Landslide Movement Research Articles

Temporal development of the displacement field of the Ponzano landslide in February 2017

The conducted research determined the temporal evolution of the displacement field for the Ponzano landslide case study. The offset-tracking method, so far used mainly for the relatively rapid but uniform displacement of glaciers, was tested for the 2017 study of the Ponzano landslide in Italy. The suitability of the method for high-resolution TerraSAR-X and medium-resolution Sentinel-1 imagery was investigated. The results proved the applicability of the OT method for studying processes with high and variable displacement dynamics. However, for such purposes, high-resolution radar data are crucial. With an uncertainty in the determination of residual displacements of about ±1 m, it was shown that the values of residual displacements occurring up to several days after the main phase of landslide movements are within the range of uncertainty but are determinable. The research conducted in the paper filled a gap in the analysis of the phenomenon just after the main movement phase. It allowed determination of the time and speed of extinction of landslide movements.

Step-like displacement prediction and failure mechanism analysis of slow-moving reservoir landslide

Landslides triggered by extreme rainfall due to global climate change are becoming more frequent. The Earth surface processes activity and landform evolution caused by landslide movement seriously affect human survival and the environment. In recent years, the reservoir slope located in the Three Gorges reservoir (TGR) area has been subject to the combined effects of extreme rainfall and reservoir regulation, which have been highly susceptible to inducing landslides. Reservoir landslides usually show step-like slow movement characteristics. The causes of slow-moving landslides are complex, the mechanisms behind them are difficult to grasp, and it may evolve into violent landslide disasters. Therefore, accurately predicting step-like displacement in slow-moving landslides is an effective solution for risk reduction. To achieve the accurate prediction of the step-like displacement of slow-moving landslides and the analysis of the failure mechanism, this study establishes a prediction model applicable to step-like displacement prediction of slow-moving reservoir landslides is developed based on 16 years of continuously monitored cumulative displacement of the Jiuxianping landslide, combined with the Empirical Mode Decomposition (EMD) method and the Improved Particle Swarm Optimization (IPSO) optimized the Long short-term memory (LSTM) neural network. This approach can effectively improve step-like displacement prediction accuracy. In particular, this approach can better represent the association between the step displacement of slow-moving landslides with environmental characteristics (e.g., rainfall, reservoir level). The study reveals that there are differences in the mechanisms and influencing conditions that cause the deformation of different areas of the landslide. Additionally, the reservoir water level fluctuation and seasonal rainfall are identified as the primary reasons contributing to the stepped displacement of the Jiuxianping landslide. The method provides a basis for the step-like displacement prediction, instability mechanism and landform evolution study of slow-moving reservoir landslides and provides valuable guidance for the prevention and control of similar reservoir geomorphic hazards worldwide.

Investigating kinematics and triggers of slow-moving reservoir landslide using an improved MT-InSAR method

The safety of the Three Gorges Reservoir, the world’s largest hydraulic project, has attracted significant attention. Among the landslides in the area, the Xinpu landslide complex stands out as one of the largest. However, accurately detecting and interpreting the timing and magnitude of its movement remains a challenge. This study introduces a framework using interferometric synthetic aperture radar (InSAR) for investigating the Xinpu landslide complex. In areas with dense vegetation like Xinpu, estimating landslide movement has traditionally been problematic. The proposed method, based on independent component analysis-assisted intermittent multi-temporal InSAR, overcomes this limitation by retrieving complete and reliable time-series deformation without prior deformation models. Through an analysis of Sentinel-1 datasets covering a period of 4 years, our approach significantly enhances deformation density and accuracy in comparison to other multi-temporal InSAR techniques. When contrasted with these methods, our proposed approach exhibits an average RMS improvement of up to 46.2% between GNSS measurements and the InSAR-derived results. The complete time-series deformation reveals diverse triggers at different sections of the Xinpu landslide complex. Precipitation, with a 45-day lag, primarily controls the landslide, while the toe of the landslide shows joint effects from precipitation and water level fluctuations, with a 14-day lag. Cross-correlation analysis estimates lag times for deformation responses to different triggers and enables discussion of the complex’s kinematic process. Overall, this approach enhances InSAR performance in vegetated areas and aids in uncovering landslide triggers for effective hazard mitigation.

