Mechanical Behavior of Critical Geo-Materials and Landslide Evolution Processes

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Geomechanics".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 313

Special Issue Editors

Badong National Observation and Research Station of Geohazards, China University of Geosciences, Wuhan 430074, China
Interests: landslide evolution process; slope dynamic stability; soil properties; reservoir landslide; rainfall-induced shallow landslide; landslide risk assessment; landslide reliability

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Guest Editor
College of Transportation Engineering, Nanjing Tech University, Nanjing 211816, China
Interests: slope stability analysis; slope failure mechanism; probability analysis of stability in geotechnical engineering; slope risk assessment; river erosion landslide; landslide disaster monitoring and early warning

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Guest Editor
Badong National Observation and Research Station of Geohazards (BNORSG), China University of Geosciences, Wuhan 43007, China
Interests: slope engineering; rock and soil deformation and control; refined modeling; dynamic load simulation and stability; large-scale in situ testing
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Guest Editor
School of Earth and Environment, Anhui University of Science and Technology, Huainan 232001, China
Interests: reservoir landslide; sliding zone soil; soil-water interaction; physicochemical interaction; micromechanism of sliding zone evolution

Special Issue Information

Dear Colleagues,

Landslides are complex geological processes driven by the interplay of mechanical weakening, hydrologic forcing, and structural heterogeneity. Critical geo-materials (e.g., slip zones and weak intercalation) act as "weak links" controlling landslide initiation and progression. Traditional stability analyses often oversimplify these interactions, neglecting time-dependent behaviors such as creep, fatigue, and rate-dependent strength degradation. Recent advancements in multi-scale monitoring (e.g., InSAR and distributed fiber optics) and high-fidelity modeling (e.g., material point method and discrete element modeling) have revealed the nonlinear evolution of landslides, yet challenges remain in quantifying feedback between mechanical behavior and environmental triggers. With increasing climate extremes and human activities, understanding landslide evolution is critical for early warning and infrastructure resilience. This Special Issue addresses gaps involving mechanism-driven modeling, dynamic parameterization, uncertainty quantification, etc. The issue complements the journal’s focus on geotechnical risk management by providing novel methodologies and field applications.

The goal of this Special Issue is to collect papers (original research articles and review papers) to give insights about the understanding of mechanical interactions within landslide-critical geo-materials (e.g., slip zones and weak interlayers) and their role in controlling landslide evolution. We seek interdisciplinary studies integrating geomechanics, hydrology, and advanced monitoring to unravel dynamic failure mechanisms and improve predictive models. We anticipate that this Special Issue will encompass the nonlinear behavior of geological materials, multi-physics coupling effects, and evolution stage characterization under natural/anthropogenic triggers.

This Special Issue welcomes manuscripts that link the following themes:

  • Mechanical behavior of slip zones: strain softening effect, rate-dependent strength, cyclic loading effects, and microstructural evolution.
  • Hydromechanical coupling: pore pressure dynamics, unsaturated seepage, and drainage control.
  • Evolution stage characterization: deformation rate thresholds, acoustic emission patterns, and precursor identification.
  • Multi-scale modeling: from grain-scale DEM simulations to regional risk mapping.
  • Case studies: evolution analyses of reservoir, seismic, or rainfall-triggered landslides.

We look forward to receiving your original research articles and reviews.

Dr. Shu Zhang
Dr. Shuangfeng Guo
Dr. Qinwen Tan
Dr. Xuexue Su
Guest Editors

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Keywords

  • landslide evolution
  • geo-material mechanics
  • multi-field coupling
  • rate-dependent strength
  • hydromechanical interaction
  • progressive failure
  • risk prediction
  • numerical modeling
  • field experiments
 

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Published Papers (1 paper)

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Research

19 pages, 2353 KiB  
Article
A Novel Bimodal Hydro-Mechanical Coupling Model for Evaluating Rainfall-Induced Unsaturated Slope Stability
by Tzu-Hao Huang, Ya-Sin Yang and Hsin-Fu Yeh
Geosciences 2025, 15(7), 265; https://doi.org/10.3390/geosciences15070265 - 9 Jul 2025
Viewed by 180
Abstract
The soil water characteristic curve (SWCC) is a key foundation in unsaturated soil mechanics describing the relationship between matric suction and water content, which is crucial for studies on effective stress, permeability coefficients, and other soil properties. In natural environments, colluvial and residual [...] Read more.
The soil water characteristic curve (SWCC) is a key foundation in unsaturated soil mechanics describing the relationship between matric suction and water content, which is crucial for studies on effective stress, permeability coefficients, and other soil properties. In natural environments, colluvial and residual soils typically exhibit high pore heterogeneity, and previous studies have shown that the SWCC is closely related to the distribution of pore sizes. The SWCC of soils may display either a unimodal or bimodal distribution, leading to different hydraulic behaviors. Past unsaturated slope stability analyses have used the unimodal SWCC model, but this assumption may result in evaluation errors, affecting the accuracy of seepage and slope stability analyses. This study proposes a novel bimodal hydro-mechanical coupling model to investigate the influence of bimodal SWCC representations on rainfall-induced seepage behavior and stability of unsaturated slopes. By fitting the unimodal and bimodal SWCCs with experimental data, the results show that the bimodal model provides a higher degree of fit and smaller errors, offering a more accurate description of the relationship between matric suction and effective saturation, thus improving the accuracy of soil hydraulic property assessment. Furthermore, the study established a hypothetical slope model and used field data of landslides to simulate the collapse of Babaoliao in Chiayi County, Taiwan. The results show that the bimodal model predicts slope instability 1 to 3 h earlier than the unimodal model, with the rate of change in the safety factor being about 16.6% to 25.1% higher. The research results indicate the superiority of the bimodal model in soils with dual-porosity structures. The bimodal model can improve the accuracy and reliability of slope stability assessments. Full article
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