Infrastructure for Climate Resilient Growth · Chhattisgarh and Odisha but for Bihar was only...

Infrastructure for Climate Resilient Growth Vulnerability assessment

___________________________________________________ Report for IPE Global Limited SCA ref: IPE-INT-ICRG-2016 (135) – Ricardo

ED 61288 | Issue Number 2 | Date 31/03/2017

Infrastructure for Climate Resilient Growth | i

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Author:

Richard Smithers, Nidhi Mittal, Mohiuddin Ahmed, Navneet Naik, Ben Kiff, Sanjay Dube

Approved By:

Heather Haydock

Date:

31 March 2017

Ricardo Energy & Environment reference:

Ref: ED61288 - Issue Number 2

Infrastructure for Climate Resilient Growth | 1



Executive summary This report describes a vulnerability assessment, which has sought to identify what issues are highly vulnerable to climate change and extreme weather events, where and for whom across the 103 ICRG blocks that can be addressed by MGNREGS options. This information should be an important consideration for relevant decision-makers at Gram Panchayat, block, district and state levels to ensure that MGNREGS is targeted in ways that promote climate resilience of both natural resources and the communities that depend on them. In order to ensure that the vulnerability assessment is able to inform the MGNREGS planning cycle during ICRG’s first year, the assessment was largely a desk exercise building upon methods used by other studies of climate change vulnerabilities in India and on the ICRG team’s previous application of definitions in the Intergovernmental Panel on Climate Change Fifth Assessment Report. This meant that the scope and resolution of the vulnerability assessment in terms of the biophysical and socioeconomic issues that it addressed were determined by the extent of available data. The vulnerability assessment was produced according to the following stepwise process:

1. Climate sensitivities were identified by using biophysical parameters as proxies for climate sensitivities. Similarly, adaptive capacities were addressed by using socioeconomic parameters that are proxies for adaptive capacities. The parameters reflect those used by other studies of climate change vulnerabilities in India and, importantly, the potential contribution of MGNREGS works to reducing climate sensitivities or increasing adaptive capacities i.e. their ability to address climate vulnerabilities and thereby increase resilience. The final selection (see table below) only included parameters supported by suitable open access datasets.

Final selection of biophysical and socioeconomic parameters Biophysical Socioeconomic Groundwater availability Net irrigated area Irrigation intensity Area under foodgrains Cropping intensity Crop yield – foodgrains Soil erosion Soil fertility Number of adult cattle Forest cover

% Households with monthly income < Rs 5000 % Landless households deriving major part of their income from manual casual labour % Houseless rural % Women-headed households % Disabled % Primitive tribal group households

2. Separate maps were produced for each of the biophysical parameters and socioeconomic

parameters by ICRG block and/or district dependent on data availability. The values of each parameter for each block or district was ranked relative to values for the parameter across all ICRG blocks or districts within each state as High (H), Medium (M) and Low (L) and colour-coded maps were produced using a GIS.

3. Relevant biophysical parameters were aggregated in different groupings in relation to four

broad climate-sensitive issues (Water, Land, Agriculture and Forests) and, similarly, the socioeconomic parameters were aggregated in different groupings with regard to two broad socioeconomic issues that limit adaptive capacity (Poverty and Marginalisation). Aggregate climate sensitivity and adaptive capacity were then calculated at block and/or district level and subdivided into H, M and L classes and further colour-coded maps produced.

4. For each state, the resultant aggregated maps for ICRG blocks and/or districts of the four

climate-sensitive issues were each overlaid separately with the resultant aggregated maps of each of the two issues relating to adaptive capacity, interacting the H, M, L scores using a matrix to identify a combined H, M, L score for the vulnerability of each block or district. Colour-coded maps were produced by block and/or district of these various vulnerabilities, as well as aggregate vulnerability.




5. State directories were produced to supplement presentation of the maps, which list for each state by ICRG block and/or district: a. Aggregate vulnerability (i.e. H, M or L determined from all of the biophysical and

socioeconomic parameters in combination) b. Vulnerabilities where ranked as High in relation to each of the possible combinations of the

four climate-sensitive issues and two issues related to adaptive capacity c. Rankings (H, M or L) of the individual biophysical and socioeconomic parameters

associated with vulnerabilities ranked as High, in order to provide a simple overview of what climate sensitivities need to be reduced and adaptive capacities increased, where and in relation to whom, if vulnerabilities are to be reduced and climate resilience thereby increased.

The vulnerability assessment’s stepwise process was undertaken at district and block level for Chhattisgarh and Odisha but for Bihar was only possible at district level due to a lack of block-level data for the biophysical parameters. A detailed explanation is provided of how it is intended that decision-makers at all levels can make short term (April – June 2017) use of the maps and directories to inform prioritisation of MGNREGS options that have potential to reduce climate sensitivities or increase adaptive capacities and thereby resilience. It will be important that decision-makers use the outputs of the vulnerability assessment as a general guide rather than interpreting them as being specifically correct. Ultimately, vulnerabilities at any specific location need to be determined bottom-up supported by knowledge of the outputs of this vulnerability assessment at block and district levels. Ground-truthing of the final output of the vulnerability assessment with stakeholders at block, district and state level is strongly recommended in order to ensure the efficacy of the assessment and common understanding and commitment to its use in informing decisions. The ICRG team will build upon the vulnerability assessment by developing a menu of priority MGNREGS options for each ICRG district and block by end of June 2017. MGNREGS options will be assessed in terms of their ability to address vulnerabilities by reducing climate sensitivity or increasing adaptive capacity and thereby promote resilience. It is proposed that MGNREGS options will be ranked on a relative basis using criteria that build upon those outlined in the technical guidelines for the national adaptation plan process published by the United Nations Framework Convention on Climate Change (UNFCCC) Secretariat. In the medium term (July 2017 onwards), these menus could further inform MGNREGS planning decisions at all levels by providing a simple overview of the relative priority of MGNREGS options at block and district level not only in relation to high vulnerabilities and associated climate sensitivities and low adaptive capacities but also with regard to issues, such as: potential climate impact if suitable MGNREGS options are not implemented; their efficacy; timing/urgency for action; likely social acceptance; availability of suitable technology; knowledge and skills; costs (including human resources); and co-benefits for adaptation, development and mitigation. The systematic process of identifying highly vulnerable issues and ranking MGNREGS works in their regard could be used by the ICRG team to contribute to training and capacity building at all levels, identification of best practices, highlighting research and evidence needs, and further development of the programmes monitoring and evaluation framework. The outputs from the vulnerability assessment and subsequent menus of priority MGNREGS options could also help inform measurement of social benefits from the ICRG programme. In addition, the outputs of the vulnerability assessment outputs might be used by others beyond ICRG and MGNREGS to promote implementation of convergence between complementary government schemes that have potential traction on the biophysical climate sensitivities and socioeconomic adaptive capacities that have been addressed in this study. As an immediate and important next step after this deliverable is finalised, a practical and concise version of this report will be produced for stakeholders at state, district, block or gram panchayat level. It is intended that it would comprise:

A brief non-technical bullet point summary of the method and data used

The state directories of ICRG blocks and districts

A straightforward explanation of how they can make short term (April – June 2017) use of the maps and directories to inform prioritisation of MGNREGS options that have potential to reduce climate sensitivities or increase adaptive capacities and thereby resilience.




Table of contents

1 Background ................................................................................................................ 5 1.1 Vision and purposes of vulnerability assessment ............................................................. 6

2 Methodology .............................................................................................................. 6 2.1 Definitions of terms ............................................................................................................ 6 2.2 General approach .............................................................................................................. 7 2.3 Selection of parameters .................................................................................................... 9 2.4 State-specific approaches ............................................................................................... 12 2.5 Caveats and assumptions ............................................................................................... 12

3 Findings .................................................................................................................... 13 3.1 Maps of individual biophysical and socioeconomic parameters ..................................... 13 3.2 Maps of climate sensitivities by aggregated biophysical parameters ............................. 13 3.3 Maps of adaptive capacities by aggregated socioeconomic parameters ....................... 13 3.4 Maps of climate vulnerabilities ........................................................................................ 14 3.5 State directories of vulnerabilities by district and block ................................................... 14

4 Next steps: use of vulnerability assessment to prioritise MGNREGS options .... 15

5 Recommendations ................................................................................................... 17 5.1 Use of vulnerability assessment in MGNREGS planning ............................................... 17

5.1.1 Short term (April – June 2017) ............................................................................... 17 5.1.2 Medium term (July 2017 onwards) ......................................................................... 18 5.1.3 Longer term ............................................................................................................ 18

5.2 Use of vulnerability assessment across ICRG outputs ................................................... 18 5.3 Use of vulnerability assessment by others ...................................................................... 18

6 References ............................................................................................................... 18

7 Appendices ................................................................................................................. i Appendix 1: IPCC AR5 definitions of terms Appendix 2: Open access datasets used for each biophysical and socioeconomic parameter Appendix 3: Bihar: State directory of high vulnerabilities by district Appendix 4: Chhattisgarh: State directory of high vulnerabilities by district Appendix 5: Odisha: State directory of high vulnerabilities by district Appendix 6: Bihar: Index of ICRG districts Appendix 7: Bihar: Maps of climate sensitivities represented by individual biophysical parameters Appendix 8: Bihar: Maps of adaptive capacities represented by individual socioeconomic

parameters Appendix 9: Bihar: Maps of climate sensitivities by aggregated biophysical parameters Appendix 10: Bihar: Maps of adaptive capacities by aggregated socioeconomic parameters Appendix 11: Bihar: Maps of vulnerabilities Appendix 12: Chhattisgarh: Index of ICRG districts and blocks Appendix 13: Chhattisgarh: Maps of climate sensitivities represented by individual biophysical

parameters Appendix 14: Chhattisgarh: Maps of adaptive capacities represented by individual socioeconomic

parameters Appendix 15: Chhattisgarh: Maps of climate sensitivities by aggregated biophysical parameters Appendix 16: Chhattisgarh: Maps of adaptive capacities by aggregated socioeconomic parameters Appendix 17: Chhattisgarh: Maps of vulnerabilities Appendix 18: Odisha: Index of ICRG districts and blocks Appendix 19: Odisha: Maps of climate sensitivities represented by individual biophysical parameters Appendix 20: Odisha: Maps of adaptive capacities represented by individual socioeconomic

parameters Appendix 21: Odisha: Maps of climate sensitivities by aggregated biophysical parameters Appendix 22: Odisha: Maps of adaptive capacities by aggregated socioeconomic parameters Appendix 23: Odisha: Maps of vulnerabilities




1 Background

India is one of the most vulnerable countries to the impacts of changing weather patterns and climatic extremes, as 60% of people depend for their livelihoods on rain-fed agriculture. Well-planned, resilient rural infrastructure can reduce such impacts, e.g. by ensuring good irrigation and helping restore the natural resource base. The Government of India invests nearly £4 billion annually in constructing rural infrastructure through the Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS), while ensuring a wage guarantee to nearly 40 million households. Hence, MGNREGS has huge potential to improve the climate resilience of the poorest and most vulnerable people in the country.

Infrastructure for Climate Resilient Growth (ICRG) is a 43-month technical assistance programme supported by the UK’s Department for International Development (DFID). It is seeking to facilitate more effective investment in rural infrastructure under MGNREGS to support rural economic growth and improve the climate resilience of vulnerable people in India, especially women and girls. The intended outcome is improved quality of the physical assets under MGNREGS demonstrated in 103 blocks of three states in India (Bihar, Chhattisgarh and Odisha), which are among the 2,500 blocks that are the Government of India’s special focus for implementation of MGNREGS works. DFID selected the states in consultation with the Ministry of Rural Development (MoRD) and the districts and the blocks were selected in consultation with the three state governments and the MoRD.

