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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 1-20, December.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:12:p:2186-:d:1302568
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    References listed on IDEAS

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    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.
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