Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale

Rainfall-induced landslides represent an important threat in mountainous areas. Therefore, a physically-based model called Fast Shallow Landslide Assessment Model (FSLAM) was developed to calculate large areas (>100 km(2)) with a high-resolution topography in a very short computational time. FSLAM applies a simplified hydrological model and the infinite slope theory, while the two most sensitive soil properties regarding slope stability (cohesion and friction angle) can be stochastically included. The model has five necessary input raster files including information of soil properties, vegetation, elevation and rainfall. The principal output is the probability of failure (PoF) map. The Principality of Andorra was selected as case study, where FSLAM was successfully applied and validated using the existing landslide inventory. The PoF raster file of Andorra (including 19 million cells) was calculated in only 2 min. Therefore, an accurate calibration of the input parameters was easy, which strongly improved the final outcomes.

Automated summary

The Fast Shallow Landslide Assessment Model (FSLAM) is able to calculate rainfall-induced landslide probability maps for large areas in a short amount of time. By incorporating soil properties, vegetation, elevation, and rainfall information, the model can significantly improve prediction accuracy.