Optimal mining sequence for coal faces under a bedding slope:insight from landslide prevention

Repetitive mining beneath bedding slopes is identified as a critical factor in geomorphic disturbances, especially landslides and surface subsidence. Prior research has largely concentrated on surface deformation in plains due to multi-seam coal mining and the instability of natural bedding slopes, yet the cumulative impact of different mining sequences on bedding slopes has been less explored. This study combines drone surveys and geological data to construct a comprehensive three-dimensional model of bedding slopes. Utilizing FLAC3D and PFC2D models, derived from laboratory experiments, it simulates stress, deformation, and failure dynamics of slopes under various mining sequences. Incorporating fractal dimension analysis, the research evaluates the stability of slopes in relation to different mining sequences. The findings reveal that mining in an upslope direction minimizes disruption to overlying strata. Initiating extraction from lower segments increases tensile-shear stress in coal pillar overburdens, resulting in greater creep deformation towards the downslope than when starting from upper segments, potentially leading to localized landslides and widespread creep deformation in mined-out areas. The downslope upward mining sequence exhibits the least fractal dimensions, indicating minimal disturbance to both strata and surface. While all five mining scenarios maintain good slope stability under normal conditions, recalibrated stability assessments based on fractal dimensions suggest that downslope upward mining offers the highest stability under rainfall, contrasting with the lower stability and potential instability risks of upslope downward mining. These insights are pivotal for mining operations and geological hazard mitigation in multi-seam coal exploitation on bedding slopes.

Uncertainties of landslide susceptibility prediction:influences of different study area scales and mapping unit scales

This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.

Exploring mechanism of hidden,steep obliquely inclined bedding landslides using a 3DEC model:A case study of the Shanyang landslide in Shaanxi Province,China

Catastrophic geological disasters frequently occur on slopes with obliquely inclined bedding structures(also referred to as obliquely inclined bedding slopes),where the apparent dip sliding is not readily visible.This phenomenon has become a focal point in landslide research.Yet,there is a lack of studies on the failure modes and mechanisms of hidden,steep obliquely inclined bedding slopes.This study investigated the Shanyang landslide in Shaanxi Province,China.Using field investigations,laboratory tests of geotechnical parameters,and the 3DEC software,this study developed a numerical model of the landslide to analyze the failure process of such slopes.The findings indicate that the Shanyang landslide primarily crept along a weak interlayer under the action of gravity.The landslide,initially following a dip angle with the support of a stable inclined rock mass,shifted direction under the influence of argillization in the weak interlayer,moving towards the apparent dip angle.The slide resistance effect of the karstic dissolution zone was increasingly significant during this process,with lateral friction being the primary resistance force.A reduction in the lateral friction due to karstic dissolution made the apparent dip sliding characteristics of the Shanyang landslide more pronounced.Notably,deformations such as bending and uplift at the slope’s foot suggest that the main slide resistance shifts from lateral friction within the karstic dissolution zone to the slope foot’s resistance force,leading to the eventual buckling failure of the landslide.This study unveils a novel failure mode of apparent dip creep-buckling in the Shanyang landslide,highlighting the critical role of lateral friction from the karstic dissolution zone in its failure mechanism.These insights offer a valuable reference for mitigating risks and preventing disasters related to obliquely inclined bedding landslides.

Landslide susceptibility prediction using slope unit-based machine learning models considering the heterogeneity of conditioning factors