Multistate transition and coupled solid–liquid modeling of motion process of long-runout landslide

The recognition, repetition and prediction of the post-failure motion process of long-runout landslides are key scientific problems in the prevention and mitigation of geological disasters. In this study, a new numerical method involving LPF3D based on a multialgorithm and multiconstitutive model was proposed to simulate long-runout landslides with high precision and efficiency. The following results were obtained: (a) The motion process of landslides showed a steric effect with mobility, including gradual disintegration and spreading. The sliding mass can be divided into three states (dense, dilute and ultradilute) in the motion process, which can be solved by three dynamic regimes (friction, collision, and inertial); (b) Coupling simulation between the solid grain and liquid phases was achieved, focusing on drag force influences; (c) Different algorithms and constitutive models were employed in phase-state simulations. The volume fraction is an important indicator to distinguish different state types and solid‒liquid ratios. The flume experimental results were favorably validated against long-runout landslide case data; and (d) In this method, matched dynamic numerical modeling was developed to better capture the realistic motion process of long-runout landslides, and the advantages of continuum media and discrete media were combined to improve the computational accuracy and efficiency. This new method can reflect the realistic physical and mechanical processes in long-runout landslide motion and provide a suitable method for risk assessment and pre-failure prediction.

Input-parameter optimization using a SVR based ensemble model to predict landslide displacements in a reservoir area – A comparative study

For reservoir landslides with limited in situ monitoring data, improving the accuracy of an ensemble prediction model through historical displacement-related factor deconstruction and model optimization is challenging. Unfortunately, even though various support vector regression (SVR) based ensemble prediction models have been proposed for this purpose, the optimal combination of new algorithms and their degree of improved prediction accuracy is still unclear. Based on four evaluation indicators, this paper presents a comparative study of a typical landslide displacement prediction model containing four important nodes (landslide displacement decomposition, inducing factor frequency-component extraction, input parameter selection, and optimization algorithm selection) vital to prediction accuracy. The empirical mode decomposition (EMD) series model was adopted to decompose the landslide displacement and extract the frequency component of the factors that affect the landslide movement. Four trajectory similarity judgment models were used to select input variables for the SVR-based prediction model. Nine swarm intelligence (SI) algorithms were used to help optimize the landslide prediction model. A case study shows that the SVR-based ensemble landslide prediction model works well in predicting the displacement of a slow-moving landslide. The combination of EEMD-CEEMDAN-LCSS-PSO yields the best prediction performance, with MAPE, RMSE, MAE, and R2 values of 0.004, 2.38, 8.64, and 0.96, respectively. The findings of this study can impact further studies of landslide ensemble prediction model optimization with insights into the algorithm selection, parameter setting, evaluation measures, and experimental settings.

Seismically progressive motion mechanism of earth slopes considering shear band porewater pressure feedback under earthquake excitations

The complicated seismic response of earth slopes and the transition mechanism from progressive to catastrophic motion of landslides have long been recognized as one of the most challenging research topics in geotechnical earthquake engineering. In this paper, this fundamental conundrum will be tentatively unveiled from a new perspective combining the seismic slope displacement analysis with (mechanical) dynamic porewater pressure feedback of the shear band soils against the earthquake excitation. We present both the conceptual scheme and the calculation framework to numerically study the dynamic changes of porewater pressure, shear strength parameters, and hydraulic properties of the shear band soils. Their significant influences to the change of earthquake-induced landslide movement modes are systematically investigated. Different dilation angles are chosen to characterize the shear dilation and shear contraction processes in the shear band soil, while the dynamic porewater pressure feedback in the shear band soil during the continuous seismic displacement is investigated. The results show that the seismic slope displacement and failure strongly depend on the mechanical feedback of the shear band soil. When the dilation angle is positive, the porewater pressure feedback in the shear band during the slope movement is negative, and the effective resistance stress increases, which is not susceptible to catastrophic motion. On the other hand, when the dilation angle is negative, the positive porewater pressure feedback may lead to catastrophic failure. At last, the effects of shear softening/hardening combined with dilation angle evolution on the ultimate slope movement mode are also put forward.

