, preparedness, climate risk management and climate change adaptation are rather weak across institutions and governance levels.

In certain sectors, there are insufficient human resources; in many cases, incentives for specialized education or training are lacking, and qualified staff turnover is high. As part of the SSRI project, an assessment was made of the existing gaps in institutional capacity for all aspects of hazard and risk management in Timor Leste. A capacity development requirements will be specified based on the needs identified.

The method for modelling and mapping each of the main hazards, is elaborated below.

11.1.1 Flood hazard assessment and mapping

The approach for flood hazard assessment and mapping is based on international best practice and takes account of data availability for Timor Leste.

Flood Hazard maps provide spatially distributed information on flood type, flood extent, water depths or water levels, and flow velocity or relevant water flow direction and other information. Flood hazard maps are most commonly produced my numerical modelling of the hydrological and hydraulic routing processes of the catchment.

Methodology for Flood Hazard mapping Flood Hazard maps provide spatially distributed information on flood type, flood extent, water depths or water levels, and flow velocity or relevant water flow direction and other information. Flood hazard maps are most commonly produced by numerical modelling of the hydrological and hydraulic routing processes of the catchment.

Modelling Overview In flood risk management, numerical modelling tools have become almost indispensable for delineating zones at risk from flooding and making robust, evidence-based decisions on flood mitigation measures. The underlying hydrological and hydraulic models can also assist with understanding flood response, in order to inform the design of flood management/defence options and flood forecasting and emergency response systems.

There is currently a wide array of commercial modelling packages, for example, Info works (1D and 2D by Innovyze, formerly HR Wallingford), MIKE (DHI), HEC 1D and 2D (USACE), Tuflow, SOBEK 2D and Flo2D packages to name a few. These and other tools typically provide a map-based interface to the underlying models, and survey data, models, time series data and asset information can easily be added as it becomes available.

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The project will develop a modelling tool that may be utilized for present and future flood risk assessment. This will need to be ensured by:

• Developing the modelling tool in consultation with the relevant government agencies in Timor Leste; • Using appropriate methods given existing limitations on data availability and quality, while taking care that methods will allow for future model development should better/more data become available; • Undertaking detailed modelling for the main river basins of Timor Leste with less detailed representation of minor and/or lower risk sub-catchments. However, the modelling tool will be scalable to include greater level of detail of minor sub-basins in the future; and • Providing the tool as a key project deliverable and undertaking extensive capacity building of MSS to maintain and further develop the tool.

The main stages in the analysis are discussed in the following subsections.

Hydrological modelling The purpose of the hydrological analysis will be to model the response of the catchment and sub- catchments to rainfall and to derive flood hydrographs of different return periods (magnitudes). The approach will be tailored to the available data following the initial data review. The potential impacts of climate change will need to be considered as described below.

Rainfall-runoff models of all upstream catchments that feed into the main basins will be developed to simulate the runoff responses (i.e. hydrograph shape) of these catchments. Rainfall-runoff modelling will be based on catchment physical data (topography, land use, soils, geology) and rainfall event characteristics (observed rainfall time series data of specific events, and statistical rainfall parameters when modelling design rainfall). Catchment-scale topographic data is needed to provide catchment physical parameters such as area, slope, stream length etc. for input to the rainfall-runoff model. For this purpose, topographic data of relatively coarse resolution (coarse compared to what is needed for floodplain hydraulic modelling) can be used. There is LiDAR data available for the whole of Timor Leste which is held by the Ministry of Finance and will be made available for the project with no cost.

Model calibration will be approached by adjusting hydrological parameters that control the percentage runoff, time to peak and rate of runoff as well as baseflow and comparing modelled and observed hydrographs. There is limited hydrometric records for Timor Leste, but through the ALGIS project, the hydrometric network is being expanded. In the early stages of the project detailed hydrometric data analysis will be conducted including data modelling to extend the usefulness of the existing data.

For rapidly responding sub-catchments like those in the steep upstream catchments, rainfall-runoff modelling requires sub-daily rainfall and flow data (e.g. hourly) for calibration. Sub-daily rainfall data is also required for development of design rainfall parameters. Design rainfall is rainfall that defines events of given probability or chance of occurrence (for example the 1 in 100year rainfall or rainfall with a 1% chance of occurring). For design rainfall-runoff modelling, historical rainfall data will be analysed statistically to derive the depth-duration-frequency (DDF) curve which will give the rainfall depth for different return period storms of different durations (or existing DDF curves will be reviewed and used if appropriate). Again, sub- daily data is most appropriate as it allows the derivation of storms of all durations. If sub-daily rainfall data is not available for this analysis, a standard distribution can be used to derive the hyetographs for rainfall- runoff modelling. A rainfall-runoff approach is proposed here for the development of design flood hydrographs, as it will ensure that account can be taken of the influence of floodplain storage within catchments. Rainfall-runoff modelling is best suited to investigating climate and land use change impacts, and for exploring factors such as the travel time of flood peaks, which are important for designing flood forecasting and early warning systems, and for informing disaster response planning which rely on accurate estimates of time of arrival of peak flows.

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The hydrographs generated by the rainfall-runoff model will be scaled to match flood peaks derived from a statistical analysis of historical gauge data if data of sufficient length and quality is available to develop an appropriate statistical analysis of flood peaks. If gauged data for the study catchment is limited there may be a need to adopt a regional approach by first extending the analysis to include gauges for hydrologically similar catchments perhaps in the Indonesian side of the island. The resulting runoff hydrographs will be used as input to the hydrodynamic model described in the following section.

Hydraulic modelling A hydraulic model of each floodplain will be developed to route the flood hydrograph through the channel and floodplain of the study basin. To develop such a model, the main data requirement is high resolution topographic data of the channel and floodplain which will be acquired as follows:

Channel topography Normally, channel topography would be provided by undertaking channel cross-sectional surveys. To take account of the channel in the hydraulic model, a topographic survey of the river channel will need to be conducted, to capture the main changes in the longitudinal and cross-sectional river profile along key reaches. Survey density (cross-section spacing) would normally vary depending on whether the area is highly populated or more rural to ensure that the highest risk areas are well covered. Whether an area has historically flooded is also a key factor, as well as future flood risk under climate change. Hence in the unpopulated and low risk parts of the basin, cross-sections survey spacing can be sparse, while in densely populated areas or areas of historical flooding, or likely to flood in the future, it would be desirable to have cross-sections more closely spaced. These guidelines can be tempered by the variability of the channel profile in these areas. It may be necessary to forego cross-section surveys in some areas altogether and extract the data from the floodplain DEM for constructing the model in these areas. Alternatively, if the channel profile is changing very rapidly, closer spacing might be required. In some low-lying areas, where floodplain flow dominates or where the channel bed is exposed during floodplain DEM surveys, cross- section surveys can also be foregone since the DEM data will be high resolution LiDAR. It should also be noted that the river beds in Timor Leste are often dry for large portions of the year, particularly in the lower reaches, which means that LiDAR surveys could have captured the bed levels along the river, eliminating the need for channel surveys. It should be noted that any cross-section surveys that may be carried out as part of this study will be a ‘snap-shot’ in time of the channel profile which will change with time. It would therefore be important to ensure that a programme of regular channel surveys is implemented particularly at gauging stations, critical infrastructure and along active reaches.

Any existing survey or as-built drawings for existing structures, as well as any reports on the original design would be useful to help to characterise structures such as bridges, and other structures across the river, as well as any linear structures such as existing river walls. Typically channel topographic surveys could take months to be completed, particularly for large areas and where seasonal weather conditions might hamper surveys. A detailed scope of the channel surveys will be developed at the start of the project and surveys will be scheduled based on the order in which basins are to be modelled.

Floodplain topography LiDAR data is very high resolution DEM data and will provide significantly enhanced accuracy for the hydraulic modelling in comparison other sources.

Using all topographic datasets, baseline models of the floodplain of the river basins will be developed, that represents the current catchment conditions, including current operation and maintenance practices for any structures on the main channel and floodplain as well as linear flood defences that influence the movement of water between the channel and floodplain. The baseline model will be used to assess the existing standard of protection (i.e. the minimum size of the event for which flooding occurs), provide clarity on the current flooding mechanisms within the catchment and serve as a baseline against which the economic appraisal of proposed interventions can be made.

The baseline model will need to utilize a mixture of 1D and 2D modelling techniques, based on the combined topographical datasets (i.e. floodplain DTM, channel and hydrographic survey data, if available).

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Appropriate channel, floodplain frictional resistance values can be estimated from photographs, land-use maps and site visits. Key structures of significance to flow conveyance will be identified for inclusion in the model.

The hydraulic model will need to be calibrated and verified in tandem with the hydrological model by varying channel and floodplain frictional resistance and structure discharge coefficients values until good agreement is obtained between modelled and observed levels and flows at key gauging locations or observed flood extent maps derived from historical flood surveys and satellite imagery. Calibration to historical events will need to be undertaken in the hydrological model, ensuring that the modelled runoff hydrographs fit the observed as closely as possible. Depending on the availability of data, calibration of the hydraulic model will be done to fit observed flood levels and extents at key locations for which observations are available. This will include anecdotal information from the communities affected by flooding, which will be collected as part of the social surveys. Anecdotal information will also be collected using participatory GIS methods where possible. All data available for calibration will be reviewed and ascertained during the early stage of the project to confirm this approach.

The extent of the detail with which the system can be represented will depend on the available data, including data that can be realistically collected during the study period. It is envisaged that the level of detailed representation within the model will vary along the various reaches within the catchments and from sub-catchment to sub-catchment. The hydraulic model will be created to ensure that the urban and important agricultural areas and those identified as significant to the cause and/or effect of flooding, are well represented. Where necessary, less significant reaches and sub-catchments may be modelled using simple routing models which will link into the more detailed hydraulic reaches. Should risks be identified or more detailed information (like channel surveys) become available for the reaches designated as less critical now, the model could be easily updated to enable full hydraulic modelling along these reaches.

It is important to note that model accuracy will be dependent on the quality of the input data, the extent of detailed topographical representation and the accuracy of modelling assumptions. Three significant sources of error may be the accuracy and spatial resolutions of the topographic data used to build the model, choice of model parameters such as roughness (frictional resistance) and discharge coefficients, particularly for over bank flows.

The calibrated and verified hydraulic model will be used to run design events of different annual probability (return period) of occurrence, to produce flood maps. Sensitivity analyses

Given the uncertainty that is likely to be associated with the limited datasets and possible data quality issues, several sensitivity analyses will need to be done. This would provide an assessment of likely uncertainty as well as areas where attention should be focused in subsequent analyses, to improve certainty.

Roughness Initial channel roughness values will be determined from field surveys which will characterise each reach of the river based on vegetation type and density and channel geometry and classification (i.e. bed material grain size and bedforms). Land-use maps can be used to generate roughness polygons for the floodplain areas within the 2D model extents. Assumed roughness values will need to be varied within practical bounds to determine the sensitivity of peak flow rates to the choice of roughness.

Hydrological parameters The hydrological model will be a potential source of error which will propagate to the hydraulic model. It will therefore be important to assess the effect of hydrological parameter uncertainty on flood extent. This will include catchment runoff coefficients, and uncertainty in rainfall data.

Sedimentation in the channel

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Given the geomorphologically active nature of many of the catchments, and the likely impact this will have on flood flows, it would be important to examine the sensitivity of the model to changes in sedimentation in the channel. It is unlikely that this can be done for the entire system, so based on the preliminary geomorphological studies to be done a number of key locations could be chosen to examine the variability of flood extent, levels and velocities to varying sedimentation within the channel. This will provide an assessment of the impact on flow conveyance and channel capacity caused by different levels of sedimentation and would give a good indication of the benefits of channel dredging and long-term maintenance as a management option in areas where this is an issue.

Flash Flood Hazard Mapping Flash floods are defined as events which cause flooding within 6 hours of the occurrence of the rainfall event. Flash floods essentially occur where precipitation cannot infiltrate either because rainfall intensity is such that the rate of rainfall is faster than the rate of infiltration into soil, or where slopes are so steep that water runs off at a faster rate than it can be absorbed. Also, where hard standing surfaces such as buildings, roads and other impervious surface cover large areas with insufficient urban drainage capacity built in to the urbanisation, flash flooding may occur. Hence flash flooding is a function of the intensity and duration of rainfall, antecedent soil moisture conditions, slope of the ground and presence of hard standing surfaces, with limited drainage. Several issues will need to be considered in flash-flood hazard and risk map delineation: 1) Flash-flood prone areas can be identified in a first approach by using meteorological criteria, in terms of rainfall amounts and intensities above a threshold that have impacted the same area in the past. 2) Geomorphologic criteria are of primary importance in flash-flood prone areas, and modelling of solid transport is particularly important, since it highly affects the extent of the flood. 3) Classical 1-D hydraulic modelling for hazard delineation may not be useful in small to medium flash- flood prone areas. 4) Risk assessment is of great importance in flash-flood prone areas, because many areas may have been highly developed and thus presenting a high vulnerability. 5) Flash-flood risk maps should therefore comprise of: hazard identification by delineated extents mainly based on meteorological and geomorphologic aspects, and vulnerability analysis to prevent or mitigate settlements on hazard areas from suffering their devastating effects.

The hydrological modelling will identify fast responding catchments during the rainfall-runoff analysis. The assessment will classify sub-catchments by response time (time between start of rainfall and peak of runoff) from which catchments with response times less than 6 will be identified as at risk of flash flooding and categorised by severity (shortest response time to largest response time). More detailed assessments will be conducted on these catchments to map the communities that likely to be susceptible to flash flooding. Importantly, knowledge of the flashy response catchments will help identify where flood forecasts cannot be based on combined meteorological and hydrological factors (i.e. rainfall forecasts plus trigger river flow or level information), as there will be insufficient time for the hydrological response to determine what action should be taken (i.e. river levels should not be the trigger for issuing warnings and undertaking evacuations). Flashy catchments would benefit from meteorological forecast triggers for flood warning and response.

Modelling the impacts of climate and land-use changes Climate Change A benefit of rainfall-runoff hydrological modelling is the ability to assess the impacts of future climate change on catchment hydrological response such as flood magnitude, time to peak (time between peak rainfall and peak flow at specific locations) and event duration. Work has already been done to examine the effects of climate change on rainfall events in Timor Leste (Initial National Communication). As part of this project, a methodology for incorporating the effects of climate change into the modelling of flood risk will be developed to ensure that the findings of the Initial National Communication are translated into the likely changes to flood flows.

The impact of climate change will be modelled using a perturbation, or ‘delta change’, approach. This is a straightforward method that uses simple step changes that are applied to observed meteorological time

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I series. The magnitude and direction of these changes is derived from General Circulation Model (GCM) output to produce a set of monthly or seasonal change factors, which are in turn applied to the observed series. Perturbed time series can then be run through rainfall-runoff models to ascertain the subsequent impact on flow in that catchment.

This method requires the following steps to be undertaken: Selection of projections: Identification of appropriate GCM projections, such as the UNDP country climate profiles or the new World Bank Knowledge Portal. Appropriate selections will be made for emissions scenarios (Low, Medium and/or High) and time slice(s) (i.e. which time period to focus the analysis on).

Model selection: Projections from three climate models will be selected from those available, representing ‘wet’, ‘dry’ and ‘mid’ future. This gives an indication of the uncertainty across the models. This stage will also include a validation exercise for the selected models, to ascertain their reliability in simulating conditions in Timor Leste.

Scaling: It may be considered preferable for nearer-term timescales to scale back rainfall projections from the end of the century. This would reduce the influence of multi-annual and decadal variability on the climate change signal.

Derivation of PET factors: GCM projections are available for temperature and rainfall; however, for use in a rainfall-runoff model, change factors for potential evapotranspiration (PET) are required. PET change factors will be derived from the temperature projections.

Grid cells vs. catchment boundaries: Change factors are provided by GCM grid cell. For any catchment used in the rainfall-runoff modelling that bestrides more than one grid cell, it will be necessary to apportion the change factors accordingly. This will be calculated in GIS software.

The selected seasonal change factors can then be used to perturb a baseline observed series of rainfall and PET according to the delta change approach described above. This produces a series of plausible future climate time series to be used as inputs to rainfall-runoff modelling to ascertain the impact on flows.

A sensitivity analysis will also be undertaken of the change factors used, which will assess how the impact on flow varies with different approaches. The method above, for example, looks specifically at changes in mean conditions; additionally, it would be beneficial to consider other forms of change (e.g. differences in the number of dry/wet days) to see the impact on flow under these conditions.

Land use Change Impacts on flood risk It is likely that one approach to flood risk and erosion management will be to manage catchment land use, particularly on hillslopes. Conversions to new land uses or where land management practices are significantly altered can be modelled to examine their impacts, by making the necessary amendments to the hydrological and hydraulic model parameters. Changes to land use on the hillslopes and in the upper catchment would require re-parameterisation of the hydrological model, ideally based on empirical evidence of the changes in hydrological parameters for a given change in land use, from proxy catchments or regional studies.

Alternatively, sensitivity tests can be applied to hydrological response characteristics such as time-to-peak and standard percentage runoff to broadly assess the implications of change at various spatial levels. For changes to land use in the catchment (such as implementation of agroforestry), the hydraulic model parameters can be varied to represent the change in flood risk.

Choice of modelling software The flood model to be developed should ideally be comprised of an integrated hydrological and hydraulic model. A review of modelling packages will be undertaken in parallel with the review of available data, and the most appropriate modelling package chosen, based on the data available for modelling, the important

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I flooding processes to be represented in the model, the need/desire to ensure that the model is updatable (i.e. sustainable) in the future as more data becomes available.

Hydrological model The hydrological modelling tool will need to include individual rainfall-runoff models of all upstream sub- catchments as upstream and lateral inflows to the hydraulic routing model. The modelling framework should also include a tool for assessment of impact of (sets of) flood mitigation measures and development scenarios, as well as the assessment of flood risk under climate and land use changes using projections for climate and land use changes in longer time scales. Many proprietary hydraulic modelling software packages incorporate standard and well established hydrological models such as Hec-HMS, US SCS, Probability Distributed Moisture (PDM) model. Other hydrological modelling software that can be used includes well-known hydrological models such as TOPOG, TOPMODEL and physically-based rainfall runoff models, but these are likely to require extensive datasets that are unlikely to be available. Ideally, the model used for flood rainfall-runoff hydrological modelling should also be applicable for lowflows water resources rainfall-runoff modelling (for sustainability of use in the management of the basin in the future). It is envisaged that Hec-HMS will be used for undertaking the hydrological modelling.

Hydraulic Model In determining the modelling software to be used, it is important to consider the processes that are important to flood risk in the study area. It is likely that a model capable of 1-dimensional as well as 2-dimensional flood process representation, and ideally a linked 1D-2D model will be needed. This will enable modelling of the 1-D processes that are important within the upstream reaches and where channel processes dominate, and will ensure that changes in channel cross-section profile along the river as well the influence of hydraulic structures like bridges, dams and weirs, and natural hydraulic controls on flooding, are correctly represented within the model. The 2D capability will ensure accurate representation of floodplain flows particularly in the middle and downstream reaches where flow propagation along complex 2D flow paths dominates. Along reaches where flow exceeds channel capacity and propagates along the floodplain along 2D flow paths a linked 1D-2D model will be more appropriate to represent the interlinked 1D and 2D processes. In some places, and depending on the availability of data for channel and floodplain representation, it may be necessary (or appropriate) to use 1D or 2D modelling alone.

There are a number of models which are capable of linked 1D-2D modelling and 2D modelling on its own, including Mike Flood, ISIS-Tuflow, ISIS 2D, Info Works 2D, HydroF, SOBEK 2D, and Flo-2D. Ideally, the chosen model will include full solution modelling of open channels, floodplains, and hydraulic structures (even if the data to support this is not currently available, it will be important to use modelling software that will be updatable should additional data become available in the future).

A GIS-based model which provides the facility to import ground elevation models, as well as other types of topographical data and which enables full flood mapping capability is desirable. Flood depth, velocity and hazard mapping outputs in all standard GIS formats will also be a plus. The choice of modelling software will need to be cognizant of cost of implementing and maintaining the model as well as the maintenance of capabilities in using the models. The decision on software will therefore be made following consultation with the eventual custodians and end users of the model, and within the framework of capacity building and institutional improvement.

Data availability for flood hazard modelling and mapping

The Agriculture and Land-use Geographic Information System (ALGIS) is an institution within the Ministry of Agriculture and Fisheries (MAF) which was established by FAO and issues monthly reports about climatological conditions for agricultural purposes.

ALGIS has 12 automatic stations in Timor Leste. Information from these stations is collected manually and no telemetry capabilities exists within these stations at the moment. ALGIS collaborates with NDMD/NDOC during disasters, especially during flood and fire disasters. They coordinate the response from a village point of view, undertaking assessment of the community needs and providing relief. ALGIS also seems to

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I send information about rainfall during the rainy season, although how this is accomplished and what type of information is shared is unclear.

Seeds of Life (SoL) maintain a wide network of automatic weather stations. Most their automatic stations have no telemetry capabilities yet, but an upgrade of this system is taking place and four of their stations are sending data automatically. All the information from the automatic stations is sent to National Directorate for Meteorology and Geophysics (NDMG) which has a database with information from all the different weather stations in the country.

The National Directorate for Water Quality and Control (NDWQC) is a directorate within the Ministry of Public Works and Transport Communication maintains a manual weather station network.

Monitoring and forecasting responsibilities generally fall within the National Directorate for Meteorology and Geophysics (NDMG) role in Timor Leste. However, NDMG capacities are very limited and therefore hydrometric monitoring in Timor Leste is very poor.

Hydrometric Observation Network There is a wide network of weather stations in Timor Leste (Figure 0-1). A total of 82 weather stations are present in Timor Leste. The features of these stations and their condition vary widely. Only four of these stations are believed to have telemetry capacities at this stage, and some of them are manual stations. NDMG is responsible for collecting all the information from all the weather stations in a database.

There is very little information about hydrological stations in Timor Leste, although some information has been found about the Norwegian Water Resources and Energy Directorate’s International Sector or about the HydroChina ZhongNan Engineering Corporation deploying hydrological stations in Timor Leste, but no information about the success of these missions. Very few information is available about stations deployed in Timor Leste previously. In the 1980’s the stream-flow measurement network in Timor-Leste consisted of four automatic water level recorders (AWLR) and 2 staff gauges. It seems that data for none of these stations is available and/or none of these stations were operational for a continuous significant length of time.

Given the paucity of hydrometric data available for Timor Leste (particularly with respect to historical hydrological data), flood hazard modelling will be heavily reliant on the use of meteorological data, physical data about the catchments (DEM, soil, land use, geology) and extensive sensitivity testing of model outputs.

It is understood that LiDAR DEM data is available for the entire territory, which will be a positive as it will allow hydrological and hydraulic modeling to be conducted to a high spatial resolution, although model calibration and validation will not be possible.

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Figure 0-1: Timor Leste weather station

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11.1.2 Landslide Hazard Assessment and Mapping

Because of the difficulty of specifying a timeframe for the occurrence of a landslide, landslide is often represented by landslide susceptibility (Brabb, 1985). Hence similar to the concept of flood prone areas, landslide susceptibility only identifies potentially affected areas and does not imply a timeframe when a landslide might occur. Hence landslide hazard will equate to landslide susceptibility. Landslide hazard maps will be produced and will be a key climate risk information dataset for infrastructure siting, design and construction decisions in the future.

The data required to undertake landslide hazard mapping includes geologic, topographic, hydrologic, vegetation maps, aerial photographs of the study area, history of landslides and associated reports including photographic characterisation of previous landslides, satellite imagery.

During the early stages of the project, these data sets will be collected and a landslide inventory map produced. In this preliminary assessment, an isopleth map of existing landslides will be produced using a combined factor analysis of bedrock, topography, landslide inventory and hydrology. Isopleth maps show areas of frequent or infrequent landslide occurrence. The isopleth maps produced during the early stage will be used to help to focus the more detailed analysis during the later stages of the project.

Assessing the likelihood of future landslide occurrences requires an understanding of conditions and processes controlling past landslides. This can be achieved by examining and mapping past landslide activity in the area. Overlaying a map of past landslides with geologic topographic, and hydrologic maps, will indicate which natural or artificially created circumstances are likely to produce landslides in the future. In addition, the effect of existing land use on landslide activity will also identify where anthropogenic factors such as inappropriate land use, increases the risk of landslide occurrence. For example, certain landslides may only occur in road cuts or excavations. Landslide susceptibility is also higher on degraded land than on managed land.

A review of any existing landslide inventory maps will be undertaken and updated as part of the study to intermediate and then detailed landslide inventory maps. The effort to produce detailed inventory maps will depend on what level of detailed mapping already exists. As part of this project, field studies of selected landslide prone areas will be undertaken to provide insight into how different factors have contributed to landslides in the catchments of Timor Leste and to characterise the conditions associated with selected landslide prone area, to be incorporated into the landslide inventory. Given the size of the country and number of catchments, it will not be possible to develop the map of past and existing landslides solely from field work. Hence aerial photographs, where available, will be used to supplement field work. Depending on vegetative cover, photo quality, and the skill of the interpreter, overall identification accuracy of 80 to 85 percent is realistic using aerial photography. Development of landslides inventory maps requires a geologist with experience of landslide or landform interpretation. A simple inventory identifies the definite and probable areas of existing landslides and is the minimum level required for a landslide hazard assessment. A map is produced in which each landslide is outlined and an arrow is drawn to denote the direction it moved.

The map produced would also show the outlined landslide types and distinguish between areas of landslide origin and deposit. Large-scale features such as secondary scarps sag ponds, and ground-crack patterns may be represented on individual landslides.

Producing the Landslide Hazard Map

The landslide hazard map is generated based on the overlaying, analysis and interpretation of the maps of the inventoried landslides and the permanent factors found to influence the occurrence of landslides discussed above. By overlaying the landslide inventory map on the maps of the type of bedrock, slope steepness, and indirect hydrologic measures, the association of past landslides with the factors controlling landslide occurrence can be recognized.

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The hazard map produced will divide each catchment into sub-areas based on the degree of a potential hazard from landslides. Four levels of relative hazard are identified on a landslide hazard map: (1) low; (2) moderate; (3) high; and (4) extreme hazard. The level of landslide hazard is measured on the ordinal scale with this method and is a quantitative representation of differing hazard levels that shows only the order of relative hazard at a particular site and not absolute hazard. Predicting absolute hazard is not possible with current capabilities. Consequently, there is no way to compare hazard zones at different sites or to determine the likelihood of occurrence at a high hazard area. It should be stressed that these relative hazard zones are based on the existing landslides and conditions influencing their occurrence in a specific area. The hazard zones which are determined for an area hold true only for the area for which they were prepared. Similar conditions found outside the assessed area may not produce the same degree of hazard because of some seemingly minor difference in one of the factors.

However, extrapolating the data to areas with characteristics similar to those found to be associated with past landslides is an effective tool for forecasting where, but not when, landslides are likely to occur in the future.

The method of landslide hazard mapping described above will rely heavily on the interpretation of a geologist or geotechnical engineer and is an essential first step of landslide hazard mapping. This initial assessment will utilise GIS mapping and analysis to produce landslide hazard maps. Depending on the availability of datasets, statistical and/or physically-based modelling methods will also be applied to map landslide hazard and will be subject of more detailed analysis.

11.1.3 Drought Hazard Assessment and Mapping

Drought is a natural hazard known to be very difficult to quantify as its general characteristics, creeping onset, long lasting duration, large spatial extent and cross boundary effects have hindered scientists and practitioners to precisely define the hazard. Even though most drought impact research and public recognition focuses on the agricultural sector, drought has more damage potential. Its multifaceted character affects a variety of environmental and socioeconomics systems that can be classified into several different categories.

Commonly, the drought hazard is described by one or a set of drought indicators. For example, Standard Precipitation Index: The Standardized Precipitation Index (SPI) is a tool which was developed primarily for defining and monitoring drought. The SPI allows an analyst to determine the rarity of a drought at a given time scale (temporal resolution) of interest for any rainfall station with historic data. It can also be used to determine periods of anomalously wet events. Mathematically, the SPI is based on the cumulative probability of a given rainfall event occurring at a station. Palmer Drought Severity Index: The Palmer Drought Severity Index (PDSI) uses readily available temperature and precipitation data to estimate relative dryness. The PDSI has been reasonably successful at quantifying long-term drought. As it uses temperature data and a physical water balance model, it can capture the basic effect of global warming on drought through changes in potential evapotranspiration.

The standardized precipitation and evapotranspiration index (SPEI) (Vicente Serrano et al 2010a) has become popular in recent years. But, even though more than 100 drought indicators are known and have been compared in a number of studies, clear guidance on their usage is still lacking. One reason for this is that most indices describe general anomalies of meteorological conditions, but only few drought indices were developed with or have been tested against observed drought impact data. Vulnerability to drought is typically estimated by a combination of relevant, subjectively weighted vulnerability factors which requires explicit but difficult to obtain information on physical, ecological and socioeconomic parameters. Although drought impacts are symptoms of vulnerability the majority of current approaches do not consider past drought impact reports to estimate vulnerability, and only a few studies have validated their approaches using historical drought impact observations (Aggett 2012, Naumann et al 2013, Karavitis et al 2014).

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The SPEI is an evolution of the well-established standardized precipitation index (SPI) (McKee et al 1993) and was developed to not only account for water input through precipitation, but also for water losses through evaporation. In contrast to SPI, which has a limited interpretability in dry regions (Wu et al 2007), SPEI has been shown empirically to be a better suited predictor for several environmental variables than SPI, including river flow (Lorenzo-Lacruz et al 2010, López-Moreno et al 2013) and can be derived from widely available meteorological observations used for drought quantification.

Timor Leste does not hold long historical datasets of precipitation and temperature so a review historical data, will be undertaken to determine which indicator will be used to calculate drought susceptibility. Drought indicator will be calculated for each grid cell within each catchment model and for each month within the year, resulting in a drought hazard map by month and a drought susceptibility map. The results will be calibrated on observed droughts, in particular the recent drought of 2016.

11.1.4 Soil Erosion Hazard modelling and Mapping

Soil erosion threatens agriculture, natural resources and the environment due to the loss of fertile topsoil for agriculture, siltation of streams and lakes, eutrophication of surface water bodies and loss of aquatic biodiversity. Management practices to minimize these problems can be effectively carried out if the magnitude and spatial distribution of soil erosion are known. Soil erosion models can simulate erosion processes in the watershed and may be able to consider many of the complex interactions that affect rates of erosion. Soil erosion models are categorized as empirical, semi-empirical and physical process-based models. The most commonly adopted empirical models are the Universal Soil Loss Equation (USLE) (Wischmeier and Smith, 1965) and Revised Universal Soil Loss Equation (RUSLE) (Renard et al., 1991). Other models like the Erosion Productivity Impact Calculator (EPIC) (Williams et al., 1990), European Soil Erosion Model (EUROSEM) (Morgan et al., 1992) and Water Erosion Prediction Project (WEPP) (Flanagan and Nearing, 1995) are also used to estimate the status of soil loss. These methods analyze soil erosion by attempting to estimate the volumes or masses of soil loss. However, soil erosion by water is one of the major causes of land degradation and, therefore, it is necessary to establish soil conservation measures to reduce the land degradation and ensure development of a sustainable management of soil resources. The implementation of effective soil conservation measures must be preceded by a spatially distributed erosion hazard and risk assessment and the development of soil erosion hazard mapping.

Soil erosion hazard mapping is an essential tool for planners and policy makers initiating remedial measures and for prioritizing areas. The approach which will be adopted here will use a numerical model of soil erosion hazard assessment, using GIS to compute a synthetic soil erosion hazard index (SEHI). The main parameters which impact on soil erosion will be generated using catchment topographic and soil datasets as well as remote sensing data.

Soil Erosion hazard mapping will require the following datasets: 1) Land use and land management practices (satellite imagery e.g. Landsat) 2) Soil type maps 3) Digital Elevation model (LiDAR data) 4) Monthly rainfall data 5) Population data

Soil erosion rates can be calculated to predict soil erosion rates under different resource and land- use conditions. Several models and methods can be used to predict soil erosion. Empirical erosion prediction models continue to play an important role in soil conservation planning and are widely used to predict soil erosion. The Revised Universal Soil Loss Equation (RUSLE) (Equation 1) will be adopted for the assessment of soil erosion in Timor Leste.

