With the acceleration of global climate change, the evolution of geographical environments has become increasingly complex. This study explores the mechanisms through which topography-climate coupling influences extreme precipitation events in China. Using integrated geographic datasets on precipitation, temperature, and land use/cover, combined with GIS technology and a random forest regression (RFR) model, the spatiotemporal evolution from 1990 to 2020 is analysed. Unlike previous studies that only focused on a single factor or pairwise correlations, this study innovatively quantifies the nonlinear coupling effects of terrain features, climate variables, and land use/cover change (LUCC) on extreme precipitation’s spatial distribution and intensity. The results show that topographic factors, including elevation, slope, and terrain variation, significantly impact the spatial distribution and intensity of rainfall. Extreme precipitation events are spatially clustered, mainly in the southern Qinghai-Tibet Plateau, the southeastern coastal region, and the hilly areas of the middle and lower Yangtze River. These high-risk areas are characterized by complex terrain, steep slopes, and high temperatures. Moreover, the occurrence of extreme rainfall is found to be driven by multi-factor interactions rather than by a single factor. The prediction model demonstrates high accuracy (R2 = 0.85, MSE = 0.00023), providing valuable insights for disaster prevention and geographical environmental research.
Zhou et al. (Sun,) studied this question.