JOINT COOPERATION PROGRAMME

Component B: Water resources management planning and Integrated Water Resources Management (IWRM) tools

Document B1.1 Final report Einlanden-Digul-Bikuma basin IWRM case study

27 September 2012

Project: 1201430.000

Client: Water Mondiaal Partners for Water Royal Netherlands Embassy in Jakarta

Period: January 2011 – March 2013

JOINT COOPERATION PROJECT

COMPONENT B: INTEGRATED WATER RESOURCES MANAGEMENT

Einlanden-Digul-Bikuma Basin Case Study Report

DRAFT September 27, 2012

Agnese Boccalon, Marnix van der Vat and Hatmoko Waluyo

Table of Contents

EXECUTIVE SUMMARY...... 5 1. INTRODUCTION ...... 8 1.1 Objectives and main activities ...... 8 1.2 Partners...... 10 1.3 Client and beneficiaries ...... 10 2. BACKGROUND INFORMATION...... 12 2.1 The Einlanden-Digul-Bikuma river basin...... 12 2.2 Institutions ...... 14 2.3 Regulations ...... 15 2.4 Water resource planning and management in the EDB...... 16 3. ANALYTICAL APPROACH AND TOOLS...... 17 3.1 Hydrological analysis...... 17 3.2 Multi-criteria analysis...... 19 4. GLOBAL DATASETS INPUT FOR HYDROLOGICAL ANALYSIS...... 20 4.1 Precipitation...... 20 4.2 Evapo-transpiration...... 21 4.3 Topography...... 21 4.4 Land use data ...... 22 4.5 Soil data...... 24 4.6 General overview on the EDB basin ...... 25 5. HYDRO-METEOROLOGICAL ANALYSIS ...... 27 5.1 Catchment delineation...... 27 5.2 Precipitation patterns...... 29 5.3 Discharge patterns...... 31 5.4 Frequency analysis ...... 35 5.5 Water balance analysis and validation of model output ...... 37 5.6 Sensitivity analysis...... 39 6. WATER DEMAND...... 42 6.1 Current water demand ...... 42 6.2 The MIFEE project and its water requirements ...... 43 6.2.1 Water requirements for paddy...... 46 6.2.2 Water requirements for oil palm ...... 48 6.2.3 Water requirements for sugar cane...... 50 7. WATER RESOURCES PLANNING ...... 52 7.1 Principles of water resources planning...... 52 7.2 Multi-criteria analysis for the EDB catchment ...... 53 8. CONCLUSIONS and RECOMMANDATIONS...... 58 8.1 Conclusions...... 58 8.2 Recommendations...... 58 9. REFERENCES ...... 60 ANNEXES ...... 62 Annex 1: Identified soil and land cover parameters in the EDB basin ...... 62

Index of Figures

Figure 1-1 Meeting with local district authorities in Merauke...... 11

Figure 2-1 Location of the EDB river basin in Papua province ...... 12 Figure 2-2 Overview of the administrative units comprised in the EDB catchment area ...... 13 Figure 2-3 Agro-climatic zones in the EDB catchment based on [Oldeman et al., 1980] ...... 14 Figure 2-4 Overview of the institutional framework for water resources management in Indonesia....15

2 Figure 3-1 Overview of the analytical process for the hydrological analysis component of the EDB basin...... 18

Figure 4-1 TRMM rainfall input dataset used for rainfall data preparation...... 20 Figure 4-2 CSI-CGIAR input dataset used for the preparation of evapo-transpiration input maps...... 21 Figure 4-3 SRTM map of Indonesia ...... 21 Figure 4-4 GlobCover land use input for the EDB catchment ...... 22 Figure 4-5 FAO HSWD input for soil mapping in the EDB catchment ...... 24 Figure 4-6 Elevation Map (left) and land cover map (right) for the EDB basin...... 25 Figure 4-7 Soil map of the EDB basin...... 26 Figure 4-8 Monthly evapo-transpiration (left) and daily precipitation (right) map for the EDB basin .26

Figure 5-1 Example of Local Drainage Direction map...... 27 Figure 5-2 Results of the catchment delineation process with W-Flow...... 28 Figure 5-3 Oldeman agro-climatic zones based on TRMM bias-corrected precipitation input ...... 29 Figure 5-4 Precipitation variability based on distance from the coast and elevation...... 30 Figure 5-5 Distribution of annual rainfall between wet and dry season for the 16 EDB sub-catchments ...... 30 Figure 5-6 Comparison of selected EDB sub-catchments hyetographs...... 31 Figure 5-7 Location of the EDB catchments with larger annual discharge...... 33 Figure 5-8 Annual average discharge patterns of the EDB sub-catchments ...... 33 Figure 5-9 Monthly discharge patterns of low-discharge rivers in the EDB...... 34 Figure 5-10 Dry season monthly discharge for small EDB sub-catchments...... 35 Figure 5-11 Comparison of cumulative dry season rainfall and discharge for selected EDB sub- catchments...... 35 Figure 5-12 The water cycle components 37 Figure 5-13 Comparison of rainfall-runoff relation as derived by Van der Weert (1994) and model results...... 38 Figure 5-14 Monthly runoff coefficient for selected EDB sub-catchments ...... 39 Figure 5-15 Results of the sensitivity analysis test for the river Kumbe ...... 40

Figure 6-1 Kabupaten in the EDB basin 42 Figure 6-2 Overview of MIFEE development phases 2010-2030 ...... 45 Figure 6-3 Long storage near Merauke 46 Figure 6-4 Irrigation water requirements for rice, compared with rainfall patterns ...... 46 Figure 6-5 Rice irrigation water requirements and simulated average river discharge for MIFEE KSPP 1...... 47 Figure 6-6 River discharge and irrigation water requirements for paddy at comparison...... 48 Figure 6-7 Oil palm plantation in the EDB 48 Figure 6-8 Comparison of dependable rainfall with water requirements for oil palm...... 49 Figure 6-9 Comparison of sugarcane CWR and precipitation patterns in the Merauke area ...... 50

Figure 7-1 IWRM in water resources planning 53

Index of Tables

Table 4-1 22 Land cover categories of the GlobCover map...... 23 Table 4-2 Selected land cover categories in the EDB catchment ...... 23 Table 4-3 Soil classes identified in the EDB catchment ...... 24

Table 5-1 The 17 sub-catchments of the EDB basin ...... 28 Table 5-2 Average annual rainfall in the EDB sub-catchments ...... 29 Table 5-3 Dry season rainfall as percentage of annual rainfall by rainfall range ...... 31

3 Table 5-4 Outflow gauging points of the 17 EDB sub-catchments ...... 32 Table 5-5 Average monthly discharge patterns of 16 EDB sub-catchments (m3/s)...... 32 Table 5-6 Dependable flow (m3/s) for 7 selected rivers of the EDB basin ...... 36 Table 5-7 Rainfall and runoff modeled values in the EDB...... 38 Table 5-8 Monthly runoff coefficient values for selected EDB sub-catchments...... 39 Table 5-9 List of tested parameters for the sensitivity analysis...... 40

Table 6-1 Population statistics for the EDB basin, 2005 ...... 42 Table 6-2 An example of the structure of the MIFEE project...... 44 Table 6-3 Estimated IWR for oil palm during the dry season...... 49 Table 6-4 Comparison of monthly IWR for oil palm with simulated average river discharge ...... 50 Table 7-1 Selected criteria for the multi-criteria analysis ...... 55 Table 7-2 Multi-criteria evaluation for development strategies in the EDB ...... 57

4 EXECUTIVE SUMMARY

Component B of the Joint Cooperation Programme (JCP) has focused on the development of an Integrated Water Resources Management (IWRM) study in the Einlanden-Digul-Bikuma (EDB) basin in eastern Papua Province. The study was carried out in the period October 2011 - October 2012 and involved desk research and computation, and three field visits to the basin. The catchment has been selected to prepare a hydrological assessment of available water resources to serve as a support tool for the revision of the strategic management plan developed at the river basin scale – the Pola. Developing the Pola is a responsibility of the local water basin authority (Balai Wilayah Sungai or BWS), and it is an obligation following the implementation of the 2004 Water Law of the Government of Indonesia. Development of the pola is requested by the Water Resources Directorate General (DG-WR) of the Indonesia Ministry of Public Works (PU), which ultimately decides on the quality of the submitted plan, accepting or rejecting the final document. DG-WR has requested JCP to support revision of the existing draft Pola for the EDB basin.

The Einlanden-Digul-Bikuma (EDB) river basin is situated in the South Eastern part of Papua province in Indonesia. The surface area of the basin is approximately 133,000 km2, and the current population living in the basin amounts to about 524,000 inhabitants. The EDB is a river basin unit covering the administrative boundaries of 8 kabupaten (districts), namely Merauke, Boven Digul, Mappi, Pegunungan Bintang, Jayawijaya, Yahukimo, Tolikara and Asmat. Of these, the Merauke district is the one where the bulk of the commercial and agricultural activity is currently taking place in the basin.

At present, it is reported that the area for rice cultivation is about 37,000 hectares, where at least one rice harvest a year is obtained from rainfed paddy cultivation. On approximately half of this area a second, irrigated crop is cultivated during the dry season.

The analytical approach for the implementation of the EDB case study has involved four phases, namely: x the sourcing of global datasets containing the information to generate the input maps for the hydrological modelling, and the consequent preparation of the input maps (global data sets where used in the absence of sufficient local data on hydrology and meteorology); x the construction of the W-Flow hydrological model for the EDB basin with parameterization of model inputs; x the generation of the model discharge series with validation of model results; x the setting up of a multi-criteria analysis to evaluate different water development strategies as foreseen by local and national government authorities

Where applicable, the assessment of the selected criteria for the multi-criteria evaluation has taken into account the outcome of the water availability assessment resulting from the hydrological analysis.

The main inputs used for the analysis have been global datasets providing information for topography (SRTM from NASA), land cover (GlobCover from ESA), soil types (HWSD from FAO), precipitation (TRMM from NASA) and potential evapotranspiration (Global-PET from CSI-CGIAR). These datasets provided the input to elaborate the required maps for the running of the hydrological model that generated the discharge series: the W-Flow model.

17 river sub-catchments have been identified in the EDB basin. These catchments are the Lorentz, Einlanden, Mappi and Digul to the north, Bian, Kumbe, Maro and Sakiramke to the south-east and a number of small catchment along the coastal area of the basin, namely Fajit, Sanuna, Jeitja, Juliana, Buaya, Buede, Imenoe, Muli and Mengan.

River discharge series for the EDB sub-catchments have been generated for the period March 2002 – December 2011, based on the availability of TRMM precipitation data.

The EDB basin is located in the inter-tropical climatic zone, with one dry and one wet season a year. Usually the dry season runs from June to October, and the wet season from November to May. Based on the

5 TRMM input data for precipitation, the average rainfall in the EDB catchment has been estimated to reach 2,760 mm/year. Yet, rainfall patterns show high variability, both in terms of time and space. Over the same observation period (2002-2011), average annual rainfall varies between a total of 1,650mm/year for sub- catchments located in the south-eastern part of the basin (Sakiramke sub-catchment), to 4,240 mm/year for catchments which are more upstream (Lorentz sub-catchment). A positive correlation between precipitation on the one hand, and elevation and distance from the coast on the other has been detected, with precipitation being higher in the mountainous area as compared to coastal areas.

Model output revealed that, for the time period considered, average annual discharge at the EDB catchment scale can be estimated as 7,960 m3/s varying in a range between 4,400 and 10,500 m3/s in the dry and wet season respectively.

In terms of annual mean discharge, the main 4 rivers in the basin are the Einlanden (3,133 m3/s), Digul (2.127 m3/s), Mappi (580 m3/s) and Lorentz (380 m3/s). All the other rivers in the basin have an estimated average annual discharge below the 250 m3/s. Variability in discharge pattern between the dry and the wet season is higher for those sub-basins whose catchments are located in the south-eastern and coastal areas. In these parts of the catchment total rainfall amounts are lower, and so is the rainfall contribution to river discharge.

Given the small size of commercial and industrial activities in the basin, most of the current water demand in the Einlanden-Digul-Bikuma catchment is represented by domestic water use and irrigation. No large demand for water by the energy or industrial sector has been identified.

Comparing water availability with water demand in the basin, it appears that at present there are sufficient water resources available to meet water demand. This statement however makes reference to the basin as a whole, and does not take into consideration water availability and water demand patterns at the sub- catchment level, nor water quality aspects, which overall may limit actual water availability in time and space (i.e. river water in the coastal area of Merauke cannot be used for irrigation purposes during the dry season because of salinity intrusion from the sea shore).

The Indonesian government is trying to push the development process of Papua through a number of programmes. A large initiative to accelerate economic growth in the EDB basin is the Merauke Integrated Food and Energy Estate (MIFEE). The initiative was officially launched in August 2010 by the Indonesian Minister of Agriculture, Suswono, and currently foresees the development of an area of about 1.2 million hectares for food and energy crops, among which oil palm and sugar cane would cover at least 50% of all allocate area for cultivation.

In view of the agro-business development envisaged in the MIFEE project, it is expected that sufficient availability of fresh water will determine the actual development potential in the area. Based on the model results and available information in terms of allocated area per type of crop, a comparison between water availability from river discharge and net crop water requirements based on local precipitation patterns has been computed for rice, oil palm and sugar cane.

Results show that for the foreseen extent of agricultural land allocated to rice crops (40,000 ha), effective rainfall will not be sufficient to obtain more than one annual harvest. For cultivation of oil palm plantations (255,000 to 550,000 hectares) severe yield loss is expected in the absence of irrigation. Given the estimated plant water requirements and the location of the plantations, it appears that for 5 to 6 months in a year, precipitation in the Merauke area will not be enough to satisfy the oil palm water requirement. For an average precipitation year, it is expected that sugar cane will not require irrigation. Yet, should a dry year occur in which annual precipitation is 30% lower than the average value, sugarcane plantations would also require supplementary irrigation at the beginning of sowing (October), in the month of February, and in the last 2 months of the development crop stage (May and June).

6 Overall, it can be concluded that the selected location for MIFEE in south Papua is not optimal due to the limited amount of rainfall in the area. This is expected to result in lower yields, especially for oil palm and rice, than can be expected for other areas in Indonesia.

A multi-criteria analysis (MCA) has been performed within the IWRM study for the EDB basin to provide an example of IWRM tool that can be used for the evaluation of different strategies. The scope of the MCA has been that of providing an example to show the impact that different use and management of the water resources can have on society as a whole, not only in economic terms, but also considering social, financial, technical and environmental aspects.

From these considerations it can be concluded that, despite the physical availability of water resources at the basin scale, current and future land development in the catchment should carefully take into account the local availability of sufficient volumes of water at the time period where water demand is higher, also considering the water demand of other water users who rely on the same source for supply.

These considerations should particularly be instructive for policy makers and private sector investors, who should carefully take into account the reduced availability of water in the southern areas of the catchment during the dry season, and the influence that this reduced availability might have on the long-term sustainability of the foreseen agro-business development project in the area.

7 1. INTRODUCTION The Collaborative Developments on Integrated Water Resources Management (IWRM) Tools is one of the 6 building components of the Joint Cooperation Programme (JCP), a 5-year initiative financed by the Government of the Netherlands through the Dutch Embassy in Jakarta, and organized in two phases: an initial phase of 2 years from 2010 to 2012, and a second phase of 3 years from 2012 to 2015. The aim of the JCP is the promotion and fostering of constructive collaboration between Dutch and Indonesian institutions in the field of water resources management and climate analysis. The background, objectives and set-up of the JCP are described in the program proposal document. Reference is made to this document for further information on these aspects.

