Rural Connectivity Improvement Project (RRP IND 52328)

CLIMATE RISK AND VULNERABILITY ASSESSMENT (CRVA) FOR THE RURAL ROADS IN MAHARASHTRA

I. INTRODUCTION

A. Background

1. The climate vulnerability of the rural roads to be improved under the proposed project is a function of climate change potential impact and the adaptive capacity of the Maharashtra Rural Road Development Association (MRRDA). The assessment of climate change potential impact is very much similar to environmental assessment requiring the definition of effects in terms of intensity, duration, and scope. The World Bank (2015)1 provides a more succinct definition in the context of transport which requires the assessment of exposure and sensitivity of rural roads of climate change to define the climate risk. In turn, the exposure to climate change is determined by the type, magnitude, timing, and speed of climate events and variation (Fay, Ebinger, and Block, 2010) while the climate sensitivity of rural roads is determined by structural design and location. However, potential impacts do not necessarily translate into actual impacts based on exposure and sensitivity. The adaptive capacity-defined here as the availability of resources to MRRDA for coping with impacts and minimizing damage, is an important factor on how potential becomes actual impacts.

2. The potential impacts of climate change to roads in general and rural roads are particularly well known. The increase in sea level rise and storm surge can damage or temporarily cut access through coastal roads. The increase in rainfall and rainfall intensity can overwhelm cross drains which can result to localized flooding, road embankment slope failures, traffic disruption, and washout of road sections. What is less known are the impacts of slow onset climate change like the gradual increase in air temperature and its impact of premature rutting and fatigue cracking during a typical 20-year economic life. Gudipudi, Padmini & Underwood, Shane & Zalghout, Ali. (2017)2 evaluated pavement distresses using historical and climate projections3 and AASHTOWare Pavement ME software indicated that projected increase in temperature will results to an increase from 2–9% for fatigue cracking and 9–40% for asphalt concrete rutting at the end of 20 years across all climatic zones. Kumlai, S., Jitsangiam, P. & Pichayapan, P. (2017)4 had similar findings on the effect of temperature increase to asphalt pavement. Their study assessed the effect of predicted increase in temperature to the dynamic moduli to express the viscoelasticity of asphalt concrete across a range of temperatures and frequencies. Using a 20- year temperature and climatic records which coincides with the economic life of typical rural road asphalt pavement for different pavement designs, the examination showed that an increase in temperature due to climate change will result to a shorter pavement life of around four years.

3. MJM Alam and M. Zakaria (undated)5 studied the extent of damage to road pavement structure due to prolonged flood submergence in Bangladesh. The assessment focused on asphalt concrete and tested for California Bearing Ratio for sub-grade and Marshall Stability and Flow for surface layer under 4, 7, 30 and 45 days of submergence. The study concluded that a

1 J.O.Ebinger and N. Vandycke. 2015. Vulnerability of Transport Systems to Climate Risks. 2 Impact of climate change on pavement structural performance in the United States. Transportation Research Part Transport and Environment. 57. 172–184. 10.1016/j.trd.2017.09.022. 3 Climate data from both an ensemble of 19 different climate models at both RCP8.5 and RCP4.5 as well as three individual prediction models at the same Representative Concentration Pathways (RCP) levels. 4 Kumlai, S., Jitsangiam, P. & Pichayapan, P. 2017. KSCE Journal of Civil Engineering. Volume 21: pp 1222. https://doi.org/10.1007/s12205-016-1080-6 5 MJM Alam and M Zakaria. ”Design and Construction of Roads in Flood Affected Areas.” Department of Engineering, BUET. 2

rural road inundation for 45 days will reduce its unit weight to 4.6%, 5.8% and 10.6% for compaction efforts of 56, 35 and 10 blows, respectively, and California Bearing Ratio reductions of 16.7%, 29.6% and 37.5%, respectively. For the surface layer, stability and flow of flexible pavement is affected by the duration of inundation. An inundation of 30 days causes the flow value to increase by about 93% and stability reduction by 26%. The study also indicated that that the longer the period of inundation of the asphalt concrete pavement, the more severe will be the deterioration although the rate of destruction may decrease.

B. Background of the Maharashtra Rural Connectivity Improvement Project

4. Maharashtra is ’s leading state in terms of its contribution to the national economy. In 2016–2017 Maharashtra accounted for 14.8% of India’s national gross domestic product (GDP).6 Maharashtra is also India’s second most populous state with an estimated population of 112 million (9.2% of the national population) and third largest in land area with 308,000 square kilometers (9.4% of the total land area). The state’s economy is driven by the service and industry sectors which accounted for 61% and 28% of the state’s Gross State Domestic Product in 2016– 2017. The Agriculture sector’s contribution to the economy has diminished over time from 21% in 1990–1991 down to 11% in 2016–2017. Agriculture and allied services accounts for 47% of employment overall but engages as much as 79% of the rural population. The agriculture sector is shifting towards high value commercial horticulture crops such as grapes, oranges and mangoes which requires a network or rural roads to allow effective transport of products to market centers.

