The impoundment of the 660-km long reservoir behind the huge Three Gorges Dam, the world's largest hydropower station, increased regional seismicity and reactivated severe geohazards. Before the ...reservoir filling was initiated in 2003, the region had approximately two earthquakes per year with magnitudes between 3.0 and 4.9; after the full impoundment in 2008, approximately 14 earthquakes per year occurred with magnitudes between 3.0 and 5.4. In addition, hundreds of landslides were reactivated and are now in a state of intermittent creep. Many landslides exhibit step-like annual pattern of displacement in response to quasi-regular variations in seasonal rainfall and reservoir level. Additional problems include rock avalanches, impulse waves and debris flows. The seriousness of these events motivated numerous studies that resulted in 1) Better insight into the behavior and evolution mechanism of geohazards in the Three Gorges Reservoir Area (TGRA); 2) Implementation of monitoring and early-warning systems of geohazards; and 3) Design and construction of preventive countermeasures including lattice anchors, stabilizing piles, rock bolts, drainage canals and tunnels, and huge revetments. This paper reviews the hydro-geologic setting of TGRA geohazards, examines their occurrence and evolution in the past few decades, offers insight learned from extensive research on TGRA geohazards, and suggests topics for future research to address the remaining challenges.
The uncertainty involved in the interpreted geological model may be categorized as the stratigraphic uncertainty and the properties uncertainty. Note that although the influence of the properties ...uncertainty on the behavior or performance of the geotechnical system and the geotechnical design has been extensively reported in the literature, the studies that address the stratigraphic uncertainty are limited. This paper presents a study regarding the influence of the stratigraphic uncertainty on the behavior of the geotechnical system and the geotechnical design. In which, the uncertainty in the stratigraphic configuration is characterized using the stochastic Markov random field-based approach with a large number of potential stratigraphic realizations. With these stratigraphic realizations as inputs, the influence of the stratigraphic uncertainty on the behavior of the geotechnical system is evaluated in a probabilistic manner; then, the design of the geotechnical system is formulated as a bi-objective optimization-based problem that considers the design safety and the cost simultaneously. To demonstrate the effectiveness of the proposed probabilistic analysis and design approach, the problem of designing stabilizing piles in a slope consisting of multiple strata is studied. The parametric study is further conducted to analyze how the probabilistic analysis results are influenced by the pile parameters and how the probabilistic design results are influenced by the additional boreholes.
•The uncertainty in the stratigraphic configuration is characterized with the stochastic Markov random field-based approach.•The influence of the stratigraphic uncertainty on the behavior of the geotechnical system is studied.•The influence of the pile parameters on the probabilistic analysis results of the reinforced slope is studied.•The superiority of the proposed probabilistic analysis and design over the deterministic approaches is demonstrated with an illustrative application.
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•Centrifuge modelling as an important tool in the understanding of deformation and failure behaviours of landslides.•Various mitigation methods modelled and verified through ...centrifuge modelling.•Seven important aspects suggested for future research on centrifuge modelling for landslides.
Landslides are serious geohazards that occur under a variety of climatic conditions and can cause many casualties and significant economic losses. Centrifuge modelling, as a representative type of physical modelling, provides a realistic simulation of the stress level in a small-scale model and has been applied over the last 50 years to develop a better understanding of landslides. With recent developments in this technology, the application of centrifuge modelling in landslide science has significantly increased. Here, we present an overview of physical models that can capture landslide processes during centrifuge modelling. This review focuses on (i) the experimental principles and considerations, (ii) landslide models subjected to various triggering factors, including centrifugal acceleration, rainfall, earthquakes, water level changes, thawing permafrost, excavation, external loading and miscellaneous conditions, and (iii) different methods for mitigating landslides modelled in centrifuge, such as the application of nails, piles, geotextiles, vegetation, etc. The behaviors of all the centrifuge models are discussed, with emphasis on the deformation and failure mechanisms and experimental techniques. Based on this review, we provide a best-practice methodology for preparing a centrifuge landslide test and propose further efforts in terms of the seven aspects of model materials, testing design and equipment, measurement methods, scaling laws, full-scale test applications, landslide early warning, and 3D modelling to better understand the complex behaviour of landslides.
