Predictive model of regional coseismic landslides' permanent displacement considering uncertainty.

Coseismic landslides are common secondary earthquake geohazards in meizoseismal areas. Newmark sliding block permanent displacement method has been widely adopted to develop regional coseismic landslide hazard maps. However, uncertainties from the slope parameters (e.g., cohesion, pore water pressure, and block thickness) are not commonly considered in the ground displacement predictions. This study proposes a novel framework that consists of two uncertainty assessment methods of Monte Carlo and logic tree simulations (MCS and LTS) with seven different displacement regression functions to predict the regional coseismic landslides' permanent displacement. Compared with the existing methods, the proposed framework is argument-driven, avoiding huge number of repetitive simulations. The Jiuzhaigou earthquake, in China, is considered as an illustrative example to compare the performance of the framework with considered regression functions. The corresponding results show that using LTS, with a certain regression function, leads to better predictions compared to using MCS. It is demonstrated that the proposed framework can provide a meaningful measure for making informed decisions to diminish the potential risk of earthquake induced landslides, and/or generating emergency strategies to mitigate post-earthquake consequences. It should be noted that the application of the proposed method for deposits where the soil strength parameter values do not fit the normal distribution may be limited as only normal distribution for soil strengths is considered in this study. [ABSTRACT FROM AUTHOR]