An evaluation model for landslide and debris flow prediction using multiple hydrometeorological variables

Abstract

Landslide and debris flows are typically triggered by rainfall-related weather conditions, including short-duration storms and long-lasting rainfall. The critical precipitation of landslides and debris flow occurrence is different under various hydrometeorological conditions. In this study, the trigger sensitivities of different daily hydrological variables were assessed using 50 days-worth of recorded landslide and debris flows using the Soil and Water Assessment Tool model. The event days were divided into long-lasting rainfall trigger (LLR-trigger) event days and short-duration storm trigger (SDS-trigger) event days with six determinate criteria based on modeled wetness states. The landslide and debris flow prediction model was built using nine hydrometeorological variables, and the predictive performance was tested with simulated data from 2010 to 2012. The results suggest that, except for rainfall, historical hydrological variables and their development provide important information for triggering landslides and debris flows. The prediction model with an area under curve (AUC) value of 0.85 was able to capture most of the landslides and debris flows. The temporal distribution of the two triggering events predicted by the model was consistent with the annual precipitation distribution. In addition, the spatial variations of the specific trigger types could be attributed to the different land covers. Despite some uncertainty, this study provides an idea of improving the landslide and debris flow prediction model.