Poverty and marginalisation and social exclusion are key issues in India (Steinbach et al., 2016). Extreme poverty is intimately linked to the socioeconomic status of populations. It is caused by deep deprivation from a range of assets, including income, shelter and land, access to basic services (such as healthcare and education) and, consequently, skills and employment opportunities (Mittal et al., 2016). Populations experiencing extreme poverty face overlapping forms of marginalisation that are mutually reinforcing (OECD, 2013). Identity-based exclusion causes segments of the population, such as women and girls, disabled people and indigenous tribal populations, to be disparaged or stereotyped due to prevalent social norms. This leads to such groups suffering from inadequate assets, poor services or a weak political voice, thereby impeding their ability to lift themselves out of poverty (Kabeer, 2010).

Almost one in three (29.5%) of India’s population lives below the global poverty line (Government of India Planning Commission, 2014) and are disproportionately affected by climate impacts (Steinbach et al., 2016). The extreme poor and excluded groups in states such as Bihar, Chhattisgarh and Odisha are vulnerable to climate change and extreme weather events (e.g. flooding, droughts, heatwaves and cyclones), as they have weak adaptive capacities due to their heavy dependence on natural resources, and limited financial and social resources with which to protect themselves, recover from asset and livelihood losses or move to safer areas (Granoff et al., 2015). Hence, climate change has potential to compound marginalisation and to consign people to a vicious cycle of poverty and exclusion (Mittal et al., 2016) and there is a vital need for support from social protection and safety-net programmes like MGNREGS. Among extreme poor vulnerable groups in India, some of the most marginalised people are women and girls whose adaptive capacities to cope with climate change and extreme weather events are weaker than those of men. This is because they have their fewer productive assets, poorer access to education, skills and livelihoods, lower incomes, and greater family and domestic work responsibilities (Steinbach et al, 2016; Bhattacharya, 2017). People with disabilities are also more likely to experience poverty and have limited adaptive capacities in relation to climate change and extreme weather, as they face multiple barriers in accessing education, health care and employment, and often have mobility issues, which make them dependent on others (DFID, 2015). Indigenous people or primitive tribal groups are especially vulnerable to climate change and have lower adaptive capacities given their heavy reliance on natural resources. They tend to live close to nature and have intimate knowledge of local weather and plant and animal life. However, their traditional skills and knowledge on crop patterns and agriculture are now threatened by climate change (United Nations, 2008).




1.1 Vision and purposes of vulnerability assessment

The assessment sought to identify what issues are highly vulnerable to climate change and extreme weather events, where and for whom across the 103 ICRG blocks that can be addressed by MGNREGS options. This information should be an important consideration for relevant decision-makers at Gram Panchayat, block, district and state levels to ensure that MGNREGS is targeted in ways that promote climate resilience of both natural resources and the communities that depend on them.

In order to ensure that the vulnerability assessment is able to inform the MGNREGS planning cycle during ICRG’s first year, the assessment was largely a desk exercise building upon methods used by other studies of climate change vulnerabilities in India (e.g. Esteves et al., 2013a/b) and on the ICRG team’s previous application of definitions in the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5; IPCC, 2014). This meant that the scope and resolution of the vulnerability assessment in terms of the biophysical and socioeconomic issues that it addressed were largely determined by the extent of available data. Ground-truthing of the final output with stakeholders at block, district and state level will be vital to ensure the efficacy of the assessment and common understanding and commitment to its use in informing decisions.

Other climate change vulnerability assessments in India have, in general, sought to identify aggregate vulnerability across a wide range of issues. While this assessment built directly upon their methods it deliberately set out to identify vulnerabilities in ways that would allow the underlying individual climate sensitivities and limitations to adaptive capacities to be traced. The intention was that this would then mean that they could be specifically addressed by subsequent prioritisation of MGREGS options.

As an immediate and important next step after this deliverable is finalised, a practical and concise version of this report will be produced for stakeholders at state, district, block or gram panchayat level. It is intended that it would comprise:

A brief non-technical bullet point summary of the method and data used

The state directories of ICRG blocks and districts

A straightforward explanation of how they can make short term (April – June 2017) use of the maps and directories to inform prioritisation of MGNREGS options that have potential to reduce climate sensitivities or increase adaptive capacities and thereby resilience.

2 Methodology

2.1 Definitions of terms

Definitions of terms used were consistent with IPCC AR5, as detailed in Appendix 1. Most notably, IPCC AR5 defines vulnerability as ‘The propensity or predisposition to be adversely affected’. Hence vulnerability assessment needs to consider sensitivity or susceptibility to harm and lack of capacity to cope and adapt (Figure 1). Notably, this meant that exposure to climate change or extreme weather events was not a consideration for this vulnerability assessment. Exposure will instead be taken into account when the ICRG team subsequently seeks to build upon this report by prioritising each MGNREGS option in relation to the vulnerabilities by considering the magnitude of the potential impact if the option is not implemented (Figure 1: impact assessment) and other criteria (see Section 4).




Figure 1. Illustration of inter-relationships between IPCC AR5 definitions of terms

2.2 General approach

The vulnerability assessment was produced according to the following stepwise process:

1. Climate sensitivities were identified by using biophysical parameters as proxies and, similarly adaptive capacities were addressed by using socioeconomic parameters (Table 1, see Section 2.3 for an explanation of how and why these parameters were selected).

Table 1. Final selection of biophysical and socioeconomic parameters

Biophysical Socioeconomic

Groundwater availability

Net irrigated area

Irrigation intensity

Area under foodgrains

Cropping intensity

Crop yield – foodgrains

Soil erosion

Soil fertility

Number of adult cattle

Forest cover

% Households with monthly income < Rs 5000

% Landless households deriving major part of their income from manual casual labour

% Houseless rural

% Women-headed households

% Disabled

% Primitive tribal group households

2. Separate maps were produced for each of the biophysical parameters and socioeconomic parameters by ICRG block and/or district dependent on data availability (Section 2.4). The values of each parameter for each block or district was ranked relative to values for the parameter across all ICRG blocks or districts within each state by subdividing the range of values into three classes (High, H; Medium, M; and Low, L), each with a equal sized range of values. A GIS was then used to map each parameter by colour-coding the blocks and/or districts according to their rank. Low actual values for any of the parameters led to a High ranking. For example, the following were ranked as High:

Climate sensitivity: a low actual value for groundwater availability, area under foodgrains or forest cover (all of which can be directly or indirectly increased by MGNREGS options, see Section 2.3, Table 2). There was only one exception: a high




actual value for soil erosion was ranked as Low (soil erosion can be directly or indirectly reduced by MGNREGS options, see Table 2)

Adaptive capacity: households deriving a major part of their income from manual casual labour, women-headed households or primitive tribal group households (all of which can be supported directly or indirectly by MGNREGS options).

3. Relevant biophysical parameters were aggregated in different groupings in relation to four broad climate-sensitive issues (Water, Land, Agriculture and Forests, see Table 2) and, similarly, the socioeconomic parameters were aggregated in different groupings with regard to two broad socioeconomic issues that limit adaptive capacity (Poverty and Marginalisation, see Section 2.3, Table 3). Aggregate climate sensitivity and adaptive capacity were also each calculated across all of the biophysical parameters and socioeconomic parameters respectively at block and/or district level. Aggregation was achieved by converting the H, M, and L ranks to scores (3, 2, and 1 respectively) and adding together the scores for all parameters relating to each issue for each block or district before once more subdividing the range of values at block or district level in each state into H, M and L classes, each with an equal-sized range of values. A GIS was then used again to produce colour-coded maps of the blocks and/or districts according to their rank.

4. For each state, the resultant aggregated maps for ICRG blocks and/or districts of the four climate-sensitive issues were each overlaid separately with the resultant aggregated maps of each of the two issues relating to adaptive capacity, interacting the H, M, L scores using a matrix (Figure 2) to identify a combined H, M, L score for the vulnerability of each block or district in relation to each of the possible combinations of climate-sensitive issues and issues relation to adaptive capacity, as well as in relation to aggregate vulnerability. Colour-coded maps by block and/or district of these various vulnerabilities, as well as aggregate vulnerability, were then produced for each state using a GIS.

Figure 2. Vulnerability ratings

Ad

ap

tive c

ap

ac

ity

H

M

L

L M H

Sensitivity

Potentially vulnerable

Vulnerable

Highly vulnerable




5. State directories were produced to supplement presentation of the maps, which list for each state by ICRG block and/or district:

Aggregate vulnerability (i.e. H, M or L determined from all of the biophysical and socioeconomic parameters in combination)

Vulnerabilities where ranked as High in relation to each of the possible combinations of the four climate-sensitive issues and two issues related to adaptive capacity

Rankings (H, M or L) of the individual biophysical and socioeconomic parameters associated with vulnerabilities ranked as High, in order to provide a simple overview of what climate sensitivities need to be reduced and adaptive capacities increased, where and in relation to whom, if vulnerabilities are to be reduced and climate resilience thereby increased.

2.3 Selection of parameters

Biophysical parameters were selected that are proxies for climate sensitivities and socioeconomic parameters were selected that are proxies for adaptive capacities. Both biophysical and socioeconomic parameters were identified that reflect those used by other studies of climate change vulnerabilities in India (e.g. Rama Rao et al. 2016) and particularly by such studies in relation to MGNREGS (e.g. Bhattacharyya 2017, Chakraborty & Das 2014, Esteves et al. 2013a and b, Haque 2011, Kareemulla et al. 2009, 2010, Krishnan & Balakrishnan 2012, Kumar & Prasanna 2010, Ravindranath & Murthy 2013, Sinha 2011, Steinbach et al 2016, Tiwari et al. 2011, Verma 2011). Importantly, biophysical and socioeconomic parameters were selected that reflect the potential contribution of MGNREGS works to reducing climate sensitivities (Table 2) or increasing adaptive capacities (Table 3), i.e. their ability to address climate vulnerabilities and thereby increase resilience. However, both biophysical and socioeconomic parameters only made it through to the final selection (Table 1) if they were supported by open access datasets that provide values at district level and preferably at block level (see Appendix 2).

Table 2. Biophysical parameters in relation to MGNREGS options and climate-sensitive issues

Climate-sensitive issues

Output-based MGNREGS options

Potential contribution to reducing climate sensitivity

Biophysical parameters

Water Water conservation, water harvesting, recharging of ground water resources and water management

Watershed management

Micro and minor irrigation

Restoration of traditional water bodies and flood control works

Erosion control

Ground water recharge

Soil moisture retention

Improved availability of water for irrigation

Improved availability of drinking water

Improvement in soil fertility

Improved vegetative growth and crop production


Net irrigated area


Soil erosion

Soil fertility

Land Land development (both common and private lands)

Land levelling, field bunding, contour bunding, terracing, graded bunding, field

Improvement in soil fertility and quality

Productive use of degraded lands, including reclamation


Soil erosion

Soil fertility




Climate-sensitive issues

Output-based MGNREGS options

Potential contribution to reducing climate sensitivity


bunding, pasture development

Flood control measures

Silt-spreading in farm fields (from desilting water bodies)

Drought proofing

Soil improvement

Erosion control

Improvement in soil moisture

Improved production from trees, crops and other vegetation

Increased crop yields

Agriculture Water conservation, water harvesting, recharging of ground water resources and water management

Watershed management

Micro and minor irrigation

Restoration of traditional water bodies and flood control works

Horticulture


Productive use of degraded lands including reclamation

Erosion control

Flood control for crop protection, etc.


