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Water-Related Landslide Hazard Process and Its Triggering Events

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

Deadline for manuscript submissions: 20 November 2025 | Viewed by 11074

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Special Issue Editor

Dr. Wei Liu

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Guest Editor

Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
Interests: landslide movement; debris flow formation; dynamic mechanism; numerical simu-lation; mountain disaster chain

Special Issue Information

Dear Colleagues,

Water plays a pivotal role in increasing the likelihood of landslide hazards through soil saturation, pressure elevation, lubrication, erosion induction, and contribution to hydraulic fracturing. Its impact on landslides encompasses various aspects, including triggering events, slope deformation, and mass movement. Understanding the interactions between water and slopes is crucial for accurately predicting and effectively mitigating landslide hazards. However, several unresolved issues persist.

This Special Issue delves into a systematic and comprehensive investigation of the role of water in landslide formation, focusing on theory, methodology, and practical applications. It aligns well with the established research domains of field investigations, remote sensing monitoring, numerical simulations, physical model experiments, and risk assessment, as well as the emerging areas of deep learning and the integration of environmental water and soil. Researchers are invited to submit their original and innovative work for potential inclusion in this Special Issue. High-quality reviews are also encouraged. Your valuable contributions that enrich our understanding of the role of water in landslide hazards are eagerly anticipated and warmly welcomed.

Dr. Wei Liu
Guest Editor

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Keywords

landslide
rainfall infiltration
pore water pressure
liquid–solid multiphase flow
hydrology
numerical simu-lation
risk assessment

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Published Papers (9 papers)

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Research

20 pages, 2924 KB

Open AccessArticle

Short-Term Displacement Prediction of Rainfall-Induced Landslides Through the Integration of Static and Dynamic Factors: A Case Study of China

by Chuyun Cheng, Wenyi Zhao, Lun Wu, Xiaoyin Chang, Bronte Scheuer, Jianxue Zhang, Ruhao Huang and Yuan Tian

Water 2025, 17(19), 2882; https://doi.org/10.3390/w17192882 - 2 Oct 2025

Viewed by 301

Abstract

Rainfall-induced landslide deformation is governed by both intrinsic geological conditions and external dynamic triggers. However, many existing predictive models rely primarily on rainfall inputs, which limits their interpretability and robustness. To address these shortcomings, this study introduces a group-based data augmentation method informed by displacement curve morphology and proposes a multi-slope predictive framework that integrates static geological attributes with dynamic triggering factors. Using monitoring data from 274 sites across China, the framework was implemented with a Temporal Fusion Transformer (TFT) and benchmarked against baseline models, including SVR, XGBoost, and LSTM models. The results demonstrate that group-based augmentation enhances the stability and accuracy of predictions, while the integrated dynamic–static TFT framework delivers superior accuracy and improved interpretability. Statistical significance testing further confirms consistent performance improvements across all groups. Collectively, these findings highlight the framework’s effectiveness for short-term landslide forecasting and underscore its potential to advance early warning systems. Full article

(This article belongs to the Special Issue Water-Related Landslide Hazard Process and Its Triggering Events)

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22 pages, 21059 KB

Open AccessArticle

Numerical Investigation of the Erosive Dynamics of Glacial Lake Outburst Floods: A Case Study of the 2020 Jinwuco Event in Southeastern Tibetan Plateau

by Shuwu Li, Changhu Li, Pu Li, Yifan Shu, Zhengzheng Li and Zhang Wang

Water 2025, 17(19), 2837; https://doi.org/10.3390/w17192837 - 27 Sep 2025

Viewed by 503

Abstract

Glacial lake outburst floods (GLOFs) represent increasingly common and high-magnitude geohazards across the cryosphere of the Tibetan Plateau, particularly under ongoing climate warming and glacier retreat. This study combines multi-temporal remote sensing imagery and detailed Flo-2D hydrodynamic modeling to investigate the erosive dynamics of the 2020 Jinwuco GLOF in Southeastern Tibetan Plateau. Key conclusions include: (1) The 2.35 km-long flood routing channel exhibits pronounced non-uniformity in horizontal curvature, channel width, and cross-sectional shape, significantly influencing flood propagation; five representative cross-sections divide the channel into six distinct segments. (2) Prominent lateral erosion occurred proximally to the dam, attributable to extreme erosive forces and high sediment transport capacity during peak discharge, with horizontal channel curvature further amplifying local impact and erosion. (3) Erosion rates were highest near the dam and in downstream narrow segments, while mid-reach sections with greater width experienced lower erosion. (4) Maximum flow depths reached 28.12 m in topographically confined reaches, whereas peak velocities occurred in upstream and downstream curved sections. (5) The apparent critical erosive shear stress of bank material is controlled not only by soil strength but also by flood dynamics and pre-existing channel morphology, indicating strong feedback between flow dynamics, channel morphology, and critical erosive shear stress of bank material. This study provides a generalized and transferable framework for analyzing GLOF-related erosion in data-scarce high-altitude regions, offering critical insights for hazard assessment, regional planning, and risk mitigation strategies. Full article

