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Previous determinations of the optimal stabilizing pile location have generally been based on the idealized assumption of arc-shaped sliding surfaces. This assumption, however, may be inconsistent with the actual situation of most common irregular shapes, such as the step shape; as a result, determinations based on this assumption tend to involve considerable error. This paper presents a strategy, termed the local safety partitioning (LSP) methodology, for accurately determining optimal pile locations for step-shaped configurations. Instead of assuming the sliding surface to be arc-shaped, this strategy considers the actual sliding shapes. A new index termed the local safety factor is introduced for measuring the stabilities of local landslide masses, and this method employs the Swedish slice method to calculate the value of the index. The LSP methodology consists of four procedures: slicing the landslide mass into blocks, calculating the local safety factor of each sliced block, dividing the landslide mass into local partitions based on the previous step, and identifying the optimum pile position using previously identified partitions. The performance of the presented methodology is illustrated using the Jinle No. 2 landslide case for well-rounded demonstration and using the Yancun landslide case for additional validation. The results indicate that analysis of a reinforced landslide employing the LSP methodology acquires the largest safety factor and smallest deflection, shear force and bending moment on the pile body compared with any other case from a series of positions that incorporate traditional positions for arc-shaped sliding surfaces. The presented methodology provides a simple but accurate determination of the optimal stabilizing pile location for stepped sliding surfaces, although it may involve errors and unexpected limitations when applied to arc shapes and peculiar scenarios. [ABSTRACT FROM AUTHOR]

The distribution of soil pressure in landslides above anti-slide piles is a key factor in their design. The paper describes the evolution of stresses near soil-piles by testing a physical scale model during progressive loading. Displacement monitoring data on the surface of the landslide during loading discloses four main evolutionary stages: the initial stage of deformation, the uniform deformation stage, the accelerating deformation stage, and the damage stage. During initial deformation, the vertical distribution of soil pressure above anti-slide piles is sigmoidal, with the highest pressures occurring in the middle and upper parts of the slide mass. Next, during the uniform deformation stage, the soil pressure begins to assume a parabolic shape in a vertical profile, and this shape is fully realized during subsequent accelerating deformation. Finally, during the damage stage, the soil pressure relaxes to low values near the center of the slide mass, effectively inverting the parabola. Thus, the distribution of soil pressure above anti-slide piles changes in a complex manner during deformation, and these effects must be accommodated in the analysis and design of anti-slide piles. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The fate of reservoir landslides is mainly dictated by the mechanical behavior of soil in the sliding zone. This soil may be altered under changing environmental conditions of both physical and chemical nature. In this paper, we present a laboratory study on the changing soil properties under complex physicochemical interactions. The soil specimens are subjected to 1, 2, 3, 5, 7, and 10 wetting-drying cycles. The soil strength is determined by triaxial tests. These tests are performed with three types of pore water, namely, acidic groundwater (AGW), normal groundwater (NGW), and distilled water (DW). The deterioration of soil strength, the change in soil microstructure and mineral composition are observed and correlated. Interesting findings for reservoir landslides are drawn: acidic underground water considerably damages the soil microstructure and deteriorates the shear strength compared to normal underground water, while distilled water causes minimal disaggregation. A three-stage micromechanism associated with four physicochemical interactions is revealed, providing insights into microstructure damage and mineral transformation. • Combined effect of physicochemical interaction on the shear strength of sliding zone soil. • Microstructure evolution of sliding zone soil by five classified pores. • Variations in minerals and cations signify potential chemical interactions between soil and water. • Four types of physicochemical interactions in the evolution process of sliding zone soil. • Three-stage evolutionary mechanism for soil deterioration. [ABSTRACT FROM AUTHOR]

