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A large number of laboratory investigations related to the permeability have been conducted on the sliding zones. Yet little attention has been paid to the particular sliding zones of the slide-prone Badong Formation. Here, we experimentally investigate the permeability nature and the mechanism of seepage in the viscous sliding zone of the Huangtupo Landslide. Saturated seepage tests have been performed first with consideration of six dry densities and thirteen hydraulic gradients, in conjunction with the mercury intrusion porosimetry test and scanning electron microscopy test for the microstructure analysis after seepage. The results show that seepage in the sliding zone soil does not follow Darcy's Law, since there is a threshold hydraulic gradient (i0) below which no flow is observed and a critical hydraulic gradient (icr) over which the hydraulic conductivity (K) tends to be stable. The percentage of bound water could be responsible for the occurrence of i0 and icr. Furthermore, pore size distributions (PSD) less than 0.6 µm and between 10 and 90 µm exhibit positive and negative correlations with the i0, respectively, indicating that the i0 is related to the PSD. The mechanism accounting for this result is that pore water pressure forces fine clay particles into the surrounding large pores and converts arranged particles to discretely distributed ones, thereby weakening the connectivity of pores. The seepages in the sliding zones behave differently from that in the sliding mass and sliding bed in response to the permeability. [ABSTRACT FROM AUTHOR]

Numerous engineering case studies suggest that the complexity and oscillatory of landslide displacement types, influenced by diverse deformation patterns, monitoring errors, and varied observation time frames, present challenges for the application of traditional warning criteria in assessing landslide movement in practice. As such, this study attempts to propose a data-dependent early warning criterion through the dimensionless analysis of displacement for two typical landslide displacement patterns: exponential pattern and step-like pattern. The displacement trend in exponential pattern landslides is extracted using the simple moving average (SMA) method, with the onset of acceleration (OOA) determined through the application of the Pettitt test. The Deformation Standardized Anomaly Index (DSAI) is defined to quantitatively evaluate the alert levels corresponding to each monitored displacement data of both patterns. After validating the proposed criterion in ten landslide cases, results indicate that the landslides have a high probability of losing stability when DSAI exceeds four, and the landslide tends to stabilize as DSAI decreases. Compared to displacement speed ratio (DSR), the proposed DSAI is more applicable, aligning with the actual conditions of both landslides with exponential pattern and step-like pattern and exhibiting a relatively low false alarm rate, making it a valuable criterion for landslide early warning. [ABSTRACT FROM AUTHOR]

Timely evaluation of landslide risk based on displacement data is crucial for the effective warning of landslide events. However, the complexity and diversity of displacement curves obtained in the field make the selection of evaluation criteria and thresholds challenging and subjective. Thus, this study proposes a new early warning criterion called the deformation probability index (DPI) to overcome this limitation. By analyzing features of landslide displacement curves obtained from the field, four linetypes were identified, and differences in velocity data between pre-failure and post-failure landslides were summarized from a probabilistic perspective. Subsequently, the DPI is defined to assess the early warning level of a landslide by converting observed velocity values into standardized velocity values using cumulative distribution function standardization. The resulting DPI values are divided into five early warning intervals with three alerting levels to indicate the relative stability of the landslide. Applying the proposed method to 16 landslides from around the world demonstrates the effectiveness of the DPI criterion in evaluating landslide risk, with a high correlation between alerting levels and observed landslide occurrences. The DPI criterion demonstrates notable sensitivity exclusively to displacement velocity and monitoring frequency, exhibiting remarkable generality and accuracy, thus offering a new method for landslide early warning. [ABSTRACT FROM AUTHOR]

Block-flexure toppling failure is frequently encountered in interbedded anti-inclined rock (IAR) slopes, and seriously threatens the construction of hydropower infrastructure. In this study, we first investigated the Lean Reservoir area's geological setting and the Linda landslide's characteristics. Then, uniform design and random design were used to design 110 training datasets and 31 testing datasets, respectively. Afterwards, the toppling response was obtained by using the discrete element code. Finally, support vector regression was used to obtain the influence weights of 21 impact factors. The results show that the influence weight of the slope angle and rock formation dip angle on the toppling deformation among tertiary impact factors is 25.96% and 17.28%, respectively, which are much greater than the other 19 impact factors within the research range. For the primary impact factors, the influence weight is sorted from large to small as slope geometry parameters, joints parameters, and rock mechanics parameters. Joints parameters, especially the geometric parameters, cannot be ignored when evaluating the stability of IAR slopes. Through numerical simulation, it was qualitatively determined that failure surfaces of slopes were controlled by cross joints and that the rocks in the slope toe play a role in preventing slope deformation. [ABSTRACT FROM AUTHOR]

Rainfall with heavy intensity and long duration is a main inducing factor that triggers landslides on anti-inclined rock slopes. Numerous interbedded anti-inclined rock (IAR) slopes in Southwest China frequently experience mountain collapses and landslides under heavy rainfall. Therefore, it is necessary to study the failure mode of IAR slopes during rainfall. In this study, the Linda landslide and Mari landslide, typical IAR landslides in the study area, were used as examples to build a physical model of IAR slopes under continuous rainfall conditions, and a self-made rainfall simulation system was used to mimic natural rainfall conditions. The multi-physics data of displacement, velocity, stress, strain, pore water pressure, and acoustic signals in model deformation and failure under rainfall conditions were obtained using multi-field monitoring technology. In addition, the materials' water content and mechanical parameters at different locations of the model were obtained after the experiment. The analysis results indicate that: in the first and middle periods of rainfall, the slope model experienced a shallow local deformation and a holistic toppling deformation; until the late rain, the failure of the IAR slope caused by rainfall finally presented a typical failure mode of multiple failures and collapses of regressive landslides. According to its multi-field evolution characteristics, the velocity and acoustic signals were highly consistent with the failure characteristics of the model, which could be used as landslide early warning indicators. In addition, it was observed that the shape of the multi-slip surfaces generated by the model was a concave double straight line extending from the slope toe to the slope surface and sharing the failure section at the slope toe. Finally, the deformation and failure process of the model could be speculated to be divided into five stages based on the deformation behavior and multi-field physical data feature: the initial interlayer dislocation stage, the deformation stage, the crack propagation stage, the retrogressive failure stage, and the holistic failure stage. The failure mode and deformation mechanism of IAR slopes under rainfall were revealed in the model test, which could provide appropriate guidance for the analysis and evaluation of similar landslides. Highlights: The failure of the interbedded anti-inclined rock slope model caused by rainfall presented a typical failure mode of multiple failures and collapses of regressive landslides. The velocity and acoustic signals are highly consistent with the failure characteristics of the model, and the shape of the multi-slip surfaces was a concave double straight line extending from the slope toe to the slope surface. According to its multi-field evolution characteristics, the deformation and failure process of the model under rainfall conditions can be divided into five stages. [ABSTRACT FROM AUTHOR]

