To better understand the dynamic process of rock avalanches blocking rivers, a novel numerical approach based on the coupled Eulerian-finite-discrete element method (CEFDEM) is proposed. The ...Samaoding paleolandslide blocking river event, which occurred at the upstream of the Jinsha River was used as a case study to further validate the new numerical approach. Field investigations, thermoluminescence dating, and geomorphological analysis were conducted to determine basic geological conditions and provide data for the numerical simulations. Then a calibrated 3D landslide blocking river simulation based on the CEFDEM was conducted. The landslide blocking river lasted for 70 s and landslide scale from the numerical simulation agrees well with the field investigation. The maximum overall feature speed of the entire sliding mass is 35 m/s, while part of the sliding mass can reach 69 m/s. Dynamic fragmentation of the rock slide is stratified such that the bottom of the sliding body has higher fragmentation degree than the top. The variation of kinetic energy, accumulated friction dissipation, and fracture energy of the sliding mass are also shown. The impulsive water wave is triggered immediately after sliding mass runs into river, and its maximum height is 132 m, while part of the wave can reach a speed of 64 m/s. The river water will be pushed by the subsequent sliding mass movement. A comparison of the CEFDEM model and particle flow code (PFC) model in landslide blocking river was conducted, and the advantages and limitations of CEFDEM model were discussed in detail.
•A novel numerical approach of CEFDEM is proposed.•Continuity of rock and its fragmentation characteristics are considered and reflected well.•Dynamic process of a high-level rock slide blocking river in the deep valley is shown.
There are three main factors controlling the formation of debris flow; of these, the ability to evaluate the volume of source materials in a catchment is the most significant. Source materials come ...from channel bed sediment, nearby landslides and rilling and surface erosion of slopes. The objective of this study was to develop a multi-source method–including field surveys, optical remote sensing interpretation, and interferometric synthetic aperture radar (InSAR) technology–to estimate the volume of source materials in the debris flow in the Xulong Gully (XLG), China. The qualitative degree of stability of the source materials was estimated with volume of approximately 91.9 × 104 m3. Considering sediment connectivity, landslides debris were interpreted using optical remote sensing, and their volume was calculated, using an empirical formula, to be about 191.01 × 104 m3. Continuous monitoring using InSAR could help to obtain the large-scope precise process of ground surface deformation. Estimated erosion rate ranges from 1633 m3/(km2·year) to 4552 m3/(km2·year) and annual volume of erosion was 9.08 × 104 m3/year–25.31 × 104 m3/year. Higher elevation with good vegetation coverage showed the sedimentation process, while lower elevation area with little vegetation showed erosion process. The highest degree of erosion occurred in the summer, followed by spring, autumn, and winter. The trend of the degree of erosion was consistent with that of the monthly rainfall in the XLG in 2018. Verification results demonstrated that the proposed approach could improve the efficiency and accuracy of the estimates of source material volume in debris flows and assess hazards.
•A quantitative approach estimating debris flow source material is established.•Proposing an improved volume statistical formula considering connectivity.•InSAR is introduced to estimate annual changing volume of erosion.•Analyzing slope erosion and sedimentation process in dry-hot valley area
A large number of landslides have occurred in the upstream reaches of the Jinsha River, Tibetan Plateau due to the intensity of tectonic movement in the area. Remote sensing and field investigation ...indicate that one of them, the Samaoding paleolandslide, previously blocked the river. Various river-blocking phenomena are well preserved, including the old landslide dam and deposits, fluvial sediments, and hydrostatic sandy sediment. To better understand the evolution of the Samaoding landslide, the authors carried out thermoluminescence (TL) dating and numerical simulations. The TL analysis shows that the landslide occurred at 10.6 ± 0.5 Ka BP. Discrete element method (DEM) simulation of the landslide based on landform restoration provided results that are consistent with field observations. The simulation indicates that the entire landslide process lasted for 80 s, and the sliding mass reached a maximum velocity of 64 m/s. The landslide formed a landslide dam with a length of 1900 m, a width of 600 m, and a depth of 200 m. The simulation results show that the level of the riverbed at that the time of the landslide was at least 25 m higher than it is today. On the combined basis of the simulation results and field observations, the authors propose explanation that the following valley evolution sequence occurred after river blocking. The landslide dam experienced flood overtopping and then was eroded until it had mostly had been transported away by river flow, and the river then rapidly incised the bedrock to form the present-day landform. Based on the field investigations, the authors summarize the failure mechanism of steep-inclined antidip rockslides and found that tectonics play an important role in the formation of landslide dams (or trigger of landslides) and the failure of landslide dams in an active tectonic environment of Tibetan Plateau.
•The Samaoding paleolandslide occurred at 10.6 ± 0.5 Ka BP according to TL analysis.•Detailed run out process of the Samaoding paleolandslide was well reproduced by DEM simulation.•The relative incision rate of the study area is at least 250 cm/ka in the past 10,000 years.•The evolution of the Samaoding paleolandslide is proposed.•Failure mechanism of steep-inclined antidip rockslides is summarized.