Reservoir landslide evolution is a complex multi-fields dynamic process which involves the interaction of the seepage field, stress field, displacement field and temperature field. After installing the stabilizing structure into landslide, the landslide and stabilizing structure will establish the landslide-stabilization system and lead to a more complex multi-fields evolution process under the reservoir operation. To study this complex problem, this paper designs and establishes a comprehensive in-situ multi-fields information monitoring platform which has been installed on Majiagou landslide in Three Gorges Reservoir area. The multi-fields information monitoring platform has four components: the landslide-stabilization system, the in-situ multi-field monitoring system, the data transmission and receiving system, and the database management system. The landslide-stabilization system includes Majiagou landslide and two experimental reinforced concrete piles. The in-situ monitoring system consists of landslide surface deformation monitoring system, experimental piles monitoring system and boreholes monitoring system. The landslide surface deformation monitoring system includes GPS stations and fiber lines. The experimental pile monitoring system consists of earth pressure cells around piles, stress and strain gauges on steel bars, and strain and temperature fiber sensors in piles. The borehole monitoring system includes boreholes with inclinometers, water pressure and water level gauges, fiber sensors. Therefore, the in-situ monitoring system can monitor the seepage, stress, displacement and temperature fields in the landslide, as well as the force and deformation in the experimental piles. Currently, the data transmission and management system is under construction and will be finished soon. Current monitoring results show that the landslide moves along three slip surfaces and the deformation of the experimental piles is influenced by reservoir operation. This platform can provide multi-fields data for scholars to study the evolution of landslide-stabilization system. [ABSTRACT FROM AUTHOR]

The paper presents a study on the location determination of stabilizing piles in colluvial landslides with the interbedding of hard and soft bedrocks. A double-arc model is proposed to describe the shape of sliding surface of colluvial landslides, and the corresponding slope surface can be divided into three types, namely the concave type, straight line type, and convex type, respectively. The driving force of colluvial landslides and interbedding characteristics of hard and soft bedrocks are two important factors affecting the determination of optimal location for stabilizing piles. The results indicate that the stabilizing effect of the piles mainly depends upon the hard bedrock. The effect of the location of hard layer bedrock on the pile deformation is represented by the location coefficient. It is found that the optimal location of stabilizing pile locates where both top and bottom hard layers are present; and, the location with a top soft layer is unfavorable, particularly when the hard layer has a large location coefficient. The case study of Yanguan landslide illustrates that the location of stabilizing pile is determined with the proposed method is effective, with a considerable decrease in both the displacement and internal force of the stabilizing piles. [ABSTRACT FROM AUTHOR]

The mechanical behavior of in situ sliding zone soil is unique and is significant for the state identification and prediction of landslides. This study focuses on interpreting the anisotropic deformation observed on the sliding zone soil of the Huangtupo landslide during an in situ triaxial creep test; specifically, the deformation of the A-Surface (towards 35° dip direction) of the soil cube, which points approximately to the landslide sliding orientation, is significantly large. Such anisotropy could be attributed to damaged structure, assumed as pre-existing directional cracks, of the in situ soil. Therefore, a Discrete Element Method (DEM) model containing prefabricated cracks is established to investigate the deforming behavior of compressed soil during in situ creep test on the mesoscopic scale. Results indicated that the specimen's anisotropic deformation is intimately related to the presence of prefabricated cracks. Subjected to the prefabricated cracks, microcracks generated during the loading process of the specimen initiated and developed in a directional way, subsequently forming directed cracks. Then the directed cracks tend to form a complete slip zone. However, due to the insufficient vertical load, the directed cracks were unable to coalesce, and the soil mass did not fail during the in situ creep test. Thereafter, additional load was applied in the simulation model. The directed cracks then merged and a full slip zone formed, and the soil was completely destroyed. As a consequence, the anisotropic characteristics of compressed in situ sliding zone soil can be well explained in view of the cracks development. This study may help perceive the landslide deformation characteristics and facilitate the evaluation and prediction methods of landslide stability. • Anisotropic deformation of the in situ sliding zone during compression • Formation of cracked slip zone in a compressed soil sample • Brand new recognition on the in situ sliding zone soil with prefabricated cracks [ABSTRACT FROM AUTHOR]

Due to the landslide-prone geological conditions, many landslides have occurred in the Three Gorges Reservoir Region (TGRR), most of which are slow-moving ancient landslides characterized by preexisting shear surfaces. In this study, with the purpose of making full use of reactivated residual strength to prevent and treat the slow-moving landslides, such as designing anti-slide piles, the Huangtupo landslide as a typical reactivated ancient landslide in the TGRR was selected to study the overconsolidation (OCR) effect on the reactivated residual strength of deep-seated sliding zone soil by conducting a series of laboratory ring shear tests. It was found that after a short rest of one day, the reactivated residual strength increased with the increase of OCR under a given normal effective stress, but it was lost after a small shear displacement. The overconsolidation effect on reactivated residual strength at a lower stress was more prominent than that at a higher stress. Very coarse sand with a size of 1–2 mm inside the remoulded deep-seated sliding zone soil sample exerts direct control on the reactivated residual strength, and it significantly influences the overconsolidation effect on reactivated residual strength. The results could provide a reliable scientific basis for improving the stability analysis and reinforcement measures of the slow-moving landslides in the TGRR, as well as can be applied to similar slow-moving landslides in other areas. • The reactivated residual strength increased with the increase of OCR after a short rest of one day. • The overconsolidation effect at a lower stress was more prominent than that at a higher stress. • Very coarse sand inside the soil sample significantly influences the overconsolidation effect. [ABSTRACT FROM AUTHOR]