To perform landslide susceptibility prediction(LSP),it is important to select appropriate mapping unit and landslide-related conditioning factors.The efficient and automatic multi-scale segmentation(MSS)method proposed by the authors promotes the application of slope units.However,LSP modeling based on these slope units has not been performed.Moreover,the heterogeneity of conditioning factors in slope units is neglected,leading to incomplete input variables of LSP modeling.In this study,the slope units extracted by the MSS method are used to construct LSP modeling,and the heterogeneity of conditioning factors is represented by the internal variations of conditioning factors within slope unit using the descriptive statistics features of mean,standard deviation and range.Thus,slope units-based machine learning models considering internal variations of conditioning factors(variant slope-machine learning)are proposed.The Chongyi County is selected as the case study and is divided into 53,055 slope units.Fifteen original slope unit-based conditioning factors are expanded to 38 slope unit-based conditioning factors through considering their internal variations.Random forest(RF)and multi-layer perceptron(MLP)machine learning models are used to construct variant Slope-RF and Slope-MLP models.Meanwhile,the Slope-RF and Slope-MLP models without considering the internal variations of conditioning factors,and conventional grid units-based machine learning(Grid-RF and MLP)models are built for comparisons through the LSP performance assessments.Results show that the variant Slopemachine learning models have higher LSP performances than Slope-machine learning models;LSP results of variant Slope-machine learning models have stronger directivity and practical application than Grid-machine learning models.It is concluded that slope units extracted by MSS method can be appropriate for LSP modeling,and the heterogeneity of conditioning factors within slope units can more comprehensively reflect the relationships between conditioning factors and landslides.The research results have important reference significance for land use and landslide prevention.

Extensive identification of landslide boundaries using remote sensing images and deep learning method

The frequent occurrence of extreme weather events has rendered numerous landslides to a global natural disaster issue.It is crucial to rapidly and accurately determine the boundaries of landslides for geohazards evaluation and emergency response.Therefore,the Skip Connection DeepLab neural network(SCDnn),a deep learning model based on 770 optical remote sensing images of landslide,is proposed to improve the accuracy of landslide boundary detection.The SCDnn model is optimized for the over-segmentation issue which occurs in conventional deep learning models when there is a significant degree of similarity between topographical geomorphic features.SCDnn exhibits notable improvements in landslide feature extraction and semantic segmentation by combining an enhanced Atrous Spatial Pyramid Convolutional Block(ASPC)with a coding structure that reduces model complexity.The experimental results demonstrate that SCDnn can identify landslide boundaries in 119 images with MIoU values between 0.8and 0.9;while 52 images with MIoU values exceeding 0.9,which exceeds the identification accuracy of existing techniques.This work can offer a novel technique for the automatic extensive identification of landslide boundaries in remote sensing images in addition to establishing the groundwork for future inve stigations and applications in related domains.

Evaluation of the treatment effect of rear slope cutting on hydrodynamic pressure landslides:A case study

After the impoundment of the Three Gorges Reservoir,some huge ancient landslides were reactivated and deformed,showing typical hydrodynamic pressure landslide characteristics.The Baishuihe landslide was a typical hydrodynamic pressure landslide.The management department conducted slope cutting treatments from 2018 to 2019.To evaluate the treatment effect of rear slope cutting,this study analyzed the data of the surface deformation survey and field monitoring over the past 20 years and the characteristics of the reservoir water-triggered Baishuihe landslide deformation,and calculated the seepage field,displacement field,and stability coefficient before and after landslide treatment.The results showed that the deformation of the Baishuihe landslide was primarily related to a decrease in the reservoir water level.Owing to the poor permeability of the landslide soil,the decrease in the reservoir water level produced a seepage force pointing to the outside of the landslide body,leading to the step deformation of the landslide displacement.The landslide was treated by rear slope cutting,and the“step”deformation of the landslide disappeared after treatment.The hydrodynamic pressure caused by the change in reservoir water after cutting the slope did not disappear.However,as the slope cutting greatly reduced the overall sliding force of the landslide,its stability was greatly improved.Notably,high stability can still be ensured under extreme rainfall after treatment.Slope cutting is effective for treating hydrodynamic pressure landslides.This study can provide effective technical support for the treatment of reservoir landslides.

