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Analyzing and quantifying the deformation process of landslides is of paramount importance in facilitating landslide early warning. As such, this study is committed to proposing a universal phenomenological model for deformation stages division and early warning of landslides based on the kinematic features. First, five landslide deformation patterns were classified based on the creep theory, and suggestions for stage division of each deformation pattern are presented. Then, the statistical characteristics of landslide velocity were analyzed, and a probability-based deformation stage division method was proposed. Finally, the Comprehensive Standardized Deformation Index (CSDI) model, which includes the calculation of the CSDI M - M (Min-Max normalization) and CSDI M (Mean normalization) was proposed and verified in 24 landslides worldwide. The results show that, except for the oscillating pattern, the CSDI M - M is feasible in the stages division of all deformation patterns with a strong correspondence with the actual state of the landslides. The CSDI M is a reliable landslide warning criterion and threshold determination method, as it is effective in the early warning of imminent landslides with a low false alarm rate. The CSDI model provides new insight into the division of landslide deformation stages and landslide risk assessment. [ABSTRACT FROM AUTHOR]

The evaluation of landslide runout behavior plays a vital role in the risk assessment of landslides. In this study, the runout behavior of a landslide that occurred on December 10, 2019, in the Three Gorges Reservoir region, China, known as the Kamenziwan landslide, is studied with the discrete element method. A field survey is first conducted to study the geological characteristics and failure mechanism of this landslide. The survey results indicate that this landslide is possibly caused by the long-term fluctuation of the reservoir water level. Then, a three-dimensional (3-D) numerical model of this landslide is constructed on the basis of the terrain data obtained before and after the landslide occurrence. The critical input parameters to the numerical model, in terms of the contact micro-parameters among particles, are calibrated with the machine learning method and uniaxial compression tests. To depict the effectiveness of the built numerical model, the simulation results are compared with the video snapshots taken by a local resident. Finally, the runout behavior and the energy transformation of the landslide are analyzed based on the validated numerical model. [ABSTRACT FROM AUTHOR]

Rock avalanches often cause many casualties and considerable property damage due to hypermobility. To better understand the propagation process of rock avalanches, the mechanical energy evolution was investigated based on numerical simulation method and field investigation. Taking the well-known Jiweishan landslide as an example, the kinetic, potential, and dissipation energy elements were extracted from the kinematics parameters, and effective collisions were determined by calculating the local peaks of velocity. The lower velocity regions were observed in the middle portion of the sliding mass. Blocks in these regions were the medium through which the energy was transferred from the back portion of sliding mass to the front portion, acting like the stationary spheres in Newton's Cradle. The entire sliding mass followed the law of conservation of energy, while the energy evolution of the individual blocks varied by their locations. Considering that more collisions occurred in the front portion of the sliding mass, blocks in this area received more energy during propagation, thus they traveled a longer distance. Furthermore, the energy transfer became more obvious with the increase in the volume of sliding mass, causing a larger travel distance for the rock avalanche. [ABSTRACT FROM AUTHOR]

In recent years, numerous landslide catastrophes have occurred, generating considerable financial losses and other tolls. The deformational and mechanical properties of sliding zone soil would be in primary significance to landslide research, as the sliding zone basically controls the initiation and mobility of the landslide. An in situ triaxial test was carried out on a sample from the sliding zone of the Huangtupo 1# landslide, a subdivision of the Huangtupo landslide in the Three Gorges area of China. The test results indicate that (a) the sliding zone exhibits low compressibility due to the high rock content (54.3%) and long-time consolidation by the overlying soil mass; (b) only decaying creep occurs without abrupt failure, and a constitutive equation with both linear and nonlinear viscoplastic terms is deduced to accurately fit the test data; (c) the surface with an orientation of 35° presents anisotropic traits in terms of displacement, possibly due to cracks that formed at similar orientations within the sample cube; and (d) the creep behavior of the landslide may be closely related to the properties of the sliding zone soil. When a similar stress magnitude to that of the in situ stress environment is applied to the sample, the sliding zone soil behavior matches the landslide deformative behavior. The test results indicate that the Huangtupo 1# landslide will continue to creep, as interpreted from the deformation traits and structural properties of the sample. However, unavoidable limitations of the test and extreme external factors, namely unexpected rainfall and water fluctuation, cannot be ignored. [ABSTRACT FROM AUTHOR]