A = R × K × L × S × C × P (1)

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I where A is the soil loss in t ha−1 year−1; K is the soil erodibility factor (thahha−1 MJ−1mm−1); R is the rainfall- runoff erosivity factor in MJmmha−1 h−1 year−1; L is the slope length factor; S is the slope steepness factor; C is the cover and management factor and P is the conservation practices factor. The L, S, C and P values are dimensionless. For each of the factors in equation 1, individual maps will be generated in raster GIS for each grid cell within each catchment.

For the C factor, the classified land cover map will be converted to the C factor layer through reclassification of each land cover type by its corresponding C value, which was estimated from the RUSLE guide table (Renard et al., 1997). While the P factor will be assigned according to the conservation practice in the area which ranges from 0.0 to 1.0, with the highest value assigned to areas with no conservation practices. Conservation information will be assessed from, survey based on the past and current management status and aerial photographs of the catchments. The six RUSLE factors will be integrated in a GIS environment and classified as four levels of erosion: low, moderate, high and very high.

11.1.5 Multi-hazard mapping

In addition to hazard maps for individual hazards, a multi-hazard map (MHM) will be developed for all major river basins in Timor Leste.

The main purpose of MHM is to gather together in one map the different hazard-related information for a study area to convey a composite picture of the natural hazards of varying magnitude, frequency, and area of effect. A MHM may also be referred to as a "composite," "synthesized," and "overlay" hazard map. One area may suffer the presence of a number of natural hazards. Using individual maps to convey information on each hazard can be cumbersome and confusing for planners and decision-makers because of their number and their possible differences in area covered, scales, and detail.

Many natural hazards can be caused by the same natural event. The inducing or triggering mechanism which can interconnect several hazards can more easily be seen through the use of a MHM. Characteristics of the natural phenomenon and its trigger mechanisms are synthesized from different sources and placed on a single map.

Additionally, the effects and impact of a single hazard event, include different types of impacts, each having different severities and each affecting different locations.

The MHM is an excellent tool to create an awareness in mitigating multiple hazards. It becomes a comprehensive analytical tool for assessing vulnerability and risk, especially when combined with the mapping of critical facilities. It is also useful in infrastructure design and construction, particularly in a country like Timor Leste where small scale infrastructure in a given area can be susceptible to multiple hazards, all of which can be triggered by the same set of long-term/creeping conditions as well as single events.

The adoption of a multiple hazard mitigation strategy also has several implications in Disaster Risk Management and emergency preparedness planning. For example, it provides a more equitable basis for allocating disaster planning funds; stimulates the use of more efficient, integrated emergency preparedness response and recovery procedures; and promotes the creation of cooperative agreements to involve all relevant agencies and interested groups.

11.2 Risk and Vulnerability Modelling and Mapping

This short review summarises the salient features of the detailed methodology in the Economic Commission for Latin America and the Caribbean’s “Handbook for Estimating the Socio-economic and Environmental Effects of Disasters” published in 4 volumes.

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At the outset it is important to evaluate which damage and loss receptors are essential, nice to have and irrelevant in Timor Leste. A case for irrelevancy must be made on the grounds of proportionality, that is the effort involved in collecting and analysing data is far greater than their proportional contribution to total damages or losses derived when measured as a benchmark to per property at risk, per head of population or GDP (national or local). It is important not to waste too much time in monetary quantifications that do not yield applicable results.

Preventing a natural disaster should be a high yield investment and the investment of mitigation measures should be less than the loss of assets and loss of production associated, discounted over the lifetime of proposed measures. Damages and losses should be expressed in monetary terms where it is practical to do so and split into Direct and Indirect Losses within Social and Economic sectors (damage and loss receptors) and infrastructure. These are defined as follows: • Social Sectors o Affected Population o Housing and Human Settlement o Education and culture o Health

• Economic Sectors o Agriculture o Trade and Industry o Tourism

• Infrastructure o Energy o Drinking Water and Sanitation o Transport and Communications

Damages and losses should be divided into these sub sector categories but there should be also an emphasis on differentiating flood risk on socio-demographic grounds to highlight the consequences of flooding on the most vulnerable and poorest members of society and from a gender perspective. A prime goal should be to investigate vulnerability reduction in areas of greatest susceptibility for those with least coping strategies. Size and population demographics should be disaggregated to identify high-risk categories (children under five, nursing mothers and pregnant women, the disabled and the elderly, etc.)

A natural disaster is in fact a ‘disinvestment’ and the scale of economic losses and damage depends on the scale of disinvestments or assets lost; how this impacts on the flow of goods and services; and how long disruption of these flows will be affected. Accumulating these factors will equate to total loss, but total loss must be viewed in relation to the effect on the national economy or regional economy, however defined. In worst case scenarios, there could be a Macro-economic meltdown and a rate of recovery spanning several years. Macro-economic analysis of natural disasters is complementary to damage or loss assessments to each defined sector. This will look at the effect on employment, tax revenues, income, exports, imports, health and welfare provision etc. as a result of business and community disruption during the flood and post flood recovery. For example, imported components of resources to repair/replace assets damaged will affect the balance of payments. Macro-economic analysis and Sector analysis should not be combined as this may lead to a double counting of losses. Again, analytical proportionality is the key to success. There is usually an interesting trade off between GDP and gross investment decline as a result of a natural disaster and a boost during the reconstruction period. Disasters may have a positive effect in allowing inward investment during restoration and force economic renaissance or regeneration that would otherwise not have been contemplated. Thus, not all resource streams as a result of a disaster will be negative.

It is crucial to select an appropriate method for evaluating asset damages using either depreciated costs or replacement costs or, what are becoming increasingly fashionable, the application of proportional loss

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Direct Physical Damage and Economic loss estimation can be a ‘bean counting’ exercise whilst indirect damage estimates need to be more considered in relation to available resources. Scale and analytical complexity is implicit here. Potential damage, lost production at petrol-chemical industries may be straight forward to evaluate and express in monetary terms, but loss of schooling or health care facilities may be of hugely significant societal importance but unfathomable to evaluate let alone quantify within the timescale of the project. Thus, there may be a danger of diverting remedial actions from where societal needs are greatest to where economic benefits are proven. This will be a challenge.

Before a sectoral assessment of damages and losses can begin defined geographical areas of risk are required for selected natural disaster. Then for each sector the following sequential analysis is required:

• Identification of direct damage or effects; • Quantification of direct damage or effects; • Valuation of direct damage or effects; • Identification of indirect losses; • Quantification of indirect losses; • Valuation of indirect losses; • Development of a typology of affected property according to size, prevailing construction materials and type of ownership; • Determination of the geographic or spatial distribution of total physical damage and economic losses; • Assessment of corresponding social effects; • Assessment of macroeconomic effects; • Assessment of the impact on employment; • Assessment of the impact on women or minorities

11.3 Detailed Data Requirements

A summary of data attributes for each sector follows as a hierarchy of requirements. Thus, it is not sufficient to know the number of dwellings but how many of these are single or multiple storeys and of these which are of solid construction and which are temporary and then whether of single or multiple occupancy.

Sector 1st Order 2nd Order 3rd Order 4th Order Housing and Number of Single Solid or Single or Human dwellings storey/Multi temporary multi settlement Storey construction occupancy Education Number of Solid or Education Number of schools temporary level students/ construction classrooms Cultural Number of Classification Size Visitor Heritage Buildings/Open (schools, Numbers spaces/ sports libraries, arenas museums) Health Number of Characteristics Health care Geographical Health care (day centre, workers, coverage/ facilities Hospital) equipment

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and medical catchment supplies area Energy- Number of Km Energy electricity Electricity Transmission Distribution Generation and Centres Plants Distribution Systems Energy-oil Number of Number of Oil Distribution Production refineries facilities facilities Drinking Number of Km of Population Water supply Water Water Distribution served rates treatment Networks plants Sewage Number of Km of Population Treatment Treatment Sewage Sewerage served volumes Treatment Systems plants /Septic Tanks Irrigation Number and Km irrigation Agricultural infrastructure Location plant Areas served Transport - Type of road Volumes of Alternative Roads surface by km traffic routes Transport - Number of Km of Track Volume of Railways Railway traffic Stations Transport - Number of Port Number of Tonnes of Harbours facilities Ships cargo and passengers Agriculture Numbers of Hectares of Production Numbers of farms land types Livestock Trade and Type of Numbers Productive Value Added Industry enterprise by Employees capital size (large, stock medium, small)

For all these sectors or receptors, asset values for building fabric, stock and equipment is required.

For each of the damage sectors an evaluation is required of:

• Direct damages and economic losses • Indirect damages and economic losses • Macro-economic affects

Whilst Direct damages and economic losses are easier to enumerate and quantify than Indirect damages/losses, the scale of macro-economic affects will generally relate to the scale of the disaster. The following generic affects may be associated with some or all of the Sectors identified but the tables below pick out specific affects which may not always be significant and worthy of further exploration:

• Effects on Gross Domestic product (GDP), largely through reduced output • Effects on Gross Investment; predicted investment must be put on hold and investment concentrated on repair/recovery; damaged stocks must be replaced and there will be an unexpected financial burden on repair and recovery

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• Effects on the Balance of Payments through decreased exports and increased imports of goods and services. Funding may be relieved through delivery of money and or resources from donor organizations outside the country • Effects on Public Finances through lost tax revenues or decline in public utility and other revenues and increased outlay for reconstruction and damage repairs • Effects of Prices and Inflation through the increased price of commodities and construction materials • Possible effects on employment • Differential effects on women • Impact on the environment

Housing and Human settlement

Direct damages Indirect Damages Macro-economic affects Buildings, Furniture and Temporary Accommodation/ Effect on GDP of reduced equipment refuge housing leases Clean up of Homes, including Post flood vulnerability Increase in Construction possible demolition reduction (resilience and sector resistance measures) Cost of re-connecting public Relocation of destroyed Effect on external sector services properties through increased imports for repairs Clean up of public areas Land purchase for re-location Effect on public sector away from flood plain responsible for post flood recovery Effect on prices and inflation through shortage of materials Effect on employment and income

Education and Culture

Direct damages Indirect Damages Macro-economic affects To stock, buildings, Temporary lease of premises Loss of contribution to furnishings, equipment and to provide ongoing cultural/ development growth rate collections educational services because of impaired education from long term flooding Special treatment for heritage Post flood vulnerability Temporary loss of buildings reduction (resilience and employment in the sectors resistance measures) Special treatment for Relocation of destroyed Effect on external sector moveable goods and archives properties through increased imports for repairs Clean up Income not received as fees or Effect on public sector income responsible for post flood recovery Cost of transferring Effect on prices and inflation undamaged items to new through shortage of materials premises

Health Sector

Direct damages Indirect Damages Macro-economic affects

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Health sector infrastructure Costs of monitoring and Decline in activity in the and medical equipment controlling the spread of productive sector because of infectious and trauma contagious diseases Medications and vaccines Cost of additional medical and Losses should be measured in outpatient care especially to terms of the health sector’s vulnerable groups contribution to GDP Furnishings and fittings Decline and care of victim’s Temporary loss (or gain) of wellbeing and living standards employment in the sector Laboratories Post disaster vulnerability Effect on external sector reduction (resilience and through increased imports for resistance measures) repairs Relocation of destroyed Increase in public budgetary properties outlays needed to meet emergency health care, rehabilitation and reconstruction requirements NB Differential effects on Effect on prices and inflation women through shortage of materials

Energy Sector - Electrical

Direct damages Indirect Damages Macro-economic affects Damage to electrical power Cost of temporary supply of Foreign-currency spending for plants electricity equipment, materials and specialized labor that must be imported for the rehabilitation of facilities and machinery Damage to transmission, Foregone profits by electricity distribution, grids and suppliers substations Damage to energy distribution Lost/ foregone consumer centres, administration blocks opportunities for use of electricity, often far wider than flooded area

Energy Sector - Oil

Direct damages Indirect Damages Macro-economic affects Damage to oil production Temporary supply of oil and oil Effect on GDP because of facilities derivatives slowdown in oil production and refining Damage to oil refineries Impact on the environment as Foreign-currency spending for a result of oil spillage equipment, materials and specialized labor that must be imported for the rehabilitation of facilities and machinery Damage to distribution Temporary loss of facilities including storage and employment in the sector pipelines

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Drinking Water and Sanitation (including waste disposal facilities)

Direct damages Indirect Damages Macro-economic affects Damage to Infrastructure and Impact on the environment Foreign-currency spending for equipment (Treatment works because of sewage spillage equipment, materials and and pumping stations) and contamination be solid specialized labor waste that must be imported for the rehabilitation of facilities and machinery Loss of stocks (Chemicals, Reductions in potable water Temporary loss of stored water, spare parts) output and Distribution of employment in the sector drinking water by tanker/ bowsers Increase in potable water/ Affects on GDP due to sewage treatment production economic slowdown because costs of lack of available water Losses due to income not Possible changes in the price received by utilities of water Impact on health due to disruption in treatment/disposal

Transport and communications

Direct damages Indirect Damages Macro-economic affects Damage to roads, railways Resource costs in disruption, Effect on GDP especially diversion and delay in terms of because of closure of extra vehicle operational costs harbours and ports and passenger value of time Damage to water and air Loss of income to operatives General effect on employment transport (harbours, ports, and tourism marinas and airports) Damage to Loss of income/revenue to Effect on external sector telecommunications transportation hubs through increased imports for infrastructure repairs

Agriculture

Direct damages Indirect Damages Macro-economic affects Loss of farmland Opportunities foregone i.e. Loss of employment future production Physical infrastructure and Impact on the environment Future food security machinery Loss of livestock Export and import balances Lost Production (crops and Effects of producer prices, meat products etc.) wholesale prices and retail prices leading to inflation

Trade and Industry

Direct damages Indirect Damages Macro-economic affects Reconstruction costs of Lost production, value added Loss of tax revenue buildings

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Costs of assets lost Interruption of supply chain Effect on GDP through (equipment, machinery, affecting trade and industry imbalance of imports and vehicles) away from floodplain exports Costs of stock and raw Environmental impacts Foreign-currency spending for materials lost through contamination equipment, materials and specialized labor that must be imported for the rehabilitation of facilities and machinery Costs of work in progress lost Loss of employment temporary or permanent

11.4 Economic Loss and Damages current practice and feasibility of proposed technologies

11.4.1 Current DRM Policy and Guidelines in Timor Leste Timor Leste is extremely vulnerable to a whole range of hydro-meteorological hazards with especially the rural population dispersed in remote areas often inaccessible following catastrophic events. In response to this The Government of Timor Leste has developed a National Disaster Risk management policy29

The overarching objective of this Risk management policy is to: • Promote studies of the identification of risks zones; • Create early warning systems, particularly relating to rains and droughts; • Conduct training and capacity building of human resources in disaster risk management • Can provide immediate response when disaster occurs; • Establish inter-sectoral coordination mechanisms to respond to natural disasters.

The National Disaster Management Directorate (NDMD) has already established the Disaster Management Information System (DMIS), which has several GIS hazard maps for Timor-Leste’s common natural hazards. The disaster database named Desinventar allows data on hazard type, damage caused and mortality and morbidity to be recorded by disaster event. The veracity of this disaster database will be critically evaluated and improvements recommended to allow consistency of recording events and accessibility of data. The role of remote technology, particularly UAV (Unmanned Aerial Vehicles) or Drones, as complementary to existing manual data collection and recording procedures will be evaluated.

Specific Policy 3 of the Policy document relates to Emergency Disaster Reporting and Communication to the Public

Advice of a developing hazard or of the occurrence of a disaster will come from two main sources: • Official source (e.g. geological or meteorological international agencies, National Disaster Management Directorate (NDMD), Disaster Operations Centre (DOC), National Police of Timor Leste (PNTL), Forces of Defence Timor Leste (F-FDTL), District Administrators, UN Agencies); or • Unofficial sources, such as the church or other members of the public.

Any official (police, fire service etc.) or other person becoming aware that a disaster or major emergency has occurred should report the situation to the nearest District Administrator, Sub-District Administrator, police officer, civil security officer or fire service officer to verify its extent and accuracy. Once verified, the District Administrator or Sub-District Administrator will report to the DOC and NDMD.

29 MINISTRY OF SOCIAL SOLIDARITY Secretary of State for Social Assistance and Natural Disasters National Disaster Management Directorate National Disaster Risk Management Policy March 2008 Dili, Timor-Leste

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When there is advance warning of the likely impact of a hazard or when a disaster has occurred, it is the responsibility of the DOC to ensure that timely and appropriate warning messages are broadcast to the public advising of the degree of threat and action that should be taken. When the threat has abated, information will be passed to the public as well as to any search and rescue and recovery efforts that are underway. Departments and organisations should assist in this communication process by ensuring that all relevant information is forwarded to the DOC and NDMD. Clearly conventional means of communication can be time consuming and delay positive reaction to an event or disaster.

In the chaos created by a hazard event that multiple communication channels collecting and disseminating data about the event should be consistently robust and relay appropriate information relating to agreed physical and socio-economic attributes of the event. In short, who, what and where is affected. Conventional methods of data collection can be thwarted by the scale, access and lack of coordinating responsibilities.

3.2.3.2 of the policy document relates to Specific Policy on Post-Disaster Survey

The present policy recognises that organised surveys are a “very effective way of collecting standardised information on the impact of a disaster”. Survey teams, preferably with members from a range of different sectors, should be deployed to the affected area as soon as possible after the event. Annex 7 of the policy document provides standard forms for Flash Reports and Initial Reports. Copies of these standard forms are required to be held at national, district and sub-district level ready for use in an emergency. Standard instructions for survey teams are available with the forms. If required, the results of a survey can be passed by radio using the numbers on each section of the forms as a guide. It is suggested that rapid aerial surveys can provide a useful overview of the situation after a disaster and may be valuable in preparing for response, but these “are not an adequate substitute for a planned survey”.

Thus, the collation of disaster data relies on the smooth transition between survey teams in the field and District and national coordinators, which can be cumbersome and may blur the veracity of the data and thus hamper recovery and any agreed victim compensation.

3.3.2.1 of the Policy requires formal Damage Assessment Reports and Recovery Activities

District Administrators are responsible for preparing a full report on the impact of the disaster to the National Disaster Coordinator (NDC) within two weeks of the end of major response operations. These reports will be added to a similar report prepared by the DOC covering the national aspects of the damage. Again, reports appear to be separately assembled at separate locations which could again blur the veracity of the situation on the ground.

After considering the damage assessment reports, the NDC, may recommend to the Inter-Ministerial Commission for Disaster Management (CIGD) the establishment of a recovery program management committee appointed by the CIGD. Paraphrasing the instruction, the composition of the committee will be determined by the nature of the disaster, and this committee will be responsible for managing the recovery program and ensuring that the CIGD is informed of the progress of recovery activities.

3.3.2.2 of the Policy document outlines the process of Post-Disaster Review. The CIGD is responsible for ensuring that a thorough and accurate review of the activities and procedures used during a disaster response operation is conducted to ensure that the experience gained and lessons learned can be applied towards improving future mitigation, preparedness, response and recovery procedures. Advice is that the post-disaster review needs to be as comprehensive as possible and should, after a significant disaster, include the following aspects:

• Status of mitigation measures, preparedness measures and response plans prior to the disaster; • Communications; • Warning, including origin(s), transmission and receipt, processing, dissemination, action taken (by government, the community, etc.), functioning of warning systems;

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• Activation of the response system and mobilisation of resources; • Procedural aspects of the DOC including information acquisition, receipt, analysis, display, decision making, dissemination of information; • Assigning of tasks to organisations involved; • Operations conducted, including search and rescue, casualty handling, initial relief measures, clearance of vital routes/areas, evacuation, restoration of services; • Arrangements for emergency feeding, health, welfare and shelter; • International assistance arrangements; • Assessment of public education/awareness programs, in the light of community reactions; • Training aspects; • Provision of information for recovery programs; • Any special factors raised by the nature of the particular disaster; and • Research requirements revealed by the disaster.

If circumstances are appropriate the review can include input from specialists on future trends and developments. It is therefore timely that a review of improved technology-based procedures for managing the collection of physical damage and economic loss data, is instigated and considered as part of application for GCF funding.

11.4.2 NDOC’s Operating Manual The Government of Timor-Leste’s Ministry of Social Solidarity National Disaster Operations Centre has an Operating Manual 30 which was written to enable the National Disaster Operations Centre (NDOC) to meet its responsibilities efficiently and effectively. It provides persons working in NDOC with the guidelines and checklists they will need when carrying out their emergency duties. It is also a key reference for emergency preparedness activities such as training courses and simulation exercises.

The NDOC is responsible for ensuring that all necessary damage and needs assessments (DANAs) are undertaken. The information obtained from DANAs is an essential input for NDOC operational planning, and can be expected to guide a significant part of the activities of the NDOC. Details of the damage assessment process are given in Annex N of the document and summarised here.

NDOC requires information on the type and scale of damage which has been incurred, and the consequent needs, in order to assist organisations and communities with relief and restoration resources.

The following actions are required to be undertaken in the NDOC in order to assess properly the damage which has occurred and the needs arising from that damage: • Identify areas where it is likely that damage has occurred • Mobilise damage and needs assessment (DANA) teams to visit affected areas and collect data on the damage incurred and the needs arising from the damage • Collect data from the teams • Collate the data and produce damage and needs reports for each affected area

The outputs from this process (the damage and needs reports) can then be used by the NDOC to develop plans to respond to the needs identified. Currently this is very much a manual process passing forms backwards and forwards between Districts, sub Districts and NDOC which is time consuming and open to error or misinterpretation as data and instruction are passed up and down the command line.

The objective of the damage and needs assessment data collection process is to collect damage data in a consistent format with consistent criteria, to support later analysis of the impact of the emergency across all areas affected. The data is collected by teams mobilised from Dili, or from a nearby District, Sub-district

30 Government of Timor-Leste Ministry of Social Solidarity National Disaster Operations Centre Operating Manual Version 3 - 27 July 2009

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I or Suco office, at the request of the NDOC. The teams consist of trained personnel and use a standard Data Collection Form (DCF)31 as issued by the DOC. The table below summarises the data collected32.

Contents of the Observation Form

Type of Disaster Use of Property Occupant Type of House Level of Destruction Fire Residence Owner Permanent Total Strong Wind Large Business Occupier Semi Permanent Partial Lanslide Small Business Government Owned Temporary Minimal Inundation Other Rented Earthquake Other

As far as possible teams aim to complete one DCF per each Aldeia which has suffered damage. Appropriate representatives of the Aldeia and the relevant Suco then sign off the DCF before it is sent to the NDOC.

The process is convoluted with the Disaster and Needs Assessment (DANA) teams instructed to take the following steps when collecting data:

• Assemble at the nominated District, Sub-district or Suco office when notified by the NDOC. • Obtain the transportation and supplies, including the Data Collection Forms (DCFs) that are vital for undertaking the DANA task • Proceed to the relevant affected areas and complete the DCFs according to the training received. • Return to the nominated District, Sub-district or Suco office and arrange to transmit the collected data to the DOC. This is done manually with what appears to be significant multiple handling

The CDO is responsible for ensuring that DANA reports are prepared from the data collected by the DANA teams. This can be done using the facilities of the data base system33 in the NDOC, or, should this not be available for any reason, through a manual process of collation of the data collected.

The data is summarised as: Location Time of Last Category of Extent of Damage Report Damage Destruction

With important operation information as follows: Roads Roads Preferred Operational Operational Comments Known to Known to Routes Airfields Helipads be Open be Closed

With a status report as follows (which should find its way into Desinventar):

31 It is assumed this is the ‘so-called’ Observation Form 32 Translated from Tetun 33 It is assumed by the author that this is the Desinventar database.

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Location Number Number Number Number Number Number of of of Evacuated Homeless Unaccounted Deceased Injured Trapped For

Clearly mobilisation is of the essence to reduce causalities and use of UAV’s might assist in early pin pointing of crisis points and avoid abortive sorties and the utter frustration of blocked access. The pros and cons of use of Drones in disaster management will be reviewed later.

11.4.3 Classification of damage that Receives Aid A further Guidance document34 is used to classify and allocate damage restitution. Section 5 of this guidance gives a Classification of damage that Receives Aid.

The level of house damage as a result of the disaster is classified in 3 categories. The differentiation of this damage level ultimately will distinguish also the form and the amount of aid to be given (by law) to each victim. They are as the followings: • Severe Damage or Total Damage

This classifies houses that are collapsed or destroyed, or houses that are not habitable because of the structural insecurity with little chance of repair. • Moderate Damage

This classifies houses that are damaged but still standing, and where the damage does not influence the strength of the structure, but is estimated as unsafe if the same disaster emerges again. In short, these houses need to be significantly repaired to become adequate to live again. • Light Damage

This classifies damaged houses that structurally have not experienced significant damage, and are still adequate to be occupied, with only improvement required other than the main structure, for example doors, windows, ceilings, etc., that is relatively superficial damage.

Clearly an early reconnaissance to classify these states of damage will expedite getting occupants to safety and payment of Government compensation/aid. Drones again are ideal to produce high definition photographic images of damaged properties with GPS georeferencing.

Section 9.1.1 of the Guidance outlines The Aid request procedure • The District Administrator (DA) as District Disaster Management Coordinator on behalf of District Disaster Management Committee (DDMC) presents the aid proposal for the construction of houses based on a disaster incident at the latest 30 days after the disaster incident to NDMD; • NDMD carries out the factual verification of the data that was presented by the District Administrator; • Based on the results of the factual verification, NDMD introduces the help proposal to Deputy- Prime Minister as National Disaster Coordinator (NDC); • NDC carries out any necessary factual verification and coordinates with inter-ministerial Commission for Disaster Management (CIGD) about the pre-set levels of compensation/aid; • NDC publishes the Qualification Document of the aid recipient names, at the same time the ‘Order Letter/The Agreement Letter’ for the channeling of the aid fund, that is transferred directly to the special account that is managed by DDMC.

Procedures for handling what is known as The Aid Executive are set out as follows:

34 The Operational Guide for the Social Restoration Program of Assistance to the Victims of Natural Disaster

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• Damages to less than 10 heads of households per location are handled by only the Suco Disaster Management Commission. • Damages to between 11 and 30 heads of households per location are handled by the Sub-District Disaster Management Commission. • Damages to more than 30 heads of households per location are handled at the DDMC level.

Each of these levels prepares reports to include: • Reports on the relevant disaster • The number of houses damaged; • Type of damages (heavy, moderate, light), see above; • The estimate of the amount of losses; • The list of the names of victims and the address of houses that suffer damages; • Photographs of damaged houses; • Efforts that were carried out by the local government; • Fund sharing available from the local government. • What type of assistance would be most effective (cash or materials)

There is no collection of data on indirect or intangible losses and physical damages on the Forms or Reports and crop losses are not compensated though the Ministry of Agriculture has some emergency powers to provide seeds.

The SIGAS35 accounting system controls payment to victims with a recovery package for total damage set at USD 368 and USD 150 for partial damage. These are agreed amounts to allow victims to manage their immediate recovery and are exclusive of any materials necessary for rebuilding, with a sum approximately equivalent to USD 1,000. These aid payments are a universal entitlement, but tend to cover first time disaster only with an encouragement for self-help to mitigate against or plan for future disasters.

An ongoing situation report will determine whether a National emergency is triggered and whether a multi hazard or multi sector situation is ongoing.

11.4.4 Next Steps There are concerns at NDOC regarding the convolution of the rapid assessment process which can take up to 2 weeks and the recovery package can take “many months”. Reasons given are remoteness, distance, inadequate communication systems, though smart phones are being increasingly used to phone in data. The irony is that even in remote areas victims will use face book and other social media to share images of the disaster but there is no formal crowd sourcing to organise this. The biggest threats were felt to be poor communication services and poor sharing of data with double entry and inadequate auditing to filter out misleading or poor data. There are 442 sucos who would benefit from a real-time validation process with a robust quality assurance system.

Synchronisation is key as this will save time. Currently the 3 constituent parts of the data gathering and dissemination process are: • The Disaster Risk Management Portal which is an information system and repository of data and reports/guidance/policy rather than an interactive database • The SIGAS accounting system to manage the flow and appropriateness of victim aid • The Desinventor database which (as the review below indicates) is poorly managed in both real time and as a record of historic events.

Drone technology was discussed at NDOC who prefer the development of a single data entry system. The support of Drone systems in disaster management was fully recognised but only as a support system. A Risk Management Application (App) was felt to be a priority for investigation.

35 Ministry of Social Solidarity: Information Systems for Delivery of Social assistance

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Relevant inputs and reports could be managed on a simple real time system available to all tracking the observation data, verification data and compensatory responses, including a Metadatabase to collate and track disparate reporting. The benefits would be:

• Rapid and simple access to data • Single data storage database • Shorter lead times from data requests to delivery • Improved feedback through standard reporting • Better ownership and accountability • Transparency • More assured data quality • Faster resource allocation • Costs savings for rapid assessment teams • Reduced operational costs for Loss and physical damage data collection and storage • On demand data both to and from District and sub District data from NDOC

Currently the cost of Disaster Risk management including an average of 10 to 15 rapid assessments per year is around USD 600,000 but rising to USD1.5 million if site mobilisation and travel and DSA costs (at USD 40 per day) are factored in.

There is therefore a business case to merge the current system with a portable computer application available to the District, sub District, NDOC and their rapid assessment teams to streamline the efficiency of disaster response. Of course, development will have its challenges with user literacy and training costs and the acceptance of technology replacing conventional approaches; the USD 40 is a clear incentive to the rapid assessment teams and some of their trips, particularly if the app is complemented by a proportionate level of drone technology (see below). However, conventional methods of data gathering will always have their place in Disaster management using long standing trained personnel, thus avoiding the GIGO (Garbage In Garbage Out) principle that creeps into computer based modelling and applications if data audits are side lined.

What is clear is that the current system is driven by compensation and access to monetary packages for rebuilding and immediate financial support to disaster victims, not on humanitarian considerations and post disaster needs assessments. The latter can only be effectively channeled through an asset register/inventory of sectoral loss and physical damage characteristics.

11.5 The Desinventar database

From 1994, the creation of a common conceptual and methodological framework was begun in Latin America by groups of researchers, academics, and institutional actors linked to the Network of Social Studies in the Prevention of Disasters in Latin America (Red de Estudios Sociales en Prevención de Desastres en América Latina - LA RED).

These groups conceptualised a system of acquisition, collection, retrieval, query and analysis of information about disasters of small, medium and greater impact, based on pre-existing official data, academic records, newspaper sources and institutional reports in nine countries in Latin America. This effort was then picked up by UNDP and UNISDR who sponsored the implementation of similar systems in the Caribbean, Asia and Africa. The developed conceptualisation, methodology and software tool is called Disaster Inventory System - DesInventar (Sistema de Inventario de Desastres).

Currently the only database for recording historic disaster data in Timor Leste is via Desinventar. An analysis of this indicates data appears incomplete and high level with no detailed attribute data. The

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Count of Event Column Labels Row Labels ACCIDENT CONFLICT DROUGHT EPIDEMIC FIRE FLOOD HAILSTORM LANDSLIDE RAINS SPATE STRONG WIND SURGE Grand Total AILEU 10 7 2 43 62 AINARO 1 1 11 8 5 1 41 68 BAUCAU 2 8 43 18 5 1 85 162 BOBONARO 1 1 26 6 1 1 2 39 77 COVALIMA 2 10 27 7 1 26 73 DILI 4 5 1 25 106 15 1 35 1 193 ERMERA 1 54 9 8 119 191 LAUTEM 3 59 27 1 3 2 78 173 LIQUICA 2 1 13 10 6 32 MANATUTO 1 16 14 9 12 52 MANUFAHI 19 26 2 92 139 OECUSSE 107 6 2 3 123 241 VIQUEQUE 3 12 23 1 3 71 113 Grand Total 10 25 1 1 405 287 1 60 5 10 770 1 1576

Some 93% of all reported occurrences relate to fire (25.7%), flood (18.2%) and strong wind (48.9%).