(This article belongs to the Special Issue Water-Related Landslide Hazard Process and Its Triggering Events)

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23 pages, 8136 KB

Open AccessArticle

Numerical Simulation Study on Seepage-Stress Coupling Mechanisms of Traction-Type and Translational Landslides Based on Crack Characteristics

by Meng Wu, Guoyu Yuan, Qinglin Yi and Wei Liu

Water 2025, 17(18), 2679; https://doi.org/10.3390/w17182679 - 10 Sep 2025

Viewed by 357

Abstract

This study examines the deformation and failure mechanisms of two reservoir bank landslides: the traction-type Baijiabao landslide and the translational Baishuihe landslide. Based on long-term monitoring data and a hydro-mechanical coupled numerical model of rainfall infiltration, we investigate the impact of crack depth on landslide stability. Results show that the Baishuihe landslide exhibits translational failure, initiated at the rear by tension cracks and rear subsidence, followed by toe uplift, whereas the Baijiabao landslide displays traction-type progressive failure, starting with toe erosion and later developing rear-edge cracks. Rainfall induces similar seepage patterns in both landslides, with infiltration concentrated at the crest, toe, and convex terrain areas. As crack depth increases, soil saturation near the cracks decreases nonlinearly, while the base remains saturated. However, displacement responses differ: Traction-type landslides exhibit opposing lateral movements with minimal vertical displacement. In contrast, translational landslides show displacement increasing with crack depth, dominated by gravity. These findings guide targeted mitigation: traction-type landslides require crack control and toe protection, while translational landslides need measures to block thrust transfer and monitor deep slip surfaces. This study offers new insights into the effect of crack depth on landslide stability, contributing to improved landslide hazard assessment and management. Full article

(This article belongs to the Special Issue Water-Related Landslide Hazard Process and Its Triggering Events)

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20 pages, 16378 KB

Open AccessArticle

Ice Avalanche-Triggered Glacier Lake Outburst Flood: Hazard Assessment at Jiongpuco, Southeastern Tibet

by Shuwu Li, Changhu Li, Zhengzheng Li, Lei Li and Wei Wang

Water 2025, 17(14), 2102; https://doi.org/10.3390/w17142102 - 15 Jul 2025

Viewed by 1215

Abstract

With ongoing global warming, glacier lake outburst floods (GLOFs) and associated debris flows pose increasing threats to downstream communities and infrastructure. Glacial lakes differ in their triggering factors and breach mechanisms, necessitating event-specific analysis. This study investigates the GLOF risk of Jiongpuco Lake, located in the southeastern part of the Tibetan Plateau, using an integrated approach combining remote sensing, field surveys, and numerical modeling. Results show that the lake has expanded significantly—from 2.08 km² in 1990 to 5.43 km² in 2021—with the most rapid increase observed between 2015 and 2016. InSAR data and optical imagery indicate that surrounding moraine deposits remain generally stable. However, ice avalanches from the glacier terminus are identified as the primary trigger for lake outburst via wave-induced overtopping. Mechanical and geomorphological analyses suggest that the moraine dam is resistant to downcutting erosion, reinforcing overtopping as the dominant failure mode. To assess potential impacts, three numerical simulation scenarios were conducted based on different avalanche volumes. Under the extreme scenario involving a 5-million m³ ice avalanche, the modeled peak discharge at the dam site reaches approximately 19,000 m³/s. Despite the high flood magnitude, the broad and gently sloped downstream terrain facilitates rapid attenuation of flood peaks, resulting in limited impact on downstream settlements. These findings offer critical insights for GLOF hazard assessment, disaster preparedness, and risk mitigation under a changing climate. Full article

(This article belongs to the Special Issue Water-Related Landslide Hazard Process and Its Triggering Events)

