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

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