Fine-scale assessment of blue-water dependence via crop rotation systems in South Asia under a changing climate

Abstract Cropland productivity in South Asia (SA) relies on both blue-water (i.e. irrigation from surface and groundwater) and green-water (rainwater stored in the soil) supplies. The blue-water dependence index (BDI), which reflects the fraction of blue water in total crop water demand of a certain location, is a crucial indicator for managing freshwater resources effectively, ensuring sustainable food production systems and adapting agricultural practices to climate change. The knowledge of BDI for SA croplands at fine spatial scales is limited. Here we present a comprehensive modeling framework for fine-scale BDI assessment using an evapotranspiration-based approach to calculate crop water demand. A novel hierarchical decision tree approach was employed to identify major crop rotation systems, forming the basis for estimating regional crop water demand. We produced annual crop rotation maps at 250 m spatial resolution for 18 years (2003–2020) with an overall accuracy of 78.60%. Our results based on the national-scale analysis reveal that croplands in India, Pakistan, and Bangladesh have an averaged BDI value of 0.32, 0.65, and 0.39, respectively. Notably, cotton and sugarcane crops have the highest BDI (⩾0.42) in SA. Future climate data under different scenarios indicate that the BDI in tropical croplands is expected to decrease, while arid to semi-arid croplands will require more irrigation water to support optimal crop growth. In light of the future variability of BDI, our research further implies a few candidate strategies for climate change mitigation in SA that include enhancing water management infrastructures, developing climate-resistant crop varieties, and relocating crop cultivation areas with transboundary cooperation.