Landslide Simulation Research Articles

Correction to: Synthetic libraries of urban landslide simulations to identify slope failure hotspots and drivers across spatial scales and landscapes

Correction to: Synthetic libraries of urban landslide simulations to identify slope failure hotspots and drivers across spatial scales and landscapes

Discrete-element method simulations of shallow landslides triggered by rainfall

Rainfall infiltration is a primary cause of slope failure. Analyzing the entire process of a landslide triggered by rainfall is crucial for the design of infrastructure. However, the complexity associated with simulating large deformations has often hindered previous studies from modeling the entire landslide process subsequent to rainfall infiltration. This study aims to provide a method to simulate the entire process of landslides considering rainfall and more insight into the mechanism of landslides. The discrete element method (DEM) is first applied to model the entire process of shallow landslides triggered by rainfall. The numerical results indicate that the intensity and duration of rainfall infiltration have significant impacts on the slope stability. The particle displacement field, resulting from landslides due to rainfall, corresponds with three distinct stages within the landslide process. The increased rainfall intensity causes the area of the particles within failure mass grows rapidly during the initial stage of the landslide. The closer to the slope surface the faster the particle velocity. The simulations demonstrate that the slope surface transitions from a linear to a concave downward geometry during the landslides. Larger particles display greater displacement and velocity compared to smaller particles.

Synthetic libraries of urban landslide simulations to identify slope failure hotspots and drivers across spatial scales and landscapes

AbstractRainfall-triggered landslides are most deadly in developing countries, and future urban sprawl and climate change could intensify existing risks. In these regions, enhancing efforts in urban landslide risk mitigation and climate change adaptation is crucial. Current landslide probability assessment methodologies struggle to support effective mitigation because they fail to represent local anthropogenic factors (e.g. informal housing) across space and time scales. To meet this challenge, we demonstrated in previous work that hillslope-scale mechanistic models representing such localised changes can be used to create synthetic libraries of urban landslides that account for both data and future scenario uncertainty. Here, we show how these libraries can become an explorative tool for researchers and stakeholders, allowing them to investigate slope stability variations across spatial scales and landscapes. Results highlight, for example, how the main slope instability drivers change according to the location (e.g., upper vs lower catchment), the landcover (e.g. forest vs urban) and the spatial scale analysed (e.g. at hillslope scale slope stability was mostly controlled by water table height, whereas at regional scale by slope geometry). Ultimately, we demonstrate that stochastic analyses can lead to a greater understanding of the system interactions and they can support the identification of mitigation strategies that perform well across spatial scales and uncertain scenarios. These strategies should be prioritised even if future conditions are unknown. This reasoning is shown on a data-scarce region with expanding informal housing. However, the same methodology can be applied to any urban context and with any mechanistic-based model.

Improved mesh-free SPH approach for loose top coal caving modeling

This study presents an innovative model in computational geotechnical engineering by improving the Smoothed Particle Hydrodynamics (SPH) method for simulating loose particle dynamics in coal caving processes. The improved model integrates an elastic-perfectly plastic constitutive model with the Drucker-Prager yield criterion and includes several improvements aimed at boosting accuracy, stability, and efficiency. These improvements include gravity loading coupled with particle damping, first-order stress field smoothing, and kernel gradient correction. A series of numerical experiments validates the effectiveness of the improved SPH model, demonstrating its capability to predict large deformations and track the evolution of the coal-rock interface in coal caving processes. Furthermore, the study analyzes the model's sensitivity to material parameters such as the angle of friction and material density, which aids in configuring the model for distinct coal mining situations. Results show that the non-cohesive elastic-perfectly plastic constitutive model can effectively simulate the flow behavior of granular particles, and the landslide simulation results are in good agreement with the experiments. The improved SPH algorithm with stress smoothing technique solves the problem of numerical noise, and the “double peak” stress distribution around the coal outlet is identified. The established SPH model offers an effective tool for understanding dynamics behaviors of loose top coal. Significantly, the model requires only five material parameters, which can be identified through standard experiments, avoiding the typically arduous process of parameter selection or calibration commonly existing in Discrete Element Method simulations.