5. Maharashtra has a road network of 303,000 kilometers (km), of which 67% are rural roads. Roads are the dominant mode of transportation, utilized by over 80% of passengers and 60% of freight traffic. However long-term underinvestment has affected all levels of the road network, and the rural road network is in the worst condition. In rural areas, many villages still rely on earthen tracks, which are unsuitable for motorized traffic and can easily become impassable during the rainy season. Poor road infrastructure affects economic growth in rural areas, agricultural productivity, and employment, and has a strong link to poverty. Greater investment in Maharashtra’s rural infrastructure is required to boost the agriculture sector and improve the livelihoods and living standards of the state’s rural population.

6. The state government recognizes the importance of rural connectivity in vitalizing rural livelihoods and addressing poverty alleviation. In 2000, the Government of India launched the Pradhan Mantri Gram Sadak Yojana (PMGSY)7 with the primary objective of providing connectivity by way of all-weather roads to eligible unconnected habitations in the rural areas. Under the PMGSY, the state government has completed upgrading of around 25,600 km of roads connecting 8,315 habitations by 2018.8 Following the PMGSY model, the state government initiated the Mukhya Mantri Gram Sadak Yojana (MMGSY) program to connect villages in remote rural areas that had not yet been reached by PMGSY, and to improve existing roads not covered under PMGSY. The MMGSY was launched in 2015–16 and aims to cover 30,000 km of rural roads over 5 years. By January 2019, the state had completed upgrading around 7,000 km under the MMGSY.

7. The proposed project takes a major slice of the MMGSY program and will have two components, these are:

6 Government of Maharashtra, Directorate of Economics and Statistics Economic. March 2018. Survey of Maharashtra 2017–2018. 7 Prime Minister's Rural Roads Scheme. Program website is published at http:/www.pmgsy.nic.in/ 8 A nationwide program in India to provide good all-weather road connectivity to unconnected villages. 3

(i) Improvement of 2,100 km of priority rural roads to all-weather standards with climate resilience, gender-inclusive, and road safety features, and (ii) Development of the MRRDA’s capacity on road asset management,

8. The succeeding Table and Figure presents the distribution of locations of the rural roads.

Table 1: Distribution of Rural Roads Proposed to be Improved Under Maharashtra Rural Connectivity Improvement Project Sr. Region/ District No of No of Length of Sr. Region/ District No of No of Length of No. Packages Roads road No Packages Roads road proposed proposed (Km) (Km) 1 6 22 91.2 1 5 10 70.18 2 6 28 79.1 2 6 13 72.82 3 Buldana 6 28 78.9 3 6 16 80.6 4 3 15 69 4 5 21 82.6 5 6 23 86.4 5 8 26 111.99 Amaravati Region 27 116 404.6 6 Wardha 5 13 65.05 1 4 14 66.6 Nagpur Region 35 99 348.64 2 Beed 6 28 99.2 1 9 46 111.175 3 Hingoli 4 19 79.94 2 6 18 81.75 4 Jalna 7 23 92.95 3 6 24 70.595 5 6 23 69.49 4 5 20 82.8 6 7 30 81.56 5 7 23 87.57 7 Osmanabad 5 26 77.44 Nashik Region 33 131 433.89 8 7 23 60.8 1 7 41 99.7 Aurangabad Region 46 186 627.98 2 5 27 67.1 1 Palghar 4 22 39.27 3 6 23 71.5 2 Raigad 4 20 54.789 4 9 36 94.2 3 5 35 81.2 5 6 28 51.3 4 Sindhudurg 5 20 67.55 Pune Region 33 155 383.8 5 4 15 60.25 Region 22 112 303.059 Maharashtra 196 799 2118.169

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Figure 1: Location of Proposed Rural Roads under the Maharashtra Rural Roads Connectivity Project (shown in red lines)

C. Objectives and methodology

9. The objectives of this CRVA are to: (i) assess exposure, sensitivity, and adaptive capacity of Maharashtra RCIP to climate risks; (ii) identify and prioritize region, district, and to the extent possible road specific climate risks that threatens the resilience of the project rural roads; and (iii) integrate in the detailed project reports (DPRs) climate-risk responsive road features and design a capacity building program for the MRRDA to improve climate resilient road design and construction practices

10. The CRVA methodology builds on climate-risk assessments performed in the previous road connectivity projects in the region. This study assesses the climate change vulnerability of the project roads as a function of climate risk and the adaptive capacity of the MRRDA, the government entity responsible for their construction and subsequent maintenance. This study starts with a review of climate change projections from various sources, expressed in term of temperature and rainfall to draw trends, absolute and relative changes to define the expected magnitude, and temporal and spatial variation to generate focused adaptation measures. This is followed by a description of the climate change sensitivity of the project that is dictated by two factors: the current structural design practices of the MRRDA and the location hazards which could be exacerbated by the projected change in temperature and rainfall. Map overlays of the 5

