Oral Presentation

Earthquake-induced landslides represent a significant seismic hazard, with some earthquake events generating thousands of landslides that affect massive areas. The considerable number and size of landslides induced by earthquakes has the potential to inundate entire towns, disrupt critical lifelines (e.g., highways, pipelines, rail lines), and create flash flooding hazards due to landslide dams, making a region uninhabitable for many months after an earthquake. Proper planning/mitigation requires accurate evaluation of the potential for seismic landslides at a regional scale. This presentation will describe recent research aimed at improving regional assessments of earthquake-induced landslides. Critical to the assessment is the detailed characterization of the subsurface at a regional scale for use in the numerical analyses. We utilize regional-scale geologic, shear strength, and groundwater table data, quantify the uncertainties associated with these data, and provide probabilistic assessments of the landslide hazard based on a logic tree approach. Current approaches are founded on the physically-based sliding block model, which has been shown to adequately predict the occurrence of earthquake-induced landslides, but we will outline future advancements that include more sophisticated numerical simulations that can be integrated with machine learning approaches to better assess landslide size and landslide runout.