IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v26y2024i4d10.1007_s10668-023-03093-4.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-023-03093-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10668-023-03093-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    4. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jonmenjoy Barman & Brototi Biswas & K. Srinivasa Rao, 2024. "A hybrid integration of analytical hierarchy process (AHP) and the multiobjective optimization on the basis of ratio analysis (MOORA) for landslide susceptibility zonation of Aizawl, India," 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 8571-8596, July.
    2. Gökhan Demir & Mustafa Aytekin & Aykut Akgün & Sabriye İkizler & Orhan Tatar, 2013. "A comparison of landslide susceptibility mapping of the eastern part of the North Anatolian Fault Zone (Turkey) by likelihood-frequency ratio and analytic hierarchy process methods," 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. 65(3), pages 1481-1506, February.
    3. Viet-Ha Nhu & Ataollah Shirzadi & Himan Shahabi & Sushant K. Singh & Nadhir Al-Ansari & John J. Clague & Abolfazl Jaafari & Wei Chen & Shaghayegh Miraki & Jie Dou & Chinh Luu & Krzysztof Górski & Binh, 2020. "Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms," IJERPH, MDPI, vol. 17(8), pages 1-30, April.
    4. 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.
    5. Idris Bello Yamusa & Mohd Suhaili Ismail & Abdulwaheed Tella, 2022. "Highway Proneness Appraisal to Landslides along Taiping to Ipoh Segment Malaysia, Using MCDM and GIS Techniques," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
    6. Danang Sri Hadmoko & Franck Lavigne & Guruh Samodra, 2017. "Application of a semiquantitative and GIS-based statistical model to landslide susceptibility zonation in Kayangan Catchment, Java, Indonesia," 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. 87(1), pages 437-468, May.
    7. Vahed Ghiasi & Seyed Amir Reza Ghasemi & Mahyar Yousefi, 2021. "Landslide susceptibility mapping through continuous fuzzification and geometric average multi-criteria decision-making approaches," 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(1), pages 795-808, May.
    8. Masanori Kohno & Yuki Higuchi & Yusuke Ono, 2023. "Evaluating earthquake-induced widespread slope failure hazards using an AHP-GIS combination," 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. 116(2), pages 1485-1512, March.
    9. Txomin Bornaetxea & Juan Remondo & Jaime Bonachea & Pablo Valenzuela, 2023. "Exploring available landslide inventories for susceptibility analysis in Gipuzkoa province (Spain)," 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. 118(3), pages 2513-2542, September.
    10. Rui Yuan & Jing Chen, 2022. "A hybrid deep learning method for landslide susceptibility analysis with the application of InSAR data," 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. 114(2), pages 1393-1426, November.
    11. Sadhan Malik & Subodh Chandra Pal & Biswajit Das & Rabin Chakrabortty, 2020. "Assessment of vegetation status of Sali River basin, a tributary of Damodar River in Bankura District, West Bengal, using satellite data," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(6), pages 5651-5685, August.
    12. Santos Daniel Chicas & Heng Li & Nobuya Mizoue & Tetsuji Ota & Yan Du & Márk Somogyvári, 2024. "Landslide susceptibility mapping core-base factors and models’ performance variability: a systematic review," 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(14), pages 12573-12593, November.
    13. Kibeom Kwon & Minkyu Kang & Dongku Kim & Hangseok Choi, 2023. "Prioritization of Hazardous Zones Using an Advanced Risk Management Model Combining the Analytic Hierarchy Process and Fuzzy Set Theory," Sustainability, MDPI, vol. 15(15), pages 1-15, August.
    14. Nzotcha, Urbain & Kenfack, Joseph & Blanche Manjia, Marceline, 2019. "Integrated multi-criteria decision making methodology for pumped hydro-energy storage plant site selection from a sustainable development perspective with an application," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 930-947.
    15. 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.
    16. Viet-Tien Nguyen & Trong Hien Tran & Ngoc Anh Ha & Van Liem Ngo & Al-Ansari Nadhir & Van Phong Tran & Huu Duy Nguyen & Malek M. A. & Ata Amini & Indra Prakash & Lanh Si Ho & Binh Thai Pham, 2019. "GIS Based Novel Hybrid Computational Intelligence Models for Mapping Landslide Susceptibility: A Case Study at Da Lat City, Vietnam," Sustainability, MDPI, vol. 11(24), pages 1-24, December.
    17. Neshat, Aminreza & Pradhan, Biswajeet & Dadras, Mohsen, 2014. "Groundwater vulnerability assessment using an improved DRASTIC method in GIS," Resources, Conservation & Recycling, Elsevier, vol. 86(C), pages 74-86.
    18. Netra Bhandary & Ranjan Dahal & Manita Timilsina & Ryuichi Yatabe, 2013. "Rainfall event-based landslide susceptibility zonation mapping," 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. 69(1), pages 365-388, October.
    19. Wenqun Xiu & Shuying Wang & Wenguang Qi & Xue Li & Chisheng Wang, 2021. "Disaster Chain Analysis of Landfill Landslide: Scenario Simulation and Chain-Cutting Modeling," Sustainability, MDPI, vol. 13(9), pages 1-22, April.
    20. Di Wang & Mengmeng Hao & Shuai Chen & Ze Meng & Dong Jiang & Fangyu Ding, 2021. "Assessment of landslide susceptibility and risk factors in 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. 108(3), pages 3045-3059, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:endesu:v:26:y:2024:i:4:d:10.1007_s10668-023-03093-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.