road location, hazards, and districts that are expected to experience more severe climate change allowed the initial assessment of the potential impacts of climate change. This was followed by transect walks covering all project roads. A transect walk is a participatory approach of gathering baseline, identifying environmental and climate risk, and formulating adaptation options by walking along the entire stretch of the project road. Identified potential climate change impacts from the map overlays and transect walks were addressed in the DPRs that incorporated engineering design and safeguard assessment findings and recommendations. For this project, the principal climate risk is attributed to the increase in rainfall and the sensitivity of the several districts and roads to flooding, landslides, storm surge, and seal level rise. Adaptive structural measures in terms of additional or bigger drainage, additional retaining walls, increase in road surface elevation, and construction on new side drains were included in the road design while the capacity building of the MRRDA in terms of planning and construction forms part of the implementation support consultant’s terms of reference. The succeeding figure is an adaptation of the Government of Australia’s framework for defining vulnerability as presented in the World Bank’s Moving Towards Climate Resilient Transport (2015) while the list below enumerates the activities undertaken under this study: (i) review of climate change projects in the region, and the State, (ii) Review of existing risks to the project roads that can be exacerbated by climate change to include flooding, sea level rise, storm surge, erosion and landslide, (iii) assess the sensitivity of rural roads to projected increase in temperature and rainfall, (iv) overlay projected change in rainfall and temperature with the existing locational risks, (v) conduct transect walk to all roads and identify with the field engineers and concerned communities’ particular sections of the roads that are prone to the identified climate impacts, (vi) engage the engineers and community to formulate engineering adaptation measures that should be included in the project design, and (vii) estimate the costs of adaptation measures for each road.

Projected Change in Temperature and Rainfall Current Rural Road Design Practices Exposure to Climate Change Sensitivity to Climate Change Location Risk e.g. flooding, lanslide, storm surge, sea Transect walk level rise, and incrase in air Potential Impact of Adaptive temperature Climate Change to Rural Capacity of Roads MRRDA

Climate Change Risk to Rural Roads

Figure 2: Framework for Defining Climate Vulnerability of Rural Roads in Maharashtra

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II. EXPOSURE OF THE PROJECT RURAL ROADS TO CLIMATE CHANGE

11. This section briefly describes the magnitude, timing, and speed of climate change to which the proposed rural roads will be exposed. Climate change, expressed in terms of changes in temperature and rainfall, over the immediate time slice of 2030s coinciding with the economic life of rural roads was considered using the Hadley Climate Model of the UK Met Office by the Maharashtra Department of Environment and the Beijing Climate Center Climate System Model as presented in the World Bank’s Climate Change Portal. The projections made by these organizations indicated a gradual increase in mean monthly temperature across the State in order of 0.68–1.68oC. However, substantial increase in monthly rainfall, in the order of 40–80% is expected during the 2030s.

12. India is undergoing accelerated change in climate over the past century. According to the World Bank, over the past century the country has undergone the following changes: (i) The mean annual temperature has increased by 0.56°C per 100 years between 1901 and 2007 (ii) The seasonal mean rainfall has decreased over the 20th century. (iii) The mean maximum temperature increase is 1.02°C per 100 years over the period 1901–2007. (iv) The mean minimum temperature increase is 0.12°C per 100 year over 1901–2007. (v) The extreme rainfall event has become more frequent over the 20th century in northern India. (vi) The sea level has increased by 0.21 meters as of 2009.

13. The Department of Environment, State Government of Maharashtra conducted climate modeling and projections as part of their Maharashtra State Adaptation Action Plan on Climate Change9. The Department used the Hadley Climate Model Version 3-HADCM3 developed by the UK Met Office and adopted a one-way nesting approach that allows a unidirectional sharing of global to regional model with a 25kmx25km resolution. The future changes in temperature and rainfall utilized PRECIS model for A1B scenario for baseline period from 1970–2000 and future time period of 2021–2041. Model results were validated against the India Meteorological Department’s 1x1 degree gridded data rainfall data from 1951–2007 and mean, maximum, and minimum temperature records from 1969–2005. Daily mean climatologies of district wise datasets (IMD, 2010) of number of rainy days, maximum temperature, minimum temperature and mean temperature values have been used to assess the district wise variation in the number of rainy days during June, July, August, and September and the variability in temperature. The climate change projections for the 2030s for the State of Maharashtra if provided in the succeeding Table and significant findings are as follows: (i) Temperature and rainfall are projected to increase all over the state though there are regional variations. The mean temperature for 2030s shows a slight increase in temperature of 1–1.5oC during all seasons. Similar kind of increase is also found in the minimum temperature and maximum temperature with approximately 1–2oC increase in 2030s compared to baseline. (ii) Amravati and Aurangabad divisions will have greater rise in annual mean temperature than other parts of the state.

9 Government of Maharashtra, Department of Environment. 2014. “Assessing Climate Change Vulnerability and Adaptation Strategies for Maharashtra: Maharashtra State Adaptation Action Plan on Climate Change (MSAAPC).” file:///C:/Users/bingr/Documents/Mumbai%2007022019/Maharashtra%20Climate%20Change%20Final%20Report. pdf 7

(iii) Projected increase in monsoon rainfall by the 2030s is relatively more for Amravati and Nashik divisions, though divisions like Konkan and Nagpur receive, are expected to continue to receive more rainfall in absolute terms. (iv) Minimum temperature is projected to increase particularly in the Konkan, Pune and Nashik divisions in the 2030s relative to the baseline for these areas.

