Evaluation and Sensitivity Analysis of An Ensemble-based Coupled Flash Flood and Landslide Modelling System Using Remote Sensing Forcing

Abstract:

Heavy rainfall-triggered landslides are often associated with flood events and cause additional loss of life and property. It is pertinent to build a robust coupled flash flood and landslide disaster early warning system for disaster preparedness and hazard management based. In this study, we built an ensemble-based coupled flash flood and landslide disaster early warning system, which is aimed for operational use by the US National Weather Service, by integrating the Coupled Routing and Excess STorage (CREST) model and Sacramento Soil Moisture Accounting Model (SAC-SMA) with the physically based SLope-Infiltration-Distributed Equilibrium (SLIDE) landslide prediction model. We further evaluated this ensemble-based prototype warning system by conducting multi-year simulations driven by the Multi-Radar Multi-Sensor (MRMS) rainfall estimates in North Carolina and Oregon. We comprehensively evaluated the predictive capabilities of this system against observed and reported flood and landslides events. We then evaluated the sensitivity of the coupled system to the simulated hydrological processes. Our results show that the system is generally capable of making accurate predictions of flash flood and landslide events in terms of their locations and time of occurrence. The occurrence of predicted landslides show high sensitivity to total infiltration and soil water content, highlighting the importance of accurately simulating the hydrological processes on the accurate forecasting of rainfall triggered landslide events.