Explainable flash flood susceptibility mapping on the Tibetan Plateau

Flash flood hazards on the Qinghai–Tibet Plateau are surging under rapid warming and humidification, driving glacier retreat, lake outbursts, and extreme precipitation that imperil water security across Asia. To address the limitations of studies relying primarily on historical observations and lacking quantitative insights into disaster mechanisms and dynamic prediction, this study integrates a logistic regression model with the geographical detector approach. Using multi-source flash flood records from 1950 to 2023 and 12 environmental variables (elevation, slope, precipitation, river network density, land use, etc.), the analysis quantifies the interactive effects of key drivers and uncovers the nonlinear mechanisms governing flash flood sensitivity. The results indicate that: (1) the model demonstrates strong predictive capability, achieving 78% accuracy and an AUC of 0.87; (2) mean annual precipitation is the dominant factor, while its interaction with river proximity enhances the explanatory power of flash flood disasters by 37%, indicating a nonlinear reinforcing effect; and (3) high-resolution sensitivity mapping for 2023 reveals that areas of high and very high flash flood sensitivity are concentrated in the South Tibet Valley and Hengduan Mountains, aligning with regions of glacial lake expansion and frequent extreme precipitation. In contrast, medium- and low-sensitivity areas are widely distributed across the North Tibet Plateau, where arid geomorphology and sparse river networks exert dominant control. This spatial pattern corresponds closely with regional topographic, climatic, and hydrological processes. The study offers a transferable approach for dynamic flash flood risk early warning, precise disaster zoning, and improved resilience of transboundary basins on the Qinghai–Tibet Plateau.