Date: 18-23 March 2013
Assessing the effectiveness of climate change adaptation actions is important for monitoring and evaluation at regular intervals, efficient allocation of limited resources and making sure that maladaptation doesn’t happen. Identifying and quantifying a set of indicators through participatory processes has gained popularity due to the importance of community based approaches in climate change adaptation. With this background, a project has been implemented for identifying and quantifying a set of adaptation effectiveness indicators with study locations in drought affected areas of the Gangetic Basin.
A set of effectiveness indicators were identified first by conducting literature review followed by a regional consultation workshop and these indicators were further vetted at national level expert consultation meetings where individual indicators were visited for their relevance to the country and study location specific circumstances. Multiple criteria analysis was carried out for prioritizing those indicators that satisfy most criteria. These indicators were transformed into structured questionnaires for consultations with local farming communities, district administration and nongovernmental organizations that engage in implementing adaptation projects. The survey data has been statistically analyzed for identifying associations between adaptation practices and various socio-economic characteristics (Pearson chi-square test). Further, these indicators were converted into Local Adaptation Index (LaIn) by using the computational procedure adopted by the Global Adaptation Index (GaIn).
The study has revealed important aspects to be considered while identifying the adaptation effectiveness indicators that include processes used for identification, ranking, and quantifying indicators; perception of individuals on wellbeing and it’s relationship with climate change; availability of data for quantifying indicators; gender and economic composition of respondents engaged in ranking indicators. Interesting associations were found between the demographic characteristics and adaptation effectiveness indicators and how local adaptation index could compare with the global adaptation index and issues underlying those comparisons.
Acknowledgements: The authors acknowledge the funding support received from the S8 (Suishinhi) project of Ministry of Environment, Government of Japan for carrying out this study.
Date: 18-23 March 2013