A Virtual Reality Simulation of a Real Landslide for Education and Training: Case of Chiradzulu, Malawi, 2023 Landslide

Virtual reality (VR) is a promising new educational and training tool in the field of disaster and emergency management, especially for hazards that are not frequent or well known to the public and require spatial and situational understanding. The objective of this paper is to describe an educational VR simulation that was developed based on a landslide that really occurred in Southern Malawi during the March 2023 Cyclone Freddy. The cyclone induced several landslides that caused many casualties and significant damage. The VR simulation framework consisted of four critical steps using Unity3D for the creation of the simulation including data preparation, terrain and environmental modeling, landslide simulation development, and virtual reality interactions. The simulation scenarios were diversified to include three distinct landscapes that can help users learn how factors such as terrain can influence landslide impacts. The VR simulation offers users an intimate, firsthand experience of the landslide’s unfolding and allows users the ability to explore various facets of the landslide phenomena. This VR simulation aims to provide an educational tool to facilitate an in-depth understanding of and interaction with a real-word landslide to learn about the impacts of landslides and how different factors can influence these impacts.

The study of the natural frequency evolution and numerical simulation of retrogressive landslides

A retrogressive landslide is influenced by the cyclical fluctuations in reservoir water levels is considered a common natural disaster. Tension cracks are important indicators for assessing landslide status in the case of retrogressive landslides. Displacement monitoring is a commonly used method and provides an intuitive reflection of the landslide deformation; however, it does not directly indicate the depth of the tension cracks. Based on the principles of vibrational dynamics, a retrogressive landslide is proposed to be initially classified as a single-mass spring oscillator model before the development of cracks. Following the development of tension cracks, the model can be classified as a double-mass spring oscillator model. The model patterns are verified through numerical simulations using ABAQUS. Based on the numerical simulations, with an increase in the number of reservoir water cycle fluctuations, the displacement and stress of the landslide exhibit periodic growth. However, during displacement growth, the tension cracks do not necessarily increase. As the tension cracks deepen, the landslide transitions from a single-mass spring oscillator model to a double-mass spring oscillator model, with the appearance of a second-order natural frequency. Moreover, as the tension cracks deepen, the numerical values of the natural frequency change. The maximum change in first-order natural frequency is 3.5 Hz. The maximum change in second-order natural frequency is 4.5 Hz. The variation in the natural frequency can reflect the depth of development of the landslide's tension cracks and, consequently, indicate changes in the stability state of the landslide.

PLANES4LOD2: Reconstruction of LoD-2 building models using a depth attention-based fully convolutional neural network

Level of detail (LoD)-2 reconstruction is an inevitable task in digital twin-related applications such as disaster management, flood simulation, landslide simulation and solar panel recommendation. However, there is a lack of capable methods that can exploit fine details in RGB imagery and mitigate noise in photogrammetric digital surface models (DSMs). Our investigation is focused on the use of roof planes to achieve a geometrically complete and correct, and topologically consistent LoD-2 building reconstruction. Using UNet with the EfficientNet-B3 backbone, the developed approach starts with jointly predicting building sections and roof planes from the orthorectified RGB imagery and a photogrammetric DSM. The detected sections and planes are then vectorized by employing tree search and simplified with the Douglas Peucker algorithm. Subsequently, height values from the noisy input DSM and the vectorized image-based (and simplified) roof planes are used to derive 3D-planes. Finally, the building model is formed by computing plane intersections as the ridge lines. This study demonstrates that a well-designed depth attention module (DAM), which is the bottleneck of the UNet, can achieve a very good use of both spectral and depth features. The resultant 1-to-n correspondence between building section and roof plane benefits accurate and consistent building model reconstruction. Furthermore, it leads to a superior generalization capability of the proposed method. Experiments with 1437 buildings from the cities Cologne and Braunschweig, Germany, demonstrate the success of the proposed workflow in reconstructing compound buildings with complex roof structures. The achieved geometric mean absolute error (MAE) is 1.06m and 0.24m respectively. Comprehensive comparative evaluations showcase the superiority of the approach in terms of geometric completeness and accuracy, and topological consistence with. The improvement over SAT2LOD2 (Gui and Qin, 2021) is 1.12m in Cologne (data accessible at https://github.com/dlrPHS/GPUB) and 0.47m in Braunschweig in geometrical MAE.

