Landslide Behavior Research Articles

Exploring the integration of InSAR data into climate‐driven creep models to assess slow‐moving landslide dynamics

AbstractThe deformation behavior of slow‐moving large landslides is often governed by rainfall characteristics. Based on observational data such as precipitation, deformation measurement, and pore water pressure measurements in the slip zone, in many cases a strong correlation between strong rainfall events, a time‐delayed increase of pore water pressures in the slip zone, and, simultaneously to this, an increase of the deformation rate of the landslide can be found. Based on such detailed data, calculation models, which couples the relation between rainfall characteristics and the development of pore water pressures in the slip zone on one hand and the deformation behavior of the slope on the other, can be developed and be used for a better understanding and a prediction of deformation behavior of such slow‐moving landslides. Climate change issues will lead to a change in rainfall frequency and magnitude and annual temperature distribution characteristics in several regions worldwide, which will also lead to changes in the deformation behavior of such large landslides. In this contribution, satellite‐based interferometric synthetic aperture radar (InSAR) data are discussed to be used as source for deformation measurements as bases for prediction models describing the rainfall‐triggered deformation behavior of slow‐moving landslides.

Incorporating Effects of Slope Units and Sliding Areas into Seismically Induced Landslide Risk Modeling in Tectonically Active Mountainous Areas

Traditional Newmark models estimate earthquake-induced landslide hazards by calculating permanent displacements exceeding the critical acceleration, which is determined from static factors of safety and hillslope geometries. However, these studies typically predict the potential landslide mass only for the source area, rather than the entire landslide zone, which includes both the source and sliding/depositional areas. In this study, we present a modified Newmark Runout model that incorporates sliding and depositional areas to improve the estimation of landslide chain risks. This model defines the landslide runout as the direction from the source area to the nearest river channel within the same slope unit, simulating natural landslide behavior under gravitational effects, which enables the prediction of the entire landslide zone. We applied the model to a subset of the Minjiang Catchment affected by the 1933 MW 7.3 Diexi Earthquake in China to assess long-term landslide chain risks. The results indicate that the predicted total landslide zone closely matches that of the Xinmo Landslide that occurred on 24 June 2017, despite some uncertainties in the sliding direction caused by the old landslide along the sliding path. Distance-weighted kernel density analysis was used to reduce the prediction uncertainties. The hazard levels of the buildings and roads were determined by the distance to the nearest entire landslide zone, thereby assessing the landslide risk. The landslide dam risks were estimated using the kernel density module for channels blocked by the predicted landslides, modeling intersections of the total landslide zone and the channels. High-risk landslide dam zones spatially correspond to the locations of the knickpoints primarily induced by landslide dams, validating the model’s accuracy. These analyses demonstrate the effectiveness of the presented model for Newmark-based landslide risk estimations, with implications for geohazard chain risk assessments, risk mitigation, and land use planning and management.

Multi-scale investigation on staged deterioration mechanism of sliding-zone soils induced by reservoir fluctuations

Water level fluctuations in the reservoir deteriorate soils and rocks on the bank landslides by drying-wetting (D-W) cycles, which results in a significant decrease in mechanical properties. A comprehensive understanding of deterioration mechanism of sliding-zone soils is of great significance for interpreting the deformation behavior of landslides. However, quantitative investigation on the deterioration characteristics of soils considering the structural evolution under D-W cycles is still limited. Here, we carry out a series of laboratory tests to characterize the multi-scale deterioration of sliding-zone soils and reveal the mechanism of shear strength decay under D-W cycles. Firstly, we describe the micropores into five grades by scanning electron microscope and observe a critical change in porosity after the first three cycles. We categorize the mesoscale cracks into five classes using digital photography and observe a stepwise increase in crack area ratio. Secondly, we propose a shear strength decay model based on fractal theory which is verified by the results of consolidated undrained triaxial tests. Cohesion and friction angle of sliding-zone soils are found to show different decay patterns resulting from the staged evolution of structure. Then, structural deterioration processes including cementation destruction, pores expansion, aggregations decomposition, and clusters assembly are considered to occur to decay the shear strength differently. Finally, a three-stage deterioration mechanism associated with four structural deterioration processes is revealed, which helps to better interpret the intrinsic mechanism of shear strength decay. These findings provide the theoretical basis for the further accurate evaluation of reservoir landslides stability under water level fluctuations.