Accurate and reliable displacement forecasting plays a key role in landslide early warning. However, due to the epistemic uncertainties associated with landslide systems, errors are unavoidable and sometimes significant in traditional methods of deterministic point forecasting. Transforming traditional point forecasting into probabilistic forecasting is essential for quantifying the associated uncertainties and improving the reliability of landslide displacement forecasting. This paper proposes a hybrid approach based on bootstrap, extreme learning machine (ELM), and artificial neural network (ANN) methods to quantify the associated uncertainties via probabilistic forecasting. The hybrid approach consists of two steps. First, a bootstrap-based ELM is applied to estimate the true regression mean of landslide displacement and the corresponding variance of model uncertainties. Second, an ANN is used to estimate the variance of noise. Reliable prediction intervals (PIs) can be computed by combining the true regression mean, variance of model uncertainty, and variance of noise. The performance of the proposed hybrid approach was validated using monitoring data from the Shuping landslide, Three Gorges Reservoir area, China. The obtained results suggest that the Bootstrap-ELM-ANN approach can be used to perform probabilistic forecasting in the medium term and long term and to quantify the uncertainties associated with landslide displacement forecasting for colluvial landslides with step-like deformation in the Three Gorges Reservoir area. [ABSTRACT FROM AUTHOR]

This study presents a hybrid approach based on two-step cluster and decision tree C5.0 algorithms to establish a deformation forecasting model for a step-like landslide. The Zhujiadian landslide, a typical step-like landslide in the Three Gorges Reservoir area, was selected as a case study. Approximately , 6 years of historical records of landslide displacement, precipitation , and reservoir level were used to build the forecasting model. The forecasting model consisted of seven comprehensive rules governing hydrologic parameters and their magnitudes and was developed to predict landslide deformation. This model was applied to rapidly forecast the likelihood of step-like landslide deformation resulting from rainfall and water level fluctuations in the Three Gorges Reservoir area. Given the satisfactory accuracy of the trained model, the presented approach can be used to establish forecasting models for step-like landslides and to facilitate rapid decision making. [ABSTRACT FROM AUTHOR]

In this study, a data mining approach is proposed to investigate the hydrological causes of the Majiagou landslide, located in the Three Gorges Reservoir in China. It is possible to determine the cause-and-effect relationships between hydrological parameters and landslide movement. The data mining approach consists of two steps: first, hydrological indicators and landslide movements are discretized using the two-step cluster analysis; second, the association rule mining with the Apriori algorithm is employed to identify the contribution of each hydrological parameter to landslide movement. The results obtained suggest that deformation and later failure occurred first at the toe of the landslide and progressed upslope due to rising water level in the reservoir, prolonged heavy rainfall, and rapid drawdown in the reservoir. The proposed novel use of field data and data mining has the potential for providing procedures and solutions for an effective interpretation of landslide monitoring data. [ABSTRACT FROM AUTHOR]

Huangtupo landslide, volumetrically the largest, most complex landslide in the Three Gorges Reservoir region of China, is a dangerous mass on which the district of Badong has been inadvertently situated. Risk remediation efforts include the construction of a large observational tunnel and monitoring system that are unique in the world. This tunnel and its side branches permit detailed mapping of its 3D structure while providing samples for laboratory analysis. The new investigations validate that the Huangtupo landslide is a composite of several independent landslides and that movement occurs along the major rupture zones as well as on interlayer sliding zones in the underlying Badong Formation. Uranium-thorium disequilibrium dating establishes that the northern part of the landslide, called the Riverside Slump, underwent at least two periods of movement at about 100 and 40 ka (ka stands for a thousand years). These events were induced by the steep slope created by the downcutting of the Yangzte River. The results from in situ displacement monitoring over a 7-year period confirm that the central part of the landslide is creeping at a slow, relatively stable rate of about 15 mm/year rather than being in a stage of acceleration under the protection of anchored concrete beams and other defense structures at its toe. Available data suggest that engineering measures can control the independent landslides that together constitute the huge Huangtupo mass, which will avoid the need for costly relocation of thousands of people. [ABSTRACT FROM AUTHOR]

Physical modelling is a useful method to examine how landslides deform and fail at the laboratory scale. Reliable and accurate measurement systems are required for landslide model tests. This study comprehensively evaluates the performance of a multismartphone measurement (MSM) system for landslide model tests. Two slope models with different particle sizes were selected to assess the trueness and precision of the MSM system based on photogrammetry techniques under varied conditions, including different smartphone qualities and phone configurations. Benchmark data from a 3D laser scanner and preprinted markers were employed in the entire-point tests and marker-point tests, respectively. In addition, the MSM system's application test for monitoring landslides is presented. The results show that the system can be applied to achieve both trueness and precision at the millimetre level and submillimetre level in the entire-point tests and marker-point tests, respectively. Best-practice settings of the MSM system based on assessment tests are suggested for landslide slope models. The deformation behaviour of the excavation-induced slope model in the application test was clearly illustrated through the marker-based MSM system. [ABSTRACT FROM AUTHOR]