14. In terms of rainfall spatial distribution, frequency, and intensity of extreme rainfall the same study revealed that extreme rainfall in 2030s, defined rainfall intensity of a monsoon season in future which is greater than 99% of rainfall intensity of monsoon season in the entire baseline period at each grid point , intensity increases in all regions, and with large amount of increase in Aurangabad and northern regions of Nashik division compared to Konkan belt and Vidharbha Region. Extreme rainfall index, calculated 99th percentile of rainfall at every grid for the JJA time period, shows an increase in all regions with large amount of increase in Aurangabad and northern regions of Nashik division compared to Konkan belt and Vidharbha Region. It essentially means that Aurangabad and northern Nashik regions would have higher contribution from extreme rainfall in their total rainfall of 2030s.

15. The seasonal and spatial temperature variability projected in 2030s should also be a major concern of the MRRDA in the design and construction of rural roads. Although very little change is expected from the seasonal mean temperature, maximum temperature and minimum temperature, the early onset of the monsoon seems to cool these temperatures more than observations. The mean temperature shows a slight increase 1–1.5oC during all seasons; and minimum temperature and maximum temperature increases approximately 1–2oC. The and regions are expected to have higher increase in temperature between 1–1.2oC compared to Nashik, Pune and Konkan regions with 0.5–1oC.

Figure 3: Projected increase in temperature over Maharashtra in the 2030s relative to the baseline (in degree Celsius)

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Figure 4: Projected increase in precipitation over Maharashtra in the 2030s relative to the baseline (in percent)

Table 2: Division-wise climate change projections (Maharashtra Environment Department)

A. Projected Climate Change in the Study Area

16. Climate Change Projections Based on CMIP5 and RCP8.5

17. A more recent projection of temperature and rainfall changes in the State is provided in the World Bank’s Climate Change Portal 2.0. The succeeding Tables present the temperature and rainfall projection based on the Beijing Climate Center Climate System Model (bcc-csm_1) 9

which has conducted most of the Coupled Model Inter-Comparison Project Phase 5 experiments. The projected change in temperature and rainfall were derived using the representative concentration pathways 8.5. Historical records were compiled by the Climate Research Unit, University of East Anglia from 1986–2005. The significant findings are as follows: (i) The State is expected to experience a general increase in average monthly temperature from 0.68oC in Nagpur to 0.79oC in Nashik Region. Konkan and Nashik may experience higher temperature increase compared to the other regions. (ii) Highest increase in average monthly temperature are expected in Nagpur and Amravati with 1.45oC and 1.43oC during the month of October. (iii) The project will experience an increase in rainfall. The highest annual average increase is expected in Konkan and Nagpur regions. (iv) Substantial increase in monthly rainfall may occur during the months of June and August across the State. Higher increase in monthly rainfall are expected in Nagpur and Konkan which could register 89% and 78% higher than historical averages.

18. Although downscaled global climate models are in agreement on the increasing trend of monsoon rainfall, the distribution is not linear in between the months of June, July, August, and September. Patil10 et. al (2013) assessed trend of rainfall in using 47 years (1958– 2004) data from 13 observatories pertaining to annual, seasonal (kharif) and monthly rainfall depths during kharif season using non-parametric Mann-Kendall (MK) test and modified Mann- Kendall (MMK) trend test. The study revealed “seasonal (Kharif) rainfall was observed to be decreasing and June month’s rainfall showed increasing trend while July month’s rainfall showed decreasing trend at 99%, 95% and 90% level of significance, respectively. The decreasing trend of rainfall was observed during July month for the rainfall gauging stations under high rainfall zone (Welhe-99%, Mulshi-95%andMaval-95%) and medium rainfall zone (Bhor-99%, Ambegaon-99%, Junnar-95%, Khed-99%, Pune-99% and Purandhar-99%) of Pune district.”

Table 3: Historical and Projected Increase in Temperature in the Project Regions, CMIP5, RCP8.5 Month Nashik Aurangabad Amravati Nagpur Konkan Pune Historical Projected Historical Projected Historical Projected Historical Projected Historical Projected Historical Projected Increase Increase Increase Increase Increase Increase Jan 20.62 1.17 21.55 1.11 21.61 0.92 21.16 0.81 23.19 0.87 20.88 1.04 Feb 22.22 0.89 23.68 0.89 24.32 0.81 23.96 0.84 24.25 1 22.54 0.95 Mar 25.84 0.92 27.54 0.91 28.55 0.73 28.25 0.67 26.54 0.81 25.9 0.88 Apr 28.89 0.98 30.82 0.97 32.48 0.77 32.35 0.76 28.44 0.91 28.81 0.96 May 30.16 0.98 32.2 1.07 34.73 1.18 35.11 1.14 29.05 0.73 29.92 0.15 Jun 27.99 0.16 29.34 -0.1 31.67 -0.39 32.12 -0.42 26.61 0.16 27.58 0.65 Jul 25.61 0.54 26.59 0.48 27.65 0.24 28.06 0.26 25.21 0.77 27.47 0.65 Aug 24.57 0.86 25.66 0.8 26.53 0.39 27.05 0.26 24.83 0.8 24.75 0.83 Sep 25.33 0.03 26.21 -0.16 27.17 0.33 27.58 0.28 25.31 0.48 25.25 0.19 Oct 25.63 1.07 26.35 1.25 26.79 1.43 26.59 1.45 25.88 1.12 25.44 1.1 Nov 23.35 0.88 23.91 0.95 24.17 1 23.52 0.99 25.04 0.93 23.26 0.89 Dec 20.93 1.02 21.35 1.06 21.49 1.09 20.77 1.08 23.37 0.9 20.77 1.02