Early warning system for shallow landslides using rainfall threshold and slope stability analysis

A combined cluster and regression analysis were performed for the first time to identify rainfall threshold that triggers landslide events in Amboori, Kerala, India. Amboori is a tropical area that is highly vulnerable to landslides. The 2, 3, and 5-day antecedent rainfall data versus daily rainfall was clustered to identify a cluster of critical events that could potentially trigger landslides. Further, the cluster of critical events was utilized for regression analysis to develop the threshold equations. The 5-day antecedent(xvariable) vs. daily rainfall(y-variable) provided the best fit to the data with a threshold equation of y = 80.7-0.1981 x. The intercept of the equation indicates that if the 5-day antecedent rainfall is zero, the minimum daily rainfall needed to trigger the landslide in the Amboori region would be 80.7 mm. The negative coefficient of the antecedent rainfall indicates that when the cumulative antecedent rainfall increases, the amount of daily rainfall required to trigger monsoon landslide decreases. The coefficient value indicates that the contribution of the 5-day antecedent rainfall is～20% to the landslide trigger threshold. The slope stability analysis carried out for the area, using Probabilistic Infinite Slope Analysis Model(PISA-m), was utilized to identify the areas vulnerable to landslide in the region. The locations in the area where past landslides have occurred demonstrate lower Factors of Safety(FS) in the slope stability analysis. Thus, rainfall threshold analysis together with the FS values from slope stability can be suitable for developing a simple, cost-effective, and comprehensive early-warning system for shallow landslides in Amboori and similar regions.

Human-induced landslide on a high cut slope: a case of repeated failures due to multi-excavation

The paper attempts to represent a case of repeated failures on a high cut slope due to multi-excavation. The characteristics of each failure induced by excavation are analyzed through geological investigation, and then a geological model at different failure stages is proposed. The geological analysis shows that the excavation-induced repeated failures are related to the exposure of the weak bedding plane and the toe unloading of the cut slope, Numerical modeling is conducted based on a sequential method, taking into account the main failure stages of cut slope. The simulation results fairly coincide with the practical phenomena observed in field. It is shown that the decrease in normal stress of displaced mass on cut slope will induce the increase in shear stress in bedding planes and that at the toe of the cut slope. The released stress leads to repeated gravitational instabilities of cut slope due to the decrease in normal stress and the increase in shear stress along the bedding planes of mudstone.

A case study of a giant reactivated landslide based on NPR anchor cable Newton force early warning

In a large ancient landslide,approximately 240,000 m3 of sediments were reactivated,posing a grave threat to the safety of iron ore stopes.To trace the deformation and evolution history of reactivated Landslide,we conducted geological surveys and combined real-time monitoring equipment to analyze the landslide data since 1986 and the deformation status of the reactivated Landslide.A multi-factor comprehensive landslide monitoring method and an Newton force early warning system(NFEWS)were established,focusing on underground stress,surface deformation information and landslide stability.Furthermore,we developed a four-level early warning grading standard,employing surface cracks and changes in underground stress thresholds as early warning indicators.This standard adds expert assessment to avoid false alarms and realize real-time dynamics of mining landslides during excavation and transportation.Through the case study and analysis of Nanfen open-pit mine,the NFEWS system offers valuable insights and solution for early warning of landslides in analogous open-pit mines.Finally,the evaluation index system of landslide hazard susceptibility was established by selecting the Newton force influence factor.A landslide susceptibility zoning map is constructed using the information value model.The rationality and accuracy are assessed from three perspectives:frequency ratio,landslide hazard point density,and receiver operating characteristic(ROC)curve.The improved Newton force landslide early warning system provides a good reference for the analysis and monitoring of the creep landslide evolution process.