Joint Roughness Coefficient (JRC) is one of the principal parameters used to calculate the shear strength and conducting aperture of discontinuities. Originally, 10 standard discontinuity profiles ...were commonly associated with JRC values. However, as the original profiles provided a rough estimation of joint roughness, many researchers attempted to investigate different methods of analysis to determine JRCs accurately. In the current study, we are proposing a new method for accurate JRC estimation. Firstly, we introduced a new roughness index (λ) using a Root Mean Square method, which considers inclination angle, amplitude of asperities and their directions. Secondly, the logistics function between λ and JRC was derived after locating the mean line, which is the line between maximum and minimum points of asperities. Finally, three formulae were developed to calculate upper-bound, suggested and lower-bound values of JRCs in relation to the variation of λ for two-dimensional discontinuity profiles. Comparison of our experimental test results with data available in the literature showed that the proposed roughness index, λ, can be used to determine JRC values accurately resulting in better estimation of discontinuity shear strength and conducting apertures. In addition, the sensitivity of JRC, shear strength and the ratio of mechanical aperture to conducting aperture (E/e) with respect to λ were also investigated. The results revealed that trends of JRC, shear strength and E/e ratios are similar. These parameters are found to be most sensitive when λ is in the range of 0.05–0.20.
•We proposed a new method to calculate accurate JRC values for rock joint surfaces.•A new roughness index (λ) was introduced by using Root Mean Square method (Z2).•A logistics function between λ and JRC was derived.•Direct shear box test results were compared with shear strengths determined by using proposed roughness index and Z2.•It was verified that new roughness index could be used to determine accurate JRC values for rock joints.
This paper compares the performance of five popular machine learning methods, namely, particle swarm optimization–extreme learning machine (PSO–ELM), particle swarm optimization–kernel extreme ...learning machine (PSO–KELM), particle swarm optimization–support vector machine (PSO–SVM), particle swarm optimization–least squares support vector machine (PSO–LSSVM), and long short-term memory neural network (LSTM), in the prediction of reservoir landslide displacement. The Baishuihe, Shuping, and Baijiabao landslides in the Three Gorges reservoir area of China were used for case studies. Cumulative displacement was decomposed into trend displacement and periodic displacement by the Hodrick–Prescott filter. The double exponential smoothing method and the five machine learning methods were used to predict the trend and periodic displacement, respectively. The five machine learning methods are compared in three aspects: highest single prediction accuracy, mean prediction accuracy, and prediction stability. The results show that no method performed the best for all three aspects in the three landslide cases. LSTM and PSO–ELM achieved better single prediction accuracy, but worse mean prediction accuracy and stability. PSO–KELM, PSO–LSSVM, and PSO–SVM always yielded consistent predictions with slight variations. On the whole, PSO–KELM and PSO–LSSVM are recommended for their superior mean prediction accuracy and prediction stability.
•The performances of machine learning methods depend on the selected evaluation index and reservoir landslide case.•Using single prediction accuracy for evaluating the superiority of machine learning methods may be unreliable.•PSO-KELM and PSO-LSSVM are recommended for their superior mean prediction accuracy and prediction stability.
Although numerical methods based on strength reduction are becoming popular in slope stability analysis, they fail to provide a distinct critical slip surface and only provide a shear band. The ...widely used visualization techniques for defining the critical slip surface are susceptible to subjective judgment and are inefficient for batch analysis and three-dimensional analysis. When a slope fails, the displacements on the two sides of the critical slip surface will be substantially different. Based on this observation, an automatic identification method for locating the critical slip surface is proposed. The k-means clustering algorithm is first applied to automatically separate the nodal displacements into two categories representing the sliding mass and the stable block. Then, the scatters near the separation surface are obtained by constructing the alpha shape of the sliding mass. Finally, the critical slip surface is obtained by fitting the extracted scatters. A homogeneous slope, a slope with a thin weak layer and a real landslide are used to test the effectiveness of the proposed method. The results show that the proposed method can automatically and accurately identify two-dimensional and three-dimensional critical slip surfaces.
•An automatic method for identifying the critical slip surface of slopes is proposed.•The proposed method is simple and not susceptible to subjective judgments.•The proposed method can accurately identify the distinct 2D/3D critical slip surface.
An accurate prediction of landslide displacement is challenging and of great interest to governments and researchers. In order to reduce the risk of selecting the types of influencing factors and ...artificial neural networks (ANNs), a multiple ANNs switched prediction method is proposed for landslide displacement forecasting. In the first stage, a set of individual neural networks are developed based on different environmental factors and/or different training algorithms. In the second stage, a switched prediction method is used to select the appropriate individual neural network for prediction purpose. For verification and testing, three typical landslides in Three Gorges Reservoir, namely Baishuihe landslide, Bazimen landslide and Shiliushubao landslide, are presented to test the effectiveness of our method. Application results demonstrate that the proposed method can significantly improve model generalization and perform similarly to, or better than, the best individual ANN predictor.