Velocity distribution and movement of multiple slow-moving landslides characterized by an optimized MTInSAR workflow

Slow-moving landslides can be found worldwide, exhibiting gradual movement over years to decades, with velocities ranging from millimeters to meters per year. However, slow-moving landslides can undergo transformation into rapid and catastrophic events, leading to severe damage to human society. Given the presence of >2500 pre-existing slow-moving landslides identified and cataloged using LiDAR bare ground data in Taiwan, it is crucial to efficiently assess their activity prior to the typhoon and heavy rainfall seasons. Therefore, a key research objective is to enhance the ability to detect landslide velocities and movements over large areas spanning tens of thousands of square kilometers. This study aims to establish a workflow that employs the multitemporal interferometric synthetic aperture radar (MTInSAR) technique for the detection and monitoring of multiple slow-moving landslides across wide regions. Specifically, we propose an optimized analysis package called “multi-snap2stamps,” based on the existing snap2stamps method, to generate interferograms for multiple regions simultaneously. Focusing on the analysis of nine pre-existing slow-moving landslides, with velocities <1.6 m/year (classified as very slow or extremely slow landslides according to established criteria), distributed across Taiwan with diverse terrain and geological conditions, this study investigates the characteristics of these deep-seated landslides using the proposed MTInSAR analysis workflow in both spatial and temporal domains. The results reveal that two slow-moving landslide sites exhibit significant seasonal signals in the time series, while seven sites do not display such signals. Additionally, the MTInSAR time series effectively captures accelerated movement in the Shiding-T001 landslide, which corresponds well with in situ inclinometer monitoring data. This study demonstrates the effective analysis of velocity distribution and movement characteristics of slow-moving landslides using the proposed MTInSAR workflow. Furthermore, it highlights the potential of this workflow for improving landslide motion detection over vast areas of interest in the future.

Stability analysis of reference station and compensation for monitoring stations in GNSS landslide monitoring

The Real-Time Kinematic (RTK) positioning method of the Global Navigation Satellite System (GNSS) has been widely used for landslide monitoring. The stability of its reference station is crucial to obtain accurate and reliable monitoring results. Unstable reference stations due to the geological environment and human activities are difficult to detect and in practical applications often ignored. As a result, it affects the positioning solutions and subsequently the interpretation and detection of landslide motions, which must be addressed in GNSS landslide monitoring. To solve this problem, we propose using the Precise Point Positioning (PPP) technique to analyze the stability of the reference station by verifying its position. The deformations of the monitoring stations are then compensated. First, the reference station coordinates are obtained by the PPP technique and tectonic motion is considered in data processing. The change or breakout of the reference station position is then determined using a cumulative sum control chart method. Finally, each monitoring station’s displacements are compensated according to the displacements of the reference station. According to the results of the Tengqing landslide experiment, the PPP technique can be used in GNSS landslide monitoring to analyze the stability of reference stations. With PPP, millimeter-level accuracy for the coordinates of reference stations is achieved. Compared to the traditional deformation series, the compensated displacement series more reliably reflects the landslide motions. This study will increase the reliability of monitoring results and contribute to implementing GNSS in monitoring landslides.

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.

The effect of tree growth disturbances inertia on dendrogeomorphic spatio-temporal analysis of landslides: A case study

Tree-ring analysis is currently a frequently used absolute dating method for spatio-temporal analysis of landslide movements. However, like all absolute dating methods, this approach has various limitations. One possible limiting factor is the inertia of tree growth responses to the influence of landslide movements. When landslide movements occur with a small recurrence interval (months or early years), trees with an inertial response to an older event may not be able to record a younger event. One possible growth response of trees to a landslide movement with the absence of inertia is a change in the size of the vessel lumen area (VLA; anatomical response) in deciduous trees. Thus, this study aimed to quantify the effect of the absence of VLA inertia on the spatio-temporal analysis of two landslide events of known occurrence with a short time between their occurrence (2010 and 2013). Ninety-six individuals of European beech (Fagus sylvatica L.) were sampled and two types of landslide signals (changes in tree-ring eccentricity and changes in VLA size) were extracted from their tree-ring series. The effect of the absence of inertia was evident in the younger event, with 171.2% more trees responding anatomically than through tree-ring eccentricity. In the case of the spatial extent analysis of the younger landslide event, 29.0% more was detected as an active area through anatomical changes (VLA) compared to the tree-ring eccentricity analysis. The use of growth disturbances without inertia could in the future reduce the negative general property of tree-ring-based chronologies of landslide movements, which are considered minimal when using classical growth disturbances with inertia. The implementation of anatomical responses could lead to a more effective use of dendrogeomorphic data in landslide hazard assessment.

