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Risk Assessment of Earthquake–Landslide Hazard Chain Based on CF-SVM and Newmark Model—Using Changbai Mountain as an Example

Author

Listed:
  • Kai Ke

    (College of Jilin Emergency Management, Changchun Institute of Technology, Changchun 130012, China)

  • Yichen Zhang

    (College of Jilin Emergency Management, Changchun Institute of Technology, Changchun 130012, China)

  • Jiquan Zhang

    (School of Environment, Northeast Normal University, Changchun 130117, China)

  • Yanan Chen

    (College of Jilin Emergency Management, Changchun Institute of Technology, Changchun 130012, China)

  • Chenyang Wu

    (College of Surveying and Mapping Engineering, Changchun Institute of Technology, Changchun 130021, China)

  • Zuoquan Nie

    (College of Jilin Emergency Management, Changchun Institute of Technology, Changchun 130012, China)

  • Junnan Wu

    (College of Jilin Emergency Management, Changchun Institute of Technology, Changchun 130012, China)

Abstract

Changbai Mountain is an important part of the development and opening pilot area of Changjitu. It is the birthplace of Songhua River, Yalu River, and Tumen River, and is known as the source of the three rivers. Millions of people live in the basin. A volcanic eruption accompanied by earthquakes would lead to a large number of landslides, debris flows, and show a chain effect, the formation of a secondary geological disaster chain, which is a serious threat to people’s lives and property safety. This paper selected indexes from three aspects: the hazard of earthquake-induced geological disaster chain, the exposure and vulnerability of disaster-bearing bodies, and the risk assessment of earthquake-induced geological disaster chain. The sensitivity values of each influence factor were calculated by the certainty factor (CF) using the support vector machine, and then, the susceptibility assessment was obtained. The cumulative displacement calculated by the Newmark model represented the potential risk intensity. We considered the Changbai Mountain volcanic earthquake–landslide disaster chain as an example. The results of risk assessment showed that the extremely high and high risk areas were mainly located within the 12 km radius of Tianchi Lake, and the other areas in the study area were mainly associated with very low to low risk values. The verification results showed that the receiver operating characteristic (ROC) curve area was 0.8373, indicating that the method was very effective in the identification and assessment of seismic hazard chain risk. In these high-risk areas, relevant countermeasures should be formulated to prevent the risk of geological disasters, strengthen the implementation of regional disaster prevention and reduction work, and ensure the safety of residents’ lives and property.

Suggested Citation

  • Kai Ke & Yichen Zhang & Jiquan Zhang & Yanan Chen & Chenyang Wu & Zuoquan Nie & Junnan Wu, 2023. "Risk Assessment of Earthquake–Landslide Hazard Chain Based on CF-SVM and Newmark Model—Using Changbai Mountain as an Example," Land, MDPI, vol. 12(3), pages 1-20, March.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:3:p:696-:d:1099055
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    References listed on IDEAS

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    1. Majid Mohammady & Hamid Reza Pourghasemi & Mojtaba Amiri, 2019. "Assessment of land subsidence susceptibility in Semnan plain (Iran): a comparison of support vector machine and weights of evidence data mining algorithms," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(2), pages 951-971, November.
    2. V. Del Gaudio & P. Pierri & G. Calcagnile, 2012. "Analysis of seismic hazard in landslide-prone regions: criteria and example for an area of Daunia (southern Italy)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 61(1), pages 203-215, March.
    3. Lina Han & Qing Ma & Feng Zhang & Yichen Zhang & Jiquan Zhang & Yongbin Bao & Jing Zhao, 2019. "Risk Assessment of An Earthquake-Collapse-Landslide Disaster Chain by Bayesian Network and Newmark Models," IJERPH, MDPI, vol. 16(18), pages 1-17, September.
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    5. Zhi-hua Yang & Heng-xing Lan & Xing Gao & Lang-ping Li & Yun-shan Meng & Yu-ming Wu, 2015. "Urgent landslide susceptibility assessment in the 2013 Lushan earthquake-impacted area, Sichuan Province, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(3), pages 2467-2487, February.
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    Cited by:

    1. Peng Yu & Jie Dong & Hongwei Hao & Yongjian Xie & Hui Zhang & Jianshou Wang & Chenghao Zhu & Yong Guan & Haochen Yu, 2023. "Risk Assessment and Prevention Planning for Collapse Geological Hazards Considering Extreme Rainfall—A Case Study of Laoshan District in Eastern China," Land, MDPI, vol. 12(8), pages 1-22, August.
    2. Xuedong Zhang & Haoyun Xie & Zidong Xu & Zhaowen Li & Bo Chen, 2024. "Evaluating landslide susceptibility: an AHP method-based approach enhanced with optimized random forest modeling," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(9), pages 8153-8207, July.
    3. Zhihua Yang & Yuming Wu & Changbao Guo & Ximao Mai, 2024. "Construction of a Joint Newmark–Runout Model for Seismic Landslide Risk Identification: A Case Study in the Eastern Tibetan Plateau," Land, MDPI, vol. 13(11), pages 1-20, November.

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