Analysis of Slope Stability with Different Vegetation Types under the Influence of Rainfall

Author:

Chen Bozhou1,Shui Wei2,Liu Yuanmeng1,Deng Ruyue2

Affiliation:

1. Zijin College of Geology and Mining, Fuzhou University, Fuzhou 350108, China

2. College of Environment & Safety Engineering, Fuzhou University, Fuzhou 350108, China

Abstract

Rainfall-prone shallow landslides account for one-fifth of the global land area, and rainfall is critical to the mechanics and hydrology of shallow slopes. In typical geological disaster-prone areas, the hydrodynamic responses of slopes with different vegetation types under rainfall conditions require further study. The purpose of this study was to analyze the hydraulic stability of soils with different vegetation types under rainfall conditions and their effects on slope stability. Thus, the soil–water characteristic curves and water-stable aggregate characteristics of soils with three vegetation types were analyzed. A two-dimensional finite element model was used to simulate the slope stability of extreme rainfall environments with different rainfall durations. The results showed that the matric suction of soil with trees was less affected by rainfall with a better stability of water-stable aggregates than that of soil with shrubs and grass. The plastic strain cloud map showed that the maximum plastic strain occurred at the toe of the slope. In addition, the potential slip depth of slopes with trees was smaller than that of slopes with shrubs and grass. Under the two rainfall durations, the factor of safety (FoS) of slopes with trees changed by 0.06, whereas that of slopes with shrubs and grass changed by 0.1. The findings of this study provide valuable insights into changes in the stability of slopes with different vegetation types under varying rainfall conditions. It is of great significance to provide a scientific basis for the application of ecological measures in the prevention and control of mountain disasters and guide the implementation of appropriate land management measures.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Forestry

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