Computational modeling of near-fault earthquake-induced landslides considering stochastic ground motions and spatially varying soil

Landslides represent a large-deformation process influenced by various factors of uncertainty, such as types of ground motion (GM), randomness of GMs, and spatial variability of soils. The behavior of landslides is profoundly affected, making their assessment and measurement challenging. This paper proposes a computational approach for simulating the large-deformation process of landslides based on three-dimensional (3D) non-ordinary state-based peridynamics (NOSBPD). The analysis results of NOSBPD indicate that the mean runout distance triggered by pulse-like ground motions (PLGMs) is 16% greater than that induced by non-pulse ground motions (NPGMs), suggesting that PLGMs exhibit higher destructiveness. Besides, this paper establishes a runout distance assessment framework by considering the stochastic nature of PLGMs. This framework allows for the evaluation of the specific risk probability of landslides caused by stochastic PLGMs that match the target spectrum specified by codes. By introducing the theory of random fields and implementing a coupled procedure in peridynamics, we conducted a detailed analysis of the impact of spatial heterogeneity on the evolution process and consequences of landslides. Additionally, compared to two-dimensional (2D) analysis, the mean runout distance obtained from 3D analysis increased by 27.5%. This suggests that 2D analysis may underestimate the consequences of landslides. The findings of this study can serve as a scientific foundation for predicting the extent and scope of landslides triggered by near-fault earthquakes.

DEM analysis on diffuse failure of soil slope triggered by earthquakes

Earthquake-induced diffuse landslide can cause considerable harm. This study used discrete element modeling (DEM) to investigate the diffuse failure of soil slopes triggered by earthquakes. Initially, the DEM was validated through demonstrating satisfactory agreement with the experimental results of a shaking table test. Subsequently, the time and most realistic location of diffuse failure occurrence was quantified using discrete second-order work. Diffuse failure was associated with abrupt fluctuation of the second-order work and a local burst of kinetic energy. Within the context of second-order analysis, the frictional resistance of the slope was analyzed. Both the in-phase and the out-of-phase evolutions of frictional resistance and seismic loading were captured. The distinctive in-phase response was identified as an important feature of diffuse failure. Moreover, the predominant influence of particle rolling behavior on frictional resistance development during diffuse failure progression was highlighted. The magnitude and anisotropy of the contact force are profoundly influenced by the input vibration amplitude, resulting in variations in frictional resistance, which suggests that stress-induced anisotropy plays a crucial role in diffuse failure. The results of this study shed light on the grain-scale failure mechanisms of earthquake-induced landslides, and serve as the basis for elucidating the failure behavior of seismic-induced landslides.

Numerical Analysis of Seepage Field Response Characteristics of Weathered Granite Landslides under Fluctuating Rainfall Conditions

The threat and destructiveness of landslide disasters caused by extreme rainfall are increasing. Rainfall intensity is a key factor in the mechanism of rainfall-induced landslides. However, under natural conditions, rainfall intensity is highly variable. This study focuses on the Fanling landslide and investigates the effects of varying rainfall intensity amplitudes, rainfall durations, and total rainfall amounts on landslide behavior. Three experimental groups were established, and ten rainfall conditions were simulated numerically to analyze the seepage field response of the landslide under fluctuating rainfall conditions. The results indicate that (1) there are positive correlations between the final pore pressure and both the amplitude and duration of rainfall intensity; (2) the pore water pressure response in the upper slope changes significantly, initiating deformation; and (3) the total rainfall amount is the most direct factor affecting the pore pressure response and landslide deformation. Compared to long-term stable rainfall, short-term fluctuating rainstorms are more likely to trigger landslides. These findings enhance our understanding of landslide mechanisms under fluctuating rainfall, providing valuable insights for disaster prevention and mitigation.

