Joint InSAR and discrete element numerical simulation method for landslide identification and monitoring: a case study of the Gongjue landslide, Jinsha River, China

The river-blocking landslide disasters are widely distributed in the mountainous areas of southwest China, characterized by high-elevation long-runout movements with significant destructive power. The identification and monitoring of high-elevation long-runout landslides, as well as the prediction of unstable landslide movements, hold great significance for regional disaster mitigation and prevention. In this study, we used interferometric synthetic aperture radar to identify and monitor potential landslides in the Gongjue segment of the Jinsha River Basin in China. The Sela landslide was selected for rainfall infiltration simulation, predict the entire process of landslide instability, and explore its failure characteristics from a dynamic perspective. The monitoring results revealed the presence of four typical landslides in Gongjue County, situated within the Jinsha River area, with slope deformation rates exceeding 17 cm/yr. The maximum observed slope deformation rate reaches 46 cm/yr. Decomposition results of the time-series deformation characteristics of the landslide feature measurement points show that rainfall was the primary factor influencing the periodic deformations of landslides. Simulation results indicated that rainfall promotes landslide deformation. Under the influence of rainfall, the movement speed of the landslide increases rapidly, and the front sliding body slides first, followed by the instability of the upper sliding body. This is consistent with the damage mode caused by a traction-type landslide. Subsequently, the particle movement speed maintains a short period of rapid sliding, gradually decreasing and eventually reaching a stable state. The results of this study provide an important reference for carrying out remote monitoring and risk prediction for high-elevation long-runout landslides.