Effect of earthquake-induced liquefaction of runout-path material on the movement of landslide

Effect of earthquake-induced liquefaction of runout-path material on the movement of landslide

Assessing the influence of non-plastic fines on rainfall-induced landslide initiation and propagation: Flume test findings

Numerous fluidized landslides with long runout distances and fast movements have been triggered by heavy rainfall under climate change. Non-plastic fines are frequently involved in many fluidized landslides. However, the role of fines in the initiation and movement of landslides has not been well understood. This study aimed to investigate the role of non-plastic fines in the initiation and movement of rainfall-induced landslides in a flume test setup. The experiments were conducted using mixtures of silica sand (D50 = 0.16 mm) with different non-plastic fines (D50 = 0.035 mm) content under different initial densities. The results demonstrated that the behavior of landsliding greatly depends on fines content (FC) and initial packing density (presented by density index, Id) of the soil layers in the flume. The landsliding phenomena could be classified into five failure modes, including slow and fast retrogressive individual sliding, sudden multiple sliding, and deep-seated and shallow fluidized sliding. As the FC increased or Id decreased, the landsliding behavior gradually evolved from slow retrogressive individual sliding to shallow fluidized sliding. For the tests with Id ≥ −0.06, the peak velocity (Vp) of the landsliding increased continuously with FC. Conversely, for the tests with Id ≤ −0.19, an optimal FC of 30 % was identified at which Vp reached its maximum. Additionally, for FC ≤ 10 %, Vp decreased with the increasing Id, while for FC ≥ 20 %, an optional Id existed at which Vp reached its maximum for a given FC, and the value of optimal Id (−0.2 ∼ −0.04) varied with FC (20 % ∼ 40 %). The peak pore-water pressure (PWP) (up) generally increased with the increase of FC. Furthermore, an optimal Id existed at which the PWP built up after landsliding occurrence (Δu) reached its maximum. The equivalent intergranular void ratio (es*) and equivalent interfine void ratio (ef*), which are calculated by considering both FC and void ratio, are found to be appropriate indices for evaluating and explaining the role of fines in the observed landsliding behavior. In conclusion, the addition of non-plastic fines can change the structure of test materials and result in different failure modes and mobility of landslides by affecting both interparticle contacts and PWP responses. These findings provide insights into the mechanisms of landsliding behavior and have implications for the assessment and mitigation of landslides in geotechnical engineering.

Landslide Susceptibility Assessment of a Railway Based on GIS Application

This study uses GIS-based maps to identify the potential for landslide movement on the railroad section between Prupuk Station and Purwokerto Station. The preparation was conducted by overlaying various maps obtained by online resource data, including rainfall, slope, geology, soil type, and land use, by using the DVMBG 2004 landslide prediction model. The distribution of landslide susceptibility levels shows that of the overall railway lines, 1.10% was very low, 17.29% was low, 63.16% was medium, 18.25% was high, and 0.21% was very high. The results of this study can be used as a reference for operators to provide information systems, landslide monitoring, and mitigation systems, especially for railroads in areas with high and very high vulnerability for landslides. Detailed conditions of landslide parameters and assessment of landslide occurrence on the location are needed to improve the accuracy of the models.

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.