Soil moisture retention

Improved availability of water for irrigation


Increased crop yields

Increased number of livestock


Cropping intensity


Soil erosion

Soil fertility


Forests Afforestation for timber, fruit, fodder, and fibre

Boundary and block plantation

Agro-forestry, silvi-pasture

Pasture development

Wasteland development

Improved soil quality and moisture retention

Erosion control

Non-timber forest products, including fuelwood and fodder

Improved micro-climate


Improved availability of water in surface water bodies

Forest cover


Soil erosion

Table 3. Socioeconomic parameters in relation to MGNREGS and issues limiting adaptive capacity




Issues limiting adaptive capacity

Potential contribution of MGNREGS options to increasing adaptive capacity

Socioeconomic parameters

Reasons for selection

Poverty Diversification of livelihoods for the poor and landless

Income generation and savings potential for the houseless who could invest in a safe shelter

Improved ability of the poorest families to access healthcare, education, skills and employment opportunities for themselves and their children

Individuals, households and communities who are able to escape the vicious cycle of poverty

% of households with monthly income < Rs 5000 The lives of the poor are often inextricably linked to the natural environment, which they may depend on for food, fuel, medicine, shelter and livelihoods. Climate change and extreme weather events may have enormous impacts on their lives in terms of asset or livelihood loss. Their abilities to prepare, recover or move to safer places is limited by a lack of financial and social resources. Some people in extreme poverty reside in remote zones that are often neglected due to a lack of connectivity and inaccessibility, and their adaptive capacities can, therefore, be particularly low. (Krishnan, S. and Balakrishnan, A. 2012.; OECD, 2013; Mittal et al., 2016) % of houseless rural Homeless rural populations have extremely limited adaptive capacities to cope with climate change and extreme weather events, as they neither have assets nor savings, nor a shelter for protection. (OECD, 2013; Mittal et al., 2016) % of landless households deriving major part of their income from manual casual labour Landless households who work mainly as manual casual labourers do not have secure livelihoods. Their adaptive capacities may be subject to high levels of seasonal fluctuation due to variations in demand for labour. A lack of assets, such as land, means that they are dependent on landowners who may exploit them or discriminate against them, leading to low wages, marginalisation, high debts and low adaptive capacities to address climate change and extreme weather events. (Kareemulla et al., 2010; Granoff et al., 2015).

Marginalisation Improved gender parity and resilient outcomes for women and girls

Improved livelihoods, participation and empowerment of marginalised disabled and indigenous tribal groups

Improved productivity of marginalised individuals, households and communities and

% of women-headed households Women-headed households have low adaptive capacity to cope with climate change and extreme weather events. There are persistent gender disparities in the labour market and they may have limited access to formal credit markets and land. These households often take care of a higher proportion of dependent children and the elderly, as compared with other households. Women who are heads of households with no other adult help have a “double day burden”, as they have to fulfil both domestic duties and make money outside the home. Hence, they face greater time and mobility constraints and may have to work fewer hours or choose lower-paying jobs. (Mittal et al., 2016; Bhattacharyya, 2017) % of disabled People with disabilities have low adaptive capacity to climate change and extreme weather events, as they often depend on others, have limited means to support




Issues limiting adaptive capacity

Potential contribution of MGNREGS options to increasing adaptive capacity


Reasons for selection

contribution to local economies

their livelihoods and a mobility challenge. They are not easily able to relocate or find emergency shelter in a disaster situation; face disproportionate human security and protection issues; and are more prone to discrimination due to resource scarcity. In particular, women, children and elderly with disabilities may be abandoned and face difficulties in accessing health care, food and shelter. Evidence suggests that people with disabilities have a mortality rate two to four times higher than the non-disabled population in disaster situations. (DFID, 2015; Mittal et al., 2016) % of Primitive Tribal Group households Primitive Tribal Groups and indigenous communities may be marginalised or located very remotely with less mobility or access to basic services, face linguistic and cultural barriers in terms of engaging with wider communities or service providers, have limited participation in local-level decision-making processes and may be discriminated against in times of disaster. These factors mean that they may have low adaptive capacities to cope with climate change and extreme weather events, which may be further limited by their high dependence on natural resources. (Kumar & Prasanna, 2010; Mittal et al., 2016)

The socioeconomic parameters address the percentages of households, as opposed to absolute numbers, in order to ensure that:

Actual population figures do not lead to less populated blocks being deprioritised

ICRG’s goal of penetrating the 103 blocks across the three states is met, as agreed with the respective state governments, irrespective of block’s actual population size or its remoteness.

2.4 State-specific approaches The vulnerability assessment’s stepwise process (Section 2.2) was undertaken at district and block level for Chhattisgarh and Odisha but for Bihar was only possible at district level due to a lack of block-level data for the biophysical parameters. In Step 2, the separate maps produced for each of the biophysical parameters and socioeconomic parameters only rank ICRG blocks and districts where data was available (the maps identify blocks where data is unavailable for individual parameters). In Step 3 (and also overlain in Step 4), the aggregated maps of the four climate-sensitive issues and two issues relating to adaptive capacity for ICRG blocks in Chhattisgarh and Odisha drew upon values for the constituent biophysical or socioeconomic parameters using the following protocols in descending order:

1. Block values for parameters were used, where available

2. District values for parameters were assigned to blocks, where data was unavailable

3. Blocks were assigned a Low rank and scored 1, where data was neither available at block nor district level.

2.5 Caveats and assumptions Some important caveats and assumptions that should be borne in mind when interpreting the outputs of the vulnerability assessment include:

As noted in Section 1.1, in order to ensure that the vulnerability assessment is able to inform the MGNREGS planning cycle during ICRG’s first year, this comparative vulnerability assessment of blocks and districts is based on secondary data. It is neither supported by primary observations nor, to date by ground-truthing with stakeholders, so the outcomes of the




study are limited by the level of accuracy, comparability and disaggregation of the data. The vulnerability assessment has focused on providing a level of information that can inform the prioritisation of the MGNREGS work options, as opposed to determining the underlying reasons for climate sensitivities or limited adaptive capacities.

Differences in the ranking of individual parameters between district and block level, highlight that data on climate sensitivities and adaptive capacities (and thereby vulnerabilities) vary with scale. Ultimately, vulnerabilities at any specific location need to be determined bottom-up supported by knowledge of the outputs of this vulnerability assessment at block and district levels.

Although the socioeconomic parameters focus on the percentages of households that is not to say that the absolute numbers of households in relation to each of the parameters are unimportant. They could be potentially useful and relevant data to assess and compare in the next phase of the study when MGNREGS options will be prioritised in relation to highly vulnerable issues

Socioeconomic adaptive capacities of populations have a close interlinkage with the degree to which individuals and communities are empowered by political institutions and are able to influence and/or engage with political processes that affect their lives, as well as the prevalence of ‘active’ formal or informal community-based or community-led institutions that can drive ongoing change. Capturing such qualitative attributes of adaptive capacity was beyond the scope of this study.

3 Findings

3.1 Maps of individual biophysical and socioeconomic parameters

The maps by ICRG block and/or district of climate sensitivities and adaptive capacities represented by individual biophysical or socioeconomic parameters (Table 1) produced in Step 2 can be found at:

Appendix 4 and 5: Bihar

Appendix 10 and 11: Chhattisgarh

Appendix 16 and 17: Odisha

3.2 Maps of climate sensitivities by aggregated biophysical parameters

The maps by ICRG block and/or district of climate sensitivities in relation to the four broad climate-sensitive issues (water, land, agriculture and forests, see Table 2) plus maps of aggregate climate sensitivity, produced in Step 3, can be found at:

Appendix 9: Bihar

Appendix 15: Chhattisgarh

Appendix 21: Odisha.

3.3 Maps of adaptive capacities by aggregated socioeconomic parameters

The maps by ICRG block and/or district of climate sensitivities in relation to the two broad socioeconomic issues that limit adaptive capacity (poverty and marginalisation, see Table 3) plus maps of aggregate adaptive capacity, produced in Step 3, can be found at:

Appendix 10: Bihar






3.4 Maps of climate vulnerabilities The maps by ICRG block and/or district of climate vulnerabilities plus maps of aggregate vulnerability, produced in Step 4, can be found at:

Appendix 11: Bihar



3.5 State directories of vulnerabilities by district and block

Directories of vulnerabilities for each state can be found at Appendices 3 – 5. These directories are intended to provide a summary of the maps for decision-makers at Gram Panchayat, block, district or state level and help to focus their attention on what climate sensitivities need to be reduced and adaptive capacities increased, where and in relation to whom, if vulnerabilities are to be reduced and climate resilience thereby increased. Summaries for each state are provided in Tables 5 – 7. A recommendation and explanation of how the directories and maps can be used for MGNREGS planning in the short-term (April – June 2017) is provided at Section 5.1.1. Their use by the ICRG team to identify a menu of priority MGNREGS options for each ICRG district and block by end of June 2017 is described in Section 4, and a recommendation and explanation of how those menus could be used in MGNREGS planning by decision-makers at all levels from July 2017 onwards is provided at Section 5.1.2. Table 5. Bihar: Districts with High aggregate vulnerability

District High Vulnerability (Poverty) High Vulnerability (Marginalisation)

Katihar Land Agriculture Forest

Land Agriculture Forest

Begusarai Water Agriculture

Water Land Agriculture Forest

Table 6. Chhattisgarh: Blocks with High aggregate vulnerability

District Block High Vulnerability (Poverty)

High Vulnerability (Marginalisation)

Bilaspur Kota Water Land Agriculture Forest

Land Forest

Bilaspur Marwahi Water Land Forest

Water Land Forest

Jashpur Kansabel

Water Land Forest

Jashpur Kunkuri


Jashpur Manora







Jashpur Pharsabaha

Water Land Forest

Korba Pali Land Agriculture Forest


Koriya Bharatpur Land Agriculture

Land Agriculture

Koriya Sonhat Land Agriculture Forest


Rajnanadgaon Mohla Water Land

Water Land

Surajpur Pratappur Land

Surajpur Premnagar Land Agriculture

Table 7. Odisha: Blocks with High aggregate vulnerability



Bolangir Titlagarh Water Forest

Water Forest

Kalahandi Bhawanipatna Water Land Agriculture Forest

Water

Kalahandi Lanjigarh Water Water Land Agriculture Forest

Kendujhar Jhumpura Water Water Land Agriculture Forest

Mayurbhanj Thakurmunda Water Forest

Nuapada Komana Land Agriculture

Nuapada Sinapali Water Land Agriculture

Water Land Agriculture

4 Next steps: use of vulnerability assessment to prioritise MGNREGS options

The ICRG team will be able to build upon the vulnerability assessment by developing a menu of priority MGNREGS options for each ICRG district and block by end of June 2017. MGNREGS options will be assessed in terms of their ability to address vulnerabilities by reducing climate sensitivity or increasing adaptive capacity and thereby promote resilience. It is proposed that MGNREGS options will be prioritised by ranking them on a relative basis using criteria that build upon those outlined in the technical




guidelines for the national adaptation plan process published by the United Nations Framework Convention on Climate Change (UNFCCC) Secretariat (Least Developed Countries Expert Group, 2012), which may include:

Impact – The magnitude of the potential impact (i.e. if the MGNREGS option is not implemented), assessed by considering the nature of each vulnerability in relation to its potential exposure to climate change (Figure 4), i.e. as determined from consideration of future-climate scenarios (e.g. with regard to droughts, heatwaves, floods and cyclones)

Figure 4. Impact assessment: inter-relationships between IPCC AR5 definitions of terms

Efficacy – The extent to which the MGNREGS option address likely climate change scenarios and their potential impact. ‘No regrets’ options have a positive impact even if climate change is not as anticipated.

