Soil Moisture–Vegetation Stress–Based Agricultural Drought Index Integrating Remote Sensing–Derived Soil Moisture and Vegetation Indices

Abstract

Agricultural drought has significant impacts on society and governance, including reduced food production and revenue. Thus, accurate monitoring and assessment of drought is crucial to provide an early warning system for socioeconomic impacts resulting from prolonged moisture deficit. Although meteorological drought provides a potential signature for water availability, it is insufficient to fully characterize agricultural drought. More efficient calculation and assessment methods are required that account for cropping patterns, soil characteristics, and soil moisture patterns to reflect actual crop water stress. To address this need, an integrated approach called the Soil Moisture–Vegetation Stress-Based Agricultural Drought Index (SVADI) is discussed herein. The approach utilizes remote sensing observations of soil moisture and vegetation to derive soil moisture and vegetation stress-based drought indices. Shannon's entropy formula is employed to dynamically combine the indices and determine their relative importance. Findings of the study establish SVADI as an effective tool for accurately assessing agricultural drought in the region. The study focuses on eastern India, consisting of five Indian states (Bihar, Jharkhand, Chhattisgarh, Odisha, and West Bengal), which can also be implemented elsewhere.