Stability assessment of landslide-prone road cut rock slopes in Himalayan terrain:A finite element method based approach

Large-scale slope destabilization could be aggravated due to swift urbanization and ever-rising demands of geoengineering projects such as dams,tunnels,bridges and widening roads.National Highway-58 connects Delhi to Badrinath in India,which passes through complex geomorphological and geological terrain and often encounters cut slopes susceptible to slope failures.In the present investigation,a detailed geotechnical appraisal is conducted along the road cut slopes from Rishikesh to Devprayag in the Himalayas.Twenty vulnerable road cut slopes were demarcated for detailed slope stability analysis using Phase2D finite element modeling simulator.Nonlinear generalized Hoek-Brown(GHB)criterion was adopted for stability analyses.Out of 20 slopes,five slopes(S6,S7,S18,S19 and S20)are unstable with factor of safety(FoS)less than or equal to 1,and thus needs immediate attention.The FoS values of four slopes(S2,S9,S13 and S17)lie between 1 and 1.3,i.e.marginally stable,and slopes S1,S3,S4,S5,S8,S10,Sll,S12,S14,S15 and S16 are stable.Mohr-Coulomb(MC)criterion was also adopted to compare the slope stability analysis with GHB criterion.The FoS calculated from GHB criterion is close to that using MC criterion for lower values of FoS whereas for higher values,the difference is marked.For the jointed rock in the Himalayan region,the nonlinear GHB criterion gives better results as compared to MC criterion and matches with the prevailing field conditions.Accordingly,some suggestions are proposed to strengthen the stability of cut slopes.

Prediction of the instability probability for rainfall induced landslides:the effect of morphological differences in geomorphology within mapping units

Slope units is an effective mapping unit for rainfall landslides prediction at regional scale.At present,slope units extracted by hydrology and morphological method report very different morphological feature and boundaries.In order to investigate the effect of morphological difference on the prediction performance,this paper presents a general landslide probability analysis model for slope units.Monte Carlo method was used to describe the spatial uncertainties of soil mechanical parameters within slope units,and random search technique was performed to obtain the minimum safety factor;transient hydrological processes simulation was used to provide key hydrological parameters required by the model,thereby achieving landslide prediction driven by quantitative precipitation estimation and forecasting data.The prediction performance of conventional slope units(CSUs)and homogeneous slope units(HSUs)were analyzed in three case studies from Fengjie County,China.The results indicate that the mean missing alarm rate of CSUs and HSUs are 31.4% and 10.6%,respectively.Receiver Operating Characteristics(ROC)analysis also reveals that HSUs is capable of improving the overall prediction performance,and may be used further for rainfall-induced landslide prediction at regional scale.

Submarine Landslide Identified in DLW3102 Core of the Northern Continental Slope, South China Sea

In this paper, we take DLW3101 core obtained at the top of the canyon(no landslide area) and DLW3102 core obtained at the bottom of the canyon(landslide area) on the northern continental slope of the South China Sea as research objects. The chronostratigraphic framework of the DLW3101 core and elemental strata of the DLW3101 core and the DLW3102 core since MIS5 are established by analyzing oxygen isotope, calcium carbonate content, and X-Ray Fluorescence(XRF) scanning elements. On the basis of the information obtained by analyzing the sedimentary structure and chemical elements in the landslide deposition, we found that the DLW3102 core shows four layers of submarine landslides, and each landslide layer is characterized by high Si, K, Ti, and Fe contents, thereby indicating terrigenous clastic sources. L1(2.15–2.44 m) occurred in MIS2, which is a slump sedimentary layer with a small sliding distance and scale. L2(15.48–16.00 m) occurred in MIS5 and is a debris flow-deposited layer with a scale and sliding distance that are greater than those of L1. L3(19.00–20.90 m) occurred in MIS5; its upper part(19.00–20.00 m) is a debris flow-deposited layer, and its lower part(20.00–20.90 m) is a sliding deposition layer. The landslide scale of L3 is large. L4(22.93–24.27 m) occurred in MIS5; its upper part(22.93–23.50 m) is a turbid sedimentary layer, and its lower part(23.50–24.27m) is a slump sedimentary layer. The landslide scale of L4 is large.