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]

Block-flexure toppling failures in interbedded anti-inclined rock (IAR) slopes present significant risks to infrastructure and safety. Based on the Linda landslide field investigations, this study conducted a series of physical modelling tests encompassing 15 slope angle and bedding angle combinations. The aim of 15 sets of tests was to explore the deformation and failure mechanisms in IAR slopes. The observations during the deformation and failure stages elucidated how changes in slope and bedding angles influence rock mass deformation and failure characteristics. The findings highlight that slope angle critically impacts IAR slope stability, while bedding angle notably affects deformation depth, failure area, and failure surface configuration. IAR slopes with bedding angles less than 60° tend to exhibit shallow, single-surface failures with the linear failure surface, whereas bedding angles exceeding 70° lead to deep-seated, large-area, multi-surface failures characterised by double-folded failure surfaces. The magnitude of the failure inclination angle increases with slope and bedding angles, ranging from 0 to 35°. Furthermore, deformation and failure in IAR slopes involve the progressive extension of cracks from the slope crest to the interior, eventually reaching the slope toe. Finally, the block-flexure toppling process in IAR slopes can be divided into an incubation deformation stage and an accelerated deformation stage, and based on curve characteristics, different deformation modes of the IAR slopes can be further classified as stepwise cumulative accelerated deformation mode and leap deformation mode. Highlights: Fifteen cases of physical modelling tests covering various slope angles and bedding angles were conducted to replicate the deformation and failure mechanism in interbedded anti-inclined rock (IAR) slopes; Slope angle plays a pivotal role in determining the stability of IAR slopes, whereas bedding angle controls slope deformation depth, failure area, and failure surface characteristics; The IAR landslide is a progressive failure process that extends from the slope crest to the slope toe; The deformation process of IAR slopes can be categorised into the incubation deformation stage and the accelerated deformation stage. Additionally, the deformation mode can be further classified as either stepwise cumulative accelerated or leap deformation modes. [ABSTRACT FROM AUTHOR]

This study investigated a dynamic stability analytical model for bedding rock slope with soil interlayer, considering various rain patterns. The critical rain intensities for anhydrous and water-filled fissure were derived, respectively. Rain coefficients (i.e., concentration and peak position coefficients) were subsequently introduced to investigate rain patterns. The evolving water head under different infiltration scenarios was derived based on Darcy's law and mass conversation law. Additionally, the time-varying water pressure along soil interlayer was obtained based on triangular distribution assumption. An analytical model incorporating time-varying water head was established to predict slope stability based on limit equilibrium method. Numerical simulations further validated the analytical solutions for time-varying water head and pressure. The evolving characteristic of slope stability was analyzed, and a failure threshold was proposed. Results demonstrated that rain patterns and rain coefficients significantly impact on the rainfall threshold corresponding to slope failure. For uniform rain-induced slope failure, rainfall threshold tends to increase as rain intensity decreases. For unimodal rain-induced slope failure, the rainfall threshold is the largest for post-peak rain corresponding to slope failure, followed by the medium-peak rain, and the smallest for forward-peak rain. These results and findings enhance our understanding of the dynamic stability of bedding rock slope with inclined soil interlayer and provide valuable insights into assessing the evolving slope stability under different rain patterns. Highlights: An analytical model of dynamic slope stability coupling time-varying water head was established. Impacts of rain pattern and rainfall intensity on slope stability were systematically investigated. Rainfall threshold for slope failure considering different rain patterns was proposed based on analytical model. 〹 [ABSTRACT FROM AUTHOR]

A simplified geomechanical model was proposed by considering three typical necking-type slopes; this model lays a foundation for the further investigation of the deformation behaviors of such slopes. Three physical models of necking-type slopes were built according to the geomechanical model with slope evolution stages. Finally, preliminary calculations related to the arching effect in the physical model were conducted. Three evolution stages of necking-type slopes, namely, the initial stage, compression stage, and failure stage, were presented based on the formation and disappearance of the arching effect within the slope. The specific parameters of the geomechanical model were given. In the setup of the tilting test, the failure angle of the necking-type slope model was calculated to be approximately 50° with a large lateral resistance coefficient. The proposed geomechanical model and physical models of necking-type slopes provide guidance for the establishment of geomechanical and physical models of landslides at specific sites. [ABSTRACT FROM AUTHOR]

Fluctuating reservoir levels and rainfall behind dams generally cause more severe weathering of the rock forming reservoir bank slopes. Physical weathering tends to weaken the rock and can cause slope instability. Slate sampled from a newly built reservoir area was exposed to cyclic wetting and drying to accelerate physical weathering. A series of tests, including uniaxial and triaxial compressive tests, investigated the weakening of slate. Based on the tests, the degradation of the mechanical properties, failure model, and energy evolution process were studied. Cyclic wetting and drying significantly weaken the specimens. Specifically, the mechanical properties show a monotonic reduction with the number of wetting and drying cycles and the confining stress. The average rebound hardness value of the samples decreases from 30.7 to 20.3 as the number of wetting and drying cycles increases from 0 to 10. The weathering degree and mechanical properties of the specimens can be estimated by the rebound hardness through one linear function and six exponential functions. Five types of fractures and three failure modes were found to describe the failure features of the specimens, and cyclic wetting and drying tended to complicate the failure modes. The evolution process of strain energy represented by five specified types can be divided into three stages according to the variations in the energy parameters, and two newly proposed energy parameters can be used to reflect the energy dissipated by micro-fissure closure and fracture generation. [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]