A material point method analysis of failure mechanism and kinematic behavior of rainfall-induced landslide

A material point method analysis of failure mechanism and kinematic behavior of rainfall-induced landslide

Deformation and collapse of rock slopes considering weak plane orientation

Some slopes experience multiple slides without collapse, while other slopes collapse once they are unstable. The early warning of slope collapse is a difficult but important subject. Considering the influence of weak planes on rock slope deformation and collapse is helpful for interpreting the behavior of deep-seated landslides and designing an early warning system. To investigate the deformation behavior of rock slopes with consideration on weak planes, artificial cemented sand plates were produced and stacked to form physical slope models with different weak plane orientations, where inclined loading was applied to induce the deformation and collapse of the slope. In addition, the deformation of real slopes was examined based on topographic features. The average strain at collapse is referred to as the critical strain, whose value changes for various slopes. Sorted by critical strain in descending order, the slope models include an anaclinal slope with 60° weak planes, an anaclinal slope with 30° weak planes, a cataclinal slope where the 30° weak planes coincide with the slope face, and a cataclinal slope with daylighting 20° weak planes. Similar to the experimental results, anaclinal slopes also present greater average strain values than cataclinal slopes for real slopes. A smaller critical strain implies a higher possibility for slope collapse when unstable. Local deformation does not always lead to collapse, but as the average velocity and the average strain rate of the sliding body increase, or the velocity ratio (VR) between the upper and lower parts of the sliding body approaches 1, a sliding surface inside the slope is likely developing and coalescing. Hence, such deformation features may contribute to a landslide warning system.

Characterizing Seasonality and Trend From In Situ Time‐Series Observations Using Explainable Deep Learning for Ground Deformation Forecasting

AbstractGround deformation, a critical indicator of geohazard evolution, exhibits both seasonal fluctuations and long‐term trend changes. This study explores interpretable deformation forecasting using an explainable deep learning approach, utilizing field observation data to extract and characterize these critical features from time series. We demonstrate that extracting and utilizing shared, similar seasonal and trend features across multi‐point observations significantly enhances ground deformation forecasting accuracy. Notably, the extracted seasonal features reveal the dominant role of the hydrological response in deformation at seasonal timescales, providing insights into the underlying source of predictability. This proof‐of‐concept study highlights the promise of interpretable ground deformation forecasting, with applications expected to encompass landslide behavior, volcanism, or seismic activity.

Slope Stability Analysis Based on the Explicit Smoothed Particle Finite Element Method

A landslide is a common natural disaster that causes environmental damage, casualties and economic losses, which seriously affects the sustainable development of society. In geomechanics, it is one of the largest deformation problems. Herein, the GPU-accelerated explicit smoothed particle finite element method (eSPFEM) for large deformation analysis in geomechanics was developed on the CUDA platform based on high-performance computing using a self-designed eSPFEM program code. The eSPFEM combines the strain smoothing nodal integration techniques found in the particle finite element method (PFEM) framework, which allows for the use of low-order triangular elements without volume locking and avoids frequent information transfer and mapping errors between Gaussian points and particles in PFEM. A numerical simulation of slope instability using the eSPFEM and based on a strength reduction technique was conducted using various examples, including a cohesive homogeneous slope, a non-cohesive homogeneous slope, a non-homogeneous slope and a slope with a thin soft band. The calculation results show that the eSPFEM can be applied to slope stability analysis under different working conditions, simulating the entire process of slope instability initiation, sliding and reaccumulation, and obtaining reliable FOS values. A numerical simulation was conducted to analyse a landslide that occurred in the Zhangjiazhuang tunnel on the Lanzhou–Xinjiang high-speed railway line on 18 January 2016. A natural unsaturated soil slope, a soil slope with a high moisture content and a soil slope with a high moisture content subjected to an earthquake were analysed. The findings of this study are in good agreement with the actual slope failure conditions. The primary triggers identified for the landslide were heavy rainfall and earthquakes. The verification results indicate that the eSPFEM can effectively simulate an actual landslide case, showcasing high accuracy and applicability in simulating the large deformation behaviour of landslides.

Landslide development model based on tree-ring data and quantification of the magnitude of landslide movements