This report describes the activities and results of Phase I of the JCP Component B Integrated Water Resources Management Tools project, implemented in the period October 2011 - October 2012.

1.1 Objectives and main activities The primary objective of the Collaborative Developments on Integrated Water Resources Management Tools project is to support Indonesian water management organizations with improving their understanding of, and access to, state of the art tools and methodologies needed to carry out IWRM studies. During Phase I of the JCP, Component B has focused its attention on capacity building activities among Indonesian institutions, with the purpose to facilitate the preparation and revision of river basin plans such as the Pola, the recently introduced water management strategy implemented nationally at the river basin level.

Three key activities have been carried out within the framework of component B: a. execution of a case study in integrated water resources management at the river basin scale; b. development of an approach to use global datasets and open source tools for hydrological analysis in data poor areas and dissemination of this approach in two workshops; c. expert support for the establishment of a WMO regional training centre for hydrology in Indonesia

These three activities are shortly described in more detail in the sections below.

River basin analysis case study During Phase I of the project the Dutch research institute Deltares and its Indonesian partner organization PusAir (Research Center for Water Resources) have collaborated in the analysis of a selected IWRM case study in Indonesia. Following consultation with the Dutch Embassy in Jakarta, the Einlanden-Digul-Bikuma (EDB) catchment in South-East Papua Province has been selected for the analysis, based on its relevance for its current and foreseen agro-industrial development projects in the area, and for the peculiar characteristics in terms of limited quantitative data availability for meteorological and hydrological measurements. For these reasons, Deltares, PusAir and the Dutch Embassy reckoned that the EDB basin could represent a good selection for the on-the-job-training aimed at the capacity-building aspects of this component. Building on the experience gained during this exercise, it is expected that PusAir staff will be able to carry out autonomously water resources studies in other areas of the country.

The type of information collected during the EDB study includes data on: - Topography; - Meteorology; - Water use and irrigation; - Land use; - Spatial planning; - Water quality; - Occurrence of flooding; - Involvement of government and non-government stakeholders in water related issues; - Future developments with respect to water resources and water use; - Other issues arising around the use of water

8

The collected data has been prepared as an input for hydrological modeling with the aim to produce daily discharge series for the main rivers in the EDB basin area. Subsequently, these discharge series have been validated and used for the assessment of seasonal water availability and for comparison with water demand mainly generated by the agricultural sector.

At the broader scale, the availability of river discharge series in the EDB catchment is of relevance for the development of the Pola and Rencana documents. The latter are long-term water resources management tools used for strategic planning (Pola) and implementation (Rencana) of water development activities aimed at ensuring medium-term sustainability of the water source in both quantitative and qualitative term. Thanks to the elaboration of these discharge series, Component B of the JCP has played an important role in supporting the definition and revision of the Pola document for the Einlanden-Digul-Bikuma basin. The activities related to this component of the project are described in more detail in Chapter 4 (Global Dataset Input for Hydrological Analysis), Chapter 5 (Hydro-Meteorological Analysis), Chapter 6 (Water Demand) and Chapter 7 (Water Resources planning) of this report.

Workshops The Collaborative Developments in IWRM Tools project has also prepared and delivered two national one- week workshops on the use of global data for hydrological analysis in data-scarce areas. The first workshop focused on the collection and preparation of global data to be used as input for the hydrological modelling of a number of selected river basins in Indonesia. The second workshop was a follow-up of the first, and included the running of the hydrological model and validation of the model outcomes, using quantitative analysis tools and existing data.

First workshop in Citeko (Bogor), February 2012

The two workshops took place in the months of February and May, 2012, with approximately 25 participants coming from different Indonesian institutions directly or indirectly involved in the management of water resources. For the purpose of generating hydrological data for different Indonesian catchments, the workshops have been organized in collaboration with Component C2 of the JCP, namely the Water Management Datasets for River Basin and Lowlands project.

WMO Regional Training Center for Hydrology Within the Joint Cooperation Programme, Component B has also supported PusAir in the initial steps for the establishment of a World Meteorological Organization (WMO) Regional Training Center on Hydrology (RTC-H) at PusAir premises in Bandung. JCP has assisted in the strategic thinking about the regional hub role of both institutes and has contributed directly to the preparation of curricula and training materials. This report does not cover these activities.

9 1.2 Partners The main actors of the Collaborative Development of Integrated Water Resources Management Tools component of the Joint Cooperation Programme are Deltares and PusAir. KNMI – the Dutch Meteorological Institute – and BMKG – the Indonesian Institute for Meteorology, Climate and Geo-physics - have assisted in the provision of climate inputs, and have been active in the activities concerning the establishment of PusAir as a WMO Regional Training Centre for Hydrology.

All together, these institutes have joined forces to work on the IWRM study for the Einlanden-Digul- Bikuma (EDB) river basin in South-East Papua.

Overall, the project has employed a team of 7 people, 2 from Deltares and 5 from PusAir. The project has also seen the involvement of a Bachelor student from the University of Twente who has spent 4 full months at PusAir in Bandung, working on the hydrological analysis component of the project. Table 1.1 provides an overview of the staffing for the project, with the responsible lead for each organization.

Table 1-1 Staffing for JCP Component B JCP partner Staff Position in Component B Deltares Marnix van der Vat Lead Agnese Boccalon Bouke Pieter Ottow (student) PusAir Waluyo Hatmoko Lead Radhika Amirwandi Rahmawati Solihah Rendy Firmansyah BMKG Budi Suhardi Lead

1.3 Client and beneficiaries The Embassy of the Netherlands is the donor financing the Joint Cooperation Programme. The Embassy keeps close relationships with different Indonesian Ministries to foster the collaboration between the Dutch and the Indonesian governments in a number of key sectors, among which the water sector plays a major role. During the project definition stage consultations have been carried out with the Directorate General of Water Resources (DGWR), part of the Indonesian Ministry of Public Works (PU). DGWR is in charge of the control of compliance of technical and procedural requirements of the Polas for the river basin in Indonesia. Under specific request of DGWR, Deltares and PusAir have been invited to support the process of revision of the Pola for the EDB river basin. DGWR is therefore one of the main beneficiaries of Component B of the Joint Cooperation Programme.

At the river basin level, the authority responsible for the drafting of the Pola is the Balai Wilayah Sungai (BWS). In the case of the EDB, BWS Papua outsourced the process of drafting the Pola to an external consultant. At the time of JCP Component B being involved in the study, a second consultant had been hired by BWS Papua for the process of revision of the existing Pola. For the direct benefit derived from the accessibility to the elaborated analytical approach and resulting data, BWS and the national consultants are also considered beneficiaries of the outcome of Component B of the Joint Cooperation Programme.

Indirect beneficiaries of the project also include: - the local population living in the districts of the Einlanden-Digul-Bikuma catchment; - the local government units of the Ministry of Agriculture, Ministry of Spatial Planning (provincial and district Bappeda offices), Ministry of Fisheries, Ministry of Forestry and other relevant governmental entities who have taken part in the consultation meetings in Papua;

10 - local civil society institutions such as WWF and the Bikuma Forum, who represent different interested of non-governmental parties in the EDB basin; - commercial investors seizing investment opportunities in the EDB catchment

Figure 1-1 Meeting with local district authorities in Merauke

11 2. BACKGROUND INFORMATION This chapter provides a concise overview of the social, institutional and administrative framework characterizing the Einlanden-Digul-Bikuma basin. First an introduction is given on the general features of the catchment area and of social dynamics at the provincial level, secondly we provide a list of the main Indonesian institutions whose mandate is directly or indirectly affecting water resources availability, thirdly an overview over the main regulatory framework in the water sector is provided, and lastly, we included a short description for the current and most important water resources planning strategies that are relevant for water sector decisions at the national and local scale.

2.1 The Einlanden-Digul-Bikuma river basin The Einlanden-Digul-Bikuma (EDB) river basin is situated in the South Eastern part of Papua province in Indonesia, as shown in Figure 2.1. The surface area of river basin is about 133,000 km2, and it is home to more than half million people. The river basin is an administrative unit consisting of several physical river basins. In this study, 17 sub-catchments have been identified. A more detailed description of these sub- catchment is provided in chapter 5.

Figure 2-1 Location of the EDB river basin in Papua province

Population in the area has considerably increased with the transmigration programme implemented by the national government and started in the 1960s. Through this initiative, at the end of the 1980s, around 23,000 families had been moved to Papua province, most of them allocated to the Merauke area. In the early 1990s, a new 5-years transmigration plan envisaged the arrival of other 29,905 families to the area. As a result of these processes, in 1997 official government statistics report that around 246,000 people have been moved to Papua since 1964, with another 110,000 due to be sent by 1999 (DTE, 2011). Nowadays, the percentage of native Papuans as compared to transmigrants from other Indonesian provinces is decreasing.

Beyond population growth, the migration of other Indonesian groups to Papua is bringing a change in current livelihood habits of Papuans, both in terms of social dynamics (culture, customs) and in terms of eating habits. Indeed, while native Papuans mainly rely on subsistence farming for their livelihood, and have a diet based on sago and hunted meat and fish as a staple food, immigrants from other Indonesian provinces predominantly consume rice in their diets. Sago is a starch extracted from a palm tree growing in forested areas, and the preservation of this land cover type is a prerequisite for food security of native Papuans. The

12 arrival of transmigrants has therefore created a new demand for rice production. Based on these modified population and social dynamics, food self-sufficiency in Papua as a whole has declined.

Figure 2-2 Overview of the administrative units comprised in the EDB catchment area

In administrative terms, the EDB catchment embraces – fully or just partly – 8 kabupaten (districts), namely Kabupaten Merauke, Boven Digul, Mappi, Pegunungan Bintang, Jayawijaya, Yahukimo, Tolikara and Asmat. Figure 2.2 provides an overview of the location and dimension of these administrative units.

In the mountainous areas people live of subsistence farming and generate their income from small business activities. In the low-land areas, irrigated agriculture and a larger number of business activities represents the main source of income for the population.

Current developments in the basin, driven by local and national initiatives, see considerable investment in the agri-business industry as a major development for the area. Reference is made to the Merauke Integrated Food and Energy Estate, the so-called MIFEE project which is currently under preliminary implementation. A more detailed description of the MIFEE project is provided in Chapter 6. Looking at morphology, the variation in the elevation range within the basin boundaries varies considerably, with mountainous area in the Northern part of the basin reaching altitudes of about 5,000 m, progressively sloping down to the coast.

General precipitation patterns in Papua province have been already studied in the 1990s. Van der Weert (1994) reports the distribution of annual rainfall ranges in the province as follows: - 4.2% Dry (1,000 – 1,500 mm/year) - 42.3% Moist (1,500 – 3,000 mm/year) - 42.7% Wet (3,000 – 5,000 mm/year) - 10.9% Very wet (>5,000 mm/year)

The EDB catchment is located in the South-East part of the Province where, generally speaking, precipitation ranges are lower than the provincial average values. This is illustrated in Figure 2.3. Based on the agro-climatic classification developed by Oldeman et al. (1980), 10 out of the 14 agro-climatic zones defined according to specific precipitation patterns are present in the EDB catchment. The definition of wet and dry month developed by Oldeman et al is:

13 ƒ Wet month: mean monthly rainfall is at least 200 mm ƒ Dry month: mean monthly rainfall is less then 100 mm

Figure 2.3 shows that the drier areas in the basin are located in the southern part of the catchment where the number of wet months progressively decreases from an average of 9 to an average of 5 months per year. The intermediate areas is characterized by a category A agro-climatic zone, which means that, on average, there are at least 9 months in a year in which monthly precipitation is above the 200 mm/month. Further discussion about current precipitation patterns is presented in section 5.2 of this report.

Figure 2-3 Agro-climatic zones in the EDB catchment based on [Oldeman et al., 1980]

2.2 Institutions The main institutions playing a role in water resources management in Indonesia are shown in Figure 2.3. At the central government level, the Directorate General of Water Resources (DGWR) of the Ministry of Public Works (PU) is the main institution drafting and delivering policies for surface water resources management. On the other hand, management of groundwater resources is pertinence of the Ministry of Mining and Energy. The national planning bureau BAPPENAS is responsible for the national planning activities including water resources planning. The planning bureau in the provincial and district level is called BAPPEDA Propinsi and Kabupaten with main task of coordination in the provincial and kabupaten level respectively. The EDB river basin territory is managed by Balai Wilayah Sungai Papua under Directorate General of Water Resources of the Ministry of Public Works.

Institutional coordination between different government agencies involved in water resources planning and resources management strategies that affect water resources management (i.e. Ministry of Agriculture, Ministry of Public Works) in Indonesia requires nowadays significant improvements (ADB, 2010). There exist a certain level of hierarchy within agencies belonging to the same ministry, but little or no coordinated action is performed across agencies belonging to different ministries or between ministries themselves. This is particularly true when considering the situation following the implementation of the 2004 Water Act, which promoted decentralization of management for water resources management. Strategic development plans are therefore not designed in a coordinated way, but just represent the planning of single ministries, or those of their agencies.

14 Central Government

M inistry of P ublic M instry of Intern al National Planing W orks A ffair Agency

D G of W ater Resources

Provincial Government

Governor

Balai W ilayah P rovincia l Pu blic Provincial Planning Sungai (BWS) W orks Agency

District Government

Bupati

P roject of BW S at D istrict P ublic District Planning Kabupaten Works Agency

Figure 2-4 Overview of the institutional framework for water resources management in Indonesia

In Indonesia, there are many organizations involved in water resources management. This makes coordination difficult. Example of an overlapping task is that of water conservation activities, which are carried out by both the Ministry of Public Works and the Ministry of Forestry. Yet, another relevant example is the one provided by the strategic plan for water resources management at the river basin scale – the Pola- which aims to get together all the different river basin stakeholders in the consultation, evaluation and planning process for water resources development at the catchment level. This plan, whose main responsibility for drafting and assessment resides within the Ministry of Public Works, is at times not recognized by other government agencies who think that the Pola is the only responsibility of the Ministry of Public Works.

2.3 Regulations Reformation in the water resources sector in Indonesia started in 2001 with the establishment of the Coordination Team for Water Resources Management (TKPSDA). The team was in charge of formulating national policies on water resources and various policy tools, as well as initiating the drafting of the new Water law. Indonesian water law no. 7/2004 was established in the year of 2004, setting up the basis for water resources management in Indonesia in line with integrated water resource management (IWRM) and decentralization principles. Government regulations following the approval of the 2004 water law addresses 7 main water sector areas, namely: irrigation, water resources management, drinking water supply systems

15 (SPAM), groundwater, dams, swamps and river management concerns. Until 2011, the Indonesian government has published six regulations except for regulation on swamps. Based on regulation number 11A/PRT/M/2006, presidential Regulation no. 12/2012 divides Indonesia into 131 River Basin Territory (RBT), consisting of 5 cross-boundary RBT, 29 inter-provincial RBT , 29 RBT of national strategic importance, 53 inter-district (kabupaten) RBT, and 15 single-district RBT. At the provincial and district level there exist provincial and district regulations which, if necessary, can be used to implement government regulations.

