Comment on egusphere-2022-772

Abstract

To enhance the timeliness and accuracy of spatial prediction of co-seismic landslides, we propose an improved three-stage spatial prediction strategy and developed a corresponding hazard assessment software named Mat.LShazard V1.0. Based on this software, we evaluate the applicability of this improved spatial prediction strategy in six earthquake events that have occurred near the Sichuan Yunnan region including the Wenchuan, Ludian, Lushan, Jiuzhaigou, Minxian and Yushu earthquakes. The results indicate that in the first stage (within a half-hour of the earthquake), except for the 2013 Minxian earthquake, the AUC values of the modelling performance in other five events are above 0.8. Among them, the AUC value of the Wenchuan earthquake is the highest, reaching 0.947. The prediction results in the first stage can meet the requirements of emergency rescue with immediately obtaining the overall predicted information of the possible coseismic landslide locations in the quake-affected area. In the second and third stages (Within 12 hours of the quake), with the improvement of landslide data quality, the prediction ability of the model based on the entire landslide database is gradually improved. Based on the entire landslide database, the AUC value of the six events exceeds 0.9, indicating a very high prediction accuracy. Whether in the second or third stage (After 3 days of the seismic event), the predicted landslide area (Ap) is in good agreement with the observed landslide area (Ao). However, based on incomplete landslide data in the meizoseismal area, Ap is much smaller than Ao. When the prediction model based on complete landslide data is built, Ap is nearly identical to Ao. This study provides a new application tool for coseismic landslide disaster prevention and mitigation in different stages of emergency rescue, temporary resettlement, and latereconstruction after a major earthquake.