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GIS-based prediction method of shallow landslides induced by heavy rainfall in large mountainous areas.

Authors :
Luo, Xiaoxiong
Li, Congjiang
Zhou, Jiawen
Source :
Journal of Mountain Science; May2024, Vol. 21 Issue 5, p1534-1548, 15p
Publication Year :
2024

Abstract

Rainwater runoff that does not infiltrate the soil during heavy rainfall may increase slope instability. The effect of runoff is usually neglected in conventional rainfall-induced slope failure analysis to simplify the model. To analyze the effect of runoff on slope stability, this study simultaneously simulated the effects of surface runoff and rainfall infiltration on bank slopes in the Three Gorges Reservoir Area. A shallow slope failure method that can be used to analyze runoff was proposed based on the modified Green-Ampt model, the simplified Saint-Venant model, and the infinite slope model. In this model, the modified Green–Ampt model was used to estimate the rainfall infiltration capacity and the wetting front depth. The eight-flow (D8) method and the simplified Saint-Venant model were selected to estimate the distribution of runoff. By considering the wetting front depth as the slip surface depth, the factor of safety of the slope could be determined using the infinite slope stability model. A comparison of the different models reveals that runoff can escalate the instability of certain slopes, causing stable slopes to become unstable. Comparison of the unstable areas obtained from the simulation with the actual landslide sites shows that the model proposed in this study can successfully predict landslides at these sites. The slope instability assessment model proposed in this study offers an alternative approach for estimating high-risk areas in large mountainous regions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16726316
Volume :
21
Issue :
5
Database :
Complementary Index
Journal :
Journal of Mountain Science
Publication Type :
Academic Journal
Accession number :
177817364
Full Text :
https://doi.org/10.1007/s11629-023-8535-2