Mechanism of colluvial landslide induction by rainfall and slope construction:A case study

The landslide hazards occurring in the complex geological genesis accumulation body are usually controlled by the coupling action of many internal and external factors.Therefore,this paper takes the dam-front Danbo accumulation body landslide of Yangfanggou hydropower station on the Yalong River as the geological prototype,and discusses the process and mechanism of slope stability degradation under the combined action of rainfall and slope construction.Based on the detailed understanding of the basic characteristics of the accumulation body,the development characteristics of the landslide and the construction situation of the slope engineering,the study conducted correlation analysis between rainfall and landslide displacement,the physical and mechanical tests of all types of rocksoil masses,and the numerical simulation testing of seepage field variation of the landslide section.It is found that the special slope structure and material composition of the old landslide accumulation layer on the upper part of the Danbo accumulation body are the internal factors for the occurrence of thrust loadinduced landslide,and the construction of the slope engineering not only creates free space conditions for sliding,but also provides channels for the infiltration of rainfall into the slope after confluence,which is an external factor that caused the mechanical properties of the sliding zone soil to gradually weaken from the trailing edge to the leading edge.The geomechanical model of such landslide is that the active section of the trailing edge produces the"source of force",the transition section of the middle section affects the occurrence of sliding,and the anti-sliding section of the leading edge controls the occurrence of landslide hazards.The results of this research provide not only a useful supplement to the theory of landslide formation mechanisms but also a scientific basis for guiding the prevention and control of similar hazards.

Slope stability analysis of Balia Nala landslide, Kumaun Lesser Himalaya, Nainital, Uttarakhand, India

Balia Nala is the outlet of the Nainital lake, flowing towards southeast direction. Presence of Nainital habitation at its right bank has high socio-economic importance. This study presents the stability analysis of a ravine/valley along Balia Nala. Variegated slates(lower Krol and upper Blaini formations) are the main rock types, wherever the outcrop does exist and rest of the area is covered by slope wash and river borne materials. Three sets of joints are presented in the area, but 4 sets of joints also exist at some locations. Nainital lake fault intersected by Manora fault from southwest direction passes through eastern side of the study area, and some small faults, which are sub-branches of Nainital lake fault, are observed(with 10 m offset) and promote the landslide in the area. This study shows that different kinds of discontinuities(joints, faults and shear zones) and rapid down cutting by the stream due to neotectonic activity affect the stability of the slope. The fragile lithology and deep V-shaped valley further accelerate the mass movement in the study area. In addition, rock mass rating(RMR), factor of safety(FOS) and graphical analysis of the joints indicate the study area as landslide-prone zone. This study will be helpful in not only reducing the risk on life of people, but also in assisting the ongoing civil work in the study area.

Geotechnical and GIS-based environmental factors and vulnerability studies of the Okemesi landslide,Nigeria

Landslide is a geological hazard typically associated with extreme events such as earthquakes,heavy rainfall,volcanic eruptions,changes in groundwater level,etc.This study was carried out in Okemesi-Ekiti(also known as Okemesi),Southwest Nigeria,with the purpose of using remote sensing and GIS technologies to analyze the environmental factors(grain size,direct shear strength resistance,rainfall data,wet density,surface,and slope)resulting in the occurrence of the Okemesi landslide.The study also aimed to conduct a vulnerability analysis in the study area to identify regions with a probability of landslide occurrence.The grain size analysis of the soil in the Okemesi landslide area showed that slope materials comprised 17.14%gravel,59.31%sand,and 19.48%fines,thus the soil type could be classified as poorly graded gravely sand with a high possibility of landslide occurrence.The geomorphic characteristics of the study area was characterized by slopes ranging from 0.00°to 49.00°,while most slopes in the area were less than 8.00°.The slope aspect direction was mainly in south(157.51°–202.50°),southwest(202.51°–247.50°),west(247.51°–292.50°),and north(0.00°–22.50°and 337.51°–360.00°).The highlands were primarily bounded by the slope directions of north(0.00°–22.50°and 337.51°–360.00°),northeast(22.51°–67.50°),east(67.51°–112.51°),and southeast(112.51°–157.50°),which indicated the potential direction of mass movement.The study area can be divided into three vulnerability zones:high,medium,and low,with the area percentages of 9.00%,61.80%,and 29.20%,respectively.The analysis suggested that the Okemesi landslide was likely triggered by rainfall,which might have weakened the physical structure of slope materials.Understanding the causes and impacts of landslides is crucial for policymakers to implement measures to mitigate landslide hazards,protect infrastructure,and prevent the loss of life in the landslide-prone regions.

