Mapping farmer vulnerability to target interventions for climate-resilient agriculture: science in practice

Abstract Farmers in dryland regions are highly vulnerable to rainfall variability. This vulnerability is unequal, as it mediated by biophysical and social factors. Implementing policies for climate resilience requires identification of farmers who most extreme events like dry spells. We develop a novel approach conceptualizing spell at the farm scale terms monsoon crop water deficit. Using inputs weather, terrain, soil properties, land-use-land-cover, cadastral maps, our tool models an hourly balance 30 m × resolution maps deficit under rainfed conditions. good indicator relative sensitivity spells allows prioritization interventions within focus region. Our tool, developed deployed Maharashtra State Project on Climate-Resilient Agriculture, iteratively calibrated refined. present result one such iteration where 72% cases were found have agreement between modelled output farmers' perception spell-induced stress. work demonstrates how hazards may be mapped micro-scales assist policy makers targeting ecologically fragile with high