Agricultural Drought Hotspot Assessment in the Middle Ganga Plain,India, Using Multi-Parameter Approaches

Agricultural drought threatens food security and livelihoods in the Middle Ganga Plain (MGP),India. This study identifies agricultural drought hotspots using a multi-parameter approach, integrating a Drought Vulnerability Index (DVI) from 16 parameters and a Drought Preparedness Index (DPI) from 22 indicators. These indices were combined within a novel Vulnerability–Preparedness Framework to systematically delineate high-risk areas. The Artificial Neural Network (ANN) model has been employed to identify the hotspot zones The results show that 17.46% of the region is a drought 'Hotspot', with a critical 6.57% classified as an 'Intense Hotspot' concentrated in the districts of Gazipur, Jaunpur, Mirzapur, and Varanasi in the south western part of the study region. Analysis of the Standardized Precipitation Index (SPI) for these districts confirmed a history of recurring meteorological dry spells. Correlation analysis linked hotspot formation to high population density, a large agricultural labor force, and significant groundwater extraction. The model’s robustness was validated, demonstrating high accuracy with an Area Under the Curve (AUC) of 0.889 and strong agreement between predicted and observed data on the Taylor diagram. This study advances SDG 2 (Zero Hunger), SDG 6 (Clean Water), and SDG 13 (Climate Action) by mapping agricultural drought risks to guide sustainable water use and build climate resilience. These findings provide crucial spatial intelligence for policymakers to develop targeted interventions and site-specific water management strategies to enhance agricultural resilience in the MGP.