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,...

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Main Authors: Zhihua Yang, Yuming Wu, Changbao Guo, Ximao Mai
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Land
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Online Access:https://www.mdpi.com/2073-445X/13/11/1832
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author Zhihua Yang
Yuming Wu
Changbao Guo
Ximao Mai
author_facet Zhihua Yang
Yuming Wu
Changbao Guo
Ximao Mai
author_sort Zhihua Yang
collection DOAJ
description 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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spelling doaj-art-bffb79e801754ace853c540b78042a5b2024-11-26T18:09:25ZengMDPI AGLand2073-445X2024-11-011311183210.3390/land13111832Construction of a Joint Newmark–Runout Model for Seismic Landslide Risk Identification: A Case Study in the Eastern Tibetan PlateauZhihua Yang0Yuming Wu1Changbao Guo2Ximao Mai3Institute of Geomechanics, Chinese Academy of Geological Sciences, Beijing 100081, ChinaInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaInstitute of Geomechanics, Chinese Academy of Geological Sciences, Beijing 100081, ChinaInstitute of Geomechanics, Chinese Academy of Geological Sciences, Beijing 100081, ChinaThe 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.https://www.mdpi.com/2073-445X/13/11/1832seismic landslidelandslide hazardlandslide riskjoint Newmark–Runout modelLuding earthquake
spellingShingle Zhihua Yang
Yuming Wu
Changbao Guo
Ximao Mai
Construction of a Joint Newmark–Runout Model for Seismic Landslide Risk Identification: A Case Study in the Eastern Tibetan Plateau
Land
seismic landslide
landslide hazard
landslide risk
joint Newmark–Runout model
Luding earthquake
title Construction of a Joint Newmark–Runout Model for Seismic Landslide Risk Identification: A Case Study in the Eastern Tibetan Plateau
title_full Construction of a Joint Newmark–Runout Model for Seismic Landslide Risk Identification: A Case Study in the Eastern Tibetan Plateau
title_fullStr Construction of a Joint Newmark–Runout Model for Seismic Landslide Risk Identification: A Case Study in the Eastern Tibetan Plateau
title_full_unstemmed Construction of a Joint Newmark–Runout Model for Seismic Landslide Risk Identification: A Case Study in the Eastern Tibetan Plateau
title_short Construction of a Joint Newmark–Runout Model for Seismic Landslide Risk Identification: A Case Study in the Eastern Tibetan Plateau
title_sort construction of a joint newmark runout model for seismic landslide risk identification a case study in the eastern tibetan plateau
topic seismic landslide
landslide hazard
landslide risk
joint Newmark–Runout model
Luding earthquake
url https://www.mdpi.com/2073-445X/13/11/1832
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