The table below characterises the consequences of the top three hazards, excluding conflict:

Impact of Total Rank % Rank 2 % Rank % % Disaster 1 Total Total 3 Total Conflict Deaths 113 Flood 38.9 Rains 18.6 Wind 9.7 12.4 Injured 209 Flood 54.6 Rains 23.9 Fire 6.7 3.3 Missing 26 Flood 53.9 Wind 19.2 Hail 19.2 0.0 Houses 22,160 Flood 3.6 Wind 1.7 Rain 1.2 89.5 Destroyed Houses 39,397 Flood 34.2 Wind 10.0 Rains 0.7 53.8 Damaged Victims 120,780 Flood 23.2 Drought 11.8 Fire 1.7 56.2 Households 69.450 Flood 28.8 Wind 9.3 Rain 1.6 59.2 affected Households 1,789 Flood 87.8 Wind 1.7 Hail 2.0 Relocated Houses 1.891 Flood 72.8 Surge 4.6 Fire 1.5 19.4 Evacuated US $ 4,000 Wind 50.0 Fire 50.0 damage Area (Ha) 296 Flood 80.7 Landslide 13.5 Rain 5.7 Damaged Livestock 162 Flood 77.1 Rains 15.4 Wind 7.4 lost Length of 25 Flood 100.0 Road (m)

These statistics show, conflict apart, that floods appear to be the overriding disaster to beset Timor Leste since 2001 with rains and strong winds secondary. However, it is clear that the collection of data is far from

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I complete with apparent very limited data on monetary damages, area flooded, livestock lost and lengths of road affected. For example, only a total of USD 4,000 damage was recorded in the whole 15/16 year period split equally between fire and wind!

Either the Desinventar database should be disbanded in favour of an improved repository of relevant Loss and Damage data (see later) or a clear ownership of the database established with accountability for collecting, inputting and auditing the data with timescales set for each stage of the process. Understanding the scale and trends of past disasters will inform the potential for future disasters, assist with model verification and assist the policy objectives of disaster management.

The report (as part of Deliverable 3)36 indicates the “wish list” of loss and damage data requirements (direct, indirect and intangible). This must be scrutinised with an agreement as to the priority for post disaster needs assessment with attribute data for each category of loss and damage assigned as appropriate to any future Loss and Damage Database. Some data is derived from field or remote data collection; others like macroeconomic effects derived by discussion with third parties.

11.6 Sector Data Availability

The type of sector data37 required for a comprehensive asset inventory database and the source of sector data availability has been researched and is summarised comprehensively below:

36 Overview methodology: Physical Damage and Economic Loss Estimates for Hydro-meteorological Hazards 37 Sometimes call Lifeline data in Disaster Risk Management

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Sector Data availability 1st Order In GIS Source/ 2nd Order In GIS Source/ 3rd Order In GIS Source/ 4th Order In GIS Source/ Comments format? Custodian format? Custodian format? Custodian format? Custodian Housing and Human settlement Number of dwellings Y MOF Single storey/Multi Storey Solid or temporary Y MOF Single or multi occupancy Y MOF The dataset is a product of the 2015 census and availability is still limited or upon- construction request. Spatial Data is in point vector format showing the locations of dwelling units/buildings with attributes showing numerical equivalent of responses from the census observation and interviews. Education Number of schools Y MOE Solid or temporary Education level Y MOF Number of students/ The dataset shows an updated list of educational institutions and is publicly construction classrooms available. Spatial ata is in point vector format with attributes showing the name and location of buildings, level, type, school code, cluster code and wether the facility is with electricty or not. Cultural Heritage Number of Buildings/ MTCA Classification (schools, Size Visitor Numbers Open spaces/ sports libraries, museums) arenas Health Number of Health care Y MOH Characteristics (day Y MOH Health care workers, Geographical coverage/ Y MAF The dataset shows an updated list of educational institutions and is publicly facilities centre, Hospital) equipment and medical catchment area available. Spatial ata is in point vector format with attributes showing the name and supplies location of buildings and classification. Energy- electricity Number of Electricity MPMR Km Transmission and Energy Distribution Generation Plants Distribution Systems Centres Energy-oil Number of Production MPMR Number of Oil refineries Distribution facilities facilities Drinking Water Number of Water DNQCA Km of Distribution Population served Y DNQCA Water supply rates treatment plants Networks Sewage Treatment Number of Sewage MCIE Km of Sewerage Systems Population served Treatment volumes Treatment plants /Septic Tanks Irrigation infrastructure Number and Location Y MAF Km irrigation plant Agricultural Areas served Y MAF The dataset is a product of an iventory conducted in 2015 with support from JICA and availability is still limited or upon-request. Spatial Data is in point vector format showing the name and locations of the iriigation schemes, year when the schemes were constructed and rehabilitated, service area, householp beneficiaries, type of scheme and the source of water Transport - Roads Type of road surface by km Y MPWTC Volumes of traffic Alternative routes Y There are several datasets available referring to transport. First is the the product of a map digitization from an Aerial Photograph Map produced by the Australian Peace Keeping Force in 2006 and is publicly available. The spatial data is in polyline vector format with description and length attributes for roads, tracks and trails and in polyline and point vector format for bridges. Another spatial dataset only shows the main road in polyline vector format with road-link names and descriptions and length attributes. In 2015 the MPWTC with assistance from ILO also produced the updated Rural Roads dataset in polyline vector format with attributes showing the codes, type of network, access and length but the availability of this dataset is limited and upon- request. Transport – Railways Not Applicable in Timor Leste Transport - Harbours Number of Port facilities Y MPWTC Number of Ships Tonnes of cargo and The dataset is a product of a map digitization from an Aerial Photograph Map passengers produced by the Asutralian Peace Keeping Force in 2006 and is publicly available. The spatial data is in point and polyline vector format with shape attributes (length and area). Agriculture Numbers of farms MAF Hectares of land Production types Numbers of Livestock Y Trade and Industry Type of enterprise by size MCIE Numbers Employees Productive capital stock Value Added (large, medium, small)

Color Legend Acronyms

Readily available to UNDP MSS Directorate of Social MPNR Ministry of Petroleum and Y Yes Solidarity Mineral Resources Available from 3rd party MOE Ministry of Education MPWTC Ministry of Punlic Works but incomplete National Directorate of Water Quality and Sanitation Available from 3rd Party MTAC Ministry of Tourism, Arts MAF Ministry of Agriculture and unsure about and Culture Gisheries. National completeness Directorate For Irrigation and Water Resources Unsure MOH Ministry of Health MCIE Ministry of Commerce, Industry and Environment 200

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11.7 Development of an asset inventory database

The current Observation Form data and the generally incomplete data provided in Desinventar are the only formal repositories for Loss and Damage Information with the Observation data stored on Excel spreadsheets with no synergy with the SIGAS (Ministry of Social Solidarity’s Information System for Delivery of Social Assistance).

There is a requirement for the creation of a L&D sectoral Database collecting georeferenced information of all receptors. Receptor data (houses, schools, roads etc.,) for each sector/lifeline would have both a unique L&D code and a georeference (which exist in some form now or need to be derived). Attributes would be attached to these as follows, for example:

Education Sector attributes: • Type (Primary, Secondary, Tertiary) • Construction (Material of Building, Material of Roof) • Number of Pupils • Other uses • Links to other Lifelines (Water, electricity)

Or: Transport Sector attributes: • Type (Main, Rural) • Construction (Asphalt, gravel, dirt) • Access (EW or NS access) • Condition (Good, Medium, Poor) • Links to other Lifelines

Or: House Sector attributes: • Roof Construction • Building Construction • Occupants by gender/age • Ownership (Owned, Occupied – Rent, Occupied Government) • Links to other lifelines (roads, Electricity, Water)

Or: Water Sources attributes: • Type (Pumped, Gravity) • Beneficiaries • Links to other lifelines (Electricity)

These are just examples but a database architecture is required to define all Lifeline attributes for all Receptor sectors and the associated links. For example, a disaster besetting a water source will affect households not affected by the disaster; or a landslide affecting a rural road will impact on access to Households, schools, church etc.

11.8 DRMapp

NDOC were keen to see the development of an integrated App to manage L&D data during an incident, coordinate response and record consequences and actions along with a Post Disaster Needs Assessment (PDNA). The asset register database would be the building block for this process. This would not only allow consistency of delivery of a response but allow efficiencies

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Each Sub-District or Suco would have a DRMapp super user who would enter L&D data (which would be georeferenced) and NDOC would manage the incident and monitor a trigger level of response depending on the scale of the incident or disaster:

Level 1 Contained in Suco Level 2 Multi Suco with Rapid response teams managed by Municipality (District or Sub-District); this could involve the deployment of hovering drones to assist where access is restricted Level 3 National Level response required; this could involve the deployment of fixed wing drones Level 4 International Aid required

The benefits of DRMapp would be: • Speed of response • Quality of Lifeline/Sector data and attributes in defining the physical/socio-economic characteristics of the disaster/event • Transfers NDOC’s role from largely compensatory to humanitarian • A conduit for initiation and improvement of PDNA • Back up validation by drones: o Has this water supply been restored? o Is road accessible again? o Are there any people waiting rescue? The limitations that will need addressing include: • Cross over platforms in App development (IOS/Android) can be expensive • Poor speed of Communications • Unreliability of internet • Assumption that an asset inventory/register database has been developed

The challenge in creating both a database and DRMapp will be: • Development of a common reference for each Sector/Lifeline • Willingness of data holders (Ministries) to approve and coordinate the database initiative. This can be very time consuming • Seamless coordination between sector database and DRM database to maintain the integrity of the system • Cost of geocoding of data, as geocoding is key to success • Developing a commitment to quality assurance and data integrity

11.9 A Cost model for DRMapp

At this concept stage a cost estimate model for both the development of the asset register and DRMapp are presented for further consideration.

Cost Scenarios Lower Upper Comments/Notes (USD) (USD) A Collection of asset register 7,000 21,000 (2) (1) Validation, data datasets (note 1) cleansing, conversion. If data is in correct format and already geocoded

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with one source per Ministry

(2) Delays in coordination; wasted time; disparate data sources; format issues, lack of cooperation

B Development of DRMapp38 40,000 (3) 300,000 (4) (3) Inventory only; basic functionality (4) Mature knowledge management with inventory, reporting and feedback

C Hover Drones x 6 (1 per 30,000 (5) 40,000 (5) including training pilot Municipality) Fixed wing Drone x 1 15,000 30,000 (6) (6) spare D Data Processing: (7) 4 times per year times Hover data (7) 8,000 12,000 2 weeks each pass Fixed data (8) 5,000 40,000 (9) assumed (8) In house expert; 4 times per year (5cms to 8cms pixels) (9) Outsourcing processing E GIS Software 15,000 30,000

Cash Flows and IRRs have been estimated for lower and upper scenarios assuming 10% or 5% of existing annual costs of NDOC are saved ($1.5 million). The benefits of a superior DRM system, replacing largely manual transactions, are not considered in these estimates.

The cash flows (over 20 years) project the following IRR for 4 scenarios: Scenario A Lower range cost estimates with 10% savings 70% IRR Scenario B Upper range cost estimates with 10% savings 21% IRR Scenario C Lower range cost estimates with 5% savings 58% IRR Scenario D Upper range cost estimates with 5% savings 0% IRR

See cash flow for Scenario B below

38 How much it costs to develop a mobile application? January 21, 2016, Djangostars, Lena Hagen, Marketing, PR and Social Media Manager

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Project ID: DRMapp - Scenario B Project Name: Outline Costs for DRM asset data base and DRMapp Municipality: 6 pilot Municipalities I.R.R. : 21% Project Description: Upper range estimates with 10% savings Total Cost: $ 1,439,000

Costs Benefits Cash Flow Total Cost

Capital Cost Annual Costs Stream Project Life (yrs) Project Life 1 451,000 451,000 - - 451,000 2 52,000 52,000 150,000 150,000 98,000 3 13,000 52,000 150,000 150,000 98,000 4 13,000 52,000 150,000 150,000 98,000 5 13,000 52,000 150,000 150,000 98,000 6 13,000 52,000 150,000 150,000 98,000 7 13,000 52,000 150,000 150,000 98,000 8 13,000 52,000 150,000 150,000 98,000 9 13,000 52,000 150,000 150,000 98,000 10 13,000 52,000 150,000 150,000 98,000 11 13,000 52,000 150,000 150,000 98,000 12 13,000 52,000 150,000 150,000 98,000 13 13,000 52,000 150,000 150,000 98,000 14 13,000 52,000 150,000 150,000 98,000 15 13,000 52,000 150,000 150,000 98,000 16 13,000 52,000 150,000 150,000 98,000 17 13,000 52,000 150,000 150,000 98,000 18 13,000 52,000 150,000 150,000 98,000 19 13,000 52,000 150,000 150,000 98,000 20 13,000 52,000 150,000 150,000 98,000 20% 286,000 1,439,000 21% Providing, following detailed costing of the DRM asset inventory database and the DRMapp, savings can be greater than 10% and capital costs of development less than $451,000 (annual costs less than $52,000) the development is viable.

11.10 Review of Drone technology39

The use of drones or unmanned aerial vehicles (UAV), can significantly enhance risk and damage assessments, and revolutionize disaster preparation, response and management capacities in the future. The deployment of drones will be aimed at supporting the government’s response planning activities and strengthen the preparation for and response to disasters including the assessment of physical damages for post disaster needs assessment. It will also help in making better-informed decisions in protecting their livelihoods.

39 Main reference: Guy Carpenter, et.al. Drones for Disaster Response and Relief Operations (April 2015),

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I Data generated from the drone flights will also be useful in the long-term monitoring of hazards (fast and flow on-set hazards) which will feed into the continued updating of hazard and risk information used in climate risk management, design of climate resilient infrastructure, and environmental monitoring. Drones equipped with photogrammetric and navigation equipment will be used to allow rapid and reliable assessments of important hazard parameters.

Advantages of Using Drone for Loss and Damage Accounting

The main advantages of the introduction of drone technology to DRM capabilities of MSS include:

• Reduction in disaster response personnel exposure to unnecessary danger. • Enhance the effectiveness of data gathered from responders. • Drones provide unique viewing angles at low altitudes not possible from manned • aircraft. • Drone technology is highly deployable. • Drone technology is cost-efficient.

Aerial Drone Types

Payloads

Electro-Optical/Infrared (EO/IR) Sensors

EO/IR sensors are the workhorses of drone-based sensing technology. These sensors provide the most commonly used data collected from drone platforms.

• Electro-Optical – Mainly used for day operations, EO sensors are relatively cheap and widely available. They include video cameras and high-definition photography equipment. • Infrared - Excellent for night operations. Infrared sensors detect the heat signatures of various objects. This is particularly useful in disaster management for identifying hot spots from fires or for locating survivors at night and in large, open environments.

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• Dual EO/IR – These sensors are often combined into a dual package that can be used for both day and night operations. • EO900 – The EO900 enables EO intelligence, surveillance, and reconnaissance (ISR) support from a great distance, so its drone platform will not interfere with manned aircraft moving in and out of the disaster area.

Mapping sensors

Mapping sensors scan the ground and create 2D or 3D maps of the surrounding area. Much drone-based mapping is now geo-referenced, allowing it to be easily transposed onto existing geographical information systems (GIS).

• Hyper/Multi Spectral imagers – Spectral imagers could be used to identify chemical leaks/spillage or other dangerous substances. • LiDAR – Creates highly detailed topographical maps and 3D maps of urban areas. These can be used to create highly precise flood maps. • Synthetic Aperture Radar (SAR) – Provides detailed imagery of the ground day or night through cloud, fog, and smoke. SAR can detect metal and certain other types of materials very well. SAR can also detect changes that can help mitigate disasters in their early stages. For example, SAR can be used to monitor a swelling river before it floods, track receding floodwaters, or monitor a slow, but steadily advancing landslide.

Communications Relay

Given their ability to quickly reach high altitudes, and, in the case of rotary-wing platforms, hover in place for a prolonged period, drones provide ideal stopgap solutions when communications infrastructure is disrupted.

• UHF/VHF – Drones can broadcast basic UHF/VHF radio communications across a long distance. • FM repeater – When local infrastructure is down, emergency radio stations could be broadcast through a drone with this capability. • Wave Relay (IP network relay) -- WaveRelay provides a networking node in the sky for emergency management personnel, allowing for the transmission of data and voice communications. One of the biggest challenges in large-scale relief efforts is harmonizing interagency communications technology. IP networks could be the bridge between these organizations. • Cell phone tower – Drones can act as a cellular tower in the sky to quickly re-establish cellular signal over an area that has experienced cellular infrastructure damage. • Wireless ground sensors -- A drone could be a mobile data link to capture information from ground sensors and transmit it back to the command center, saving emergency response teams time and allowing them to avoid unnecessary danger by not having to visit each ground sensor individually. Ground sensors can be used to monitor water flow, water depth, motion detection for security, and the movement of earth in a landslide situation, amongst other applications.

Sniffers

Sniffers detect the presence of certain substances or radiation in the air. Mounted on drones, these are extremely useful in CBRNE situations.

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• Methane Sniffer – These sniffers assess air quality to identify high concentrations of methane. This can alert personnel on the ground to a potentially explosive environment and can also help detect leaks in gas transportation infrastructure. • Radiation Sensor – These sensors can detect the presence of high levels of radiation. They are important tools for safely monitoring high-radiation environments as well as alerting ground personnel to potentially dangerous radiation plumes.

Cargo Space / Personnel Capsule

• Cargo holds – Cargo space on larger drones can be used for the transport of large objects, including people. They can also use ropes and hooks to carry cargo capsules beneath the drone. Smaller drones can also use payload space to carry small, but important, items like medicine to people in need. • Personnel Capsules – Specially designed chambers on larger drones, such as the Lockheed Martin K-MAX (essentially a retrofitted helicopter), can transport personnel as effectively and comfortably as space in manned aircraft. Personnel capsules can also be suspended below heavy-lift drones.

Firefighting Tools

• High-pressure hoses – Heavy-lift drones can be fitted with high-pressure hoses to spray flame retardant on fires. • Bambi buckets – Heavy-lift drones can be equipped with Bambi buckets suspended beneath the aircraft. This will allow them to quickly gather water from a nearby source and dump it on approaching flames during wildfires.

Other

• Laser pointer – Fitted with a laser pointer, a drone can help direct emergency responders to the correct house or person for rescue/help.

Applicable drone platforms and payloads for reconnaissance and mapping

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11.11 Climate Proofing Infrastructure in the 6 target municipalities – feasibility and methodology

The identification and prioritization of climate proofing needs were undertaken as part of project design which included a risk assessment of the infrastructure units using the currently available national hazard maps (against which the existing and approved PDIM and PNDS infrastructure had also been assessed).

The risk assessment was undertaken using a GIS-based socio-economic risk model that was developed for the preparation of this proposal. The assessment incorporates the hazard maps, all receptor data of existing and planned infrastructure (including roads, water supply systems, irrigation systems, flood defences, agricultural land, dwellings, land use categories, socio-economic indices) based on the latest 2015 census survey and calculates the damages and losses to infrastructure, agriculture, property, and livelihoods, under baseline and climate change scenarios.

The results of the risk assessment identified the extreme hazard categories of each hazard incident (moderate and high severity flood risk for prioritization and the 1 in 100-year flood depth for design of the infrastructure; high and very high severity drought; moderate and high severity erosion; and high and very high intensity landslide risk) for each infrastructure unit, which was then used to design and identify the designs and methods for climate proofing. Section 2.9 of this FS provides the detailed results of the risk assessment, while this section, provides details of the prioritization and design of climate proofing for the rural infrastructure projects.

Following the risk-based analysis of the extent of hydro metrological hazards (Floods, landslides, erosion and drought) in all Municipalities and watersheds in Timor Leste40 , 6 Municipalities were selected and structural measures were identified in each to create resilience to four components of public infrastructure: Rural Roads, Water Supply, Irrigation Systems and Flood Protection. In addition, areas of high risk land erosion were identified with a view to introduction of agro-forestry options to minimise the effects of erosion on agricultural land.

40 Analysis of Climate Change Risks, Impacts and Vulnerability for baseline and projected Climate Change Scenarios: Dr John Chatterton Project Deliverable 1 December 2016

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I Some 144 projects were identified initially by UNDP SSRI (Small Scale Rural Infrastructure) team in the 6 Municipalities41. The SSRI team in association with Municipality Development Officers dismissed 12 of the projects for several reasons:

• Already part of another rural road project (La-RR-10, La-RR-06 and B-RR-01) • Infrastructure still fit for purpose (La-RR-07 and La-RR-08) • No obvious beneficiaries from desk study (A-RR-08, B-RR-08, V-FP-01, L-FP-04, E-FP- 02, E-FP-03, La-FP-04, B-FP-01)

Project Type Viqueque (V) Aileu Baucau (B) Ermera (E) Lautem Liquica (L) (A) (La) Rural Roads 5 14 6 9 6 9 (RR) Irrigation 3 3 7 4 6 2 Systems (IS) Water Supply 6 3 9 6 11 3 (WS) Flood 3 5 2 1 4 5 Protection (FP) Total 17 25 24 20 27 19

The outline design of climate proofing measures for each of the remaining infrastructure units was undertaken using the following approaches for each type of infrastructure.

Roads

Site reconnaissance and surveys were conducted to determine the number and location of hydrological and drainage structures, bridges, embankments and protective structures required for each rural road infrastructure unit. Sizing of drainage structures was based on historical data of drainage structures and previous projects implemented. Based on the site-reconnaissance and assessment of the vulnerability of the road right-of-way, sections and locations vulnerable to landslides, erosion and flooding are addressed accordingly. Combinations of both grey and green engineering measures were considered to be adopted in safeguarding the infrastructure against climate induced hazards including:

• Masonry retaining walls depending on the condition and vulnerability of particular sections of the road

• This was combined with soil-bioengineering interventions to address critical sections of the road that are at risk from climate induced hazards (mainly landslides, erosion and flooding).

Materials considered, based on what was previously used and available are those that are locally available and have been tested, having the required properties for both flexible and rigid pavements, and the base and sub-base layers. Most of the rural road projects to be implemented will follow the same surfacing approach of using ‘plum concrete’ as per the draft rural road standards. For the preliminary designs data were available from past projects and hence the pricing obtained to determine the project estimate.

The site reconnaissance and survey also determined the geometric properties of the road (alignment, width, curves etc) which will be finalized during detailed final design.

41 See Annex 7 for notes on project identification, consultation and selection process

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I Traffic analysis – volume and load analysis are usually an important parameter for road designs to determine the structural properties of the road. However, in the case of rural roads in Timor-Leste there is usually a common trend in terms of the size of vehicles, volume of traffic and the loads. Hence, most rural roads follow a similar design. During the detailed design stage this will be reviewed.

Surveys and geotechnical analysis were also conducted to collect data on the characteristic and structural properties of road cross section, information collected to determine the depth of excavation, volume of fill materials and backfill, etc. required based on the existing condition.

Water Supply Systems and Irrigation Systems

The most common system in rural Timor-Leste for both water supply systems and irrigation schemes are gravity fed (from springs, surface water collected from catchment – water capturing and rivers). Climate proofing design of small-scale irrigation and water supply units embeds consideration of drought discharge volumes and recharge rates to ensure continuous functionality of the system and water availability, as well as water source protection measures to reduce the risks of drying out water sources and catchment rehabilitation to stabilize water yielding capacities of the catchments.

Both elements of water availability and drought period are common barriers to adequate water supply for domestic purposes and agricultural activities. Therefore, in periods of drought or low precipitation, particularly when the discharge volume at water source is low, the absence of infrastructure makes it difficult- if not impossible- for the transmission, storage and distribution of water. This is expected to be exacerbated as a result of the projected climate impact, leaving the communities ill-prepared for the adverse consequences, unless adequate climate resilient solutions for rural infrastructure are put in place.

The project will formalize existing systems by replacing/surfacing the informal irrigation and water supply transmission channels, which will reduce transmission losses, improve the serviceability to farms and increase the efficiency of the channels during low flows and dry periods. The following specific outline design activities were undertaken for water supply and irrigation systems.

Water Supply

Water supply project were identified and prioritized by the respective sucos (villages) in their Suco Development Plans and selected for implementation in the respective municipalities. Site visits and interviews were conducted to collect information for the outline designs.

For each of the Water Supply Systems beneficiaries data/information to determine key features and functional and structural capacity of the system were collected, e.g. demographic data, population/size of the community, density/locations of households in the community (for siting of the public taps), and key economic activities.

Site visit and interviews were conducted to determine the current situation in the community/village with respect to water collection and consumption pattern. For the water supply systems, the reservoir sizing has been designed based on the population (beneficiaries) and using the national average of 35 litres per person per day (as per the manual for water supply systems) with provision for population growth for at least 20 years or the design life of the water supply systems, and 30% increase factored into the design to account for capacity requirement due to climate change impacts which will increase the water needs/consumption.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I Any existing water supply system was inspected and if any type of system in place, and its functionality assessed. This included examining where there are traditional systems comprising of bamboo being used for piping water from water source and collecting information via villager interviews to determine the main source collecting water, types of water sources, distance of source from community, volume of water from source and the system capacity to supply water to the community during dry spells/periods. Formalization of existing water supply systems by replacement and protection of informal transmission lines will reduce transmission losses, and increase efficiency and reliability of supply to households, particularly during low flows and dry periods. Protection will also reduce damage of transmission lines from landslides and erosion.

An important aspect of the preliminary assessment for the design was identification of water source(s) and determination of the potential discharge capacity of the source(s) to supply water to the community. Site reconnaissance, initial surveys (including elevations) and measurements were taken to determine key design features of the systems including location of system components such as the reservoirs, public taps, and water distribution and transmission lines. Water storage reservoirs will improve supply reliability during dry season and reservoirs will be managed by the water management group (GMF) that will agree on the operating rules during the dry season based on water availability and reservoir recharge rates. Based on the field visits, surveys and interviews and data collected, outline designs and cost estimates were prepared based on data gathered/collected.

Irrigation Schemes

Proposed irrigation projects that were identified and prioritized by the respective sucos (villages) in their Suco Development Plans were reviewed and selected for implementation in the respective municipalities. Technical teams conducted site visits and held interviews with beneficiaries and stakeholders to collect information for the preliminary designs.

Preliminary data were collected on site to determine the total hectares of lands that can be potentially be irrigated, the types of agricultural activities/crops that farmers were engaged in, cropping patterns, etc.

Inspection was done to determine the presence of any existing irrigation channel and/or system, and its functionality. This included examining where there are traditional systems comprising of bamboo used for channelling water or earthen/unlined channels and collecting information and assessing the situation by interviewing villagers e.g what is the main source available, the type and number of source(s), volume of water from source and the system capacity to supply water to the community during dry spells/periods. Formalization of existing systems by surfacing the irrigation transmission earthen channels will reduce transmission losses, improve the serviceability to farms and increase the inefficiency of the channels during low flows and dry periods. The formalization and implementation of irrigation infrastructure has two key positive impacts (1) increased capacity of the community to produce crops more than once per year and (2) increase in cultivable lands due to availability and improved reliability of water.

One aspect during the preliminary assessment for the design was identification of water source(s) and determination of the water debit of the source(s). Interviews were done with members of the community (including the chief of villages/chief of sub-villages) to get information about the water source. Site reconnaissance, initial surveys (including elevations) and measurements were taken to determine key design features of the schemes including the elevation and location of reservoirs, alignment of irrigation channels, location of control structures. Outline designs and cost estimates were prepared base on the data collected.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I River embankments/flood protection

River embankment and flood protection infrastructure were mainly to provide safeguards to new and existing infrastructure e.g for some of the projects identified gabion embankments/wall were built along the banks of the river to prevent erosion and/or destruction of hydraulic structures. This also include protection of existing road infrastructure, community houses, schools and other buildings.

Information for the preliminary design for the embankments/flood protection infrastructure were collected from site visits and surveys in the field along with interviews conducted with community and relevant stakeholders. This exercise also provided the technical team with useful historical information relating to river flows and flooding in the community which was verified using existing indicative flood hazard maps.

Detailed design of flood defences will be based on more comprehensive and detailed hydrological assessment based on analysis of the catchment/watershed area and river discharge and flow rates, topographical surveys etc. to be undertaken as well as detailed hydraulic modelling of the floodplain within which the flood defences will be located.

Site reconnaissance and measurements were undertaken to determine structural elements of the embankment, location and geometric features (height, width etc.), associated structures and identifying intervention(s) that can combine bioengineering with the hard engineering structure on each of the site. Based on site visits and preliminary data collected the outline designs and cost estimates were prepared.

11.11.1 Methodology for identifying and prioritising infrastructure projects

The 130 projects were subject to Cost Benefit analysis.

Capital, operational (where appropriate) and maintenance costs were provided for each project, and the Internal Rate of Return calculated based on monetised benefits relating to the avoidance of economic losses to communities (Sucos) assuming no resilience measures were put in place (The Do Nothing option). Clearly these resilience measures can never prevent all losses associated with worsening hydro-meteorological hazards but, at this broad analysis of feasibility, it is assumed that residual losses after completion of the projects are not included.

The identification of high and very high risk for all 4 hydro-meteorological hazards did not include an assessment of their probability of occurrence, so under Do Nothing it is impossible to predict both the timing and frequency of a damaging event. The timing and frequency are very important when deriving the benefits of resilient mitigation measures: an assumption that a landslide event, for example, in a very high risk location will occur every 10 years on average will give a wholly different Internal Rate of Return for the project than one that is expected to occur every 2 years.

The Desinventar42 database used to populate Timor Leste’s historical hazards is incomplete and of insufficient length of record to make assumptions as to the historical frequency of hazard events in specific locations. For example, in Ermera only 8 landslide events were recorded between February 2009 and January 2015, and all in different locations.

42 Reviewed in detail in “Loss and Damages current practice and feasibility of proposed technologies”

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Serial Event District Sub-District Suco Date Location 1548 LANDSLIDE ERMERA ERMERA RIHEU 08/12/2014 Aldeia Gomhei 1551 LANDSLIDE ERMERA ERMERA POETETE 31/12/2014 Aldeia Ermera villa 1014 LANDSLIDE ERMERA ATSABE LASAUN 12/12/2013 Aldeia Tai-ubu 219 LANDSLIDE ERMERA ATSABE OBULO 05/02/2009 1560 LANDSLIDE ERMERA ERMERA POETETE 26/12/2015 Aldeia Tidibessi 1025 LANDSLIDE ERMERA ATSABE LAUBONO 01/02/2014 Aldeia Purugua 1573 LANDSLIDE ERMERA HATOLIA LISSAPAT 21/11/2014 Aldeia Hatupae 1527 LANDSLIDE ERMERA 05/01/2015 However, the objective of creating structural resilience to infrastructure is not just to ameliorate the effects of major hazards in High and Very High risk areas but to resist the degradation of infrastructure over time as increasingly adverse weather events associated with climate change make their use ineffective. Thus, a road in a low or medium risk area may degrade (under Do Nothing) over time reducing access or inhibiting access altogether.

This being the case, to enable comparison of the relative priority of the cost benefit of all rural road schemes, and all flood protection schemes etc. the Do Nothing losses were assumed for each scheme with the same frequency and timing of occurrence. Thus, the IRRs are relative and not absolute giving a ranking of scheme viability.

For simplicity, the time horizon for each project is 20 years43, and it is quite possible that in reality no economic loss would be experienced especially, say landslides, at the high-risk locations within this period, or at least for some schemes. For others, economic loss may be more frequent. What is certain is that the propensity of damaging hydro-meteorological hazards is expected to increase into the future and the theoretical predictions of losses (almost certainly more frequent than in reality) will enable priority ranked projects both Nationally for all projects and by project type. The aim of this exercise is to inform of likely priority areas for investment which will require further detailed modelling and investigation once GCF funding is secured.

In environmental project appraisal, benefits may be regarded as Monetary benefits expressed in USD, or non-monetised benefits expressed as beneficiaries of the projects (Households protected, population benefiting, service areas benefitting – for irrigation systems).

Total number of beneficiaries and reduced annual economic losses under baseline and CC scenarios were calculated during the feasibility study using existing indicative hazard mapping, socio-economic datasets available for all of Timor Leste (official statistics of the 2017 Census), and a GIS-based socio-economic risk model that was developed for the feasibility study. To calculate the number of beneficiaries for rural roads, GIS techniques were used to derive “catchment” areas of beneficiaries. The risk map layers were used to first identify whether the road falls within the High Risk Category and then using a buffer distance of 5K the household beneficiaries were determined based on the 2015 census. For flood projects, the location of the proposed projects were identified using Google Earth imagery to digitise polygons of beneficiary areas and combined with the Flood Risk Map, the number of location of households counted if they fall within the High Risk Category. Again, using the 2015 census the number of beneficiaries was determined. If the project is meant to benefit the whole community, the total household and population of the said community was used. For irrigation schemes, beneficiaries were calculated based on households and population of the Irrigation Service Areas along the length of the proposed irrigation scheme. For water supply projects, beneficiaries were calculated based on the Service Area (Suco) Households Population for each scheme. It should be noted that the population groups benefited by individual infrastructure works do not overlap, as each suco (village) only receives 1

43 The SSRI engineers have confirmed that the Water Supply tanks (see photo below) have a manufacturer’s guarantee of 20 years and although rigid pavement would have a 40 year life, lack of reinforcement and general wear and tear on rural roads in an increasingly hostile climatic environment a 20 year life before refurbishing is regarded as more realistic.

