Abstract
Droughts pose significant challenges to food security, affecting millions of people and hectares of land in India. Despite their widespread impact, assessing drought patterns at a high spatial resolution remains a challenge, particularly in regions with poor data availability. Standardised Precipitation Evapotranspiration Index (SPEI) is one of the most widely accepted drought indices. The publicly available SPEI reanalysis dataset has a poor spatial resolution for regional drought studies. Land Surface Temperature (LST) has the potential to act as an effective proxy for SPEI and can be used for high-resolution drought studies. The study considered six homogeneous drought regions (NWH, CPR, NEI, NCP, NWI, and SPR) over India, and the recent trend in LST and SPEI over these regions was estimated using modified Mann-Kendell (MMK) trend and Sen’s slope estimator at monthly, seasonal, and annual time scales. The correlation between SPEI and LST was also checked at a 95% confidence level. Results indicate statistically significant decreasing annual LST trends in NWH (slope = −0.10), CPR (slope = −0.09), and NWI (slope = −0.11) regions, while increasing SPEI trends were observed in NWI (slope = 0.06) and NCP (slope = 0.01) regions during 2001–2019. Additionally, NCP (p = 0.025), CPR (p = 0.002), and NWI (p = 0.020) exhibited significantly decreasing LST trends during winter, with a notable post-monsoon decrease observed in NWI. Significant correlations between annual LST and SPEI were observed only in CPR (r =−0.527) and NWI (r = −0.601), with seasonal associations found predominantly in winter across CPR, NEI, NCP, and NWI regions. Notably, a significant correlation was observed in all months except July over NWI, with consistent correlations during most of the winter months in NWH, CPR, NCP, and NWI regions. The observed trends and correlations can provide valuable insights for policymakers and stakeholders in formulating effective drought mitigation strategies.
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