To facilitate the process of water resources management at the river basin scale, law No 7/2004 has introduced the concept and Strategic plan (Pola) and Implementation plan (Rencana) to be drafted for each identified river basin entity under the coordination and supervision of the Directorate General of the Ministry of Public Works. The Pola is an integrated and comprehensive strategic water resources management plan for a river basin territory, in which the competent authority preparing the strategic plan needs to assess the current and historical status of water resources in the basin following specific indications and methodologies provided by the DGWR. Assessment is carried out both in terms of quantity and quality of water resources. Based on the deficiencies or concerns highlighted by the investigation study, a plan for water resources development is then drafted for the medium term (20 years). The drafting of the Pola is the responsibility of the Balai Wilayah Sungai of each river basin, which can decide to seek special consultants for the carrying out of the actual research study. To become an enforceable tool, the Pola needs to be approved by the Minister of Public Works. Rencana is the implementation plan following the Pola. The Rencana should include the foreseen objectives of the water resources development plans, highlighting the benefits, and outlining in detail the structural and non-structural actions required to reach the set water resources development activities for the basin.

2.4 Water resource planning and management in the EDB The Einlanden Digul Bikuma (EDB) is one of the 5 cross-boundary river basin territories in Indonesia, and water resources management in the basin is regulated by Central Government authorities. At the provincial level, the RBT is managed by the Balai Wilayah Sungai (BWS) Papua, with headquarters in Jayapura. BWS Papua is the local government authority responsible for the drafting of the Pola documents for the EDB basin. The government authorities responsible for spatial planning actions at the provincial and district levels are respectively Bappeda Provinsi and Bappeda Kabupaten. In the case of the EDB, Bappeda Provinsi Papua and Bappeda Provinsi Merauke are the spatial planning authorities responsible for planning actions at the two administrative levels. In this context, it is important to notice how, despite its high importance in terms of spatial planning at both the district and basin level, the Merauke Integrated Food and Energy Estate (MIFEE) project – discussed with more detail in section 6.2 of this report – is not being mentioned in the current planning program of the provincial Bappeda, but only in the district planning projects

Looking at the Pola for the EDB basin, this was first drafted in 2009, by a national consultant selected by BWS Papua. The draft document however has not been approved by the Directorate General of Water Resources in Jakarta because it lacked quality in its content and in the depth of the required analysis and, above all, because it did not formulate a future water resource management strategy for the basin. A revision of the strategic planning for the EDB basin has therefore been called upon, and BWS Papua selected a new national consultant to carry out the revision process of the document. At the time of Deltares and Pusair involvement in the JCP project, the new consultant was carrying out its revision process for the Pola.

With the investigation study on hydrological conditions in the EDB basin, the JCP component B project aimed to provide the qualitative and quantitative basis to support the revision process of the Pola by the hired consultant. This would take place by rendering available the findings of the hydrological modeling or all of the sub-catchments in the EDB basin, and by providing expert advice when and if needed.

16 3. ANALYTICAL APPROACH AND TOOLS The analytical approach for the implementation of the EDB case study has primarily involved two components: a. preparation of a hydrological model generating the discharge series for the major rivers in the EDB basin; b. the selection and definition of criteria for the design of a multi-criteria analysis aimed at the evaluation of possible water development strategies

3.1 Hydrological analysis A hydrological analysis is required to estimate water availability in time and space. To carry out the hydrological assessment in the Einlanden-Digul-Bikuma basin, the number of measurements available from the field was limited to a few discharge measurements for one location, which did not provide enough bases for the analysis.

This data poor condition in the EDB called for the use of global datasets produced with the use of remote sensing imaging. These inputs have been processed and integrated in an hydrological model to generate the discharge series for the main river catchments in the EDB basin.

The required steps to carry out the hydrological analysis have been the following:

1. Identification of the model to be used to produce the discharge series for the hydrological analysis; 2. identification of the required input for the hydrological model; 3. Identification and evaluation of the availability of resources for model input; 4. Preparation of the selected input in a format suitable for model input; 5. Running of the model with calibration; 6. Analysis of model results

The combination of these different steps and components of the hydrological modelling is shown schematically in Figure 3.1.

Simulation period The current study covers a time period of nearly 10 years, from 1 March 2002 to 1 December 2011, as determined by the availability of satellite derived rainfall data.

Simulation time step and spatial resolution The selected time step for the simulation of discharge time series is one day. For the analysis period above mentioned, this translates in a total of 3562 daily time steps.

The spatial resolution of input data ranges from a 90 metres grid for the topography to a 28 kilometres grid for the precipitation. For hydrological modelling a resolution of 270 metres has been selected as a compromise between topographical accuracy and calculation efficiency. To be able to generate discharge series for the catchments in the EDB basin, JCP Component B has decided to focus on the use of freely available software. This is because, upon completion of the case study, the Indonesian partners will still be able to access and use the same tools, independently of the involvement of Deltares in future projects.

The decision on the software to be used has led to the selection of the Open Source Geographic Information System (GIS) software Quantum GIS (or Q-GIS, http://www.qgis.org) used in combination with W-Flow (Schellekens, 2011), a distributed hydrological model developed at Deltares, and based on a dynamic GIS language called PCRaster (Karssenberg et al., 2001). Quantum GIS has been used for the data preparation phase, while W-Flow has been used for the generation of the river discharge series based on the input prepared with QGIS.

17

Figure 3-1 Overview of the analytical process for the hydrological analysis component of the EDB basin

Quantum GIS Quantum GIS is an open source geographic information system software developed by the Open Source Geo-Spatial Foundation (OSGeo). The tool supports several vector, raster, and database formats, such for

18 example ESRI shape files and GeoTIFF files. Most of the functions available with non-open source software (i.e. ArcGIS) are available within QGIS. Quantum GIS has been used in the phase of data preparation. For rainfall and evapo-transpiration datasets, the tool has been used for map resizing, namely in the process of map transformation from the original dataset input resolution format (i.e. 28 km * 28 km for TRMM rainfall map) to the selected input format to be used in the hydrological model (270m * 270m for W-Flow input maps).

W-Flow W-Flow is a distributed hydrological model developed at Deltares, and is an open source (GPL) model distributed at no cost and without any warranty.

As to the data input used in Q-GIS and subsequently in W-Flow, freely available datasets have been selected for data retrieval and elaboration. The different datasets are described in more detail in Chapter 4.

3.2 Multi-criteria analysis The need for a multi-criteria analysis in water resources management draws from the fact that water is not a single-use resource. While farmers need water for irrigation, urban dwellers rely on water for domestic water supply and daily small-business activities, national parks require water for the conservation of ecosystems, and governmental agencies for preservation or development of local infrastructure.

A water assessment study based on a number of criteria that take into account all of the different values attached to the water resource is therefore required during the implementation of Integrated Water Resource Management projects.

For the EDB case study, the selection of evaluation criteria has been formulated looking at who the major stakeholders in the basin were, and what were the most valuable benefits that these stakeholders were getting from the use of the water resource.

The process of definition of the multi-criteria analysis is described in more detail in Chapter 7.

19 4. GLOBAL DATASETS INPUT FOR HYDROLOGICAL ANALYSIS

The hydrological analysis aims to describe water availability by calculating time series of discharges for the rivers within the EDB basin. A number of input parameters need to be known to ultimately compute surface water flow with the use of a hydrological model. The required input parameters for W-Flow are: - Topography; - Precipitation; - Potential evapo-transpiration; - Land use and land cover types; - Soil types;

All of the above-mentioned input factors are nowadays freely available from regional and international research institutes that work in the field of natural resources management and remote sensing and are often available at the global scale, from which the naming global datasets.

During the development of Component B work, the global datasets that have been selected to perform the data preparation for the hydro-meteorological assessment have been:

- the NASA Tropical Rainfall Measuring Mission (TRMM) for precipitation data; - the NASA Shuttle Radar Topographic Mission (SRTM) for topographic data; - the GlobCover database of the European Spatial Agency (ESA) for land use and land cover data; - the FAO Harmonized World Soil Database (HWSD) for soil data; - the CGIAR-CSI Global Potential Evapo-transpiration dataset for evapo-transpiration data

In the following sections, a short description of the source and format of each of these data input is provided.

4.1 Precipitation

Figure 4-1 TRMM rainfall input dataset used for rainfall data preparation

Source NASA Tropical Rainfall Measuring Mission (TRMM) (http://trmm.gsfc.nasa.gov/) bias-corrected with methodology by [Vernimmen et al., 2012) Version 2012 Source format NASA TRMM: binary file type, 3hrs time resolution Resolution TRMM bias-corrected: raster (.map), approximately 28,000 m (0.25 degrees), daily time resolution

The primary source of rainfall data is the NASA Tropical Rainfall Measuring Mission (TRMM), which offers daily rainfall data for grid cells having a resolution of about 28 *28 km. TRMM is a joint

20 collaboration between the National Aeronautics and Space Administration (NASA) and the Japanese Aerospace Exploration Agency (JAXA) aimed to monitor and study tropical rainfall patterns. Vernimmen et al. (2011) developed a bias-correction procedure to improve TRMM data for Indonesia, based on a comparison of field and TRMM data. The resulting dataset has been used as an input for the preparation of the rainfall maps for W-Flow.

4.2 Evapo-transpiration

Figure 4-2 CSI-CGIAR input dataset used for the preparation of evapo-transpiration input maps

Source CSI-CGIAR Global-PET (http://www.cgiar-csi.org/2010/04/134/) Consortium for Spatial Information of the Consultative Group on International Agricultural Research (CSI-CGIAR) Global Potential Evapo-Transpiration Version October 2009 Source format ARC/INFO Grid, monthly time step Resolution 30 Arcsec (~ 1km at equator)

Information on potential evapo-transpiration patterns at the catchment level is needed to estimate evaporation from open-surface water bodies and transpiration of vegetation (forest and agricultural land). The Global Potential Evapo-Transpiration dataset of CSI-CGIAR has been used as input for the study. This data set provides average monthly values for the potential evapo-transpiration.

4.3 Topography

Figure 4-3 SRTM map of Indonesia Source: http://s239.photobucket.com/albums/ff165/keleher88/SRTM%20INDO/?action=view¤t=1ca0.jpg&newest=1

21 Source NASA Shuttle Radar Topographic Mission (SRTM) (http://dds.cr.usgs.gov/srtm/ ) Version 2007, Version 4 Source format ArcInfo (.asc), datum WGS84 Resolution 90m

In a GIS environment a topographic map is often referred to as a Digital Elevation Model (DEM). In the specific case of the SRTM dataset, this is not a true surface elevation model, but rather a canopy elevation model. SRTM well represents elevation patterns in steep areas but, due to the low vertical resolution of the model (1 meter), representation of elevation features in lowland areas is less accurate. Yet, for the purposes of this study, the SRTM datasets provides a good input for further data elaboration for topography at the basin and sub- basin scale.

4.4 Land use data

Figure 4-4 GlobCover land use input for the EDB catchment

Source European Spatial Agency (ESA) Ionia GlobCover (http://due.esrin.esa.int/globcover/) Version 2.3.2009 (Version 2.3) Source format Raster (.tif GeoTIFF file) Resolution 300m

For its completeness in terms of data availability, and for its satisfactory degree of spatial resolution, the European Space Agency GlobCover data has been selected to represent land cover types in the Einlanden-Digul- Bikuma catchment. GlobCover data have been collected by the Envisat environmental satellite, and provide a global land cover map with a 300 meters resolution, resulting from satellite image capturing run in the period January-December 2009.

GlobCover version 2.3 has 22 land cover classes defined in accordance with the UN Land Cover Classification System (LCCS) (Bontemps S. et al., 2011). These classes are listed in Table 4.1. Of the 22 land cover classes, a reclassification into 12 new classes has been performed to represent the predominant land types characterizing the EDB catchment. These classes are shown in Table 4.2. The assigned parameters values for each land cover type are reported in Annex 1.

22 Table 4-1 22 Land cover categories of the GlobCover map

Table 4-2 Selected land cover categories in the EDB catchment

23 4.5 Soil data

Figure 4-5 FAO HSWD input for soil mapping in the EDB catchment

Source FAO-IIASA Harmonized World Soil Database (HWSD) (http://www.iiasa.ac.at/Research/LUC/External-World-soil-database/HTML/) Version 1.1 (March 2009) Source format Raster file (.bil) linked to attribute database in Microsoft Access format Resolution 30 Arcsec (~ 1km at equator)

Information on soil characteristics is important for hydrological modelling because soil physical properties influence the patterns of the rainfall-to-runoff transformation, which is a process mainly driven by the infiltration capacity and the saturation hydraulic conductivity of soils, along with surface gradient. As for elevation, soil types geographical occurrence and soil physical properties are not features that vary in the short term, and this is the reason why we refer to the soil map as a static map.

The FAO-IIASA Harmonized World Soil Database is an improved version of the FAO Digital Soil Map of the World database updated with national and regional soil information provided by national research institutes. The HWSD database has been developed in partnership with ISRIC (World Soil Information independent knowledge centre), the European Soil Bureau Network (ESBN) and the Institute of Soil Science of the Chinese Academy of Science.

The HWSD soil dataset is available in a raster environment. A so-called HWSD Viewer - downloadable together with the HWSD dataset - provides a link between the raster database and the shape file describing soil type categories, occurrence and physical characteristics.

6 soil classes have been identified as being dominant in the EDB catchment. These categories are shown in Table 4.3. Table 4-3 Soil classes identified in the EDB catchment Soil code Soil family Texture class 4448 Acrisols Clay 4469 Acrisols Loam 4470 Cambisols Loam (4480) Cambisols Loam (4483) Leptosols Sandy Loam 4513 Leptosols Sandy Loam 4524 Fluvisols Clay 4555 Histosols Clay (4556) Histosols Clay

24 For each of these soil classes, 13 soil physical parameters required as an input for W-Flow have been defined. These parameters are described in more detail in Paragraph 5.6 of this report, while the values associated with each soil type are shown in Annex 1.

4.6 General overview on the EDB basin Given the above mentioned sources of datasets, an overview of the main climatic and morphological features for the Einlanden-Digul-Bikuma basin resulting from the input maps preparation process is described in short below.

In terms of topography, Figure 4.6 (left) shows how a large share of the EDB catchment area is a low-laying delta extending to the south and to the west of the basin, within an elevation range below 50 meters. On the contrary, the northern part of the catchment shows high elevation ranges above 1,000 meters in the most northern part, and above 500m just south of it. In terms of land cover1, Figure 4.6 (right) shows that a large part of the catchment is covered with closed to open (15%) broad leaved evergreen forest, mixed with semi-deciduous forest (land cover class 40). Based on the land cover classes provided by the input dataset GlobCover, figure 4.6 further shows that in the western part of the basin, the geographic area covered with land type class 40 gets regularly flooded, with the lighter green area (class 170) representing land regularly flooded by saline water, and with the darkest green area (class 160) representing land regularly flooded by fresh water. Yet, a mixture of other land cover categories exist within the basin, with category 20 (red colour) representing a mix of mosaic crop land (50- 70%) and vegetation (50-30%).

