Occurrence probability assessment of earthquake-triggered landslides with Newmark displacement values and logistic regression: The Wenchuan earthquake, China

Abstract

The Newmark displacement model has been used to predict earthquake-triggered landslides. Logistic regression (LR) is also a common landslide hazard assessment method. We combined the Newmark displacement model and LR and applied them to Wenchuan County and Beichuan County in China, which were affected by the Ms. 8.0 Wenchuan earthquake on May 12th, 2008, to develop a mechanism-based landslide occurrence probability model and improve the predictive accuracy. A total of 1904 landslide sites in Wenchuan County and 3800 random non-landslide sites were selected as the training dataset. We applied the Newmark model and obtained the distribution of permanent displacement (Dn) for a 30×30m grid. Four factors (Dn, topographic relief, and distances to drainages and roads) were used as independent variables for LR. Then, a combined model was obtained, with an AUC (area under the curve) value of 0.797 for Wenchuan County. A total of 617 landslide sites and non-landslide sites in Beichuan County were used as a validation dataset with AUC=0.753. The proposed method may also be applied to earthquake-induced landslides in other regions.