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Non monetised benefits are as significant to justifying project priority as monetised benefits. In theory, all socio-benefits can be monetised but not without considerable survey and field investigations.

For example, a landslide will cut off a community from its market place or hinterland meaning pregnant women may not be able visit their community clinics or perishable produce cannot get to market. Health will suffer as will income. As a “catch all” to represent these social and economic losses data from the Timor Leste Household Income and Expenditure Survey, 2011 was used to reflect social and economic opportunity foregone as a result of a hazard shock. The two attributes of Crop Income per month and Total Income per month were used as surrogate socio-economic values.

It is not suggested that all this income would be lost as a result of a hazard shock besetting a community but using the full value will, in some way, assist with quantifying the scale of socio- economic loss. A landslide cutting off a community will not deny the population of all its income but using this value will suggest a maximum level of socio-economic disruption.

The following are high level summaries of Household income in Timor Leste:

Crop Income per Urban USD 37 Household per month Rural USD 85 Total Income per Urban USD 634 Household per month Rural USD 291

Total Income is made up of:

• Wage Income • Crop income • Livestock, Fishing and Forestry income • Business Income • Other income including money transfers

The following economic indicators (monetised) and beneficiaries (non-monetised) are used to represent the benefits of infrastructure projects within the highest risk zones identified:

Hazard Economic Beneficiary Infrastructure Indicators Indicators Interventions Landslide Total Income Households Rural Road Population resilience Flood Property Damage Households Flood Mitigation Crop Income Population (Topographic Flooded Land Area Wet Index) (TWI) Erosion Crop Income Households Agri-Forestry Population Crop Area

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Drought Total Income Service Area Water Supply (Suco) Households Population Drought Crop Income Agricultural Area Irrigation Households Systems Population

11.11.2 Cost Benefit Analysis and project Ranking Cash Flow spreadsheets have been developed to indicate the broad scale Internal Rate of Return (IRR) for each project comparing total costs (capital and periodic and annual maintenance) with the benefits as defined by the economic indicators. IRR’s are calculated for:

• All costs • Capital costs only • Economic indicators representing elimination of potential losses associated with improved climate resilient infrastructure

An IRR value #NUM! indicates a highly negative rate of return on the investments.

The projects are ranked for all projects in all Municipalities and for each individual project type to indicate where project investments are worth value for money. However, where costs are particularly high in relation to the monetary benefits the final decision of scheme priority relates to the scale of the beneficiary indicators. Projects are coded Green, Yellow and Red with Green in the top third of the ranking process, yellow in the middle third and red in the bottom third.

A project whose IRR is in the bottom or middle third (and even negative) could be elevated if its beneficiary rankings are in either the middle or higher third.

Beneficiaries are also listed for each project: Households, Population and Water Service Area for Irrigation projects. The ranking of all projects is summarised in Table 0-1 and Table 0-2. Table 0-1 assumes no maintenance for rural roads and disruption to roads when an event occurs is for 3 months. Table 0-2 assumes maintenance is included and disruption is one month.

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Table 0-1: Total project Ranking (assuming no maintenance for rural roads)

Irrigation Annual Breakdown of Capital Cost (US$) System Household Capital Cost Total Captal Project Code Internal Rate of Return Service Area Beneficiaries (US$) Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Cost (US$) (Ha) 2 11 19 22 35 36 37 38 39 40 B-RR-05 157.00% 110 349,980 24,499 59,497 120,743 120,743 24,499 349,980 La-RR-02 154.00% 227 249,972 17,498 42,495 86,240 86,240 17,498 249,972 B-RR-02 139.00% 441 434,977 30,448 73,946 150,067 150,067 30,448 434,977 E-RR-06 117.00% 344 300,000 21,000 51,000 103,500 103,500 21,000 300,000 La-RR-06 93.00% 368 200,000 14,000 34,000 69,000 69,000 14,000 200,000 E-RR-02 78.00% 408 599,900 41,993 101,983 206,966 206,966 41,993 599,900 E-RR-07 73.00% 200 300,000 21,000 51,000 103,500 103,500 21,000 300,000 B-IS-01 70.49% 232.00 780 25,000 1,750 4,250 8,625 8,625 1,750 25,000 B-RR-06 68.00% 25 149,997 10,500 25,499 51,749 51,749 10,500 149,997 La-RR-03 62.00% 41 99,991 6,999 16,999 34,497 34,497 6,999 99,991 B-RR-07 59.00% 114 374,995 26,250 63,749 129,373 129,373 26,250 374,995 V-RR-04 59.00% 426 300,471 21,033 51,080 103,663 103,663 21,033 300,471 La-RR-05 53.00% 62 199,954 13,997 33,992 68,984 68,984 13,997 199,954 A-RR-05 46.00% 39 189,390 13,257 32,196 65,340 65,340 13,257 189,390 La-RR-04 45.00% 63 49,966 3,498 8,494 17,238 17,238 3,498 49,966 L-RR-08 44.00% 88 85,002 5,950 14,450 29,326 29,326 5,950 85,002 E-RR-08 38.00% 71 650,000 45,500 110,500 224,250 224,250 45,500 650,000 B-RR-03 37.00% 108 199,993 14,000 33,999 68,998 68,998 14,000 199,993 B-IS-03 36.47% 27.00 766 65,000 4,550 11,050 22,425 22,425 4,550 65,000 B-WS-04 33.09% 243 75,000 5,250 12,750 25,875 25,875 5,250 75,000 L-RR-09 30.00% 210 300,000 21,000 51,000 103,500 103,500 21,000 300,000 La-FP-05 28.29% 95,000 6,650 16,150 32,775 32,775 6,650 95,000 E-RR-01 26.00% 399 650,000 45,500 110,500 224,250 224,250 45,500 650,000 B-WS-03 25.95% 196 75,000 5,250 12,750 25,875 25,875 5,250 75,000 V-IS-03 23.32% 233.00 573 75,000 5,250 12,750 25,875 25,875 5,250 75,000 V-IS-02 20.68% 131.00 746 120,000 8,400 20,400 41,400 41,400 8,400 120,000 V-IS-01 20.66% 103.00 793 120,000 8,400 20,400 41,400 41,400 8,400 120,000 A-WS-01 20.36% 201 100,000 7,000 17,000 34,500 34,500 7,000 100,000 V-WS-03 20.33% 105 40,000 2,800 6,800 13,800 13,800 2,800 40,000 V-WS-06 20.04% 277 150,000 10,500 25,500 51,750 51,750 10,500 150,000 B-IS-07 19.67% 5.30 418 65,000 4,550 11,050 22,425 22,425 4,550 65,000 A-RR-12 17.00% 26 150,000 10,500 25,500 51,750 51,750 10,500 150,000 A-RR-15 17.00% 76 249,900 17,493 42,483 86,216 86,216 17,493 249,900 La-WS-04 15.58% 115 60,000 4,200 10,200 20,700 20,700 4,200 60,000 La-WS-03 15.21% 120 65,000 4,550 11,050 22,425 22,425 4,550 65,000 V-WS-05 14.73% 218 150,000 10,500 25,500 51,750 51,750 10,500 150,000 B-IS-04 14.57% 143.00 362 90,000 6,300 15,300 31,050 31,050 6,300 90,000 A-WS-02 14.55% 128 75,000 5,250 12,750 25,875 25,875 5,250 75,000 E-WS-01 14.04% 137 85,000 5,950 14,450 29,325 29,325 5,950 85,000 E-RR-09 14.00% 133 599,900 41,993 101,983 206,966 206,966 41,993 599,900 A-FP-02 13.96% 58 50,000 3,500 8,500 17,250 17,250 3,500 50,000 La-WS-08 13.06% 78 35,000 2,450 5,950 12,075 12,075 2,450 35,000 A-RR-07 13.00% 65 307,980 21,559 52,357 106,253 106,253 21,559 307,980 L-RR-06 13.00% 50 150,000 10,500 25,500 51,750 51,750 10,500 150,000 B-IS-06 12.40% 13.00 247 50,000 3,500 8,500 17,250 17,250 3,500 50,000 E-WS-06 12.22% 127 85,000 5,950 14,450 29,325 29,325 5,950 85,000 A-RR-10 12.00% 147 189,999 13,300 32,300 65,550 65,550 13,300 189,999 A-RR-13 12.00% 25 174,988 12,249 29,748 60,371 60,371 12,249 174,988 La-WS-10 11.97% 115 75,000 5,250 12,750 25,875 25,875 5,250 75,000 V-RR-03 11.00% 98 499,989 34,999 84,998 172,496 172,496 34,999 499,989 La-WS-07 10.94% 101 65,000 4,550 11,050 22,425 22,425 4,550 65,000 E-WS-05 10.29% 219 200,000 14,000 34,000 69,000 69,000 14,000 200,000 L-RR-01 10.00% 43 150,000 10,500 25,500 51,750 51,750 10,500 150,000 V-RR-01 10.00% 125 449,979 31,499 76,496 155,243 155,243 31,499 449,979 E-WS-04 9.99% 123 95,000 6,650 16,150 32,775 32,775 6,650 95,000 L-RR-04 9.00% 165 650,025 45,502 110,504 224,259 224,259 45,502 650,025 La-WS-06 8.82% 88 60,000 4,200 10,200 20,700 20,700 4,200 60,000 V-RR-02 8.00% 110 449,989 31,499 76,498 155,246 155,246 31,499 449,989 V-RR-05 7.00% 112 499,975 34,998 84,996 172,491 172,491 34,998 499,975 A-IS-03 6.26% 20.00 365 120,000 8,400 20,400 41,400 41,400 8,400 120,000 La-WS-11 5.93% 65 40,000 2,800 6,800 13,800 13,800 2,800 40,000 E-IS-04 5.63% 221.00 402 185,000 12,950 31,450 63,825 63,825 12,950 185,000 B-WS-02 5.30% 132 150,000 10,500 25,500 51,750 51,750 10,500 150,000 L-WS-03 5.13% 97 95,000 6,650 16,150 32,775 32,775 6,650 95,000 A-IS-01 4.50% 94.00 238 85,000 5,950 14,450 29,325 29,325 5,950 85,000 L-WS-02 4.30% 125 150,000 10,500 25,500 51,750 51,750 10,500 150,000 La-IS-06 4.16% 81.00 235 75,000 5,250 12,750 25,875 25,875 5,250 75,000 A-RR-04 4.00% 55 209,720 14,680 35,652 72,353 72,353 14,680 209,720 B-IS-02 2.03% 12.00 112 30,000 2,100 5,100 10,350 10,350 2,100 30,000 E-RR-05 2.00% 147 350,000 24,500 59,500 120,750 120,750 24,500 350,000 La-WS-02 1.77% 78 85,000 5,950 14,450 29,325 29,325 5,950 85,000 La-WS-01 1.47% 105 150,000 10,500 25,500 51,750 51,750 10,500 150,000 B-WS-09 1.26% 76 85,000 5,950 14,450 29,325 29,325 5,950 85,000 L-RR-03 1.00% 85 650,000 45,500 110,500 224,250 224,250 45,500 650,000 V-FP-01 0.42% 9 157,500 11,025 26,775 54,338 54,338 11,025 157,500 E-IS-01 0.24% 107.00 230 175,000 12,250 29,750 60,375 60,375 12,250 175,000 La-WS-05 -0.12% 62 60,000 4,200 10,200 20,700 20,700 4,200 60,000 B-WS-06 -0.85% 57 50,000 3,500 8,500 17,250 17,250 3,500 50,000 L-WS-01 -0.89% 72 95,000 6,650 16,150 32,775 32,775 6,650 95,000 L-IS-02 -1.19% 470.00 264 150,000 10,500 25,500 51,750 51,750 10,500 150,000 E-WS-03 -1.38% 97 175,000 12,250 29,750 60,375 60,375 12,250 175,000 E-WS-02 -2.36% 80 135,000 9,450 22,950 46,575 46,575 9,450 135,000 B-WS-01 -2.41% 59 65,000 4,550 11,050 22,425 22,425 4,550 65,000 L-RR-05 -3.00% 60 650,000 45,500 110,500 224,250 224,250 45,500 650,000 E-RR-03 -4.00% 56 350,000 24,500 59,500 120,750 120,750 24,500 350,000 B-WS-05 -4.37% 75 150,000 10,500 25,500 51,750 51,750 10,500 150,000 A-IS-02 -5.44% 51.00 177 120,000 8,400 20,400 41,400 41,400 8,400 120,000 A-RR-01 -6.00% 45 85,000 5,950 14,450 29,325 29,325 5,950 85,000 B-WS-07 -6.18% 73 175,000 12,250 29,750 60,375 60,375 12,250 175,000 V-WS-04 -6.68% 65 142,625 9,984 24,246 49,206 49,206 9,984 142,625 A-RR-06 -7.00% 26 130,500 9,135 22,185 45,023 45,023 9,135 130,500 A-RR-11 -7.00% 25 194,990 13,649 33,148 67,272 67,272 13,649 194,990 La-IS-05 -7.26% 16.00 201 135,000 9,450 22,950 46,575 46,575 9,450 135,000 E-FP-01 -7.84% 3 72,900 5,103 12,393 25,151 25,151 5,103 72,900 La-IS-04 -8.00% 240 196,687 13,768 33,437 67,857 67,857 13,768 196,687 A-RR-02 -8.00% 36 85,000 5,950 14,450 29,325 29,325 5,950 85,000 E-RR-04 -8.00% 20 249,000 17,430 42,330 85,905 85,905 17,430 249,000 A-RR-03 -9.00% 5 150,000 10,500 25,500 51,750 51,750 10,500 150,000 L-RR-07 -9.00% 21 450,000 31,500 76,500 155,250 155,250 31,500 450,000 V-WS-02 -9.20% 59 150,000 10,500 25,500 51,750 51,750 10,500 150,000 L-IS-01 -10.24% 1,051.00 453 450,000 31,500 76,500 155,250 155,250 31,500 450,000 L-RR-02 -11.00% 24 699,960 48,997 118,993 241,486 241,486 48,997 699,960 L-FP-01 -12.14% 14 175,000 12,250 29,750 60,375 60,375 12,250 175,000 A-RR-09 -14.00% 6 180,005 12,600 30,601 62,102 62,102 12,600 180,005 L-FP-06 -14.95% 1 150,000 10,500 25,500 51,750 51,750 10,500 150,000 La-IS-02 -17.99% 22.00 109 95,000 6,650 16,150 32,775 32,775 6,650 95,000 A-RR-14 -19.00% 5 150,000 10,500 25,500 51,750 51,750 10,500 150,000 A-FP-01 -20.00% 1,654 85,000 5,950 14,450 29,325 29,325 5,950 85,000 A-FP-03 -20.00% 8 320,000 22,400 54,400 110,400 110,400 22,400 320,000 A-FP-04 -20.00% 1 200,000 14,000 34,000 69,000 69,000 14,000 200,000 A-FP-05 -20.00% 1 85,000 5,950 14,450 29,325 29,325 5,950 85,000 A-WS-03 -20.00% 32 90,000 6,300 15,300 31,050 31,050 6,300 90,000 B-FP-02 -20.00% 300,000 21,000 51,000 103,500 103,500 21,000 300,000 B-FP-03 -20.00% 225,000 15,750 38,250 77,625 77,625 15,750 225,000 B-IS-05 -20.00% 180.00 9 120,000 8,400 20,400 41,400 41,400 8,400 120,000 B-WS-08 -20.00% 21 50,000 3,500 8,500 17,250 17,250 3,500 50,000 E-IS-02 -20.00% 34.00 110 175,000 12,250 29,750 60,375 60,375 12,250 175,000 E-IS-03 -20.00% 49.00 290 500,000 35,000 85,000 172,500 172,500 35,000 500,000 La-FP-01 -20.00% 114,750 8,033 19,508 39,589 39,589 8,033 114,750 La-FP-02 -20.00% 193,500 13,545 32,895 66,758 66,758 13,545 193,500 La-FP-03 -20.00% 209,250 14,648 35,573 72,191 72,191 14,648 209,250 La-IS-01 -20.00% 311.00 149 400,000 28,000 68,000 138,000 138,000 28,000 400,000 La-IS-03 -20.00% 94.00 110 60,000 4,200 10,200 20,700 20,700 4,200 60,000 La-WS-09 -20.00% 21 50,000 3,500 8,500 17,250 17,250 3,500 50,000 L-FP-02 -20.00% 1 200,000 14,000 34,000 69,000 69,000 14,000 200,000 L-FP-03 -20.00% 2 250,000 17,500 42,500 86,250 86,250 17,500 250,000 L-FP-05 -20.00% 6 175,000 12,250 29,750 60,375 60,375 12,250 175,000 V-FP-02 -20.00% 258,750 18,113 43,988 89,269 89,269 18,113 258,750 V-FP-03 -20.00% 112,500 7,875 19,125 38,813 38,813 7,875 112,500 V-WS-01 -20.00% 42 123,300 8,631 20,961 42,539 42,539 8,631 123,300

25,658,250 1,796,077 4,361,902 8,852,096 8,852,096 1,796,077 25,658,250

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Table 0-2: Total Project Ranking (including O&M costs)

Irrigation Annual Breakdown of Capital Cost (US$) Maintenance Cost System Household Capital Cost % of Project Code Internal Rate of Return Total Cost % capital Service Area Beneficiaries (US$) Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 5 Yrs 20 Yrs (Ha) over 20 years 2 6 11 19 22 35 36 37 38 39 40 41 A B 42 B-IS-01 70.49% 232.00 780 25,000 1,750 4,250 8,625 8,625 1,750 25,000 - 9,000 36,000 144% B-RR-02 42.36% 441 434,977 30,448 73,946 150,067 150,067 30,448 434,977 - 24,640 98,560 23% L-RR-08 39.22% 88 85,002 5,950 14,450 29,326 29,326 5,950 85,002 - 19,200 76,800 90% B-IS-03 36.47% 27.00 766 65,000 4,550 11,050 22,425 22,425 4,550 65,000 - 9,000 36,000 55% B-WS-04 33.09% 243 75,000 5,250 12,750 25,875 25,875 5,250 75,000 - 21,600 102,600 137% La-FP-05 28.29% 95,000 6,650 16,150 32,775 32,775 6,650 95,000 - 11,850 47,400 50% B-WS-03 25.95% 196 75,000 5,250 12,750 25,875 25,875 5,250 75,000 - 21,600 102,600 137% V-IS-03 23.32% 233.00 573 75,000 5,250 12,750 25,875 25,875 5,250 75,000 - 9,000 36,000 48% V-IS-02 20.68% 131.00 746 120,000 8,400 20,400 41,400 41,400 8,400 120,000 - 9,000 36,000 30% V-IS-01 20.66% 103.00 793 120,000 8,400 20,400 41,400 41,400 8,400 120,000 - 9,000 36,000 30% A-WS-01 20.36% 201 100,000 7,000 17,000 34,500 34,500 7,000 100,000 - 21,600 102,600 103% V-WS-03 20.33% 105 40,000 2,800 6,800 13,800 13,800 2,800 40,000 - 21,600 102,600 257% V-WS-06 20.04% 277 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% B-IS-07 19.67% 5.30 418 65,000 4,550 11,050 22,425 22,425 4,550 65,000 - 9,000 36,000 55% La-RR-06 19.28% 368 200,000 14,000 34,000 69,000 69,000 14,000 200,000 - 112,000 448,000 224% E-RR-06 16.76% 344 300,000 21,000 51,000 103,500 103,500 21,000 300,000 - 64,000 256,000 85% La-WS-04 15.58% 115 60,000 4,200 10,200 20,700 20,700 4,200 60,000 - 21,600 102,600 171% La-WS-03 15.21% 120 65,000 4,550 11,050 22,425 22,425 4,550 65,000 - 21,600 102,600 158% V-WS-05 14.73% 218 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% B-IS-04 14.57% 143.00 362 90,000 6,300 15,300 31,050 31,050 6,300 90,000 - 9,000 36,000 40% A-WS-02 14.55% 128 75,000 5,250 12,750 25,875 25,875 5,250 75,000 - 21,600 102,600 137% E-WS-01 14.04% 137 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 21,600 102,600 121% A-FP-02 13.96% 58 50,000 3,500 8,500 17,250 17,250 3,500 50,000 - 1,500 6,000 12% La-WS-08 13.06% 78 35,000 2,450 5,950 12,075 12,075 2,450 35,000 - 21,600 102,600 293% B-RR-03 12.61% 108 199,993 14,000 33,999 68,998 68,998 14,000 199,993 - 87,360 349,440 175% B-IS-06 12.40% 13.00 247 50,000 3,500 8,500 17,250 17,250 3,500 50,000 - 9,000 36,000 72% E-WS-06 12.22% 127 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 21,600 102,600 121% La-WS-10 11.97% 115 75,000 5,250 12,750 25,875 25,875 5,250 75,000 - 21,600 102,600 137% B-RR-05 11.08% 110 349,980 24,499 59,497 120,743 120,743 24,499 349,980 - 13,760 55,040 16% La-WS-07 10.94% 101 65,000 4,550 11,050 22,425 22,425 4,550 65,000 - 21,600 102,600 158% E-WS-05 10.29% 219 200,000 14,000 34,000 69,000 69,000 14,000 200,000 - 21,600 102,600 51% E-WS-04 9.99% 123 95,000 6,650 16,150 32,775 32,775 6,650 95,000 - 21,600 102,600 108% La-WS-06 8.82% 88 60,000 4,200 10,200 20,700 20,700 4,200 60,000 - 21,600 102,600 171% B-RR-07 6.74% 114 374,995 26,250 63,749 129,373 129,373 26,250 374,995 - 64,000 256,000 68% A-IS-03 6.26% 20.00 365 120,000 8,400 20,400 41,400 41,400 8,400 120,000 - 9,000 36,000 30% La-WS-11 5.93% 65 40,000 2,800 6,800 13,800 13,800 2,800 40,000 - 21,600 102,600 257% E-IS-04 5.63% 221.00 402 185,000 12,950 31,450 63,825 63,825 12,950 185,000 - 9,000 36,000 19% La-RR-02 5.50% 227 249,972 17,498 42,495 86,240 86,240 17,498 249,972 - 51,520 206,080 82% B-WS-02 5.30% 132 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% L-WS-03 5.13% 97 95,000 6,650 16,150 32,775 32,775 6,650 95,000 - 21,600 102,600 108% A-IS-01 4.50% 94.00 238 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 9,000 36,000 42% L-WS-02 4.30% 125 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% La-IS-06 4.16% 81.00 235 75,000 5,250 12,750 25,875 25,875 5,250 75,000 - 9,000 36,000 48% A-RR-15 2.93% 76 249,900 17,493 42,483 86,216 86,216 17,493 249,900 - 70,080 280,320 112% E-RR-07 2.86% 200 300,000 21,000 51,000 103,500 103,500 21,000 300,000 - 54,720 218,880 73% V-RR-01 2.78% 125 449,979 31,499 76,496 155,243 155,243 31,499 449,979 - 108,160 432,640 96% E-RR-02 2.74% 408 599,900 41,993 101,983 206,966 206,966 41,993 599,900 - 80,000 320,000 53% B-IS-02 2.03% 12.00 112 30,000 2,100 5,100 10,350 10,350 2,100 30,000 - 9,000 36,000 120% La-WS-02 1.77% 78 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 21,600 102,600 121% La-WS-01 1.47% 105 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% B-WS-09 1.26% 76 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 21,600 102,600 121% B-RR-06 0.96% 25 149,997 10,500 25,499 51,749 51,749 10,500 149,997 - 12,800 51,200 34% V-FP-01 0.42% 9 157,500 11,025 26,775 54,338 54,338 11,025 157,500 - 10,500 42,000 27% E-IS-01 0.24% 107.00 230 175,000 12,250 29,750 60,375 60,375 12,250 175,000 - 9,000 36,000 21% La-WS-05 -0.12% 62 60,000 4,200 10,200 20,700 20,700 4,200 60,000 - 21,600 102,600 171% A-RR-12 -0.72% 26 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 16,000 64,000 43% B-WS-06 -0.85% 57 50,000 3,500 8,500 17,250 17,250 3,500 50,000 - 21,600 102,600 205% L-WS-01 -0.89% 72 95,000 6,650 16,150 32,775 32,775 6,650 95,000 - 21,600 102,600 108% L-IS-02 -1.19% 470.00 264 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 9,000 36,000 24% E-WS-03 -1.38% 97 175,000 12,250 29,750 60,375 60,375 12,250 175,000 - 21,600 102,600 59% E-WS-02 -2.36% 80 135,000 9,450 22,950 46,575 46,575 9,450 135,000 - 21,600 102,600 76% B-WS-01 -2.41% 59 65,000 4,550 11,050 22,425 22,425 4,550 65,000 - 21,600 102,600 158% B-WS-05 -4.37% 75 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% A-IS-02 -5.44% 51.00 177 120,000 8,400 20,400 41,400 41,400 8,400 120,000 - 9,000 36,000 30% B-WS-07 -6.18% 73 175,000 12,250 29,750 60,375 60,375 12,250 175,000 - 21,600 102,600 59% V-WS-04 -6.68% 65 142,625 9,984 24,246 49,206 49,206 9,984 142,625 - 21,600 102,600 72% L-RR-04 -7.24% 165 650,025 45,502 110,504 224,259 224,259 45,502 650,025 - 240,000 960,000 148% La-IS-05 -7.26% 16.00 201 135,000 9,450 22,950 46,575 46,575 9,450 135,000 - 9,000 36,000 27% E-FP-01 -7.84% 3 72,900 5,103 12,393 25,151 25,151 5,103 72,900 - 4,860 19,440 27% La-IS-04 -8.00% 240 196,687 13,768 33,437 67,857 67,857 13,768 196,687 - 9,000 36,000 18% La-RR-03 -8.59% 41 99,991 6,999 16,999 34,497 34,497 6,999 99,991 - 16,000 64,000 64% V-WS-02 -9.20% 59 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% A-RR-13 -9.20% 25 174,988 12,249 29,748 60,371 60,371 12,249 174,988 - 32,000 128,000 73% L-IS-01 -10.24% 1,051.00 453 450,000 31,500 76,500 155,250 155,250 31,500 450,000 - 9,000 36,000 8% L-FP-01 -12.14% 14 175,000 12,250 29,750 60,375 60,375 12,250 175,000 - 4,500 18,000 10% L-FP-06 -14.95% 1 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 3,000 12,000 8% La-IS-02 -17.99% 22.00 109 95,000 6,650 16,150 32,775 32,775 6,650 95,000 - 9,000 36,000 38% A-RR-14 -20.00% 5 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 32,000 128,000 85% A-RR-09 -20.00% 6 180,005 12,600 30,601 62,102 62,102 12,600 180,005 - 112,960 451,840 251% A-FP-01 -20.00% 1,654 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 3,000 12,000 14% A-FP-03 -20.00% 8 320,000 22,400 54,400 110,400 110,400 22,400 320,000 - 30,000 120,000 38% A-FP-04 -20.00% 1 200,000 14,000 34,000 69,000 69,000 14,000 200,000 - 15,000 60,000 30% A-FP-05 -20.00% 1 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 7,500 30,000 35% A-RR-01 -20.00% 45 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 240,000 960,000 1129% A-RR-02 -20.00% 36 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 256,000 1,024,000 1205% A-RR-03 -20.00% 5 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 48,000 192,000 128% A-RR-04 -20.00% 55 209,720 14,680 35,652 72,353 72,353 14,680 209,720 - 192,000 768,000 366% A-RR-05 -20.00% 39 189,390 13,257 32,196 65,340 65,340 13,257 189,390 - 19,200 76,800 41% A-RR-06 -20.00% 26 130,500 9,135 22,185 45,023 45,023 9,135 130,500 - 160,000 640,000 490% A-RR-07 -20.00% 65 307,980 21,559 52,357 106,253 106,253 21,559 307,980 - 108,160 432,640 140% A-RR-10 -20.00% 147 189,999 13,300 32,300 65,550 65,550 13,300 189,999 - 242,560 970,240 511% A-RR-11 -20.00% 25 194,990 13,649 33,148 67,272 67,272 13,649 194,990 - 227,520 910,080 467% A-WS-03 -20.00% 32 90,000 6,300 15,300 31,050 31,050 6,300 90,000 - 21,600 102,600 114% B-FP-02 -20.00% 300,000 21,000 51,000 103,500 103,500 21,000 300,000 - 22,800 91,200 30% B-FP-03 -20.00% 225,000 15,750 38,250 77,625 77,625 15,750 225,000 - 16,500 66,000 29% B-IS-05 -20.00% 180.00 9 120,000 8,400 20,400 41,400 41,400 8,400 120,000 - 9,000 36,000 30% B-WS-08 -20.00% 21 50,000 3,500 8,500 17,250 17,250 3,500 50,000 - 21,600 102,600 205% E-IS-02 -20.00% 34.00 110 175,000 12,250 29,750 60,375 60,375 12,250 175,000 - 9,000 36,000 21% E-IS-03 -20.00% 49.00 290 500,000 35,000 85,000 172,500 172,500 35,000 500,000 - 9,000 36,000 7% E-RR-01 -20.00% 399 650,000 45,500 110,500 224,250 224,250 45,500 650,000 - 256,000 1,024,000 158% E-RR-03 -20.00% 56 350,000 24,500 59,500 120,750 120,750 24,500 350,000 - 320,000 1,280,000 366% E-RR-04 -20.00% 20 249,000 17,430 42,330 85,905 85,905 17,430 249,000 - 30,912 123,648 50% E-RR-05 -20.00% 147 350,000 24,500 59,500 120,750 120,750 24,500 350,000 - 121,920 411,480 118% E-RR-08 -20.00% 71 650,000 45,500 110,500 224,250 224,250 45,500 650,000 - 32,000 128,000 20% E-RR-09 -20.00% 133 599,900 41,993 101,983 206,966 206,966 41,993 599,900 - 160,000 640,000 107% La-FP-01 -20.00% 114,750 8,033 19,508 39,589 39,589 8,033 114,750 - 7,650 30,600 27% La-FP-02 -20.00% 193,500 13,545 32,895 66,758 66,758 13,545 193,500 - 12,900 51,600 27% La-FP-03 -20.00% 209,250 14,648 35,573 72,191 72,191 14,648 209,250 - 13,950 55,800 27% La-IS-01 -20.00% 311.00 149 400,000 28,000 68,000 138,000 138,000 28,000 400,000 - 9,000 36,000 9% La-IS-03 -20.00% 94.00 110 60,000 4,200 10,200 20,700 20,700 4,200 60,000 - 9,000 36,000 60% La-RR-04 -20.00% 63 49,966 3,498 8,494 17,238 17,238 3,498 49,966 - 139,520 558,080 1117% La-RR-05 -20.00% 62 199,954 13,997 33,992 68,984 68,984 13,997 199,954 - 168,960 675,840 338% La-WS-09 -20.00% 21 50,000 3,500 8,500 17,250 17,250 3,500 50,000 - 21,600 102,600 205% L-FP-02 -20.00% 1 200,000 14,000 34,000 69,000 69,000 14,000 200,000 - 7,500 30,000 15% L-FP-03 -20.00% 2 250,000 17,500 42,500 86,250 86,250 17,500 250,000 - 10,050 40,200 16% L-FP-05 -20.00% 6 175,000 12,250 29,750 60,375 60,375 12,250 175,000 - 4,500 18,000 10% L-RR-01 -20.00% 43 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 48,000 192,000 128% L-RR-02 -20.00% 24 699,960 48,997 118,993 241,486 241,486 48,997 699,960 - 384,000 1,536,000 219% L-RR-03 -20.00% 85 650,000 45,500 110,500 224,250 224,250 45,500 650,000 - 256,000 1,024,000 158% L-RR-05 -20.00% 60 650,000 45,500 110,500 224,250 224,250 45,500 650,000 - 256,000 1,024,000 158% L-RR-06 -20.00% 50 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 48,000 192,000 128% L-RR-07 -20.00% 21 450,000 31,500 76,500 155,250 155,250 31,500 450,000 - 192,000 768,000 171% L-RR-09 -20.00% 210 300,000 21,000 51,000 103,500 103,500 21,000 300,000 - 160,000 640,000 213% V-FP-02 -20.00% 258,750 18,113 43,988 89,269 89,269 18,113 258,750 - 17,250 69,000 27% V-FP-03 -20.00% 112,500 7,875 19,125 38,813 38,813 7,875 112,500 - 7,500 30,000 27% V-RR-02 -20.00% 110 449,989 31,499 76,498 155,246 155,246 31,499 449,989 - 93,760 375,040 83% V-RR-03 -20.00% 98 499,989 34,999 84,998 172,496 172,496 34,999 499,989 - 112,960 451,840 90% V-RR-04 -20.00% 426 300,471 21,033 51,080 103,663 103,663 21,033 300,471 - 242,560 970,240 323% V-RR-05 -20.00% 112 499,975 34,998 84,996 172,491 172,491 34,998 499,975 - 227,520 910,080 182% V-WS-01 -20.00% 42 123,300 8,631 20,961 42,539 42,539 8,631 123,300 - 21,600 102,600 83% 102600 121% 25,658,250 1,796,077 4,361,902 8,852,096 8,852,096 1,796,077 25,658,250 62280 48%

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I A total of the yearly capital costs (assigned by SSRI project engineer) and overall total by IRR ranking priority are:

Year 1 Year 2 Year 3 Year 4 Year 5 Total All Projects 613,016 1,488,752 3,021,292 3,021,292 613,016 8,757,368 34% 594,102 1,442,818 2,928,072 2,928,072 594,102 8,487,165 33% 588,960 1,430,332 2,902,732 2,902,732 588,960 8,413,717 33% Total 1,796,077 4,361,902 8,852,096 8,852,096 1,796,077 25,658,250 100% Excluding Rural Road maintenance - 67% of project costs (USD 17.2 million) representing 87 projects are in high and medium ranking priority

Year 1 Year 2 Year 3 Year 4 Year 5 Total All Projects 373,794 907,786 1,842,272 1,842,272 373,794 5,339,919 21% 437,464 1,062,414 2,156,075 2,156,075 437,464 6,249,493 24% 984,819 2,391,702 4,853,749 4,853,749 984,819 14,068,838 55% Total 1,796,077 4,361,902 8,852,096 8,852,096 1,796,077 25,658,250 100% Including Rural Road maintenance - 45% of project costs (USD 11.6 million) representing 77 projects are in high and medium ranking priority.