Figure 4-6 Elevation Map (left) and land cover map (right) for the EDB basin

In the EDB basin, 10 different soil types have been identified based on the FAO HWSD input dataset. Of these 10 categories, some are more predominant than others. In the majority of the low-lying area, soil types are of the category Fluvisol (dark green color, category 4524) and Histosols (pink color, category 24555). Both soil categories have high clay content, which suggests that while the water retention capacity of the soil is high, the fertility of the soil is moderate given the – on average – little content of organic matter. In the slightly higher elevation are (51-80m), soils seems to be also characterized by clayey content, with the soil category being classified as an Acrisol (dark blue color, category 4448). Soil porosity in Acrisols is

1 Please consider that the colors reported in Table 4.2 and 4.3 do not correspond to the colors reported in Figure 4.6.

25 moderate for forested land. However, when forest is cleared, Acrisols soil surface degrades forming a hard surface crust (Isric, undated) causing erosion and hampering soil water infiltration.

In its higher elevation areas, the EDB catchment is characterized by more sandy-loamy soils (soil categories 4513, 4483 and 4480).

Looking at the climate aspects proper of the EDB basin, precipitation and evapo- transpiration conditions vary temporally (on a daily basis) and spatially (mountainous versus coastal regions). As a consequence, the maps shown in Figure 4.8 only represent a snapshot of satellite data for a specific time period (June 2002 for evapo-transpiration, and 5th March 2002 for the precipitation map). Figure 4-7 Soil map of the EDB basin

In general terms, for the 10 years observation period, evapo-transpiration in the EDB basin varies in a range between 50 mm/month (June) and 180 mm/month (December), with the rate being the highest in the south- eastern part of the catchment (kabupaten Merauke) during the period September to December (130 to 180 mm/month). The intermediate area covering kabupaten Mappi, Boven Digul and Asmat is the area with highest potential evapo-transpiration rates in the rest of the year (January to August). Throughout the year, the mountaineous areas of he catchment located to the north (kabupaten Pegunungan Bintang, Jayawijaya, Yahukimo, Tolikara) are the areas with lowest potential evapo-transpiration rates.

Figure 4-8 Monthly evapo-transpiration (left) and daily precipitation (right) map for the EDB basin

Precipitation in the EDB basin show higher rainfall monthly ranges in the northern part of the catchments (annual average rainfalls above 4,000 mm/year) with decreasing patterns in the central (3,000-4,000 mm/year) and coastal areas (1,600-2,000 mm/year). Rainfall patterns at the catchment and sub-catchment scale are described in more details in paragraph 5.2.

26 5. HYDRO-METEOROLOGICAL ANALYSIS The hydro-meteorological analysis has been executed using W-Flow for the hydrological component, and using statistical tools for the meteorological part.

5.1 Catchment delineation To study the hydrological conditions characterizing the EDB basin, we first needed to define the hydrological boundary conditions of the catchment as a whole, which results from the aggregation of the multiple sub-catchments which the EDB embraces.

A hydrological catchment boundary is the line defining the topographic area contributing to the discharge of a river. The delimitation of the boundary condition is determined by local topography (distribution of elevation), which in turn determines the water flow pattern based on the surface gradient. W-Flow delineates the catchment boundaries based on the LDD script (Local Drainage Direction), which computes the slope of the terrain by comparing the elevation in neighbouring cells from the elevation gridded layer provided as an input. Based on the difference in elevation, W-Flow identifies a surface flow path which water will follow. Figure 5-1 Example of Local Drainage Direction map

The catchment delineation steps with W-Flow also required to identify a number of gauging stations along the river shape. These are the points for which the modelled river discharge time series will be provided by the model. The first gauging point has to represent the outlet of the catchment.

Generally speaking, in a catchment the elevation of the river bed is the lowest. In order to avoid disturbance of vegetation cover in the input digital elevation map (SRTM), we burned an existing river layer into the SRTM map by providing an elevation of -200 meters to all the points in the line identifying river features. With this operation we forced W-Flow to identify the river with the lowest altitude, eventually inducing the model to collect all surface water in the river system.

The required input maps used for the catchment delineation of the sub-catchments of the EDB are: - the SRTM elevation map; - the river layer

The catchment delineation operation produced the outcome illustrated in Figure 5.2. The initial outcome of the W-Flow computation led to the identification of 18 river sub-catchments within the morphological boundaries of the EDB river basin (Figure 5.2 left). However, taking into consideration the international boundary with Papua New Guinea (PNG), it resulted that 3 sub-catchments are shared between Indonesia and PNG. Following the selection of the EDB sub-catchments based on administrative boundaries, the final catchment delineation for the EDB basin is the one shown in Figure 5.2 (right side). The Fly river catchment has been excluded from the analysis, since the majority of the catchment is located in Papua New Guinea. Based on the results of the delineation, 17 main sub-catchments were identified in the EDB basin, for a total surface area of around 133,000 km2. Of these basins, two (Maro and Sakiramke) are shared basins with neighbouring Papua New Guinea (PNG). In figure 5.2 the vertical line identifiable on the right side of the catchment shape represents the administrative border with Papua New Guinea.

27

Figure 5-2 Results of the catchment delineation process with W-Flow

Figure 5.2 clearly shows that the EDB consists of a few large catchments, some middle size catchments, and a larger number of small catchments, especially along the coastal areas. The biggest catchment is the Einlanden catchment with a surface area of about 37,000 km2. It is located in the North-Western part of the EDB basin, and is predominantly characterized by high elevation ranges (up to 4,300m) and forest land cover in the northern part, and by a rapidly decreasing elevation in the central and southern parts. The second-largest sub-catchment is the Digul river catchment, which covers an area of about 30,000 km2, and which shows a variability of altitude and land cover type dependent on the distance from the coastal area. Table 5.1 presents a comprehensive list of all the catchments in the EDB basin, with their surface area coverage.

Table 5-1 The 17 sub-catchments of the EDB basin Catchment ID Sub-catchment Area (km2) Catchment ID Sub-catchment Area (km2) 1 Bian 10,005 10 Kumbe 4,434 2 Buaya 2,222 11 Lorentz 4,169 3 Buede 7,929 12 Mappi 8,307 4 Digul 29,712 13 Maro 8,709 5 Einlanden 37,164 14 Mengan 6,766 6 Fajit 549 15 Muli 2,538 7 Imenoe 1,177 16 Sakiramke 5,222 8 Jeitja 1,555 17 Sanuna 597 9 Juliana 1,746 Total EDB 132,801

The EDB catchment takes the name from the Einlanden, Digul and Bikuma (Bian, Kumbe and Maro) catchments, which overall represent around 70% of the total catchment area, and the largest cumulative river discharge flow of the entire basin.

28 5.2 Precipitation patterns Based on the original precipitation ranges defined by [Oldman et al., 1980] according to which a wet and dry month are defined by, respectively, a 200mm and 100mm of mean monthly rainfall, precipitation patterns in the EDB basin have been re-classified using the TRMM-bias corrected input provided by [Vernimmen et al., 2012]. The results of the re-classification – based on the 10-years available satellite records – are shown in Figure 5.3. Based on this reclassification, the EDB basin is characterized by 6 predominant agro-climate zones

Figure 5.3 shows that the drier areas within the EDB basin are located in the southern part of the catchment where the number of wet months in a year progressively decreases from 6 to 3, and with the number of dry months increasing correspondingly. Based on the results of the reclassification, kabupaten Merauke is the driest kabupaten within the EDB basin. The northen part of the basin shows rainfall patterns with at least 9 months in a year with precipitation higher than 200mm/month.

Figure 5-3 Oldeman agro-climatic zones based on TRMM bias-corrected precipitation input

Based on the bias-corrected TRMM input data for precipitation, the average rainfall in the EDB catchment has been estimated to reach 2760 mm/year. Yet, rainfall patterns show high variability, both in terms of location and time. For the same observation period (2002-2011), average annual rainfall can vary between a total of 1650mm/year for sub-catchments located in the south-eastern part of the basin (Sakiramke sub-catchment), to 4240 mm/year for catchments which are more upstream (Lorentz sub-catchment). These findings show a positive correlation between precipitation on the one hand, and elevation and distance from the coast on the other. Table 5.2 provides the average annual precipitation values for the 17 catchments in the EDB.

Table 5-2 Average annual rainfall in the EDB sub-catchments P P Catchment ID Catchment (mm/year) Catchment ID Catchment (mm/year) 1 Sanuna 4047 10 Maro 2002 2 Mappi 3577 11 Kumbe 1951 3 Lorentz 4238 12 Sakiramke 1648 4 Jeitja 3470 13 Muli 1862 5 Einlanden 3970 14 Menggan 1947

29 6 Fajit 3938 15 Imenoe 1807 7 Digul 3645 16 Buede 1829 8 Bian 2317 17 Buaya 1674 9 Juliana 2992 Total average 2760

Figure 5.4 clearly shows the correlation between distance from the coast and precipitation, with areas along the coast receiving on average up to a third of the annual rainfall totals of catchment areas in the mountainous regions.

Figure 5-4 Precipitation variability based on distance from the coast and elevation

At the basin scale, rainfall variability is also high when considering month to month variation and seasonal patterns. The dry season runs indicatively from May to September/October, while the bulk of the precipitation occurs in the wet period lasting from November till April. The distribution of rainfall between dry and wet season in the EDB basin is shown in Figure 5.5.

Wet and dry season rainfall totals (mm)

Average wet season 4,500 Averarage dry season 3,500 2,500 1,500 500

Precipitation (mm) Precipitation -500

Muli Maro Bian Jeitja Digul Fajit Buaya Buede Mappi Imenoe Kumbe Juliana SanunaLorentz Menggan Sakiramke Einlanden Sub-catchment

Figure 5-5 Distribution of annual rainfall between wet and dry season for the 16 EDB sub-catchments

From the graph, two main considerations can be drawn: o the EDB sub-catchments receiving higher volumes of rainfall are located in the North-Western parts of the basin, while catchments located in the South and South-East are the ones receiving least rainfall;

30 o there is a relation between the total annual rainfall range and the percentage distribution of rainfall within the dry and wet season, with catchments having lower annual totals showing lower percentage of rainfall during the dry season, as reported in Table 5.3.

Table 5-3 Dry season rainfall as percentage of annual rainfall by rainfall range Annual precipitation range Percentage of dry season rainfall (mm/year) to annual rainfall (%) 1,600 – 2,000 23 2,001 – 3,000 31 3,000 – 4,300 44

The difference in rainfall distribution patterns depending on the geographical location within the basin is further illustrated in Figure 5.6. The graph shows that, the divergence in monthly rainfall between northern (Digul) and Southern (Bi-Ku-Ma) sub-catchments is higher during dry season months as compared to wet season months. In turn, this means that the dry to wet season rainfall variation within the same catchment is higher for catchments located in the south.

450

400

350

300 Bian 250 Maro 200 Kumbe Digul 150

100 Precipitation (mm/month)

50

0 1 2 3 4 5 6 7 8 9 10 11 12 Month

Figure 5-6 Comparison of selected EDB sub-catchments hyetographs

5.3 Discharge patterns

Discharge patterns in the EDB catchment have been defined at the level of the 17 sub-catchment. Daily discharge values have been generated with W-Flow, using the input maps prepared with QGis. To monitor the modelling of the rainfall to runoff transformation, a number of gauging stations have been defined for each catchment depending on location (upstream, middle reach and downstream sections). For the 17 EDB sub-catchments, a total of 48 gauging stations have been created, and the daily discharge series are available for each of these 48 points in the basin. For each sub-catchment there is a so-called outflow gauging point representing the point of outlet for the discharge of a single sub-catchment. The outflow gauging points are listed in Table 5.4.

31 Table 5-4 Outflow gauging points of the 17 EDB sub-catchments Sub-catchment Outflow Sub-catchment Outflow Sub-catchment Outflow gauging point gauging point gauging point Lorentz 4 Kumbe 30 Buaya 39 Einlanden 11 Maro 34 Buede 42 Digul 15 Fajit 35 Imenoe 43 Mappi 19 Sanuna 36 Muli 44 Menggan 22 Jeitja 37 Sakiramke 48 Bian 26 Juliana 38

Computed at this outflow gauging stations, the 9-year (2002-2011) average monthly discharge patterns of the 17 identified sub-catchments is summarized in Table 5.5. The table excludes the values for the Bian catchment since, as further explained later, the model discharge results did not provide a realistic representation of the model precipitation inputs.

Table 5-5 Average monthly discharge patterns of 16 EDB sub-catchments (m3/s) Annual Jan Feb March Apr May Jun Jul Aug Sep Oct Nov Dec Buaya 53 70 102 95 102 42 23 9 8 10 23 61 92 Buede 241 377 511 487 492 205 93 38 14 9 55 203 412 Digul 2,127 2,205 2,635 2,870 2,628 2,329 1,608 1,122 1,090 1,333 2,077 2,731 2,892 Einlanden 3,133 2,821 3,398 3,380 3,486 3,601 2,889 2,161 1,946 2,693 3,519 3,828 3,869 Fajit 48 37 38 57 54 57 46 28 29 47 64 70 52 Imenoe 35 58 83 68 82 36 18 4 1 4 8 17 46 Jeitja 96 76 86 120 112 96 76 51 47 87 139 144 123 Juliana 95 79 97 123 122 98 57 38 29 62 125 148 165 Kumbe 131 211 227 294 255 103 48 15 15 20 55 125 201 Lorentz 380 413 438 416 431 401 350 269 224 365 388 463 401 Mappi 580 530 659 727 737 650 410 242 216 341 629 861 955 Maro 222 361 433 564 448 187 76 33 22 31 56 154 299 Menggan 201 313 421 386 407 168 74 21 15 17 59 200 335 Muli 80 120 165 142 199 88 46 8 1 5 25 46 115 Sakiramke 96 173 226 298 227 75 17 8 2 4 10 25 86 Sanuna 51 39 42 58 57 56 46 28 28 49 69 75 59

Total_16 7,569 7,883 9,561 10,085 9,839 8,192 5,877 4,075 3,687 5,077 7,301 9,151 10,102

The results of the W-Flow modelling show that the estimated annual discharge for the overall EDB basin amounts to around 8,000 m3/s, varying in a range between 4,000 and 10,500 m3/s in the dry and wet season respectively. In terms of annual discharge, the main 5 rivers in the basin are the Einlanden (3,133 m3/s), Digul (2.127 m3/s), Mappi (580 m3/s), Bian (392 m3/s) and Lorentz (380 m3/s). All the other rivers in the basin have an estimated average annual discharge below the 250 m3/s.

32

Figure 5-7 Location of the EDB catchments with larger annual discharge

Figure 5.7 clearly shows that the 4 of the 5 main contributors of discharge in the EDB are located in the northern part of the catchment, where the wet season is longer. In the southern area, the catchment of the river Bian is the 4th largest contributor in terms of river discharge.

Figure 5.8 provides an overview of the discharge values for the 17 sub-catchments listed in Table 5.5.

Figure 5-8 Annual average discharge patterns of the EDB sub-catchments

Figure 5.8 shows that the Einlanden and the Digul rivers are the two main contributors to the river discharge of the EDB basin. Together, these two rivers alone make up for the 66% of the total discharge in the basin. With the river Mappi, whose annual average discharge is estimated in 580 m3/s, the 3 rivers make up for 73% of the total EDB basin discharge.

A closer look at the patterns of river discharge depicted in Figure 5.8 is provided in Figure 5.9, which projects the hydrographs of the EDB sub-catchments excluding the largest rivers (Einlanden, Digul, Mappi and Bian). The shapes of the hydrographs of the smaller catchments clearly define the sub-

33 division between the wet and the dry season, the latter taking place between the months of June to September.

