Research Report
ADAPTATION EFFECTIVENESS INDICATORS FOR AGRICULTURE IN THE GANGETIC BASIN
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ADAPTATION EFFECTIVENESS INDICATORS FOR AGRICULTURE IN THE GANGETIC BASIN

2012-01
Contributor: 
R. Kotru, ICIMOD
N. Pradhan, ICIMOD
D. Mohan, TERI
G. Rabbani, BCAS
2013-03

Measuring the effectiveness of adaptation to climate change has assumed significance for the reasons that huge amount of resources are being made available for climate change adaptation and it is important for various stakeholders to identify and prioritize adaptation actions before they are implemented on the ground so as to achieve adaptation efficiently. Identifying adaptation effectiveness indicators is the first step to measuring the effectiveness of adaptation actions at local level. Keeping this in view, the project entitled ‘Identification of win-win adaptation options through adaptation metrics and integrated adaptation decision making frameworks’ was implemented in the Gangetic Basin with the collaboration of national level partners of BCAS in Bangladesh, TERI in India and ICIMOD in Nepal. The study was funded by the Ministry of Environment, Japan through suishinhi (S8) with Ibaraki University, Japan as nodal institution.
The study was conducted in the drought-prone villages of Bangladesh, India and Nepal in the Gangetic Basin. The approach consisted of identifying local indicators and integrating them in to the analytical framework adapted by the Global Adaptation Index (GaIn). The index developed with local indicators is being termed as Local Adaptation Index (LaIn). A broad set of indicators were identified from the literature reviews and regional consultations. These indicators were further put through national and community level consultations for identifying the final set of indicators that can be integrated into the LaIn computation.
In Bangladesh, the surveys were conducted in the drought prone area of Chapai Nawabganj district. The repeated droughts in the district have manifested in the form of loss in crop production, increase in pest attack, and perennial water crisis. One of the prominent responses in the region is to drill deep tube wells to supplement the rainfall deficit for crop and household purposes. However, this single intervention has failed to provide an effective remedy to the problem. The field surveys have indicated that options such as adoption of drought tolerant and short duration crop varieties followed by relay cropping are the need of the hour. Subsidies to farmers and farmer field schools were seen as an important policy options for adapting to climate change in this region. To evaluate the effectiveness of these options, the respondents have identified several effectiveness indicators which have shown statistically significant association with the demographic background of the respondents. Period of fresh water availability and calorie intake per person have shown significant association with the gender among all the environmental and social indicators while none of the economic indicators have shown significant association with the socio-economic background.
In India, the study was carried out in the drought-prone areas of Kanpur Dehat District of Uttar Pradesh. The prominent adaptation option in vogue in the area is construction of water harvesting structures such as contour bunds. The surveys have revealed that there is a need to introduce improved irrigation systems, improved soil management practices and improved drought forecasting to go hand in hand with the water harvesting being implemented. The respondents felt that the indicators increased water availability, duration of water stress, % of income used for health care, food self-sufficiency, increased assets and total farm income will better reflect the effectiveness of the identified adaptation options. The statistical analysis has not revealed any significant association between practices, for all the top ranked indicators and socio-economic characteristics of the respondents. However, the associations were significant for the other less significant indicators (i.e. those ranked 2 and below).
In Nepal, the study was carried out in the drought-prone areas of Bara and Parsa districts. The repeated droughts in the region have decreased crop yields, were responsible for increase in insect pests, and decreased availability of fresh water. The significant adaptation options identified in the study location were small irrigation systems, irrigation scheduling in the canal, irrigation rationing, and community based maintenance of irrigation canals. The top ranked indicators such as number of farmers with drought concerns, nutritional diversity, change in household income etc didn’t show any association with the practices identified as well as the socio-economic background of the respondents. However, indicators such as soil organic carbon content and crop yield change differed significantly by the socio-economic status of the respondents.
The above identified indicators were quantified through consulting literature and integrated using the same methodology adopted by Global Adaptation Index (GaIn) leading to development of Local Adaptation Index (LaIn). The results were presented to show the shift in LaIn values after introduction of a certain practice compared to the business as usual. However, these calculations are provisional at this stage and final report will consist of detailed and much refined calculations. In summary, the study was able to identify number of environmental, policy and economic indicators that could help in measuring the effectiveness of adaptation actions at the local level.
However, several questions remain to be answered which include the cost of implementing such indicator-rich measurement system for small projects with little funds to spare for monitoring and evaluation, the capacity considerations for various stakeholders and how these indicators work in consistency with the measurements done at the macro level. The community was involved towards the end of the indicator identification process and most community respondents had difficulty in recognizing, understanding and linking the indicators to their context. Hence, there is a need to conduct a completely bottom-up exercise at the study locations and see to what extent the bottom-up set of indicators differ from the top-down set of indicators. Additional questions emerges is the possibility of including combination of these two indicators (i.e. bottom up and top down) in calculating LaIn and what it means for the ultimate user and outcome and conducting the same exercise in flood prone areas to see how the indicators differ between drought and flood prone areas. The project team aims to answer these questions in the rest of the project phase (2013-2015).

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