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Landslide on Hydrological Response

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A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrogeology".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 7964

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Dr. Lei Zhang

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Guest Editor

School of Water Resources and Environment, China University of Geosciences (Beijing), Beijing, China
Interests: reservoir landslide; deformation mechanism; stability evaluation; landslide early warning
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Special Issue Information

Dear Colleagues,

Hydrological factors, such as rainfall and reservoir water level fluctuations, play a crucial role in triggering landslides. These factors periodically alter the seepage field within a landslide. Changes in pore water pressure and seepage forces exerted on soil or rock significantly affect landslide stability. A clear understanding of these mechanisms is vital for effective landslide risk mitigation and the protection of communities.

This Special Issue focuses on advancing research into the relationship between hydrological processes and landslide dynamics. Topics of interest include the following:

Early identification and susceptibility evaluation of water-induced landslide;
Application of novel monitoring technology in water-induced landslide;
Formation and deformation mechanism of water-induced landslide;
Early warning and stability analysis of water-induced landslide;
Comprehensive risk assessment of water-induced landslide.

By addressing these themes, this Special Issue aims to deepen our understanding of hydrological–landslide interactions and promote practical solutions for landslide risk management. Researchers are encouraged to contribute original studies, reviews, and case studies to this multidisciplinary platform.

Dr. Lei Zhang
Guest Editor

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Keywords

water-induced landslide
landslide stability
deformation mechanism
landslide susceptibility mapping
multi-fields monitoring

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Published Papers (7 papers)

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Research

29 pages, 43065 KB

Open AccessArticle

Numerical Simulation Research on Landslide Instability Mechanism Under Periodic Precipitation Conditions

by Ziang Liu, Lianxia Ma, Qihang Liu, Liang Song and Xiaomin Dai

Water 2026, 18(13), 1643; https://doi.org/10.3390/w18131643 - 6 Jul 2026

Viewed by 389

Abstract

Slope stability has consistently been a critical concern in mountainous road sections, with precipitation being the most significant factor precipitating slope instability. This study aims to elucidate the mechanism of slope instability under precipitation conditions and the extent of the impact of internal disaster-causing factors. To achieve this objective, a numerical simulation analysis method combining GeoStudio2018R2 and FLAC3D7.0 software was employed to conduct a comprehensive analysis of an unstable slope in Xinjiang. Regarding research methodology, cyclic precipitation and seasonal snowmelt were considered as external influencing factors. Initially, a two-dimensional model was constructed using GeoStudio software to analyze the spatial and temporal variations in pore water pressure and moisture content within the slope, elucidating their dynamic characteristics at different temporal and spatial scales. Subsequently, a three-dimensional numerical model was established using FLAC3D software to conduct a detailed analysis of the stress–strain state of the slope under various conditions, thereby obtaining disaster parameters such as displacement and sliding velocity in different directions. Through further comparison and verification of the overall stability analysis results of the slope obtained from both software packages, it was observed that they exhibited a consistent trend. The research findings indicate that under conditions of high-intensity short-term precipitation, the safety factor of the slope decreases to the lowest level, potentially leading to shallow landslides with smaller displacement but faster sliding velocity. Conversely, seasonal snowmelt and long-term localized precipitation have a more profound impact on the internal structure of the slope, with the sliding zone potentially penetrating into the deep bedrock. Although the occurrence frequency is low, the impact range is extensive. By combining two-dimensional and three-dimensional analyses, a comprehensive assessment of the different disaster-causing factors of the slope was conducted, enhancing the accuracy of the analysis results. The research findings provide a scientific basis and reference value for the formulation of subsequent slope protection and monitoring plans. Full article

(This article belongs to the Special Issue Landslide on Hydrological Response)

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25 pages, 11529 KB

Open AccessArticle

Fully Softened Strength as an Experimental Substitute for Five Wet–Dry Cycles in Expansive Clay Slope Stability: Equivalence of System Response Under Shallow Failure Conditions

by Jose Luis Chavez-Torres, Kunyong Zhang and Camila Nickole Fernandez-Morocho

Water 2026, 18(9), 1079; https://doi.org/10.3390/w18091079 - 30 Apr 2026

Viewed by 866

Abstract

Expansive clay slopes are vulnerable to progressive strength loss induced by repeated wetting and drying, a mechanism that drives shallow failure in active moisture zones. Reproducing this degradation experimentally is time-consuming and resource-intensive. This study evaluates whether Fully Softened Strength (FSS) can serve as a practical substitute for five wet–dry cycles in expansive clay slope stability assessment. Direct shear tests were conducted on wet–dry-cycled and reconstituted FSS specimens across fourteen experimental water contents. Strength parameters were incorporated into homogeneous and heterogeneous limit equilibrium slope models, considering degraded layer thicknesses of 1–5 m and suspended water table conditions. Equivalence was assessed using root mean square error (RMSE), prediction bias, and physical representativeness. Five wet–dry cycles produced a dominant cohesion reduction of 70.4% with minor changes in friction angle, reaching a quasi-stationary degraded state. FSS reproduced an equivalent system response through mechanical compensation between cohesion and friction—not through equality of strength parameters—under shallow failure conditions. The best statistical fit was obtained at w = 43.5% (RMSE = 0.314); however, w = 42.0%, coinciding with the liquid limit, provided a physically more robust interpretation with near-zero bias. Equivalence was found to be valid only for normal stresses ≤ 50 kPa, representative of shallow failure depths of 1–4 m. Full article