11.11.3 Rural Road Projects Rural road projects will protect roads and therefore communities using these roads to gain access to jobs, market, school, church, medical facilities and family etc. GIS techniques were used to derive “catchment” areas of beneficiaries using improved rural roads (see Figure 0-2). Decision on total beneficiaries was taken based on topography and lack of easy access to existing roads in the event of a landslide or wholescale degradation of the road surface and supporting infrastructure.

Under the Do Nothing base line scenario it was assumed that, as well as all potential landslides or degradation occurring with the same frequency (see above) the disruption would be for 1 month. Default disruption of up to 9 months were used where IRR’s were still low or negative. This “forcing” of the IRR was reflected in the rankings.

Taking out the high costs of annual and periodic cyclical maintenance improves the IRR indicating positive returns on investment and allows realistic ranking at this pre-feasibility stage of benefit cost analysis. The trial rankings were based on no maintenance costs included and road closure under Do Nothing for 3 months as advised by the infrastructure engineers.

In the example below E-RR-02 periodic degradation of the existing road during adverse conditions, including total instability would cut off the community in the beneficiary buffer involving an unacceptable journey detour to markets, etc.

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S-Lauala-Talikotu Road ! & (! (

(! (!

(! (! (!! (! ( (! (! ! ((! (! (! (! (!(! (! ! (!(! (!( (! (! (! (! (! ! (! ( (! (!

(! (! (! (! (! ! ((! (!(! (!(! (!(! (!

(! (!! (! (! (!(! ( !(! (! (!(! (!(!(!(! (! (! (!( (! (! ! (!((! (! (! (! (! ! (! !(! ! ( ( ( (!(! (! (! (! (! (! (! ! (! (! (! ((! (!(! (! (!(! (! (! (! (! ! (!(! ( (! !(! (! (! (! (! (! ! (! (! ! (!! ( (!(!( (! (! ( ! (! ! (! ! (! ( (! ( (! ( (!(!(! (! (! ! (! (! (! ! ( (!(! ! ( (! (!( (! (! (! (! ! (!(! (! (! ( (!(! (! (! (! (! (! (!(!(! (! ! (! (! ! (!(! (! (! ( (! ! (! (! ! ( (! (! (! (!( !(! ! (! (! ! ( (! (! (!(! ! !(!(! (! (! (! (! (! ( ( ( (! (! ( ( (! ! (! (! (!(! (! E-Lauala (! ( (! (! (!(! (! (! (! ! (! ! (! (! (! !!(! ( (! (! ( (! (!(!(! !! (!(!!((!(!(! (! (! (! Talikotu(!(! (!(!(! (! (!(((!(! (! (! (! ( (! (!(! (! (! (! (! (! (! (!!(! (! (! (! (! (! (! (!(( ! (! (! (! (! (! (! (!(! (! ((! (! (! ! (! (! (!! ! (! (! (! !(! ((! (! (!(! (! (! ( ( Road( ! (! (!(! (! ! ! ((! ( ( (! ! (!! !( (! (!(! (! ! (!( (!!(! ! ( ( ( (! ( ! & (! (! (! ( ! (!(! (! (! (!(!(! (! (! (! (! (! (! (! (! (!(! (! ! (! (! ! (! (! ((! (! ! (! (! (! (! (! (!(!(! !(!(! (! ! (!(! (!(! (! (! (( ((! (! (! (! (! (! (! (! (!(! (! (! (! (! (!

Legend Landslide Risk Levels

River Proposed Road Very Low High (! Beneficiaries Main Road Low Very High E-RR-02 Benefit Buffer Rural Roads Moderate

Figure 0-2: Emera Road #2 (E-RR-02) (new proposed road in red)

Figure 0-34: Tillustrateshe existing the existing road condition road condition along along the the proposed proposed road road for for E- RRE-RR-02.-02

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Project ID: E-RR-02 Project Name: Rehabilitation of road and drains from Lauala to Talikotu Municipality: Ermera I.R.R. : 3% Project Desciption: Clearing, grubbing and excavation, construction of various drainage structures (culverts and causeways) and concrete kerb (retaining wall) and drainage channel, gabion installation and soil bioengineering, gravel and concrete surfacing for 7.0 kms Total Cost: $ 919,900.00 599900 - 1 month disruption COST MONETARY BENEFITS NON-MONETARY BENEFITS Unit Cost Economic Benefit Beneficiaries Cash Flow Length of Road Maintenance Total Cost Total Total Capital Cost Stream Households Population (km) Cost Income Benefits

Project Life (yrs) Project Life 2.50 599,900 408 2,385 1 1.25 299,950 7,500 307,450 - - 307,450 2 1.25 299,950 7,500 307,450 - - 307,450 3 7,500 7,500 120,443 120,443 112,943 4 7,500 7,500 - - 7,500 5 50,000 50,000 120,443 120,443 70,443 Comments 6 7,500 7,500 - - 7,500 IRR No maintenance 7 7,500 7,500 120,443 120,443 112,943 27% 8 7,500 7,500 - - 7,500 IRR 9 months disruption 9 7,500 7,500 120,443 120,443 112,943 69% 10 50,000 50,000 - - 50,000 IRR No maintenance with 11 7,500 7,500 120,443 120,443 112,943 3 month disruption scenario 12 7,500 7,500 - - 7,500 78% 13 7,500 7,500 120,443 120,443 112,943 14 7,500 7,500 - - 7,500 15 50,000 50,000 120,443 120,443 70,443 16 7,500 7,500 - - 7,500 17 7,500 7,500 120,443 120,443 112,943 18 7,500 7,500 - - 7,500 19 7,500 7,500 120,443 120,443 112,943 20 50,000 50,000 - - 50,000 35% 320,000 919,900 3% INTERNAL RATE OF RETURN (IRR) Table 3 (above) indicates the range of IRRs and project cash flow. In this case the large number of beneficiaries (408 households) ensures that including maintenance costs gives an IRR of 3% and ranks the project in the middle third of projects considered in the pilot municipalities. Annual and Periodic maintenance costs make up 53% of the capital costs.

The IRR reflects a combination of the scale of costs and number of beneficiaries. The highest ranked road project: B-RR-02 has many beneficiaries (441 households) and though high capital costs maintenance costs (23% of capital costs) are relatively low.

The priority ranking for Rural Road projects (including maintenance costs) is summarised below:

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B-RR-02 42.36% 441 434,977 30,448 73,946 150,067 150,067 30,448 434,977 - 24,640 98,560 23% L-RR-08 39.22% 88 85,002 5,950 14,450 29,326 29,326 5,950 85,002 - 19,200 76,800 90% La-RR-06 19.28% 368 200,000 14,000 34,000 69,000 69,000 14,000 200,000 - 112,000 448,000 224% E-RR-06 16.76% 344 300,000 21,000 51,000 103,500 103,500 21,000 300,000 - 64,000 256,000 85% B-RR-03 12.61% 108 199,993 14,000 33,999 68,998 68,998 14,000 199,993 - 87,360 349,440 175% B-RR-05 11.08% 110 349,980 24,499 59,497 120,743 120,743 24,499 349,980 - 13,760 55,040 16% B-RR-07 6.74% 114 374,995 26,250 63,749 129,373 129,373 26,250 374,995 - 64,000 256,000 68% La-RR-02 5.50% 227 249,972 17,498 42,495 86,240 86,240 17,498 249,972 - 51,520 206,080 82% A-RR-15 2.93% 76 249,900 17,493 42,483 86,216 86,216 17,493 249,900 - 70,080 280,320 112% E-RR-07 2.86% 200 300,000 21,000 51,000 103,500 103,500 21,000 300,000 - 54,720 218,880 73% V-RR-01 2.78% 125 449,979 31,499 76,496 155,243 155,243 31,499 449,979 - 108,160 432,640 96% E-RR-02 2.74% 408 599,900 41,993 101,983 206,966 206,966 41,993 599,900 - 80,000 320,000 53% B-RR-06 0.96% 25 149,997 10,500 25,499 51,749 51,749 10,500 149,997 - 12,800 51,200 34% A-RR-12 -0.72% 26 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 16,000 64,000 43% L-RR-04 -7.24% 165 650,025 45,502 110,504 224,259 224,259 45,502 650,025 - 240,000 960,000 148% La-RR-03 -8.59% 41 99,991 6,999 16,999 34,497 34,497 6,999 99,991 - 16,000 64,000 64% A-RR-13 -9.20% 25 174,988 12,249 29,748 60,371 60,371 12,249 174,988 - 32,000 128,000 73% A-RR-14 -20.00% 5 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 32,000 128,000 85% A-RR-09 -20.00% 6 180,005 12,600 30,601 62,102 62,102 12,600 180,005 - 112,960 451,840 251% A-RR-01 -20.00% 45 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 240,000 960,000 1129% A-RR-02 -20.00% 36 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 256,000 1,024,000 1205% A-RR-03 -20.00% 5 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 48,000 192,000 128% A-RR-04 -20.00% 55 209,720 14,680 35,652 72,353 72,353 14,680 209,720 - 192,000 768,000 366% A-RR-05 -20.00% 39 189,390 13,257 32,196 65,340 65,340 13,257 189,390 - 19,200 76,800 41% A-RR-06 -20.00% 26 130,500 9,135 22,185 45,023 45,023 9,135 130,500 - 160,000 640,000 490% A-RR-07 -20.00% 65 307,980 21,559 52,357 106,253 106,253 21,559 307,980 - 108,160 432,640 140% A-RR-10 -20.00% 147 189,999 13,300 32,300 65,550 65,550 13,300 189,999 - 242,560 970,240 511% A-RR-11 -20.00% 25 194,990 13,649 33,148 67,272 67,272 13,649 194,990 - 227,520 910,080 467% E-RR-01 -20.00% 399 650,000 45,500 110,500 224,250 224,250 45,500 650,000 - 256,000 1,024,000 158% E-RR-03 -20.00% 56 350,000 24,500 59,500 120,750 120,750 24,500 350,000 - 320,000 1,280,000 366% E-RR-04 -20.00% 20 249,000 17,430 42,330 85,905 85,905 17,430 249,000 - 30,912 123,648 50% E-RR-05 -20.00% 147 350,000 24,500 59,500 120,750 120,750 24,500 350,000 - 121,920 411,480 118% E-RR-08 -20.00% 71 650,000 45,500 110,500 224,250 224,250 45,500 650,000 - 32,000 128,000 20% E-RR-09 -20.00% 133 599,900 41,993 101,983 206,966 206,966 41,993 599,900 - 160,000 640,000 107% La-RR-04 -20.00% 63 49,966 3,498 8,494 17,238 17,238 3,498 49,966 - 139,520 558,080 1117% La-RR-05 -20.00% 62 199,954 13,997 33,992 68,984 68,984 13,997 199,954 - 168,960 675,840 338% L-RR-01 -20.00% 43 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 48,000 192,000 128% L-RR-02 -20.00% 24 699,960 48,997 118,993 241,486 241,486 48,997 699,960 - 384,000 1,536,000 219% L-RR-03 -20.00% 85 650,000 45,500 110,500 224,250 224,250 45,500 650,000 - 256,000 1,024,000 158% L-RR-05 -20.00% 60 650,000 45,500 110,500 224,250 224,250 45,500 650,000 - 256,000 1,024,000 158% L-RR-06 -20.00% 50 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 48,000 192,000 128% L-RR-07 -20.00% 21 450,000 31,500 76,500 155,250 155,250 31,500 450,000 - 192,000 768,000 171% L-RR-09 -20.00% 210 300,000 21,000 51,000 103,500 103,500 21,000 300,000 - 160,000 640,000 213% V-RR-02 -20.00% 110 449,989 31,499 76,498 155,246 155,246 31,499 449,989 - 93,760 375,040 83% V-RR-03 -20.00% 98 499,989 34,999 84,998 172,496 172,496 34,999 499,989 - 112,960 451,840 90% V-RR-04 -20.00% 426 300,471 21,033 51,080 103,663 103,663 21,033 300,471 - 242,560 970,240 323% V-RR-05 -20.00% 112 499,975 34,998 84,996 172,491 172,491 34,998 499,975 - 227,520 910,080 182% Very high negative values are capped at -20% See Table 2 for Column Headings

14 Projects ranked in the third or lowest ranking IRR band are within the high and medium ranking bands with respect to beneficiary households and could be considered for inclusion. Their economic ranking reflects the high project costs, especially the whole life annual and periodic maintenance costs (see last column). 5 projects ranked in the Highest and second IRR band are in the lowest beneficiary ranking band. This reflects the significantly lower whole life project costs, especially periodic and annual maintenance.

A summary of Rural Roads priority ranking and year by year investment of capital costs over 5 years with total follows:

Year 1 Year 2 Year 3 Year 4 Year 5 Total Rural Roads 153,644 373,136 757,247 757,247 153,644 2,194,919 15% 197,735 480,213 974,549 974,549 197,735 2,824,780 19% 684,025 1,661,204 3,371,267 3,371,267 684,025 9,771,788 66% Total 1,035,404 2,514,553 5,103,063 5,103,063 1,035,404 14,791,488 100% Including Rural Road maintenance - 34% of project costs (USD 5.0 million) representing 18 projects are in high and medium ranking priority but 4 of these have a negative IRR.

Year 1 Year 2 Year 3 Year 4 Year 5 Total Rural Roads 499,966 1,214,202 2,464,117 2,464,117 499,966 7,142,368 48% 369,227 896,693 1,819,759 1,819,759 369,227 5,274,665 36% 166,212 403,657 819,187 819,187 166,212 2,374,455 16% Total 1,035,404 2,514,553 5,103,063 5,103,063 1,035,404 14,791,488 100%

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I Excluding Rural Road maintenance - 84% of project costs (USD 12.4 million) representing 37 projects are in high and medium ranking priority but 2 of these have a negative IRR. 11.11.4 Water Supply Projects Water supply projects will secure water supplies to prescribed areas, especially in times of drought, with monetised benefits using total household income of water supply service area protected (usually the households in the Suco) as an economic surrogate. Figure 0-5 illustrates a typical reservoir installation.

Figure 0-5: Completed Reservoir installation in Ermera

Project La-WS-04 presents the IRR and cash flows for a similar storage reservoir as shown above providing secure supple to 125 households with a 16% IRR.

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Project ID: La-WS-04 Project Name: Rehabilitation of water supply (water pump) system in suco souro Municipality: Lautem I.R.R. : 16% Project Description: Water pump and installation of 60 m3 of reservoir, installation if 2 km of transmission and distribution pipelines and construction of 12 public taps Total Cost: $ 162,600.00 COST MONETARY BENEFITS NON-MONETARY BENEFITS Unit Cost Economic Benefit Beneficiaries Cash Flow Length Canal Maintenance Total Cost Total Total Capital Cost Stream Households Population (km) Cost Income Benefits

Project Life (yrs) Project Life 2.00 60,000 115 500 1 60,000 60,000 - - 60,000 2 5,400 5,400 - - 5,400 3 5,400 5,400 33,523 33,523 28,123 4 5,400 5,400 - - 5,400 5 5,400 5,400 33,523 33,523 28,123 Comments 6 5,400 5,400 - - 5,400 No Maintenance 7 5,400 5,400 33,523 33,523 28,123 24% 8 5,400 5,400 - - 5,400 9 5,400 5,400 33,523 33,523 28,123 10 5,400 5,400 - - 5,400 11 5,400 5,400 33,523 33,523 28,123 12 5,400 5,400 - - 5,400 13 5,400 5,400 33,523 33,523 28,123 14 5,400 5,400 - - 5,400 15 5,400 5,400 33,523 33,523 28,123 16 5,400 5,400 - - 5,400 17 5,400 5,400 33,523 33,523 28,123 18 5,400 5,400 - - 5,400 19 5,400 5,400 33,523 33,523 28,123 20 5,400 5,400 - - 5,400 63% 102,600 162,600 16% INTERNAL RATE OF RETURN (IRR) The priority ranking for Water Supply projects (including maintenance costs) is:

B-WS-04 33.09% 243 75,000 5,250 12,750 25,875 25,875 5,250 75,000 - 21,600 102,600 137% B-WS-03 25.95% 196 75,000 5,250 12,750 25,875 25,875 5,250 75,000 - 21,600 102,600 137% A-WS-01 20.36% 201 100,000 7,000 17,000 34,500 34,500 7,000 100,000 - 21,600 102,600 103% V-WS-03 20.33% 105 40,000 2,800 6,800 13,800 13,800 2,800 40,000 - 21,600 102,600 257% V-WS-06 20.04% 277 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% La-WS-04 15.58% 115 60,000 4,200 10,200 20,700 20,700 4,200 60,000 - 21,600 102,600 171% La-WS-03 15.21% 120 65,000 4,550 11,050 22,425 22,425 4,550 65,000 - 21,600 102,600 158% V-WS-05 14.73% 218 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% A-WS-02 14.55% 128 75,000 5,250 12,750 25,875 25,875 5,250 75,000 - 21,600 102,600 137% E-WS-01 14.04% 137 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 21,600 102,600 121% La-WS-08 13.06% 78 35,000 2,450 5,950 12,075 12,075 2,450 35,000 - 21,600 102,600 293% E-WS-06 12.22% 127 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 21,600 102,600 121% La-WS-10 11.97% 115 75,000 5,250 12,750 25,875 25,875 5,250 75,000 - 21,600 102,600 137% La-WS-07 10.94% 101 65,000 4,550 11,050 22,425 22,425 4,550 65,000 - 21,600 102,600 158% E-WS-05 10.29% 219 200,000 14,000 34,000 69,000 69,000 14,000 200,000 - 21,600 102,600 51% E-WS-04 9.99% 123 95,000 6,650 16,150 32,775 32,775 6,650 95,000 - 21,600 102,600 108% La-WS-06 8.82% 88 60,000 4,200 10,200 20,700 20,700 4,200 60,000 - 21,600 102,600 171% La-WS-11 5.93% 65 40,000 2,800 6,800 13,800 13,800 2,800 40,000 - 21,600 102,600 257% B-WS-02 5.30% 132 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% L-WS-03 5.13% 97 95,000 6,650 16,150 32,775 32,775 6,650 95,000 - 21,600 102,600 108% L-WS-02 4.30% 125 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% La-WS-02 1.77% 78 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 21,600 102,600 121% La-WS-01 1.47% 105 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% B-WS-09 1.26% 76 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 21,600 102,600 121% La-WS-05 -0.12% 62 60,000 4,200 10,200 20,700 20,700 4,200 60,000 - 21,600 102,600 171% B-WS-06 -0.85% 57 50,000 3,500 8,500 17,250 17,250 3,500 50,000 - 21,600 102,600 205% L-WS-01 -0.89% 72 95,000 6,650 16,150 32,775 32,775 6,650 95,000 - 21,600 102,600 108% E-WS-03 -1.38% 97 175,000 12,250 29,750 60,375 60,375 12,250 175,000 - 21,600 102,600 59% E-WS-02 -2.36% 80 135,000 9,450 22,950 46,575 46,575 9,450 135,000 - 21,600 102,600 76% B-WS-01 -2.41% 59 65,000 4,550 11,050 22,425 22,425 4,550 65,000 - 21,600 102,600 158% B-WS-05 -4.37% 75 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% B-WS-07 -6.18% 73 175,000 12,250 29,750 60,375 60,375 12,250 175,000 - 21,600 102,600 59% V-WS-04 -6.68% 65 142,625 9,984 24,246 49,206 49,206 9,984 142,625 - 21,600 102,600 72% V-WS-02 -9.20% 59 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 21,600 102,600 68% A-WS-03 -20.00% 32 90,000 6,300 15,300 31,050 31,050 6,300 90,000 - 21,600 102,600 114% B-WS-08 -20.00% 21 50,000 3,500 8,500 17,250 17,250 3,500 50,000 - 21,600 102,600 205% La-WS-09 -20.00% 21 50,000 3,500 8,500 17,250 17,250 3,500 50,000 - 21,600 102,600 205% V-WS-01 -20.00% 42 123,300 8,631 20,961 42,539 42,539 8,631 123,300 - 21,600 102,600 83% Very high negative values are capped at -20% See Table 2 for Column Headings

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I 34 projects are in the highest and medium priority ranks though 10 have a negative IRR. Although maintenance costs are in the highest-ranking band for 11 of the projects in the Highest IRR ranking band, a combination of low capital costs and high numbers of beneficiaries maintains high IRR’s.

All Projects ranked in the third or lowest ranking IRR band are also within the lowest ranking band with respect to beneficiary household. Their low economic ranking reflects their high project costs. No projects ranked in the Highest IRR band are in the lowest beneficiary ranking band.

A summary of Water Supply priority ranking and year by year investment of capital costs over 5 years with total and capital costs follows:

Year 1 Year 2 Year 3 Year 4 Year 5 Total 63,700 154,700 313,950 313,950 63,700 910,000 24% 144,550 351,050 712,425 712,425 144,550 2,065,000 55% 54,665 132,757 269,419 269,419 54,665 780,925 21% 262,915 638,507 1,295,794 1,295,794 262,915 3,755,925 100% Some 79% of the capital costs representing 34 projects with a capital cost of USD 3.0 million are within the high and medium priority rankings but 4 of these have a negative IRR. 11.11.5 Irrigation System projects Irrigation System projects will give resilience to Irrigation infrastructure and protect crop income, especially during dry season drought, for the crop land within a defined service area.

Project V-IS-03 presents the IRR and cash flows for the construction of a 1 km irrigation channel and supporting infrastructure providing a secure water supply to 573 households within the 273 Ha Service Area returning a 20% IRR.

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Project ID: V-IS-03 Project Name: Rehabilitation of irrigation channel at Belia 1 and 2 Municipality: Viqueque I.R.R. : 23% Project Description: Clearance and excavation, rehabilitation of intake tank, 1 Km of masonry irrigation channel, check gates and gabion wall, back filling and soil bio engineering work Total Cost: $ 143,800.00 bio engineering works COST MONETARY BENEFITS NON-MONETARY BENEFITS Unit Cost Economic Benefit Beneficiaries Length of Cash Flow Operational Maintenance Total Cost Total Total Irrigation Capital Cost Stream Households Service Area Cost Cost Income Benefits

System (km) Project Life (yrs) Project Life 1.00 75,000 573 233.00 1 75,000 1,800 800 77,600 - - 77,600 2 1,800 800 2,600 - - 2,600 3 1,800 800 2,600 48,663 48,663 46,063 4 1,800 800 2,600 - - 2,600 5 1,800 5,000 6,800 48,663 48,663 41,863 Comments 6 1,800 800 2,600 - - 2,600 IRR No O&M Costs 7 1,800 800 2,600 48,663 48,663 46,063 28% 8 1,800 800 2,600 - - 2,600 9 1,800 800 2,600 48,663 48,663 46,063 10 1,800 5,000 6,800 - - 6,800 11 1,800 800 2,600 48,663 48,663 46,063 12 1,800 800 2,600 - - 2,600 13 1,800 800 2,600 48,663 48,663 46,063 14 1,800 800 2,600 - - 2,600 15 1,800 5,000 6,800 48,663 48,663 41,863 16 1,800 800 2,600 - - 2,600 17 1,800 800 2,600 48,663 48,663 46,063 18 1,800 800 2,600 - - 2,600 19 1,800 800 2,600 48,663 48,663 46,063 20 1,800 5,000 6,800 - - 6,800 23% 32,800 143,800 23% INTERNAL RATE OF RETURN (IRR)

4 Projects ranked in the lowest ranking IRR band are within the high and medium ranking bands with respect to beneficiary households or Irrigation Service areas and could be considered for inclusion. Their low economic ranking generally reflects their high capital costs. No projects ranked in the Highest IRR ranking band are in the lowest or medium beneficiary ranking band.

A summary of Irrigation System priority ranking and year by year investment of capital costs over 5 years with total and capital costs follows:

Irrigation System 39,200 95,200 193,200 193,200 39,200 560,000 15% 69,300 168,300 341,550 341,550 69,300 990,000 27% 149,218 362,387 735,432 735,432 149,218 2,131,687 58% Total 257,718 625,887 1,270,182 1,270,182 257,718 3,681,687 100%

Some 42% of the capital costs representing 20 projects with a capital cost of USD 1.6 million are within the high and medium priority rankings but 6 of these have a negative IRR. 11.11.6 Flood protection projects Modelling of affected areas used an index-based method (Topographic Wetness Index) where flood areas were identified as high, medium or low flooded areas; thus, in a high defined area flood depths would be expected to accumulate to deeper depths than areas defined as low. The following summarises USD damage values based on socio-economic risk analysis. Where a construction/roof code was not available the rural or urban median value was applied.

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Census code Flood Damage (USD) for Flood Depth Ranges House Type Roof H2 H3 Low Medium High 1U Concrete/Brick Concrete 1 5 2,823 10,041 13,650 2U Concrete/Brick Corrugated iron or zinc 1 2 1,220 4,338 5,898 3U Concrete/Brick Asbestos 1 4 284 1,011 1,374 4U Concrete/Brick Tiles 1 3 1,840 6,543 8,895 5U Wood Asbestos 2 4 523 1,862 2,531 6U Wood Corrugated iron or zinc 2 2 523 1,862 2,531 7U Corrugated iron/zinc Asbestos 4 4 426 1,517 2,062 8U Corrugated iron/zinc Corrugated iron/zinc 4 2 426 1,517 2,062 9U Bamboo Corrugated iron/zinc 3 2 299 1,062 1,444 10U Bamboo Asbestos 3 4 299 1,062 1,444 11U Bamboo Bamboo 3 6 102 363 494 12U Rock Palm leaves 7 1 102 363 494 13U Wood Other 2 7 831 2,955 4,017 14U Thatch/Palm Trunk/ClayVarious 6 2 102 363 494 Median 426 1,517 2,062 1R Concrete/Brick Concrete 1 5 2,439 8,672 11,790 2R Concrete/Brick Corrugated iron or zinc 1 2 866 3,081 4,188 3R Concrete/Brick Asbestos 1 4 789 2,806 3,815 4R Concrete/Brick Tiles 1 3 1,030 3,662 4,978 5R Wood Asbestos 2 4 315 1,121 1,523 6R Wood Corrugated iron or zinc 2 2 315 1,121 1,523 7R Corrugated iron/zinc Asbestos 4 4 229 813 1,105 8R Corrugated iron/zinc Corrugated iron/zinc 4 2 229 813 1,105 9R Bamboo Corrugated iron/zinc 3 2 162 575 781 10R Bamboo Asbestos 3 4 162 575 781 11R Bamboo Bamboo 3 6 62 222 302 12R Rock Palm leaves 7 1 62 222 302 13R Wood Other 2 7 507 1,803 2,452 14R Thatch/Palm Trunk/ClayVarious 6 2 62 222 302 Median 272 967 1,314 The wetness Index method did not allow flood probability to be estimated, neither therefore annual average damages so a similar method was used to represent damages saved by flood protection measures as used for the other infrastructure projects.

The number or properties in each flood depth band were multiplied by the appropriate damage value and accumulated as an “event” damage. It was assumed for all projects that this so-called event damage would occur with comparable frequency so a ranking of project priority could be deduced from IRR calculations.

To capture potential crop losses from flooding – under Do Nothing - (as no land use or crop data was available) the crop income data was used and applied to all properties within an estimated hinterland of the flood plain where it was likely households would grow their crops. Benefits are thus the savings of crop income loss as a result of improved flood protection.

Only 2 Flood Protection projects are cost beneficial as most of the resilience work is strengthening of the river banks (River training gabions for example).

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La-FP-05 28.29% 95,000 6,650 16,150 32,775 32,775 6,650 95,000 - 11,850 47,400 50% A-FP-02 13.96% 58 50,000 3,500 8,500 17,250 17,250 3,500 50,000 - 1,500 6,000 12% V-FP-01 0.42% 9 157,500 11,025 26,775 54,338 54,338 11,025 157,500 - 10,500 42,000 27% E-FP-01 -7.84% 3 72,900 5,103 12,393 25,151 25,151 5,103 72,900 - 4,860 19,440 27% L-FP-01 -12.14% 14 175,000 12,250 29,750 60,375 60,375 12,250 175,000 - 4,500 18,000 10% L-FP-06 -14.95% 1 150,000 10,500 25,500 51,750 51,750 10,500 150,000 - 3,000 12,000 8% A-FP-01 -20.00% 1,654 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 3,000 12,000 14% A-FP-03 -20.00% 8 320,000 22,400 54,400 110,400 110,400 22,400 320,000 - 30,000 120,000 38% A-FP-04 -20.00% 1 200,000 14,000 34,000 69,000 69,000 14,000 200,000 - 15,000 60,000 30% A-FP-05 -20.00% 1 85,000 5,950 14,450 29,325 29,325 5,950 85,000 - 7,500 30,000 35% B-FP-02 -20.00% 300,000 21,000 51,000 103,500 103,500 21,000 300,000 - 22,800 91,200 30% B-FP-03 -20.00% 225,000 15,750 38,250 77,625 77,625 15,750 225,000 - 16,500 66,000 29% La-FP-01 -20.00% 114,750 8,033 19,508 39,589 39,589 8,033 114,750 - 7,650 30,600 27% La-FP-02 -20.00% 193,500 13,545 32,895 66,758 66,758 13,545 193,500 - 12,900 51,600 27% La-FP-03 -20.00% 209,250 14,648 35,573 72,191 72,191 14,648 209,250 - 13,950 55,800 27% L-FP-02 -20.00% 1 200,000 14,000 34,000 69,000 69,000 14,000 200,000 - 7,500 30,000 15% L-FP-03 -20.00% 2 250,000 17,500 42,500 86,250 86,250 17,500 250,000 - 10,050 40,200 16% L-FP-05 -20.00% 6 175,000 12,250 29,750 60,375 60,375 12,250 175,000 - 4,500 18,000 10% V-FP-02 -20.00% 258,750 18,113 43,988 89,269 89,269 18,113 258,750 - 17,250 69,000 27% V-FP-03 -20.00% 112,500 7,875 19,125 38,813 38,813 7,875 112,500 - 7,500 30,000 27% Very high negative values are capped at -20% See Table 2 for Column Headings

The following example, E-FP-01 shows the high medium and low flood zones with 3 households (14 people) and only 3.49 hectares protected. The IRR is negative despite the assumption that household damages and crop income as estimated are lost yearly (a gross assumption):

Project ID: E-FP-01 Project Name: Gabion wall installment in Gegrama Municipality: Baucau I.R.R. : -8% Project Description: Clearing and excavation, 320 meters by 3 layer of gabion embankment, backfilling and soil bio-engineering work Total Cost: $ 92,340.00 COST NON-MONETARY BENEFITS Unit Cost Beneficiaries Crop Property Cash Flow Length of Flood Maintenance Total Cost Income Total Flooded Area Capital Cost Damage by Stream Households Population Protection (km) Cost from Benefits (Hectares) Flood

Project Life (yrs) Project Life properties 0.32 72,900 3 3 3 14 3.49 1 72,900 72,900 255 2,387 2,642 - 70,258 2 - 255 2,387 2,642 2,642 3 - 255 2,387 2,642 2,642 4 - 255 2,387 2,642 2,642 5 4,860 4,860 255 2,387 2,642 - 2,218 Comments 6 - 255 2,387 2,642 2,642 IRR No Maintenance 7 - 255 2,387 2,642 2,642 -3% 8 - 255 2,387 2,642 2,642 9 - 255 2,387 2,642 2,642 10 4,860 4,860 255 2,387 2,642 - 2,218 11 - 255 2,387 2,642 2,642 12 - 255 2,387 2,642 2,642 13 - 255 2,387 2,642 2,642 14 - 255 2,387 2,642 2,642 15 4,860 4,860 255 2,387 2,642 - 2,218 16 - 255 2,387 2,642 2,642 17 - 255 2,387 2,642 2,642 18 - 255 2,387 2,642 2,642 19 - 255 2,387 2,642 2,642 20 4,860 4,860 255 2,387 2,642 - 2,218 21% 19,440 92,340 -8% INTERNAL RATE OF RETURN (IRR)

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Legend Flood Hazard Risk Levels

Beneficiaries Low Proposed Flood Control Scheme Medium E-FP-01 River High

Figure 0-6: The flood plain at Gegrama, Ermera Municipality

The second example (La-FP-05) appears to provide a highly positive IRR with 123 households in the flood plain and benefits distributed every 5 years.

