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A Model between Cohesion and Its Inter-Controlled Factors of Fine-Grained Sediments in Beichuan Debris Flow, Sichuan Province, China

Author

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  • Qinjun Wang

    (International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    Yanqihu Campus, University of Chinese Academy of Sciences, Beijing 101408, China
    Key Laboratory of the Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Sanya 572029, China)

  • Jingjing Xie

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    Yanqihu Campus, University of Chinese Academy of Sciences, Beijing 101408, China)

  • Jingyi Yang

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    Yanqihu Campus, University of Chinese Academy of Sciences, Beijing 101408, China)

  • Peng Liu

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    Yanqihu Campus, University of Chinese Academy of Sciences, Beijing 101408, China)

  • Dingkun Chang

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    Yanqihu Campus, University of Chinese Academy of Sciences, Beijing 101408, China)

  • Wentao Xu

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    Yanqihu Campus, University of Chinese Academy of Sciences, Beijing 101408, China)

Abstract

Cohesion is the attraction between adjacent particles within the same material, which is the main inter-controlled factor of fine-grained sediment stability, and thus plays an important role in debris flow hazard early warning. However, there is no quantitative model of cohesion and its inter-controlled factors, including effective internal friction angle, permeability coefficient and density. Therefore, establishing a quantitative model of cohesion and its inter-controlled factors is of considerable significance in debris flow hazard early warning. Taking Beichuan county in southwestern China as the study area, we carried out a series of experiments on cohesion and its inter-controlled factors. Using the value of cohesion as the dependent variable and values of normalized density, normalized logarithm of permeability coefficient and normalized effective internal friction angle as the independent variables, we established a quantitative model of cohesion and its inter-controlled factors by the least-squares multivariate statistical method. Fitting of the model showed that its determination coefficient (R 2 ) was 0.61, indicating that the corresponding correlation coefficient (R) was 0.78. Furthermore, t -tests of the model showed that except for the p value of density, which was 0.05, those of other factors were less than 0.01, indicating that cohesion was significantly correlated to its inter-controlled factors, providing a scientific basis for debris flow hazard early warning.

Suggested Citation

  • Qinjun Wang & Jingjing Xie & Jingyi Yang & Peng Liu & Dingkun Chang & Wentao Xu, 2022. "A Model between Cohesion and Its Inter-Controlled Factors of Fine-Grained Sediments in Beichuan Debris Flow, Sichuan Province, China," Sustainability, MDPI, vol. 14(19), pages 1-12, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12832-:d:936322
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    References listed on IDEAS

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    1. Yu Huang & Chongqiang Zhu, 2014. "Simulation of flow slides in municipal solid waste dumps using a modified MPS method," 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. 74(2), pages 491-508, November.
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