The hydrograph of the river Bian has been omitted from Figure 5.9 because results did not correspond in the expected way with the rainfall pattern for this sub-catchment. In order to avoid bias in the interpretation of results, the Bian sub-catchments has been excluded from the rest of the discharge analysis.

Figure 5-9 Monthly discharge patterns of low-discharge rivers in the EDB

Figure 5.9 shows that while for the rest of the sub-catchments the discharge pattern between dry and wet season is quite uniform, for the Lorentz sub-catchment the variation in discharge between dry and wet season is less evident. To verify the quality of the model results, we have compared the monthly precipitation patterns with the discharge monthly values for the Lorents river. From this comparison we have identified no inconsistent correspondence. The shape of the hydrograph of the Lorentz river is the results of the high input in precipitation received by the catchment throughout the year. Given the location of the catchment in areas of high elevation, we expect that evapo-transpiration is lower, and that therefore there is a closer rainfall to runoff transformation, resulting in higher monthly values of river discharge. Taking into account this clear seasonal discharge pattern, the estimated dry and wet period discharge for the EDB basin as a whole amount to about 5,000 m3/s during the dry period, and to 9,400 m3/s during the wet period. Based on these figures, the variation in total basin discharge between the wet and dry season is estimated in 47% of the wet season flow.

Figure 5.10 shows that for the EDB sub-catchments having low annual discharge patterns, the average dry season monthly discharge is very low except for the Jeitja river, all other rivers depicted in the figure show during the month of July and August an average monthly discharge below 50 m3/s.

34 Monthly average discharge EDB sub-catchments (All but Einlanden, Digul, Mappi, Lorents and Bian)

200 Menggan 175 Kumbe 150 Maro Sakiramke 125 Fajit 100 Muli Sanuna 75 Jeitja 50 Juliana Buaya 25 Buede 0 Imenoe 5 6 7 8 9 10 Month

Figure 5-10 Dry season monthly discharge for small EDB sub-catchments

Due to the scarce availability of field data, we have been unable to compare these model results with actual observations. We therefore would like to emphasize that the model output requires validation with field measurements to be used as a reference for qualitative judgments regarding monthly and dry season water availability in terms of river discharge. Yet, to test the consistency of the model output with the provided model input, we have compared the cumulative discharge in the small EDB basins with the cumulative average precipitation input received by these sub-catchments. Results are shown in Figure 5.11, which provides a focused overview (May to October months) on the dry season discharge for these small catchments. The graph shows a clear correspondence between received rainfall and rivers’ discharge. Based on the data input, we therefore conclude that discharge modelling with W-Flow is consistent with the precipitation input data provided at the initial stage of the analysis. .

3000 1,400 P (mm/month) Q (m3/s) 1,200 2500

1,000 2000 800 1500

600 (m3/s) Q

P (mm/month)P 1000 400

500 200

0 0 5 6 7 8 9 10 Month

Figure 5-11 Comparison of cumulative dry season rainfall and discharge for selected EDB sub-catchments

5.4 Frequency analysis A discharge frequency analysis has been carried out for the 5 main rivers in the EDB basin, and for the Kumbe and Maro rivers because of their importance for the southern part of the EDB basin, where most people live. With the aim to identify different ranges of dependable river flow, we have analyzed the 10, 20, 50, 80 and 90 percentiles of the monthly river discharge for each of the above mentioned catchments.

35 The discharge value corresponding to the 10th percentile of the simulated discharge time series represents the discharge that is not exceeded during 10% of the time series. It therefore presents an indicator of the dependable low flow. In a similar way, the 80th percentile discharge value corresponds to the discharge that is not exceeded during 80% of the simulated time series. It therefore presents an indicator of the dependable high flow. The 50th percentile represents the median value for the simulated time series.

Table 5.6 summarizes the results for the 7 selected rivers in the basin for monthly and total annual flow.

Table 5-6 Dependable flow (m3/s) for 7 selected rivers of the EDB basin

36 From the data in Table 5.6 it can be concluded that the amplitude of change between the dependable flow in the dry season and the mean annual value is stronger then the variation taking place between the mean discharge value and the dependable flow during high flow months. This means that the intensity of dry periods is stronger than for wet periods. A second observation from the results of Table 5.6 is that for small rivers such as the Kumbe and the Maro, the dependable low flow in the dry season (August and September) approaches a flow rate of 1 m3/s. These seem to be extremely high low figures for river discharge. As underlined in the previous paragraph, the parameterization of W-Flow discharge computation might require further refinement, but in the absence of a field data to compare the modelled output, we suggest that these figures should be used only in qualitative terms if no comparison with field measurements can be performed.

5.5 Water balance analysis and validation of model output

A water balance analysis is the computation of the flow of water into and out of a catchment and the change in volume of water within the catchment. The water balance equation can be represented as:

Inflows (precipitation) = Outflows (discharge, evapo- transpiration, deep percolation) + Storage

The discharge component of the outflow is composed of surface and sub-surface runoff. When the underground contribution to surface river flow is negligible, the average annual water balance can be reduced to (van der Weert, 1994): Figure 5-12 The water cycle components Source: http://www-k12.atmos.washington.edu

Evapo-transpiration = Precipitation – Runoff

In the case of river basin modelling, where it is not possible to compare modelled data with field data due to the scarcity of reliable measurements, a water balance analysis can help in the validation of the model. Van der Weert (1994) presents a characterization of hydrological conditions of different regions of Indonesia based on the quantification of the different components of the water balance equations (precipitation, discharge and evapo-transpiration) and identifying regional patterns depending on the area’s precipitation and temperature regimes. The reference values provided by van der Weert for Papua are used in this study to validate the W-Flow input parameters. The annual catchment rainfall to runoff relation identified by van der Weert is presented in Figure 5.13. The relation can also be expressed with a formula, depending on the annual precipitation range:

Q = 155 * (P/1000)2.5 for P< 1,800 mm/yr Q = 0.94 * P – 1018 for P> 1,800 mm/yr where: Q = average runoff (mm/year) P = average rainfall (mm/year)

Figure 5.13 presents a comparison of the simulated rainfall-runoff values for the EDB sub-catchments with rainfall-runoff curve presented by Van der Weert.

37

Figure 5-13 Comparison of rainfall-runoff relation as derived by Van der Weert (1994) and model results

Figure 5.13 shows a very good correspondence between the modelled data and the study of van der Weert, showing that on average, the percentage of rainfall that transforms into runoff is about 55%, varying in a range of 35 to 70% depending on the catchment. The computed values for each catchment are shown in Table 5.7.

Table 5-7 Rainfall and runoff modeled values in the EDB Average P Average Q Average Q Estimated ET Catchment Mm/year mm/year % % Buaya 1,674 752 45 55 Buede 1,829 959 52 48 Digul 3,645 2,258 62 38 Einlanden 3,970 2,659 67 33 Fajit 3,938 2,757 70 30 Imenoe 1,807 938 52 48 Jeitja 3,470 1,947 56 44 Juliana 2,992 1,716 57 43 Kumbe 1,951 932 48 52 Lorentz 4,238 2,874 68 32 Mappi 3,577 2,202 62 38 Maro 2,002 804 40 60 Menggan 1,947 937 48 52 Muli 1,862 994 53 47 Sakiramke 1,648 580 35 65 Sanuna 4,047 2,694 67 33

Based on these results, it appears that catchment with lower percentage of discharge are located in the southern and south-eastern parts of the EDB basin (Kumbe, Maro, Sakiramke), while sub-catchments with higher values of the rainfall to runoff transformation are located in the north-western part of the basin (Faijt,

38 Lorentz, Einlanden). This means that the runoff percentage increases with higher rainfall, which is in accordance with the findings of Van der Weert.

Table 5-8 presents the simulated monthly runoff coefficients for the Einlanden, Digul, Mappi, Bian, Kumbe and Maro sub-catchments, computed in m/month.

Table 5-8 Monthly runoff coefficient values for selected EDB sub-catchments 1 2 3 4 5 6 7 8 9 10 11 12 Annual Einlanden 0.6 0.7 0.6 0.7 0.7 0.7 0.6 0.6 0.6 0.7 0.7 0.7 0.66 Digul 0.6 0.7 0.6 0.7 0.7 0.6 0.5 0.5 0.5 0.6 0.6 0.7 0.60 Mappi 0.6 0.6 0.6 0.6 0.7 0.6 0.5 0.5 0.4 0.6 0.6 0.8 0.59 Kumbe 0.5 0.6 0.5 0.7 0.5 0.4 0.2 0.2 0.1 0.2 0.4 0.5 0.40 Maro 0.4 0.5 0.5 0.6 0.5 0.3 0.2 0.2 0.1 0.1 0.2 0.3 0.33

Data from Table 5.8 are represented in Figure 5.14. The graph shows a lower runoff coefficient value during the dry months of June to October. Compared with the definition of dry season based on rainfall threshold values (May to September), we can conclude that the there is about 1 month lag period between a reduction in rainfall and a reduction in river discharge. Moreover, the figure shows that the variation in runoff coefficient is higher for small catchments (Kumbe and Maro) as compared to catchments with higher annual discharge values (i.e. Einlanden and Digul). This pattern results from the fact that larger catchments receive, on average, higher total amounts of rainfall through the year as compared to small south-eastern coastal catchments which receive the bulk of the precipitation input only during the wet season. With a higher average monthly precipitation input, the contribution to river discharge is more constant over time. Yet, reduced river discharge in small sub-catchments during the driest months is also the results of higher evapotranspiration values in the non-mountainous regions of the catchment.

Figure 5-14 Monthly runoff coefficient for selected EDB sub-catchments

For the large catchments of the Einlanden, Digul and Mappi, the variation in the runoff coefficient values [0.4-0.7] is smaller than the variation in the runoff coefficient values of smaller and more southern catchments like the Kumbe and Maro, for which the range of variation is [0.1-0.7]. This means that the smaller catchments are more sensible to variations in precipitation, than the larger catchments.

5.6 Sensitivity analysis A sensitivity analysis has been performed to test what is the influence played by different input model parameters in determining river discharge. The analysis aimed to test how sensitive river flow is to changes in

39 variables such as, for example, soil infiltration capacity or soil rooting depth. The sensitivity analysis should contribute to a better understanding of model behavior and more confidence in its results.

The river Kumbe has been selected as the sub-catchment for the sensitivity analysis testing. For this catchment, the values of 18 parameters have been multiplied by a factor of 2 to determine their impact on simulated river flow. The test has been run on a time period of 30 days during a wet season month (high initial soil water saturation capacity) and a rainfall event of 100 mm/day has been simulated on day 5. The list of parameters, with their initial and modified values is presented in Table 5.9 below.

Table 5-9 List of tested parameters for the sensitivity analysis Parameter name Initial valueSensitivity valueParameter name Initial valueSensitivity value Albedo 0.20-0.35 0.4-.07 InfiltCapSoil 60-600 120-1,200 Beta 0.6 1.2 LeafAreaIndex 3.7-6.2 7.4-11.6 CanopyGapFraction 0.4-1 0.8-1 M 2,500 1,250 EoverR 0.05 0.1 MaxCanopyStorage 1-2.6 2-5.2 FirstZoneCapacity 10,000 20,000 N 0.02-0.4 0.04-0.8 FirstZoneKsatVer 8.6-864 17.2-1,728 N_River 0.045 0.09 FirstZoneMinCapacity 10,000 20,000 PathFrac 0.05-0.4 0.1-0.8 InfiltCapPath 5 10 RootingDepth 900-1,900 1,800-3,800 ThetaR 0.05-0.08 0.1-0.16 ThetaS 0.2-0.5 0.4-1

The results of the sensitivity analysis run are shown in Figure 5.15 for those input parameters that have a significant effect on river discharge. A short description of the influence of the parameters on the river’s hydrograph is provided below.

Figure 5-15 Results of the sensitivity analysis test for the river Kumbe

FirstZoneCapacity: maximum water retention capacity of the soil saturated store, measured in millimeters. Doubling of the FirstZoneCapacity increases the depth of the soil, and produces a situation in which at the initial state, the soil water retention capacity is no longer at its maximum. For the augmented water retention capacity of the soil, less runoff is produced and more rainwater is stored into the ground. This significantly reduces the peak discharge of the hydrograph.

FirstZoneKsatVer: saturated conductivity of the soil at the surface.

40 A doubling of the saturated conductivity of the soil at the surface increases the hydraulic conductivity of the soil, and accelerates the rainfall to runoff process in its sub-surface flow component. The outflow of water from the subsurface is faster, and this causes higher river runoff.

M: soil parameter determining the decrease of soil saturated conductivity with depth. The M parameter has been halved as compared to the original value because deemed to high. A lower value of M makes the decrease in soil hydraulic conductivity lower, causing lower runoff from groundwater.

MaxCanopyStorage: the maximum storage capacity of the canopy cover. A doubling of the maximum storage capacity of the canopy cover increases rainfall interception by the vegetation canopy, increasing the volume of water that evaporates.

N: Manning roughness parameter. A doubling of the N manning coefficient delays overland flow, therefore delaying the surface runoff to the river, and stretching the peak of the hydrograph.

N_river: Manning parameter for the river. A doubling of the Manning parameter for the river slows down river runoff, which produces a delaying effect on the river hydrograph, stretching its peak.

ThetaR: soil residual water content. A doubling of the soil residual water content results in a lowering of the maximum available soil water content (maximum available soil water content is ThetaS - ThetaR). This means that at the initial state, there is more water than the soil can hold. That residual water makes the runoff in the beginning extreme high.

ThetaS: soil water content at saturation. A doubling of the soil water content at saturation produces that in the initial state the soil is not saturated with water, leaving more room for further infiltration, and therefore slowing down the rainfall to runoff transformation, and therefore slightly decreasing the contribution of rainfall to river discharge.

41 6. WATER DEMAND

Chapter 6 provides an overview of the water demand components in the EDB basin. Following a brief presentation of the main water demand sectors, focus is given to the development of the agro-industry project of MIFEE, an integrated food and energy production initiative developing in the Merauke area, which is expected to have a major impact on water demand.

6.1 Current water demand Water demand in the Einlanden-Digul-Bikuma basin mainly consists of water demand for domestic consumption and irrigated agriculture. Some small businesses use an insignificant amount. No large industrial activities are present. In the higher reaches of the basin there are a number of small hydropower plants which supply electricity to the local population, but their functioning is not water consuming.

The EDB basin has some 524,000 inhabitants, of which nearly a third live in kabupaten Merauke. The basin figure represents about 18% of the total population in Papua province (2,852,000 inhabitants), and only 0.22% of the current total population of Indonesia (237.6 million). The other two high-density populated areas are kabupaten Jayawijaya and kabupaten Yahikimo. Together these two kabupaten account for 47% of the population in the basin. Population, area and population density figures for the 8 kabupaten of the EDB basin are summarized in Table 6.1. These population data are sourced from a GIS map of the Indonesian DESA supplied by Pusair. Figure 6-1 Kabupaten in the EDB basin

Table 6-1 Population statistics for the EDB basin, 2005 Population Population Kabupaten Population percentage Area (km2) density of total (%) (inh/km2) ASMAT 36,790 7 10,549 3 BOVEN DIGOEL 9,394 2 28,097 0 JAYAWIJAYA 137,805 26 3,724 37 MAPPI 34,054 7 24,287 1 MERAUKE 150,436 29 43,164 3 PEGUNUNGAN BINTANG 39,361 8 8,112 5 TOLIKARA 6,625 1 694 10 YAHUKIMO 109,303 21 10,847 10 Total 523,768 100 129,473 9

Public water supply to the population is essential, and has high priority according to the Indonesian Water Law. Current water supply for the city of Merauke is mainly sourced from the Rawa Biru swamp, located in the eastern part of the district, along the border with Papua New Guinea. Currently, water quality from this source is reported to be of good standards, but local authorities showed concerns

42 about quantitative aspects should population in the area increase in the future. At the small scale, there exist a number of shallow wells in the urban areas, but supply is not constant over time, and quality of water is increasingly affected by salinity intrusion as reported by the local inhabitants.