Active thickness estimation and failure simulation of translational landslide using multi-orbit InSAR observations: A case study of the Xiongba landslide

The active thickness of the translational landslides plays a pivotal role in evaluating its hazards and simulating its instability. Existing techniques have difficulties in estimating the accurate active thickness due to the limitations of observation conditions and imaging geometry, leading to deviations in failure simulations. To overcome these challenges, this study proposes an enhanced method that utilizes multi-orbit Interferometric Synthetic Aperture Radar (InSAR) observations to estimate the active thickness of the translational landslides and subsequently conduct more accurate instability simulations. The method involves integrating multi-orbit InSAR imaging parameters with the spatial geometry of the landslide to establish a slope coordinate system. This system enables the projection of one-dimensional InSAR Line Of Sight (LOS) displacements onto the three-dimensional displacements of the landslide. Subsequently, the active thickness is estimated by combining InSAR three-dimensional displacements with the mass conservation method. Finally, the estimated thickness is incorporated into the geological model construction to simulate the dynamic movement of the landslide. The method was applied to the Xiongba translational landslide in Gongga County, Tibet Autonomous Region, China. The results show that the deformation is mainly concentrated at its forefront, with maximum three-dimensional deformation rates of 4.7 m/a, 2.3 m/a, and 1.24 m/a. The landslide encompasses an estimated area of around 5.33 square kilometers, and its active thickness varies from 0 to 106.59 m. The maximum displacement distance reaches 1469.76 m, with a peak velocity of 60.37 m/s. The proposed method provides scientific support for assessing, analyzing, and preventing landslide disasters.

A depth-averaged SPH-FV landslide dynamic model for evaluating hazard zones

Thousands of landslides worldwide lead to significant casualties and property damage. A numerical model is crucial for simulating the runout of possible future landslides and generating reliable hazard zone maps. Two main methods can be adopted to simulate motion: one based on the Eulerian description and the other based on the Lagrangian description. Each description offers varying adaptability to simulating landslides. In this paper, we proposed a method of coupling the depth-averaged smoothed particle hydrodynamics (SPH) method and a finite volume scheme with the van Leer splitting (FV-VLS). For the solid phase, we utilized the depth-averaged SPH method to simulate the movement process. The SPH method can track the movement of key parts. In contrast, we employed the FV-VLS based on the Eulerian description to reduce the calculation amount. In 1-D dam break simulation, both the depth-averaged SPH and FV-VLS methods yielded similar results. The 1-D two-phase dam break simulation shows that buoyancy reduces friction and lateral solid stress, increases hydraulic stress, and generates a complex motion process. The Yigong landslide simulation indicates that solid fractions will affect the motion trajectory in the 2-D simulation. A smaller solid fraction will cause the landslide to affect a larger area.

Assessment and simulation of potential landslide caused by the rainfall intensity in Batu City during 2021

Rain is the main factor causing landslides; rainwater can enter the soil through rock gaps and then accumulate in the impermeable layer; the layer then becomes a slip plane that triggers the landslide. This study aims to determine the level of influence of rainfall on landslide events in Batu City in 2021. Batu City is one of the main tourist cities in Indonesia, so security and safety are the main factors that must be considered. The method used in this research is a descriptive analysis of rainfall and landslide data. The analysis process was approached with a literature review and simple mathematical calculations visualized on a 2D map using GIS and Geostudio to simulate groundwater infiltration and safety factors. The results showed that the number of landslide events increased with increasing rainfall. The rainfall for Batu City is between 1749.15-2238.73 mm, while most landslides occur in January and February. Landslides in Batu City in 2021 occurred 78 times, most of which occurred in Songgokerto Village (15 incidents). The intensity of rainfall greatly influences the occurrence of massive landslides; apart from changing the physical properties of the soil or rock, the mechanical properties also change rapidly. The wetting-drying process will make the properties of soil particles and rock aggregates more vulnerable or the durability index of the soil and rock layers will decrease due to continuous rainfall.

Process and numerical simulation of landslide sliding caused by permafrost degradation and seasonal precipitation

Process and numerical simulation of landslide sliding caused by permafrost degradation and seasonal precipitation

Simulasi Model Material Tanah Pada Bidang Gelincir Longsor Dengan Variasi Sudut Kemiringan (Studi Kasus Material Tanah di Daerah Kabupaten Gorontalo Utara)

Landslides are one of the geological disasters that often occur in Indonesia. North Gorontalo is an area where landslides occur every year. Based on data from the 2022 Badan Penanggulangan Bencana Daerah (BPBD), in the last year, there were 8 landslides. Landslides can occur due to several factors, namely; human factors and natural factors. In principle, landslides occur when the restraining force is less than the driving force. In this study a landslide simulation will be carried out using a simulation model made on a lab scale, the size of the simulation model is 40 cm x 30 cm x 25 cm. The simulation was carried out using soil samples taken at the research location. Variables that were observed during the simulation were the effect of the slope angle (o) on the exiting water (ml), the water infiltration time (t), and the effect of the slope (o) on the depth of the slip plane (cm). The soil taken from the research location will be subjected to a sieving analysis test with a hydrometer test to determine the texture class of the soil. From the soil texture test results, some of the research locations have a sand-gravel type of texture. The simulation test carried out also obtained the result that the slope of the slope greatly influences the water infiltration time with the depth of the slip plane. The greater the angle of the slope of the sled that is carried out, the results of the variable being measured will also be directly proportional.