Legend Flood Hazard Risk Levels

Beneficiaries Low Proposed Flood Control Scheme Medium La-FP-05 Main Road High

Figure 0-7: Floodplain at Suco Mehara, Lautem

The project is designed to create a 790m gabion embankment to prevent excessive drainage affecting the community.

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Project ID: La-FP-05 Project Name: Construction of Drainage and retaining wall in Suco Mehara Municipality: Lautem I.R.R. : 28% Project Description: Clearance and excavation for construction of 790 M by 3 layers of gabion embankment, back filling and soil bio engineering work Total Cost: $ 142,400.00 COST NON-MONETARY BENEFITS Unit Cost Beneficiaries Crop Property Cash Flow Length of Flood Maintenance Total Cost Income Total Flooded Area Capital Cost Damage by Stream Households Population Protection (km) Cost from Benefits (Hectares) Flood

Project Life (yrs) Project Life properties 0.79 95,000 123 133,488 123 684 14.95 1 95,000 95,000 66,744 66,744 - 28,256 2 - - 3 - - 4 - - 5 11,850 11,850 66,744 66,744 54,894 Comments 6 - - 7 - - 8 - - 9 - - 10 11,850 11,850 66,744 66,744 54,894 11 - - 12 - - 13 - - 14 - - 15 11,850 11,850 66,744 66,744 54,894 16 - - 17 - - 18 - - 19 - - 20 11,850 11,850 - 66,744 66,744 54,894 33% 47,400 142,400 28% INTERNAL RATE OF RETURN (IRR) One Project ranked in the lowest ranking IRR band is within the high-ranking bands with respect to beneficiaries as this project (A-FP-01) is designed to protect an Administration Post, with the whole sub-district gaining some advantage from this project, and therefore could be considered for inclusion. The general low economic project ranking reflects the high project costs and the relatively low numbers of beneficiaries. Maintenance costs are generally low however, in comparison to, say, rural road projects which increases the viability of these flood protection projects.

A summary of Flood Protection priority ranking and year by year investment of capital costs over 5 years with total and capital costs follows:

Year 1 Year 2 Year 3 Year 4 Year 5 Total Flood Control 10,150 24,650 50,025 50,025 10,150 145,000 4% 11,025 26,775 54,338 54,338 11,025 157,500 5% 218,866 531,531 1,078,694 1,078,694 218,866 3,126,650 91% Total 240,041 582,956 1,183,057 1,183,057 240,041 3,429,150 100% Some 9% of the projects capital costs representing 6 projects with a capital cost of USD circa 300,000 are within the high and medium priority rankings, but 3 of these have a negative IRR. 11.11.7 Conclusions on the Ranking of all projects The purpose of ranking projects using comparative benefit numeraires is to assess scheme viability.

Some projects do not easily reflect monetised benefits but using the priority beneficiary data, reflecting the scale of non-monetised benefits, can allow legitimate reason to increase the project priority.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I It is clear that for rural roads periodic and annual maintenance costs are significant and in many projects, represent over 100% of capital costs ensuring low or heavily negative IRR’s. As GCF funding of the infrastructure projects is over 5 years and represents largely capital costs, any external funding must be matched with in-country financing. In ever more hostile climatic environments that continued improvement to climate-proofing infrastructure and periodically maintenance must be considered as well as routine maintenance.

The following table compares the percentage cost of whole life maintenance costs in relation to capital outlay. Some 55 projects (27 rural road projects) have whole life maintenance over 20 years greater than initial capital costs. 11.11.8 Next Steps This analysis has achieved the following:

• Defined the broad quantum of beneficiaries for: o Households and population o Irrigation Service Areas • Monetised these benefits through implementation of each project using economic surrogates: o Household Income o Crop Income o Damage saved (flood protection only) • Cash Flow streams of costs and benefits to estimate Internal Rates of Return for each of 130 projects • Ranked the projects by IRR value • Classified projects as High, Medium or Low priority based on IRR • Indicated where priority might be changed depending on scale of non-monetised beneficiaries and capital and maintenance cost profiles

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Project Maintenance Cost Total Total over 5 over 20 % of capital Yrs Yrs over 20 years A-RR-02 256000 1024000 1205% A-RR-01 240000 960000 1129% La-RR-04 139520 558080 1117% A-RR-10 242560 970240 511% A-RR-06 160000 640000 490% A-RR-11 227520 910080 467% A-RR-04 192000 768000 366% E-RR-03 320000 1280000 366% La-RR-05 168960 675840 338% V-RR-04 242560 970240 323% La-WS-08 21600 102600 293% V-WS-03 21600 102600 257% La-WS-11 21600 102600 257% A-RR-09 112960 451840 251% La-RR-06 112000 448000 224% L-RR-02 384000 1536000 219% L-RR-09 160000 640000 213% B-WS-06 21600 102600 205% B-WS-08 21600 102600 205% La-WS-09 21600 102600 205% V-RR-05 227520 910080 182% B-RR-03 87360 349440 175% La-WS-04 21600 102600 171% La-WS-06 21600 102600 171% La-WS-05 21600 102600 171% L-RR-07 192000 768000 171% La-WS-03 21600 102600 158% La-WS-07 21600 102600 158% B-WS-01 21600 102600 158% E-RR-01 256000 1024000 158% L-RR-03 256000 1024000 158% L-RR-05 256000 1024000 158% L-RR-04 240000 960000 148% B-IS-01 9000 36000 144% A-RR-07 108160 432640 140% B-WS-04 21600 102600 137% B-WS-03 21600 102600 137% A-WS-02 21600 102600 137% La-WS-10 21600 102600 137% A-RR-03 48000 192000 128% L-RR-01 48000 192000 128% L-RR-06 48000 192000 128% E-WS-01 21600 102600 121% E-WS-06 21600 102600 121% La-WS-02 21600 102600 121% B-WS-09 21600 102600 121% B-IS-02 9000 36000 120% E-RR-05 121920 411480 118% A-WS-03 21600 102600 114% A-RR-15 70080 280320 112% E-WS-04 21600 102600 108% L-WS-03 21600 102600 108% L-WS-01 21600 102600 108% E-RR-09 160000 640000 107% A-WS-01 21600 102600 103% V-RR-01 108160 432640 96% V-RR-03 112960 451840 90% L-RR-08 19200 76800 90% E-RR-06 64000 256000 85% A-RR-14 32000 128000 85% V-RR-02 93760 375040 83% V-WS-01 21600 102600 83% La-RR-02 51520 206080 82% E-WS-02 21600 102600 76% A-RR-13 32000 128000 73% E-RR-07 54720 218880 73% B-IS-06 9000 36000 72% V-WS-04 21600 102600 72% V-WS-06 21600 102600 68% V-WS-05 21600 102600 68% B-WS-02 21600 102600 68% L-WS-02 21600 102600 68% La-WS-01 21600 102600 68% B-WS-05 21600 102600 68% V-WS-02 21600 102600 68% B-RR-07 64000 256000 68% La-RR-03 16000 64000 64% La-IS-03 9000 36000 60% E-WS-03 21600 102600 59% B-WS-07 21600 102600 59% B-IS-03 9000 36000 55% B-IS-07 9000 36000 55% E-RR-02 80000 320000 53% E-WS-05 21600 102600 51% 231 La-FP-05 11850 47400 50% E-RR-04 30912 123648 50% V-IS-03 9000 36000 48% La-IS-06 9000 36000 48% A-RR-12 16000 64000 43% A-IS-01 9000 36000 42% A-RR-05 19200 76800 41% B-IS-04 9000 36000 40% La-IS-02 9000 36000 38% A-FP-03 30000 120000 38% A-FP-05 7500 30000 35% B-RR-06 12800 51200 34% B-FP-02 22800 91200 30% V-IS-02 9000 36000 30% V-IS-01 9000 36000 30% A-IS-03 9000 36000 30% A-IS-02 9000 36000 30% A-FP-04 15000 60000 30% B-IS-05 9000 36000 30% B-FP-03 16500 66000 29% V-FP-01 10500 42000 27% La-IS-05 9000 36000 27% E-FP-01 4860 19440 27% La-FP-01 7650 30600 27% La-FP-02 12900 51600 27% La-FP-03 13950 55800 27% V-FP-02 17250 69000 27% V-FP-03 7500 30000 27% L-IS-02 9000 36000 24% B-RR-02 24640 98560 23% E-IS-01 9000 36000 21% E-IS-02 9000 36000 21% E-RR-08 32000 128000 20% E-IS-04 9000 36000 19% La-IS-04 9000 36000 18% L-FP-03 10050 40200 16% B-RR-05 13760 55040 16% L-FP-02 7500 30000 15% A-FP-01 3000 12000 14% A-FP-02 1500 6000 12% L-FP-01 4500 18000 10% L-FP-05 4500 18000 10% La-IS-01 9000 36000 9% L-IS-01 9000 36000 8% L-FP-06 3000 12000 8% E-IS-03 9000 36000 7% Project Maintenance Cost Total Total over 5 over 20 % of capital Yrs Yrs over 20 years A-RR-02 256000 1024000 1205% A-RR-01 240000 960000 1129% La-RR-04 139520 558080 1117% A-RR-10 242560 970240 511% A-RR-06 160000 640000 490% A-RR-11 227520 910080 467% A-RR-04 192000 768000 366% E-RR-03 320000 1280000 366% La-RR-05 168960 675840 338% V-RR-04 242560 970240 323% La-WS-08 21600 102600 293% V-WS-03 21600 102600 257% La-WS-11 21600 102600 257% A-RR-09 112960 451840 251% La-RR-06 112000 448000 224% L-RR-02 384000 1536000 219% L-RR-09 160000 640000 213% B-WS-06 21600 102600 205% B-WS-08 21600 102600 205% La-WS-09 21600 102600 205% V-RR-05 227520 910080 182% B-RR-03 87360 349440 175% La-WS-04 21600 102600 171% La-WS-06 21600 102600 171% La-WS-05 21600 102600 171% L-RR-07 192000 768000 171% La-WS-03 21600 102600 158% La-WS-07 21600 102600 158% B-WS-01 21600 102600 158% E-RR-01 256000 1024000 158% L-RR-03 256000 1024000 158% L-RR-05 256000 1024000 158% L-RR-04 240000 960000 148% B-IS-01 9000 36000 144% A-RR-07 108160 432640 140% B-WS-04 21600 102600 137% B-WS-03 21600 102600 137% A-WS-02 21600 102600 137% La-WS-10 21600 102600 137% A-RR-03 48000 192000 128% L-RR-01 48000 192000 128% L-RR-06 48000 192000 128% E-WS-01 21600 102600 121% E-WS-06 21600 102600 121% La-WS-02 21600 102600 121% B-WS-09 21600 102600 121% B-IS-02 9000 36000 120% E-RR-05 121920 411480 118% A-WS-03 21600 102600 114% A-RR-15 70080 280320 112% E-WS-04 21600 102600 108% L-WS-03 21600 102600 108% L-WS-01 21600 102600 108% E-RR-09 160000 640000 107% A-WS-01 21600 102600 103% V-RR-01 108160 432640 96% V-RR-03 112960 451840 90% L-RR-08 19200 76800 90% E-RR-06 64000 256000 85% A-RR-14 32000 128000 85% V-RR-02 93760 375040 83% V-WS-01 21600 102600 83% La-RR-02 51520 206080 82% E-WS-02 21600 102600 76% A-RR-13 32000 128000 73% E-RR-07 54720 218880 73% B-IS-06 9000 36000 72% V-WS-04 21600 102600 72% V-WS-06 21600 102600 68% V-WS-05 21600 102600 68% B-WS-02 21600 102600 68% L-WS-02 21600 102600 68% La-WS-01 21600 102600 68% Annex II – Feasibility Study B-WS-05 21600 102600 68% V-WS-02 21600 102600 GREEN68% CLIMATE FUND FUNDING PROPOSAL B-RR-07 64000 256000 68% I La-RR-03 16000 64000 64% La-IS-03 9000 36000 60% E-WS-03 21600 102600 59% B-WS-07 21600 102600 59% B-IS-03 9000 36000 55% B-IS-07 9000 36000 55% E-RR-02 80000 320000 53% E-WS-05 21600 102600 51% La-FP-05 11850 47400 50% E-RR-04 30912 123648 50% V-IS-03 9000 36000 48% La-IS-06 9000 36000 48% A-RR-12 16000 64000 43% A-IS-01 9000 36000 42% A-RR-05 19200 76800 41% B-IS-04 9000 36000 40% La-IS-02 9000 36000 38% A-FP-03 30000 120000 38% A-FP-05 7500 30000 35% B-RR-06 12800 51200 34% B-FP-02 22800 91200 30% V-IS-02 9000 36000 30% V-IS-01 9000 36000 30% A-IS-03 9000 36000 30% A-IS-02 9000 36000 30% A-FP-04 15000 60000 30% B-IS-05 9000 36000 30% B-FP-03 16500 66000 29% V-FP-01 10500 42000 27% La-IS-05 9000 36000 27% E-FP-01 4860 19440 27% La-FP-01 7650 30600 27% La-FP-02 12900 51600 27% La-FP-03 13950 55800 27% V-FP-02 17250 69000 27% V-FP-03 7500 30000 27% L-IS-02 9000 36000 24% B-RR-02 24640 98560 23% E-IS-01 9000 36000 21% E-IS-02 9000 36000 21% E-RR-08 32000 128000 20% E-IS-04 9000 36000 19% La-IS-04 9000 36000 18% L-FP-03 10050 40200 16% B-RR-05 13760 55040 16% L-FP-02 7500 30000 15% A-FP-01 3000 12000 14% A-FP-02 1500 6000 12% L-FP-01 4500 18000 10% L-FP-05 4500 18000 10% La-IS-01 9000 36000 9% L-IS-01 9000 36000 8% L-FP-06 3000 12000 8% E-IS-03 9000 36000 7%

11.12 Agro-forestry and reforestation for catchment management and infrastructure climate proofing and protection44

11.12.1 Benefits to agro-forestry and reforestation in addressing land degradation A watershed is an area of land that drains into a common water body such as a river or lake and is also known as a basin or catchment. The ecosystem of a watershed is complex and depends on biotic and physical factors for its health and function. Human activities have a direct influence on the watershed ecosystem as they impact on the quality and quantity of surface water groundwater and other natural resources in the watershed. Upstream activities influence river flows, water quality, soil erosion and sedimentation downstream. When the biological and physical processes

44Main references for this section https://www.dole.gov.ph/files/Philippine%20Agribusiness%20Investment%20Opportunities%20by%20Department%2 0of%20Agriculture%20.pdf http://www.fao.org/fileadmin/templates/est/AAACP/pacific/FAO_AAACP_Paper_Series_No_10_1_.pdf http://www.bic.searca.org/news/2011/may1/phi/13.html http://kubanni.abu.edu.ng:8080/jspui/bitstream/123456789/7281/1/ECONOMIC%20ANALYSIS%20OF%20GUAVA% 20%28Psidiunguajava%29%20PRODUCTION%20AMONG%20SMALL%20HOLDER%20FARMERS%20IN%20SEL ECTED%20LOCAL%20GOVERNMENT%20AREAS%20OF%20KADUNA%20STATE%2C%20NIGERIA.pdf

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The main components of watershed management are resource conservation, crop production and alternate land-use systems. Watershed management must be integrated and address both water and the related land resources that affect or are affected by water. Watershed management includes floods and droughts, surface water and groundwater, water supply and water quality. Related land resources include streams, wetlands, forests, soil, fisheries, flora and fauna. The premise that “everything is connected to everything else” lies at the heart of watershed management. By understanding the natural functions of a watershed before change occurs, harmful impacts on the system can be identified so that prevention, remediation, or improvements can be incorporated into management plans. Watershed management is not so much about managing natural resources, but about managing human activity as it affects these resources. The drainage area of the river provides the natural boundary for managing and mitigating human and environmental interactions.

Agroforestry systems play an important role in conservation of natural resources, especially soil. Adoption of agroforestry practices enhances the productivity of resource poor small and marginal farmers. Agroforestry has both productive and service functions. Among the productive functions, fuel wood, fodder and fruit are the most important besides construction wood, gums, resins, medicines, fibres and a host of other economic base and greater food security. The service functions include shade, reduction in wind speed, control of erosion and maintenance and improvement of soil fertility. Agroforestry systems increase nutrients inputs through nitrogen fixing trees and nutrient uptake from deep soil horizons. They reduce nutrient leaching losses through tree root and mycorrhizal systems. Agroforestry systems recycle nutrients through decomposition of litter, pruning and root residues. Agroforestry is a medium and a combination of agricultural and forestry technologies to create integrated, diverse and productive land use systems (Garrett and Agus, 2000). While agroforests are typically less diverse than native forest, they do contain a significant number of plant and animal species. This diversity can, in time, provide ecological resilience and contribute to the maintenance of beneficial ecological functions. Similar to plantation forests, agroforests can help relieve some of the pressure to harvest native forests.

Agroforestry is a collective name for land-use systems and technologies where woody perennials (trees, shrubs, palms, bamboos, etc.) are deliberately used on the same land-management units as agricultural crops and/or animals, in some form of spatial arrangement or temporal sequence. In agroforestry systems, there are both ecological and economical interactions between the different components.

Hence, agroforestry normally involves two or more species of plants (or plants and animals), at least one of which is a woody perennial. An agroforestry system always has two or more outputs and the cycle of an agroforestry system is always more than one year. Even the simplest agroforestry system is more complex, ecologically (structurally and functionally) and economically, than a mono-cropping system.

11.12.2 Agroforestry and reforestation approach Agro-forestry and reforestation will be implemented in the catchments upstream of the infrastructure to reduce the soil erosion and landslide risks in these catchment, thus adding an additional layer of protection and lengthening the service life of the infrastructure.

The project will assist MAF in developing the agro-forestry and reforestation strategy and specific implementation procedures for the sub-catchments within which the infrastructure projects will be located. The strategy will include: • Using available hazard maps and detailed hazard mapping for identifying priority areas for Agroforestry and Reforestation intervention, specifically targeting areas that will compromise the infrastructure due to climate change related hazards;

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• Specific procedures on engaging families and CBOs; and • Using Key Result Areas to objectively measure project performance.

Three approaches will be taken and follows:

Family-Based Agroforestry Strategy The family-based approach is recommended for areas that are privately owned. The approaches will require direct and constant engagement with families or households. A total of 100 ha was earmarked under this category.

The recommended target sites for implementing this approach are in areas within a 100m buffer of the infrastructure. This will facilitate project implementation, monitoring and evaluation and the provision of support/assistance.

Community-Based Agroforestry Strategy For areas that are state-owned, the community-based approach is recommended. The project will engage with organized farmer or community groups or Community Based Organizations (CBOs). A total of 100 ha will also be earmarked under this category.

The recommended target sites for this approach are areas located in upstream section of the sub- catchments that are under the same problematic condition as mentioned above.

Reforestation Strategy For areas where Agroforestry is not suitable, reforestation will be the alternative approach.

11.12.3 Initial Area of Target Sites for Agroforestry Intervention Initial estimate of the number of households located in areas with the highest vulnerability to soil erosion in the 6 target municipalities is 23,412 and approximately 100ha. These areas are under the threat of land degradation and farming communities in these areas are likely to lose crop yields because of the combined effect of catchment degradation and climate change exacerbated hazard risks.

Agroforestry was identified as the best-proven approach to address this problem. Through agroforestry intervention, target beneficiaries will be incentivized and will be supported to implement climate resilient livelihoods that are conducive to resilient catchment management and climate risk reduction.

11.12.4 Socio-Economic Assessment and Livelihood Practices The figures in the discussion below represents the profile of potential family beneficiaries located within the buffer, based on the most recent census (2015) of Timor-Leste.

Potential beneficiaries in the Municipality of Aileu In the municipality of Aileu, the total population is 1,751 with 282 households. A small percentage (16%) of households are headed by a female. Almost half (46%) of the total population is female. Almost every household in Aileu rears and owns a small ruminant, 1 or 2 large ruminants, an average of 3 poultry and 1 or 2 pigs.

A large majority (93%) of the households in Aileu are engaged in maize production are cultivating root crops like cassava (79%) and sweet Potato (74%). A small fraction (12%) are engaged in rice production. Almost half are engaged in vegetable (44%) and beans (49%) production. Almost half (42%) of the households are also engaged in the production of temporary fruit bearing plants.

Around 36% are rearing fruit bearing trees and almost a quarter (21%) are also already engaged in Timber Production. A third (37%) are cultivating coffee and 24% are also in coconut farming.

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Potential beneficiaries in the Municipality of Baucau Baucau has 560 households with 2,540 members, half of whom are females. A small fraction (16%) of households are headed by a female.

In Baucau, every households’ rears and owns an average of 2 small ruminants, 1 or 2 large ruminants, an average of 4 to 5 poultry and 2 pigs. Most of the families in Baucau are into maize (79%), cassava (76%) and sweet potato (70%) farming. Almost half of them are cultivating rice (47%) and beans (42%). Almost half are also growing fruit bearing plants (48%). A small fraction (33%) are into vegetable farming. A large fraction (70%) of the households are in coconut farming More than half (54%) of the households are already engage in fruit bearing tree production and around 38% of the families are also into Tree production. A very small percentage (5%) is engage in coffee.

Potential beneficiaries in the Municipality of Ermera In Ermera, a total of 3,509 persons represents 595 households of which a small percentage (13%) are headed by female. Though more than half (52%) of the population are female. Ermera households rear and own an average of 1 small ruminant, 1 large ruminant, an average of 3 to 4 poultry and 2 pigs.

Households in Ermera are mostly engaged in sweet potato (72%), maize (71%), cassava (64%) production. More than half (51%) are engaged in vegetable farming and around a 33% are into beans. Almost half (49%) are also into coffee production. A very small fraction of the households is into coconut (17%) farming and rice (7%) cultivation. The percentage of those engage in permanent and temporary fruit bearing trees are almost the same, 30% and 33% respectively with a small fraction (14%) also that are into tree production.

Potential beneficiaries in the Municipality of Liquica There are 372 households with 2,184 members in the municipality of Liquica. Half of the populations are female and females head 11% of the households. In Liquica, every household rears and owns an average of 1 small ruminant and 1 large ruminant, an average of 5 to 6 poultry and 2 pigs.

A large majority of the households in Liquica are cultivating maize (84%) and cassava (80%). Most families are also engaged in beans (66%), vegetable (62%) and sweet potato (60%) production. A very small fraction (2%) is into rice. The households that are engaged in planting temporary fruit trees are quite high, around 67%. Coconut planters comprise 74% of the total households and half are growing coffee. A large fraction (66%) is into fruit bearing tree production and 37% are into tree farming.

Potential beneficiaries in the Municipality of Lautem In the municipality of Lautem, the total population is 3,532 with 643 households. A small percentage (19%) of the households are headed by a female. Almost half (49%) of the total population are females. Lautem households on the average rears and owns an average of 1 small ruminant and at least 4 large ruminants, an average of 9 poultry and 2 to 3 pigs.

Maize (77%) production is where most of the households are engaged in Lautem, followed by cassava (63%) and sweet potato (46%). A quarter are also into rice (23%), beans (26%) and fruit bearing (15%) plants. A small fraction is engaged in vegetable (15%) farming. A small fraction of the households is into timber (15%) and coffee (5%) production. Coconut growers account to 34% of the total households and more than quarter are into fruit bearing trees (27%) production.

Potential beneficiaries in the Municipality of Viqueque Viqueque has 551 households with 2,430 members and more than half (51%) of it are females. A small fraction (18%) of households are headed by a female.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I In Viqueque, almost every household rears and owns an average of 1 small ruminant and around 4 large ruminants, 6 poultry and 2 pigs.

In Viqueque, 60% are engage in cassava production followed by maize (59%) and sweet potato (54%). Almost half of the households are cultivating vegetables (49%), beans (49%) and rice (42%). A quarter is also engaged in planting fruit bearing plants (25%). More than half of the households are into coconut (55%) production. Coffee planters only account for 9%. Around 32% and 39% of the households are engaged in fruit bearing trees and timber production respectively.

11.12.5 Potential Agroforestry Species The general condition of the target sites suggest that Agroforestry species must be able to immediately address the following

• soil erosion and land degradation • improve gradually the geo-physical condition of the catchment • reduce incidence of burning (slash and burn farming) • promote the culture of planting and growing high value crops • provide short and long term yet sustainable economic benefits to project beneficiaries and • promote the creation of sustainable enterprise • ultimately reduce the impact of climate change on infrastructure.

The Agroforestry species selected must also be based on what the farmer wants and those that will warrant support from service providers and the government. The next consideration is if the species perfectly fits the Agroforestry design or configuration highly recommended to the target sites.

Based on the geomorphological condition of the target sites the proposed design of the Agroforestry intervention is a Agri-Silvicutural System (ASS). This design has three major components: Multi- Purpose Trees (MPTs), Cash-Crops (CCs) and Fruit Bearing Trees (FBTs).

The functions of the Agroforestry components are as follows: MPTs will be planted as hedgerows to address soil erosion and control water flow. The MPTs will also serve as local source of natural fertilizer, main ingredients of natural pesticides and insecticides and alternative fuel wood source. Leaves of MPTs are also excellent feed source for poultry and livestock.

CCs will be the immediate source of income of the project beneficiaries while waiting for the main crop (FBTs) to grow and become productive. The CCs will be cultivated along the alleys in between the hedgerows of MPTs. Any CCs that will thrive on the alleys can be grown if it will not lead to further land degradation. The project beneficiaries who will engage in agroforestry will also agree on the type of CCs they will produce simultaneously each planting season to increase the volume of production and facilitate transport and marketing of their produce.

FBTs are the main crop of the proposed Agroforestry intervention. The species were selected based on the most commonly available and widely grown species in the municipalities. The FBTs will also serve as a deterrent that will discourage the common practice of burning for land clearing prior to agricultural cultivation. The intervention will also serve as a precursor in the development of a culture of planting and caring for trees alike among the project stakeholders.

The list of potential agroforestry species in Timor-Leste is shown in Table 0-3.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I 11.12.6 Technical Feasibility of Introducing the Agroforestry Species MPTs Ai-gamal and Lamtoro (Leucaena leucocephala) are two species highly recommended to serve as MPTs for the Agroforestry Intervention. These species are widely and locally available in Timor- Leste. Farmers plant this species as live-fence, living-post for barbed-wire fence, and farm hedgerows for SWC measure and alley cropping. These species can grow in any type of soil. Ai- Gamal can thrive up to 1600 m elevation and Lamtoro up to a maximum of 2,100 m.

CCs Timor-Leste farmers are very innovative and can grow any crop even in thin-layered problematic soil. The selection of CCs that will be grown will depend of the agreement between and among farmers who will engage in the Agroforestry intervention because they are more familiar and knowledgeable of the condition of the target sites and are more experienced. They will also receive technical assistance to help them make decisions.

FBTs The list of FBTs in Table 0-3 also shows the site requirement for each species. This will be the principal basis in making the final selection.

11.12.7 Expected Yields Despite knowing that project beneficiaries will not immediately reap the full benefits from planting FBTs, Municipal key officials are still very optimistic and are fully convinced that Agroforestry will not only provide sustainable income but will also improve the economy of the municipality.

Though the recommended Agroforestry component main crop species or FBTs are already locally grown and native of Timor-Leste, a thorough documentation on their yield production has yet to be done. Table 0-3 shows the list recommended FBTs, the specific site requirements to achieve optimal production and their Return on Investment (ROI).

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Table 0-3: List of recommended FBTs, site requirement and return on investments (ROI)

11.12.8 Current livelihood support provided/received by target sites The MAF is still provides free seeds for basic farm commodities like rice and corn; land preparation assistance using hand-tractors, and technical assistance to farmers.

11.12.9 Outline of Potential Suite of Viable Agroforestry Businesses with high hazard reduction potential Eventually, once the main crop or the FBTs becomes productive there will be an excess supply that will lead to an artificial fluctuation in the market, lowering the cost of the raw products. Another factor to be considered is the short-shelf life of the fresh fruits. The project partners and the AFs must recognize this at the earlier stage and the recommend solutions are:

• AFs to enter into Supply Contracts to ensure their produce are no longer in their hands when the market fluctuates due to oversupply • Create new business enterprises to add-value to the crop like Fruit Processing Plants.

This condition is true also for the CCs.

11.12.10 Gender and Adaptation benefits Agroforestry is an intervention where farmers produce or grow different crops by combining and mixing them simultaneously or sequentially. Hence, every inch of the farm is utilized. The crops grown are complementing each other. Hedgerows protect the cash crops from erosion, provides a source of organic fertilizer and ingredient for natural pesticides. Growing FBTs or main crops will also benefit from the production and maintenance of CCs. MPTs can also protect the main crops if utilized as shade trees.

Family members, especially children and girls who are usually tasked to gather firewood need not to walk far and look for places to collect since the MPTs can already supply their requirement. The family may decide also not to free graze their livestock and poultry because they can use as animal feed the young leaves and small branches of MPTs and agricultural waste from their farm. Women will be more engaged in harvesting, cleaning, sorting and marketing fruits when the FBTs become productive. In short members of the family will share the responsibilities in tending the farm.

Based on the socio-economic profile of potential beneficiaries half of the family members are consisting of woman and almost a quarter are headed by them. Hence, the likelihood those women, young and adult, will also have a big role in running the farm as an enterprise.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I 11.12.11 Main barriers and Opportunities of Agroforestry-based livelihood activities A major element for successful Agroforestry-based enterprise is management. Management means the capacity of the farmer to effectively and efficiently make decisions and put those decisions into action. The various components of the Agroforestry farm have different and varying needs. The MPTs require less attention when they are already established - hedgerows only require periodic pruning. Some components require more attention like the CCs. It actually depends on the farmer if he decides to use mulch to minimize weeds or drip irrigation technology to eliminate manual watering. The FBTs on the other hand require much attention during the growing period but once established it requires less attention until it becomes productive where it require the farmers’ intervention to ensure that the fruits are of high quality.

The element of management in agroforestry will require farmers to conduct proper recording (physical and financial), scheduling and forecasting of his activities and documentation of successes and failures or best practices. As a manager, also, the farmer must look beyond his farm and plan for future expansion if feasible. The farmer also has to collaborate and coordinate with other agroforestry farmers for purposes of pooling the farm produce thereby facilitating transport and marketing, share his experiences, both negative and positive, and also learn from them. He has also to work genuinely work with service providers and earn the respect of others who are in the same enterprise.

Managing an Agroforestry allows the farmer and all members of the family the opportunity to experience also the benefits of working with nature where each farm element or component are complementing each other while producing goods and service and helping the local economy and at the same time making the infrastructure more resilient to climate change.

