A Sustainable Framework for Drought Modeling using Meteorological Drought Indicators as Proxies for Hydrological Drought

Droughts are among the most severe natural disasters, with profound impacts on human livelihoods, agricultural productivity, and economic stability. Addressing freshwater scarcity through sustainable water resource management remains a global priority, yet accurate estimation of freshwater availability is often hindered by uncertainties in climate projections. In India, this challenge is amplified by the scarcity of streamflow data and the limited availability of reliable hydrological records across catchments. Despite these constraints, the abundance of meteorological data offers an alternative avenue to assess drought conditions. Emerging studies highlight a strong link between meteorological and hydrological droughts, suggesting that meteorological indicators can serve as a proxy to predict hydrological drought dynamics. This study develops a generalized framework to explore the relationship between meteorological and hydrological droughts using twelve diverse catchments across India. The monthly stream flow data were analyzed to calculate the Standardized Streamflow Index (SSI), quantifying the severity of the hydrological drought. Simultaneously, key meteorological drought indices—Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Palmer Drought Severity Index (PDSI)—were derived using precipitation and temperature records. Correlation and time-series analyses revealed that meteorological drought indices, combined with catchment-specific characteristics such as soil type, elevation, and topography, can effectively predict hydrological drought conditions in regions with sparse hydrological data. This research enhances our understanding of drought propagation mechanisms in India and provides a foundation for developing early warning systems and informed sustainable water resource management strategies, particularly in data-scarce regions.