10 Patil, Jyoti & Sarangi, A & Singh, D.K. & R Rao, A & Dahiya, Shashi. 2013. Rainfall trend analysis: A case study of Pune district in western Maharashtra region. Journal of Soil and Water Conservation. 12. 10

Table 4: Historical and Projected Increase in Rainfall in the Project Regions, CMIP5, RCP8.5 Month Nashik Aurangabad Amravati Nagpur Konkan Pune Historical Projected Historical Projected Historical Projected Historical Projected Historical Projected Historical Projected Increase Increase Increase Increase Increase Increase Jan 1.57 4.53 4.72 9.37 4.72 9.37 13.38 0.47 0 0.06 1.03 6.65 Feb 0.48 1.68 1.33 0.65 1.33 0.65 16.8 -0.34 0.16 -0.76 0.63 1.7 Mar 1.33 3.58 2.73 5.38 2.73 5.38 20.08 -1.93 2.19 0.27 1.05 3.89 Apr 2.83 1.02 2.66 1.65 2.66 1.65 8.07 8.99 17.1 1.78 6.92 1.33 May 19.32 1.56 20.43 1.62 20.43 1.62 16.07 1.34 37.39 6.57 26.08 2.46 Jun 138.05 58.77 150.51 65.43 150.51 65.43 168.2 52.98 345.57 74.51 173.78 73.13 Jul 231.51 -12.62 154.38 -13.09 154.38 -13.09 297.68 32.55 439.2 111.51 195.2 -16.67 Aug 193.21 55 152.08 45.99 152.08 45.99 284.44 32.45 277.43 170.21 151.14 64.79 Sep 178.57 15.58 147.89 19.7 147.89 19.7 165.4 21.6 166.16 66.02 156.09 5.42 Oct 56.52 -11.82 53.51 15.82 53.51 -15.82 62.75 12.84 100.79 6.22 70.75 -12.85 Nov 8.53 0.34 14.75 -0.37 14.75 -0.37 14.1 0.5 19.62 10.35 11.86 -0.63 Dec 6.27 -1.59 11.81 -1.1 11.81 -1.1 12.72 4.06 9.8 10.36 10.09 -1.89 III. SENSITIVITY OF THE PROJECT RURAL ROADS TO CLIMATE CHANGE

19. The current practices in the structural design of the rural roads make it more sensitive to changes climate change. Some of these practices like the use of annual average rainfall in the pavement design, road improvement ore focused on pavement, and the tendency to simply maintain existing structures like the number, locations, and sizes of culverts highlights the sensitivity of the rural roads with the prospect of different climatic conditions. The lack of collector side drains, inadequate retaining walls particularly on flood-prone areas, and inadequate collector side drains were identified during the engineering design stage. In sizing minor hydraulic structures like drainage works, bridges, and culverts, design engineers rely on different charts of highest daily rainfall for different return periods. These charts were derived based on highest recorded daily rainfall. In India, the map of one-day highest rainfall was first developed in 1938 based on a 30-year record from 1891–1920, updated to 1955 records, and then in 1990. In Godavari basin that encompasses the project regions, maximum daily rainfall occurs during monsoon depressions or cyclonic storms emanating from the Bay and Bengal and moving across the country in a westerly to northwesterly directions is the single biggest contributor to heavy rainfall. However, as shown on the previous sections, global climate models consistently projected higher monthly rainfall in order beyond 40% and more frequent occurrence of rainfall extremes.

20. The location of the project rural road where natural hazards already exist is also a major climate sensitivity determinant. Certain sections of the State are susceptible to erosion, flooding, and storm surge and sea level rise making it more sensitive to climate change than the other areas. The results of overlay between road location and risk maps allowed the qualitative identification of sensitivities to climate change and are presented below: (i) Erosion. The steep portions Maharashtra's western part forming the Sahyadri Range rising to an average elevation of 1,000m are susceptible to erosion as depicted in the succeeding figure. Along the ridge line is considered as having very high risk to landslide while the immediate surround areas are considered as high risk. An overlay of the project road location, a sample of which is provided in Figure 5, allows the identification of roads located on very high and high erosion risk areas. A total of 11 roads are located on high erosion risk areas, these are: (a) MMGSY 1079, ADB VR-130, SH34-Sapane Bk, Palghar, Vada; (b) MMGSY 1113, ADB VR- 266&VR275, SH76-Chikhale, Palghar, Vada; (c) MMGSY 1072, ADB VR-356, SH- 79-Sathepada, Palghar; (d) MMGSY 1078, ADB VR-360/VR442, SH79- Dongarpada, Palghar, Vada; (e) MMGSY 763, ADB VR-85, SH82-Umberkhand, Thane, ; (f) MMGSY 1118, ADB VR-62, Janori-Padali Deshmukh, Nashik, 11

