Construction of a Joint Newmark–Runout Model for Seismic Landslide Risk Identification: A Case Study in the Eastern Tibetan Plateau

The key to seismic landslide risk identification resides in the accurate evaluation of seismic landslide hazards. The traditional evaluation models for seismic landslide hazard seldom consider the landslide dynamic runout process, leading to an underestimation of seismic landslide hazard. Therefore, a joint Newmark–Runout model based on landslide dynamic runout is proposed. According to the evaluation results of static seismic landslide hazard, the landslide source points can be extracted, and the landslide dynamic runout process is simulated to obtain the dynamic seismic landslide hazard. Finally, the static and dynamic seismic landslide hazards are fused to obtain an optimized seismic landslide hazard. In September 2022, a strong Ms6.8 earthquake occurred in the eastern Tibetan Plateau, triggering thousands of landslides. Taking the 2022 Luding earthquake-induced landslide as a sample, the function relationship between seismic slope displacement and landslide occurrence probability is statistically modeled, which partly improves the traditional Newmark model. The optimized seismic landslide hazard evaluation of the Luding earthquake area is conducted, and then, the seismic landslide risk identification is completed by taking roads and buildings as hazard-affected bodies. The results show that the length of the roads facing very high and high seismic landslide risks are 3.36 km and 15.66 km, respectively, and the buildings on the Moxi platform near the epicenter are less vulnerable to seismic landslides. The research findings can furnish critical scientific and technological support for swift earthquake relief operations.

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Publication Details

Journal
Land
Published
2024-11-04
DOI
https://doi.org/10.3390/land13111832
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
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article

Construction of a Joint Newmark–Runout Model for Seismic Landslide Risk Identification: A Case Study in the Eastern Tibetan Plateau

Ximao Mai, Zhihua Yang, Yuming Wu, Changbao Guo
Land
Landslides and related hazards
article

Construction of a Joint Newmark–Runout Model for Seismic Landslide Risk Identification: A Case Study in the Eastern Tibetan Plateau

Ximao Mai, Zhihua Yang, Yuming Wu, Changbao Guo
article en

Abstract

The key to seismic landslide risk identification resides in the accurate evaluation of seismic landslide hazards. The traditional evaluation models for seismic landslide hazard seldom consider the landslide dynamic runout process, leading to an underestimation of seismic landslide hazard. Therefore, a joint Newmark–Runout model based on landslide dynamic runout is proposed. According to the evaluation results of static seismic landslide hazard, the landslide source points can be extracted, and the landslide dynamic runout process is simulated to obtain the dynamic seismic landslide hazard. Finally, the static and dynamic seismic landslide hazards are fused to obtain an optimized seismic landslide hazard. In September 2022, a strong Ms6.8 earthquake occurred in the eastern Tibetan Plateau, triggering thousands of landslides. Taking the 2022 Luding earthquake-induced landslide as a sample, the function relationship between seismic slope displacement and landslide occurrence probability is statistically modeled, which partly improves the traditional Newmark model. The optimized seismic landslide hazard evaluation of the Luding earthquake area is conducted, and then, the seismic landslide risk identification is completed by taking roads and buildings as hazard-affected bodies. The results show that the length of the roads facing very high and high seismic landslide risks are 3.36 km and 15.66 km, respectively, and the buildings on the Moxi platform near the epicenter are less vulnerable to seismic landslides. The research findings can furnish critical scientific and technological support for swift earthquake relief operations.

LandVol. 13(11)
Chinese Academy of Sciences (CN), Chinese Academy of Geological Sciences (CN), China University of Geosciences (CN), Institute of Geographic Sciences and Natural Resources Research (CN)
National Natural Science Foundation of China
Sustainable cities and communities
Openalex Percentile: Top 71%
Landslides and related hazards
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