A Modified Method for Evaluating the Stability of the Finite Slope during Intense Rainfall

The Green–Ampt (GA) model is a widely used analytical method to calculate the depth of the wetting front during intense rainfall. However, it neglects the existence of the transition layer and the seepage parallel to the slope surface. Therefore, a modified stratified Green–Ampt (MSGA) model is proposed. A process to assess the stability of the finite slope during a rainfall event is demonstrated by combining the MSGA model and the limit equilibrium method. In the case of the Liangshuijing landslide, the factor of safety presents a negative correlation with the depth of the wetting front. The factor of safety obtained by the stratified Green–Ampt (SGA) model is smaller than that calculated by the MSGA model, and the gap between the factor of safety based on the two methods widens with time. The moving speed of the wetting front accelerates with the increase in the length of the slope surface, and the size effect becomes apparent when the length is short. In the initial stage of infiltration, the effect of the seepage parallel to the slope surface is small. The effect of the seepage cannot be neglected at the latter stage. The result calculated by the MSGA model agrees well with the measured result in the test.

Authors

Institutions

Publication Details

Journal
Water
Published
2024-10-10
DOI
https://doi.org/10.3390/w16202877
Citations
5
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
3.55

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Modified Method for Evaluating the Stability of the Finite Slope during Intense Rainfall

Longwei Li, Xiaoyang Wei, Simin Cai, Wenhui Xu et al.
5 citations
Water
Landslides and related hazards
3.55
article

A Modified Method for Evaluating the Stability of the Finite Slope during Intense Rainfall

Longwei Li, Xiaoyang Wei, Simin Cai, Wenhui Xu, Weizhong Ren
article en
5 citations

Abstract

The Green–Ampt (GA) model is a widely used analytical method to calculate the depth of the wetting front during intense rainfall. However, it neglects the existence of the transition layer and the seepage parallel to the slope surface. Therefore, a modified stratified Green–Ampt (MSGA) model is proposed. A process to assess the stability of the finite slope during a rainfall event is demonstrated by combining the MSGA model and the limit equilibrium method. In the case of the Liangshuijing landslide, the factor of safety presents a negative correlation with the depth of the wetting front. The factor of safety obtained by the stratified Green–Ampt (SGA) model is smaller than that calculated by the MSGA model, and the gap between the factor of safety based on the two methods widens with time. The moving speed of the wetting front accelerates with the increase in the length of the slope surface, and the size effect becomes apparent when the length is short. In the initial stage of infiltration, the effect of the seepage parallel to the slope surface is small. The effect of the seepage cannot be neglected at the latter stage. The result calculated by the MSGA model agrees well with the measured result in the test.

WaterVol. 16(20)
Institute of Rock and Soil Mechanics (CN), University of Chinese Academy of Sciences (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 8%
Landslides and related hazards
3.55
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Modified Method for Evaluating the Stability of the Finite Slope during Intense Rainfall — Longwei Li, Xiaoyang Wei, et al. · Water (2024) | TGRS Research Map | TGRS