Urgency for action – The most urgent actions are those where delay could lead to greater impact (due to the speed of impact and/or time for the MGNREGS option to become effective, e.g. tree planting to provide shade or shelter that will not be provided until the trees mature) and/or increased costs.

Longevity and timescale – The extent to which the MGNREGS option offers the potential for a short-term (e.g. <5 years), medium-term (5-10 years) or long-term increase in climate resilience.

Social acceptance – The extent to which Gram Panchayats and people will support and/or implement the MGNREGS option.

Equity – The extent to which the MGNREGS option offers the potential for greater parity in terms of wages, livelihood options, and employment opportunities to those who live in poverty (e.g. households with monthly income < Rs 5000, landless households deriving major part of their income from manual casual labour and houseless rural) and/or are marginalised (e.g. women-headed households, disabled and primitive tribal group households)

Reach – The degree to which the MGNREGS option offers greater penetration and scale in terms of total numbers of beneficiaries reached, and specifically in relation to women and girls.

Technology – The extent to which the technology to implement the MGNREGS option is readily available.

Knowledge and skills – The extent to which the skills and knowledge to implement the MGNREGS option are readily available.

Costs – The financial costs associated with design and implementation of the MGNREGS option, including operational costs (e.g. human resources) and investment costs. High costs will be scored as ‘Low’ whereas low costs will be scored as ‘High’.

Co-benefits for adaptation and development – The extent to which the MGNREGS option delivers potential co-benefits for reducing climate sensitivity or increasing adaptive capacity in relation to other vulnerabilities and for the achievement of development goals.




Co-benefits for mitigation – The extent to which the adaptation action will reduce greenhouse gas (GHG) emissions (N.B. this criterion could have a negative score, i.e. some MGNREGS options could actually increase GHG emissions).

As with the outputs of the vulnerability assessment, it will be vital to undertake ground-truthing of the prioritisation of MGNREGS options with stakeholders at block, district and state level. Ensuring the efficacy of the resultant menus of options and common understanding and commitment will be essential if they are to be of use in MGNREGS planning.

5 Recommendations

5.1 Use of vulnerability assessment in MGNREGS planning

5.1.1 Short term (April – June 2017)

In order to promote climate resilience, decision-makers are encouraged to prioritise MGNREGS options that reduce climate sensitivities or increase adaptive capacities associated with High vulnerabilities by reference to the maps and directories, as follows:

1. At a state or district level: a. Focus on those districts and blocks with High aggregate vulnerability (i.e. those listed

in Tables 5 – 7) as being of potentially highest priority and follow through points 1b-d. b. Focus on the districts’ or blocks’ individual High vulnerabilities in relation to individual

issues leading to High climate sensitivity (i.e. Water, Land, Agriculture and/or Water) and.Low adaptive capacity (i.e. Poverty and/or Marginalisation).

c. Consider prioritising output-based MGNREGS options from Table 2 that can potentially contribute to reducing climate sensitivity specifically in relation to those biophysical parameters that are associated with the High climate sensitivity (i.e. those listed in Appendices 3 – 5).

d. Consider how the MGNREGS options identified in point 1b can be implemented in ways that potentially contribute to increasing adaptive capacity (as described in Table 3) specifically in relation to those people associated with the Low adaptive capacity (i.e. those listed in Appendices 3 – 5).

2. At a block level: blocks with High aggregate vulnerability (i.e. listed in Tables 5 – 7) or blocks listed that have individual issues associated with High vulnerability (see Appendices 3 – 5)

a. Focus on the block’s individual High vulnerabilities as being of potentially highest priority and follow through points 1b-d.

3. All blocks a. Identify if there are issues that have High climate sensitivity not associated with a

High vulnerability (from Appendices 3 -5) and follow point 1c b. Identify if there are issues that lead to Low adaptive capacity not associated with a High

vulnerability (see Appendices 3 -5) and follow 1d.

Ground-truthing of the final output of the vulnerability assessment (by the ICRG team’s international expert on climate resilience and ICRG state experts in late April/May) with stakeholders at block, district and state level is strongly recommended in order to ensure the efficacy of the assessment and common understanding and commitment to its use in informing decisions. It will be important that decision-makers at all levels use the outputs of the vulnerability assessment as a general guide rather than interpreting them as being specifically correct. Differences in the ranking of individual parameters between district and block level, highlight that data on climate sensitivities and adaptive capacities (and thereby vulnerabilities) vary with scale. Ultimately, vulnerabilities at any specific location need to be determined bottom-up by stakeholders supported by knowledge of the outputs of this vulnerability assessment at block and district levels.




5.1.2 Medium term (July 2017 onwards)

The menus of priority MGNREGS options for each ICRG district and block (to be produced by the ICRG team by end-June) could further inform MGNREGS planning decisions at all levels (Gram Panchayat, block, district and state). It would also provide decision-makers with a simple overview of the relative priority of MGNREGS options at block and district level not only in relation to High vulnerabilities and associated climate sensitivities and limitations to adaptive capacities but also with regard to: potential climate impact if suitable MGNREGS options are not implemented; their efficacy; timing/urgency for action; likely social acceptance; availability of suitable technology; knowledge and skills; costs (including human resources); and co-benefits for adaptation, development and mitigation.

5.1.3 Longer term In the longer term over the course of the ICRG programme and beyond, the vulnerability assessment should be reviewed with block, district and state level stakeholders to identify how its use in practice has worked well or less well. This should then inform further refinements of the vulnerability assessment itself and the prioritisation MGNREGS options based upon it.

5.2 Use of vulnerability assessment across ICRG outputs

The systematic process of identifying highly vulnerable issues and ranking MGNREGS works in their regard could be used to contribute to:

Training and capacity building at all levels (Gram Panchayat, block, district and state)

Identification of best practices

Highlighting research and evidence needs

Development of the monitoring and evaluation framework.

The vulnerability assessment maps, state directories and menus of priority MGNREGS options for each ICRG district and block could also help inform measurement of social benefits from the ICRG programme.

5.3 Use of vulnerability assessment by others

In addition to use of the outputs of the vulnerability assessment by those involved by decision-makers involved in MGNREGS planning and by the ICRG team, there may be potential for them to be used more widely. Other government schemes may have traction on the same biophysical climate sensitivities and socioeconomic adaptive capacities that have been addressed in this study. Where this is the case, the state directories and maps in this report could be consulted by those involved in such complementary schemes in order to promote implementation of convergence with MGNREGS.

6 References

Bhattacharyya, S. 2017. Impact of MGNREGS on sustainable livelihood of women. Journal of Rural and Community Affairs, II (I), 34-57. Chakraborty B. and Das, S. 2014. MGNREGS and water management: sustainability issues of built forms in rural India. Journal of Construction in Developing Countries, 19(2), 33–50. Climate Change Cell, Forest and Environment Department, Government of Odisha. 2016. Odisha Climate Change Action Plan (2015-2020) (DRAFT). Accessed on 17 March 2017 at http://climatechangecellodisha.org/pdf/Odisha_SAPCC_2016-2020.pdf DFID. 2015. Disability framework – One year on leaving no one behind. DFID, London. Accessed on 17 March 2017 at https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/554802/DFID-Disability-Framework-2015.pdf

http://climatechangecellodisha.org/pdf/Odisha_SAPCC_2016-2020.pdf

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/554802/DFID-Disability-Framework-2015.pdf

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/554802/DFID-Disability-Framework-2015.pdf




Esteves, T.. Rao, K.V., Sinha, B., Roy, S.S., Rao, B., Jha, S., Singh, A.B., Vishal, P., Nitasha, S., Rao, A., Murthy, I.K., Sharma, R., Porsche, I., Basu, K. and Ravindranath N.H. 2013a. Agricultural and livelihood vulnerability reduction through the MGNREGS. Economic & Political Weekly XLVIII, 94-103. Esteves, T., Rao, K.V., Sinha, B., Roy, S.S., Rai, B.B., Rao, I.B., Sharma, N., Rao, S., Patil, V., Murthy, I.K., Srinivasan, J., Chaturvedi, R.K., Sharma, J., Jha, S.K., Mishra, S., Singh, A.B., Rakhroy, H.S., Rai, S., Sharma, R., Schwan, S., Basu, K., Guerten, N., Porsché, I., Ranjan, N., Tripathy, K.K. and Ravindranath, N.H. 2013b. Environmental benefits and vulnerability reduction through Mahatma Gandhi NREGS: synthesis report. Ministry of Rural Development, Government of India and Deutsche GIZ. Government of Bihar. 2015. Bihar State Action Plan on Climate Change. Accessed on 17 March 2017 at http://www.moef.gov.in/sites/default/files/Bihar-State%20Action%20Plan%20on%20Climate%20Change%20(2).pdf Government of Chhattisgarh. 2013. State action plan on climate change. Final draft – May 2013. Accessed on 17 March 2017 at http://www.moef.nic.in/sites/default/files/sapcc/Chhattisgarh.pdf Government of India Planning Commission. 2014. Report of the expert group to review the methodology for measurement of poverty. Accessed on 17 March 2017 at http://planningcommission.nic.in/reports/genrep/pov_rep0707.pdf Granoff, I., Eis, J., McFarland, W. and Hoy, C. 2015. Zero poverty, zero emissions. Eradicating extreme poverty in the climate crisis. Overseas Development Institute, London. Accessed on 17 March 2017 at https://www.odi.org/sites/odi.org.uk/files/odi-assets/publications-opinion-files/9847.pdf Haque, T. 2011. Socio-economic impact of implementation of Mahatma Gandhi National Rural Employment Guarantee Act in India. Social Change, 41(3) 445-71. IPCC. 2014. Annex II: Glossary [Mach, K.J., S. Planton and C. von Stechow (eds.)]. In: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, pp. 117-130. Kabeer, N. 2010. Can the MDGs provide a pathway to social justice? The challenge of intersecting inequalities. Institute of Development Studies, New York. Kareemulla, K., Srinivas Reddy, K., Rama Rao, C.A., Kumar, S. and Venkateswarlu, B. 2009. Soil and water conservation works through National Rural Employment Guarantee Scheme (NREGS) in Andhra Pradesh – an analysis of livelihood impact. Agricultural Economics Research Review, 22 (Conference Number), 443-450. Kareemulla, K., Kumar, S., Srinivas Reddy, K., Rama Rao, C.A. and Venkateswarlu, B. 2010. Impact of NREGS on rural livelihoods and agricultural capital formation. Indian Journal of Agricultural Economics, 65:3, 524-539. Krishnan, S. and Balakrishnan, A. 2012. Impact of watershed works of MGNREGS on poverty alleviation – a micro-level study. Indian Streams Research Journal, 2(7) 2230-7850. Kumar, R. and Prasanna, R. 2010. Role of NREGA in providing additional employment for tribals and curtailing migration, National Rural Employment Guarantee Act (NREGA): design, process and impact, Ministry of Rural Development, Delhi. Least Developed Countries Expert Group. 2012. National Adaptation Plans. Technical guidelines for the national adaptation plan process. UNFCCC Secretariat. Accessed on 17 March 2017 at https://unfccc.int/files/adaptation/cancun_adaptation_framework/application/pdf/naptechguidelines_eng_high__res.pdf Mittal, N., Perera, N. and Korkeala, O. 2016. Learning materials: leaving no-one behind in the climate and environment context. Evidence on Demand, UK ii, 69 pp. Accessed on 17 March 2017 at