(This article belongs to the Special Issue Landslide on Hydrological Response)

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21 pages, 7514 KB

Open AccessArticle

Multi-Scale Displacement Prediction and Failure Mechanism Identification for Hydrodynamically Triggered Landslides

by Jian Qi, Ning Sun, Zhong Zheng, Yunzi Wang, Zhengxing Yu, Shuliang Peng, Jing Jin and Changhao Lyu

Water 2026, 18(8), 917; https://doi.org/10.3390/w18080917 - 11 Apr 2026

Viewed by 518

Abstract

Hydrodynamically triggered landslides remain a major concern in reservoir regions, where the mechanisms controlling displacement evolution are still not fully understood and the multi-scale deformation responses induced by individual hydrodynamic factors remain difficult to quantify. To address these issues, this study establishes a TSD-TET composite framework by integrating time-series signal decomposition with deep learning for multi-scale displacement prediction and the mechanism-oriented interpretation of hydrodynamically triggered landslides. The monitored displacement sequence is first decomposed into physically interpretable components, including trend, periodic, and random terms. Each component is subsequently predicted using deep temporal learning models to capture different deformation characteristics at multiple temporal scales. Meanwhile, key hydrodynamic driving factors, including rainfall, reservoir water level, and groundwater level, are decomposed within the same framework to examine their statistical associations with different displacement components. The proposed approach is applied to the Donglingxin landslide located in the Sanbanxi Hydropower Station reservoir area. Results show that the model achieves high prediction accuracy under both long-term forecasting horizons and limited-sample conditions, with a cumulative displacement coefficient of determination reaching R² = 0.945. Mechanism analysis further indicates that trend deformation is mainly controlled by geological structure and gravitational loading, periodic deformation is strongly modulated by hydrological cycles associated with reservoir water level fluctuations, and random deformation is more likely to reflect short-term disturbances and transient hydrodynamic forcing. These findings provide new insights into the deformation mechanisms of hydrodynamically triggered landslides and offer a promising technical pathway for improving displacement prediction, monitoring, and early warning of reservoir-induced landslide hazards. Full article

(This article belongs to the Special Issue Landslide on Hydrological Response)

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19 pages, 4470 KB

Open AccessArticle

A Regional-Scale Early Warning System for Rainfall-Induced Shallow Landslides Based on the Outputs of a Physically Based Model: Application to Cili County, China

by Wei Lin, Rosa M. Palau, Marcel Hürlimann, Kunlong Yin and Yuanyao Li

Water 2026, 18(2), 168; https://doi.org/10.3390/w18020168 - 8 Jan 2026

Viewed by 1618

Abstract

This paper presents a new method for a regional-scale rainfall-induced landslide early warning system (LEWS) based on the outputs of the “Fast Shallow Landslide Assessment Model” (FSLAM), a physically based model used to compute slope stability at a regional scale. The LEWS combines landslide susceptibility and rainfall thresholds to depict the areas that are prone to slope failures and issues qualitative warnings over the study area. Both the susceptibility map and the rainfall thresholds were obtained based on the outputs from running FSLAM with 25 different rainfall scenarios. The final output of the LEWS is a slope-unit-based map. The LEWS was implemented for Cili County, Hunan Province, China, and tested for the year 2020. The warning level stayed “Low” during most of the year. High warnings were issued during the summer and were either due to intense rainfall events or abundant long-duration precipitation. The LEWS was able to issue appropriate warnings corresponding to the time and location of three known landslides that occurred in the study area in 2020. Although long-term validation with more landslide data and improved geotechnical data is needed to reduce the LEWS uncertainties, this approach is promising and could support authorities managing landslide risk. Full article

(This article belongs to the Special Issue Landslide on Hydrological Response)

