Enhancing agricultural drought monitoring with the Integrated Agricultural Drought Index (IADI): A multi-source remote sensing approach

Drought has significantly threatened India’s agro-economic sector, resulting in widespread environmental degradation and socio-economic challenges. This study provides remote sensing technology to overcome the limitations of traditional drought monitoring methods. To address this, Integrated Agricultural Drought Index (IADI), a newly proposed index that combines multiple remotely sensed-derived indicators with Analytical Hierarchy Process (AHP) for comprehensive agricultural drought assessment, is used. IADI integrates indicators such as Vegetation Health Index (VHI), Normalized Difference Drought Index (NDDI) and Enhanced Vegetation Index (EVI) to provide a concise assessment suitable for different farming systems. The study was conducted in the upper Dwarkeswar river basin focusing on drought trends from 2000 to 2019. Initially, drought years were identified using the Rainfall Anomaly Index (RAI). Subsequently, spatial drought indices were calculated and integrated into the IADI framework. The results revealed significant spatial variation in drought severity with an annual increase of 21.88 km² in drought-affected areas (R² = 0.98). Validation using Area Under Curve-Receiver Operating Characteristic (AUC-ROC) showed that the IADI achieved an accuracy of 76 %, outperforming individual indices such as VHI (72 %), NDDI (49 %) and EVI (47 %). These results highlight the improved predictive power of IADI, providing useful insights for real-time drought monitoring, resource allocation and strategic planning. This approach provides a sustainable framework for drought management, assisting policymakers and stakeholders in enhancing regional food security and resilience to climate variability.