http://www.moef.gov.in/sites/default/files/Bihar-State%20Action%20Plan%20on%20Climate%20Change%20(2).pdf

http://www.moef.gov.in/sites/default/files/Bihar-State%20Action%20Plan%20on%20Climate%20Change%20(2).pdf

http://www.moef.nic.in/sites/default/files/sapcc/Chhattisgarh.pdf

http://planningcommission.nic.in/reports/genrep/pov_rep0707.pdf

https://www.odi.org/sites/odi.org.uk/files/odi-assets/publications-opinion-files/9847.pdf

https://unfccc.int/files/adaptation/cancun_adaptation_framework/application/pdf/naptechguidelines_eng_high__res.pdf

https://unfccc.int/files/adaptation/cancun_adaptation_framework/application/pdf/naptechguidelines_eng_high__res.pdf




https://www.gov.uk/dfid-research-outputs/learning-materials-leaving-no-one-behind-in-the-climate-and-environment-context OECD. 2013. Keeping the multiple dimensions of poverty at the heart of development. Accessed on 17 March 2017 at https://www.oecd.org/dac/POST-2015%20multidimensional%20poverty.pdf Rama Rao, C.A., Raju, B.M.K., Subba Rao, A.V.M., Rao, K.V., Rao, V.U.M., Kausalya Ramachandran, Venkateswarlu, B., Sikka, A.K., Srinivasa Rao, M., Maheswari, M. and Srinivasa Rao, Ch. 2016. A district level assessment of vulnerability of Indian agriculture to climate change. Current Science, 110:10, 1939-1946. Ravindranath, N.H. and Murthy, I.K. 2013 Greening of MGNREGS. New Delhi: United Nations Development Programme. Sinha, B., Basu, A. and Katiyar, A.S. 2011. Adapting to climate change: opportunities under MGNREGS, Report for the Ministry of Rural Development/UNDP. Indian Institute of Forest Management. Steinbach, D., Flower, B., Kaur, N., Godfrey Wood, R., D’Errico, S., Ahuja, R. and Sowmithri, V.R. 2016. Aligning social protection and climate resilience: a case study of MGNREGS and MGNREGSEB in Andhra Pradesh. IIED, London. Accessed on 17 March 2017 at http://pubs.iied.org/10156IIED Tiwari, R., Somashekhar, H.I., Parama, V.R., Murthy, I.K., Kumar, M.S.M, Kumar, B.K.M., Parate, H., Varma, M., Malaviya, S., Rao, A.S., Sengupta, A., Kattumuri, R. and Ravindranath, N.H. 2011. MGNREGS for environmental service enhancement and vulnerability reduction: rapid appraisal in Chitradurga District, Karnataka. Economic & Political Weekly, 46(20) 39-47. United Nations. 2008. Climate change and indigenous people. Accessed on 17 March 2017 at http://www.un.org/en/events/indigenousday/pdf/Backgrounder_ClimateChange_FINAL.pdf Verma, S. and Shah, T. 2012. Labor Market Dynamics in Post- MGNREGS Rural India. Water Policy Research Highlight, 8. Accessed on 17 March 2017 at http://www.iwmi.cgiar.org/iwmi-tata/PDFs/2012_Highlight-08.pdf

https://www.gov.uk/dfid-research-outputs/learning-materials-leaving-no-one-behind-in-the-climate-and-environment-context

https://www.gov.uk/dfid-research-outputs/learning-materials-leaving-no-one-behind-in-the-climate-and-environment-context

https://www.oecd.org/dac/POST-2015%20multidimensional%20poverty.pdf

http://pubs.iied.org/10156IIED

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http://www.iwmi.cgiar.org/iwmi-tata/PDFs/2012_Highlight-08.pdf

http://www.iwmi.cgiar.org/iwmi-tata/PDFs/2012_Highlight-08.pdf




7 Appendices

Appendix 1: IPCC AR5 definitions of terms

Appendix 2: Open access datasets used for each biophysical and socioeconomic parameter

Appendix 3: Bihar: State directory of high vulnerabilities by district

Appendix 4: Chhattisgarh: State directory of high vulnerabilities by district

Appendix 5: Odisha: State directory of high vulnerabilities by district

Appendix 6: Bihar: Index of ICRG districts

Appendix 7: Bihar: Maps of climate sensitivities represented by individual biophysical parameters

Appendix 8: Bihar: Maps of adaptive capacities represented by individual socioeconomic parameters

Appendix 9: Bihar: Maps of climate sensitivities by aggregated biophysical parameters

Appendix 10: Bihar: Maps of adaptive capacities by aggregated socioeconomic parameters

Appendix 11: Bihar: Maps of vulnerabilities

Appendix 12: Chhattisgarh: Index of ICRG districts and blocks

Appendix 13: Chhattisgarh: Maps of climate sensitivities represented by individual biophysical parameters

Appendix 14: Chhattisgarh: Maps of adaptive capacities represented by individual socioeconomic parameters

Appendix 15: Chhattisgarh: Maps of climate sensitivities by aggregated biophysical parameters

Appendix 16: Chhattisgarh: Maps of adaptive capacities by aggregated socioeconomic parameters

Appendix 17: Chhattisgarh: Maps of vulnerabilities

Appendix 18: Odisha: Index of ICRG districts and blocks

Appendix 19: Odisha: Maps of climate sensitivities represented by individual biophysical parameters

Appendix 20: Odisha: Maps of adaptive capacities represented by individual socioeconomic parameters

Appendix 21: Odisha: Maps of climate sensitivities by aggregated biophysical parameters

Appendix 22: Odisha: Maps of adaptive capacities by aggregated socioeconomic parameters

Appendix 23: Odisha: Maps of vulnerabilities

Infrastructure for Climate Resilient Growth | ii



Appendix 1 – IPCC AR5 definitions of terms

Term Definition

Adaptation ‘The process of adjustment to actual or expected climate and its effects. In human systems, adaptation seeks to moderate or avoid harm or exploit beneficial opportunities. In some natural systems, human intervention may facilitate adjustment to expected climate and its effects’.

Adaptive capacity

‘The ability of systems, institutions, humans, and other organisms to adjust to potential damage, to take advantage of opportunities, or to respond to consequences’.

Exposure ‘The presence of people, livelihoods, species or ecosystems, environmental functions, services, and resources, infrastructure, or economic, social, or cultural assets in places and settings that could be adversely affected’.

Impact – consequences or outcomes

‘Effects on natural and human systems. The term impacts is used primarily to refer to the effects on natural and human systems of extreme weather and climate events and of climate change. Impacts generally refer to effects on lives, livelihoods, health, ecosystems, economies, societies, cultures, services and infrastructure due to the interaction of climate changes or hazardous climate events occurring within a specific time period and the vulnerability of an exposed society or system. Impacts are also referred to as consequences and outcomes. The impacts of climate change on geophysical systems, including floods, droughts and sea level rise, are a subset of impacts called physical impacts’.

Resilience ‘The capacity of social, economic and environmental systems to cope with a hazardous event or trend or disturbance, responding or reorganising in ways that maintain their essential function, identity and structure, while also maintaining the capacity for adaptation, learning and transformation’. This definition means that ‘resilience’ may be regarded as a universally positive attribute unlike ‘resistance’ (the degree to which a system opposes or prevents an effect of a stimulus).

Sensitivity ‘The degree to which a system or species is affected, either adversely or beneficially, by climate variability or change. The effect may be direct (e.g., a change in crop yield in response to a change in the mean, range, or variability of temperature) or indirect (e.g., damages caused by an increase in the frequency of coastal flooding due to sea-level rise)’.

Vulnerability ‘The propensity or predisposition to be adversely affected’. Vulnerability encompasses a variety of concepts and elements including sensitivity or susceptibility to harm and lack of capacity to cope and adapt.

Infrastructure for Climate Resilient Growth | iii



Appendix 2 – Open access datasets used for each biophysical and socioeconomic parameter

Parameter Source: Bihar Source: Chhattisgarh Source Odisha



Net groundwater availability:

http://www.cgwb.gov.in/District_Profile/Bihar

Net groundwater availability:

http://www.cgwb.gov.in/District_Profile/Chhatisgarh

Groundwater gap:

http://www.dowrorissa.gov.in/DIP/DIPIndex.htm

Net irrigated area

http://www.nicra-icar.in/nicrarevised/index.php/state-wise-plan

http://www.pmksy.gov.in/mis/rptDIPDocAllDistrict.aspx?+9obX73JelKah0vmHWn5uRkjAErnPxpP2Y0pZFd2S+R6jGP38TBtSU3307MQsWrlTcVF+q3a3S9t552qW3QliM3PNYFVxuEjjbvQWMvaYGHrEOZs3apv+MILJqj14KaAsNVr9ZLj9xsLhM0e2qvAE3qDSFNR2varJ/Yk3kiMwni9rs5ZqjM6pCA9nT15N8uuTDeg2Lkl6+7ZBepxuIPSNRbJ0xBNqA9QWcJO5drP44Q02fwNGmzGAtungQdGhc8L



Calculated from net irrigated area (above) and culturable command area:


Calculated from net irrigated area (above) and culturable command area:


Calculated from net irrigated area (above) and total irrigated area:




http://www.pmksy.gov.in/mis/rptDIPDocAllDistrict.aspx?+9obX73JelKah0vmHWn5uRkjAErnPxpP2Y0pZFd2S+R6jGP38TBtSU3307MQsWrlTcVF+q3a3S9t552qW3QliM3PNYFVxuEjjbvQWMvaYGHrEOZs3apv+MILJqj14Ka












Infrastructure for Climate Resilient Growth | iv



Parameter Source: Bihar Source: Chhattisgarh Source Odisha AsNVr9ZLj9xsLhM0e2qvAE3qDSFNR2varJ/Yk3kiMwni9rs5ZqjM6pCA9nT15N8uuTDeg2Lkl6+7ZBepxuIPSNRbJ0xBNqA9QWcJO5drP44Q02fwNGmzGAtungQdGhc8L

Cropping intensity

Calculated from gross cropped area:

http://www.finance.bih.nic.in/Documents/Reports/Economic-Survey-2016-EN.pdf

And net sown area:


Calculated from gross cropped area:


And net sown area:


Calculated from gross cropped area and net sown area:




http://www.pmksy.gov.in/mis/rptDIPDocAllDistrict.aspx?JR/A+WW5KmyKYf8d/JIuh3maOc1GRUWw/zhvNTi7xo6vD9901X4Hk8wjNqmQ/i1pXbornm3q6W0uXq52z0UCY3JrCRbuUf+e7M+CRXPVHVICIZlcTszA0G8KFfYhYqeKxq91PeFcJxqyTaxmJDnWKNjnjeZIPwX1Mj5U0tPIKnfuKK+crD91Fbv0NQkPWFxh2zGGzDD9RhSFKAotTKUUXHHRS0BsIZMJ5tDXa/d+x9Ns


Infrastructure for Climate Resilient Growth | v



Parameter Source: Bihar Source: Chhattisgarh Source Odisha R7U0uuZT1MakRp5SJUJg

Soil erosion None None http://www.dowrorissa.gov.in/DIP/DIPIndex.htm

Soil fertility http://stcr.gov.in/farmer/HTML/Fertility_Maps_Macro/StateProfile/Bihar.html