The mechanical properties of stabilizing piles are directly affected by the spatial structure of the bedrock of landslides. To effectively reinforce landslides with a sandwich-type bedrock, the interaction mechanism between manually excavated stabilizing piles and the different types of bedrock must be investigated. The research presents experimental models of manually excavated stabilizing piles for two kinds of sandwich-type bedrock structures, namely hard rock–dominant interlayered bedrock (HDIB) and weak rock–dominant interlayered bedrock (WDIB). Six physical models with different bedrock structure types and dip angles θ were prepared to explore the influence of these two parameters on the pile-bedrock interaction mechanism. The mechanical properties of the pile were investigated based on the monitoring results of the earth pressure distributions against the piles and the bending moment distributions. The embedded section of the pile experiences a rotation subjected to lateral soil movement. The center point of the rotation in the HDIB is at a greater elevation than in the WDIB. The earth pressure in the HDIB appears to increase with dip angle θ but is similar to each other in the WDIB. The pile embedded in the HDIB exhibits flexible behavior, whereas the pile embedded in the WDIB exhibits rigid behavior. With the increase of dip angle θ in the WDIB material, the bending moment steadily rises followed by fluctuation. The maximum bending moment of the embedded section increases with θ. These results provide a basis for improving the design of manually excavated stabilizing piles in sandwich-type bedrock. [ABSTRACT FROM AUTHOR]

Previous studies about probabilistic back analysis for shear strength parameters of landslides generally adopted a fixed slip surface. This setting may lead to unreliable results due to the uncertainty of slip surface location speculated by limited observations. Based on Bayes' theorem, this paper proposes a probabilistic framework for the back analysis of landslides considering slip surface uncertainty. The posterior distributions of shear strength parameters in Bayesian inference are solved by Markov chain Monte Carlo simulation method. To improve computational efficiency, a response surface function based on extreme learning machine is constructed to approximate the relationship between shear strength parameters and the corresponding factor of safety and critical slip surface. A synthetic slope, for which the actual shear strength parameters and slip surface are known, is used to compare the proposed and traditional methods. The effects of measurement error of slip surface and prior distribution of shear strength parameters on probabilistic back analysis results are also investigated. Results show that the shear strength parameters obtained from traditional probabilistic back analyses neglecting slip surface uncertainty significantly deviate from actual values, and are greatly affected by prior mean of shear strength parameters. The proposed method performs better than traditional method and is less affected by the prior distributions of shear strength parameters, and the smaller the measurement error of slip surface, the higher the Bayesian back analysis accuracy. A practical landslide is applied to further verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Hydraulic parameters are key data for calculating groundwater level, which is critical for assessing reservoir landslide stability. However, the quantitative understanding the influence of hydraulic parameters on the groundwater level of a reservoir landslide remains limited. In this paper, we apply a novel global sensitivity analysis method, PAWN, to quantify the sensitivity of hydraulic properties. The Shuping landslide, which is a typical reservoir colluvial landslide located in the Three Gorges Reservoir area, China, is used as a study case. The hydraulic parameters are first sampled within their entire feasibility space by the Latin hypercube sampling method. These samples are then used as inputs into a nonintrusive finite element program to automatically compute the corresponding groundwater level outputs. Finally, sensitivity indices are calculated based on the input–output dataset via the PAWN method. The global sensitivity analysis results provide useful guidelines for site investigation and reservoir colluvial landslide model simplification and calibration. [ABSTRACT FROM AUTHOR]