Igatpuri; (g) MMGSY 1385, ADB VR30,31, MDR03-Sambhajiwadi (Thkarwadi), Pune, Junnar; (h) MMGSY 623, ADB VR-45, ODR-38-Anjrun Jod Marg, Raigarh, Khalapur; (i) MMGSY 643, ADB VR-137, Waki-Nanemachi, Raigarh, Mahad; (j) MMGSY 663, ADB VR-130, SH-102 Walan-Zolicha Kond – Bhande Kond- Tiedewadi, Raigarh, Mahad; and (k) MMGSY 2262, ADB ODR-93, Sakharpa- Guravwadi, Sangameshwar (ii) River Flood. Figure 6 provides a section of the flood risk map revealing the flood prone areas that are mostly located along rivers and reservoirs. Floods mainly result from damage to dam embankments, release of excessive water from dams, improper storm-water drainage systems and unplanned urbanization (ENVIS, Maharashtra). In Maharashtra, floods mainly result from damage to the dam embankments, release of excessive water from dams, improper storm-water drainage systems and unplanned urbanization. The eastern part of the state has higher risk of flooding from the Tapi, Wardha, and Pen Ganga rivers while the central part like the Deccan Plateau which is drought-affected also experiences flood particularly from June to October when the area receives 50% of the total annual rainfall of 600–750 mm through the southwest monsoon. The UN Global Risk Platform identified these areas as having low risk with less than 183 cm of flood at 25-year return period. Think Hazard11 classified medium river flood for the state of Maharashtra based on historical records (see

11 http://thinkhazard.org/en/report/1498-india-maharashtra/FL 12

(iii) Figure 7). Medium risk means that there is at least 20% chance of potentially damaging and life-threatening river floods will occur in the 10-year cycle project design and construction methods should consider this risk. The project districts under medium risk are: Kohalpur, Latur, Parbhani, Hingoli, Yavatmal, Akola, Chandrapur, Garhchiroli, Gondia, and Bandara. Based on the transect walk12 conducted for each project road, 76 of the total 799 roads have sections that are at risk to flood submergence with a total length of 65.3 km. Most of these roads are located in Pune and Konkan with 40 and 24 roads prone to flooding, respectively. (iv) Cyclones. The state of Maharashtra with more than 720 km of coast between to Goa is at high risk to cyclones. According to the Mararashtra Disaster Management Authority, from 1890–1995, 207 depressions/cyclonic storms/severe cyclonic storms have been recorded. Of these, 19 have affected Maharashtra particularly the Goa coast as the direction of the cyclones are moving away from the state. Think Hazard also classified the state as high hazard for cyclones or typhoons with more than 20% chance of potentially damaging winds in the next 10 years. The districts of Thane, Raigarh, Ratnagiri, Sindudurg, Nashik, Satara, Kolhapur, Sangli, Solapur, Osmanabad, Bid, Ahmednagar, and Garchiroli are more vulnerable than the rest of the state. A total of 338 project roads are at high risk to cyclones. (v) Storm surge and Coastal Flooding. The entire coastal area of the State is at risk to storm surge and coastal flooding. The UN Global Data Risk Platform provides at most 1.4 meters storm surge hazard with a return period of 25 years while Think Risk predicts potentially-damaging waves are expected to flood the coast at least once in every 10 years. The districts of Thane, Raigarh, and Ratnagiri are particularly at risk. Of the 799 roads to be improved under the project, only 1 road is located along the coast and this is the 4 km MSH 04 to Barshiv-Bhoighar Road, , Konkan Region

21. During the transect walk, representatives from the communities, design engineers, and safeguard staff are guided by an environment checklist that allowed the identification of specific road sections that are vulnerable to the potential impacts of climate change and focusing on flood, landslide, storm surge, and sea level rise– risks that the participants and the secondary data assessments have identified as the principal climate sensitivities of the project. Specific checklist items that allowed the identification of these sections include: (i) Section C1. Is the project located along the Coastal Area/Mangrove (along roadside)? Distance from the Coastline: ____ km; ( ) more than 50%; ( ) less than 20 (ii) Section D1. Are there any areas with landslide or erosion problems along the road? (If yes, indicate the location whether Right or Left side and the chainage) (iii) Section D2. Are there any Tanks/streams /rivers etc. along/crossing the road or any lakes/swamps beside the road? (If yes, list them indicating the location Right/ Left or crossing and the chainage) (iv) Section D3. Is the area along the project road prone to flooding or any problems of water stagnation and other drainage issues? (If yes, mention chainage, flood level and frequency)

12 A transect walk is a community-based exercise that involves representatives from the community, women, engineers, and safeguard specialists to survey the entire length of the proposed road to the extent possible by walking to take stock of the environmental baseline including common property resources that may be affected by the improvement of the proposed rural road and identify key issues such as alignment, affected private properties, utilities, trees, flood and erosion prone area, field drain crossings, and similar items that should be considered in the final design. 13

(v) Section E. Public Consultations: i) Consultation with local community was conducted before finalizing the alignment (Attach list of people met and dates); ii) Any suggestion received in finalizing the alignment and road related environmental issues. If suggestions received, were they incorporated into the design?

