Spatiotemporal Variations and Spatially Associated Factors of Drought in Hebei Province Based on Multi-Source Consistency Evaluation of Remote Sensing Drought Indices

Global climate change has intensified drought risk, threatening water resources, agriculture, and ecosystems. This study evaluated four Moderate Resolution Imaging Spectroradiometer (MODIS)-based drought indices in Hebei Province: the evapotranspiration-to-potential-evapotranspiration-based Crop Water Stress Index (ET/PET-based CWSI), Temperature Condition Index (TCI), Vegetation Condition Index (VCI), and Temperature Vegetation Dryness Index (TVDI). During 2001–2020, the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), the 1 km gridded soil-moisture product SMCI1.0, Taylor statistics, classification metrics, and typical drought events were used for multi-source consistency evaluation. Although the classification metrics for CWSI indicated moderate drought discrimination and relatively high false-alarm rates, the multi-source consistency evaluation showed that CWSI had the most stable overall performance among the four tested indices. Sen’s slope, the Mann–Kendall test, the Optimal Parameters-based Geographical Detector (OPGD), and random forest were used to examine trends and spatially associated factors. CWSI-derived drought intensity generally decreased, with severe and extreme drought areas decreasing and mild and moderate drought areas increasing. Severe-and-above drought was most prominent in spring. Temperature showed the strongest association with CWSI spatial differentiation, followed by elevation and socioeconomic variables. The interaction between temperature and soil type had the highest explanatory power. These results provide a reference for regional drought monitoring and water resource management.