Prediction of Rainfall-Induced Landslide-Mudslide Hazard Chain Using Coupled TRIGRS and RAMMS Models

This study develops an effective prediction method for rainfall-induced landslide-mudslide disaster chains by integrating the TRIGRS landslide prediction model with the RAMMS mudslide simulation model. Using a mountainous area prone to such disasters as a case study, it first applies the TRIGRS model to assess slope stability under rainfall conditions to identify potential landslide hazards. The identified landslide predictions serve as input for the RAMMS model to simulate the subsequent mudslide processes, predicting their paths, velocities, impact forces, and accumulation areas. Through iterative optimization of this coupled model, the system achieves comprehensive prediction of the disaster chain. Case analysis results demonstrate high accuracy in predicting both the location and scale of landslides and the characteristics of triggered mudslides, validating the model's effectiveness and providing a robust scientific basis for early warning and disaster mitigation planning.