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20 pages, 5887 KB

Open AccessArticle

Stability Analysis of Loess Slope Under Heavy Rainfall Considering Joint Effect—Case Study of Jianxi Landslide, China

by Jiahao Wang, Lei Zhang, Shi Zhao, Guoji Li and Haipeng Guo

Water 2025, 17(22), 3271; https://doi.org/10.3390/w17223271 - 15 Nov 2025

Cited by 3 | Viewed by 1200

Abstract

Loess exhibits a pronounced reduction in strength under rainfall infiltration, making loess slopes highly susceptible to instability and failure during rainfall events. Although numerous studies have investigated the failure mechanisms of loess slopes under rainfall, most have overlooked the role of joints, which are intrinsic structural features of loess. To address this gap, this study selected the Jianxi landslide, located in Lingbao city of Henan province, as a representative case and employed a numerical simulation method to examine the influence of joints on the moisture fields and stability conditions of the Jianxi landslide. The results elucidate that the safety factor of the Jianxi landslide considering joints is 15.7% lower than the one measured without considering joints and identify the critical rainfall threshold leading to landslide instability to be 100 mm/d. Furthermore, when joints are considered, the sliding zone becomes deeper, indicating a larger landslide volume and more severe potential damage. This work provides new insights into the failure mechanism of loess landslides and offers a scientific basis for early warning. Full article

(This article belongs to the Special Issue Landslide on Hydrological Response)

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19 pages, 7605 KB

Open AccessArticle

Research and Application of Spatiotemporal Evolution Mechanism of Slope Based on Fiber Optic Neural Sensing

by Gang Cheng, Yujie Nie, Lei Zhang, Jinghong Wu, Dingfeng Cao, Ziyi Wang, Yongfei Wu and Haoyu Zhang

Water 2025, 17(18), 2710; https://doi.org/10.3390/w17182710 - 13 Sep 2025

Cited by 3 | Viewed by 1297

Abstract

Slope stability monitoring and evaluation are key means to ensure the safety of engineering projects. Firstly, the classification, principles, and characteristics of distributed fiber optic sensing technology for slope engineering are introduced, and the significant advantages of this technology in slope monitoring are analyzed. Secondly, taking the Three Gorges Reservoir landslide as a case study, laboratory experiments of slopes were conducted using spatiotemporally continuous fiber optic neural sensing technology. Through the slope physical model experiment under loading excavation and rainfall conditions, it is found that (1) the strain changes monitored by vertically laid sensing cables are more sensitive to loading (with a peak strain of about 1400 με), while horizontally laid optical cables are more sensitive to excavation processes (with a peak strain of about 8900 με). Specifically, the tension–compression strain transformation in horizontally laid sensing cables can be used to identify slope failure in advance. (2) Rainfall infiltration significantly weakens the strength of the slope soil. Only considering the loading situation, the slope experiences instability and failure under a load of 120 kg. Under the premise of the soil saturation caused by rainfall infiltration, the slope experienced instability and failure under a load of 20 kg. Therefore, compared to human engineering activities, rainfall has a more significant impact on the stability of the slope. This study sheds light on the slope failure mechanism and provides a scientific basis for early warning. Full article

(This article belongs to the Special Issue Landslide on Hydrological Response)

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14 pages, 9552 KB

Open AccessArticle

Time-Varying Reliability Analysis of the Majiagou Landslide

by Chun Lan, Hui Zhang, Guangqing Hu, Xiaojin Song and Heng Sun

Water 2025, 17(8), 1185; https://doi.org/10.3390/w17081185 - 15 Apr 2025

Cited by 1 | Viewed by 1024

Abstract

Rainfall and reservoir water level (RWL) fluctuations are the most important factors affecting reservoir landslide stability. Although extensive research has explored landslide stability under the combined effect of rainfall and RWL fluctuation, quantitative investigations on the individual contributions of rainfall and RWL fluctuation to landslide stability are limited. To address this issue, taking the Majiagou landslide in the Three Gorges Region (TGR) as an example, the seepage field of the Majiagou landslide was simulated and analyzed under three different scenarios: the individual effect of rainfall; the individual effect of RWL fluctuation; and the combined effect of rainfall and RWL fluctuation. The corresponding stability condition of the three scenarios was evaluated. The results show that the fluctuation of RWL is the critical factor that governs the stability of the Majiagou landslide. Specifically, when the water level drops rapidly from 165 m to 145 m, with an average rate of 0.859 m/d, the landslide safety factor decreases most significantly. The reason is that rapid water level decline creates outward-directed seepage forces that promote slope deformation. In contrast, rainfall has a limited effect on slope stability, with the safety factor only decreasing when rainfall exceeds 50 mm/d. This is because a seepage force directed outward from the slope develops only when rainfall reaches a certain threshold, leading to a reduction in the slope’s safety factor. In addition, this study reveals that the combined effect of rainfall and RWL fluctuations generates a synergistic amplification mechanism. Specifically, the safety factor variation under combined hydrological conditions significantly exceeds the arithmetic sum of individual rainfall-induced variation and RWL-induced variation. This study helps us understand how rainfall and RWL fluctuation affect slope stability by altering the seepage field, which is crucial for preventing landslides. Full article

(This article belongs to the Special Issue Landslide on Hydrological Response)

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