Landslides pose a significant risk to human life and property, making landslide susceptibility mapping (LSM) a crucial component of landslide risk assessment. However, spatial correlations among mapping units are often neglected in statistical or machine learning models proposed for LSM. This study proposes KNN-GCN, a deep learning model for slope-unit-based LSM based on a graph convolutional network (GCN) and the K-nearest neighbor (KNN) algorithm. The model was experimentally applied to the Lueyang region and validated through the following steps. Firstly, we collected data for 15 landslide causal factors and from landslide inventories and established a slope unit map (SUM) through slope unit division. Next, we performed a multicollinearity analysis of landslide causal factors and divided the training and test sets at a 7:3 ratio. We then constructed a GCN model based on a slope unit graph (SUG) generated from the SUM using the KNN algorithm. The proposed KNN-GCN model was tuned using a grid search with fivefold cross-validation on the training set, and then trained and validated on training and test sets separately. Finally, the performance of the KNN-GCN model was compared with that of six other models which were categorized into two groups: CG#1 was the traditional KNN, support vector regression (SVC), and automated machine learning (AutoML), and CG#2 included KNN-G, SVC-G and AutoML-G with additional spatial information. Our results demonstrate that the proposed model achieves superior performance (area under the curve [AUC] = 0.8351) and generates the most comprehensible susceptibility map with distinct boundaries between different susceptibility levels. Notably, while the proposed KNN-GCN model displays exceptional performance in slope-unit-based LSM, its implementation requires high-level computing resources, and it is not recommended for small datasets. [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]

The in situ stress field in valley areas is an important factor to consider in the construction of hydropower projects in southwest China. Due to intense tectonic movement, the action of gravity, and rapid river erosion, the resulting stress has a complex distribution and a large magnitude. The availability of stress measurements is insufficient to provide adequate understanding of the regional stress state. In this research, inversion analysis for the in situ stress field of a valley in the upper reaches of the Lancang River is carried out by using stepwise regression analysis and the FLAC3D numerical simulation, and the temporal and spatial distribution characteristics of the in situ stress are obtained. Based on those results, the influence of stress unloading effects on slope stability is discussed. The results show that the formation of the modern in situ stress field is the comprehensive result of interactions among gravity, tectonic movement, and river erosion. The reliability of the inverse result can be increased by improving the mesh density of the calculated model and considering multistep river erosion. Under the influence of the unloading effects, tensile fractures were formed and the rock mass loosened near the slope surface. With the presence of bedding dipping into the slope, toppling failure was triggered by the unloading rebound that mainly occurred in the stress relaxation zone. [ABSTRACT FROM AUTHOR]

The parameter mi accounts for the anisotropy of rock strength, and the accurate determination of mi is a primary requirement of the Hoek–Brown (H–B) strength criterion. In this study, a relation for mi as a bivariate, second-order, polynomial function of the minor principal stress (σ3) and the angle (β) between the major principal stress and weak plane is developed. First, the possible contribution of σ3 and β to mi is systematically investigated based on substantial uniaxial and triaxial compression test data of various rock types collected from the available literature. This investigation allows mi to be described in terms of σ3 and β. A self-defined fitting function is adopted to formulate the functional relationship among these metrics. Using this relation, the H–B strength criterion is modified, and its performance is evaluated in two examples. The examples illustrate the improved ability of the modified criterion to determine the strength of metamorphic and sedimentary rocks. The applicability of this criterion to additional rock types warrants further study. [ABSTRACT FROM AUTHOR]

The stability of an arching slope in deformable materials above strong rocks strongly depends on the shape and width of the span. Equations for a free surface problem that incorporate these two parameters were derived using a simplified two-dimensional arching slope model, and were validated using physical model tests under 1g and centrifugal conditions. The results are used to estimate the maximum excavation width for a weak claystone slope in a lignite mine, for which we calculate a safety factor of 1.31. [ABSTRACT FROM AUTHOR]

Red-bed mudstone is widely distributed throughout the Three Gorges Reservoir Area, China. This geological material easily disintegrates into fragments during engineering activities. The potential factors that influence the disintegration (grain composition, slake durability index, grain roundness, fractal dimension, and surface energy) and shear strength (cohesion and friction angle) of red-bed mudstone fragments are investigated via cyclic wetting and drying tests and direct shear tests. The results show that the disintegration process includes three stages and that the grains gradually become well graded. The roundness exhibits a linear relationship with the number of cycles. However, the variations in the slake durability index, fractal dimension (mass-size distribution based), surface energy, cohesion, and friction angle show three distinct stages. In addition, the fractal dimension (quantity-size distribution based) and friction angle are significantly affected by the assumption that the specimens are isotropic, and the grain behaviors involve compaction, rotation, and separation. The cohesion and friction angle display linear relationships with the slake durability index, roundness, fractal dimension (mass-size distribution based), and surface energy, indicating the potential to assess the shear strength of mudstone fragments from the aspect of disintegration. [ABSTRACT FROM AUTHOR]

Although advances in piling equipment and technologies have extended the global use of stabilizing piles (to stabilize slope or landslide), the design of stabilizing piles remains a challenge. Specifically, the installation of stabilizing piles can alter the behavior of the slope; and the spatial variability of the geotechnical parameters required in the design is difficult to characterize with certainty, which can degrade the design performance. This paper presents an optimization-based design framework for stabilizing piles. The authors explicitly consider the coupling between the stabilizing piles and the slope, and the robustness of the stability of the reinforced slope against the spatial variability of the geotechnical parameters. The proposed design framework is implemented as a multiobjective optimization problem considering the design robustness as an objective, in addition to safety and cost efficiency, two objectives considered in the conventional design approaches. The design of stabilizing piles in an earth slope is studied as an example to illustrate the effectiveness of this new design framework. A comparison study is also undertaken to demonstrate the superiority of this new framework over the conventional design approaches. [ABSTRACT FROM AUTHOR]