COMPREHENSIVE CONTROL MEASURES IN THE VERY LARGE TAKISAKA LANDSLIDE AREA IN JAPAN

The purpose of this paper is to highlight the comprehensive control measures in the very large Takisaka landslide area in Japan. The Takisaka landslide area is one of the most representative large landslide areas in Japan. The location of the Takisaka landslide is extremely peculiar and this landslide could pose a great threat to the surrounding area. The landslide area is directly adjacent to the main channel of the Agano River, which has a length of 210 km and a catchment area of 7,710 km2 and flows from the eastern part of Fukushima Prefecture through Niigata Prefecture to the Sea of Japan. In the worst case, if the Takisaka landslide were to occur on a large scale, the sliding mass of soil could dam up the mainstream of the Agano River. In this case, a large reservoir would be created upstream and many residential areas would be flooded. In addition, if the reservoir were to burst, there would be flooding downstream. In order to avoid such a situation, the Takisaka landslide area must be managed extremely carefully, and comprehensive and drastic countermeasures must be taken. Originally, it is impossible to completely prevent such a large landslide by hard countermeasures using engineering structures alone. Therefore, for such a large landslide, it is necessary to monitor the amount of landslide movement in real-time continuously and to immediately issue an evacuation order to nearby residents when a critical amount of movement is measured. At the same time, however, it is also necessary to install hard measures using engineering structures to prevent the continuous movement of the landslide. This report first describes the characteristics of the Takisaka landslide. Then, comprehensive control measures, both soft measures and hard measures, are reported. The main part of the soft measures is the early warning system based on the comprehensive real-time monitoring system of this landslide. The main components of the hard measures are drainage works to collect and channel dangerous groundwater, such as drainage tunnels, drainage wells, and drainage boreholes. Finally, the effect of the drainage works already installed is illustrated three-dimensionally.

Utilization of the Accelerometer Sensor in Android Smartphones Development of Ground Movement Detection Tools in Areas Landslide Prone Based on the Internet of Things

The result of this research is an Internet of Things (IoT) program that utilizes the accelerometer sensor on Android smartphones as a tool for detecting ground movement in landslide-prone areas. If the sensor indicates a change in its coordinates, it will be used as an indication of ground movement on the accelerometer sensor. Meanwhile, the gyroscope sensor detects vibrations, and the program will send notifications as a sign of ground movement. Overall, the development of this landslide movement detection device in landslide-prone areas employs the Research and Development (R&amp;D) methodology. The Research and Development method aims to produce specific products and test the effectiveness of these products. The development method for the ground movement system utilizes a prototype method to observe and comprehend how the application functions. The results of this research demonstrate that the accelerometer sensor on Android smartphones can produce sufficiently accurate data for detecting ground movement. Integration with IoT technology opens opportunities for developing an early warning system that is effective and responsive to the potential landslide disasters. It is hoped that this research can provide a significant contribution to the development of more advanced ground movement detection systems in the future.

Analysis of Mass Wasting Processes in the Slumgullion Landslide Using Multi-Track Time-Series UAVSAR Images

The Slumgullion landslide is a large translational debris slide whose currently active part has likely been sliding for approximately 300 years. Its permanent motion and evolutionary processes have attracted the attention of many researchers. In order to study its mass wasting processes and evolution trend, the spatial–temporal displacement of the Slumgullion landslide was retrieved using an adaptive pixel offset tracking (POT) method with multi-track Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) images. Based on three-dimensional displacement and slope information, we then revealed the spatial–temporal distribution of surface mass depletion or accumulation in the landslide, which provides a new perspective to analyze the evolutionary processes of landslides. The results indicate that the Slumgullion landslide had a spatially variable displacement, with a maximum displacement of 35 m. The novel findings of this study mainly include two parts. First, we found that the surface mass accumulated in the toe of the landslide and depleted in the top and middle area during the interval, which could increase the resisting force and decrease the driving force of the Slumgullion landslide. This result is compelling evidence which indicates the Slumgullion landslide should eventually tend to be stable. Second, we found that the distribution of geological structures can well explain some of the unique mass wasting in the Slumgullion landslide. The larger local mass depletion in the landslide neck area verifies that the sharp velocity increase in this region is not only caused by the reduction in width but is also significantly affected by the local normal faults. In summary, this study provides an insight into the relation between the landslide motion, mass volume change, and geological structure. The results demonstrate the great potential of multi-track airborne SAR for displacement monitoring and evolutionary analysis of landslides.

Modelling seasonal landslide motion: Does it only depend on fluctuations in normal effective stress?

