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Landslide risk assessment based on susceptibility and vulnerability

Author

Listed:
  • Jamal Mosaffaie

    (Soil Conservation and Watershed Management Research Institute (SCWMRI), Agricultural Research, Education and Extension Organization (AREEO))

  • Amin Salehpour Jam

    (Soil Conservation and Watershed Management Research Institute (SCWMRI), Agricultural Research, Education and Extension Organization (AREEO))

  • Faramarz Sarfaraz

    (Qazvin Agricultural and Natural Resources Research and Education Center)

Abstract

The aim of this study was to map the landslide risk at the Alamut watershed based on relative vulnerability and susceptibility. The potential of damage to the resources was considered landslide vulnerability. The fuzzy gamma operators were also used to assess landslide susceptibility. Thematic layers of 10 causal factors including slope, aspect, altitude, land use, lithology, distance to road, distance to stream, distance to fault, peak ground acceleration and mean annual precipitation were prepared. The landslide inventory map comprising 40 landslides covering 1417 hectares was partitioned into two subsets including 70% for training and 30% for testing. The Dr and Qs indices were applied to compare the validity of the landslide susceptibility maps. The spatial landslide risk was obtained by multiplying the landslide susceptibility and landslide vulnerability. The results show that the LSM derived by gamma of 0.95 has the most validity with Qs equal to 1.93. The ascending trend of the Dr index for low to high classes implies the correct classification of the LSM. The most important role in the occurrence of landslides has been related to lithology and land use factors. Although residential areas cover a small area of the watershed, 84.35% of the very high-risk class and 91.21% of the high-risk class are located in these areas. These results imply that in the Alamut watershed, the principles of land use planning have not been considered for landslide management. Therefore, the results of this study can be very useful for landslide risk management in the region.

Suggested Citation

  • Jamal Mosaffaie & Amin Salehpour Jam & Faramarz Sarfaraz, 2024. "Landslide risk assessment based on susceptibility and vulnerability," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(4), pages 9285-9303, April.
  • Handle: RePEc:spr:endesu:v:26:y:2024:i:4:d:10.1007_s10668-023-03093-4
    DOI: 10.1007/s10668-023-03093-4
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    References listed on IDEAS

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    1. Amin Salehpour Jam & Jamal Mosaffaie & Faramarz Sarfaraz & Samad Shadfar & Rouhangiz Akhtari, 2021. "GIS-based landslide susceptibility mapping using hybrid MCDM 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. 108(1), pages 1025-1046, August.
    2. Hamid Pourghasemi & Biswajeet Pradhan & Candan Gokceoglu, 2012. "Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran," 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. 63(2), pages 965-996, September.
    3. Ali Yalcin & Fikri Bulut, 2007. "Landslide susceptibility mapping using GIS and digital photogrammetric techniques: a case study from Ardesen (NE-Turkey)," 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. 41(1), pages 201-226, April.
    4. Jie Dou & Hiromitsu Yamagishi & Hamid Pourghasemi & Ali Yunus & Xuan Song & Yueren Xu & Zhongfan Zhu, 2015. "An integrated artificial neural network model for the landslide susceptibility assessment of Osado Island, Japan," 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. 78(3), pages 1749-1776, September.
    5. Shah Fahad & Faisal Alnori & Fang Su & Jian Deng, 2022. "Adoption of green innovation practices in SMEs sector: evidence from an emerging economy," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 35(1), pages 5486-5501, December.
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