Analysis of landslide events by studying anomalies in tree-ring series of disturbed trees provides unique data on past landslide behaviour. However, a comprehensive spatio-temporal model of landslide evolution using dendrogeomorphic data has not yet been constructed. In terms of determining landslide hazard, one of the key issues, besides the frequency of movements, is their magnitude. Thus, this study is aimed at constructing a model of landslide area development including quantification of landslide displacements. Moreover, not only standard macroscopic growth disturbance but also quantitative anatomical parameters of tree rings were used as a basis for these objectives. The research was carried out on a landslide of the Váh river bank (Slovakia) using data from 32 disturbed black locust (Robinia pseudoacacia L.) individuals. Anatomical analysis revealed a reduction in the vessel lumen area in response to landslide movements. The response was associated with tension wood formation or damage to the tree root system. The reconstructed chronology of landslide movements revealed the main phase of landslide in 2017 and its subsequent evolution. Based on the chronological information and the morphology of the landslide body, a spatio-temporal model of the landslide evolution from the initial slope failure to the present was constructed. The model showed the interrelationships between vertical displacement of the main block, compression and tension deformations within the landslide body, and lateral erosion of the landslide toe by the river. Quantification of the magnitude of landslide displacements was realized from exposed roots in tension cracks but also from the ruptured tree trunk. The limitations and advantages of both approaches are discussed.

Smoothed particle hydrodynamics approach for modelling submerged granular flows and the induced water wave generation

In this study, we develop a Smoothed Particle Hydrodynamics (SPH) 2D-model for simulating fully submerged granular flows and their arising water waves. The granular particles are characterised by a non-Newtonian flow pattern, following a Casson constitutive law, generalised by applying the infinitesimal strain theory to avoid numerical singularities inherited from the original law. The implementation of this rheological model on the weakly compressible viscous Navier-Stokes equations enables the simultaneous modelling of the motion of granular flows and their resulting water waves, establishing a monolithic representation of fluid-structure coupling. The novelty of this model lies in the numerical continuity of the generalised rheological model based mainly on the yield stress criterion, which is computed purely from the mechanical properties of granular materials, including internal friction, cohesion, and viscosity coefficients. The proposed SPH model is validated through two benchmarks available in the literature, representing a submarine landslide along an inclined plane and an immersed granular column collapse. The outcomes of our study illustrate the effectiveness of the proposed model in accurately predicting the motions of submerged granular masses and their resulting water waves, which is crucial for accurately predicting the behaviour of underwater landslides and other natural hazards.

Experimental study on the failure of loose accumulation landslides under rainfall conditions

Rainfall plays a pivotal role in triggering the failure of loose accumulation landslides. To understand their stability, it is essential to explore the deformation, failure patterns, fine particle migration, and infiltration behavior of such landslides under rainy conditions. Employing the Yuqiupo landslide as a case study, this research dissects the fundamental attributes of the Yuqiupo landslide through geological examinations. Moreover, the study replicates the failure of the loose accumulation landslide via artificial rainfall experiments. By employing acquired data on soil volumetric water content and matrix suction from these experiments and observing measurable shifts in the landslide’s failure progression and rainfall circumstances, the water-hydraulic conditions of the accumulation landslide are meticulously dissected. The conducted experiments disclose that the failure of the loose accumulation landslide emanates from the combined effects of preferential flow and matrix flow within unsaturated conditions. Rainfall triggers an elevation in soil moisture content and a concurrent decrease in matrix suction, compromising the slope’s stability and ultimately causing the landslide. Furthermore, our research includes a quantitative analysis of changes in particle size distribution before and after the landslide’s failure. This endeavor underscores the influence of distinct failure modes on the migration of fine particles, with these migration patterns distinctly shaped by prevailing rainfall conditions.

Optical and Thermal Image Processing for Monitoring Rainfall Triggered Shallow Landslides: Insights from Analogue Laboratory Experiments

This study explores the innovative use of digital image processing (DIP) techniques, also named PhotoMonitoring, for analysing the triggering conditions of shallow landslides. The approach, based on the combination of optical and infrared thermographic imaging (IRT), was applied to a laboratory-scale slope, reproduced in a flume test apparatus. Three experiments were conducted to replicate rainfall-induced shallow landslides, applying change detection and digital image correlation analysis to both optical and thermal images. The method combines IRT’s ability to measure ground surface temperature changes with DIP’s capacity to track movement and displacement. Results showed the high reliability of the displacement time-series obtained through IRT-DIP with respect to the reference optical-DIP. The IRT-DIP technique also detects anomaly signals two minutes before landslide occurrence that can be regarded as a possible failure precursor. This study testifies to the potential of image analysis as a remote sensing technique, demonstrating the ability of DIP to capture the dynamics of shallow landslides, as well as the advantages of optical–IRT combinations to follow slope deformation processes during night-time. This approach, if properly adapted to real-scale scenarios, may contribute to a better understanding of landslide behaviour, improve landslide monitoring strategies, and promote more effective early warning systems (EWS).

