Remote Sensing-Based Identification of Sensitive Environmental Intervals Controlling Drought Propagation Time Across China

Drought early warning is important for reducing agricultural production risks and ensuring regional water security. However, existing warning systems often focus on drought propagation probabilities and average propagation times, with insufficient attention to the identification of changes in propagation time. This study constructs a meteorological drought–soil drought–groundwater drought propagation chain and uses both Granger causality and the maximum positive correlation coefficient method to quantify stage-specific propagation time. Random forest, PDP/LOWESS, and SHAP analyses are then applied to identify important environmental factors and determine their cross-method sensitive intervals. The results show that PET, NDVI, mean annual precipitation, and temperature exhibit high importance across multiple regions and stages. Additionally, sensitive intervals in which important environmental factors significantly affect propagation time were found. In Stage 1 in North China, the effect of the NDVI on propagation time decreases after it exceeds about 0.1. In Stage 2 in Southeast China, temperatures around 17–18 °C are associated with shortened propagation times. The changes are inconsistent across regions and stages. When important factors enter or approach sensitive intervals, propagation time is more likely to change. The propagation time–important factor–sensitive interval analysis framework proposed in this study provides supplementary evidence for determining whether drought propagation time exhibits nonlinear sensitivity to important environmental factors. This framework provides a new perspective for assessing drought early warning needs. The identified sensitive intervals can help recognize environmental conditions associated with rapid changes in drought propagation time, providing additional information for drought risk assessment and region-specific early warning strategies.