AbstractLandslide motion is often simulated with interface‐like laws able to capture changes in frictional strength caused by the growth of the pore water pressure and the consequent reduction of the effective stress normal to the plane of sliding. Here it is argued that, although often neglected, the evolution of all the 3D stress components within the basal shear zone of landslides also contributes to changes in frictional strength and must be accounted for to predict changes in seasonal velocity. For this purpose, an augmented sliding‐consolidation model is proposed which allows for the computation of excess pore pressure development and downslope sliding with any constitutive law with 3D stress evolution. Simulations of idealised infinite slope models subjected to hydrologic forcing are used to study the role of in‐situ stress conditions and stress rate multiaxiality. Specifically, a Drucker‐Prager perfectly plastic model is used to replicate frictional failure and shear deformation at the base of landslides. The model reveals that conditions amenable to the shearing of a frictional interface are met only after numerous rainfall cycles, that is, when multiaxial stress rates are suppressed. In this case, the landslide is predicted to move through a seasonal ratcheting controlled only by the effective stress component normal to the plane of sliding. By contrast, in newly formed landslides, the multiaxial stress evolution is found to produce further regimes of motion, from plastic shakedown to cyclic failure, neither of which can be captured by interface‐like frictional laws. Notably, the model suggests that a transition across these regimes can emerge in response to an aggravation of the magnitude of forcing, implying that (i) fluctuations in climate may alter the seasonal trends of motion observed today; (ii) our ability to quantify landslide‐induced risks is impaired unless proper geomechanical models are used to examine their long‐term dynamics.

Coupled CFD-DEM simulation of submarine landslide movement behavior

Submarine landslide is a common disaster geological phenomenon in the ocean, which can be destructive to underwater infrastructure. Therefore, it is necessary to simulate the evolutionary behavior of submarine viscous landslides. In this paper, computational fluid dynamics (CFD) and discrete element method (DEM) are used to establish the fluid-solid coupling model of water-particle interaction. Firstly, the inter-particle cohesion model is introduced to train the coupled CFD-DEM analysis of the kinematic evolution process, and at the same time, two typical cases are carried out to verify the analysis. In the experimental simulation, the kinematic and morphological characteristics of the submarine landslide were simulated considering the viscous effect and initial velocity of the landslide, and the influence mechanism of the landslide motion and evolution process was investigated in depth. The results show that the coupled method can better simulate the motion of submarine landslide, and the viscous effect of the landslide has a significant influence on its kinematic and morphological characteristics, and the initial velocity also significantly affects the evolution and distribution characteristics of the particle flow field of each part of the landslide in the process of motion. This study is important for the simulation and effective prediction of the kinematic evolution process of real submarine landslides.

The role of progressive brittle fracture in the 1931 landslide at Dogface Rock, Katoomba

The 1931 Dogface Rock landslide in Katoomba NSW was a complex, progressive cliff collapse with a failure volume in the order of 100,000 m3 that was triggered by the extraction of remnant coal pillars from the Katoomba Colliery, about 200 m below the top of the escarpment. Although underground coal mining is generally accepted as a cause of the rockslide, previous studies have not explicitly investigated the role of progressive brittle fracture in the collapse. This paper presents an integrated study which incorporates remotely piloted aircraft photogrammetry with a discrete element method numerical investigation of the landslide, and thereby explores the role of progressive brittle fracture, and re-examines the failure mechanism and runout motion of this multi-stage landslide. Remotely piloted aircraft photography is used to build a georeferenced 3D model of the site with Structure-from-Motion photogrammetry software. A digital geotechnical mapping workflow is demonstrated to investigate the morphology of the landslide scar, extract statistics on discontinuity orientation, persistence, and spacing, and undertake trace mapping of newer brittle fractures that interacted with pre-existing high persistence joints as the landslide rupture surface developed. A series of discrete element method numerical laboratory tests are used to calibrate bonded block contact properties that reproduce laboratory scale intact rock index parameters including UCS and tensile strength. Upscaled rock block contact parameters are then applied to a cliff-scale model that investigates the progressive development of rock mass damage induced by mining. Following extraction of the remnant pillars, rock mass damage develops mostly by extensile strains that produce tension cracks. Brittle fractures propagate upwards from the mine level and eventually initiate toppling of massive sandstone slabs defined by high persistence pre-existing subvertical joints. The investigation illustrates how the integration of photogrammetry with discrete element numerical methods can be used to characterise progressive brittle failure and runout of large rock slope failures.