Deformation Behavior and Reactivation Mechanism of the Dandu Ancient Landslide Triggered by Seasonal Rainfall: A Case Study from the East Tibetan Plateau, China

In recent years, numerous ancient landslides initially triggered by historic earthquakes on the eastern Tibetan Plateau have been reactivated by fault activity and heavy rainfall, causing severe human and economic losses. Previous studies have indicated that short-term heavy rainfall plays a crucial role in the reactivation of ancient landslides. However, the deformation behavior and reactivation mechanisms of seasonal rainfall-induced ancient landslides remain poorly understood. In this paper, taking the Dandu ancient landslide as an example, field investigations, ring shear experiments, and interferometric synthetic aperture radar (InSAR) deformation monitoring were performed. The cracks in the landslide, formed by fault creeping and seismic activity, provide pathways for rainwater infiltration, ultimately reducing the shear resistance of the slip zone and causing reactivation and deformation of the Dandu landslide. The deformation behavior of landslides is very responsive to seasonal rainfall, with sliding movements beginning to accelerate sharply during the rainy season and decelerating during the dry season. However, this response generally lags by several weeks, indicating that rainfall takes time to infiltrate into the slip zone. These research results could help us better understand the reactivation mechanism of ancient landslides triggered by seasonal rainfall. Furthermore, these findings explain why many slope failures take place in the dry season, which typically occurs approximately a month after the rainy season, rather than in the rainy season itself.

The 1st Willy Alvarenga Lacerda lecture: New perspectives for landslide analysis and management

Landslides are widespread all over the world, often causing significant consequences in terms of loss of life and property damage. This explains why many scientists from Geology and Geotechnics have long been engaged in solving complex problems of both theoretical and practical interest. Geologists have systematically investigated the common characteristics of landslides proposing several classification systems, while not providing general laws for the triggering and evolution stages. Geotechnical engineers have implemented models to quantitatively analyze these stages but not to develop a general framework for typical landslide behaviors. Aimed to bridge the scientific branches dealing with landslides and based on the past efforts of many researchers all over the world, this paper focuses on deep-seated landslides developing along an existing and/or a new slip surface and multiple shallow landslides that may involve large areas in short periods of time. Considering that these phenomena are often analyzed at one single topographical scale and through monodisciplinary approaches, the paper proposes a new vision that highlights the possibility of a landslide management modern and open to the advanced technologies.

Prediction of landslide velocity and displacement from groundwater level changes considering the shear rate-dependent friction of sliding zone soil

In reactivated slow-moving landslides, the prediction of velocity and displacement is a crucial issue for understanding landslide kinematics and realizing warning systems. A variety of data-based numerical models have been used to predict landslide displacement; however, kinematics-based models, which consider the shear behaviors of soils within the sliding zone that fundamentally control landslide movement, have been relatively limited. In the present research, the Tangjiao landslide in the Three Gorges Reservoir (TGR) in China was taken as a case study. The monitored ground displacement from March 2007 to September 2016 and deformation signs observed in the field survey show that the Tangjiao landslide experienced slow movement with the ground displacement increasing stepwise in response to seasonal rainfall and periodic fluctuation of the reservoir water level. We performed a rate-stepped continuous ring shear test on two specimens remolded from the sliding zone soil at shear rates ranging from 0.01 to 10 mm/s. The test results show that the residual strengths of both specimens show a nonmonotonic shear rate dependency, i.e., a weak negative shear rate dependency (fitted by an exponential law) followed by a significant positive dependency (fitted by a linear law). The transition from a negative shear rate dependency to a positive shear rate dependency may be attributed to the change in shear mode when the shear rate exceeds a critical value. This complex shear rate-dependent residual behavior regulates the movement of the Tangjiao landslide in the reactivated state. On this basis, a kinematics-based model for predicting landslide velocity and displacement was proposed by taking into account the shear rate-dependent friction of the sliding zone soil. This model can reproduce the velocity and displacement of the Tangjiao landslide from the change in groundwater level (i.e., stress perturbations in this paper). The results suggest that by using this model, the well-investigated material parameters can enhance the prediction reliability and accuracy of landslide behavior. Our proposed approach, with the ability to reliably predict landslide velocity and displacement, such as the Tangjiao landslide in this work, has important implications for predicting movement trends and developing early warning systems for reactivated slow-moving landslides, especially translational landslides under similar geological conditions.