The behavior of stabilizing piles with different embedded lengths in bedrock with a hard upper layer and a weak lower layer is examined using physical model tests. Based on the geological model of the landslide with bedrock with a hard upper layer and a weak lower layer, the pile–landslide physical model is developed and includes the data collection system, the pile–landslide model and the loading system. The real-time deformation and moment of the stabilizing pile is obtained in the process of loading at the trailing edge of the landslide for different percentages of hard bedrock. The test results indicate that the percentage of hard bedrock has a strong influence on the deformation and moment of the stabilizing pile embedded in bedrock with a hard upper layer and a weak lower layer. A higher percentage of hard bedrock can result in a greater maximum bending moment of the stabilizing pile and a smaller displacement at the stabilizing pile head, and vice versa. The results also show that 40% of hard bedrock can be considered the critical condition in bedrock with a hard upper layer and a weak lower layer. The percentage of hard bedrock has a limited influence on the deformation of the stabilizing pile when the percentage is greater than 40%. Moreover, four tests with stabilizing piles with different embedded lengths are conducted to investigate the most suitable embedded length in the bedrock with a hard upper layer and a weak lower layer. The results indicate that 28.5 cm is a reasonable embedded length for the stabilizing pile in the two-layered bedrock with a hard rock percentage of 20%. [ABSTRACT FROM AUTHOR]

The paper presents a novel optimal plane arrangement of stabilizing piles in terms of the provided half simplified flattened ellipsoid model, which can be used to describe the three-dimensional characteristics of sliding mass for colluvial landslides. By studying the friction soil arching effect between the adjacent stabilizing piles, a reasonable pile spacing model for stabilizing piles was deduced in consideration of the driving force and shear strength of sliding mass as well as the dimension of pile cross-section. The results indicate that the net pile spacing is in direct proportion to the height of pile cross-section and shear strength parameters of sliding mass, but in inverse proportion to the driving force intensity. Consequently, the net pile spacing should steadily increase from the major slip profile to the profiles near the boundaries accordingly, which can be called the non-uniformly spaced arrangement principle of stabilizing piles for colluvial landslides. In view of the scale factor and groundwater in the different cross sections of landslide, the improved formula of stability coefficient based on the Fellennius method was proposed accordingly. Furthermore, the concept of stability limit was put forward to confine the rational arrangement region for stabilizing piles; consequently, the region beyond the rational arrangement region is not necessary to set piles any more. The case study of the Erliban landslide in the Three Gorges Reservoir Region of China shows that the quantitative optimal plane arrangement scheme based on the proposed reasonable pile spacing model and stability limit only requires 25 stabilizing piles rather than 31 stabilizing piles in the conventional uniformly spaced arrangement scheme, with an obtainable savings of 19.4% in the number of stabilizing piles. [ABSTRACT FROM AUTHOR]

