Abstract Landslide hazard prediction for the Three Gorges area is necessary for mitigating geohazards, especially under extreme rainfall conditions. A method for calculating rainfall in the extreme rainfall return period was first proposed. Then, geological conditions of the Baishuihe landslide on the reservoir shore were modelled, along with soil parameters. Four geological profiles were chosen, and the phreatic line of the landslide was simulated in the SEEP/W programme. The profiles were then divided into slices, and, the long-term stability and failure probability of each slice was calculated using the uncertainty of the soil parameters and the Monte Carlo method. An Empirical Bayesian Kriging (EBK) method in ArcGIS was used to obtain a hazard distribution map for the landslide’s active area and the deeper landslide. The standardized extreme rainfall for different return periods were then used to predict the hazard of the active area and determine the relationship between the unstable area within the active area and the rainfall return period. The stability of the Baishuihe landslide shows a periodic trend and a strong relationship with the reservoir water level and the rainfall distribution, while the stability of the deeper landslide is less affected. With an increase in the rainfall return period, the unstable area of the active area expands. The ratio of the unstable area in the active area and the rainfall return period show a logarithmic correlation. This paper solves the standardization problem of rainfall return period in the field of geological hazards, and realizes the visualization of local stability in the landslide area, which can promote to enhance the ability of preventing and controlling landslide hazards.


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    Title :

    Hazard Prediction for Baishuihe Landslide in the Three Gorges Reservoir during the Extreme Rainfall Return Period


    Contributors:
    Li, Deying (author) / Miao, Fasheng (author) / Xie, Yuanhua (author) / Leo, Chin (author)

    Published in:

    Publication date :

    2019-10-30


    Size :

    11 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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