Toppling deformations generally develop in interbedded anti-inclined rock slopes in the upper reaches of the Yalong River in southwest China. With the characteristics of large scales, strong deformation degrees and complex deformation modes, toppling bodies may eventually lead to instability failure in the form of landslides, which seriously threaten the construction and operation of hydropower stations in the basin. Taking three typical examples of toppling failures for interbedded anti-inclined rock slopes in the basin, the sensitivity analysis of 19 impact factors affecting the toppling deformation of this type of slope is obtained via the Grey correlation method and UDEC. The results show that the geometric parameters represented by slope angles are the most sensitive to toppling deformation, the mechanical parameters of joints are more sensitive to toppling deformation than the physical and mechanical parameters of intact rocks, and the sensitivities of the parameters of sandstone and slate gradually converge in the deformation process. [ABSTRACT FROM AUTHOR]

Rapid long-runout landslides always cause extensive damage to lives and properties, and the deposit characteristics of landslides play an important role in revealing the evolution and transport mechanism. Several intensive fieldworks were conducted at the Jiweishan landslide region in Chongqing, China to investigate the deposit features, including the motion characteristics, retention of stratigraphic sequence, inverse grading, and thickness distribution, which later helped in the calibration and setting of the numerical modeling. Based on the discrete element method (DEM), the effects of simulation parameters (friction coefficient, volume, and fall height) on the maximum travel distance and deposit area of the landslide were assessed, taking account into the joints network developed in rock mass, respectively. Sensitivity analysis was performed according to numerical data, and the calculated relative sensitivity (RS) values suggested that all parameters had an impact on the travel distance of rapid long-runout landslides, and the sensitivity could be listed in the following order of most to least sensitive: volume (RS = 0.83) > fall height (RS = 0.23) > friction coefficient (RS = 0.14). [ABSTRACT FROM AUTHOR]

This paper presents a new framework for characterizing landslide deformation. Here, the deformation of a landslide is interpreted as a summation of three components: rigid deformation, within-mass deformation, and residual deformation. On the basis of the monitored data of the landslide deformation, these three components may be characterized separately: the rigid deformation is simulated by a summation of a trend term and a periodic term, the within-mass deformation is simulated by a high-order polynomial model, and the residual deformation is simulated by a conditional random field model. In particular, the characterization of the residual deformation, the third component of the landslide deformation, with the random field allows for a probabilistic assessment of the landslide deformation in the face of geological uncertainties. With the proposed framework, the evolution of landslide deformation in both geometric and time domains may be established, which allows for an assessment of the sliding mechanism of the landslide. Further, evolution in the geometric domain may allow for an assessment of the serviceability of infrastructures in the landslide area. To illustrate this new landslide deformation characterization framework, a case study of the Yu-Kai highway landslide in Guizhou, China is presented, through which the effectiveness of the proposed framework is demonstrated. [ABSTRACT FROM AUTHOR]

Mountainous regions present severe risks, including damage to transportation infrastructure, due to the occurrence of geohazards such as rock avalanches and other types of landslides. Lessons learned from past damaging events are helpful for risk reduction in mountainous regions. In this paper, to study a rock avalanche impact on a bridge, a numerical modeling framework with the aid of the discrete element method (DEM) is developed; the progressive failure process of an expressway bridge that was damaged by a rock avalanche is reproduced, and the failure mechanisms and dynamic behaviors of the bridge under impact are assessed. The Yaxi Expressway bridge that was destroyed by the September 20, 2020, Yaoheba rock avalanche in southwest China is used as an illustrative example. A field investigation is carried out to identify geological conditions, characteristics, and the kinetic failure pattern of the rock avalanche and the bridge. The stereographic projection analyses indicate that this rock avalanche was initiated as a planar slide. A three-dimensional numerical model of the rock avalanche and bridge is developed based on the terrain data acquired. The critical parameters of the numerical model are calibrated based on results obtained from laboratory tests. Finally, the progressive failure process and failure mechanism of the impacted bridge are analyzed based on the constructed numerical model. The comprehensive analysis framework can be applied to similar events involving geohazard-structure interaction. [ABSTRACT FROM AUTHOR]

Anti-dip slope that fails in the form of flexural toppling is commonly encountered in rock engineering. This paper presents an approach to calculate the local failure probability of the anti-dip slope susceptible to flexural toppling. The realization of this approach consists of four major steps: (1) establishing geo-mechanical model of the slope and generating physical parameters randomly using Monte Carlo simulation, (2) determining the demarcation of the toppling and sliding failure zones, (3) evaluating the stability state of each single column, and (4) deriving the local failure probability by an iterative calculation. A case study of the Mari landslide is analyzed by employing the proposed approach, and the Maxwell model is applied to reduce physical parameters with time. The results show that the instability grade increases gradually throughout the whole evolution process of the slope. In the incipient stage, particular attention should be paid to the middle–upper columns, which have the highest failure probabilities. However, as the slope deformation increases, all the columns should be taken into account since they have approximately the equal possibility of failure. A simplified slope model is employed to perform a parametric analysis. The results show that (1) the local failure probability of the slope tends to decrease with increases in the rock friction angle, rock tensile strength or interface friction angle, while increasing the rock unit weight leads to a higher probability of local failure; (2) the computation results are more sensitive to the uncertainty in the interface friction angle than that in the other three above-mentioned parameters; and (3) the maximum failure probability depends on the geometric parameters, including the column interface angle, slope angle, crest angle, slope height and column thickness. [ABSTRACT FROM AUTHOR]

Data from in situ monitoring of displacement is of fundamental importance, not only in hazard assessments, but also for understanding the deformation mechanisms of landslides. However, acquiring reliable and continuous displacement data from complex landslides is often a problem because of the high cost of instruments and maintenance. Among more than 250 dangerous landslides monitored in the Chinese Three Gorges reservoir area, the most systematic and complete monitoring data have been obtained from the Shuping landslide. A ten-year record of GPS displacements measured in eight different locations, plus rainfall and reservoir level data, are utilised to identify the movement characteristics and causal factors of the Shuping landslide. The cumulative displacement curves show a series of abrupt increases that occur every year and are separated by periods of steady, slower deformations. The maximum cumulative displacement that occurred during the ten-year monitoring period was 4.7 m at site SP-2. The maximum displacement rate was 35 mm/day, which was observed on June 13, 2012 at site ZG86. Causal factors of the Shuping landslide are identified through qualitative comparisons of the monitoring data and cross-examined by grey correlation degree analysis. The results show that reservoir water level drawdown is the main factor accelerating the movement of the Shuping landslide, with heavy rainfall playing a subordinate role. The proposed use of field data and analytical methods has the potential for providing procedures and solutions for the interpretation of landslide monitoring data. [ABSTRACT FROM AUTHOR]