Effective detection of groundwater in landslide areas is crucial for landslide monitoring. The magnetic resonance sounding (MRS) method is a geophysical technique that can directly detect groundwater. However, its application in landslide groundwater monitoring is often hindered by the complex topography of landslides. This paper presents an MRS framework that accounts for the impact of landslide topography on groundwater detection. The framework includes the use of drone photogrammetry to obtain high-precision topography data and real-time kinematic equipment to acquire the coordinates of key points along the MRS coil. A three-dimensional finite element model is then constructed to calculate the alternating magnetic field generated by the MRS coil and the kernel function required for MRS inversion. Two typical landslide topography models—terrace and gully—are constructed and analyzed using numerical simulations. The results indicate that landslide topography significantly impacts the quality of groundwater information retrieved by MRS in both one-dimensional and two-dimensional inversions, affecting the accurate detection and identification of infiltration surfaces, sliding zone water, and bedrock surfaces. If accurate topography data are obtained and appropriate kernel functions are calculated, the accuracy of the inversion can be greatly improved. An example of using the MRS method to detect groundwater in a complex landslide in the Three Gorges Reservoir area of China is then presented. The MRS inversion results that consider landslide topography are confirmed using borehole data, electrical resistivity tomography detection results, and on-site drainage tunnel investigations. The water-content distribution inside the landslide body is obtained, providing information helpful to define sliding zones in multi-level landslides. The proposed landslide MRS detection framework makes it possible to apply MRS methods to the detection of landslide groundwater distribution, analysis of seepage fields, and discrimination of landslide geological structures. • Landslide topography significantly affects the quality of groundwater information retrieved by MRS. • Obtaining accurate topography data and calculating appropriate kernel functions improve MRS inversion results. • MRS field work on a complex landslide is validated by borehole data, ERT, and on-site drainage tunnel investigations. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicle (UAV) technique has been widely utilized in geohazards assessment. In this work, the effectiveness of the UAV photogrammetry in the remote sensing and assessment of the landslide behavior is demonstrated through a case study of a landslide that occurred in Guizhou, China on 10 June 2018. The post-landslide assessments were conducted through a field investigation by a team of experts; and, two UAV photogrammetry-based surveys were carried out. On the basis of a detailed inspection of the high-resolution aerial photographs collected from the UAV photogrammetry and historical satellite imagery, subsurface stratigraphic configuration revealed from borehole explorations and the local rainfall data collected, the failure mechanism of this landslide is investigated. The occurrence of this landslide is probably attributed to the combined influence of the long-term rainfall and the engineering activities at this site. An automatic landslide cracks recognition model, which is based on the deep learning-based image recognition technique of RetinaNet, is further developed to map the cracks at the landslide site. The effectiveness of this automatic crack recognition model is validated through quantitative comparisons between the landslide cracks recognized and the field survey results. Based upon the landslide cracks identified on two different dates after this landslide event (by the field survey and automatic crack recognition model) and the subsurface displacement revealed from a drilled hole, the evolution behavior of this landslide is analyzed. The results show that the stability of this landslide was not achieved during the first slide in June 2018 and the limit of the landslide was increased much from June to November 2018. In such a situation, the elements at risk in the zones that are potentially impacted by this landslide are identified (with the aid of the UAV images collected), and a preliminary consequence assessment is conducted. • The failure mechanism of a landslide in Guizhou, China is investigated. • An automatic landslide cracks recognition model is developed using RetinaNet. • The landslide behavior is studied based on the cracks recognized on two dates. • A UAV images-based preliminary assessment of the landslide consequence is made. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract Geological disasters have occurred frequently in the Three Gorges Reservoir area. Therefore, the stability and failure mode research on riverside landslides has become increasingly important. Taking the toe of Liangshuijing landslide as a case study and combining the geological conditions of the Three Gorges Reservoir area, a centrifuge slope model is constructed. In addition, the fluctuation of the water level is simulated in the centrifuge model test. Based on the digital photography, laser displacement sensors (LDS), pore pressure transducers (PPT) and earth pressure sensors (E), multi-physical data are obtained. Finally, numerical simulation is carried out to analyze the stability and deformation characteristics of the slope model. The results indicate that: (1) At the water level rise stage, the model is dominated by the vertical displacement. And the horizontal displacement is much larger than the vertical displacement at the drainage stage. (2) Cracks first appear at the toe of the slope and extend to the middle and rear of the model gradually. Then, deformation occurs in the middle platform of the slope. (3) At the water level rise stage, the factor of safety increases rapidly. When the reservoir water level remains stable, the stability of the slope decreases slowly. And at the drainage stage, the factor of safety decreases first and then increases. (4) There is a significant positive linear correlation between the decline rate of the safety factor and the drainage rate over a certain test range. And the stability of the landslides on the reservoir banks would become worse gradually during the long-term cyclic operation of the Three Gorges Reservoir. Highlights • The fluctuation of the water level is simulated in the centrifuge model test. • Qualitative and quantitative method are combined to analysis the evolution of the landslide. • The failure mode and the deformation mechanism of the slope are revealed by the centrifuge model test. [ABSTRACT FROM AUTHOR]