Geomorphic understanding of loess landslides activity on the loess tableland:A case study in the Bailu Tableland, China

Loess landslides, predominantly triggered by human activity and precipitation, dominate the geomorphological evolution of extensive regions of the Chinese Loess Plateau. Tablelands constitute a large proportion of this Loess Plateau. Although the area has a long history of human occupation, the Bailu Tableland is relatively poorly studied. Recent landslide events along the edge of the tableland significantly affected lives and livelihoods. To develop a better understanding of geomorphological evolution and develop appropriate hazard management and mitigation strategies, we characterized recent landslide activity and determined whether there are discernable trends in activity. We used Unmanned Aerial Vehicle (UAV) observations, Interferometric Synthetic Aperture Radar (InSAR) monitoring, and Digital Terrain Analysis (DTA) to observe significant differences in the position, shape, and magnitude between old and new landslides. The geomorphological evolution of the tableland was initially driven by large landslides, while current and future morphological development is more likely affected by small landslide events. We demonstrate the successful application of InSAR to investigate potential landslides in well-vegetated loess landscapes and show that loess landslides tend to develop on slopes with high relative relief and high topographic wetness associated with gully erosion. Unlike landslides induced by groundwater variations in the Heifangtai and South Jingyang tablelands, precipitation and infrastructure construction form the main controls on landslide activity in the Bailu Tableland. We propose two geomorphological evolution models that describe loess tableland recession caused by landslides. The results from this research contribute to a better understanding of the reactivation behavior of landslides along loess tablelands, provide a scientific foundation for landslide hazard and risk management, and supplement understanding of the geomorphological evolution of loess tableland landscapes.

Tree-ring eccentricity-based dating of landslide movements: Defining a new effective approach

Dendrogeomorphic dating of landslide movements is nowadays a frequently used tool for understanding past landslide behaviour. One of the most widespread growth disturbances induced by landslides is tree-ring eccentricity. However, extracting the landslide signal from the time series of its values is a challenge that has suffered from many shortcomings so far. In this study, a new approach based on the detection of changes in tree-ring eccentricity values was developed. The approach, which combines the advantages of previous approaches, was tested on four landslides in different physical-geographical conditions with different tree species of different ages. For all landslides, the year of activity was well known and analyses of the results focused on this year. The tested methodological approach successfully detected all these known years. However, it also detected a higher amount of noise in two cases, which may have been caused by imperfect knowledge of pre-landslide slope activity or creep. An important feature identified in the results obtained by the approach was their potential independence of tree age. As with the use of other macroscopic growth disturbances, this approach does not allow dating with seasonal accuracy. However, compared to previous methodological approaches working with tree-ring eccentricity analysis, the new approach demonstrated significant advantages. The procedure does not truncate the reconstructed time series, does not smooth the landslide signal, and uses exactly defined landslide signal thresholds.

Research on the Carter Method for the location of sliding surfaces based on a numerical study

In order to investigate the potential location and magnitude of a landslide, the information regarding the location and shape of the sliding surface is important. However, obtaining such information through underground investigations is costly and time-consuming. A method proposed by Carter and Bentley (1985) provides an approach to predict the sliding surface based on ground surface information. With help of advanced techniques such as UAVs and SAR satellites, Carter’s method has been utilized in field sites of potential landslide areas recently. Geophysical surveys and drilling data are commonly used validation data, but the temporal and spatial resolutions of these data are rough and rare. For this problem, this study generated high temporal and spatial resolution data of landslide behaviour by a physically based model and these data were utilized to investigate the capability and limitations of Carter’s method. Firstly, a scenario of slope failure on a 30-degree slope was performed by a numerical model using the material point method (MPM). Next, Carter’s method was applied to predicted the sliding surface using ground surface data obtained from the MPM simulation, and the results were compared with the sliding surface data from the MPM simulation. Finally, we perform an error analysis using the concordance correlation coefficient (CCC) to assess the reliability of Carter’s method. The findings of this study contribute to understanding the capabilities and limitations of Carter’s method in landslide analysis and provide insights for improving landslide risk assessment and mitigation strategies.