An estimate of the water requirements for public water supply based on the population figures of Table 6.1 and on an average water consumption of 120 liters/capita/day shows that the required daily water supply for domestic purposes for the entire EDB catchment can be estimated in 0.73 m3/s. Comparing this domestic water demand with the water availability resulting from river discharge in the basin, it can be conclude that in quantitative terms, the EDB basin supplies a sufficient amount of water to meet the domestic water requirements. However, it should be reminded that other constraints may impinge on the actual water demand figure and water availability if one takes into consideration factors such as for example water quality (filed visits revealed that communities in the Merauke area were affected by the presence of sulfuric water) and the actual existence of piped water distribution systems (the piped water supply system is in poor conditions in Merauke, and it is non existent in other parts of the catchment).

Water requirements for irrigation in the EDB basin are difficult to quantify for a number of reasons: - lack of reliable information on the cultivated and irrigated areal extent; - lack of information on the type of crops irrigated; - lack of information on crop intensity (number of harvest per year)

Among irrigated crops, paddy cultivation is predominant. When seeding occurs at the end of the wet season, irrigation is required to supply a sufficient volume of water for non-deficit crop growth during the development and growth stages of the cereal. A second harvest of irrigated rice is obtained only from a small fraction of the total irrigated area and depends for a much larger part on irrigation to fulfil its water requirements.

Irrigated agriculture and water supply for cultivation is of particular importance in the EDB catchment for the large scale foreseen development of the Merauke Integrated Food and Energy Estate (MIFEE) programme. The initiative will be discussed more in detail in section 6.2, which also includes an estimation of irrigation water requirements for paddy, oil palm and sugar cane.

In addition to the above, there is also a water demand component aimed to preserve ecosystems and the services by them provided. This is for example of special importance for national reserves, and other natural areas having a rich biodiversity. Yet, ecosystem services also include minimum volumes of water flow in rivers to accommodate navigation purposes. With the aim to ensure a minimum river flow preserving ecosystem services, in 2011 Government Regulation number 38/2011 on Rivers was put into force. Following regulation approval, Indonesian local authorities need now to ensure a minimum river flow with 95% probability of exceedance in all river reaches. This still seems to be a too low threshold to ensure ecosystem preservation, but yet it represents a first attempt to address ecosystem services requirements in the framework of national regulation.

6.2 The MIFEE project and its water requirements MIFEE is the Merauke Integrated Food and Energy Estate project, officially launched in August 2010 by the Indonesian Minister of Agriculture Suswono. The project is a revised version of the MIRE, the Merauke Integrated Rice Estate project first envisaged in 2006. The MIRE foresaw the conversion of about 2.5 million hectares of land to agricultural land in the Eastern part of Papua province [Manikmas, 2010], mainly including the area of kabupaten Merauke, and parts of kabupaten Mappi and Boven Digul.

Inspired by MIRE, the original plan of MIFEE involved the development of an area of about 2.5 million hectares for rice and energy crop cultivation. Yet, different figures are provided by various sources concerning the extent of allocated area based on crop type. Some of the figures available are reported below:

43

Source A: Rencana Tata Ruang Wilayah (RTRW) – Merauke strategic spatial planning agency Year: 2011-2012 Total MIFEE area: 1.23 M ha Crop/land allocation: 50% food crops (615,000 ha), 30% sugar cane (369,000 ha), 20% oil palm (246,000 ha)

Source B: Down to Earth, International Campaign for Ecological Justice in Indonesia Year: Nov 2011 Total MIFEE area: 1,282,833 hectares, of which: ƒ 423,251 ha in period 2010-2014 ƒ 632,505 ha in period 2015-2019 ƒ 227,077 ha in period 2020-2030

Source C: https://awasmifee.potager.org/uploads/2012/03/mifee_en.pdf Year: 2012 Total MIFEE area: 1,834,656 hectares Crop/land allocation: 25% Sugar cane, 30% Oil palm, 33% Timber industry, 6% rice, 5% maize, 1% food crops

Source D: Directorate Spatial Planning (Direktorat Tata Ruang dan Pertanahan BAPPENAS) Year: 2010 Total MIFEE area: 1.28M ha Crop/land allocation: Short term: 423,000 ha (of which 300,000 ha of productive conversion forest (HPK)) Medium term: 631,900 ha (of which 630,000 ha HPK) Long term: 226,000 ha (of which 197,000 ha HPK)

Table 6.2 provides an overview of the foreseen MIFEE development phases as reported in the MIFEE Grand Design (published by the Ministry of Agriculture) subdivided by agricultural production center cluster or Klaster Sentra Produksi Pertanian (KSPP). Figures in table 6.3 clearly differ from figures reported by source A and source C, especially with reference to the extent of energy crops to be cultivated.

Table 6-2 An example of the structure of the MIFEE project MIFEE Phase KSPP Area (ha) Commodities KSPP-1 Greater Merauke 44,239 rice, corn, rainfed rice Phase I: short-term sugarcane, corn, ground nut, soybean, priority (2010-2014) KSPP-2 Kali Kumbe 50,140 cows Total area: KSPP-3 Yeinan 80,717 corn, ground nut, fruits, cows 228,022 ha KSPP-4 Bian 52,926 ground nut, oil palm, fruits, cows Phase II: mid-term KSPP-5 Okaba 27,705 rice, cows priority (2015-2019) KSPP-6 Wanam 112,599 fisheries, corn, sagoo, rice, cows Total area: KSPP-7 Tubang 295,904 rice, sagoo, animal husbandry, cows 751,350 ha KSPP-8 Tabonji 315,142 animal husbandry, rice, sagoo Phase III: long-term KSPP-9 Nakias 173,971 corn, ground nut, soybean, rice, cows priority (2020-2030) Total area: KSPP-10 Selil 65,280 oil palm, cows 239,251 ha Total area 1,218,623 Source: Grand Design MIFEE, MP3EI (2011), Indonesian Ministry of Economic Affairs

The location and extension of these different phases is shown in Figure 6.2.

44

Figure 6-2 Overview of MIFEE development phases 2010-2030 (MP3EI, 2011)

Although MIFEE has been flagged as a food security project improving the food availability situation in Eastern Indonesia, reported data on the dimension of the land allocation suggest that the focus is mainly on energy crops and industrial timber production. The investors involved in the project include 10 state-owned companies, and 37 private sector investors (both national and international) (DTE, 2011).

Kabupaten Merauke has been selected as a suitable location for this development mainly for its flat topography. With a total geographic extension of about 4.3M ha, the district was initially considered to have an agricultural land development potential of about 2.5M ha, consisting of 1.9M ha of wet land and 600,000 ha of dry land. Based on recommendation from Badan Koordinasi Penataan Ruang Nasional (BKPRN) - the Indonesian Agency for National Spatial Planning – MIFEE in the Merauke area has later been revised and planned for the development of 1.2M ha, of which 1.13M ha is production forest that can be converted, and 0.15M ha is land allocated to other uses. At present, the area currently in use under the MIFEE project in Merauke is of about 37,014 hectares.

Because of the strong relation existing between agricultural land development and water availability, we analyse in the following paragraphs the crop water requirements and water availability, based on the identified local rainfall and hydrological patterns. As a consequence, the computations in the next sections are based on the precipitation input sourced from the TRMM cell identified in the region of Merauke (cell 15250). Yet, while developing this analysis, it should be borne in mind that, should the full MIFEE project be developed, the change in land cover condition from forest to agricultural and urban settlement areas will affect the hydrological patterns in the area, bringing about a change in the rainfall-to runoff transformation process, eventually impinging on the availability of river flow in the river system of the region.

45 6.2.1 Water requirements for paddy At present, rice irrigation areas in kabupaten Merauke are located in the administrative unit of Kurik (Bian, Maro and Kumbe sub-catchments) with 8,907 ha; Semangga (Maro sub-catchment) with 4,000 ha; and Tanah Miring (Maro sub-catchment) with 7,038 ha, for a total irrigated area of nearly 20,000 ha. Existing irrigation areas currently receive water from 3 different sources: - small surface ponds (called long-storage) capturing rain water; - drainage canals connected to the Rawa Biru freshwater swamp; - river water during the post wet-season months

River water is not used as a source during the dry season months because of salinity resulting from sea water intrusion, combined with reduced river discharge from upstream. During field visits to the study area, the local DESA office of the ministry of agriculture reported that, during the dry season, several rice fields are not being cultivated due to insufficient water availability for crop growth. Figure 6-3 Long storage near Merauke

Based on available collected information, existing cropping patterns for rice in the Merauke area can be estimated as belonging to either one of these two categories: x one crop harvest per year, with sawing date around November, rainfed x two harvests per year, first rainfed (November-mid March), one irrigated (April- mid-August)

For the water availability constrain for paddy irrigation in the dry months, the actual cultivated area of the second cropping pattern depends on the irrigation coverage of the scheme. For both cropping intensities, cultivated rice is of short maturing variety of about 4 and a half months. Using a cropping length of 18 months, a land preparation required depth of 150 mm (FAO, 1998 and GoI, 2006) and crop coefficients as provided by [FAO, 1998], the gross irrigation water requirements for paddy in the Merauke area is projected as in Figure 6.4 below.

400 350 P20th 300 250 P 50th 200 P80th 150

(mm/month) Sawa 100 water req.

Depandable precipitation precipitation Depandable 50 0 1 2 3 4 5 6 7 8 9 10 11 12 Month

Figure 6-4 Irrigation water requirements for rice, compared with rainfall patterns

46 Figure 6.4 shows that for the November cropping patterns, excluding the land preparation phase, average monthly rainfall patterns are sufficient to satisfy paddy crop water requirements and – excluding the land preparation phase - no irrigation is required. This is however not the same case for the second crop seeded in April, for which an average rainfall year will not be able to provide sufficient rainfall input for proper crop development. In this latter case, supplementary irrigation for paddy is required especially in the months of May, July and at the end of the cropping period in early August.

According to KSSP cluster 1 of Phase I of the MIFEE Grand Design, 44,239 hectares of land will be used to cultivate rice and corn. Assuming that this area extent will comprise mainly rice (40,000 ha), and using the irrigation water requirements computed as described above, the average irrigation water demand for paddy cultivation in the period April to mid-August is estimated in 18 m3/s varying in a range between 5 (August) and 43 (April) m3/s.

KSPP I of MIFEE is geographically located in the catchment area of the Kumbe and Maro rivers. Figure 6.5 provides an overview of the comparison between the monthly irrigation water requirements for rice, and the simulated average monthly discharge in each of the two rivers.

600 Kumbe

500 Maro IWR sawa 400

300

200

100 Discharge andDischarge (m3/s)IWR

0 1 2 3 4 5 6 7 8 9 10 11 12 Month

Month 1 2 3 4 5 6 7 8 9 10 11 12 Kumbe 211 227 294 255 103 48 15 15 20 55 125 201 Maro 361 433 564 448 187 76 33 22 31 56 154 299 Kumbe + Maro 572 660 858 703 290 124 48 37 51 111 279 500 IWR sawa 19 11 6 43 21 13 9 5 0 0 47 25

Figure 6-5 Rice irrigation water requirements and simulated average river discharge for MIFEE KSPP 1

A closer look to figure 6.6 during the cropping period April to August is provided in Figure 6.7. The graph shows that, based on the model average discharges of the Kumbe and Maro rivers, the irrigation water requirements for the 40,000 hectares of paddy cultivation in the Meruake area could be met by river water in the month of May and August. On the other hand, during the months of June and July, the two river systems could still be able to supply a sufficient amount of water, but with major consequences on the residual river discharge of the two rivers, given the high irrigation water demand compared to the available river discharge. Further, one should also take into account that the provided discharge curves on Figure 6.6 and 6.7 repesent an average discharge year. Should the annual precipitation be lower than average values, river disharge would also decrease, and the Maro and KUmbe rivers alone could not be able to satisfy irrigation water requirements during the driest months of June and July.

47 80 Kumbe 70 Maro 60 IWR sawa 50 40 30 20 10 Discharge and IWR (m3/s) IWR and Discharge 0 5 6 7 8 9 Month

Figure 6-6 River discharge and irrigation water requirements for paddy at comparison

The graph shows that, while during the wet season, there is sufficient water available if rice would require irrigation, during the dry season available average river discharge from the Kumbe and Maro rivers together will not be enough to satisfy the irrigation requirements for the 40,000 hectares of irrigated rice crops in July, even if all water would be used. During the months of August and September, the river flow will be, on average, just enough for irrigation, but would leave little or no flow left in the rivers, worsening for example the salinity intrusion problem already experienced during the dry season. For the rest of the months, the supposed withdrawal of water from the river will still be significant, especially in the period between May and December.

6.2.2 Water requirements for oil palm Oil palm plantations are usually to be found in tropical areas where natural rainfall is abundant. Water requirements for oil palm depend on the tree age and on local climate conditions affecting plant evapo- transpiration. When plant water requirements are not met by local rainfall, oil palm plants suffer from water stress conditions which eventually lead to reduced crop yields. In these cases, supplementary irrigation can be considered as an option to supply the deficit amount of water required to guarantee optimal plant growth. In cases of deficient water supply and no provision of supplementary irrigation, oil palm trees decrease their yield. Carr (2011) reports estimates of yield reduction in the range of 10% for every 100 mm increase of soil water deficit. The yield reduction occurs approximately 2 years after the occurrence of the water deficit. The amount of yield reduction depends on different factors among which the growth stage of the plant, flourishing and length of the water deficit period. Figure 6-7 Oil palm plantation in the EDB

48 Based on available literature, and depending on the local climate and soil conditions, the range of required annual water intake for oil palm varies between 1,300 and 1,600 mm/year (NaanDanJain, 2011; Netafim, 2012; TNAU, 2008).

According to MIFEE plans, the total area to be used for oil palm plantation varies – depending on the source – from 246,000 to 550,000 hectares.

To compute oil palm water requirements in the Merauke area, we have used a reference value of 120 mm/month (2.0 mm/day during the wet season, 4.9 mm/day during dry months) of plant water use (1,440 mm/year) for a mature plant, selecting this intermediate value after investigating the information provided by the sources above mentioned. We have compared the required water use with the average, 20th and 80th percentile dependable rainfall values for the Merauke area. Results are shown in Figure 6.6.

