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Susceptibility analysis of shallow landslides source areas using physically based models

Author

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  • Giuseppe Sorbino
  • Carlo Sica
  • Leonardo Cascini

Abstract

Rainfall-induced shallow landslides of the flow-type involve different soils, and they often cause huge social and economical disasters, posing threat to life and livelihood all over the world. Due to the frequent large extension of the rainfall events, these landslides can be triggered over large areas (up to tens of square kilometres), and their source areas can be analysed with the aid of distributed, physically based models. Despite the high potential, such models show some limitations related to the adopted simplifying assumptions, the quantity and quality of required data, as well as the use of a quantitative interpretation of the results. A relevant example is provided in this paper referring to catastrophic phenomena involving volcaniclastic soils that frequently occur in southern Italy. Particularly, three physically based models (SHALSTAB, TRIGRS and TRIGRS-unsaturated) are used for the analysis of the source areas of huge rainfall-induced shallow landslides occurred in May 1998 inside an area of about 60 km 2 . The application is based on an extensive data set of topographical, geomorphological and hydrogeological features of the affected area, as well as on both stratigraphical settings and mechanical properties of the involved soils. The results obtained from the three models are compared by introducing two indexes aimed at quantifying the “success” and the “error” provided by each model in simulating observed source areas. Advantages and limitations of the adopted models are then discussed for their use in forecasting the rainfall-induced source areas of shallow landslides over large areas. Copyright Springer Science+Business Media B.V. 2010

Suggested Citation

  • Giuseppe Sorbino & Carlo Sica & Leonardo Cascini, 2010. "Susceptibility analysis of shallow landslides source areas using physically based models," 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. 53(2), pages 313-332, May.
  • Handle: RePEc:spr:nathaz:v:53:y:2010:i:2:p:313-332
    DOI: 10.1007/s11069-009-9431-y
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    Citations

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    Cited by:

    1. Cheng Lian & Zhigang Zeng & Wei Yao & Huiming Tang, 2013. "Displacement prediction model of landslide based on a modified ensemble empirical mode decomposition and extreme learning machine," 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. 66(2), pages 759-771, March.
    2. Dimitrios Myronidis & Charalambos Papageorgiou & Stavros Theophanous, 2016. "Landslide susceptibility mapping based on landslide history and analytic hierarchy process (AHP)," 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. 81(1), pages 245-263, March.
    3. Sebastiano Perriello Zampelli & Eliana Bellucci Sessa & Marco Cavallaro, 2012. "Application of a GIS-aided method for the assessment of volcaniclastic soil sliding susceptibility to sample areas of Campania (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 155-168, March.
    4. Yinping Nie & Xiuzhen Li & Wendy Zhou & Ruichi Xu, 2021. "Dynamic hazard assessment of group-occurring debris flows based on a coupled 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. 106(3), pages 2635-2661, April.
    5. Hyuck-Jin Park & Kang-Min Kim & In-Tak Hwang & Jung-Hyun Lee, 2022. "Regional Landslide Hazard Assessment Using Extreme Value Analysis and a Probabilistic Physically Based Approach," Sustainability, MDPI, vol. 14(5), pages 1-17, February.
    6. Dimitrios Myronidis & Charalambos Papageorgiou & Stavros Theophanous, 2016. "Landslide susceptibility mapping based on landslide history and analytic hierarchy process (AHP)," 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. 81(1), pages 245-263, March.
    7. D. W. Park & S. R. Lee & N. N. Vasu & S. H. Kang & J. Y. Park, 2016. "Coupled model for simulation of landslides and debris flows at local scale," 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. 81(3), pages 1653-1682, April.
    8. E. Piegari & R. Di Maio, 2014. "Simulations of landslide hazard scenarios by a geophysical safety factor," 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. 73(1), pages 63-76, August.
    9. Marco Materazzi & Margherita Bufalini & Matteo Gentilucci & Gilberto Pambianchi & Domenico Aringoli & Piero Farabollini, 2021. "Landslide Hazard Assessment in a Monoclinal Setting (Central Italy): Numerical vs. Geomorphological Approach," Land, MDPI, vol. 10(6), pages 1-22, June.
    10. Kyungjin An & Suyeon Kim & Taebyeong Chae & Daeryong Park, 2018. "Developing an Accessible Landslide Susceptibility Model Using Open-Source Resources," Sustainability, MDPI, vol. 10(2), pages 1-13, January.
    11. Lorella Montrasio & Roberto Valentino & Angela Corina & Lauro Rossi & Roberto Rudari, 2014. "A prototype system for space–time assessment of rainfall-induced shallow landslides in 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. 74(2), pages 1263-1290, November.

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