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Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China

Author

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  • Zhiye Wang

    (College of Environmental Studies, China University of Geosciences, Wuhan 430074, China)

  • Chuanming Ma

    (College of Environmental Studies, China University of Geosciences, Wuhan 430074, China)

  • Yang Qiu

    (College of Environmental Studies, China University of Geosciences, Wuhan 430074, China)

  • Hanxiang Xiong

    (College of Environmental Studies, China University of Geosciences, Wuhan 430074, China)

  • Minghong Li

    (College of Environmental Studies, China University of Geosciences, Wuhan 430074, China)

Abstract

At present, landslide susceptibility assessment (LSA) based on the characteristics of landslides in different areas is an effective prevention measure for landslide management. In Enshi County, China, the landslides are mainly triggered by high-intensity rainfall, which causes a large number of casualties and economic losses every year. In order to effectively control the landslide occurrence in Enshi County and mitigate the damages caused by the landslide. In this study, eight indicators were selected as assessment indicators for LSA in Enshi County. The analytic hierarchy process (AHP) model, information value (IV) model and analytic hierarchy process-information value (AHP-IV) model were, respectively, applied to assess the landslide distribution of landslides in the rainy season (RS) and non-rainy season (NRS). Based on the three models, the study area was classified into five levels of landslide susceptibility, including very high susceptibility, high susceptibility, medium susceptibility, low susceptibility, and very low susceptibility. The receiver operating characteristic (ROC) curve was applied to verify the model accuracy. The results showed that the AHP-IV model (ROC = 0.7716) was more suitable in RS, and the IV model (ROC = 0.8237) was the most appropriate model in NRS. Finally, combined with the results of landslide susceptibility in RS and NRS, an integrated landslide susceptibility map was proposed, involving year-round high susceptibility, RS high susceptibility, NRS high susceptibility and year-round low susceptibility. The integrated landslide susceptibility results provide a more detailed division in terms of the different time periods in a year, which is beneficial for the government to efficiently allocate landslide management funds and propose effective landslide management strategies. Additionally, the focused arrangement of monitoring works in landslide-prone areas enable collect landslide information efficiently, which is helpful for the subsequent landslide preventive management.

Suggested Citation

  • Zhiye Wang & Chuanming Ma & Yang Qiu & Hanxiang Xiong & Minghong Li, 2022. "Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China," IJERPH, MDPI, vol. 19(15), pages 1-22, August.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:15:p:9412-:d:877482
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    References listed on IDEAS

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    1. Yue Wang & Deliang Sun & Haijia Wen & Hong Zhang & Fengtai Zhang, 2020. "Comparison of Random Forest Model and Frequency Ratio Model for Landslide Susceptibility Mapping (LSM) in Yunyang County (Chongqing, China)," IJERPH, MDPI, vol. 17(12), pages 1-39, June.
    2. Shuai Li & Zhongyun Ni & Yinbing Zhao & Wei Hu & Zhenrui Long & Haiyu Ma & Guoli Zhou & Yuhao Luo & Chuntao Geng, 2022. "Susceptibility Analysis of Geohazards in the Longmen Mountain Region after the Wenchuan Earthquake," IJERPH, MDPI, vol. 19(6), pages 1-30, March.
    3. S. Modugno & S. C. M. Johnson & P. Borrelli & E. Alam & N. Bezak & H. Balzter, 2022. "Analysis of human exposure to landslides with a GIS multiscale approach," 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. 112(1), pages 387-412, May.
    4. Fasheng Miao & Yiping Wu & Linwei Li & Kang Liao & Longfei Zhang, 2019. "Risk assessment of snowmelt-induced landslides based on GIS and an effective snowmelt model," 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. 97(3), pages 1151-1173, July.
    5. Rachida Senouci & Nasr-Eddine Taibi & Ana Cláudia Teodoro & Lia Duarte & Hamidi Mansour & Rabia Yahia Meddah, 2021. "GIS-Based Expert Knowledge for Landslide Susceptibility Mapping (LSM): Case of Mostaganem Coast District, West of Algeria," Sustainability, MDPI, vol. 13(2), pages 1-21, January.
    6. Tirthankar Basu & Swades Pal, 2020. "A GIS-based factor clustering and landslide susceptibility analysis using AHP for Gish River Basin, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(5), pages 4787-4819, June.
    7. Anna Roccati & Guido Paliaga & Fabio Luino & Francesco Faccini & Laura Turconi, 2021. "GIS-Based Landslide Susceptibility Mapping for Land Use Planning and Risk Assessment," Land, MDPI, vol. 10(2), pages 1-28, February.
    8. Xiang Duan & Tian-shun Hou & Xiao-dong Jiang, 2021. "Study on stability of exit slope of Chenjiapo tunnel under extreme rainstorm conditions," 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. 107(2), pages 1387-1411, June.
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