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15 pages, 5758 KB

Open AccessArticle

Investigation of Natural and Human-Induced Landslides in Red Basaltic Soils

by Huu Son Nguyen, Thi Ly Khau and Trung Tin Huynh

Water 2025, 17(9), 1320; https://doi.org/10.3390/w17091320 - 28 Apr 2025

Cited by 2 | Viewed by 1438

Abstract

Landslides are mass movements of rock, soil, or debris under the influence of gravity. These phenomena occur due to the loss of slope stability or imbalance of external loads. The intensity and consequences of landslides depend on various factors such as topography, geological structure, and precipitation regime. This study investigates the characteristics of rainfall-induced landslides in red basaltic soils on the basis of field investigations, geotechnical surveys, and slope stability modeling under anthropogenic triggers. The results indicate a close relationship between soil moisture and shear strength parameters, which significantly influence slope stability. A real-time observation system recorded groundwater level fluctuation in relation to surface runoff and precipitation rates. It is revealed that intense rainfall and low temperatures regulate soil moisture, resulting in a reduction of cohesion and shear strength parameters. These findings enhance the understanding of landslide mechanism in basaltic soil regions, which are highly sensitive to precipitation. The results also highlight that human activities play a significant role in triggering landslides. Therefore, a real-time monitoring system for rainfall, soil moisture, and groundwater is essential for early warning and supports the integration of smart technologies and Internet of Things (IoT) solutions in natural disaster management. Full article

(This article belongs to the Special Issue Water-Related Landslide Hazard Process and Its Triggering Events)

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20 pages, 9287 KB

Open AccessArticle

Snow Melting Experimental Analysis on a Downscaled Shallow Landslide: A Focus on the Seepage Activity of the Snow–Soil System

by Lorenzo Panzeri, Michele Mondani, Monica Papini and Laura Longoni

Water 2025, 17(4), 597; https://doi.org/10.3390/w17040597 - 19 Feb 2025

Cited by 1 | Viewed by 982

Abstract

The stability of slopes is influenced by seasonal variations in thermal, hydrological, and mechanical processes. This study investigates the role of snowmelt in triggering shallow landslides through controlled laboratory experiments simulating winter, spring, and summer conditions. Snowpack dynamics and water movement were analyzed to understand filtration, infiltration, and runoff mechanisms. The results show that during winter, snow acts as a protective layer, slowing infiltration through its insulating and loading effects. In spring, rising temperatures melt snow, increasing water infiltration and filtration, accelerating soil saturation, and triggering slope failures. Summer rainfall-induced landslides exhibit distinct mechanisms, driven by progressive saturation. The transition from winter to spring highlights a critical phase where snowmelt interacts with warmer soils, intensifying slope instability risks. Numerical simulations using HYDRUS 1D validated the experimental findings, demonstrating its utility in modeling infiltration under varying thermal gradients. This study underscores the importance of incorporating snowmelt dynamics into landslide risk assessments and early warning systems, particularly as climate change accelerates snowmelt cycles in mountainous regions. These findings provide essential insights into seasonal variations in collapse mechanisms, emphasizing the need for further research to address the increasing impact of snowmelt in shallow landslides. Full article

(This article belongs to the Special Issue Water-Related Landslide Hazard Process and Its Triggering Events)

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24 pages, 15593 KB

Open AccessArticle

Study on Shallow Landslide Induced by Extreme Rainfall: A Case Study of Qichun County, Hubei, China

by Yousheng Li, Echuan Yan and Weibo Xiao

Water 2025, 17(4), 530; https://doi.org/10.3390/w17040530 - 12 Feb 2025

Cited by 7 | Viewed by 1433

Abstract

In light of the increasing frequency of extreme rainfall events, there has been a concomitant rise in landslides triggered by such precipitation. Despite the extensive research conducted on rainfall-induced landslides, the practical implementation of these findings is constrained by geological and environmental factors. Notably, there is a paucity of research on rainfall-induced shallow landslides in Hubei Province, China. Therefore, this study analyzes the fundamental characteristics and rainfall characteristics of landslides induced by multiple rounds of extreme rainfall in Qichun County in June and July 2016. The study explores the influence of five variables—namely, altitude, slope, slope aspect, stratum lithology, and rainfall—on landslides. The study uses numerical analysis to reveal the initiation mechanism of landslides. The research conclusions are as follows: The landslides within the study area are closely related to its natural topography, stratum lithology, and human activities. The majority of landslides are triggered by short-term extreme rainfall, while a smaller number are related to long-term continuous rainfall. The formation mechanism of landslides is primarily driven by dynamic water seepage, and the destruction process often lags behind the rainfall process. The conclusions can provide theoretical guidance for risk prevention and early warning of rainfall-induced landslides in the region. Full article

(This article belongs to the Special Issue Water-Related Landslide Hazard Process and Its Triggering Events)