None None



http://ahd.cg.gov.in/ahd.cgEnglish/template1.htm


Forest cover finance.bih.nic.in/Documents/Reports/Economic-Survey-2016-EN.pdf

http://www.pmksy.gov.in/mis/rptDIPDocAllDistrict.aspx?JR/A+WW5KmyKYf8d/JIuh3maOc1GRUWw/zhvNTi7xo6vD9901X4Hk8wjNqmQ/i1pXbornm3q6W0uXq52z0UCY3JrCRbuUf+e7M+CRXPVHVICIZlcTszA0G8KFfYhYqeKxq91PeFcJxqyTaxmJDnWKNjnjeZIPwX1Mj5U0tPIKnfuKK+crD91Fbv0NQkPWFxh2zGGzDD9RhSFKAotTKUUXHHRS0BsIZMJ5tDXa/d+x9NsR7U0uuZT1MakRp5SJUJg



% Households with monthly income < Rs 5000

(http://secc.gov.in/statewiseEmploymentAndIncomeReport?reportType=Employment%20and%20Income)



% Landless households deriving major part of their income from manual casual labour

http://secc.gov.in/stateSummaryReport#



% Houseless rural

http://secc.gov.in/statewiseTypeOfHouseholdsReport?reportType=Type of Households



% Women-headed households

http://secc.gov.in/statewiseGenderProfileReport?reportType=Gender Profile



% Disabled http://secc.gov.in/statewiseDisabilityProfileReport?reportType=Disability Profile

http://secc.gov.in/statewiseDisabilityProfileReport?reportType=Disability Profile

http://secc.gov.in/statewiseDisabilityProfileReport?reportType=Disability Profile

Infrastructure for Climate Resilient Growth | vi



Parameter Source: Bihar Source: Chhattisgarh Source Odisha

% Primitive tribal group households

http://secc.gov.in/statewisePTGLRBLMSReport?reportType=PTG , LRBL , MS






Appendix 3 – Bihar: State directory of high vulnerabilities by district District Aggregate

Vulnerability High Vulnerability (Poverty)

High Vulnerability (Marginalis.)

Associated High climate sensitivity (Water)

Associated High climate sensitivity (Land)

Associated High climate sensitivity (Agriculture)

Associated High climate sensitivity (Forest)

Associated Low adaptive capacity (Poverty)

Associated Low adaptive capacity (Marginalis.)

Banka L Land Forest

Net groundwater availability


Area under foodgrains Cropping intensity


Households monthly income < Rs 5000

Muzzafarpur M Water Agriculture

Net irrigated area Irrigation intensity

Cropping intensity Adult Cattle

Nalanda M

Water Forest

Net groundwater availability Net irrigated area Irrigation intensity

Adult Cattle Net

groundwater availability Forest area

Disabled

Paschim Champaran

L

Crop yield - foodgrains Adult Cattle

Landless households manual labour

Disabled

Madhubani M

Water Agriculture


Crop yield - foodgrains Adult Cattle

Gaya M



Soil fertility Soil fertility Adult Cattle

Houseless rural

Primitive tribal households




District Aggregate Vulnerability

High Vulnerability (Poverty)








Katihar H Land Agriculture Forest



Area under foodgrains Adult Cattle

Forest area Households monthly income < Rs 5000 Houseless rural Landless households manual labour

Women-headed households Primitive tribal households

Begusarai H Water Agriculture


Net groundwater availability Net irrigated area


Area under foodgrains Crop yield - foodgrains Adult Cattle



Women-headed households Primitive tribal households




Appendix 4 – Chhattisgarh: state directory of high vulnerabilities by district and block

District Block Aggregate Vulnerability









Bilaspur

L Land Agriculture


Area under foodgrains Cropping intensity Crop yield - foodgrains

Households monthly income < Rs 5000 Landless households manual labour

Women-headed households

Bilaspur Bilha M Land Agriculture Forest


Cropping intensity

Net groundwater availability Forest area


Bilaspur Kota H Water Land Agriculture Forest

Land Forest







Bilaspur Marwahi H Water Land Forest

Water Land Forest







Bilaspur Masturi M Land Forest

Land Forest



















Bilaspur Takhatpur M Land Forest

Land Forest







Jashpur

M


Cropping intensity Crop yield - foodgrains

Forest area Households monthly income < Rs 5000

Disabled

Jashpur Bagicha M Water


Cropping intensity


Jashpur Duldula M





Jashpur Kansabel H

Water Land Forest






Jashpur Kunkuri H







Jashpur Manora H






Disabled













Jashpur Pharsabaha H

Water Land Forest





Kabeerdham

L


Crop yield - foodgrains




Kabeerdham Bodla M

Forest Net groundwater availability



Kabeerdham Kawardha L





Kabeerdham Pandariya M



Forest area Landless households manual labour

Kabeerdham Sahaspur-Lohara

L


Cropping intensity


Korba

M Water Land






Korba Kartala M Land Forest

Land Forest






Korba Pali H Land Agriculture Forest






Households monthly income < Rs 5000 Landless















households manual labour

Korba Poudi-Uprora M Land Agriculture






Koriya

H Land Agriculture

Land Agriculture

Net irrigated area


Area under foodgrains Crop yield - foodgrains

Houseless rural


Koriya Bharatpur H Land Agriculture

Land Agriculture

Net irrigated area



Forest area Houseless rural Landless households manual labour


Koriya Sonhat H Land Agriculture Forest







Mungeli

H Water Agriculture Forest

Water Agriculture Forest

Net irrigated area



Women-headed households Disabled Primitive tribal households

Mungeli Lormi L


Cropping intensity



Infrastructure for Climate Resilient Growth | vii












Mungeli Mungeli L


Cropping intensity



Rajnanadgaon

L



Rajnanadgaon Chhuikhadhan M




Rajnanadgaon Mohla H Water Land

Water Land







Rajnanadgaon Rajnandgaon L




Surajpur

H Water Land Agriculture Forest






Women-headed households Disabled Primitive tribal households

Surajpur Bhaiyathan M




Forest area

Surajpur Pratappur H Land




Forest area Houseless rural

Infrastructure for Climate Resilient Growth | viii












Surajpur Premnagar H Land Agriculture





Surajpur Ramanujnagar M Land Agriculture





Surguja

M






Surguja Batauli L



Forest area

Surguja Lundra L



Forest area

Surguja Sitapur L



Forest area

Infrastructure for Climate Resilient Growth | ix



Appendix 5 – Odisha: state directory of high vulnerabilities by district and block










Bolangir

H Water Land Forest

Water Land Forest


Cropping intensity

Forest area Households monthly income < Rs 5000 Landless households manual labour

Disabled

Bolangir Deogaon M Water Forest

Water Forest

Net groundwater availability Irrigation intensity

Cropping intensity



Disabled

Bolangir Saintala M


Cropping intensity

Forest area Households monthly income < Rs 5000 Landless households manual labour

Bolangir Tentulikhunti (Gudvella)

L Water Forest

Water Forest




Disabled

Bolangir Titlagarh H Water Forest

Water Forest


Cropping intensity



Infrastructure for Climate Resilient Growth | x












Kalahandi

M Land Forest

Land Forest

Soil erosion Soil erosion Crop yield - foodgrains Soil erosion

Soil erosion Households monthly income < Rs 5000 Houseless rural Landless households manual labour

Disabled

Kalahandi Bhawanipatna H Water Land Agriculture Forest

Water Irrigation intensity Soil erosion

Soil erosion Crop yield - foodgrains Soil erosion

Soil erosion Households monthly income < Rs 5000 Houseless rural Landless households manual labour

Disabled

Kalahandi Golamunda M Forest Forest Irrigation intensity Soil erosion


Forest area Soil erosion


Disabled

Kalahandi Karlamunda M Water Land Agriculture Forest

Forest Irrigation intensity Soil erosion



Households monthly income < Rs 5000 Houseless rural Landless households manual labour

Disabled

Infrastructure for Climate Resilient Growth | xi












Kalahandi Kesinga M Forest Forest Irrigation intensity Soil erosion




Disabled

Kalahandi Lanjigarh H Water Water Land Agriculture Forest

Net irrigated area Irrigation intensity Soil erosion


Soil erosion Households monthly income < Rs 5000 Landless households manual labour


Kalahandi Narala M Forest

Net groundwater availability Soil erosion


Net groundwater availability Forest area Soil erosion


Kendujhar

L

Water Net irrigated area Irrigation intensity



Kendujhar Banspal L




Kendujhar Ghatgaon L




Infrastructure for Climate Resilient Growth | xii












Kendujhar Jhumpura H Water Water Land Agriculture Forest






Kendujhar Kendujhargarh L




Kendujhar Patana L




Kendujhar Saharapada L



Forest area


Kendujhar Telkoi M

Land Agriculture





Mayurbhanj

L

Forest Net Groundwater Availability


Net Groundwater Availability

Houseless rural


Mayurbhanj Bangiriposi M Water Water Net groundwater availability Net irrigated area Irrigation intensity





Infrastructure for Climate Resilient Growth | xiii












Mayurbhanj Bijatola M




Houseless rural


Mayurbhanj Bisoi M Water Water Forest






Mayurbhanj Jamda M Water Water Net groundwater availability Net irrigated area Irrigation intensity





Mayurbhanj Jashipur M




Households monthly income < Rs 5000 Houseless rural


Mayurbhanj Kaptipada L





Mayurbhanj Karanjia M Water Water Net groundwater availability Net irrigated area Irrigation intensity




Infrastructure for Climate Resilient Growth | xiv












Mayurbhanj Khunta M





Mayurbhanj Kusumi M




Houseless rural


Mayurbhanj Shamakhunta L




Houseless rural


Mayurbhanj Sukruli L




Houseless rural


Mayurbhanj Thakurmunda H Water Forest




Households monthly income < Rs 5000 Houseless rural

Mayurbhanj Udala L





Nuapada

M Water Land Agriculture Forest

Land Net Groundwater Availability Net irrigated area



Net Groundwater Availability Forest area


Infrastructure for Climate Resilient Growth | xv












Nuapada Boden M Water Land Agriculture



Area under foodgrains Crop yield - foodgrains Adult cattle


Nuapada Khariar M





Nuapada Komana H Land Agriculture





Nuapada Nuapada M Water Land Agriculture





Nuapada Sinapali H Water Land Agriculture

Water Land Agriculture





Disabled




Appendix 6 – Bihar: Index maps of ICRG districts




Bihar: Index of ICRG districts




Appendix 7 – Bihar: Maps of climate sensitivities represented by individual biophysical parameters




Bihar: Map of district-level climate sensitivity represented by net groundwater availability




Bihar: Map of district-level climate sensitivity represented by net irrigated area




Bihar: Map of district-level climate sensitivity represented by irrigation intensity

Infrastructure for Climate Resilient Growth | vii



Bihar: Map of district-level climate sensitivity represented by area under foodgrains

Infrastructure for Climate Resilient Growth | viii



Bihar: Map of district-level climate sensitivity represented by cropping intensity

Infrastructure for Climate Resilient Growth | ix



Bihar: Map of district-level climate sensitivity represented by crop yield

Infrastructure for Climate Resilient Growth | x



Bihar: Map of district-level climate sensitivity represented by soil fertility (N, P, K)

