Risk Assessment of Landslide Disasters Induced by Extreme Precipitation in the Western Henan Region

Abstract

Against the backdrop of frequent extreme meteorological events caused by global climate change, the mountains of Western Henan, with their complex geological structures and surface incisions, have become sensitive areas where landslide disasters threaten the safety barrier of the middle and upper reaches of the Yellow River. This study, from an emergency management perspective, integrates multi-source raster data and machine learning algorithms to set different return period scenarios for extreme precipitation. A four-dimensional risk assessment framework—comprising hazard, exposure, vulnerability, and disaster prevention capability—was constructed. Empirical analysis shows that landslide risk in Western Henan exhibits a significant spatial distribution pattern: high in the northwest and low in the southeast. As extreme precipitation increases, the risk of landslide disasters also rises. Lingbao City and Luoning County have formed significant high-exposure risk areas due to the high concentration of population and economy. Conversely, the weak disaster prevention resources in grassroots areas such as Lushi and Luanchuan are accompanied by high vulnerability. The study further finds that establishing a cross-departmental collaborative dynamic early warning mechanism and setting differentiated rainfall trigger thresholds can effectively guide emergency resources to transition from comprehensive prevention to precision control.