Development of an improved Scaled Drought Condition Index (ISDCI) incorporating soil moisture for drought monitoring in Xinjiang

Abstract

Various composite drought indices have been developed to quantify drought conditions. However, many challenges, such as inadequate soil moisture representation, empirical variable weights, and arbitrary drought classification, still exist. Xinjiang was selected as a typical study area, and an Improved Scaled Drought Condition Index (ISDCI) was developed by integrating precipitation, vegetation, temperature, and downscaled soil moisture with objectively determined weights. Additionally, the classification of drought severity has been refined in a relatively objective way. The results indicate the following: (1) Compared to the Scaled Drought Condition Index (SDCI) and the Vegetation Health Index (VHI), ISDCI showed a higher correlation with the Standardized Precipitation Evapotranspiration Index (SPEI) and the self-calibrating Palmer Drought Severity Index (scPDSI). (2) The optimized drought classification scheme exhibited better alignment with SPEI in terms of drought frequency and drought affected area. (3) Based on ISDCI, Xinjiang experienced an overall drying trend during the 2001–2023 growing seasons. The Ili River Basin dried the fastest (slope = − 8 × 10⁻⁴), while the Tarim River Basin showed the slowest drying trend (slope = −2 × 10⁻⁴). Oases and some mountainous areas became wetter, whereas deserts continued to dry. (4) ISDCI effectively captured major droughts, including those in Xinjiang (2008) and the Ili River Basin (2014). Overall, ISDCI offers high-resolution and near-real-time drought monitoring capabilities, providing scientific support for agricultural management and water resource regulation in arid and semi-arid regions.