The red mudstone sediments are widely encountered in earthquake region northwestern China which is vulnerable to the occurrence of landslides. Previous studies focused on rain-induced shallow landslides. Some deep-seated landslides in red clay with a gentle inclination are still not well understood. A fatal landslide named as Zhengjiamo landslide, located in Tianshui, China, was investigated. The aim of this study was to study mechanism of shear surface development under earthquake using a series of cyclic triaxial tests. The test results of the red clay from the Zhengjiamo landslide revealed that the undrained shear strength and excess pore pressure increase with increasing confining stresses σ 3 and OCR. It is also observed that those stress–strain behaviors on the deviatoric stress, axial strain and pore water pressure, subsequent to the initial contractive response, the saturated clay exhibited dilation upon continued shearing. The dilated tendency of the clay becomes more prevalent with increasing confining stresses σ 3 and OCR during the dynamic response. The reduction of shear strength of the red clay is substantially caused by the increasing number of cycles N. Under earthquakes, the sliding zone may behave in a brittle- ductile pattern. [ABSTRACT FROM AUTHOR]

Deep-seated mudstone landslides are widely distributed in northwest China. The Zhengjiamo landslide occurred in 734 CE near Taijing, Tianshui region. It was triggered by the main shock of the historical Ms = 7.0734 CE earthquake. The earthquake also induced a wide range of landslides in this area, with hundreds of fatalities and many houses destroyed by landslide debris. Based on a detailed field survey, borehole data, and mapping, a detailed geological reconstruction of the slope was achieved and the geo-mechanical features of the claystone involved in the landslide were obtained. Using the Particle Flow Code to simulate the mechanism of the Zhengjiamo landslide, the features of the landslide dynamics were obtained using a 5-stage model. During the landslide process, the slip mass at the front and upper edges exhibited higher mobility than at the rear and bottom edges. Furthermore, the contact bond strength of the sliding body gradually weakened. The model indicates that the particle bond strength has a larger influence on the maximum runout distance and landslide debris morphology than the type of weak intercalated layers. The slip mass presented a rotational slide pattern and remained on the slip plane throughout the sliding process. Finally, the earthquake uplifted the slope toe, which prevented the slip mass from gliding. The modelled scenario provided a reasonably good fit to the actual topography, verifying the modelling results. After the historical earthquake, with the clay minerals swelling and shrinking under rainfall and efflorescence conditions, the structure of the soft rock changed, contributing to the weakening of the sliding rock mass. The landslide gradually crept and evolved to its current topography. [ABSTRACT FROM AUTHOR]

Landslide early warning systems can be implemented based on the monitoring and prediction of landslide displacements. The internal mechanisms of landslides are very complex, and precise mechanistic models of landslides are difficult to obtain; therefore, data-driven models are usually applied. From the perspective of dynamic system theory, landslide development should be considered a dynamic process. Because traditional models, such as feed-forward neural networks, can only express static relationships, the applicability of these static models is quite limited in landslide prediction tasks. In our study, recurrent neural networks are established and trained into dynamic predictors of landslide displacement using a training algorithm named reservoir computing. A shortcoming of the reservoir computing algorithm is that the models will not perform well with insufficiently large training sets. Because practical landslide displacement recordings are usually quite short, interpolation techniques are employed to enhance the training of the dynamic predictors. The method proposed in this paper is applied to predict the developments of three landslides in the Three Gorges area, and the predicted values are close to the actual measurements. Improvements relative to sophisticated static predictors and basic dynamic predictors are obvious. [ABSTRACT FROM AUTHOR]

The construction of the huge Three Gorges reservoir affected a large region, and the resultant geological and environmental impacts have caused global concern. The remarkable, 30-m annual fluctuation in the reservoir water level poses a significant threat to slope stability in this area. Four hundred sixty-two landslides were identified in the Zigui basin using historical records, satellite images, field investigations and unmanned aerial vehicle (UAV) observations, enabling the construction of a complete landslide database and distribution map. Three failure modes of landslides in the Zigui basin are used to illustrate the major factors that govern reservoir-induced landslides. The results show that (1) > 99% of identified landslides occur on slopes angle <47°, while >80% occur at elevations below 600 m; (2) Jurassic Niejiashan Formation is highly prone to landslides; (3) Low reservoir levels of 145 m to 155 m greatly reduce slope stability. Based on the information entropy method that use the conditional probability of different influencing factors and principal component analysis as inputs, the relative contributions of various influencing factors are quantified and a landslide susceptibility map was drawn. This susceptibility map helps define the countermeasures that will best reduce fatalities and property losses for areas having different landslide conditions and susceptibilities. • Database of 462 reservoir-induced landslides in Zigui basin, TGR was created. • Identifying failure modes and quantifying contributions of influential factors. • Conditional probability and information entropy model yields landslide susceptibility. • Susceptibility map, failure modes, and strategies suppressing the slope instability. [ABSTRACT FROM AUTHOR]