Probabilistic reliability assessment of reservoir-area colluvial landslides considering rotated spatial variability of geotechnical parameters

Slope reliability analysis often assumes isotropic or anisotropic random fields with horizontal orientation to characterize the spatial variability of soil parameters. However, this neglects the influence of rotated anisotropic spatial variability, leading to conservative and unrealistic failure probability estimates. To overcome this limitation, we propose a novel method based on the Hierarchical Recurrent Highway Network (HRHN) with attention mechanisms. This method is applied to a time-dependent reliability assessment of the Baishuihe landslide. By incorporating the spatial variability of geotechnical properties-especially the direction of maximum fluctuation-the study constructs both the most adverse and favorable extreme scenarios, enabling the exploration of failure probability evolution under reservoir drawdown and rainfall infiltration. Compared with traditional horizontally anisotropic random fields, the proposed model produces a range of failure probabilities rather than a single curve. This interval range-formed by maximum and minimum failure probabilities-better captures the uncertainty of the model and accounts for external factors such as rainfall and geological changes. Our approach offers a more comprehensive and realistic perspective for geotechnical risk assessment.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2026-02-04
DOI
https://doi.org/10.1371/journal.pone.0340400
Primary Topic
Geotechnical Engineering and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Probabilistic reliability assessment of reservoir-area colluvial landslides considering rotated spatial variability of geotechnical parameters

Li Wu, Quan Zhao, Zhile Xu, Haifu Tang et al.
PLoS ONE
Geotechnical Engineering and Analysis
article

Probabilistic reliability assessment of reservoir-area colluvial landslides considering rotated spatial variability of geotechnical parameters

Li Wu, Quan Zhao, Zhile Xu, Haifu Tang, Long Qin
article en

Abstract

Slope reliability analysis often assumes isotropic or anisotropic random fields with horizontal orientation to characterize the spatial variability of soil parameters. However, this neglects the influence of rotated anisotropic spatial variability, leading to conservative and unrealistic failure probability estimates. To overcome this limitation, we propose a novel method based on the Hierarchical Recurrent Highway Network (HRHN) with attention mechanisms. This method is applied to a time-dependent reliability assessment of the Baishuihe landslide. By incorporating the spatial variability of geotechnical properties-especially the direction of maximum fluctuation-the study constructs both the most adverse and favorable extreme scenarios, enabling the exploration of failure probability evolution under reservoir drawdown and rainfall infiltration. Compared with traditional horizontally anisotropic random fields, the proposed model produces a range of failure probabilities rather than a single curve. This interval range-formed by maximum and minimum failure probabilities-better captures the uncertainty of the model and accounts for external factors such as rainfall and geological changes. Our approach offers a more comprehensive and realistic perspective for geotechnical risk assessment.

PLoS ONEVol. 21(2)
Guizhou University (CN), Guzhou Transportation Planning Survey & Design Academe (China) (CN), Baoding University (CN)
Openalex Percentile: Top 73%
Geotechnical Engineering and Analysis
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.