Deciphering the spatial fingerprint of drought propagation through precipitation, vegetation and groundwater

Abstract Droughts, depending on their nature, have had devastating consequences, including crop destruction, famine and millions of deaths, particularly in countries like India that heavily rely on rainfall for agriculture. The present study aims to quantify the linkage between meteorological, agricultural and hydrological drought at a high spatial resolution across India. These connections were established by developing various drought propagation metrics followed by subsequent correlation analysis, lag analysis and clustering. Standard Precipitation Index (SPI), Deviation in NDVI (Dev‐NDVI) and GRACE Drought Severity Index (GRACE‐DSI) were used to represent meteorological, agricultural and hydrological droughts. Run theory with thresholds of −1, −0.5 and −0.05 were used to delineate the drought events for meteorological, hydrological and agricultural droughts, respectively. Furthermore, multivariate K‐means clustering based on factors such as drought duration, latitude, longitude, severity, propagation and recovery speeds was done to create spatial clusters having similar drought characteristics. Correlation analysis showed the highest average correlations at a lag of around 7–8 months between meteorological and hydrological drought, a lag of 1–2 months in case of meteorological and agricultural drought and a lag of 3–4 months between agricultural and hydrological drought. The analysis of drought duration indicated that, on average, meteorological drought in India lasted for 2.34 months, while agricultural drought lasted for 3 months, reflecting a 26.5% increase, whereas hydrological drought lasted for 5.22 months, indicating a notable 123% increase. This increase in average drought duration as it propagates from meteorological to agricultural to hydrological drought can be attributed to the lengthening property of drought propagation. Clustering analysis reveals presence of five homogeneous drought clusters. Additionally, cluster analysis reveals that for meteorological and agricultural droughts arid regions showed the highest severity whereas for hydrological droughts north Indian states including Punjab and Haryana showed the highest severity.