Deformation Mechanisms and Rainfall Lag Effects of Deep-Seated Ancient Landslides in High-Mountain Regions: A Case Study of the Zhongxinrong Landslide, Upper Jinsha River

In high-mountain canyon regions, many settlements are located on large, deep-seated ancient landslides. The deformation characteristics, triggering mechanisms, and long-term developmental trends of these landslides significantly impact the safety and stability of these communities. However, the deformation mechanism under the influence of human engineering activities remains unclear. SBAS-InSAR (Small Baseline Subset-Interferometric Synthetic Aperture Radar) technology, UAV LiDAR, and field surveys were utilized in this study to identify a large ancient landslide in the upper Jinsha River Basin: the Zhongxinrong landslide. It extends approximately 1220 m in length, with a vertical displacement of around 552 m. The average thickness of the landslide mass ranges from 15.0 to 35.0 m, and the total volume is estimated to be between 1.48 × 107 m3 and 3.46 × 107 m3. The deformation of the Zhongxinrong landslide is primarily driven by a combination of natural and anthropogenic factors, leading to the formation of two distinct accumulation bodies, each exhibiting unique deformation characteristics. Accumulation Body II-1 is predominantly influenced by rainfall and road operation, resulting in significant deformation in the upper part of the landslide. In contrast, II-2 is mainly affected by rainfall and river erosion at the front edge, causing creeping tensile deformation at the toe. Detailed analysis reveals a marked acceleration in deformation following rainfall events when the cumulative rainfall over a 15-day period exceeds 120 mm. The lag time between peak rainfall and landslide displacement ranges from 2 to 28 days. Furthermore, deformation in the high-elevation accumulation area consistently exhibits a slower lag response compared to the tensile deformation area at lower zones. These findings highlight the importance of both natural and anthropogenic factors in landslide risk assessment and provide valuable insights for landslide prevention strategies, particularly in regions with similar geological and socio-environmental conditions.