Infrastructure for Climate Resilient Growth | xi



Bihar: Map of district-level climate sensitivity represented by adult cattle

Infrastructure for Climate Resilient Growth | xii



Bihar: Map of district-level climate sensitivity represented by forest area

Infrastructure for Climate Resilient Growth | xiii



Appendix 8 – Bihar: Maps of adaptive capacities represented by individual socioeconomic parameters

Infrastructure for Climate Resilient Growth | xiv



Bihar: Map of district-level adaptive capacity represented by households with monthly income < Rs 5000

Infrastructure for Climate Resilient Growth | xv



Bihar: Map of district-level adaptive capacity represented by landless households deriving major part of their income from manual casual labour

Infrastructure for Climate Resilient Growth | xvi



Bihar: Map of district-level adaptive capacity represented by houseless rural

Infrastructure for Climate Resilient Growth | xvii



Bihar: Map of district-level adaptive capacity represented by women-headed households

Infrastructure for Climate Resilient Growth | xviii



Bihar: Map of district-level adaptive capacity represented by disabled

Infrastructure for Climate Resilient Growth | xix



Bihar: Map of district-level adaptive capacity represented by primitive tribal households

Infrastructure for Climate Resilient Growth | xx



Appendix 9 – Bihar: Maps of climate sensitivities by aggregated biophysical parameters

Infrastructure for Climate Resilient Growth | xxi



Bihar: Map of district-level climate sensitivity in relation to water

Infrastructure for Climate Resilient Growth | xxii



Bihar: Map of district-level climate sensitivity in relation to land

Infrastructure for Climate Resilient Growth | xxiii



Bihar: Map of district-level climate sensitivity in relation to agriculture

Infrastructure for Climate Resilient Growth | xxiv



Bihar: Map of district-level climate sensitivity in relation to forests

Infrastructure for Climate Resilient Growth | xxv



Bihar: Map of district-level aggregate climate sensitivity

Infrastructure for Climate Resilient Growth | xxvi



Appendix 10 – Bihar: Maps of adaptive capacities by aggregated socioeconomic parameters

Infrastructure for Climate Resilient Growth | xxvii



Bihar: Map of district-level adaptive capacities in relation to poverty

Infrastructure for Climate Resilient Growth | xxviii



Bihar: Map of district-level adaptive capacities in relation to marginalisation

Infrastructure for Climate Resilient Growth | xxix



Bihar: Map of district-level aggregate adaptive capacities

Infrastructure for Climate Resilient Growth | xxx



Appendix 11 – Bihar: Maps of vulnerabilities

Infrastructure for Climate Resilient Growth | xxxi



Bihar: Map of district-level vulnerability resulting from water and poverty

Infrastructure for Climate Resilient Growth | xxxii



Bihar: Map of district-level vulnerability resulting from land and poverty

Infrastructure for Climate Resilient Growth | xxxiii



Bihar: Map of district-level vulnerability resulting from agriculture and poverty

Infrastructure for Climate Resilient Growth | xxxiv



Bihar: Map of district-level vulnerability resulting from forest and poverty

Infrastructure for Climate Resilient Growth | xxxv



Bihar: Map of district-level vulnerability resulting from forest and marginalisation

Infrastructure for Climate Resilient Growth | xxxvi



Bihar: Map of district-level vulnerability resulting from land and marginalisation

Infrastructure for Climate Resilient Growth | xxxvii



Bihar: Map of district-level vulnerability resulting from agriculture and marginalisation

Infrastructure for Climate Resilient Growth | xxxviii



Bihar: Map of district-level vulnerability resulting from forest and marginalisation

Infrastructure for Climate Resilient Growth | xxxix



Bihar: Map of district-level aggregate vulnerability

Infrastructure for Climate Resilient Growth | xl



Appendix 12 – Chhattisgarh: Index to ICRG districts and blocks

Infrastructure for Climate Resilient Growth | xli



Infrastructure for Climate Resilient Growth | xlii



Blocks

1. Kunkuri

2. Manora

3. Kansabel

4. Pharsabahar

5. Duldula

6. Bagicha

7. Takhatpur

8. Masturi

9. Marwahi

10. Kota

11. Bilha

12. Bilha

13. Sahaspur-lohara

14. Pandariya

15. Kawardha

16. Bodla

17. Poudi-uprora

18. Pali

19. Kartala

20. Sonhat

21. Bharatpur

22. Mungeli

23. Lormi

24. Rajnandgaon

25. Mohla

26. Chhuikhadhan

27. Sitapur

28. Lundra

29. Batauli

30. Pratappur

31. Bhaiyathan

32. Premnagar

33. Ramanujnagar

Infrastructure for Climate Resilient Growth | xliii



Appendix 13 – Chhattisgarh: Maps of climate sensitivities represented by individual biophysical parameters

Infrastructure for Climate Resilient Growth | xliv



Chhattisgarh: Map of district-level climate sensitivity represented by net groundwater availability

Infrastructure for Climate Resilient Growth | xlv



Chhattisgarh: Map of block-level climate sensitivity represented by net groundwater availability

Infrastructure for Climate Resilient Growth | xlvi



Chhattisgarh: Map of district-level climate sensitivity represented by net irrigated area

Infrastructure for Climate Resilient Growth | xlvii



Chhattisgarh: Map of block-level climate sensitivity represented by net irrigated area

Infrastructure for Climate Resilient Growth | xlviii



Chhattisgarh: Map of district-level climate sensitivity represented by irrigation intensity

Infrastructure for Climate Resilient Growth | xlix



Chhattisgarh: Map of block-level climate sensitivity represented by irrigation intensity

Infrastructure for Climate Resilient Growth | l



Chhattisgarh: Map of district-level climate sensitivity represented by area under foodgrains

Infrastructure for Climate Resilient Growth | li



Chhattisgarh: Map of block-level climate sensitivity represented by area under foodgrains

Infrastructure for Climate Resilient Growth | lii



Chhattisgarh: Map of district-level climate sensitivity represented by cropping intensity

Infrastructure for Climate Resilient Growth | liii



Chhattisgarh: Map of block-level climate sensitivity represented by cropping intensity

Infrastructure for Climate Resilient Growth | liv



Chhattisgarh: Map of district-level climate sensitivity represented by crop yield

Infrastructure for Climate Resilient Growth | lv



Chhattisgarh: Map of block-level climate sensitivity represented by crop yield

Infrastructure for Climate Resilient Growth | lvi



Chhattisgarh: Map of district-level climate sensitivity represented by adult cattle

Infrastructure for Climate Resilient Growth | lvii



Chhattisgarh: Map of block-level climate sensitivity represented by adult cattle

Infrastructure for Climate Resilient Growth | lviii



Chhattisgarh: Map of district-level climate sensitivity represented by forest area

Infrastructure for Climate Resilient Growth | lix



Chhattisgarh: Map of block-level climate sensitivity represented by forest area

Infrastructure for Climate Resilient Growth | lx



Appendix 14 – Chhattisgarh: Maps of adaptive capacities represented by individual socioeconomic parameters

Infrastructure for Climate Resilient Growth | lxi



Chhattisgarh: Map of district-level adaptive capacity represented by households with monthly income < Rs 5000

Infrastructure for Climate Resilient Growth | lxii



Chhattisgarh: Map of block-level adaptive capacity represented by households with monthly income < Rs 5000

Infrastructure for Climate Resilient Growth | lxiii



Chhattisgarh: Map of district-level adaptive capacity represented by landless households deriving major part of their income from manual casual labour

Infrastructure for Climate Resilient Growth | lxiv



Chhattisgarh: Map of block-level adaptive capacity represented by landless households deriving major part of their income from manual casual labour

Infrastructure for Climate Resilient Growth | lxv



Chhattisgarh: Map of district-level adaptive capacity represented by houseless rural

Infrastructure for Climate Resilient Growth | lxvi



Chhattisgarh: Map of block-level adaptive capacity represented by houseless rural

Infrastructure for Climate Resilient Growth | lxvii



Chhattisgarh: Map of district-level adaptive capacity represented by women-headed households

Infrastructure for Climate Resilient Growth | lxviii



Chhattisgarh: Map of district-level adaptive capacity represented by women-headed households

Infrastructure for Climate Resilient Growth | lxix



Chhattisgarh: Map of district-level adaptive capacity represented by disabled

Infrastructure for Climate Resilient Growth | lxx



Chhattisgarh: Map of district-level adaptive capacity represented by disabled

Infrastructure for Climate Resilient Growth | lxxi



Chhattisgarh: Map of district-level adaptive capacity represented by primitive tribal group households

Infrastructure for Climate Resilient Growth | lxxii



Chhattisgarh: Map of district-level adaptive capacity represented by primitive tribal group households

Infrastructure for Climate Resilient Growth | lxxiii



Appendix 15 – Chhattisgarh: Maps of climate sensitivities by aggregated biophysical parameters

Infrastructure for Climate Resilient Growth | lxxiv



Chhattisgarh: Map of district-level climate sensitivity in relation to water

Infrastructure for Climate Resilient Growth | lxxv



Chhattisgarh: Map of block-level climate sensitivity in relation to water

Infrastructure for Climate Resilient Growth | lxxvi



Chhattisgarh: Map of district-level climate sensitivity in relation to land

Infrastructure for Climate Resilient Growth | lxxvii



Chhattisgarh: Map of block-level climate sensitivity in relation to land

Infrastructure for Climate Resilient Growth | lxxviii



Chhattisgarh: Map of district-level climate sensitivity in relation to agriculture

Infrastructure for Climate Resilient Growth | lxxix



Chhattisgarh: Map of block-level climate sensitivity in relation to agriculture

Infrastructure for Climate Resilient Growth | lxxx



Chhattisgarh: Map of district-level climate sensitivity in relation to forests

Infrastructure for Climate Resilient Growth | lxxxi



Chhattisgarh: Map of block-level climate sensitivity in relation to forests

Infrastructure for Climate Resilient Growth | lxxxii



Chhattisgarh: Map of district-level aggregate climate sensitivity

Infrastructure for Climate Resilient Growth | lxxxiii



Chhattisgarh: Map of block-level aggregate climate sensitivity

Infrastructure for Climate Resilient Growth | lxxxiv



Appendix 16 – Chhattisgarh: Maps of adaptive capacities by aggregated socioeconomic parameters

Infrastructure for Climate Resilient Growth | lxxxv



Chhattisgarh: Map of district-level adaptive capacity in relation to poverty

Infrastructure for Climate Resilient Growth | lxxxvi



Chhattisgarh: Map of block-level adaptive capacity in relation to poverty

Infrastructure for Climate Resilient Growth | lxxxvii



Chhattisgarh: Map of district-level adaptive capacity in relation to marginalisation

Infrastructure for Climate Resilient Growth | lxxxviii



Chhattisgarh: Map of block-level adaptive capacity in relation to marginalisation

Infrastructure for Climate Resilient Growth | lxxxix



Chhattisgarh: Map of district-level aggregate adaptive capacity

Infrastructure for Climate Resilient Growth | xc



Chhattisgarh: Map of block-level aggregate adaptive capacity

Infrastructure for Climate Resilient Growth | xci



Appendix 17 – Chhattisgarh: Maps of vulnerabilities

Infrastructure for Climate Resilient Growth | xcii



Chhattisgarh: Map of district-level vulnerability resulting from water and poverty

Infrastructure for Climate Resilient Growth | xciii



Chhattisgarh: Map of block-level vulnerability resulting from water and poverty

Infrastructure for Climate Resilient Growth | xciv



Chhattisgarh: Map of district-level vulnerability resulting from land and poverty