•A set of predictors considering different environmental factors are established.•A switched method is proposed to select the appropriate individual predictor.•Three typical landslides are presented to illustrate the capability of the method.
The accurate determination of crack initiation stress (CI) is significant for understanding rock deformation and failure. In this paper, a new concept is introduced, namely the relative compression ...strain response (RCSR), which represents the compressive deformation of the rock before dilatancy of the rock is introduced. An RCSR-based method for determining CI is proposed and compared with existing methods, i.e., (1) the volumetric strain (VS) method, (2) the lateral strain (LS) method, (3) the crack volumetric strain (CVS) method, (4) the cumulative acoustic emission hit tangent (CAEHT) method, and (5) the lateral strain response (LSR) method. Data for the comparison are collected from 227 uniaxial compression test and 222 compression test for diverse rock types. The comparison results show that, the CI determined using the proposed method is in good agreement with that determined using the existing methods. The CI values determined using different methods are similar, at approximately 0.5 of uniaxial compressive strength (UCS). The ratio of CI to peak strength (PS) is approximately 0.55 under triaxial compression, which is greater than the CI/UCS ratio. According to the analysis of variance (ANOVA), there is no statistical difference among the existing methods. Compared with the exisiting methods, the proposed method has advantages of avoiding users judgment subjectivity Thus, the RCSR method can be employed to determine the CI under uniaxial and triaxial compression.
•The relative compression strain response (RCSR) method to determine the CI is proposed.•An amount of uniaxial and triaxial compression tests for different rock samples data from the literature were collected.•The CI/UCS ratio in uniaxial compression and the CI/PS ratio in triaxial compression are analyzed.
The shear mechanical behaviour of slip zone soil is of great significance for the stability analysis of landslides. Based on the shear deformation-failure characteristics of slip zone soil and the ...statistical damage theory, a shear constitutive model is proposed to describe the shear stress - displacement relation of slip zone soil. Parameters in the proposed model have clear physical-mechanical meaning, and can be easily obtained by shear tests. The shear constitutive model is verified by comparing model results with ring-shear test results on the slip zone soil from the Huangtupo landslide in the Three Gorges Reservoir Area of China. It reveals that the model is capable of capturing the salient behaviour of the slip zone soil, such as the pre-peak and post-peak deformation characteristics. Moreover, utilizing limited ring-shear test data under given normal stresses, shear stresses at various shear displacements under untested normal stress are available by this model. Finally, a dynamic evaluation method of landslide stability, which incorporates the landslide displacement by presented constitutive model, is proposed and applied to analyze the stability of the Riverside Slump II# of the Huangtupo Landslide.
•A new shear constitutive model is proposed to describe the mechanical properties of slip zone soil.•A set of ring-shear test results on the slip zone soil from an active landslide are well simulated by the model.•The proposed model is capable of predicting the shear stress - shear displacement curves.•A dynamic evaluation method of landslide stability is proposed.
Site characterization, which aims to characterize the subsurface stratigraphic configuration and the associated geo-properties, has long been a significant challenge in geological and geotechnical ...practice. Due to the complexity and inherent spatial variability of the geological bodies and the limited availability of borehole data, uncertainty is unavoidable in the characterized subsurface stratigraphic configuration and the associated geo-properties. In previous studies, the stratigraphic uncertainty and the geo-properties uncertainty were characterized separately. This paper proposes a conditional random field approach for a coupled characterization of stratigraphic and geo-properties uncertainties. The spatial correlation of the stratum existence between different subsurface elements and the spatial correlation of geo-properties are characterized by two autocorrelation functions, determined with the maximum likelihood principle. With the knowledge of the spatial correlation of the stratum existence, the stratigraphic configuration can be sampled using a modified random field approach. Then, the spatial correlation of the geo-properties is updated based on the sampled stratigraphic configuration. With the updated spatial correlation of the geo-properties, the spatial distribution of the geo-properties can readily be simulated with the conditional random field theory. The effectiveness of the proposed approach is demonstrated through a case study of probabilistic site characterization of an offshore wind farm site in Taiwan. To extend the applicability of the proposed approach, a probabilistic evaluation of liquefaction potential at this site under a given seismic shaking level is performed.
•A probabilistic method for characterizing the geological model is proposed.•Characterizations of stratigraphic and geo-properties uncertainties are coupled.•Stratigraphic configuration is simulated with modified random field approach.•Spatial variability of geo-properties is simulated with conditional random field.•The spatial correlation structure is estimated with maximum likelihood principle.
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