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