Accurate estimates of the three-dimensional (3-D) rock fracture orientation distribution are crucial for generating a reliable fracture system model. Although an earlier method by Fouché and Diebolt allows one to estimate such distributions from one-dimensional (1-D) samples, this method does not typically produce highly accurate estimates of the 3-D orientation distribution (HAE3DOD). In this study, the minimum scanline-to-fracture angle (minimum θ) and the minimum orientation sample size (minimum n) required to produce HAE3DOD are investigated. Firstly, the factors significantly influencing minimum θ and minimum n are identified, and the influence clarified. For minimum θ, the possible influencing factors include the orientation concentration parameter (к) and n, while for minimum n, the possible influencing factors include к and θ. Fractures from three selected sites in China provide sufficient data for this investigation. The investigation results reveal that minimum θ varies almost linearly with к and n. Moreover, minimum n varies linearly with к and θ. Variations in the minimum θ and minimum n values are strongly associated with discrepancies in sample density resulting from different values of these factors. To ease the estimation of minimum θ and minimum n, empirical relations that take into account the separate factors are proposed for these two variables. A practical example demonstrates that the proposed relations accurately and efficiently estimate minimum θ and minimum n and can provide sampling guidelines (i.e., the intervals of scanline direction and sample size) for producing HAE3DOD. The potential limitations of the proposed relations are also discussed. [ABSTRACT FROM AUTHOR]

The time-dependent soil creep behavior affects the strength and deformation of the shear zone in landslides. Limited studies have been carried out on the undisturbed soil samples from the deep shear zone due to the difficulties in obtaining them. This problem is investigated using a case study of the well-known Huangtupo landslide, which is the largest landslide in the Three Gorges Reservoir area of China. The creep properties of the undisturbed shear zone were studied using triaxial creep testing. Two creep stages (the primary stage and the attenuation secondary creep stage) were observed, which were characterized by a creep rate that approached zero, instantaneous deformation and the development with a constant speed. The long-term shear strength of the shear zone was calculated based on the test results. The creep stages and long-term shear strength are significantly different from those of direct creep tests of reconstituted shear zones due to the influence of the confining pressure and coarse particles. The Computerized Tomography (CT) scanning technique was also applied, and the results showed clear rotation of some coarse particles in the middle parts of the samples, which was reflected by their shapes. The changes in particle position were more significant at the bottom of the sample. Based on these results, an empirical constitutive model was proposed to describe the relations among stress, strain and time, and this model fits the experimental data well. The inhomogeneity of the undisturbed soil samples leads to different creep properties from those in ideal theoretical models; therefore, new stochastic constitutive models should be explored and developed for further studies. [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]

Orientation statistics are prone to bias when surveyed with the scanline mapping technique in which the observed probabilities differ, depending on the intersection angle between the fracture and the scanline. This bias leads to 1D frequency statistical data that are poorly representative of the 3D distribution. A widely accessible estimator named after Terzaghi was developed to estimate 3D frequencies from 1D biased observations, but the estimation accuracy is limited for fractures at narrow intersection angles to scanlines (termed the blind zone). Although numerous works have concentrated on accuracy with respect to the blind zone, accuracy outside the blind zone has rarely been studied. This work contributes to the limited investigations of accuracy outside the blind zone through a qualitative assessment that deploys a mathematical derivation of the Terzaghi equation in conjunction with a quantitative evaluation that uses fractures simulation and verification of natural fractures. The results show that the estimator does not provide a precise estimate of 3D distributions and that the estimation accuracy is correlated with the grid size adopted by the estimator. To explore the potential for improving accuracy, the particular grid size producing maximum accuracy is identified from 168 combinations of grid sizes and two other parameters. The results demonstrate that the 2° × 2° grid size provides maximum accuracy for the estimator in most cases when applied outside the blind zone. However, if the global sample density exceeds 0.5°, then maximum accuracy occurs at a grid size of 1° × 1°. [ABSTRACT FROM AUTHOR]

Jurassic strata prone to slope failure are widely distributed in the Three Gorges Reservoir region. The limit equilibrium method is generally used to analyze the stability of rock slopes that have a single failure plane. However, the stability of a stratified rock mass cannot be accurately estimated by this method because different bedding planes have variable shear strength parameters. A modified limit equilibrium method is presented with variable water pressure and shear strength used to estimate the stability coefficient of a sloping mass of stratified rock and to identify the potential sliding surface. Furthermore, an S-curve model is used to define the spatial variations of the shear strength parameters c and ϕ of the bedding plane and the tensile strength of the rock mass. This model can also describe the variation of strength parameters with distance from the slope surface, which depends on the reservoir water level. Also, it is used to evaluate the stability of the Qianjiangping landslide, located at Shazhenxi Town, Zigui County, Three Gorges Reservoir area, China. The results show the most probable sliding surface is the interface between a slightly weathered layer and subjacent bedrock. When reservoir water rises above the elevation of the slide mass toe, the stability coefficient of the slope declines sharply. When the reservoir water level is static at 135 m, the stability coefficient decreases gradually as the phreatic line changes as a result of heavy rainfall. [ABSTRACT FROM AUTHOR]

To evaluate the performance of deep learning methods on the landslide susceptibility mapping, five different convolutional neural networks (CNN)—AlexNet, Inception-v3, Xception, ResNet-101, and DenseNet-201—were employed to predict the landslide susceptibility along a transmission line. Ten landslide influencing factors were extracted from three databases and considered in the input layers. The landslide (10,481 grids) and non-landslide (10,481 grids) data were randomly subdivided into 70% (14,673 grids) and 30% (6289 grids) to construct the training and validation samples, respectively. The appropriate architecture and training parameters were carefully selected after many attempts until the training and validation accuracy was above 90%. The receiver operating characteristic (ROC) curve, landslide density (LD), and landslide ratio (LR) were determined to estimate the five CNN networks’ prediction accuracy. All CNN networks had high area-under-the-curve (AUC) values when assessing landslide susceptibility, and most landslides occurred in the outputs with predicted high and very high landslide susceptibility (LD > 65% and LR > 2.90). Generally, CNN networks had a higher accuracy than the two traditional methods due to the powerful capability of deep feature extraction. Additionally, the computational time cost in three steps was recorded to investigate the efficiency of five CNN networks, and all CNN networks accomplished the goals within an acceptable time using a commercially available computer (~ 24 h). Comparatively, AlexNet and Xception had better performance than other networks on the landslide susceptibility assessment. [ABSTRACT FROM AUTHOR]

