IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i12p2186-d1302568.html
   My bibliography  Save this article

Landslide Susceptibility Assessment in Nepal’s Chure Region: A Geospatial Analysis

Author

Listed:
  • Purna Bahadur Thapa

    (Institute of Forestry, Hetauda Campus, Tribhuvan University, Hetauda 44100, Nepal)

  • Saurav Lamichhane

    (Faculty of Forestry, Agriculture and Forestry University, Hetauda 44100, Nepal)

  • Khagendra Prasad Joshi

    (Kathmandu Forestry College, Tribhuvan University, Kathmandu 44600, Nepal)

  • Aayoush Raj Regmi

    (School of Forestry & NRM, Institute of Forestry, Tribhuvan University, Kathmandu 44600, Nepal)

  • Divya Bhattarai

    (Institute of Botany and Landscape Ecology, University of Greifswald, Soldmannstraße 15, 17489 Greifswald, Germany)

  • Hari Adhikari

    (Department of Geosciences and Geography, University of Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland)

Abstract

The Chure Hills, already vulnerable due to their fragile nature, face increased landslide risk, prompting the need for reliable susceptibility assessment. This study uses Poisson regression modeling to assess landslide susceptibility in two highly susceptible districts of the Chure region. Variance inflation factor (VIF) tests were conducted to ensure robustness, indicating no multicollinearity among the variables. Subsequently, Poisson regression analysis identified eight significant variables, among which geology, lineament density, elevation, relief, slope, rainfall, solar radiance, and land cover types emerged as important factors associated with landslide count. The analysis revealed that higher lineament density and slope were associated with lower landslide counts, indicating potential stabilizing geological and topographical influences. The categorical variable, namely geology, revealed that middle Siwalik, upper Siwalik, and quaternary geological formations were associated with lower landslide counts than lower Siwalik. Land cover types, including areas under forest, shrubland, grassland, agricultural land, water bodies, and bare ground, had a substantial significant positive association with landslide count. The generated susceptibility map that exhibited a substantial portion (23.32% in Dang and 5.22% in Surkhet) of the study area fell within the very-high-susceptibility categories, indicating pronounced landslide susceptibility in the Dang and Surkhet districts of the Chure hills. This study offers valuable insights into landslide vulnerability in the Chure region, serving as a foundation for informed decision-making, disaster risk reduction strategies, and sustainable land-use and developmental policy planning.

