SUN Pingping, ZHANG Maosheng, JIANG Ruijun, JIA Jun, LIU Feng, LIU Mengmeng. 2021: Deformation and failure mechanism of rainfall-induced shallow loess landslide. Geological Bulletin of China, 40(10): 1617-1625.
    Citation: SUN Pingping, ZHANG Maosheng, JIANG Ruijun, JIA Jun, LIU Feng, LIU Mengmeng. 2021: Deformation and failure mechanism of rainfall-induced shallow loess landslide. Geological Bulletin of China, 40(10): 1617-1625.

    Deformation and failure mechanism of rainfall-induced shallow loess landslide

    • The shallow loess landslides, triggered by precipitation has the characteristics of serious catastrophability, wide range of influence and large impact area, is one of the serious disaster in the Loess Plateau.It is difficult to identify the initial failure position and actual failure surface with the classical analysis method by using one safety factor to describe the slope stability, which limits the description of the failure process of slopes and consequently influence the effective prediction of landslides.Guided by the theory of unsaturated soil matric suction, the water- stress coupling model of loess slope was established based on the Slope Cube module with the Hydrus software.According to the statistics of slide-prone morphology of loess slopes, the slope stability response to rainfall conditions was calculated under different conbinations of convex, concave and linear, and the three slope gradients of 30°, 40° and 50°.The results show that different loess slopes have obvious responses to precipitation, and its influence is controlled by the slope types.Under the condition of the same rainfall and the same slope, the possibility of superficial surface damage occurs on the linear slope is the lowest, followed by the concave slope and the convex slope.Correspondingly, the time consuming of instability is the shortest for convex slopes, the second for the concave slopes, and the longest for the linear slopes under the same conditions.This study can provide support for early identification and prediction of shallow loess landslides.
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