11.13 Delivery mechanism of Agroforestry Intervention (considering financial and sustainability options)

The Principal Actors of Agroforestry Intervention The implementation of the Agroforestry intervention will require the active participation and full engagement of front-line actors. These actors are the project beneficiaries or the Agroforestry Farmers (AFs), the local government units (Suco, Administrative Post and Municipal level), the Municipal Agricultural Offices (MAO) through the Municipal Suco Extension Workers (MSEW). During the project inception phase, these actors will convene and agree on their specific roles and responsibilities based on the different phases of the Agroforestry Intervention.

Phase 1. Capacity Building Sessions (CBS) Though there is a general assumption that most of the MSEW had already experienced supervising and managing agroforestry activities it is still important that they fully understood their specific tasks on agreed, well-understood, specifically defined measurable activities. The CBS cover the following topics:

1. Asexual Propagation Techniques for Fruit Trees; 2. Hands-on technical training on Agroforestry; 3. Farm Record Keeping for AFs; 4. Database management; 5. Operation of Unmanned Aerial Vehicles; 6. Basic Remote Sensing Analysis; and 7. Project Monitoring and Evaluation

Phase 2. Site Assessment and Planning (SAP) This phase involves a detailed assessment of the water catchment where the infrastructures are located. The SAP phase will also provide MSEW and the AFs the opportunity to become fully aware

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I of the present condition of the target Agroforestry sites. Individual maps of the proposed sites will be produced for the Agroforestry farm planning exercises to formulate detailed work plans.

Phase 3. Seedling Production (SP) The MSEWs will have a big role in supervising the management of the FBT community nurseries. They must make sure that there is ample supply of healthy and viable seedlings during the out- planting period. The number of seedlings to be produced will be based on the result of the SAP. To minimize seedling mortality, whenever feasible, community seedling nurseries intended to produce FBTs will be located and established near the target planting sites.

Phase 4. Land Preparation and Out-Planting (LPO) Land preparation will be in stages, based on the requirement of the component crops.

Stage 1. Hedgerow Component -MPTs Hedgerows will be established along specifically defined contour lines. Whichever is more convenient to the AFs, leveling tools such as (A-frame or Engineers hose water-level) will be used to mark the contour lines on the ground. The marked contour lines will be weeded and cultivated manually using appropriate farm tools and planted directly (direct sowing) with MPT seeds. It is very important to do this activity before the end of rainy season. This will allow the MPTs to grow and established itself even during the dry season and established enough to protect the CCs.

The proposed Agroforestry Intervention is recommending the use of two locally available species - Ai-Gamal and Lamtoro. These species are not only fast-growing but they can also tolerate almost any kind of soil. These MPTs can be combined to create a hedgerow and tree line planting configuration. The space between hedgerows will depend on the slope of the planting site based on what is recommended as a result of the SAP.

Stage 2. Companion Crops Component - Cash crops Cultivation of CCs will commence when the MPT hedgerows have already fully established and are ready for pruning. The AFs will recognize at this early stage that addressing the problem of soil erosion is one of the major objectives of the Agroforestry intervention.

Land preparation will depend on the type of CCs that AFs had agreed to plant simultaneously. The AFs might choose to prepare plant beds or rows and hills. If the planting configuration will not lead to soil degradation and uncontrolled overland flow of water, any planting configuration is acceptable.

Stage 3. Main Crops Component - FBTs Planting holes will be prepared based on the hole-size requirement and recommended spacing of FBTs. Small branches/stakes of the MPTs will be planted near each planting hole. These stakes will have three specific purposes: First, it will serve as guide to the AFs during the out planting of FBTs; Second, it will serve as a warning or precaution that there is an FBT planted and growing beside it; and Third, when the MPTs starts to grow it will serve as the nurse or shade tree of the FBT. When the FBTs are already established the MPTs should be removed to avoid competition from sunlight and nutrient from the soil.

To minimize the need for manual watering, out-planting of FBTs will be scheduled during the onset of the rainy season and likewise in order to avoid heat stress and minimize mortality, out- planting activities has to be done either early in the morning or late in the afternoon. The MSEW needs to closely supervise and monitor the out-planting activities of the FBTs to ensure that AFs are using the recommended and most appropriate handling and planting techniques.

Phase 5. Monitoring and Reporting (MR) Monitoring is a crucial phase and must be implemented based on agreed targets to objectively record and measure the performance of the Agroforestry intervention. The result of monitoring

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I activities will not only serve as a feedback tool but also as basis in making immediate corrective measures, whenever necessary.

Project monitoring will be the basic task of the MSEW. They are expected to monitor and visit the Agroforestry farms and engage with the AFs at least once a week. They will prepare and a consolidated monthly, bi-annual, and annual report of their monitoring activities including a detailed write-up of their observations, problems and issues encountered and TAs provided to the AFs.

There are three general monitoring activities that need to be accomplished throughout the duration of the project.

1. Monitoring of the Economic Returns of the Agroforestry Intervention AFs will also be undergoing a training course on basic Farm Record Keeping and the MSEW ensure that AFs are using this tool. The farm records will include all related cost and return figures. The consolidated information gathered from farm records will then be useful during the project-end year economic valuation.

2. Monitoring of the Physical Performance of the Agroforestry Intervention The Agroforestry Intervention prime goal is to use it as a sustainable mitigating measure to protect the infrastructure from Climate Change related hazards such as erosion and landslide. To directly measure if this goal was achieved is to observe the improvement of ground surface ecosystem of the water catchment. Counting the number of trees that had survived and measuring the lines of hedgerows established is possible, however to observe overall physical changes an aerial survey is more appropriate. To do this, the project will make use of UAVs. The comparison of physical ground improvements due to the Agroforestry intervention will be done using before and after aerial images.

3. Monitoring of the Effectiveness of the Agroforestry Intervention in Controlling Soil Erosion To measure if the Agroforestry intervention is successful in minimizing soil-erosion, sediment-traps will be laid-out in strategic locations along. The MSEW and the AFs will visit the traps and record their observation after each major rain event.

11.14 Detailed set of activities for Agroforestry Social Business development

To develop Agroforestry as a genuine and economic and social business enterprise, it must undergo several stages of official recognition. These steps will recognize the AFs official ownership of the farm and its produce and access financial support readily from financial institutions. • Farmer Registration • Farm Registration • Product Registration (if the farmers decide to go purely organic) • Tree Registration and Certification

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I 11.15 Estimated Project Cost of the Agroforestry and reforestation Intervention45

Table 0-4: Cost Estimate per Hectare of Agroforestry Intervention

Family-based agro-forestry cost – $989,900 USD Community-based agro-forestry – $989,900 USD

Table 0-5: Cost Estimate per Hectare of Reforestation

Reforestation Cost - $886,000 USD

Development of MAF Agro-forestry strategy – $500,000 USD

Total Cost of Agro-forestry and reforestation intervention – $3,365,800 USD

45 General Assumptions: • The cost of per seedlings includes all the inputs (materials, seeds, labor, administrative cost) • The cost of seeds includes labor cost in incurred in collection, cleaning, sorting and packaging.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I 12. KNOWLEDGE MANAGEMENT, LEARNING AND STRATEGIC COMMUNICATION

12.1 Introduction

The knowledge management (KM) of the project will have the following key aims:

1. To ensure access to data and information generated by the project as well as long-term access to data on which stakeholders’ essential institutional functions rely and/or data and information that can be used for evidence for policy and practice advice (connecting people to information and knowledge) 2. Connect key stakeholder groups, practitioners and experts to ensure that key learning and experience is shared within and across sectors (connecting people to people) 3. Ensure staff in the stakeholder institutions know about effective and relevant KM techniques so that knowledge is shared, captured and retained by the institutions and shared within and across the sector (institutional KM improvement) 4. By developing and promoting KM as a tool for continuous and sustainable improvement and ensuring that KM tools generaterd by the project will be systematically used and maintained within the stakeholder institutions (Developing and embedding KM tools and practices).

At the community level the project will seek public participation and community support in the design and implementation of all aspects of the project. Co-design and engagement of communities will be undertaken through activities 1.2 (socio-economic surveys), which will involve the introduction of methods and tools for systematically collecting damages and losses data at all levels central, municipality and community level to include 'crowd sourcing and public participatory’ approaches to reporting damages and impacts of flooding. In addition, these socio- economic survey methods will be conducted alongside the awareness raising and capacity building of communities (see Engagement plan) which will enable full participation of communities in the design and implementation phases of all project activities.

Under Component 2 the planning of infrastructure works (2.2) will engage stakeholders and agro-forestry implementation (2.3) will rely on and engage communities and will be led by grass root organizations\NGOs with communities involved in planning and design/implementation of agro-forestry.

12.2 Connecting people to information and knowledge

New work should always build on the foundation of previous knowledge. New knowledge gained on the project will be captured and stored appropriately for others to access and learn from. The following series of tools and techniques will be employed to enable people to find information and knowledge more effectively throughout the project.

Tools and Description Purpose Actions techniques

Case Study Narrative Recording of Share experiences At least 20 case the Project’s progress with others, studies will be and outcomes. seeking generated per year of comments/consulta the project tion, advocacy

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Rapid Evidence A systematic review of An evidence Project feasibility review research and other baseline to enable studies will form the evidence producing project activities to project baseline which overview of the build on what has will be updated knowledge base in a gone before throughout the project particular area as it progresses. Knowledge Banks Repositories of stored Mass collection of The project will (web databases) knowledge accumulated develop a knowledge (research/evidence/best knowledge in a and data management practice), captured specific area website for all project, through various tools readily available to stakeholder and and techniques, and stakeholder beneficiary staff shared via websites and toolkits

Case Studies Cased studies will be written on all key aspects of the project and could be generated from technical reports but made appropriate for a number of different audiences. Hence technically detailed studies will be summarised and made appropriate for beneficiaries, the media and other types of audiences for the purpose of sharing experience, for soliciting comment/feedback and for advocacy purposes. Cased studies will have a clear structure that brings out key qualitative and quantitative information from the project and will be published with a broad audience in mind. The project will aim to have at least 20 case studies per year of the project.

To facilitate the generation of case studies in a systematic and consistent manner, project and programme teams will be asked to capture and record their learning and best practice in photos, videos and reports, so that others can benefit. A structured case study format will be used to make information accessible to the reader. Case studies will be published on the UNDP website as well as the project portal to be developed (see Knowledge banks below).

Evidence Review A rapid evidence review (RER) is a way of reviewing research and evidence on a particular issue. It looks at what has been done in a particular area and records the main outcomes. Evidence reviews can be run in several ways. Some are more exhaustive in their execution and ambitious in their scope. A fully-developed review will scan available literature as comprehensively as possible, using electronic databases and comprehensive sourcing. The RER provides a quicker but still useful way of gathering and consolidating knowledge. It is a useful building block from which to start work on a new topic but should not be considered a definitive review, but rather suitable as a starting point for more indepth review, or cursory information required to start a more indepth review. Any new piece of work is likely to draw on what has already been done by others in the sector. An RER ensures that you take account of this work before starting a project. This avoids duplication of effort and gives a foundation on which to build.

The project feasibility studies and all supporting material gathered during project development will form the project baseline which will be updated throughout the project as it progresses thus ensuring that the evidence baseline for all project activities is always up-to-date.

Knowledge banks Knowledge Banks are online services and resources which hold information, learning and support and also act as a project data manage and repository database. They are typically used to showcase the work of the project and provide signposts to documents, articles and toolkits.

Project Data Management and GIS

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I Catchment scale hazard and risk management is inevitably a multidisciplinary undertaking which will use and generate large numbers of spatial and non-spatial datasets. Under Output 1 the project will facilitate the dissemination and sharing of common and definitive climate risk information across by all sectors to embed climate risk considerations into their function, through the Climate Change and Biodiversity Centre (CCCB). It will establish an information platform which will consist of a national e-Library, databases, information systems and knowledge portal (web knowledge portal to increase awareness, provide interactive hazard maps, with integration with social media and possible mobile application to increase community engagement and allow two-way flow of information. It will be an integral part of the NSDI currently being developed for Timor Leste and provide the information access and sharing platform for geospatial information on hazards. This will contribute to a more effective and climate risk-informed management of all sectors.

The system will represent a major shift in how government departments currently work and will need to be supported by the introduction of appropriate data sharing protocols and importantly by extensive training and capacity building to ensure sustainability.

The data repository will provide a structured environment to enforce data integrity and support data auditing, versioning and data quality. Audit trails, as well as structured and categorised schemas, will make data collation, manipulation and analysis more manageable. The establishment of a structured GIS data repository is envisaged to provide the following advantages: • Provides a ‘single source of truth’ to provide consistency and transparency in the use of datasets used by everyone working on the project. • Enables a data security model to be implemented to constrain user permissions to appropriate levels. • Reduced duplication and redundancy of data. • Provides a mechanism to enforce data quality and consistency in accordance with standards. • Provides a structured environment to support the effective discovery of data through web- based portal services. • Enables datasets to be performance tuned for use in GIS desktop and web systems. • Provides a comprehensive trusted source of data to permit the effective investigation of spatial relationships between different datasets, which will add a further dimension to the analysis.

The spatial data repository will include and enforce metadata. It enhances the value of data, providing business critical information regarding the data’s currency and quality, which can aid in identifying gaps in data, in addition to providing a useful mechanism to support discovery services. This data repository will perform a crucial role in efficiently managing data and metadata during the project and represents a significant project deliverable. The scale, comprehensiveness and structure of the database will be dictated by the quality and quantity of the data identified in the early stages of the project. It will however also need to be cognizant of future datasets and processes that will be included, and therefore will be scalable with consideration included at the design phase. This knowledge management system will be based on the EU’s INSPIRE directive which provides a clear framework on the establishment of the SDI and its constituting services.

In addition, the data management system developed to provide a single point of ‘truth’ with respect to datasets to be used and generated by the project, it will also provide a portal for document management and will provide access for project staff and stakeholders to all relevant documents.

12.3 Connecting People to People

The following series of tools and techniques describe how knowledge management will enable people to connect to people more effectively.

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Tools and Description Purpose Actions techniques

Community of A group people who Learning from The project will set up a Practice share a common Shared number of technical (CoP/Knowledge interest working experiences, working groups, network/professi together over an publishing best interagency working onal network) extended period to practice/position groups as well as explore ways of papers regional working groups working in a specific to enable CoP people area of knowledge to interact and share experiences

Peer Assist Gaining input and First hand The project will engage insight from outside knowledge a range of local and experts to reuse and transfer, access international experts reapply existing the institutional who will provide knowledge and knowledge base technical assistance to experience the project. For long- term peer assist, the project will help establish relationships between institutions and local as well as international universities and research centres Knowledge café A group of people Informal learning This will be achieved having an open, through dialogue. through the meetings of creative conversation the technical working in an informal groups and through bi- environment on a lateral meetings topic of mutual between individual interest stakeholder organisations Knowledge Allows matching of a Starts connection This will be provided by marketplace knowledge of people to project experts who will requirement with people, people to be identifiable by their someone with document and area of expertise and expertise documents to will provide support the people project and stakeholders. In the long-term, a ‘directory’ of experts can be developed to fill this need.

Community of Practice (CoP) A CoP provides an environment (virtual and or face-to-face) that connects people and encourages the development and sharing of new ideas and strategies. This environment supports faster problem solving, cuts down on duplication of effort, and provides potentially unlimited access to expertise. Technology now allows people to network, share and develop practice entirely online.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I Virtual communities overcome the challenges of geographical boundaries. They encourage the flow of knowledge across local government and enable sustainable self-improvement.

The project will set up a number of technical working groups, interagency working groups (through the CCCB) as well as regional working groups to enable CoP people to interact and share experiences. In addition to face-to-face meetings, the project web portal will be configured to enable online cross-organisational working and sharing of ideas.

The project cross-sectoral working group will help to outline and examine the current policy framework relating to hazard management and which could best elaborate current practice and deficiencies with respect to climate risk management and DRR, and the inclusion of climate change considerations climate proofing infrastructure. The strengthening of the cross-sectoral working group, which will be comprised of representatives from all relevant ministries and institutions, is an essential first step to ensure inclusion and consultation from the beginning and throughout the process. This will enable an active participatory approach (experts from relevant line-ministries relevant agencies) and will ensure buy-in. It is envisaged that a number of technical working groups will be required, based on technical area as well as geographical relevance.

Peer Assist The project will engage a range of local and international experts who will provide technical assistance throughout the project. For long-term peer assist, the project will help establish relationships between institutions and local as well as international universities and research centres.

Technical capacity has been identified as one of the main barriers to implementation of the policy and practice of climate resilient rural infrastructure. The project will ensure that the necessary technical assistance is provided to address this and that the long-term capacity development is assured through formal learning, and also through increased access to experts e.g. through the establishment of relationships between institutions and local as well as international universities and research centres.

Knowledge café The knowledge café approach will be used when developing workshops for the techncial and cross- sectoral working groups as follows: Preparation for a knowledge café • appoint a facilitator – someone who can encourage participation. • identify the topic for discussion (e.g. to discuss/consult on a project preliminary output). • provide an informal/relaxed setting.

During a knowledge café • The facilitator should introduce the knowledge café concept, any codes of conduct, and finally pose the question. • Participants should arrange themselves into groups to discuss the question. • Each participant in turn shares their knowledge and experience without interruption, giving everyone an opportunity to talk. Alternatively, a ‘talking-stick’ can ensure only the person holding the stick can speak, thus avoiding the discussion becoming dominated by one or a few speakers. • After each participant has shared, the group continues the discussion together. • The groups should eventually reconvene to exchange ideas and findings – these could be captured electronically or on paper.

Knowledge Marketplace

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I Knowledge marketplace identifies what people know and what they need to know on a particular subject, then connects them appropriately. The knowledge marketplace can be facilitated online, via email or face-to-face.

It can be used in many situations and is particularly useful when delegating roles and responsibilities within a new project team. Success depends on the willingness of participants to both contribute and benefit in equal measure from exchanging knowledge. It is highly dependent on the degree of trust between individuals. Given the scale of the project and national remit, it will be important to develop and use the knowledge market place approach to ensure that the right expertise and knowledge is not missed by any part of the project team stakeholder or beneficiaries. By placing the knowledge marketplace online (and open to beneficiaries as well) it would also identify local experts that would otherwise go unnoticed.

12.4 Institutional KM improvement

Summarising lessons learned and experiences and sharing them with others can help build and retain knowledge. The following series of tools and techniques describe how knowledge management can enable improvement through impact assessments, evaluations and people management.

Tools and Description Purpose Actions techniques

Gone well/not Quick debrief at the Tactic knowledge All significant project gone well end of an event/activity capture and feedback events/activities will be concentrating on good about effectiveness of subject to a debrief to points and items for the event capture good/bad improvement points and lessons learned

After Action Quick discussion at Tactic knowledge All significant project review (AAR) the end of key stages capture of lessons events/activities will formative of an activity reflecting learnt e.g. noted include formal minutes evaluation on the current position minutes of project which will be made and future actions meetings available on project portal

Retrospective A formal process to Capture lessons A formal project review evaluate the learned for future lessons learned (summarise completion of the activities. Publish on document will be evaluation) event or activity to internet or intranet available for all project capture lessons staff to complete earned (managed by PM) online

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Knowledge Staff leaving should Build All project staff will Exchange exchange unique institutional/project have as final knowledge to allow memory deliverable a summary others to capture it. report to include knowledge transfer information and other lessons learned

12.5 Developing and embedding KM tools and practices

As far as possible, all KM tools will be provided as project deliverables and, importantly, through the project it is hoped that by using these tools with the stakeholders, the KM practices will be embedded with their organisations in the future.

In addition to the above the project provides many opportunities, for formal learning, awareness raising and capacity building cut across almost all outputs and activities. These sets of measures will catalyse longer-term learning and short-term professional training/retraining programs targeting all stakeholders, including vulnerable communities, local governments, universities and relevant authorities.

All knowledge products, generated within the project including technical reports, methodological guidelines, regulatory and policy, planning and outreach materials will be available on-line, and all project knowledge products and documents will be collected and archived on e-library on multi- hazard disaster risk management.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I 13. PROJECT IMPACT EVALUATION

The project impact will be assessed using the following 6 domains of impact: • Impact on physical and financial assets • Impact on Social Capital, Empowerment and change of behaviour • Impact on Food Security • Environmental Impact • Impact on Institutions, policies, and the regulatory framework • Impact on Gender

To examine the impacts of the project on rural communities, the review will examine whether the interventions implemented by the project have enhanced the value and derived benefits from existing community assets such as infrastructure, land, water, livestock and livelihoods. Impact on income generation and improvement in livelihoods will be key direct benefits to be examined while improved skill or health, education, and socio-economic conditions will be key indirect benefits to be examined. Impact on increased capacity of local communities to exploit potential economic opportunities and to develop stronger link with the markets and external partners, through the risk reduction and adaptation interventions provided by the project, will be examined. Efforts to strengthen local level organizations in the implementation of similar projects in the future will be a key impact as this will reflect whether the project has built local capacity to implement and use these new climate resilient measures in the long-term. The project also envisages measuring behavioural change in the beneficiary communities.

Likely contribution of the project to food security will be examined. Key elements of food security is availability (production and trade), access (income, markets and prices) and stability (storage and other marketing arrangement at household and local level.

Environmental degradation is very often a manifestation of poverty and the struggle for survival by the rural poor, and contributes to non-resilience to climate change and increased risk from climate- related disasters. The extent to which the project contributes to rehabilitation of the environment (particularly of the agricultural resource base and watershed management) in areas currently affected by land degradation and at high risk of hazards, is strongly associated with poverty impact. This domain concentrates on the local level environmental impacts of the project, as well as any environmental consequences of the project. It is also concerned especially with those environmental aspects, which are under the control of, or are influenced by, the rural communities. Environmental impacts may be negative as well as positive intended or unintended and all of these will be examined.

Existing institutions, policies and regulatory frameworks significantly influence the lives of the rural poor. Supporting the capabilities of existing national, and especially local public institutions in servicing the rural communities and reorienting the existing policies of institutions in favour of the poor is an increasingly expected result of development projects and is an expected outcome of this project. This encompasses the change brought about in sectoral and national policies affecting the rural communities and their exposure to hydrometeorological hazards. In addition, the degree to which the project impacts local-level decision making capacity, is also a relevant consideration and important to this project. In addition, traditional and social practices may also serve to restrict the equitable access to benefits, for example social restrictions on women’s activities, traditional allocation by gender of rural tasks and income from different crops and livestock, etc. The review will examine the extent to which a contribution has been made to improving the national, and particularly local institutions to implement and maintain, climate resilient infrastructure which affects the lives and livelihoods of rural communities.

Approach To monitor and measure the changes brought by the project, impact assignments will be designed to assist the project team to collect baseline information/data, final survey to gain insights into

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I developmental and adaptive impact of the interventions that will be carried out during the project. For this purpose, before any interventions take place, a robust baseline survey needs to be administered. During the project, it is expected follow-up surveys and final large survey will also be carried out at end of project.

The impact of the project will be assessed by undertaking the following: 1) A household survey targeting beneficiary households at least two times (baseline and final) during the project implementation; 2) Analysis of the survey data; 3) Follow-up survey which will be used by project staff; and 4) Training of project staff on the follow-up survey methodology.

The impact indicators will include but should not be limited to: (i) extent to which the project interventions such as improved DRM capacities and improved access to and use of climate risk information, have reduced exposure to hazards (ii) changes in income from agriculture and related activities (changes in income should take into account the level of home consumption); (iii) yield from agricultural production for key produce; (iv) yield of home gardens; (y) migration for seasonal work; (vi) farm land left fallowed; (vii) freshwater availability for household use; (viii) change in family savings.

As part of the community survey a section will be included to monitor community involvement in the design and implementation of community-based agro-forestry schemes – tracking participation in paid work opportunities, as well as ongoing involvement in resilience building through in-kind commitment of time to maintenance and enforcement activities e.g. the community-based agroforestry to be implemented on state land. This will include respondents’ estimation of approximate number of hours per month spent on local resilience building actions. Finally, monitoring over the implementation and results of site specific structural protection measures at 130 sites will be ensured as outlined in the ESMF.

Since the project impacts from many of the interventions are likely to be realized close to the culmination of, and even after, project implementation, the impact evaluation methodology and tools will be embedded within responsible agencies to monitor in the long-term. This will ensure regular surveying of the key impact and development indicators required for long-term assessment of project results. Project monitoring and evaluation will be undertaken in compliance with the UNDP POPP, the UNDP Evaluation Policy.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I 14. CONCLUSION

Timor Leste is among the least developed countries in the world, and gained its independence only in 2002 after years of conflict. This post-conflict society has a fast-growing population, which is largely rural-based, heavily dependent upon subsistence agriculture, and facing large deficits in rural infrastructure needed to catalyse economic development. Timor Leste is geographically highly exposed to climate-induced natural hazards, including floods, landslide, droughts, erosion, and strong winds, all of which are set to worsen under climate change. The highest impact of climate change will be to those least able to cope and living in already deprived rural areas.

Deficits in rural infrastructure are being addressed, albeit at a slow pace, not in keeping with desire of Timorese people to be economically stable and self-sufficient. Furthermore, in addressing the infrastructure deficit, government is not systematically taking account of climate risks and therefore not building climate resilient infrastructure that will be sustainable in the long-term. A lack of capacity - financial and technical at both central government and local government level are part of the reason. Lack of access to climate risk information is another, and lack of government funding for climate resilient rural infrastructure are also factors. Coupled with this, there is a need for livelihood generation in rural areas which are characterised by limited participation of income generating economic activities, and environmentally risky land use activities such as slash and burn farming, deforestation for access to firewood, farming on inappropriate slopes and over-exploiting soils with poor fertility.

The proposed project is seeking to address these barriers through two main outputs:

1) Strengthening of policies and institutions to enable climate resilient small-scale rural infrastructure development and climate risk reduction in the particularly vulnerable communities. 2) Direct investment in climate resilient small-scale rural infrastructure deployed to benefit 175,840 people across six priority districts.

Based on the multi-dimensional and complex geographic, socio-economic, institutional, and political factors outlined, this two-pronged approach is considered to be the most appropriate to address the huge challenges facing Timor Leste and to provide meaning full and concrete improvements to the lives of in rural communities facing climate risks.

The Government of TL fully recognises the need to adopt a holistic climate resilient approach to developing rural infrastructure and a proactive approach to addressing climate-induced hazards and related disasters. This GCF project has been designed to remove the barriers that currently prevent the implementation climate resilient infrastructure and effective disaster risk management through the project outputs and activities. The project has been developed in close collaboration with government and included extensive stakeholder engagement (See Annex 7).

The project supports adaptation to climate change across all sectors and specifically, the integration of climate change considerations into the development of climate resilient infrastructure. It is embedding such climate change considerations within the current infrastructure planning framework and strengthening the DRM capacity at the same time. The proposed project is technically viable as it consolidates field proven methods and practices and implements at a scale that is important for transformation of small scale rural infrastructure development in the target municipalities, while providing a strong basis for national scaling up and replication.

A key foundational activity of the project will be the strengthening of the climate risk knowledge base for the whole of Timor Leste for the major hazards. This will be done through the introduction of modern assessment, modelling and mapping techniques and tools not currently available in Timor Leste. Climate risk information hazard, risk and vulnerability information currently available

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I for Timor Leste is of a broad-brushed nature and does not provide the level of detail required for making risk informed decision, or for designing climate resilient infrastructure. The project will introduce modern and proven modelling approaches in line with international best practice and will utilize the best available physical, hydrometeorological and socio-economic data available for Timor Leste. Modern modelling software will be introduced for all hazards and a review of data availability for Timor Leste confirmed that the methods are appropriate for the data available.

Technical capacities related to hazard identification, risk identification and assessment, prevention, risk reduction, risk mitigation, risk transfer, preparedness, climate risk management and climate change adaptation are rather weak across institutions and governance levels. In certain sectors, there are insufficient human resources; in many cases, incentives for specialized education or training are lacking, and qualified staff turnover is high. As part of the SSRI project, an assessment was made of the existing gaps in institutional capacity for all aspects of hazard and risk management in Timor Leste. A capacity development plan will be specified based on the needs identified.

The project is also introducing modern approaches to assessment of economic damages (through socio-economic risk modelling of the underlying hazard impacts), and damage and loss assessment and monitoring technologies. In particular, the project will introduce drone technology to enhance the identification disaster impact and speed up mobilization of response to reduce causalities. The use of UAV’s will assist in early pin pointing of crisis points and avoid abortive work and the frustration of blocked access in the immediate after math of a disaster. There are concerns at National Disaster Operations Center (NDOC) regarding the convolution of the rapid assessment process which can take up to 2 weeks and the recovery package can take “many months”. Reasons given are remoteness, distance, inadequate communication systems, though smart phones are being increasingly used to phone in data. The biggest threats were felt to be poor communication services and poor sharing of data with double entry and inadequate auditing to filter out misleading or poor data. There are 442 sucos who would benefit from a real-time validation process with a robust quality assurance system. The support of Drone systems in disaster management was fully recognised as a support system. The use of drones or unmanned aerial vehicles (UAV), can significantly enhance risk and damage assessments, and revolutionize disaster preparation, response and management capacities in the future. The deployment of drones will be aimed at supporting the government’s response planning activities and strengthen the preparation for and response to disasters including the assessment of physical damages for post disaster needs assessment. It will also help in making better-informed decisions in protecting their livelihoods.

Data generated from the drone flights will also be useful in the long-term monitoring of hazards (fast and flow on-set hazards) which will feed into the continued updating of hazard and risk information used in climate risk management, design of climate resilient infrastructure, and environmental monitoring. Drones equipped with photogrammetric and navigation equipment will be used to allow rapid and reliable assessments of important hazard parameters. In addition, a Risk Management Application (DRMApp) will be developed to support the DRM operations.

As part of the feasibility assessment, following the risk based analysis of the extent of hydro metrological hazards (Floods, landslides, erosion and drought) in all Municipalities and watersheds in Timor Leste, the 6 most vulnerable target municipalities were selected and structural measures were identified in each to create resilience to four components of public infrastructure: Rural Roads, Water Supply, Irrigation Systems and Flood Protection. In addition, areas of high risk land erosion were identified with a view to introduction of agro-forestry options to minimise the effects of erosion on agricultural land. Some 144 projects were identified initially by UNDP SSRI (Small Scale Rural Infrastructure) team in the 6 Municipalities. Which was reduced to 130 due to the early identification of unviable projects.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I The 130 projects were subject to Cost Benefit analysis. Capital, operational (where appropriate) and maintenance costs were provided for each project, and the Internal Rate of Return calculated based on monetised benefits relating to the avoidance of economic losses to communities (Sucos) assuming no resilience measures were put in place (The Do Nothing option). Clearly these resilience measures can never prevent all losses associated with worsening hydro-meteorological hazards but, at this broad analysis of feasibility, it is assumed that residual losses after completion of the projects are not included.

In addition to the climate proofing measure that will be implemented for all types of infrastructure, the project is also implementing an eco-system based approach to catchment management for the subject catchments, to enhance the protection of the infrastructure within these catchments.

Agro-forestry and reforestation will be implemented in the catchments upstream of the infrastructure to reduce the soil erosion and landslide risks in these catchment, thus adding an additional layer of protection and lengthening the service life of the infrastructure.

In summary, with GCF funding the lack of climate risk information for CCA and DR will be addressed, the sectoral policy and legislative framework will be strengthened by embedding climate change considerations into all sectors that impact the resilience of infrastructure, CCA and DRR, and institutional capacity at central and local level will be built to enable long-term use of climate risk information, methods and tools in the planning and investment in rural infrastructure, and in the development of CCA and DRR activities. Furthermore, livelihood pressures that lead to land degradation will be addressed through the introduction of climate smart agro-forestry and reforestation in catchments within which infrastructure will be developed thus providing essential over-arching eco-system based protection for the infrastructure, reduced maintenance requirements in the long-term and reduced exposure of communities and their assets to climate induced hazards. The preferred solution provides the clear link between activities that are seeking to address CCA and DRR (as per the new CC and DRM laws) and the development of rural infrastructure (as per the SDP). The preferred solution will bring about transformative change in the way in which Timor-Leste plans and develops rural infrastructure in the future and will safeguard infrastructure and livelihoods.

