Using ensemble quantitative precipitation forecast for rainfall-induced shallow landslide predictions

Abstract

Heavy rainfall brought by typhoons has been recognised as a major trigger of landslides in Taiwan. On average, 3.75 typhoons strike the island every year, and cause large amounts of shallow landslides and debris flow in mountainous region. Because landslide occurrence strongly corresponds to the storm dynamics, a reliable typhoon forecast is therefore essential to landslide hazard management in Taiwan. Given early warnings with sufficient lead time, rainfall-induced shallow landslide forecasting can help people prepare disaster prevention measures. To account for inherent weather uncertainties, this study adopted an ensemble forecasting model for executing precipitation forecasts, instead of using a single-model output. A shallow landslide prediction model based on the infinite slope model and TOPMODEL was developed. Considering the detailed topographic characteristics of a catchment, the proposed model can estimate the change in saturated water table during rainstorms and then link with the slope-instability analysis to clarify whether shallow landslides can occur in the catchment. Two areas vulnerable to landslide in Taiwan were collected to test the applicability of the model for landslide prediction. Hydrological data and landslide records derived from 15 typhoons events were used to verify the applicability of the model. Three indices, namely the probability of detection (POD), false alarm ratio (FAR), and threat score (TS), were used to assess the performance of the model. The results indicated that for landslide prediction through the proposed model, the POD was higher than 0.73, FAR was lower than 0.33, and TS was higher than 0.53. The proposed model has potential for application in landslide early warning systems to reduce loss of life and property.