Development of Composite Drought Index Using Remotely Sensed Data: A Case Study on Sambhaji Nagar District, Maharashtra, India

Abstract

Drought is a continual natural hazard that significantly affects agriculture, water supplies, and livelihoods in semi -arid areas. The intricate nature characterized by rainfall unpredictability, soil moisture deficits, and hydrological imbalances renders effective monitoring difficult. This work formulates and assesses a Composite Drought Index (CDI) for Sambhaji Nagar district in the droughtaffected Marathwada area of Maharashtra by amalgamating various drought indicators obtained from remote sensing and reanalysi s datasets. Three literature-supported indicators were chosen: the Standardized Precipitation Index (SPI), Soil Moisture Index (SMI), and Standardized Runoff Index (SRI). Monthly raster datasets for precipitation (CHIRPS), soil moisture (GLDAS), and surface runof f (GLDAS) from 2015 to 2020 were processed at a geographical resolution of 1 km and standardized using Z-score analysis. Four weighting methodologies were utilized to develop the CDI: equal weighting, literature-informed weights, correlationderived weights, and weights based on Principal Component Analysis (PCA). Weighted overlays were executed to produce yearly CDI rasters, thereafte r categorized by drought severity levels. The validation of the CDI was performed utilizing terrestrial rainfall and soil moisture observations, assessed through performance measures such as R², RMSE, MAE, and Kling–Gupta Efficiency (KGE). The PCA-based CDI exhibited the highest performance among all methods (R² = 0.75, RMSE = 0.50, MAE = 0.39, KGE = 0.76), showcasing exceptional proficiency in delineating drought severity and spatiotemporal variability. The results underscore the efficacy of combining multisource indicators with statistical weighting, affirming the PCA-based CDI as a reliable instrument for drought monitoring and early warning. This approach provides essential assistance for sustainable drought management, water resource planning, and climateresilient agricultural techniques in Sambhaji Nagar.

Keywords: drought monitoring, drought indices, composite drought index, principal component analysis, remote sensing