The geological strength index (GSI) plays an important role in the quality evaluation and stability analysis of rock mass. Traditional methods for quantitatively estimating GSI are often subjective, time-consuming, and dangerous. This paper proposed a method for rapid and quantitative GSI estimate using 3D point clouds, which can be generated through non-contact measurement methods such as photogrammetry and Light Detection and Ranging (LiDAR). The overall methodology is as follows: (1) point clouds were acquired using a terrestrial laser scanner; (2) discontinuities were identified through artificial neural networks (ANN) and density-based spatial clustering of applications with noise (DBSCAN); (3) geometric information was extracted for the detected discontinuities; (4) GSI was estimated according to the detection and characterization of discontinuities. The proposed method was used for the Yujiashan road cut to calculate the GSI and the GSI partitioning was performed simultaneously. Three sets of discontinuity were detected in the Yujiashan road cut, and Structure Rating (SR) and Surface Conditions Point Clouds Rating (SCPC) were calculated to be 13.2 and 25, respectively. Correspondingly, the GSI was estimated to be 32, which was consistent with the results of the in-situ evaluation (rating 25–40). Furthermore, the Yujiashan road cut was divided into 17 segments, and the effect of sampling size on the GSI calculation was discussed. The application results show that the GSI of the rock mass can be obtained objectively and efficiently through 3D point clouds, which can be used as a potential alternative to the traditional method for GSI estimation. Article Highlights: A semi-automatic method was developed to determine the rockmass GSI using laser scanning. Discontinuities were detected from the 3D point cloud using a machine-learning algorithm. Four geometric parameters of detected discontinuities were extracted for GSI calculation. The scale effect of GSI calculation was investigated using the proposed partitioning algorithm. GSI estimation obtained from the proposed method matched the traditional manual surveys. [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]

This paper outlines the spatial-temporal evolution of a landslide. A multiple monitoring system that consists of a three-dimensional (3D) laser scanner, a particle image velocimeter (PIV), earth pressure cells (PCs), and a thermal infrared (TIR) imager were designed and employed for a 1 g landslide model case study. The displacement, velocity, lateral earth pressure and surface temperature were recorded during the evolution of a landslide. Four stages of evolution were identified using the measured displacements: the initial stage, the uniform stage, the accelerated stage and the failure stage. The deformation, lateral earth pressure and surface temperature of a landslide were monitored during each stage. The distribution of the lateral force with depth varied significantly during movement, and the depth of the maximum soil pressure increased with movement. The surface temperature of the moving mass was significantly higher than the surface temperature of the nonmoving mass. The average change in surface temperature showed a significant increase in surface temperature followed by a decrease in surface temperature prior to failure. This study provides procedures and solutions for landslide monitoring, interpreting landslide initiation and detecting landslides. [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]

The Huangtupo landslide is the volumetrically largest, most complex, and economically most significant landslide in the Three Gorges Reservoir Region. Detailed information about the character and dynamics of this tractive landslide is available because of access provided by a unique, 908-meter in situ research tunnel, augmented by long-term data provided by an extensive monitoring system for ground water levels, rainfall, and in situ deformation. Three major rupture surfaces plus 12 interlayer sliding zones (weak layers) were recognized during tunnel excavation, which also provided access and samples that establish a complex, multistage deformation history. Data from the in situ monitoring system shows that the toe of the landslide is creeping at a steady annual rate of about 25-30 mm, but at a slower rate of about 12 mm/year near the crown. However, the monthly creep rates are variable, being highest during May-August when rainfall is heavy and reservoir levels are low. Displacement-depth curves in the HZ6 borehole inclinometer establish that the creep of Slump Mass I# is most rapid above a depth of 37 m, where a major rupture zone occurs immediately above bedrock. Engineered defense structures along the toe of Huangtupo landslide can improve its stability to some extent. The effect of rapid changes of the reservoir level on landslide stability should be considered in reservoir management. [ABSTRACT FROM AUTHOR]

Block-flexure toppling is the most common toppling mode occurring in interbedded anti-inclined slopes. With the development of hydropower projects in Southwest China, numerous deep-seated large-area toppling failures have become revealed along the Yalong River, seriously threatening the construction and operation of hydropower infrastructure. With the Mari landslide as the research focus, a geological field investigation, base friction physical model test, and numerical simulation test were carried out to study the evolutionary process of slope failure. The results demonstrate that the deep-seated toppling in the study area initiated and developed with the river downcutting process, and the landslide was the final result of the toppling deformation. The interbedded structure of layered rock masses, the steep slate foliations in the slope, and the cross joints in the metamorphic quartz sandstone perpendicular to the rock layer are the controlling factors of the toppling deformation. The landslide induced by toppling mainly developed in the highly deformed zone, where multiple failure surfaces developed, and the location and shape of the failure surfaces were controlled by the cross joints in the metamorphic quartz sandstone. The evolutionary process of the deep-seated large-area toppling in the study area mainly underwent four stages: the initial slope formation stage, the rock column bending and cracking stage, the failure surface penetration stage, and the failure stage. [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]

In recent years, a large number of bank destruction occur in the reservoir area under the effect of water fluctuation, which may be lead to reservoir accumulative landslide geological hazards finally. The paper conducted the bank destruction forecasting study for accumulative landslides in the Three Gorges Reservoir Region, China utilizing back-propagation (BP) neural network approach. A representative scenario of Jinle landslide is then taken for analysis purposes. On the basis of the existing data sets of bank destruction cases, the BP neural network forecasting model and the corresponding programs for bank destruction are both presented, whose forecasting result is validated by two independent approaches, namely empirical method and numerical modeling method. Furthermore, the BP neural network model had obvious advantages over the convention approaches in the aspects of the fast calculation speed and high convenience. According to the bank destruction forecasting scale presented above, the corresponding revetment measures can be proposed to prevent the occurring of the bank destruction, whose effectiveness has been further validated by the actual engineering practice. [ABSTRACT FROM AUTHOR]

