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| Earthquake-triggered landslide occurrence probability in strong seismically mountainous areas：a case study of Jiuzhaigou National Geopark |
| LUO Luguang，PEI Xiangjun，HUANG Runqiu |
| (State Key Laboratory of Geohazard Prevention and Geoenvironment Protection，Chengdu University of Technology，Chengdu，Sichuan 610059，China) |
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Abstract The hazard assessment of earthquake-triggered landslides(ETLs) is an extremely crucial component of risk assessment and geohazard prevention and reduction in strong seismic mountainous areas. 1 022 co-seismic landslide polygons in the Jiuzhaigou National Geopark triggered by the 2017 Jiuzhaigou Mw 6.5 earthquake were selected as the data sample and 1 234 slope units were divided by the r.slopeunits software as the modelling units. Selecting the peak ground acceleration(PGA) and 12 topographic，geological and hydrological parameters as the selected triggering factor and the conditioning factors of ETLs respectively，the mean landslide occurrence probability and uncertainty(95% credible interval) under eight key historical earthquake cases during the period between 1933 and 2017 were determined based on the Bayesian probability method and generalized additive model. The 10-fold cross-validation results of the initial model built with the landslides triggered by the 2017 earthquake show that the average AUCROC value，representing the spatial prediction capability of the model，arrives to as much as 0.93，indicating the reliability of the landslide occurrence probability simulation results corresponding to the other seven earthquake cases. PGA plays a dominant role leading to the occurrence of ETLs in the study area and the landslide probability has a clear positive correlation with PGA. The overall high landslide probability area is distributed in a long belt shape along the valleys. This paper provides a new method and approach for comprehensive hazard assessment of ETLs and the results can be reference for the prediction of the probability of future ETLs and quick assessment after earthquake for the study area.
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2020, Vol. 39 
