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Effect of Soil Geomechanical Properties and Geo-Environmental Factors on Landslide Predisposition at Mount Oku, Cameroon

Author

Listed:
  • Wamba Danny Love Djukem

    (Department of Earth Sciences, Faculty of Sciences, University of Dschang, Dschang P.O. Box 67, Cameroon)

  • Anika Braun

    (Department of Engineering Geology, Institute of Applied Geosciences, Faculty VI Planning Building Environment, Technische Universität Berlin, 10587 Berlin, Germany)

  • Armand Sylvain Ludovic Wouatong

    (Department of Earth Sciences, Faculty of Sciences, University of Dschang, Dschang P.O. Box 67, Cameroon)

  • Christian Guedjeo

    (Department of Earth Sciences, Faculty of Sciences, University of Dschang, Dschang P.O. Box 67, Cameroon)

  • Katrin Dohmen

    (Department of Engineering Geology, Institute of Applied Geosciences, Faculty VI Planning Building Environment, Technische Universität Berlin, 10587 Berlin, Germany)

  • Pierre Wotchoko

    (HTTC Bambili, University of Bamenda, Bamenda P.O. Box 39, Cameroon)

  • Tomas Manuel Fernandez-Steeger

    (Department of Engineering Geology, Institute of Applied Geosciences, Faculty VI Planning Building Environment, Technische Universität Berlin, 10587 Berlin, Germany)

  • Hans-Balder Havenith

    (Geology Department-B18, Georisk and Environment, Faculty of Sciences, Liege University, B-4000 Liege, Belgium)

Abstract

In this work, we explored a novel approach to integrate both geo-environmental and soil geomechanical parameters in a landslide susceptibility model. A total of 179 shallow to deep landslides were identified using Google Earth images and field observations. Moreover, soil geomechanical properties of 11 representative soil samples were analyzed. The relationship between soil properties was evaluated using the Pearson correlation coefficient and geotechnical diagrams. Membership values were assigned to each soil property class, using the fuzzy membership method. The information value method allowed computing the weight value of geo-environmental factor classes. From the soil geomechanical membership values and the geo-environmental factor weights, three landslide predisposition models were produced, two separate models and one combined model. The results of the soil testing allowed classifying the soils in the study area as highly plastic clays, with high water content, swelling, and shrinkage potential. Some geo-environmental factor classes revealed their landslide prediction ability by displaying high weight values. While the model with only soil properties tended to underrate unstable and stable areas, the model combining soil properties and geo-environmental factors allowed a more precise identification of stability conditions. The geo-environmental factors model and the model combining geo-environmental factors and soil properties displayed predictive powers of 80 and 93%, respectively. It can be concluded that the spatial analysis of soil geomechanical properties can play a major role in the detection of landslide prone areas, which is of great interest for site selection and planning with respect to sustainable development at Mount Oku.

Suggested Citation

  • Wamba Danny Love Djukem & Anika Braun & Armand Sylvain Ludovic Wouatong & Christian Guedjeo & Katrin Dohmen & Pierre Wotchoko & Tomas Manuel Fernandez-Steeger & Hans-Balder Havenith, 2020. "Effect of Soil Geomechanical Properties and Geo-Environmental Factors on Landslide Predisposition at Mount Oku, Cameroon," IJERPH, MDPI, vol. 17(18), pages 1-27, September.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:18:p:6795-:d:415213
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    References listed on IDEAS

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    Cited by:

    1. Xianyu Yu & Tingting Xiong & Weiwei Jiang & Jianguo Zhou, 2023. "Comparative Assessment of the Efficacy of the Five Kinds of Models in Landslide Susceptibility Map for Factor Screening: A Case Study at Zigui-Badong in the Three Gorges Reservoir Area, China," Sustainability, MDPI, vol. 15(1), pages 1-26, January.
    2. Xiaoting Zhou & Weicheng Wu & Ziyu Lin & Guiliang Zhang & Renxiang Chen & Yong Song & Zhiling Wang & Tao Lang & Yaozu Qin & Penghui Ou & Wenchao Huangfu & Yang Zhang & Lifeng Xie & Xiaolan Huang & Xia, 2021. "Zonation of Landslide Susceptibility in Ruijin, Jiangxi, China," IJERPH, MDPI, vol. 18(11), pages 1-20, May.
    3. Lamek Nahayo & Cui Peng & Yu Lei & Rongzhi Tan, 2023. "Spatial understanding of historical and future landslide variation in Africa," 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. 119(1), pages 613-641, October.

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