400 350 P20th 300 250 P 50th 200 P80th

150 Oil palm (mm/month) 100 water req

Depandable precipitation 50 0 1 2 3 4 5 6 7 8 9 10 11 12 Month

Figure 6-8 Comparison of dependable rainfall with water requirements for oil palm

Figure 6.6 clearly shows that for 5 to 6 months in a year, precipitation in the Merauke area will not be enough to satisfy the oil palm water requirement. This situation occurs in the dry season, when demand for water is also higher in other sectors (i.e. irrigated agriculture, domestic water supply) and when river discharge is the lowest. Table 6.4 reports the estimated irrigation water requirements (excluding system distribution losses) for the entire foreseen extension of oil palm plantation within the MIFEE project.

Table 6-3 Estimated IWR for oil palm during the dry season 1 2 3 4 5 6 7 8 9 10 11 12 Oil palm water req. 62 56 62 60 151.9 147 151.9 151.9 147 151.9 60 62 P 50th (mm/month) 256 231 305 264 104 83 37 15 61 127 181 255 Deficit P50 (mm/month) 194 175 243 204 -48 -64 -115 -137 -86 -25 121 193 Deficit as % of CWR - - - - 32 43 75 90 59 17 - - IWR _246,000 ha (m3/s) 46 60 109 130 82 24 IWR_550,000 ha (m3/s) 102 135 243 290 183 54

Based on available data, oil palm plantation will predominantly be based in kabupaten Merauke, in the catchment area of the Kumbe, Maro, Bian and Sakiramke rivers. In table 6.5 the net irrigation water requirements for oil palm are compared with the average monthly river discharge of these rivers. In the computation, irrigation distribution losses are not accounted for. This means that the actual (gross) irrigation water requirement figure is bigger than the one reported in the table.

49 Table 6-4 Comparison of monthly IWR for oil palm with simulated average river discharge Jan Feb March Apr May Jun Jul Aug Sep Oct Nov Dec Bian (m3/s) 502 504 315 329 277 334 337 371 392 371 523 451 Kumbe (m3/s) 211 227 294 255 103 48 15 15 20 55 125 201 Maro (m3/s) 361 433 564 448 187 76 33 22 31 56 154 299 Sakiramke (m3/s0 173 226 298 227 75 17 8 2 4 10 25 86 Bikuma-Sakiramke (m3/s) 1247 1390 1471 1259 642 475 393 410 447 492 827 1037 IWR _246,000 ha (m3/s) 46 60 109 130 82 24 IWR as % of total river flow 7 13 28 32 18 5 IWR_550,000 ha (m3/s) 102 135 243 290 183 54 IWR as% of total river flow 16 28 62 71 41 11

Results show that, for the development foreseen a 246,000 hectares of oil palm plantation, during the driest months of an average year, the net irrigation water requirements for oil palm may reach up to 30% of the total discharge of the 4 main rivers in the area. This figure more than doubles when the extent of 550,000 ha is considered.

6.2.3 Water requirements for sugar cane

Sugarcane is planned to cover an area of about 50,140 ha in KSPP cluster 2. Based on information provided by local authorities in Merauke referring to the type of licenses released for cultivation purposes, we assume that the other food crops will only be allocated a negligible area. Based on other sources (Source C, paragraph 6.2), the total area allocated for sugar cane production amounts to 457,276 hectares.

Based on a comparison with other sugarcane cultivations in climate areas similar to those of the EDB basin, the estimated crop growing period for sugarcane in the Merauke area starts in October and ends in June. Therefore crop growth occurs only in the wet period. Based on this assumption, and using sugarcane CWR from FAO (FAO, 1986), the comparison between sugarcane CWR and average rainfall in the Merauke area (Figure 6.7) suggests that, for an average year, sugarcane does not require additional irrigation.

Monthly Precipitation variability Merauke, 2002-2011

400 P 20th 350 300 P 50th 250 200 P80th 150 (mm/month) 100 Sugarcane 50 water req. Depandable precipitation Depandable precipitation 0 1 2 3 4 5 6 7 8 9 10 11 12 Month

Figure 6-9 Comparison of sugarcane CWR and precipitation patterns in the Merauke area

50 However, in the 20th percentile of dry months, sugarcane plantations would require supplementary irrigation at the beginning of sowing (October), in the month of February, and in the last 2 months of the developed crop stage (May and June).

51 7. WATER RESOURCES PLANNING

An effective process of water resources planning in the context of a river basin management requires attention to a number of crucial aspects related to the aims of the planning, the resources available for it and the social, economic and environmental drivers and constraints characterizing the catchment for which the planning is developed. Yet, the decision-making process is also affected by the profile and the aims of the decision-makers involved (i.e. government entities, civil society actors, private sector institutions), and by the power relation existing between them.

In the context of Integrated Water Resources Management (IWRM), a water resources plan should provide a thorough assessment of the available water resources assets in the area of analysis, along with an analysis of all the current and foreseen uses related to the water sources. Based on availability and demand, a plan for the management of the water resources can then be drafted. In the end, the purpose of a water resources planning analysis is that of informing and supporting decision makers (Loucks and Van Beek, 2005).

In the case of the Einlanden-Digul-Bikuma catchment, the aim of water resources planning is the one common to the drafting of any other Pola in Indonesia, namely, the elaboration of a thorough assessment of the status of water resources availability (water quality, water quantity and infrastructural evaluations among others) to define a 20-year water resources development plan for the basin. This is according to the Indonesian Ministry of Public Work (PU) regulation on the aim and purposes of the drafting of a Pola. As reported in the PU technical guidelines and procedural arrangements for water resources management document (regulation number 22/PRT/M/2009) the Pola for a river basin should include purposes and principles of water resources management, the future scenario conditions of the river basin in terms of water availability, a water resources management strategy, and the operational policies required to implement the strategic management of water resources (Ministry of Public Works, 2009).

In the following paragraphs a short description of the principles behind water resources planning and integrated water resources management (IWRM) approaches is provided with the aim to emphasize the importance of developing water management decision based on both technical (engineering) and non- technical arguments, as compared to a form of planning that is solely driven by an engineering approach to water management. At the end of the chapter, paragraph 7.2 presents a multi-criteria analysis approach, which is here provided as an example of an evaluation of strategic developments that takes into account different aspects and values attached to the water source. For its importance as a strategic development choice for the basin, and for the impact on the water assets, we have selected the different stages of development of the MIFEE project to perform the multi-criteria analysis.

7.1 Principles of water resources planning In the context of river basin management, the concept of Integrated Water Resources Management (IWRM) is an often recurring term. The principle behind IWRM is the importance of accounting for all the different uses, functions and users of the water resource during the process of drawing medium and long-term management plans. This should be done in a wide context, equally taking into account the socio-economic (SES), administrative and institutional (AIS) and natural resource (NRS) systems related to the water source. The interaction between these elements is depicted in Figure 7.1.

Different forms of water use can be consumptive (i.e. domestic and industrial water supply and water used for irrigation) or non-consumptive (i.e. water use for transportation along rivers, habitat conservation and tourism). These forms can co-exist, and most often they satisfy the needs of different users. A sustainable living environment is an environment where different water users make use of the water source in a form that is the least harmful for the other users relying on the same – often limited - resource.

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A recurrent approach used by water management entities involved in water resources management is to adopt a problem-solving approach driven by engineering evaluation of feasibility which does not take into account the social and environmental aspects of water and its use. However, a sound water resources management plan can only result from a decision-making process that is driven by the interaction of engineering, social, environmental and economic aspects.

Although theoretically sound, this process is often partially adopted in reality, and this is frequently the cause leading to water-related conflicts over the control, use and ownership of water, or to development planning that is sustainable only over the short-term. It is well recognized that the implementation of an IWRM approach is not an easy tasks, as different stakeholders attribute different values to the same water source. However, consultations and discussions on a inclusive stakeholders platform is the good starting point to work towards the reaching of minimum and shared agreements on how water resources should be used at the basin scale without negatively affecting other water users. Figure 7-1 IWRM in water resources planning Source: Loucks & Van Beek, 2005

One of the available tools to apply the IWRM principles in water resources planning is the use of a multi-criteria analysis approach to evaluate the pros and cons of water resources management strategies based on criteria selected by the different water users.

Based on the local environmental, social, economic and engineering conditions characterizing the Einlanden-Digul-Bikuma catchment, a preliminary structuring for a multi-criteria approach for decision making at the basin level was drafted. The aim of this approach is to provide decision-makers and policy-developers with the tools to consider a water management process from all relevant perspectives, in order to develop decisions and propose actions which optimize the sustainable use of the water resources available in the basin.

7.2 Multi-criteria analysis for the EDB catchment A multi-criteria analysis is based on three components, namely: a. a number of strategies considered for possible future developments by policy-makers; b. a list of criteria to be evaluate for each strategy; c. a scale of evaluation of the criteria, based on the positive or negative effects that a selected strategy can have on the specific criteria under consideration

For the Einlanden-Digul-Bikuma case study, these three elements are presented below. Among the selected strategies we also included the Current Developments case, which provides an overview of the current situation based on the evaluation criteria selected for the assessment of future developments. As previously mentioned, this multi-criteria exercise focuses its attention of the possible development stages of the MIFEE project since, for the scope of the initiative, the foreseen spatial developments are closely linked to the availability of water resources.

3 Development Strategies As foreseen future strategies, we have identified 3 possible developments of the EDB catchment for the medium-long term. These future scenarios aim to presents possible directions of land and water

53 resources development in the basin, based on economic and political decisions taken at the district, provincial and national levels. In the paragraph below a short description of the current situation is also included to provide the bases for comparison between the current situation and the possible future developments.

Current situation At present the total population in the EDB catchment is estimated in 524,000 people, of which about 150,000 live in the Merauke district. The remaining population is predominantly rural, and lives in the hilly and mountainous areas of the catchments. While in Merauke district there is a moderate predominance of small family-run businesses and irrigated agriculture activities, the rest of the catchments mainly live of subsistence farming. Small industrial activities and irrigated agriculture are therefore predominant in the low-lands. The higher sections of the catchment have a considerable amount of protected forest, but the protection of this resource from illegal logging and/or deforestation driven by local villagers is somewhat poor.

Æ Autonomous developments The current degree of transmigration from other areas of the country is slow positive, thereby adding to the population increase in the basin. An increment in small-business activities is registered in kabupaten Merauke, and current patterns of land use will remain the same as in the current situation..

Æ Extensive agro-industry development (MIFEE 1.2M ha) The Extensive Agro-Industry Development scenario for the EDB represents the future development of the EDB catchment in which the focus will be on the generation of economic value through the development of medium and large-scale agro-business activities mainly located in the Merauke District. For the degree of production activities envisaged with this scenario, it is expected that the overall population in the basin will increase considerably driven by a need for a larger labour force to be employed in agriculture. The transmigration process from other parts of Indonesia will be sustained, with a consequent population incease in the area of major agricultural production concentration. This will speed up the degree of urbanization in the area, with an increased development of urban setting related activities. Increased urbanization will drive up the demand for urban services, including the supply of drinking water and sanitation services. More pressure will therefore be exercised on the existing land and water resources. The degree of ecosystem conservation will decrease as a result of a rising need for land and water. Forest land will decrease in size, and biodiversity will be reduced by expanding urbanization and transmigration. Agricultural production for commercial farming will produce valuable output for regional exports. Commercial enterprises owners will gain profits and employment opportunities will increase. Since employees can at best only partially be recruited locally, a large scale influx of transmigrants is to be expected.

Æ Moderate agro-business development (MIFEE 250,000 ha) The Moderate Agro-Business Development Scenario is foreseen to produce similar developments as the Extensive agro-business development scenario, but at a smaller scale. The reduction factor is represented by the smaller size of the foreseen agro-business development, which will have a lower impact in terms of required agricultural land, employed force, degree of urbanization and stress on the available water resources.

Æ Focus on sustainability This scenario foresees management of local natural resources aimed at ensuring the ecological equilibrium existing between flora, fauna and human beings. Under this scenario, no further agro- business development is fostered while natural conservation activities are promoted. Economic activities will not be centred on the production of exportable goods, but rather on the in- house generation of income and value from the sustainable use of local resources. The eco-tourism

54 sector will be promoted, bringing to the area tourism driven by environmental and cultural heritage interests. Under this scenario, there will be a greater opportunity for indigenous people to improve their economic situation without foregoing their cultural values and practices. More attention will be devoted to the preservation of natural resources such as swamps, forest and surface water systems, which will attract attention for their high degree of biological diversity. Population trend will still be upward, but not necessarily driven by transmigration waves. Pressure on local land and water resources will be limited, given the sustainable approach used for the development of economic sector activities. Authorities in the EDB will focus on wealth creation based on sustainable eco-tourism, promoting environmental sustainability and social stability.

11 Evaluation Criteria To assess the performance of the possible future development strategies in the EDB catchment, we have selected 10 evaluation criteria, each of which is briefly described below. The list of criteria is by no means complete, but it is here provided as a starting point for an integrated evaluation. The final criteria to be used should optimally be established by all stakeholders together.

Criteria have been chosen to equally account for social, economic, technical and environmental aspects of the water management strategies described above. The aim is to provide a comprehensive overview of the multiple aspects related to water resources planning in the context of a river basin, considering aspects relevant to different stakeholders.

Table 7-1 Selected criteria for the multi-criteria analysis Social Economic Environmental Aspects Technical Aspects Aspects Aspects 1. equity and social 3. level of economic 6. sustainable resources use 9. water availability inclusion growth 7. conservation of ecosystem 10. water quality 2. preservation of cultural 4. poverty alleviation services 11. technical, feasibility of the integrity and values of 5. financial feasibility 8. climate change mitigation intervention indigenous people of the intervention

What follows is a brief description of the criteria used for the evaluation.

1. Equity and social inclusion The extent to which the strategy equally delivers benefits and costs among the different stakeholders and water users

2. Preservation of cultural integrity and values of indigenous people The extent to which the strategy affects or influences the cultural values of indigenous people

3. Level of economic growth The level of economic wealth creation maintained over the long-term

4. Poverty alleviation The extent to which the strategy contributes to the reduction of poverty among the citizens of the EDB, increasing both their health conditions and their socio-economic status

5. Financial feasibility of the intervention The extent to which the foreseen development are actually capable to be carried out based on available financial resources

6. Sustainable resources use The extent to which the strategy allows for use of the natural resources that does not deteriorate their quality and quantity over time

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7. Conservation of ecosystem services The extent to which the strategy does not deteriorate the status of services provded by the environment such for example river navigation, conservation of biodiversity, CO2 storage tank

8. Climate change mitigation The extent to which the strategy reduces the pace of climate change (i.e. by deforestation, peat drainage, change land used type)

9. Water availability The extent to which the water use in the strategy can be met by the available resources for both surface and groundwater

10. Water quality The extent to which the strategy affects the quality of water resources, for both surface and groundwater

11. Technical feasibility of intervention The extent to which the strategy is implementable taking into account its technical aspects

Scale of Evaluation We decided to assign a scale of evaluation in the range of -2 to 2. For each of these numeric values, an explanation is provided:

-2 -1 0 1 2

[-2] the strategy scores considerably low on the evaluated criteria, and contributes negatively to the cumulative impact evaluation; [-1] the strategy scores moderately low on the evaluated criteria, and contributes negatively to the cumulative impact evaluation; [0] the strategy scores neutral on the evaluated criteria, meaning that the expected negative effects are offset by the positive effects, or meaning that the strategy does not have an impact (positive or negative) on the criteria evaluated. Overall, the contribution of the criteria to the cumulative impact evaluation is null; [+1] the strategy scores moderately high on the evaluated criteria for its expected positive impact, and contributes positively to the total impact evaluation of the strategy; [+2] the strategy scores considerably high on the evaluated criteria for its expected high positive impact, and contributes positively to the cumulative impact evaluation;

Using these 3 components, each strategy is evaluated for all criteria. Policy-makers can make use of such kind of an approach to draw conclusions on the benefits and costs related to the different strategies. It is not possible to obtain an overall score for each of the strategies by summing the scores on the different criteria. Indeed, since not all criteria will be perceived as being equally important, the scores on the criteria should be weighted before being summed. The weighing factors attributed to each criteria will eventually determine the final scoring for each considered strategy, and for this same reason they should be established by the decision maker in close consultation with all stakeholders.