Figure 5: A Section of the State showing the Project Roads Located on High and Very High Risk or Erosion

Figure 6: A section of the State Showing the 25 Year Flood Hazard

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Figure 7: Map Showing Medium River Flood Risk for the State of Maharashtra

Figure 8: Land Slide Hazards, State of Maharashtra (UN Global Data Risk Platform

Figure 9: Location of the only project road along the coast, MSH04 to Barshiv-Bhoigar, Raigarh District, Konkan Region 4 kms total Length

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Figure 10: Storm Surge Hazard, 25 Years Return Period, State of Maharashtra (Source: UN Global Risk Data Platform)

A. Project’s Climate Change Mitigation Potential

22. Using the ADB Transport Emission Evaluation for Project, improvements in the pavement, expressed in road roughness from 7m/km to 2.5 m/km and road capacity due to the construction of the shoulders will allow vehicles to travel faster and reduce congestion which results to decrease in fuel consumption. The reduction in the overall CO2 emission considered both future vehicular emissions based on projected traffic growths and road construction which is assumed to contribute as much as 48,400 tons/km. An estimated 1,649 tons of CO2 annually can be reduced due to road improvement. The concomitant cost of mitigation was assumed to equal to the cost of pavement improvement only.

B. MRRDA’s Climate Change Adaptive Capacity

23. The MRRDA’s capability to cope with impacts and minimize damage due to climate change is limited. The proposed project is the first partnership on rural roads development between the MRRDA and ADB. MRRDA has mainly relied on the PMGSY program for guidance and funding and since rural roads are exempted from the environmental notification there was no need to develop its safeguard capability. During the preparation of the proposed project, all environmental assessments and planning were done through consultants as there was not a single person assigned and capable of at least coordinating the activities to comply with the Bank’s environmental requirements. Although the MRRDA management has nascent understanding of the elements on how to build a climate resilient rural roads system, lack of resources and guidance has hampered its implementation. To illustrate, following flood events the reconstruction of the roads involves installation of larger drains or strengthening road embankments that incurred damages and indirectly addressing climate vulnerability.

24. Through the project, the ADB introduced the concept and methodologies for climate risk screening that covered the identification of types of hazards, exposure to hazards, and adaptation measures, there is a need for the MRRDA to formalize its climate adaptation elements to include: (i) Revisit the existing rural road sector and strategic planning process to include the assessment of climate risk and vulnerability. 17

(ii) Need to strengthen the understanding of resilient technologies and adaptation measures. (iii) Need to enhance awareness and resources available from policy making to road design and construction. (iv) Need to explore post-disaster support to ensure the rural roads remain operational for longer periods during extreme weather events and the ability to restore accessibility and connectivity after a disaster.

IV. BUILDING THE ADAPTIVE CAPACITY OF THE PROPOSED PROJECT

25. The foregoing sections assessed the potential impacts of climate change to the proposed rural road improvement project in Maharasthra. The projected climate change which will bring increase in temperature and rainfall, its temporal variation is expected to expose the rural roads to risk that can hinder the realization of the planned economic and social benefits. The potential impacts of climate change go beyond the increase in maintenance and emergency repair of rural roads due to premature deterioration from exposure to higher temperature or submergence to flood waters or repairs from landslides and storm surges. The disruption of access also brings a string of other indirect costs to include increase in travel time, fuel, and vehicle operation due to bad roads, the social costs due to poor access of communities to vital health and government services and missed work and revenue loss. These climate risk can be minimized through structural interventions and capacity building of the MRRDA.

A. Structural

26. To address the potential impacts of climate change to the rural roads, structural measures were integrated into the DPRs of each project road. These measures were formulated with the community during the transect walks. To address the potential impacts from flooding, storm surge, sea level rise, erosion and land slide, the project invested US$22.117 million in constructing new cross drains/culverts, increasing capacity of cross drains, constructing new retaining walls, increasing the road elevation, and constructing new side drains. To cope the slow onset climate change like the increase in temperature, the project was designed to make the contactors responsible for the road maintenance 5 years after the completion of the civil works. The cost of the 5-year maintenance is estimated at $13.551million.

B. MRRDA Capacity Building

27. The project will initiate the capacity of the MRRDA in climate screening, decision support systems to include knowledge products on climate resilient technologies and practices, design of information support systems to analyze climate data, and post-disaster risk and recovery among others. The capacity building will be delivered by two entities, these are: (i) Engagement of a project implementation support consultant is to support the project management unit, Regional Superintending Engineers, project implementation units, to implement the project including adapting climate change. (ii) A proposed transaction technical assistance (TA) will strengthen the capacity of the MRRDA in managing rural road infrastructure including climate-resilient design and construction of rural roads.

