Rainfall-Earthquake-Induced Landslide Hazard Prediction by Monte Carlo Simulation: A Case Study of MT. Umyeon in Korea

Abstract

Rainfall and earthquakes are two major triggers for landslides. To assess annual rainfall-earthquake-induced landslide hazards, an ensemble model containing three modules: an uncertainty-analysis module, a simulation module and an output module was proposed. In the uncertainty-analysis module, the input parameters including the topography (slope, curvature), soil depth, rainfall, peak ground acceleration and soil physical properties were considered probabilistic rather than taking specific values. A rainfall-earthquake-induced landslide hazard assessment was carried out in the simulation module, which used two separate methods: a pseudo-static model and a Newmark displacement model based on probabilistic data, which were prepared in the uncertainty-analysis module using the Monte Carlo simulation technique. In the output module, the two landslide hazard evaluations were combined into one map. The combined landslide hazard provides a range of annual probabilities of landslide occurrence corresponding to specific confidence levels. The proposed model can be used for reliable forecasting at specific confidence levels.