Applying cellular automata to dynamic simulation of a tsunamigenic submarine landslide in the South China Sea

This work presents the first known application of a new approach to tsunami modelling, by linking a discrete cellular automata (CA) dynamic model of a submarine landslide to an off-the-shelf tsunami modelling package. This has the advantage of simulating the temporal evolution of the submarine landslide rather than as a single rigid sliding mass. We first tested that the coupled model was able to satisfactorily reproduce observed tsunami wave heights resulting from the flank collapse of the Anak Krakatau volcano in the Sunda Strait (Indonesia) in December 2018, before applying it to a speculative area of interest on the North Borneo (Continental) Shelf (NBS). The NBS has one of the thickest near-shore clastic sediment wedges known globally (12 km thickness) and a very long pre-history of submarine landsliding. We modelled a small slide (5 km3 volume) because this is far more likely to occur than a recurrence of the gigantic Brunei slide (1200 km3 volume). Results indicate that a 5 km3 submarine landslide generates multiple tsunami waves, the largest of which reached 8 m at the coast of nearby Balabac Island (The Philippines). Small tsunami waves also arrived on the central Vietnam coast, more than 900 km distant. A larger potential failure on the NBS therefore appears capable of causing a tsunami with greater runup heights, which could pose a risk to much of central and southern Vietnam, northern Borneo (Sabah, Brunei) and Palawan. Finally, we note that the South China Sea is fringed by a necklace of other thick offshore clastic sediment accumulations, most notably on the southern China continental margin, offshore southern Taiwan, and offshore central Vietnam. Given the proof-of-concept of our coupled CA–tsunami modelling approach described here, we recommend this also be applied in these areas to assess the risk posed by a wide range of submarine landslides to coastal populations and infrastructural assets (including nuclear power plants).

A scalable well-balanced numerical scheme for the simulation of fast landslides with efficient time stepping

We consider a single-phase depth-averaged model for the numerical simulation of fast-moving landslides with the goal of constructing a well-balanced, yet scalable and efficient, second-order time-stepping algorithm. We apply a Strang splitting approach to distinguish between parabolic and hyperbolic problems. For the parabolic contribution, we adopt a second-order Implicit-Explicit Runge-Kutta-Chebyshev scheme, while we use a two-stage Taylor discretization combined with a path-conservative strategy, to deal with the purely hyperbolic contribution. The proposed strategy allows to decouple hyperbolic from parabolic-reaction stiff contributions resulting in an overall well-balanced scheme subject just to stability restrictions of the hyperbolic term. The spatial discretization we adopt is based on a standard finite element method, associated with a hierarchically refined Cartesian grid. After providing numerical evidence of the well-balancing property, we demonstrate the capability of the proposed approach to select time steps larger than the ones adopted by a classical Taylor-Galerkin scheme. Finally, we provide some meaningful scaling results on ideal and realistic scenarios.

A 3D Two-Phase Landslide Dynamical Model on GIS Platform

The landslide dynamics model is one of the methods for evaluating landslide motion processes, contributing to disaster prevention and mitigation. With the advancement of science and technology, GIS has become the mainstream platform for landslide simulation. However, the three-dimensional movement of landslides is intricate, leading to a lack of methods for three-dimensional landslide numerical simulation on GIS platforms. In this paper, we propose a three-dimensional, two-phase landslide dynamics model. Through the proposed solution, three-dimensional modeling and numerical simulation of landslides can be achieved on GIS platforms. Simultaneously, drawing inspiration from the SPH kernel functions, we visualize the results of the three-dimensional model on the GIS platform. Simulation of the Yigong landslide demonstrates that our solution can realize three-dimensional landslide simulation on the GIS platform. Our model adeptly captures numerous details in the landslide motion process. However, constrained by the inherent limitations of the three-dimensional model, the model results are susceptible to numerical oscillations and diffusion, with the accuracy of the model being controlled by grid partitioning.

