Randomized trial evaluates a new drought index in an irrigation area, suggesting improved water management strategies.
The Chushandian Irrigation Area (CSDIA) lacks a comprehensive drought index integrating meteorological and hydrological information, hindering accurate drought assessment and sustainable water resource management under changing climatic conditions. To address this, a multivariate standardized drought index (MSDI) based on a Copula function was developed, combining precipitation and runoff. Optimized run theory identified compound drought events, and cross-wavelet power spectrum explored large-scale climate drivers. Results show that MSDI correlates strongly with both the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) (Pearson’s r > 0.75, p < 0.01) at the monthly scale, effectively capturing drought onset, duration, and termination. From 1960 to 2018, 110 compound drought events were identified, characterized by short durations (mean 3.82 months) and low intensities (mean 4.43). The most severe event (August 1960–October 1961, duration 15 months, intensity 22.72) has a return period of about 40 years. Among nine teleconnection factors, ENSO is the dominant driver, followed by sunspot activity (SSI). BEAST change-point detection revealed a shift toward drought intensification after 1990, underscoring the need for adaptive water management strategies. These findings provide scientific support for sustainable drought monitoring, climate-resilient agricultural planning, and adaptive water management in CSDIA, contributing to the broader goal of ensuring food security and water sustainability in monsoon-dependent irrigation systems.
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田俊跃 et al. (2026) studied this question.
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