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Table 5: Estimated Cost of Structural Climate Adaptation Measures Region/District New Cross Drains Cross-Drains New Retaining Wall Length of Road Surface New Side Drains Capacity Increased Increased Ht

Number Cost No Cost Length Cost Length Cost Length (m) Cost (m) (m) Amravati 698.0 3690.4 2.0 0.4 2188.0 29.1 7901.0 19.7 15616.0 71.5 Akola 178.0 1058.6 0.0 0.0 270.0 3.5 0.0 0.0 426.0 1.8 Amravati 122.0 641.0 0.0 0.0 624.0 8.3 0.0 0.0 12117.5 52.8 Buldana 98.0 427.0 2.0 0.4 525.0 7.3 0.0 0.0 1081.0 4.5 Yavatsmal 214.0 1087.7 0.0 0.0 769.0 10.0 7901.0 19.7 1523.0 9.6 Washim 86.0 476.1 0.0 0.0 0.0 0.0 0.0 0.0 468.5 2.8 Aurangabad 844.0 2350.5 1.0 0.8 5175.0 27.5 0.0 0.0 7718.3 31.2 Aurangabad 74.0 215.0 0.0 0.0 180.0 1.2 0.0 0.0 305.0 1.3 Beed 170.0 590.7 0.0 0.0 1390.0 6.0 0.0 0.0 1550.0 5.7 Jalna 109.0 277.3 0.0 0.0 850.0 4.1 0.0 0.0 150.0 0.4 Osmanabad 125.0 399.0 1.0 0.8 335.0 2.6 0.0 0.0 1160.0 4.8 Nadeed 90.0 231.1 0.0 0.0 0.0 0.0 0.0 0.0 1178.3 4.9 Latur 79.0 183.8 0.0 0.0 1220.0 7.4 0.0 0.0 3175.0 13.3 Parbhani 88.0 176.4 0.0 0.0 350.0 2.1 0.0 0.0 50.0 0.4 Hingoli 109.0 277.3 0.0 0.0 850.0 4.1 0.0 0.0 150.0 0.4 Konkan 635.0 1141.0 119.0 41.9 8812.5 53.8 465.0 4.0 10626.0 26.8 Thane 109.0 147.8 10.0 1.4 167.0 0.8 10.3 0.2 2071.0 5.3 Palghar 112.0 217.9 33.0 8.5 1137.0 6.2 0.0 0.0 725.0 2.1 Raigad 104.0 190.7 0.0 7.7 2310.5 13.2 0.0 0.0 3039.0 7.7 Ratnagiri 214.0 365.2 19.0 2.2 3810.0 21.5 180.5 1.1 2650.0 6.6 Sindudurg 96.0 219.5 57.0 22.0 1388.0 12.1 274.3 2.7 2141.0 5.1 Nagpur 675.0 2094.0 5.0 0.7 808.0 10.8 3825.0 9.6 32191.9 65.3 Bhandara 90.0 366.9 0.0 0.0 65.0 1.3 0.0 0.0 3340.0 6.4 Chaudrapur 99.0 246.2 0.0 0.0 260.0 1.8 0.0 0.0 5642.0 7.7 Gadchiroli 81.0 201.7 0.0 0.0 155.0 1.9 0.0 0.0 3740.0 9.8 Gondia 154.0 418.2 0.0 0.0 50.0 0.7 0.0 0.0 8125.9 16.5 Nagpur 137.0 449.5 2.0 0.3 237.0 4.4 3825.0 9.6 7429.0 15.1 Wardha 114.0 411.6 3.0 0.4 41.0 0.6 0.0 0.0 3915.0 9.9 Nashik 1063.0 3130.4 0.0 0.0 2425.0 36.8 330.0 0.2 100024.0 249.7 Ahmednagar 291.0 631.8 0.0 0.0 866.0 11.2 330.0 0.2 9381.0 23.0 Dhule 183.0 713.7 0.0 0.0 415.0 6.0 0.0 0.0 21155.0 52.6 Jalgaon 136.0 348.6 0.0 0.0 118.0 1.5 0.0 0.0 21858.0 52.7 Nandurbar 169.0 689.1 0.0 0.0 279.0 3.9 0.0 0.0 23868.0 61.8 Nashik 284.0 747.0 0.0 0.0 747.0 14.2 0.0 0.0 23762.0 59.5 Pune 948.0 2475.2 0.0 7.8 3565.4 49.1 40807.0 102.0 9092.0 22.5 Kolhapur 124.0 290.7 0.0 4.4 262.0 2.6 7305.0 18.3 3236.0 9.7 Pune 274.0 562.0 0.0 0.2 1620.0 22.0 1795.0 4.5 610.0 1.0 Sanghi 117.0 308.0 0.0 1.1 383.0 3.9 7620.0 19.1 1123.0 2.4 Satara 193.0 754.1 0.0 2.1 712.4 12.6 20137.0 50.3 3317.0 7.5 Solapur 240.0 560.4 0.0 0.0 588.0 8.0 3950.0 9.9 806.0 2.0 Total 4863 14881 127 52 22974 207 53328 135 175268 467 USD 20,906,794.19 72,388.44 291,019.12 190,330.85 656,134.71 USD 22,116,667.30