A new method (kinetic vector method, KVM) is presented for analyzing the dynamic stability of wedge in rock slope. The dynamic analysis is carried out based on three dimensional distinct element code (3DEC), and the kinetic inertial force of the wedge under seismic loading can be obtained via calculating the net vectorial nodal force of the finite difference grid. Then, the factor of safety (FOS) of the wedge can be calculated based on limit equilibrium method (LEM) at each dynamic analysis step, therefore time series of the FOS for whole earthquake process can be obtained. For the purpose of evaluating the entire dynamic stability of the wedge, dynamic factor of safety (DFOS) is proposed and defined as a numerical value corresponding with a given rate of probability guarantee based on reliability theory. Consequently, the KVM inherits the merits of the LEM and also has fully nonlinear dynamic analysis capabilities, and the feasibility and correctness of the KVM are tested by an example given by Hoek and Bray (1981). Finally, a rock slope case in Wenchuan Earthquake regions of China is presented to verify the engineering practicability of the KVM, and the results matched the actual situation well. [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]

Multi-field information monitoring is useful to better understand the deformation and failure behaviour of landslides. Therefore, in this study, a physical slope model under excavation was analysed through multi-field monitoring to ascertain the failure mechanism of the slope. During the process of physical model tests, ① area information including 2D surface displacement, 2D surface strain, velocity, 2D surface temperature, and 3D surface deformation, ② line information including deep displacement and deep strain, and ③ point information of the earth pressure of the model were acquired via multi-field monitoring. The pre-failure, failure, and post-failure stages of the slope model are analysed through multi-field monitoring. The results indicate that the relative displacement between the yielding and stationary parts and a triangular shear plane reflect the deformation behaviour of the slope related to the arching effect. The arch ring expands and becomes elongated during the excavation process. The slope failure time can be effectively predicted via the inverse velocity method. Multi-field monitoring can reveal the behaviour of the slope model from different perspectives and offer new insights into the failure mechanism of the slope. [ABSTRACT FROM AUTHOR]

The estimation of shear strength of rock mass discontinuity is always a focal, but difficult, problem in the field of geotechnical engineering. Considering the disadvantages and limitation of existing estimation methods, a new approach based on the shadow area percentage (SAP) that can be used to quantify surface roughness is proposed in this article. Firstly, by the help of laser scanning technique, the three-dimensional model of the surface of rock discontinuity was established. Secondly, a light source was simulated, and there would be some shadows produced on the model surface. Thirdly, to obtain the value of SAP of each specimen, the shadow detection technique was introduced for use. Fourthly, compared with the result from direct shear testing and based on statistics, an empirical formula was found among SAP, normal stress, and shear strength. Data of Yujian (鱼简) River were used as an example, and the following conclusions have been made. (1) In the case of equal normal stress, the peak shear stress is positively proportional to the SAP. (2) The formula for estimating was derived, and the predictions of peak-shear strength made with this equation well agreed with the experimental results obtained in laboratory tests. [ABSTRACT FROM AUTHOR]

After the normal operation of the Three Gorges Reservoir, the water level of the reservoir will fluctuate periodically. Water level fluctuation will soften the rock and soil on the banks, induce underground water fluctuation and decrease the shear strength of rock soil on the banks, and in turn affect the landslide stability. The Huangtupo (黄土坡) landslide is a typical large and complex landslide in the Three Gorges Reservoir region. In particular, the stability of its riverside slumping mass has a great stake. On the basis of the analysis of engineering geological condition and formation mechanism of the Huangtupo landslide, the authors established the 2D finite element model of riverside slumping mass II# and selected proper mechanical parameters of the rock. With the GeoStudio software, according to the reservoir running curve, the simulation on coupling effect of seepage field and stress field was conducted in 7 different modes in a year. The results showed that: ➀ Huangtupo landslide is a large and complex landslide composed of multiple slumping masses, which occurred at different phases. Before reservoir impoundment, it was stable; ➁ it is quite difficult for riverside slumping mass I# and II# to slide as a whole; ➂ the stability coefficient of riverside slumping mass II# changes with the reservoir water level fluctuations. The minimum stability coefficient occurs 48 days after the water level starts to fall and the moment when the water level falls by 11.9 m. Landslide monitoring result is consistent with the numerical simulation result, which shows that although the reservoir water level fluctuation will affect the foreside stability of the landslide and induce gradual damage, the riverside slumping mass II# is stable as a whole. [ABSTRACT FROM AUTHOR]

Determination of the shear failure zones of rock joints leads to a better understanding of their shear mechanical behavior. In this paper, we present a low-cost approach to determining the shear damage zones of rock joints after direct shear tests. Experimental direct shear tests were performed on one pair of man-made and six pairs of natural samples to collect digital high-resolution images using a digital camera before and after the tests. For each sample, the images acquired before and after tests were brought into registration, and a disparity image was generated. Then, a binary image with the shear damage zones marked as true was generated, and the noise was filtered out with postprocessing methods. The traditional RISS and MN methods were employed to examine the performance of the proposed approach by comparing their accuracy, time consumption, adaptability and robustness. The results demonstrated that the proposed approach IR is comparable to the MN approach in terms of accuracy but saves 82.92% of the time, and has better accuracy, adaptability and robustness compared to the RISS approach. Highlights: A new approach based on the image registration technique was proposed to determine the shear damage zones of rock joints. The proposed approach showed better efficiency, accuracy, and robustness than the two traditional methods in the comparative study. The proposed approach has been integrated into the open-sourced SDZM toolbox, which facilitates engineering applications and comparative studies. [ABSTRACT FROM AUTHOR]