Early landslide mapping with slope units division and multi-scale objectbased image analysis——A case study in the Xianshui River basin of Sichuan,China

Previous studies on optical remote sensing mapping of landslides mainly focused on new landslides that have occurred, but little attention was paid to the early landslide due to its high concealment. In SAR technology, a prevalent method to detect early landslides, only can be used to identify the potential hazards of slow deformation. Therefore, it is necessary to explore new method of early landslides mapping by integrating all types of direct and indirect early features, such as cracks on slopes, small collapses inside and topographic features. In this study, an object-oriented image analysis method based on slope unit division and multi-scale segmentation was proposed to obtain accurate location and boundary extraction of early landslides. In the middle-and small-scale segmentation, the object, texture, spectrum, geometric features,topographic features, and other features were obtained to determine the local feature location of early landslides. The slope unit boundary was combined with the feature of a large-scale segmentation object to determine the scope of landslides. This method was tested in the Xianshui River basin in the Daofu County, Sichuan Province, China. The results demonstrate that:(1) Such features as landslide cracks and the small collapse at the bottom of slope can effectively determine the landslide position.(2) The slope unit division and the correct setting of shape factors in multiple segmentation can effectively determine the landslide boundary.(3) The accuracy of landslide location extraction was 83.33%, and the accuracy of boundary extraction for early landslides that were completely identified was evaluated as 82.67%. It is indicated that this method can improve the accuracy of boundary extraction and meet the requirements of the early landslides mapping.

GIS COMPONENT BASED 3D LANDSLIDE HAZARD ASSESSMENT SYSTEM: 3DSLOPEGIS

In this paper, based on a new Geographic Information System (GIS) grid-based three-dimensional (3D) deterministic model and taken the slope unit as the study object, the landslide hazard is mapped by the index of the 3D safety factor. Compared with the one-dimensional (1D) model of infinite slope, which is now widely used for deterministic model based landslide hazard assessment in GIS, the GIS grid-based 3D model is more acceptable and is more adaptable for three-dimensional landslide. Assuming the initial slip as the lower part of an ellipsoid, the 3D critical slip surface in the 3D slope stability analysis is obtained by means of a minimization of the 3D safety factor using the Monte Carlo random simulation. Using a hydraulic model tool for the watershed analysis in GIS, an automatic process has been developed for identifying the slope unit from digital elevation model (DEM) data. Compared with the grid-based landslide hazard mapping method, the slope unit possesses clear topographical meaning, so its results are more credible. All the calculations are implemented by a computational program, 3DSlopeGIS, in which a GIS component is used for fulfilling the GIS spatial analysis function, and all the data for the 3D slope safety factor calculation are in the form of GIS data (the vector and the grid layers). Because of all these merits of the GIS-based 3D landslide hazard mapping method, the complex algorithms and iteration procedures of the 3D problem can also be perfectly implemented.

Short-term displacement prediction for newly established monitoring slopes based on transfer learning

This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.

Landslides and Slope Fissures Triggered by the April 14,2010 Yushu Earthquake, China