Landslides frequently disrupt roadway networks in mountainous regions worldwide. Because of the relatively long roadway extension and low roadway density in mountainous regions, the occurrence of a landslide hazard along a local road segment will cause traffic paralysis on the individual roadway and will further impact regional roadway network accessibility. This paper establishes an integrative risk assessment framework based on risk theory and complex network theory to combine the results of landslide susceptibility mapping along roadways and impact assessment on the roadway network. Through an analysis of the relationship between various geo-environmental conditioning factors and historical landslides along roadways, the support vector machine (SVM) model is used to assess landslide susceptibility across the regional roadway network. Both topological connectivity of the entire roadway network and transport accessibility between local residents are considered in the impact assessment on roadway networks. To illustrate the effectiveness of the proposed risk assessment framework, a case study of the roadway network in Fengjie County, China, which is prone to landslide occurrence, is conducted. The resulting landslide risk heatmap of Fengjie County's roadway network is generated using ArcGIS software. The most critical road segments are identified as being highly susceptible to landslides, and if they are disrupted, the entire roadway network will suffer significant performance loss. The results can support adaptive strategies for landslide mitigation, preparedness, and emergency response services, as well as improve roadway plans to reduce exposure and associated consequences by adding new links to the existing roadway network. [ABSTRACT FROM AUTHOR]

A rapid and long-traveling landslide was triggered by a monsoon rainfall of a total of 446.5 mm for 3 days in the Aranayake area, Sri Lanka. The landslide destroyed 75 houses and killed 127 persons along the course of this landslide. The mechanism of this landslide was investigated by a joint team of the International Consortium on Landslides (ICL) and the National Building Research Organization (NBRO) of the Government of Sri Lanka in 2017 and 2018; the investigation was part of the WCoE and IPL projects. Physical properties of soil samples taken from the source area of the Aranayake landslide were examined through a series of undrained ring-shear tests, and the measured properties were used in a numerical method, LS-RAPID, to simulate initiations and motions of landslides in this area. The authors then tried to first reproduce a landslide, which was considered, from available pieces of evidence, to have most likely happened in the past, then, to assess the risk of a potential future landslide that is expected to occur close to the 2016 Aranayake landslide. Two possible sliding surfaces were assumed to develop through the soil mass, one along the boundary between the weathered surface soil and the jointed bedrock and another along a potential aquiclude inside the soil. This attempt to estimate movements of both past and future landslides based on the numerical reproduction of the 2016 Aranayake landslide hazard will help develop landslide hazard assessment technologies. [ABSTRACT FROM AUTHOR]

The response of a loess-mudstone landslide model to seismic activity is examined using centrifuge shaking table tests and 2D seismic input waves. The physical model of a dormant landslide is subjected to simulated seismic signals of different input amplitudes, and the dynamic response is analyzed in terms of relative peak ground acceleration (PGA), which is used to assess deformation and failure mechanisms of the slope. Relative PGA increases with increasing landslide height, reaching maximum values at the crest, while values at the toe are slightly larger than those in the middle of the slope. Relative PGA is the highest along the outer surface and weakest along the sliding surface. Horizontal values are generally larger than vertical values, and the amplitude of the seismic input strongly affects the landslide dynamic response. The PGA amplification factors increase considerably with increasing input amplitude, reaching maximum values at 0.3-0.4 g, and then decrease. The largest displacement is observed at the crest, while displacements in the middle part and at the toe increase steadily with higher input amplitudes, and displacement at the crest increases at a higher, irregular rate. Deformation is most apparent at the crest, developing from cracks into collapsed soil deposited at the toe. Local shallow sliding is observed along the landslide surface, and the dormant sliding body may generate displacement along the sliding surface caused by earthquake reactivation. A numerical model of the landslide provides results consistent with centrifuge model testing; both indicate similarity in seismically induced dynamic responses and failure characteristics. [ABSTRACT FROM AUTHOR]

Tianshui City is located in a seismically active region of China. Historically, many earthquakes with magnitudes of 6.0-8.0 have been reported in this area, and most of loess-red mudstone landslides in this area are known to have been triggered by earthquakes. However, the soil dynamics under earthquakes in the Tianshui area have been little studied. Therefore, to understand the dynamic stress-strain behavior of undisturbed soils during the earthquake, cyclic and shear strength tests were conducted on soil samples (loess and weathered red mudstone) obtained from Tianshui in a cyclic triaxial test system. Two types of laboratory tests were carried out on two kinds of soils. The first type involved the tests with different cyclic stress ratios applied and the number of cycles N more than 20, while the second type are series of stress-controlled undrained reverse-shear tests. By doing so, the differences on stress condition on the behavior of Young's modulus E , stress-strain and shear strength were measured. In addition, tests modeling natural seismic loading were also carried out for comparative purposes. Some residual shear behaviors were also recognized. The results of a series of tests designed to study the stress-strain behavior of undisturbed soils under repeated loading are presented. These tests will provide useful parameters (e.g. λ and E ) for analysis of slope stability during earthquakes and earthquake-resistant design. [ABSTRACT FROM AUTHOR]