Comparative Analysis of Multiple Drought Indices for the Hindukush Region in Pakistan

Abstract

Drought is an enduring hydro-climatic challenge in Pakistan's Hindukush region, where fragile agro-ecological systems are particularly vulnerable to fluctuations in precipitation and evapotranspiration. The lack of a universally applicable indicator and the regional variety of drought consequences necessitate assessing multiple indices to identify the most suitable index for the particular environmental dynamics of the area. This study undertakes a comparative analysis of four drought indices: the Standardized Precipitation Index (SPI), Agricultural Standardized Precipitation Index (aSPI), Reconnaissance Drought Index (RDI), and Effective Reconnaissance Drought Index (eRDI) to identify the most effective index or indices for drought assessment in the region. Using the long-term precipitation and temperature (minimum and maximum) record (1982–2022) from the National Aeronautics and Space Administration'sModern-EraRetrospectiveAnalysis for Research and Applications, Version 2 (NASA's MERRA-2) dataset, selected indices were calculated across multiple temporal scales (3, 6, 9, and 12 months). Statistical techniques, including Pearson correlation coefficient and Two-way ANOVA (Analysis of Variance), were employed to analyze inter-index consistency and temporal performance. The correlation coefficients between indices were notably high (r = 0.83–0.97, p < 0.01), indicating strong agreement, particularly between SPI and aSPI, and between RDI and eRDI. Two-way ANOVA results revealed statistically significant differences across indices and timescales (F = 16.42, p < 0.001), confirming that both index type and temporal resolution influence drought characterization. The study highlights key drought years, including the prolonged 1998–2002 event and shorter events in 2015, 2018, and 2019. Notably, aSPI demonstrated enhanced sensitivity to agricultural drought due to its emphasis on effective precipitation, while eRDI effectively captured climate-induced drought variability. The findings recommend a combined application of aSPI and eRDI for robust drought monitoring in this climate and ecologically sensitive region.