Suggested Citation

  • Purna Bahadur Thapa & Saurav Lamichhane & Khagendra Prasad Joshi & Aayoush Raj Regmi & Divya Bhattarai & Hari Adhikari, 2023. "Landslide Susceptibility Assessment in Nepal’s Chure Region: A Geospatial Analysis," Land, MDPI, vol. 12(12), pages 1-19, December.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:12:p:2186-:d:1302568
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/12/2186/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/12/12/2186/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Viet-Ha Nhu & Ayub Mohammadi & Himan Shahabi & Baharin Bin Ahmad & Nadhir Al-Ansari & Ataollah Shirzadi & John J. Clague & Abolfazl Jaafari & Wei Chen & Hoang Nguyen, 2020. "Landslide Susceptibility Mapping Using Machine Learning Algorithms and Remote Sensing Data in a Tropical Environment," IJERPH, MDPI, vol. 17(14), pages 1-23, July.
    2. Israr Ullah & Bilal Aslam & Syed Hassan Iqbal Ahmad Shah & Aqil Tariq & Shujing Qin & Muhammad Majeed & Hans-Balder Havenith, 2022. "An Integrated Approach of Machine Learning, Remote Sensing, and GIS Data for the Landslide Susceptibility Mapping," Land, MDPI, vol. 11(8), pages 1-20, August.
    3. David Petley & Gareth Hearn & Andrew Hart & Nicholas Rosser & Stuart Dunning & Katie Oven & Wishart Mitchell, 2007. "Trends in landslide occurrence in Nepal," 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. 43(1), pages 23-44, October.
    4. Motilal Ghimire, 2011. "Landslide occurrence and its relation with terrain factors in the Siwalik Hills, Nepal: case study of susceptibility assessment in three basins," 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. 56(1), pages 299-320, January.
    5. C. van Westen & N. Rengers & R. Soeters, 2003. "Use of Geomorphological Information in Indirect Landslide Susceptibility Assessment," 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. 30(3), pages 399-419, November.
    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. Motilal Ghimire & Niroj Timalsina & Wei Zhao, 2024. "A Geographical approach of watershed prioritization in the Himalayas: a case study in the middle mountain district of Nepal," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(9), pages 23527-23560, September.
    2. Uzodigwe Emmanuel Nnanwuba & Shengwu Qin & Oluwafemi Adewole Adeyeye & Ndichie Chinemelu Cosmas & Jingyu Yao & Shuangshuang Qiao & Sun Jingbo & Ekene Mathew Egwuonwu, 2022. "Prediction of Spatial Likelihood of Shallow Landslide Using GIS-Based Machine Learning in Awgu, Southeast/Nigeria," Sustainability, MDPI, vol. 14(19), pages 1-20, September.
    3. Prabin Kayastha & Megh Dhital & Florimond Smedt, 2012. "Landslide susceptibility mapping using the weight of evidence method in the Tinau watershed, Nepal," 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 479-498, September.
    4. 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.
    5. Erin L. Harvey & Mark E. Kincey & Nick J. Rosser & Arishma Gadtaula & Ethan Collins & Alexander L. Densmore & Alexandre Dunant & Katie J. Oven & Katherine Arrell & Gopi K. Basyal & Megh Raj Dhital & T, 2025. "Review of landslide inventories for Nepal between 2010 and 2021 reveals data gaps in global landslide hotspot," 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. 121(5), pages 5075-5101, March.
    6. Xiaoxiao Ju & Junjie Li & Chongxiang Sun & Bo Li, 2024. "Landslide Susceptibility Assessment Using a CNN–BiLSTM-AM Model," Sustainability, MDPI, vol. 16(21), pages 1-24, October.
    7. Hyo-sub Kang & Yun-tae Kim, 2016. "The physical vulnerability of different types of building structure to debris flow events," 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. 80(3), pages 1475-1493, February.
    8. Randell, Heather & Jiang, Chengsheng & Liang, Xin-Zhong & Murtugudde, Raghu & Sapkota, Amir, 2021. "Food insecurity and compound environmental shocks in Nepal: Implications for a changing climate," World Development, Elsevier, vol. 145(C).
    9. Abhik Saha & Vasanta Govind Kumar Villuri & Ashutosh Bhardwaj, 2022. "Development and Assessment of GIS-Based Landslide Susceptibility Mapping Models Using ANN, Fuzzy-AHP, and MCDA in Darjeeling Himalayas, West Bengal, India," Land, MDPI, vol. 11(10), pages 1-27, October.
    10. Thomas Stanley & Dalia B. Kirschbaum, 2017. "A heuristic approach to global landslide susceptibility 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. 87(1), pages 145-164, May.
    11. Paúl Carrión-Mero & Néstor Montalván-Burbano & Fernando Morante-Carballo & Adolfo Quesada-Román & Boris Apolo-Masache, 2021. "Worldwide Research Trends in Landslide Science," IJERPH, MDPI, vol. 18(18), pages 1-24, September.
    12. Siti Norsakinah Selamat & Nuriah Abd Majid & Aizat Mohd Taib, 2023. "A Comparative Assessment of Sampling Ratios Using Artificial Neural Network (ANN) for Landslide Predictive Model in Langat River Basin, Selangor, Malaysia," Sustainability, MDPI, vol. 15(1), pages 1-21, January.
    13. K. Sajinkumar & S. Anbazhagan, 2015. "Geomorphic appraisal of landslides on the windward slope of Western Ghats, southern 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. 75(1), pages 953-973, January.
    14. Seyed Vahid Razavi-Termeh & Abolghasem Sadeghi-Niaraki & Farbod Farhangi & Soo-Mi Choi, 2021. "COVID-19 Risk Mapping with Considering Socio-Economic Criteria Using Machine Learning Algorithms," IJERPH, MDPI, vol. 18(18), pages 1-21, September.
    15. Danang Hadmoko & Franck Lavigne & Junun Sartohadi & Pramono Hadi & Winaryo, 2010. "Landslide hazard and risk assessment and their application in risk management and landuse planning in eastern flank of Menoreh Mountains, Yogyakarta Province, 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. 54(3), pages 623-642, September.
    16. Paul Sestraș & Ștefan Bilașco & Sanda Roșca & Sanda Naș & Mircea V. Bondrea & Raluca Gâlgău & Ioel Vereș & Tudor Sălăgean & Velibor Spalević & Sorin M. Cîmpeanu, 2019. "Landslides Susceptibility Assessment Based on GIS Statistical Bivariate Analysis in the Hills Surrounding a Metropolitan Area," Sustainability, MDPI, vol. 11(5), pages 1-23, March.
    17. Fan Yang & Xiaozhi Men & Yangsheng Liu & Huigeng Mao & Yingnan Wang & Li Wang & Xiran Zhou & Chong Niu & Xiao Xie, 2023. "Estimation of Landslide and Mudslide Susceptibility with Multi-Modal Remote Sensing Data and Semantics: The Case of Yunnan Mountain Area," Land, MDPI, vol. 12(10), pages 1-15, October.
    18. Sohan Kumar Ghimire & Daisuke Higaki & Tara Prasad Bhattarai, 2013. "Estimation of Soil Erosion Rates and Eroded Sediment in a Degraded Catchment of the Siwalik Hills, Nepal," Land, MDPI, vol. 2(3), pages 1-22, July.
    19. Khabat Khosravi & Ebrahim Nohani & Edris Maroufinia & Hamid Reza Pourghasemi, 2016. "A GIS-based flood susceptibility assessment and its mapping in Iran: a comparison between frequency ratio and weights-of-evidence bivariate statistical models with multi-criteria decision-making techn," 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. 83(2), pages 947-987, September.
    20. Paola Gattinoni, 2009. "Parametrical landslide modeling for the hydrogeological susceptibility assessment: from the Crati Valley to the Cavallerizzo landslide (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. 50(1), pages 161-178, July.

    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:gam:jlands:v:12:y:2023:i:12:p:2186-:d:1302568. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.