Infrastructure for Climate Resilient Growth | xcv



Chhattisgarh: Map of block-level vulnerability resulting from land and poverty

Infrastructure for Climate Resilient Growth | xcvi



Chhattisgarh: Map of district-level vulnerability resulting from agriculture and poverty

Infrastructure for Climate Resilient Growth | xcvii



Chhattisgarh: Map of block-level vulnerability resulting from agriculture and poverty

Infrastructure for Climate Resilient Growth | xcviii



Chhattisgarh: Map of district-level vulnerability resulting from forest and poverty

Infrastructure for Climate Resilient Growth | xcix



Chhattisgarh: Map of block-level vulnerability resulting from forest and poverty

Infrastructure for Climate Resilient Growth | c



Chhattisgarh: Map of district-level vulnerability resulting from water and marginalisation

Infrastructure for Climate Resilient Growth | ci



Chhattisgarh: Map of block-level vulnerability resulting from water and marginalisation

Infrastructure for Climate Resilient Growth | cii



Chhattisgarh: Map of district-level vulnerability resulting from land and marginalisation

Infrastructure for Climate Resilient Growth | ciii



Chhattisgarh: Map of block-level vulnerability resulting from land and marginalisation

Infrastructure for Climate Resilient Growth | civ



Chhattisgarh: Map of district-level vulnerability resulting from agriculture and marginalisation

Infrastructure for Climate Resilient Growth | cv



Chhattisgarh: Map of block-level vulnerability resulting from agriculture and marginalisation

Infrastructure for Climate Resilient Growth | cvi



Chhattisgarh: Map of district-level vulnerability resulting from forest and marginalisation

Infrastructure for Climate Resilient Growth | cvii



Chhattisgarh: Map of block-level vulnerability resulting from forest and marginalisation

Infrastructure for Climate Resilient Growth | cviii



Chhattisgarh: Map of district-level aggregate vulnerability

Infrastructure for Climate Resilient Growth | cix



Chhattisgarh: Map of block-level aggregate vulnerability

Infrastructure for Climate Resilient Growth | cx



Appendix 18 – Odisha: Index of ICRG districts and blocks

Infrastructure for Climate Resilient Growth | cxi



Odisha: Index to ICRG districts

Infrastructure for Climate Resilient Growth | cxii



Odisha: Index to ICRG blocks

1.

Blocks 1 - Boden

2 - Khariar

3 - Komana

4 - Nuapada

5 - Sinapali

6 - Bangiriposi

7 - Bijatola

8 - Bisoi

9 - Jamda Jashipur

10 - Kaptipada

11 - Karanjia

12 - Khunta

13 - Kusumi

14 - Shamakhunta

15 - Sukruli

16 - Thakurmunda

17 - Udala Banspal

18 - Ghatgaon

19 - Jhumpura

20 - Kendujhargarh

21 - Patana

22 - Saharapada

23 - Telkoi

24 - Bhawanipatna

25 - Golamunda Karlamunda

26 - Kesinga

27 - Lanjigarh

28 - Narala

29 - Deogaon

30 - Saintala

31 - Tentulikhunti (Gudvella)

32 - Titlagarh

Infrastructure for Climate Resilient Growth | cxiii



Appendix 19 – Odisha: Maps of climate sensitivities represented by individual biophysical parameters

Infrastructure for Climate Resilient Growth | cxiv



Odisha: Map of district-level climate sensitivity represented by groundwater gap

Infrastructure for Climate Resilient Growth | cxv



Odisha: Map of block-level climate sensitivity represented by groundwater gap

Infrastructure for Climate Resilient Growth | cxvi



Odisha: Map of district-level climate sensitivity represented by net irrigated area

Infrastructure for Climate Resilient Growth | cxvii



Odisha: Map of block-level climate sensitivity represented by net irrigated area

Infrastructure for Climate Resilient Growth | cxviii



Odisha: Map of district-level climate sensitivity represented by irrigation intensity

Infrastructure for Climate Resilient Growth | cxix



Odisha: Map of block-level climate sensitivity represented by irrigation intensity

Infrastructure for Climate Resilient Growth | cxx



Odisha: Map of district-level climate sensitivity represented by area under foodgrains

Infrastructure for Climate Resilient Growth | cxxi



Odisha: Map of district-level climate sensitivity represented by cropping intensity

Infrastructure for Climate Resilient Growth | cxxii



Odisha: Map of block-level climate sensitivity represented by cropping intensity

Infrastructure for Climate Resilient Growth | cxxiii



Odisha: Map of district-level climate sensitivity represented by crop yield

Infrastructure for Climate Resilient Growth | cxxiv



Odisha: Map of district-level climate sensitivity represented by soil erosion

Infrastructure for Climate Resilient Growth | cxxv



Odisha: Map of district-level climate sensitivity represented by adult cattle

Infrastructure for Climate Resilient Growth | cxxvi



Odisha: Map of district-level climate sensitivity represented by forest area

Infrastructure for Climate Resilient Growth | cxxvii



Odisha: Map of block-level climate sensitivity represented by forest area

Infrastructure for Climate Resilient Growth | cxxviii



Appendix 20 – Odisha: Maps of adaptive capacities represented by individual socioeconomic parameters

Infrastructure for Climate Resilient Growth | cxxix



Odisha: Map of district-level adaptive capacity represented by households with monthly income < Rs 5000

Infrastructure for Climate Resilient Growth | cxxx



Odisha: Map of block-level adaptive capacity represented by households with monthly income < Rs 5000

Infrastructure for Climate Resilient Growth | cxxxi



Odisha: Map of district-level adaptive capacity represented by landless households deriving major part of the income from manual casual labour

Infrastructure for Climate Resilient Growth | cxxxii



Odisha: Map of block-level adaptive capacity represented by landless households deriving major part of the income from manual casual labour

Infrastructure for Climate Resilient Growth | cxxxiii



Odisha: Map of district-level adaptive capacity represented by houseless rural

Infrastructure for Climate Resilient Growth | cxxxiv



Odisha: Map of block-level adaptive capacity represented by houseless rural

Infrastructure for Climate Resilient Growth | cxxxv



Odisha: Map of district-level adaptive capacity represented by women-headed households

Infrastructure for Climate Resilient Growth | cxxxvi



Odisha: Map of block-level adaptive capacity represented by women-headed households

Infrastructure for Climate Resilient Growth | cxxxvii



Odisha: Map of district-level adaptive capacity represented by disabled

Infrastructure for Climate Resilient Growth | cxxxviii



Odisha: Map of block-level adaptive capacity represented by disabled

Infrastructure for Climate Resilient Growth | cxxxix



Odisha: Map of district-level adaptive capacity represented by primitive tribal households

Infrastructure for Climate Resilient Growth | cxl



Odisha: Map of block-level adaptive capacity represented by primitive tribal households

Infrastructure for Climate Resilient Growth | cxli



Appendix 21 – Odisha: Maps of climate sensitivities by aggregated biophysical parameters

Infrastructure for Climate Resilient Growth | cxlii



Odisha: Map of district-level climate sensitivity in relation to water

Infrastructure for Climate Resilient Growth | cxliii



Odisha: Map of block-level climate sensitivity in relation to water

Infrastructure for Climate Resilient Growth | cxliv



Odisha: Map of district-level climate sensitivity in relation to land

Infrastructure for Climate Resilient Growth | cxlv



Odisha: Map of block-level climate sensitivity in relation to land

Infrastructure for Climate Resilient Growth | cxlvi



Odisha: Map of district-level climate sensitivity in relation to agriculture

Infrastructure for Climate Resilient Growth | cxlvii



Odisha: Map of block-level climate sensitivity in relation to agriculture

Infrastructure for Climate Resilient Growth | cxlviii



Odisha: Map of district-level climate sensitivity in relation to forests

Infrastructure for Climate Resilient Growth | cxlix



Odisha: Map of block-level climate sensitivity in relation to forests

Infrastructure for Climate Resilient Growth | cl



Odisha: Map of district-level aggregate climate sensitivity

Infrastructure for Climate Resilient Growth | cli



Odisha: Map of block-level aggregate climate sensitivity

Infrastructure for Climate Resilient Growth | clii



Appendix 22 – Odisha: Maps of adaptive capacities by aggregated socioeconomic parameters

Infrastructure for Climate Resilient Growth | cliii



Odisha: Map of district-level adaptive capacity in relation to poverty

Infrastructure for Climate Resilient Growth | cliv



Odisha: Map of block-level adaptive capacity in relation to poverty

Infrastructure for Climate Resilient Growth | clv



Odisha: Map of district-level adaptive capacity in relation to marginalisation

Infrastructure for Climate Resilient Growth | clvi



Odisha: Map of block-level adaptive capacity in relation to marginalisation

Infrastructure for Climate Resilient Growth | clvii



Odisha: Map of district-level aggregate adaptive capacity

Infrastructure for Climate Resilient Growth | clviii



Odisha: Map of block-level aggregate adaptive capacity

Infrastructure for Climate Resilient Growth | clix



Appendix 23 – Odisha: Maps of vulnerabilities

Infrastructure for Climate Resilient Growth | clx



Odisha: Map of district-level vulnerability resulting from water and poverty

Infrastructure for Climate Resilient Growth | clxi



Odisha: Map of block-level vulnerability resulting from water and poverty

Infrastructure for Climate Resilient Growth | clxii



Odisha: Map of district-level vulnerability resulting from land and poverty

Infrastructure for Climate Resilient Growth | clxiii



Odisha: Map of block-level vulnerability resulting from land and poverty

Infrastructure for Climate Resilient Growth | clxiv



Odisha: Map of district-level vulnerability resulting from agriculture and poverty

Infrastructure for Climate Resilient Growth | clxv



Odisha: Map of block-level vulnerability resulting from agriculture and poverty

Infrastructure for Climate Resilient Growth | clxvi



Odisha: Map of district-level vulnerability resulting from forest and poverty

Infrastructure for Climate Resilient Growth | clxvii



Odisha: Map of block-level vulnerability resulting from forest and poverty

Infrastructure for Climate Resilient Growth | clxviii



Odisha: Map of district-level vulnerability resulting from water and marginalisation

Infrastructure for Climate Resilient Growth | clxix



Odisha: Map of block-level vulnerability resulting from water and marginalisation

Infrastructure for Climate Resilient Growth | clxx



Odisha: Map of district-level vulnerability resulting from land and marginalisation

Infrastructure for Climate Resilient Growth | clxxi



Odisha: Map of block-level vulnerability resulting from land and marginalisation

Infrastructure for Climate Resilient Growth | clxxii



Odisha: Map of district-level vulnerability resulting from agriculture and marginalisation

Infrastructure for Climate Resilient Growth | clxxiii



Odisha: Map of block-level vulnerability resulting from agriculture and marginalisation

Infrastructure for Climate Resilient Growth | clxxiv



Odisha: Map of district-level vulnerability resulting from forest and marginalisation

Infrastructure for Climate Resilient Growth | clxxv



Odisha: Map of block-level vulnerability resulting from forest and marginalisation

Infrastructure for Climate Resilient Growth | clxxvi



Odisha: Map of district-level aggregate vulnerability

Infrastructure for Climate Resilient Growth | clxxvii



Odisha: Map of block-level aggregate vulnerability

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Recommended citation: Smithers, R.J., Mittal, M., Ahmed, M., Naik, N., Kumar, A., Kiff, B., Dube, S. (2017) Infrastructure for Climate Resilient Growth – Vulnerability assessment. A report for the UK Department for International Development.

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