The project has particularly strong emphasis on knowledge generation, learning and information sharing/dissemination. First, it is enhancing the capacity of the MCIE to coordinate and disseminate climate risk information across all sectors via the climate change platform and associated climate risk information management systems. It is developing hazard and risk assessment modelling and mapping tools and generating definitive hazard maps for all major climate-induced hazards for the whole country to be used across all sectors in climate risk management and training MCIE and MSS staff in use and maintenance of these new tools and technologies. It is developing damages and losses accounting methods, tools, and technologies as well as asset inventory and management databases and providing a series of training in data collection and treatment; methods of risk and vulnerability assessment and economic valuation to the mandated institutions. Targeted

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I trainings in the climate proofing engineering are all part of the knowledge and skill development. Hence, relevant institutions at national and sub-national level will be strengthened to embed such knowledge and skills for continuity of the learning process.

Importantly, through the development of manuals and guidelines on climate proofing of infrastructure for each category of infrastructure, and training municipal staff in the application of climate proofing methods the project is embedding climate proofing approaches into infrastructure implementation and long-term management.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I ANNEX 1- DEVELOPMENT INDICATORS FOR TIMOR LESTE

Table 0-1: Main Human Development Indicators for Timor-Leste (UN, 2015)

Index Value Population/Life Expectancy/Mortality Population, total (millions) 1.2 Population, urban (%) 29.5 Life expectancy at birth 68.2 Adult mortality rate, female (per 1,000 people) 164 Adult mortality rate, male (per 1,000 people) 208 Infant mortality rate (per 1,000 live births) 46.2 Under-five mortality rate (per 1,000 live births) 54.6 Education Expected Years of Schooling (years) 11.7 Adult literacy rate (% ages 15 and older) 58.3 Gross enrolment ratio, primary (% of primary school-age population) 125 Gross enrolment ratio, secondary (% of secondary school-age population) 56.6 Gross enrolment ratio, tertiary (% of tertiary school-age population) 17.7 Mean years of schooling (years) 4.4 GDP Gross national income (GNI) per capita (2011 PPP$) 5,362.50 Consumer price index (2010=100) 141.1 Domestic credit provided by financial sector (% of GDP) -53.6 Gross domestic product (GDP) per capita (2011 PPP $) 2,039.70 Gross domestic product (GDP), total (2011 PPP $ billions) 2.3 Gross fixed capital formation (% of GDP) 55.7 Foreign direct investment, net inflows (% of GDP) 1.6 Exports and Imports (% of GDP) 136.7 Net official development assistance received (% of GNI) 6 Private capital flows (% of GDP) 178.6 Remittances, inflows (% of GDP) 9.4 Inequality Inequality-adjusted HDI (IHDI) 0.412 Coefficient of human inequality 29.4 Income inequality, Gini coefficient 30.4 Inequality in income (%) 17.8 Gender Development Index (GDI) 0.868 Human Development Index (HDI), female 0.548 Human Development Index (HDI), male 0.631 Violence against women ever experienced (%) 39.2 Income and Employment Estimated gross national income per capita, female (2011 PPP$) 3,122.50 Estimated gross national income per capita, male (2011 PPP$) 7,529.70 Expected years of schooling, female (years) 11.3 Expected years of schooling, male (years) 12 Labour force participation rate (% ages 15 and older) 37.9

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Labour force participation rate, female (% ages 15 and older) 24.6 Labour force participation rate, male (% ages 15 and older) 50.8 Employment in agriculture (% of total employment) 50.6 Employment in services (% of total employment) 39.8 Labour force with tertiary education (%) 2.4 Long term unemployment rate (% of the labour force) 0.4 Total unemployment rate (% of labour force) 3.9 Vulnerable employment (% of total employment) 69.6 Youth unemployment rate (% of labour force ages 15-24) 14.8 Poverty/social mobility Multidimensional Poverty Index (MPI), HDRO specifications 0.322 Population in multidimensional poverty (%) 64.3 Population in multidimensional poverty, headcount (thousands) 694 Population in multidimensional poverty, intensity of deprivation (%) 50.1 Population in severe multidimensional poverty (%) 31.5 Population living below income poverty line, PPP $1.25 a day (%) 34.9 Population near multidimensional poverty (%) 21.4 Working poor at PPP$2 a day (% of total employment) 66.9 Employment to population ratio (% ages 15 and older) 36.2 Child labour (% of ages 5 to 14) 4.2 Mobile phone subscriptions (per 100 people) 58.7 Internet users (% of population) 1.1 Environment/Services Carbon dioxide emissions per capita (tonnes) 0.2 Electrification rate, rural (% of rural population) 26.8 Impact of natural disasters, population affected (average annual per million people) 950.7 Forest area (% of total land area) 48.4

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I ANNEX 2 – LIST OF CLIMATE RESILIENCE PROJECTS FUNDED BY INTERNATIONAL AGENCIES

Table 0-1: List of Climate Resilience Project Funded by International Agencies listed in TL State Budget 2014

Implemented Year of Project Titel District Project cost Agency Implementation Future establishment of security and European Union community resilience through consolidation 2014 Aileu $5,046.65 and dissemination of early warning system World Bank Timor Leste Road Climate Resilience Project $1,785,000.00 Future establishment of security and 2014 Ainaro European Union community resilience through consolidation $5,046.65 and dissemination of early warning system Future establishment of security and European Union community resilience through consolidation 2014 Baucau $5,046.65 and dissemination of early warning system Future establishment of security and European Union community resilience through consolidation 2014 Bobonaro $5,046.65 and dissemination of early warning system Future establishment of security and European Union community resilience through consolidation 2014 Covalima $5,046.65 and dissemination of early warning system World Bank Timor Leste Road Climate Resilience Project $1,839,000.00 Future establishment of security and 2014 Dili European Union community resilience through consolidation $5,046.65 and dissemination of early warning system Future establishment of security and European Union community resilience through consolidation 2014 Ermera $3,027.99 and dissemination of early warning system Future establishment of security and European Union community resilience through consolidation 2014 Lautem $3,027.99 and dissemination of early warning system Future establishment of security and European Union community resilience through consolidation 2014 Liquica $3,027.99 and dissemination of early warning system Future establishment of security and European Union community resilience through consolidation 2014 Manatuto $3,027.99 and dissemination of early warning system Future establishment of security and European Union community resilience through consolidation 2014 Manufahi $3,027.99 and dissemination of early warning system Future establishment of security and European Union community resilience through consolidation 2014 Oecusse $3,027.99 and dissemination of early warning system Future establishment of security and European Union community resilience through consolidation 2014 Viqueque $5,046.65 and dissemination of early warning system $3,677,494.49

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Table 0-2: List of Climate Resilience Project Funded by International Agencies listed in TL State Budget 2015

Implemented Year of Project Title District Project cost Agency Implementation 2015 Disaster Risk Reduction Building community USAID $71,269.52 Resilience in Timor Leste Future establishment of security and 2015 Aileu European Union community resilience through consolidation $2,018.66 and dissemination of early warning system World Bank Timor Leste Road Climate Resilience Project $1,326,930.00 Future establishment of security and 2015 Ainaro European Union community resilience through consolidation $2,018.66 and dissemination of early warning system Disaster Risk Reduction Building community $71,269.52 Resilience in Timor Leste - phase 2 USAID Disaster Risk Reduction Building community $145,800.00 Resilience in Timor Leste 2015 Baucau Future establishment of security and European Union community resilience through consolidation $3,027.99 and dissemination of early warning system Disaster Risk Reduction Building community $71,269.52 Resilience in Timor Leste - phase 2 USAID Disaster Risk Reduction Building community $48,600.00 Resilience in Timor Leste 2015 Bobonaro Future establishment of security and European Union community resilience through consolidation $4,037.32 and dissemination of early warning system Future establishment of security and European Union community resilience through consolidation 2015 Covalima $6,055.98 and dissemination of early warning system World Bank Timor Leste Road Climate Resilience Project $1,367,140.00 Future establishment of security and European Union community resilience through consolidation $5,046.65 2015 Dili and dissemination of early warning system Disaster Risk Reduction Building community USAID $48,600.00 Resilience in Timor Leste Disaster Risk Reduction Building community $71,269.52 Resilience in Timor Leste - phase 2 USAID Disaster Risk Reduction Building community $102,600.00 Resilience in Timor Leste 2015 Ermera Future establishment of security and European Union community resilience through consolidation $4,037.32 and dissemination of early warning system Disaster Risk Reduction Building community $76,360.20 Resilience in Timor Leste - phase 2 USAID Disaster Risk Reduction Building community $97,200.00 Resilience in Timor Leste 2015 Lautem Future establishment of security and European Union community resilience through consolidation $4,037.32 and dissemination of early warning system Join edification project through conservation JICA and afforestation of hydrografic zone in Suco $107,659.78 maumeta 2015 Liquica Future establishment of security and European Union community resilience through consolidation $2,018.66 and dissemination of early warning system Disaster Risk Reduction Building community $76,360.20 Resilience in Timor Leste - phase 2 USAID Disaster Risk Reduction Building community $97,200.00 Resilience in Timor Leste 2015 Manatuto Future establishment of security and European Union community resilience through consolidation $6,055.98 and dissemination of early warning system Disaster Risk Reduction Building community USAID $76,269.52 Resilience in Timor Leste - phase 2 Future establishment of security and Manufahi European Union community resilience through consolidation $4,037.32 and dissemination of early warning system Future establishment of security and European Union community resilience through consolidation 2015 Oecusse $3,027.99 and dissemination of early warning system Future establishment of security and European Union community resilience through consolidation 2015 Viqueque $5,046.65 and dissemination of early warning system $3,906,264.28

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Table 0-3: List of Climate Resilience Project Funded by International Agencies listed in TL State Budget 2016

Implemented Year of Project Title District Project cost Agency Implementation 2016 World Bank Timor Leste Road Climate Resilience Project 2016 Aileu $1,214,400.00 World Bank Timor Leste Road Climate Resilience Project 2016 Ainaro $1,214,400.00 European Union GCCA ( global Climate Change Alliance $211,575.00 Disaster Risk Reduction Building community 2016 Baucau USAID $28,000.00 Resilience in Timor Leste - phase 2 Disaster Risk Reduction Building community USAID 2016 Bobonaro $28,000.00 Resilience in Timor Leste - phase 2 World Bank Timor Leste Road Climate Resilience Project 2016 Dili $1,251,200.00 Disaster Risk Reduction Building community USAID 2016 Ermera $28,000.00 Resilience in Timor Leste - phase 2 Disaster Risk Reduction Building community USAID 2016 Lautem $30,000.00 Resilience in Timor Leste - phase 2

Flood control project through conservation JICA and afforestation of hydrografic zone in Suco 2016 Liquica $28,239.12 maumeta

Disaster Risk Reduction Building community USAID 2016 Manatuto $30,000.00 Resilience in Timor Leste - phase 2 Disaster Risk Reduction Building community USAID 2016 Manufahi $28,000.00 Resilience in Timor Leste - phase 2 European Union GCCA ( global Climate Change Alliance 2016 Viqueque $211,575.00 $4,303,389.12 Table 0-4: List of Climate Resilience Project Funded by International Agencies listed in TL State Budget 2017

Implemented Year of Project Title District Project cost Agency Implementation 2017 World Bank Timor Leste Road Climate Resilience Project 2017 Aileu $795,981.78 World Bank Timor Leste Road Climate Resilience Project 2017 Ainaro $795,981.78 European Union GCCA ( global Climate Change Alliance 2017 Baucau $211,978.50 World Bank Timor Leste Road Climate Resilience Project 2017 Dili $820,102.44 European Union GCCA ( global Climate Change Alliance 2017 Baucau $211,978.50 $2,836,023.00

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ANNEX 3 - REVIEW OF EXISTING HAZARD MODELLING AND MAPPING FOR TIMOR LESTE

Introduction and context

This review is based on the national hazard maps for Timor Leste which was produced by the project entitled “Disaster Risk Management Institutional and Operational Systems Development in Timor-Leste”, co-funded by UNDP and the Disaster Preparedness Programme of the European Commission’s Humanitarian Aid department (DIPECHO)46. The project supported the National Disaster Management Directorate (NDMD) to address the immediate needs as identified by the Council of Ministers for the development of necessary institutional and standard operational systems to support the operationalisation of the National Policy for Disaster Risk Management, the decentralization of services, and the strengthening of the link between district and central levels, as well as among various Government structures.

One of the project outputs was a mapping and analysis tool to assist national and local officials to understand and manage disaster related risks. The computer based tool, which has been named DRMInfo, facilitates assessment, presentation and knowledge management of disaster risks in a Geographic Information System (GIS) package that requires only modest computing skills to operate. The map layers in DRMInfo are divided into hazards (also known as “sources of risk”) such as landslide potential, tsunami potential and flooding potential; and vulnerable elements in the community (also known as “elements at risk”), such as households, schools and bridges. The information can be displayed at various levels (national, district, sub-district or suco level) to provide an indication of the level of disaster risk as the maps show the intersection between sources of risk and elements at risk.

This review is based on available information to provide a basic analysis of the natural hazards which are most relevant in Timor-Leste. The broad analysis and recommendations in this document are drawn primarily from data and analysis conducted initially in 2002 under a UNDP project on hazard maps for Timor-Leste. The hazard data was revalidated in 2009 and combined with vulnerability data to produce these maps. Information about the methodologies used for the development of each map is available in the project report on the development of DRMInfo. Higher definition maps are also available from UNDP DRM Project.

Hazard and Risk Mapping products available in DRMInfo

Landslide Risk

Landslides are events where material such as rock and earth moves down a slope, often with very destructive force. Landslides are driven by gravity and important contributing factors include slope stability and water content. They are often triggered by heavy rainfall and/or runoff and are more common in areas where the vegetation providing stability and reducing the speed of runoff has been degraded.

Interpretation: The maps below show the distribution of landslide hazard across the country and categorize the hazard into five levels (very high, high, medium, low and no-data). It shows that the eastern half of the country has almost all the areas of “very high” and “high” landslide hazard, based on the

46 Taken from “Disaster Risk and Hazard Map Analysis for Timor-Leste: An overview of existing risk maps - Disaster Risk Management Institutional and Operational Systems Development in Timor-Leste Project, UNDP (2016)

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I available data. The second map shows how one of the hazard layers within DRMInfo can be combined with one or more of the layers representing elements-at-risk. In the map “Houses at Landslide Risk Timor-Leste”, landslide hazard has been combined with the national household location data. Only households that sit within the boundaries of the “very high” and “high” landslide hazard regions are depicted on this map.

The maps inform national resource managers and planners how landslide risk is distributed across the country and quantify the risk in terms of the numbers of households exposed to the hazard. Such information has the potential to support several strategies for risk reduction. In the high risk areas, the design of roads and bridges could incorporate means to prevent adjacent soils from becoming unstable due to water saturation. Houses, schools and other vulnerable infrastructure should be located to avoid exposure to the hazard wherever possible. High risk districts could be prioritized in terms of access to heavy equipment for road repair and emergency rescue that could be located there in anticipation of landslide damage. Reforestation and sustainable agricultural techniques should also be considered to stabilize potentially dangerous terrain.

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Flooding in Timor-Leste occurs as flash-flooding when heavy seasonal rain higher in catchment basins converges in tributaries as it descends, resulting in rapid rise of discharge in the water courses.

Interpretation: The map above shows the areas where water accumulates in lowland or upland floodplains when river banks have insufficient capacity to contain the flow. National resource managers will note the preponderance of flooded land on the south coast where population and infrastructure are sparse relative to the north coast. Implications for planners would be similar to those described for the landslide risk map. Overlay of elements of risk is more useful in smaller scale maps, such as suco.

Suco river flood risk The map shown on the following page illustrates how DRMInfo can usefully display smaller administrative areas in high detail.

Interpretation: This map is useful for local level flood risk reduction because it identifies specific households at risk and suggests where households and infrastructure should or should not be located. Land use regulations intended to reduce losses due to river flooding could be based on such a map. It could indicate candidate locations for flood shelters in places with many households at risk. The map could be improved with representation of essential infrastructure elements such as health clinics, schools, roads and administrative offices and any other features that would help the user visualize the risk situation, such as topography. These layers are available in DRMInfo

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Drought risk

The criteria for drought usually include the degree to which rainfall in dry years is different from normal years, measured by the ratio of the rainfall in driest 10% of years to the normal (median) rainfall. However, that degree of detail cannot be obtained from the limited data available for Timor-Leste at present. Instead, a drought hazard map was produced by combining the annual rainfall map with the groundwater occurrence map.

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Interpretation: This map shows three classifications of drought affected areas within Timor-Leste; high, medium and low. The majority of high and medium risk areas are close to the northern coast, which agrees with widely held understanding and anecdotal evidence. The map would be improved with representation of land use types such as rice and maize fields and village gardens, and existing groundwater irrigation systems. It could indicate likely locations for cultivation and development of irrigation resources such as dams, aqueducts and wells. It could potentially support decisions about agricultural microcredit, giving an indication of loan risk and discouraging inappropriate development in drought-prone areas. Maps such as these are particularly relevant when factoring in the expected consequences of climate change; which in Timor-Leste are expected to include increased rainfall variability during growing seasons, and, therefore, potentially more droughts.

Tsunami Risk

For a tsunami to build up into a wave of destructive power it needs a stretch of shoaling where the waves can grow in amplitude. It is therefore important to investigate where around Timor the underwater gradient is sufficiently gradual to cause the shoaling effect. The greatest destructive tsunami hazard occurs along the stretch of coast where the underwater gradient is lowest and the shoaling stretch is longest.

A Tsunami Hazard Map was produced, based on the degree of shoaling offshore and on the inland boundary formed by the 30 contour line. This was overlaid with households falling within the higher risk area.

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Interpretation: The above map shows that there is much greater shoaling along the south coast, making this coast more vulnerable to destructive tsunamis. On average, in the tsunami danger areas along the south coast, the 30 m contour line is about 3 km inland. This means that in the event of a tsunami hitting the South coast the danger zones are doubly vulnerable because: one, the wave can build up to a great height due to the wide shoaling stretch, and two the swash of the breaking wave will enter far inland as a result of the flat topography. It is the swash followed by the backwash that then causes death and destruction when everything in its path is dragged back out into the sea.

According to the map above the entire coastline of Viqueque District is vulnerable to potentially destructive tsunamis because of the relatively wide shoaling stretch in combination with a flat topography inland from the coast.

Other hazards and risks

Cyclone Hazard

Timor-Leste is situated in the cyclone belt; however, this hazard is not mapped because the entire country is in the “One Cyclone per Decade” zone (source: Natural Hazards Potential Map of the Circum-Pacific Region, 1995). Besides cyclones, Timor-Leste is affected annually by tropical storms. These tropical storms can be as devastating as a cyclonic activity as they can deposit extremely high amounts of rainfall in short time periods. Warning communities in the path of tropical storms is an important role of the NDMD and local officials. Therefore, developing systems and procedures for warning systems down to community level (that would also be used for other hazards such as tsunami) could be expected to be a high priority for government.

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While it is not possible to predict the exact location or intensity of likely earthquakes, it is possible to calculate the expected return period for earthquakes within various intensity ranges. Past studies on likelihood of earthquake damage to locations in the Pacific Rim put Timor in classification VIII47. This classification indicates that the country is exposed to earthquakes with intensities classified as “Destructive”48 and which could cause significant damage and loss of life. The classification also indicates a 20% probability of exceeding level VIII and experiencing a “Ruinous” to “Catastrophic” intensity earthquake within a 50 year period.

It is also possible to map locally where seismic shaking can have higher relative impact. Data on potential for ground-shaking exists due to previous analysis in Timor-Leste, as does data for potential for soil liquification (Wine Langeraar, 2002). This type of data can be used to strengthen risk reduction measures in specific localities or districts that are considered more prone to these effects. It is understood that there are very few structures in Dili or district capitals that have been built with seismic resistance incorporated, and that almost all private dwellings being constructed are non-engineered concrete/masonry buildings. Such buildings could be expected to have very high rates of failure in a strong earthquake (6.0-6.9 magnitude) and devastating levels in a major earthquake (7.0-7.9) that were to have an epicenter close to Dili or any of the district capitals.

As was recommended in the National Disaster Risk Management Plan of 2006, there are many possible interventions to reduce the risks associated with earthquakes; these include: introduction of appropriate building codes; enforcement of codes, building permits and inspections; availability of basic construction standards to the public; training of masons and carpenters; and awareness raising regarding personal safety during earthquakes.

The map below shows the locations of earthquakes in the vicinity of Timor-Leste over a 34 year period. The available data suggest that there is considerable risk from a destructive earthquake. In terms of risk analysis, the probability of a significant magnitude earthquake would be classified as having low probability (over a relatively short time period) but extremely high consequences.

47 "The World Map of Natural Hazards", Munich Reinsurance Company - Geoscience Research Group 48 Damage slight in specially designed structures; considerable in ordinary substantial buildings with partial collapse. Damage great in poorly built structures. Fall of chimneys, factory stacks, columns, monuments, walls. Heavy furniture moved.

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Annex II – Feasibility Study GREEN CLIMATE FUND FUNDING PROPOSAL I Conclusions

The national level risk maps covered in this report indicate that Timor-Leste faces high levels of exposure to disaster hazards and that there are many vulnerable elements exposed to these hazards. The maps provide guidance for government officials and planners as they give an indication of which districts have higher exposure to risk related to particular hazards. To assist further analysis more detailed maps can be produced at district, sub-district and suco level where the data indicates high levels of risk.

It should be noted that the methodologies used to produce these maps do not equate to absolute or certain risk. Direct observation is required to survey the high-risk locations that are pre- identified and to confirm the level of risk identified. Given this, district level authorities can use such national risk maps to identify areas for examination and can cross-reference with local residents understanding and historical perspective. The DRMInfo mapping tool also requires regular updating of datasets to allow risk analysis to remain current.

The support requested by the Government for conducting a National Disaster Risk Assessment would provide decision makers with a more comprehensive picture of the levels of disaster risk in different districts and sucos, as well as at the national level. UNDP is committed to support the process of conducting such a national risk assessment that would train and actively involve officials both at the national and local levels; develop their knowledge of disaster risk and lay the foundations for the development of risk reduction plans within government other agencies.

The current level of disaster risk analysis that is available provides some indications of where the government could prioritise risk reduction activities in the absence of a more comprehensive national risk assessment. This is particularly applicable when there are a number of large scale infrastructure projects that are in early phase (e.g. heavy oil power plants and transmission lines, roads projects, port upgrading, new government buildings, social housing, etc.). Many of the risks described in this document can be expected to increase substantially over the coming years due to rapid increases in population, urbanization, environmental degradation and climate change.

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ANNEX 4 - DATA AVAILABILITY FOR HAZARD AND RISK MODELLING AND MAPPING FOR TIMOR LESTE

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ANNEX 5 - MAP OF PROPOSED INFRASTRUCTURE PROJECTS

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ANNEX 6 – MAPS SHOWING CATCHMENTS IN WHICH AGRO-FORESTRY WILL BE IMPLEMENTED

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ANNEX 7 – INFRASTRUCTURE BENEFICIARY SUCOS BY MUNICIPALITY AILEU

1. Suco Liurai

A-RR-09 Estrada Husi Rairema Ba Lahae Aileu Sucu Liurai Lahae 2.59 180,005 Estrada Foun Husi Laklo Ba Aldeia A-RR-10 Aileu Sucu Liurai Liksala Eraulu Liksala 3.10 189,999 Dada bemos ba Suco Liurai A-WS-01 Aileu Sucu Liurai Sucu Liurai Remexio Sistema Grafitasaun 4.50 100,000 Konstrusaun Bareira Oralete, Suco A-FP-04 Aileu Suco Liurai Sucu Liurai Liurai 1.00 200,000

Total Male Female Household Suco Liurai 4,122 2,141 1,981 688 Banderahun 480 237 243 79 Coulaudo 394 205 189 65 Fatubessi 488 265 223 77 Fatulmau 302 160 142 49 Laclo 643 326 317 111 Quirilelo 614 317 297 109 Raimanso 473 251 222 77 Rairema 728 380 348 121

2. Suco Aisirimou

Estrada Husi Aisirimou Ba Aldeia Sucu A-RR-11 Aileu Aldeia Berkati Berkati Aisirimou 3.40 194,990 Konstrusaun Bareira Protégé Uma A-FP-05 Aileu Aisirimou Aisirimou Komunidade Iha Modo Laran 0.50 85,000

Total Male Female Household Aissirimou 2,206 1,098 1,108 326 Aituhularan 600 297 303 89 Bercati 322 165 157 49 Bessilau 373 187 186 57 Erkoatun 178 91 87 26 Hudilaran 733 358 375 105

3. Suco Madabeno

Lokedalan Husi Aldeia Manufoni Ba Sucu A-RR-13 Aileu Aldeia Lisamori Aldeia Lisamori Madabeno 2.20 174,988 Rehabilitasaun Estrada Sucu Sucu A-RR-14 Aileu Aldeia Manehalo Madabeno Liga Aldeia Manehalo Madabeno 1.20 150,000

Total Male Female Household Madabeno 1,543 760 783 241 Belumhatu 480 241 239 59

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Desmanhata 225 116 109 41 Lismori 190 89 101 37 Manehalo 350 174 176 55 Manufoni 123 57 66 20 Remapati 175 83 92 29

4. Suco Fahiria

A-IS-01 Kons. Irigasaun Sarin Aileu Fahiria Sarin 85,000 0.50 Konstrusaun Bareira Sucu Fahiria, A-FP-03 Aileu Fahiria Fahiria 320,000 Saboria 2.00

Total Male Female Household Fahiria 1,823 962 861 301 Daulala 243 135 108 33 Fahiria 134 79 55 25 Fatubuti 212 112 100 30 Manulete 292 154 138 53 Sarin 560 277 283 96 Sidole 382 205 177 64

5. Suco Lahae

A-IS-02 Kons. Irigasaun Daisoli Aileu Lahae Lahae 120,000 1.00

A-WS-03 Konst.Be’e mos 3,5 Km suco Lahae Aileu Lahae Lahae 90,000 3.50

A-RR-05 Lahae - Eralolo Road Rehabilitation Aileu Lahae Eralolo 189,390 3.21

Total Male Female Household Lahae 698 369 329 119 Denhuni 7 4 3 1 Eralolo 112 70 42 17 Lacasori 8 5 3 1 Lahae 543 276 267 95 Riatelo 28 14 14 5

BAUCAU

6. Suco Afaca

Estrada foun husi suco afaca ba suco B-RR-02 Baucau Afaca Ekubuti guruca 2.86 434,977 Rehabilitasaun beé matan boe ira, no B-WS-09 Baucau Afaca Afaca dada ba komunidade suco afaca 2.57 85,000

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Total Male Female Household Afaçá 1,204 600 604 218 Boralai 233 121 112 37 Uligata 732 361 371 136 Vecubuti 239 118 121 45

7. Suco Vemasse Tasi

Kuda Vetiver tuir Canal Skema Vemasse B-IS-01 Baucau Vemasse Tasi Irigasaun Buluto - Vemasse Tasi 2.19 25,000 B-WS- konstrusaun beé mos sub aldeia Vemasse Baucau Vemasse Tasi 04 uailacama, suco vemasse tasi Tasi 2.69 75,000 rehabilitasaun beé mos ho sistema B-WS- pomba iha suco vemasse tasi, ho fo Vemasse Baucau Vemasse Tasi 08 abastesimento ba komunidade Tasi 1.25 50,000 vemasse vila no suco caicua

B-FP-02 protecsaun ba natar iha vemasse Baucau Vemasse Vemasse 300,000 1.52

Total Male Female Household Vemasse 9,643 4,860 4,783 1,817 Caicua 77 35 42 22 Bahamori 41 18 23 11 Caicua 36 17 19 11

LAUTEM

8. Suco Illiomar

La-RR- Osoira Rehabilitasaun Estrada Osoira - Alira Lautem Alira Iliomar 1 03 Iliomar 1 1.83 99,991 La-IS- Iradarate Iradarate Iliomar Irigasaun Iradarate Lautem 05 Iliomar I I 1.71 135,000 La-WS- Sistema Grafitasaun Be'e Mos Dilno Lautem Iliomar I Iliomar I 02 4.75 85,000 La-FP- Konstrusaun Valeta, Box Culvert no Lautem Iliomar 1 Iliomar 1 04 bareira iha Suco iliomar 1 0.32 50,000

Total Male Female Household Iliomar 1 1,902 890 1,012 416 Ara'Ara 482 210 272 101 Caentau 350 170 180 74 Iliomar 542 257 285 126 Ossohira 383 181 202 85 Vatamatar 145 72 73 30

9. Suco Maina 1

La-IS- Irigasaun Nasapala Lautem Maina I Solaresi- Maina I 01 10.00 400,000 La-WS- Suco Sistema Bonba Be'e Mos Maina I Lautem Maina I 05 Maina I 2.00 60,000

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Total Male Female Household Maina 1 1,362 678 684 245 Maina 1 196 98 98 29 Mauvedara 172 81 91 38 Narunteino 313 149 164 53 Paiahara 68 32 36 12 Soleresi 613 318 295 113

LIQUICA

10. Suco Faulara

L-IS- Kontrusaun Irigasaun Liquica Faulara Guico 01 5.00 450,000 L-IS- Kontrusaun Bareira ba Irigasaun Liquica Faulara Guico 02 (retaining wall for Irrigation Protection) 1.00 150,000

Total Male Female Household Guiço 1,983 1,004 979 320 Caicassavou 686 349 337 103 Irlelo 433 224 209 72 Mau-Uno 319 156 163 49 Pandevou 297 157 140 51 Vatu-Vei 248 118 130 45

11. Suco Fatumasi

L-WS- Konstrusaun Sistema Be'e Mos Sucu Liquica Suku Fatumasi 01 Sistema Gravitasi Fatumasi 4.00 95,000 L-FP- Suku Konstrusaun Vareira Liquica Suku Fatumasi 04 Fatumasi 0.11 75,000

Total Male Female Household Fatumasi 1,551 755 796 273 Bazartete 780 375 405 138 Durubasa 41 17 24 7 Legumea 182 82 100 31 Metir 548 281 267 97

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I ANNEX 8 – PROTOTYPE CLIMATE PROOFING DESIGN OF SMALL-SCALE RURAL INFRASTRUCTURE UNITS FOR TIMOR LESTE 1.0 Water Supply System

Problem Statement Site layout and Prototype climate proofing design of infrastructure unit Design features Vulnerability: drought Site Layout (affecting water debit) − System design allows + erosion and modification and/or landslides (affecting expansion without system components significant disruption of and sedimentation) service and cost.

Drought risks to − Comprised of simple/less- population impacting complex components. on health, education, agricultural sectors.

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I Reservoir/Tank − Bigger storage capacity (reservoir) with sizes ranging from 60m3 – 90 m3. − Soil-bioengineering around reservoir to protect against landslide/erosion risks − Water level gauge to support Facility Maintenance Groups (GMFs) in monitoring water rationing to beneficiaries

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I Water Source: • Water Source Protection – Soil- bioengineering around intake structure. • Install live fencing (plant) around the water source. • Planting select species of plants around the wider catchment area.

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I (a) Intake Structure – Spring source • Intake structure designed and built with storage capacity and filter membrane. • Soil-bioengineering around water intake.

• Water intake structures, with storage capacity (for increasing the pressure and catering for reduce water debit at source).

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Public/Communal Taps: • Soil-bioengineering around public/communal taps with live fences to prevent erosion that tends to compromise the structure.

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I 2.0 Rural Roads and Bridges

Problem Site layout and Prototype climate proofing design of infrastructure unit Design features Statement

• Vulnerability: flooding, erosion Site Plan and landslides • Impact: due to extreme rainfall causing flooding, erosion and landslide

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I Road surfacing, steep slopes • Rigid pavement road surface (using plum concrete) for slopes with steep gradient.

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I Hydraulic and drainage structures: • Hydraulic and drainage structures designed to h) Concrete drains accommodate increased precipitation.

i) Masonry drains with retaining walls

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I Slope stabilization: j) CSA of road structure with gabion wall at base • Combination of engineering (structural) and non-engineering approaches combined with ecosystem-based adaptation (EBA) approaches (such as soil- bioengineering and catchment management/stabilization)

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I k) Tree planting for soil-stabilization

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I l) Deep root plants such as vetiver used for soil-bioengineering

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I • Gabion retaining Retaining walls: walls at base of road structure to support soil-stabilization

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I Plan of bridge/culvert (showing area for slope-stabilization measures) • Slope stabilization using deep root vegetation and land management measures

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3.0 Irrigation Schemes

Vulnerability to climate change Site Plan hazards: flooding, erosion and landslides, scheme designed to ensuring adequate and consistent water supply

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Irrigation Channel: • Masonry/concrete channel • Planting vetiver grass along the channel

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Gabions: • Gabion cascade

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