Rainfall pattern conditions setup.

In the context of intensifying global environmental pressures, heavy rainfall in extreme climate regions significantly increases landslide risks, threatening societal stability and sustainable development. While research on rainfall-induced landslides is well-established, the deformation and instability mechanisms of landslides under complex rainfall patterns warrant further investigation. This study focuses on the Wangjiapo landslide in the Three Gorges Reservoir area. Through comprehensive field investigations, deformation monitoring, and rainfall data analysis, we systematically characterized the landslide’s deformation characteristics. Employing the similarity theory, a flume model experiment was designed to simulate four distinct rainfall patterns. Real-time monitoring of parameters, including slope displacement, pore water pressure, soil pressure, and moisture content, was conducted using multiple sensors, such as pull wire displacement sensors, pore water pressure sensors, and soil pressure sensors. The macroscopic deformation and internal stress variations of the landslide under varying rainfall conditions were thoroughly analyzed. Statistical processing of experimental data facilitated a comparative analysis with in-situ monitoring data, with further validation performed using Geo-Studio numerical simulation methods. Through these integrated approaches, this study elucidates the influence of different rain patterns on the deformation and failure mechanisms of accumulated landslides. Our findings highlight the critical role of rainfall intensity and rainfall time series in driving landslide deformation, identifying pore water pressure and shear strength variations as crucial factors inducing landslide instability. Furthermore, we delineate four distinct stages of the landslide failure process and characterize the temporal and spatial evolution of the instability mechanism, addressing a critical gap in understanding the deformation mechanisms of landslides under complex rainfall patterns. These results provide valuable insights for landslide monitoring and early warning systems and inform strategies for landslide disaster monitoring and prevention.