ABSTRACT Rajasthan, a predominantly agrarian state in northwestern India, frequently experiences severe droughts that adversely affect agricultural productivity, water resources, and the rural livelihoods of its residents. This study presents a comprehensive analysis of the climatic drivers and spatial dynamics of drought across four highly drought‐prone districts—Barmer, Hanumangarh, Jaisalmer, and Jodhpur—using long‐term meteorological data from 1951 to 2020. Multiple drought indices, including the Standardized Precipitation Index (SPI), Effective Standardized Precipitation Index (eSPI), Reconnaissance Drought Index (RDI), and potential evapotranspiration (PET), were computed using DrinC software and analyzed alongside correlation matrices and principal component analysis (PCA) to delineate district‐specific drought regimes. Results reveal strong spatial heterogeneity, with Barmer and Jaisalmer facing the most frequent and intense droughts. In contrast, no significant long‐term precipitation trends were detected; however, a consistent and significant warming trend was observed, intensifying atmospheric evaporative demand, particularly during the premonsoon months. Correlation analysis identifies strong interdependencies among temperature, relative humidity, cloud cover, and wind speed. PCA further distilled distinct climatic mechanisms driving droughts: wind‐ and temperature‐dominated regimes in Barmer and Jodhpur and a humidity‐sensitive regime in Hanumangarh. The integration of long‐term data and multiple indices offers a nuanced understanding of meteorological drought variability and its implications for groundwater stress, agricultural planning, and water governance. Our findings underscore the need to move beyond one‐size‐fits‐all approaches and implement district‐specific, data‐informed drought management frameworks. As a case study from a globally significant semiarid region, this research provides a transferable methodology for understanding drought drivers and crafting resilient water and agricultural strategies in similar arid landscapes worldwide.
Upadhyay et al. (Thu,) studied this question.