In Table 7-2, the identified strategies have been evaluated in terms of the 11 identified criteria. Where relevant, the results of the hydrological analysis have been used. All other scores are based on expert judgement and should serve as a first indication for demonstration purposes. The different scoring is represented by the different colours as described earlier in the paragraph.

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Table 7-2 Multi-criteria evaluation for development strategies in the EDB Criteria MIFEE MIFEE Focus on Autonomous 1.2M ha 250,000 Sustainability developments ha 1. Equity and social inclusion -2 -2 1 -1 2. Preservation of cultural integrity and -2 -2 2 -1 values of indigenous people 3. Level of economic growth 2 2 0 0 4. Poverty alleviation 1 1 2 0 5. Financial feasibility of the intervention -2 -1 1 0 6. Sustainable resources use -2 -1 2 0 7. Conservation of ecosystem services -2 -1 2 0 8. Climate change mitigation -2 -1 2 0 9. Water availability -2 -2 0 -1 10. Water quality -2 -1 0 -1 11. Technical feasibility of the 0 0 1 1 intervention

A look at the results of Table 7.2 clearly shows that the strategy foreseeing the development of 1.2 million hectares of cultivated area under the MIFEE project scores significantly low in the majority of the criteria, with foreseen positive benefits only gained in terms of economic growth and poverty alleviation. This is also the case of the scenario for the development of 250,000 hectares of MIFEE, although the scoring is overall less negative as a consequence of the smaller impact generated by a smaller cultivated area.

The scenario focus on sustainability, for its predominant non-consumptive use of the water resource, provides of all the criteria higher scoring, with no foreseen impact on water availability and water quality, but also with a lower level of economic growth as compared to the MIFEE scenarios.

A look at the scenario representing autonomous developments, it can be noticed that, should the current situation remain unaltered, the impact on the environment and society as a whole would be negative for the low scoring on the social criteria of equity and preservation of cultural integrity, and for the technical criteria related to the availability of a good quality water resource.

57 8. CONCLUSIONS and RECOMMANDATIONS

8.1 Conclusions Global data sets and hydrological modelling provide input for water resources assessment in data poor areas, such as the EDB basin. The model results regarding discharges have been validated by comparison with literature values for the run-off coefficient and by performing a sensitivity analysis. However, uncertainty remains high when model results cannot be compared with discharge monitoring records.

A demonstration has been presented of strategic river basin planning in the framework of preparation of a Pola based on the principles of integrated water resources management, focussing on actual and future water supply and demand options and evaluation of different alternatives. Various criteria have been used to assess the social, economic, environmental and technical impacts of the different alternatives.

Overall, enough water is available to meet actual water demand. Current water related problems in EDB focus on quantity and quality of drinking water supply, especially the salinity of groundwater around Merauke and the sustainability of the use of Rawa Biru as a source.

Large scale development of oil palm plantations and irrigated rice estates, such as foreseen under MIFEE, will seriously impact the water resources, since not enough water is available to meet crop water requirements. Without irrigation, oil palm is expected to suffer severe yield reductions due to the limited amount of rainfall in the dry season in most years as the area where MIFEE is planned is the driest area in Papua.

Large scale estate development can be expected to generate more economic growth than other strategies. However, a negative impact has to be expected on most other criteria such as equity and social inclusion, preservation of cultural integrity and values of indigenous people, sustainable resource use, conservation of ecosystem services, climate change mitigation and the availability and quality of water. The conversion of forests to estates will be especially harmful for nature and will lead to substantial emission of green house gas. If estates will be developed on organic peat soils, the emission of green house gas will increase even further.

8.2 Recommendations The IWRM exercise for the EDB catchment revealed that the degree of availability of hydro- meteorological observed data at the catchment scale is very poor. In a context of water resources planning and assessment, historical records on observed river discharge and precipitation are the basis from which to develop knowledge about hydrological and climate patterns characterizing the study area. It is therefore recommended to start a continuous water level and discharge monitoring for the most important rivers in the EDB basin along with water quality monitoring for parameters such as salinity. The resulting data can be used to verify and improve the water resources assessment presented in this report.

The Rawa Biru wetland is the main source of drinking water for Merauke. However, it is not clear whether the current abstraction rate is sustainable. It is therefore advised to start monitoring of water levels in the wetland and measure the discharge abstracted in order to quantify the maximum sustainable yield and to prevent over-abstraction, which might result in the loss of the water source.

An analysis of future developments impacting water supply and/or demand, such as large scale plantation development under MIFEE, forms an essential part of the water resources analysis for the Pola. Therefore, it is advised to include MIFEE as one of the alternatives to be analysed in the Pola.

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Literature suggests that the rainfall in Merauke is far from sufficient for the growth of oil palm. For this reason, severe yield reduction is expected. It is recommended to start experiments with smaller scale pilot estates for oil palm to verify the yields that can be expected, especially taking into account the rainfall. These experiments should last several years, since yield reduction is expected to occur 2 years after the occurrence of water stress. Sugar cane is expected to suffer less from drought, but still it is recommended to also start experiments for sugar cane.

Development of plantations on peat lands will suffer from drainage and flooding problems as a result of soil subsidence. Furthermore, drainage of peat lands results in an increase of green house gas emission. Therefore, it is recommended to investigate the extent and depth of peat land in the EDB and to take into account the vulnerability of peat lands when planning land use changes.

The impact analysis of different strategies presented in this report serves only as a demonstration of the methodology providing an indication of the different impacts. It is recommended that a list of criteria for assessment of the impact of different alternatives will be developed in cooperation with all stakeholders. Furthermore, it is advised that in the Pola BWS will select a desired alternative based on the scores of the impacts on the selected criteria.

For the multiple uses of the water in the EDB catchment, and for the purpose of the sustainable management of the resources for the future, it is also recommended that the different government agencies (i.e. Dinas PU, Dinas Agriculture, Bappeda, Dinas Fisheries, Dinas Forestry) enhance their ability to work together and coordinate future planning. This process should take place in a transparent and inclusive way, equally facilitating the participation of non-state actors during meetings and consultations.

59 9. REFERENCES

Asian Development Bank, 2010. Institutional Strengthening for the Water Resources Sector, project number 44352-012

Bontemps S. et al., 2011. GLOBCOVER 2009: Products Description and Validation Report. European Spatial Agency (ESA) and Catholic University of Louvain

Carr M. K. V., September 2010. The water relations and irrigation requirements of sugar cane (Saccharum Officinarum): a review. Cranfield University, United Kingdom

Carr M. K. V., July 2011. The water relations and irrigation requirements of oil palm (Elaeis Guineensis): a review. Cranfield University, United Kingdom

Down to Earth (DTE), November 2011. The Land of Papua: a continuing struggle for land and livelihoods. DTE Special Edition Newsletter No. 89-90. International Campaign for Ecological Justice in Indonesia. Greenside Farmhouse, Hallbankgate, Cumbria CA82PX, England

FAO, 1986. Irrigation Water Requirements. Training Manual no. 3. Part II Determination of Irrigation Water Needs

FAO, 1998. Crop evapotranspiration – Guidelines for computing rop water requirements. FAO Irrigation and Drianage paper 56

Government on Indonesia, May 2006. Integrated Citarum Water Resources Management Project. Technical Assistance TA 4381 – INO. Ministry of Public Works, Directorate General of Water Resources

ISRIC, undated. Major Soils of the World Database. World Soil Information Center. Sourced from: http://www.isric.org/isric/webdocs/docs//major_soils_of_the_world/annexes/referenc.pdf accessed on August 2012

Karssenberg, D., Burrough, P.A., Sluiter, R. and de Jong, K., 2001, The PCRaster software and course materials for teaching numerical modeling in the environmental sciences. Transactions in GIS, 5, pp. 99-110

Loucks and Van Beek E., 2005. Water Resources Systems Planning and Management. WL Delft Hydraulics and UNESCO

Manikmas Made Oka A., 2010 Merauke Integrated Rice Estate (MIRE): The awakening of food security and food sovereignty from the eastern part of Indonesia. Indonesia Centre for Agriculture Socio Economic and Policy Studies. Agriculture Policy Analysis Vol. 08 No. 4, 2010

Ministry of Public Works, 2009. Pedoman Teknis dan Tatacara Penyusunan Pola Pengelolaan Sumber Daya Air, Government of Indonesia, regulation 22/PRT/M/2009

MP3EI, 2011. Master Plan Percepatan dan Perluasan Pembangunan Ekonomi Indonesia (Master Plan For the Acceleration And Expansion of Indonesia's Economic Development) 2011-2025, Coordinating Ministry of Economic Affairs, Government of Indonesia, ISBN 978-979-3754-14-7

NaanDanJain, March 2011. Oil Palm booklet. NaanDanJain Irrigation Ltd, Israel

60 Netafim, 2012. Information sourced from: http://www.netafim.com/crop/oil-palm/best-practice accessed in August 2012

Oldeman, L.R., Las, I. and Darwis, S.N., 1980. The agro-climatic maps of Kalimantan, Maluku, Irian Jaya and Bali, West and East Nusa Tenggara. Contributions. 33, Central Research Institute for Agriculture, Bogor

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TNAU, 2008. Tamil Nadu Agritech Portal. Oil palm water requirements. Information accessed from: http://agritech.tnau.ac.in/agriculture/agri_irrigationmgt_oilpalm.html accessed in August 2012

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61 ANNEXES

Annex 1: Identified soil and land cover parameters in the EDB basin

This annex shows the assigned values to the parameters of the soil and land cover types in the EDB basin. For each of these parameters: the first column represents the land use code associate to a specific land use type; the second column represents the sub-catchment; the third column represents the soil code corresponding to a specific soil type; the fourth column represents the value assigned to the parameter. When the number assigned to a column is represented as “ [0> “, this symbology means that all the values in the considered categories are being considered (i.e. for the column of the sub-catchments, there is no variation in the value of the parameters based on sub-catchment).

Albedo [0,> [0,> 4555 8.6 11 [0,> [0,> 0.22 [0,> [0,> 4556 8.6 14 [0,> [0,> 0.22 [0,> [0,> 4557 8.6 20 [0,> [0,> 0.23 30 [0,> [0,> 0.24 FirstZoneMinCapacity 40 [0,> [0,> 0.24 [0,> [0,> [0,> 10000 110 [0,> [0,> 0.25 130 [0,> [0,> 0.27 InfiltCapPath 140 [0,> [0,> 0.23 [0,> [0,> [0,> 5 160 [0,> [0,> 0.24 170 [0,> [0,> 0.24 InfiltCapSoil 190 [0,> [0,> 0.20 [0,> [0,> 0 120 210 [0,> [0,> 0.35 [0,> [0,> 4448 60 [0,> [0,> 4469 360 Beta [0,> [0,> 4470 360 [0,> [0,> [0,> 0.6 [0,> [0,> 4480 360 [0,> [0,> 4483 600 CanopyGapFraction [0,> [0,> 4513 600 <,175] [0,> [0,> 0.4 [0,> [0,> 4524 60 190 [0,> [0,> 1 [0,> [0,> 4555 60 210 [0,> [0,> 1 [0,> [0,> 4556 60 [0,> [0,> 4557 60 EoverR [0,> [0,> [0,> 0.05 LeafAreaIndex 11 [0,> [0,> 3.8 FirstZoneCapacity 14 [0,> [0,> 3.8 [0,> [0,> [0,> 10000 20 [0,> [0,> 4.3 30 [0,> [0,> 4.8 FirstZoneKsatVer 40 [0,> [0,> 5.4 [0,> [0,> 0 1000 110 [0,> [0,> 5.8 [0,> [0,> 4448 8.6 130 [0,> [0,> 3.7 [0,> [0,> 4469 259 140 [0,> [0,> 6.2 [0,> [0,> 4470 259 160 [0,> [0,> 5.4 [0,> [0,> 4480 259 170 [0,> [0,> 5.4 [0,> [0,> 4483 864 190 [0,> [0,> 0 [0,> [0,> 4513 864 210 [0,> [0,> 0 [0,> [0,> 4524 8.6

62 M 110 [0,> [0,> 1000 [0,> [0,> [0,> 2500 130 [0,> [0,> 1000 140 [0,> [0,> 900 160 [0,> [0,> 1900 MaxCanopyStorage 170 [0,> [0,> 1900 11 [0,> [0,> 2.6 190 [0,> [0,> 0 14 [0,> [0,> 2.6 210 [0,> [0,> 0 20 [0,> [0,> 2.3 30 [0,> [0,> 2 thetaR 40 [0,> [0,> 1 [0,> [0,> 0 0.05 110 [0,> [0,> 1.2 [0,> [0,> 4448 0.05 130 [0,> [0,> 1.1 [0,> [0,> 4469 0.08 140 [0,> [0,> 1.9 [0,> [0,> 4470 0.08 160 [0,> [0,> 1 [0,> [0,> 4480 0.08 170 [0,> [0,> 1 [0,> [0,> 4483 0.06 190 [0,> [0,> 0 [0,> [0,> 4513 0.06 210 [0,> [0,> 0 [0,> [0,> 4524 0.05 [0,> [0,> 4555 0.05 N [0,> [0,> 4556 0.05 11 [0,> [0,> 0.05 [0,> [0,> 4557 0.05 14 [0,> [0,> 0.05 20 [0,> [0,> 0.15 thetaS 30 [0,> [0,> 0.25 [0,> [0,> 0 0.5 40 [0,> [0,> 0.4 [0,> [0,> 4448 0.2 110 [0,> [0,> 0.38 [0,> [0,> 4469 0.5 130 [0,> [0,> 0.35 [0,> [0,> 4470 0.5 140 [0,> [0,> 0.3 [0,> [0,> 4480 0.5 160 [0,> [0,> 0.086 [0,> [0,> 4483 0.4 170 [0,> [0,> 0.086 [0,> [0,> 4513 0.4 190 [0,> [0,> 0.02 [0,> [0,> 4524 0.25 210 [0,> [0,> 0 [0,> [0,> 4555 0.25 [0,> [0,> 4556 0.25 N_River [0,> [0,> 4557 0.25 [0,> [0,> [0,> 0.045

PathFrac 11 [0,> [0,> 0.15 14 [0,> [0,> 0.15 20 [0,> [0,> 0.12 30 [0,> [0,> 0.08 40 [0,> [0,> 0.05 110 [0,> [0,> 0.05 130 [0,> [0,> 0.05 140 [0,> [0,> 0.05 160 [0,> [0,> 0.05 170 [0,> [0,> 0.05 190 [0,> [0,> 0.4 210 [0,> [0,> 0.15

RootingDepth 11 [0,> [0,> 1400 14 [0,> [0,> 1400 20 [0,> [0,> 1300 30 [0,> [0,> 1100 40 [0,> [0,> 1900

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