Physical-based rainfall-triggered shallow landslide forecasting

Abstract

This study demonstrates the applications of two physical-based early warning methods for rainfall-induced shallow landslide and compare their relative performance. One method is rainfall threshold-based method and the other method is by real-time simulation. The former establishes landslide threshold in advance using 50 historical rainfall events, in conjunction with physical-based rainfall-triggered shallow landslide model, to evaluate the stability of a concerned slope. Quantitative precipitation estimation (QPE) for nowcast is used in the rainfall threshold-based method for landslide predictions. The latter method also applies rainfall-triggered landslide model in real-time simulation by feeding QPE and quantitative precipitation forecast (QPF) of specified lead-time. Both methods are integrated into an early warning system (e.g. Delft-FEWS) for real-time nowcast and/or forecast purposes. The two shallow landslide early warning methods are applied to a slope in the vicinity of a highway section in Taiwan. Comparisons between the two methods are made to evaluate their performance using rainfall data from three past typhoon events. Despite of some discrepancies found in the results, both methods can predict landslide quite consistently. Without sufficient number of actual landslide records for model validation, the true accuracy of both landslide early warning methods cannot be assessed. However, the consistency of predicted landslide occurrence times during three historical typhoon events in the case study indicated that they could be viable for providing good supportive information for decision-making in landslide hazard mitigation.