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Study area: Xinjiang, China. Study focus: The Agricultural Productivity Ratio (APR) was combined with the cumulative distribution function of water deficit (WD) to construct the climatic precipitation evapotranspiration index (CPEI). Furthermore, the SPEI₃, standardized soil moisture index (SSI), and vegetation condition index (VCI) were calculated. The accuracy of these four indices and their associated drought evolution trends was compared and assessed using Pearson correlation analysis, actual agricultural drought data, Theil-Sen estimator, Mann-Kendall test, and spatial transfer matrix. New hydrological insights for the region: The results indicate that CPEI₃ outperforms conventional indices in capturing agricultural drought dynamics across Xinjiang's diverse climates. This enhanced performance is evidenced by stronger correlations with soil moisture (r = 0. 59) and NDVI compared to SPEI₃ and SSI. Notably, while VCI ranks highest in spatial accuracy, it tends to misclassify drought as non-drought, underscoring CPEI₃'s superior reliability. The drought severity trajectory reveals a distinct weakening, intensifying, and weakening pattern, with 48. 52% of the region exhibiting slight worsening. These findings demonstrate considerable potential for advancing agricultural drought monitoring and assessment practices.
Tang et al. (Fri,) studied this question.