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23 pages, 11153 KB

Open AccessArticle

Landslide Susceptibility Mapping Using an LSTM Model with Feature-Selecting for the Yangtze River Basin in China

by Peng Zuo, Wen Zhao, Wenjun Yan, Jiming Jin, Chaoying Yan, Biqiong Wu, Xiangyu Shao, Weijie Wang, Zeyu Zhou and Jin Wang

Water 2025, 17(2), 167; https://doi.org/10.3390/w17020167 - 10 Jan 2025

Cited by 3 | Viewed by 1971

Abstract

Landslide susceptibility mapping (LSM) is crucial for disaster prevention in large, complex regions characterized by high-dimensional data. This study proposes a Feature-Selecting Long Short-Term Memory (FS-LSTM) framework to enhance LSM accuracy by integrating feature selection techniques with sequence-based modeling. The Mean Decrease Impurity (MDI) and Information Gain Ratio (IGR) were used to rank landslide conditioning factors (LCFs), and these rankings structured FS-LSTM inputs to assess the impact of feature ordering on model performance. Feature-ordering experiments demonstrated that structured rankings significantly improve model accuracy compared to randomized inputs. Our model outperformed traditional machine learning algorithms, such as logistic regression and Support Vector Machine, as well as standard deep learning models like CNN and basic LSTM, achieving a score of 0.988. The MDI and IGR rankings consistently identified soil type, elevation, and average annual cumulated rainfall as the most influential LCFs, improving the interpretability of the results. Applied to the Yangtze River Basin, the FS-LSTM framework effectively identified landslide-prone areas, aligning with known geological patterns. These findings highlight the potential of combining feature selection with sequence-sensitive deep learning to enhance the robustness and interpretability of LSM. Future studies could expand this approach to other regions and incorporate real-time monitoring systems for dynamic disaster management. Full article

(This article belongs to the Special Issue Water-Related Landslide Hazard Process and Its Triggering Events)

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20 pages, 7905 KB

Open AccessArticle

Study on Soil and Water Loss on Slope Surface and Slope Stability Under Rainfall Conditions

by Fengzhan Hou, Zhenqiang Ni, Shihao Wang, Hangeng Sun, Fengxiao Zhao, Wei Zhong and Yongsheng Zhang

Water 2024, 16(24), 3643; https://doi.org/10.3390/w16243643 - 18 Dec 2024

Cited by 3 | Viewed by 1687

Abstract

For a binary structure slope with a soil layer on the top and a rock layer on the bottom, during the rainfall process, surface runoff will cause soil and water loss on the slope surface and damage to the slope environment. When rainwater infiltrates into the slope, the pore water pressure in the soil gradually increases, the shear strength of the soil decreases, and a weak zone is formed at the soil–rock interface, which has a significant impact on the stability of the slope. Therefore, to study the soil and water loss on the slope surface and the stability of the slope under rainfall conditions, we used theoretical analysis, indoor model tests, and numerical simulations to conduct a comprehensive exploration of this issue, and the following conclusions were formed: the pore water pressure in the shallow layer is greater than that in the deep layer, and the pore water pressure at the toe of the slope is greater than that at the top of the slope; as the slope gradient increases, the time when the pore water pressure at the toe of the slope begins to respond gradually speeds up; the slope displacement first occurs at the lower part of the slope, then in the middle, and finally at the upper part; the time when the displacement at each point on the slope surface begins to respond gradually speeds up with the increase in the slope; the damage form at a small slope gradient is mainly flow sliding, and the damage process is continuous; the damage form at a large slope gradient is mainly flow sliding and overall sliding, and the damage process is continuous and sudden; when the binary structure slope fails, the sliding surface includes the internal sliding surface of the soil and the sliding surface at the soil–rock interface, but when the slope gradient is small, the relative sliding at the soil–rock interface is small, and a continuous sliding surface cannot be formed; and when the slope gradients are small (30° and 40°), the displacement decreases continuously from top to bottom, and no overall sliding surface is formed. The larger values of plastic strain mainly occur in the upper and middle parts of the slope, there is no formation of a continuous plastic strain zone, and the damage mode is flow sliding; when the slope gradients are large (50° and 60°), the displacement is the largest in the upper part, and a large displacement also occurs in the lower part, forming a sliding surface that penetrates through the soil–soil and rock–soil layers. The larger values of plastic strain occur in the upper, middle, and lower parts of the slope, a continuous plastic strain zone is formed, and the damage modes are flow sliding and overall sliding; numerical simulations were carried out on a typical actual slope, and consistent results were obtained. Full article

(This article belongs to the Special Issue Water-Related Landslide Hazard Process and Its Triggering Events)

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