A general SPH framework for earthquake-induced landslide simulation

A general SPH framework for earthquake-induced landslide simulation

Convenient Method for Large-Deformation Finite-Element Simulation of Submarine Landslides Considering Shear Softening and Rate Correlation Effects

Submarine landslides pose a serious threat to the safety of underwater engineering facilities. To evaluate the safety of undersea structures, it is important to estimate and analyze the sliding processes of potential submarine landslides. In this study, a convenient model for simulating submarine landslide processes is established by using Abaqus Eulerian large deformation technology with an explicit finite element framework. The VUSDFLD Fortran subroutine is used to consider the strain-softening and rate-dependency characteristics of soil shear strength. The proposed method is validated by comparing its results with experimental data and those of mainstream numerical methods. Then, the results of a dynamic analysis of typical potential submarine landslides in the Shenhu sea area are analyzed using the proposed method. Case studies are carried out under different soil shear strength distributions, and the influence of initial stress is also analyzed. The shear strain-softening and rate-dependency effects are highly involved in the runout process. The simulated landslide’s failure mode is consistent with the geophysical interpretation of existing landslide characteristics.

APPLICATION OF LUCAS-KANADE DENSE FLOW FOR TERRAIN MOTION IN LANDSLIDE MONITORING APPLICATION

Abstract. Landslides are natural hazards that can cause severe damage and loss of life. Optical cameras are a low-cost and high-resolution alternative among many monitoring systems, as their size and capabilities can vary, allowing for flexible implementation and location. Computer vision is a branch of artificial intelligence that can analyze and understand optical images, using techniques such as optical flow, image correlation and machine learning. The application of such techniques can estimate the motion vectors, displacement fields, providing valuable information for landslide detection, monitoring and prediction. However, computer vision also faces some challenges such as illumination changes, occlusions, image quality, and computational complexity. In this work, a computer vision approach based on Lucas-Kanade optical dense flow was applied to estimate the motion vectors between consecutive images obtained during landslide simulations in a laboratory environment. The approach is applied to two experiments that vary in their illumination and setup parameters to test its applicability. We also discuss the application of this methodology to images from Sentinel-2 satellite optical sensors for landslide monitoring in real-world scenarios.

Dynamic Analysis of a Long Run-Out Rockslide Considering Dynamic Fragmentation Behavior in Jichang Town: Insights from the Three-Dimensional Coupled Finite-Discrete Element Method

To clearly realize the dynamic process as well as the dynamic fragmentation behavior of a long run-out rockslide, a novel numerical method for landslide simulation of the coupled finite-discrete element method (FDEM) was applied and the Jichang rockslide was used as a case. The calibrated simulation result of the FDEM in a rockslide deposit corresponds well with the real rockslide deposit. The main run-out process of the rockslide lasts for 75 s and can be divided into acceleration and deceleration stages, which last for 33 s and 42 s, respectively. The maximum overall rockslide movement speed is 35 m/s while the partial sliding mass reaches 45 m/s. The fracturing, fragmentation, and disintegration processes of the sliding mass can be clearly observed from the dynamic scenarios. Fracture energy generated by rock fracturing constantly increases with time in a non-linear form. Of the total fracture energy, 54% is released in the initial 5 s because of fracturing, and 39% of the total fracture energy is released because of fragmentation and disintegration in the last 35 s. The accumulated friction energy increases in the whole run-out process, and its magnitude is much greater than the kinetic energy and fracture energy of the sliding mass.

PHyL v1.0: A parallel, flexible, and advanced software for hydrological and slope stability modeling at a regional scale

Physically-based hydrological-geotechnical modeling at large scales is difficult, especially due to the time-consuming nature of flow routing and 3D soil stability models. Although parallelization techniques are commonly used for each model individually, there is currently no concurrent parallelization strategy for both. This study proposed an open-source, Parallelized, and modular modeling software for regional Hydrologic processes and Landslides simulation and prediction (PHyL v1.0). It offers parallel computation in both hydrological and 3D slope stability modules, cross-scale modeling ability via a soil moisture downscaling method, and advanced input/output (I/O) and post-processing visualization. Additionally, PHyL v1.0 is flexible and extensible, making it compatible with all mainstream operating systems. We applied PHyL v1.0 in the Yuehe River Basin, where the computational efficiencies, parallel performance, parameter sensitivity analysis, and predictive capabilities were evaluated. The PHyL v1.0 is therefore appropriately used as an advanced software for high-resolution and complex simulations of regional floods and landslides.