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Information on agricultural drought vulnerability status of different regions is extremely useful for implementation of long term drought management measures. A quantitative approach for measuring agricultural drought vulnerability at sub-district level was developed and implemented in the current study, which was carried-out in Andhra Pradesh state, India with the data of main cropping season i.e., kharif. The contributing indicators represent exposure, sensitivity and adaptive capacity components of vulnerability and were drawn from weather, soil, crop, irrigation and land holdings related data. After performing data normalisation and variance based weights generation, component wise composite indices were generated. Agricultural Drought Vulnerability Index (ADVI) was generated using the three component indices and beta distribution was fitted to it. Mandals (sub-district level administrative units) of the state were categorised into 5 classes – Less vulnerable, Moderately vulnerable, Vulnerable, Highly vulnerable and Very highly vulnerable. Districts dominant with vulnerable Mandals showed considerably larger variability of detrended yields of principal crops compared to the other districts, thus validating the index based vulnerability status. Current status of agricultural drought vulnerability in the state, based on ADVI, indicated that vulnerable to very highly vulnerable group of Mandals represent 54 % of total Mandals and about 55 % of the agricultural area and 65 % of the rainfed crop area. The variability in the agricultural drought vulnerability at disaggregated level was effectively captured by ADVI. The vulnerability status map is useful for diagnostic analysis and for formulating vulnerability reduction plans.

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

Analysing agricultural drought vulnerability at sub-district level through exposure, sensitivity and adaptive capacity based composite index