On April 14, 2010 at 07:49 (Beijing time), a catastrophic earthquake with MS7.1 occurred at the central Qinghai-Tibetan Plateau. The epicenter was located at Yushu county, Qinghai Province, China. A total of 2036 landslides were determined from visual interpretation of aerial photographs and high resolution remote sensing images, and verified by selected field investigations. These landslides covered a total area of about 1.194km2. Characteristics and failure mechanisms of these landslides are listed in this paper, including the fact that the spatial distribution of these landslides is controlled by co-seismic main surface fault ruptures. Most of the landslides were small scale, causing rather less hazards, and often occurring close to each other. The landslides were of various types, including mainly disrupted landslides and rock falls in shallows and also deep-seated landslides, liquefaction induced landslides, and compound landslides. In addition to strong ground shaking, which is the direct landslide triggering factor, geological, topographical, and human activity also have impact on the occurrence of earthquake triggered landslides. In this paper, five types of failure mechanisms related to the landslides are presented, namely, the excavated toes of slopes accompanied by strong ground shaking; surface water infiltration accompanied by strong ground shaking; co-seismic fault slipping accompanied by strong ground shaking; only strong ground shaking; and delayed occurrence of landslides due to snow melt or rainfall infiltration at sites where slopes were weakened by co-seismic ground shaking. Besides the main co-seismic surface ruptures, slope fissures were also delineated from visual interpretation of aerial photographs in high resolution. A total of 4814 slope fissures, with a total length up to 77.1km, were finally mapped. These slope fissures are mainly distributed on the slopes located at the southeastern end of the main co-seismic surface rupture zone, an area subject to strong compression during the earthquake.

Slope Stability Analyses of Outang Landslide Based on the Peak and Residual Shear Strength Behavior

Most of the natural and compacted fine-grained soil slopes that are in saturated or unsaturated condition undergo a large deformation prior to reaching failure conditions.Such slopes should be designed taking account of their strain-softening behavior using the residual shear strength (RSS) parameters.In this paper,the slope stability of a recently reactivated Outang landslide near the Three Gorges Dam in China is analyzed based on the RSS parameters of unsaturated soils.In addition,comparisons are provided in the FOS values of slope using both the peak shear strength (PSS) and RSS parameters.Firstly,a series of site investigations of the hydrologic and geologic conditions,ground surface displacements and cracks were described.The PSS and RSS behaviors of the sliding soils derived from a series of direct shear test results performed on saturated and unsaturated soil specimens are summarized.Secondly,a series of slope stability analysis were conducted considering the precipitation and Yangtze River water level variation within a representative period of 7 months,based on the PSS and the RSS properties.In this study,three different scenarios were considered,which include: i) considering only the precipitation with a constant water level;ii) considering only the decrease in water level without rainfall;iii) considering the combination of precipitation and decrease in water level.In each scenario,four steps were included to calculate the values of factor of safety (FOS) at different times.1) A steady-state seepage analysis was conducted with a constant total head at 525 m on the left boundary and 175 m on the slope surface below the Yangtze River water level.The initial pore water pressures were simulated in the slope under no precipitation and variation of water level.2) A specific boundary condition was applied on the slope surface to model the precipitation and Yangtze River water level variation.A transient seepage analysis was conducted to calculate pore water pressures at different times based on the initial pore water pressures.3) The FOS values at different times were calculated by the Morgenstern-Price method taking account of the variation of pore water pressures at different times,using the peak shear strength (PSS) parameters.4) The last step was repeated replacing PSS parameters with RSS parameters.The RSS parameters were lower than the peak values from laboratory’s direct shear test results for the soils in the sliding zones.The reduction in shear strength from peak to residual state under unsaturated soil condition was greater than that for a saturated soil.The FOS decreased almost linearly with time for the scenario in which only the influence of rainfall infiltration was considered.However,the total reduction in the FOS was relatively small.The FOS decreased rapidly at a linear rate with respect to time with a decrease in water level for the scenario in which Yangtze River water level decrease was considered.The FOS reached to a relatively constant value after Yangtze River water level reached the lowest value.The decrease in Yangtze River water level was the dominant factor that contributed to a reduction in the FOS.The FOS was strongly dependent on the development of the phreatic line after the Yangtze River water level reached the lowest value.The FOS calculated by RSS (i.e.FOSR) is less than unity;they were approximately 16% lower in comparison to that calculated by PSS (FOSP).If PSS parameters were used,the slope would still be stable even under the combined influence of precipitation and Yangtze River water level decrease.These results are inconsistent with the field observations.For this reason,the RSS parameters should be taken into account to evaluate reliably the slope stability of the Outang landslide.