Wetting and drying cycles (WDCs) have a significant impact on the shear behavior of discontinuities with different joint wall materials (DDJMs). This influence is crucial for the reasonable evaluation of the long-term stability of soft and hard interbedded rock slopes under water level fluctuations. As the surface topographies of natural discontinuities collected from the field vary, conducting comparative experiments on natural discontinuity specimens with identical surface topographies is challenging. To solve this problem, a 3D surface topography reconstruction technique was employed to obtain DDJM specimens with three types of surface topographies collected from a typical sliding-prone stratum in the Three Gorges Reservoir area, China. A series of experiments, including computed tomography scanning, 3D laser scanning, and direct shear tests, were conducted to investigate the influence of WDCs on the micro- and macroproperties of joint walls, surface topographies, and shear behavior of DDJMs. The experimental results showed that repeated WDC treatments caused the degradation of the microstructures and macroscopic physical properties of the studied joint walls, and the more severely weakened joint wall played a predominant role in reducing the shear strength of DDJMs. The influence of WDCs on the surface topographies of DDJMs was negligible in this study; changes in the shear behavior of DDJMs were closely associated with the weakening of joint walls induced by WDCs; and the impact degree of joint wall weakening on the deterioration of the shear behavior of DDJMs was interactively influenced by and positively correlated with both the joint roughness coefficient and normal stress. These results will contribute to a better understanding of the evolution of the stability of soft and hard interbedded rock slopes induced by water level fluctuations in the Three Gorges Reservoir area and other reservoir regions. [ABSTRACT FROM AUTHOR]

Rock discontinuities fundamentally impact the mechanical and hydraulic behaviors of a rock mass, and thus it is a critically important task to characterize the geometrical parameters of these rock discontinuities. To measure the discontinuity orientation more accurately and efficiently, two well-known point clouds were taken as cases (a cube and a road cut), and an artificial neural network (ANN)-an machine learning algorithm-was established to identify discontinuities from point clouds through learning a small number of training samples, which had been manually selected from the raw point clouds. Four attributes associated with geometrical features of point clouds were specified as input parameters, namely, point XYZ-coordinates, point normal, point curvature, and point density. Two main groups-discontinuity and non-discontinuity-were produced in the output layer, and the number of the discontinuity groups greatly depended on the sets of discontinuities in the real situation. Using principal component analysis (PCA) and density-based spatial clustering of applications with noise (DBSCAN), single discontinuities were extracted from the group discontinuities which were obtained using ANN, and the corresponding orientations were calculated. The results obtained with the proposed method in this study matched the field surveys and results calculated by a modified region-growing algorithm. The computational efficiency was significantly enhanced using the proposed method, only taking several seconds to process a huge data. More importantly, the accuracy of discontinuity detection was greatly improved by specifying the noise data as the non-discontinuity groups during training samples selection in ANN. The ANN approach does not require the engineers have a strong professional background in computer programming, which simplified the detection and characterization process of rock discontinuity. Furthermore, an APP-named DisDetANN-was developed to implement the rock discontinuity detection based on the proposed ANN model, and the full code of the DisDetANN has been freely shared on GitHub. Highlights: An artificial neural network was created by machine learning to detect group discontinuities from point clouds. Point coordinate, normal, curvature, and density were considered in input layers of the artificial neural network. A clustering algorithm was employed to subdivide group discontinuities into single discontinuities. Both efficiency and accuracy of the discontinuity detection was improved by the proposed approach. An APP and full codes of the proposed method were freely made available to the engineering community. [ABSTRACT FROM AUTHOR]

Recent research has paid little attention to weakening of discontinuities with different joint wall material (DDJM) induced by wetting and drying cycles. Experimental investigations were conducted to examine the effects of wetting–drying cycles on weakening of three typical types of natural planar DDJM collected from a sliding-prone formation in the Three Gorges reservoir region of China. Deterioration of the corresponding four types of discontinuities with identical joint wall material (DIJM) were also been studied for comparison. The weakening laws of DDJM were revealed from macro- and microperspectives by testing on mineral compositions, microstructures and water absorption rate of joint walls as well as shear strength of discontinuities. The results indicate that the repeated wetting–drying cycles lead to obvious changes in microstructure and increases of macro water absorption rate for the studied joint walls with the changing degree closely related to their clay mineral contents; the peak shear strengths of DDJM gradually decreases with the wetting and drying cycles for a certain normal stress with the weakening rate between that of the DIJM with two joint wall materials of the DDJM, while closer to that of DIJM with the weak half materials of the DDJM; significant correlations have been found between the variation coefficient of rock microstructure of joint walls and the macrodeterioration coefficient of DDJM; the changing rates of multi-scale parameters before and after six wetting–drying cycles vary obviously, indicating the weakening is slowed down after six wetting–drying cycles for the studied discontinuities. Highlights: Effects of wetting-drying cycles on weakening discontinuities with different joint wall material were studied. Deterioration of the discontinuities with identical joint wall material were also been investigated for comparison. The weakening laws were revealed from macro and micro perspectives. Significant correlations have been found between the variation coefficient of microstructure of joint walls and the macro deterioration coefficient. The results could provide a basis to better understand the stability evolution of rock slopes with soft and hard rock interbedded. [ABSTRACT FROM AUTHOR]

In a recent discussion by Rashida and Singh (Rock Mech Rock Eng, 2023) regarding our paper (Tan et al. Rock Mech Rock Eng 56:7599–7617, 2023) investigating the thermal effects on non-Darcian flow within heated rock fractures, several points were raised. They argued that the temperatures and durations in our experiments may not induce thermal expansion in fractured rock due to low thermal expansion coefficients. Additionally, they highlighted potential water phase changes during heating and recommended precautions, such as pre-heated water and confining pressure, which were not implemented in our experimental setup. In response, we provide further clarification. Firstly, concerning heating time, our focus is on temperature-induced alterations in fracture geometry during the heating process rather than after temperature stabilization. Secondly, our detailed analysis of the coefficient of thermal expansion for granite specimens confirms that thermal expansion does lead to fracture closure within the imposed temperature range, affecting flow characteristics. Lastly, considering the aims of the study, precautions against water phase changes were not implemented, but the potential water phase changes had a negligible effect on our results due to the low temperatures employed and the short water residence time in the fracture. In summary, we maintain the methodological soundness of our experimental setup and the appropriateness of the obtained results in alignment with the objectives of our study. The discussion and this response are helpful to further clarify our experimental results and eliminate potential ambiguities. Highlights: Temperature-induced alterations in fracture geometry during the heating process are noteworthy. Even minor fracture closure resulting from thermal expansion markedly influences flow behaviors. Low test temperatures render potential water phase changes inconsequential to our findings. [ABSTRACT FROM AUTHOR]