Catastrophic landslides occur frequently at large waste dumps, causing huge losses of lives and environmental degradation. In this study, Zhujiabaobao iron mine waste dump was surveyed and found to ...be unstable during a field investigation in April 2016. A failure potential assessment was undertaken for the waste dump; this is crucial for the prediction and mitigation of landslides hazards. Reconnaissance, geomorphological analysis, and laboratory experiments were carried out to provide basic data, and a three-dimensional waste dump model was constructed. To consider ground cracks in the waste dump and acquire information about potential sliding mass, an extended finite element model (XFEM) based on strength reduction technique was applied. An analysis shows that the factor of safety (FOS) of waste dump is 1.22, not very stable according to “The technical code for building slope engineering (GB50330-2013)” published by Chinese ministry of Housing and Urban-Rural Development, and the potential failure volume is 45 × 104 m3. Then, the potential landslide and debris flow due to slope failure were simulated using the software SFLOW based on a free-surface shallow water model (SWM). The landslide simulation considers different water contents of sliding mass, reflected in parameter Cv (sediment concentration by volume), whereas debris flow simulation was designed for 20, 50, 100, and 200-year return periods. The results show that with the decrease in Cv, the speed of sliding mass increases, and the run-out distance of landslide increases. However, even the farthest influence distance does not reach downstream buildings. The debris flow can pile up in front of gully mouth and even run into the Jinsha River. Therefore, once a landslide has occurred or when a lot of loose material is present, corresponding management measures (such as cleaning the material or setting the retaining wall) and a forewarning system should be developed to prevent huge damage caused by debris flow.
•A method combining FEM and SWM for assessing waste dump failure potential.•The cracks have been considered in the model of stability analysis via XFEM.•The numerical model can fully consider real topographical conditions.
The objective of this study was to identify the areas that are most susceptible to landslide occurrence, and to find the key factors associated with landslides along Jinsha River and its tributaries ...close to Derong and Deqin County. Thirteen influencing factors, including (a) lithology, (b) slope angle, (c) slope aspect, (d) TWI, (e) curvature, (f) SPI, (g) STI, (h) topographic relief, (i) rainfall, (j) vegetation, (k) NDVI, (l) distance-to-river, (m) and distance-to-fault, were selected as the landslide conditioning factors in landslide susceptibility mapping. These factors were mainly obtained from the field survey, digital elevation model (DEM), and Landsat 4–5 imagery using ArcGIS software. A total of 40 landslides were identified in the study area from field survey and aerial photos’ interpretation. First, the frequency ratio (FR) method was used to clarify the relationship between the landslide occurrence and the influencing factors. Then, the principal component analysis (PCA) was used to eliminate multiple collinearities between the 13 influencing factors and to reduce the dimension of the influencing factors. Subsequently, the factors that were reselected using the PCA were introduced into the logistic regression analysis to produce the landslide susceptibility map. Finally, the receiver operating characteristic (ROC) curve was used to evaluate the accuracy of the logistic regression analysis model. The landslide susceptibility map was divided into the following five classes: very low, low, moderate, high, and very high. The results showed that the ratios of the areas of the five susceptibility classes were 23.14%, 22.49%, 18.00%, 19.08%, and 17.28%, respectively. And the prediction accuracy of the model was 83.4%. The results were also compared with the FR method (79.9%) and the AHP method (76.9%), which meant that the susceptibility model was reasonable. Finally, the key factors of the landslide occurrence were determined based on the above results. Consequently, this study could serve as an effective guide for further land use planning and for the implementation of development.
Tertiary soft-rock strata exposed on the eastern side of Changbai Mountain are landslide-prone strata. In recent years, shallow landslides have frequently occurred along the highway in this region, ...leading to great challenges in highway construction and safe operations. National Highway 302, which is under construction, crosses an old landslide group close to the village of Xinyan. A shallow landslide that recently occurred in this section, the Xinyan landslide, which occurred in a road embankment composed of soft-rock materials, is studied herein as a case study. The field survey identifies the geological characteristics and current conditions of the landslide area and confirms an inheritance relationship between the Xinyan landslide and previous landslides. Through a laboratory geotechnical test, mineral composition analysis and microstructure analysis of landslide soils, it is found that the examined soft-rock materials exhibit both dispersion and expansion. The coupling effect of soil expansion and dispersion contribute to the formation of seepage channels and to the degradation of soil properties. Under the combined effects of these factors, local shear failure first occurs at the weakest toe of the embankment. Then, unloading effects and strain softening lead to the progressive propagation and expansion of the sliding surface. Finally, the failure of the Xinyan landslide enters a progressive failure mode from the slope toe to the interior area. Therefore, this study reveals that expansibility, dispersivity, extremely low shear strength levels, softening behavior and preferential flows are the main causes of the repeated failure of the gentle soft-rock slopes in this region. These results may serve as a good reference for the prevention and treatment of similar soft-rock landslides occurring in the Yanbian region or worldwide.
•A progressive slope failure in a road embankment composed of soft-rock materials is presented.•The soft-rock materials have the characteristics of expansibility and dispersivity.•The Xinyan landslide is an inheritance and development of the previous old landslides.•Unloading effect and strain softening leads to the progressive propagation of sliding surfaces.•Some suggestions on the prevention and treatment of similar soft-rock landslides are given.
The engineering-geological characteristics of fractured rock masses depend on the discontinuity properties, which can be analyzed by the stereonet-based system. However, this system faces challenges ...in describing orientations, which are spherical data, and it cannot incorporate other scalar parameters (e.g., trace length, aperture, etc.) that affect engineering practice. Therefore, a novel system based on manifold learning is proposed to analyze the distribution patterns of orientation data and characterize multiple discontinuity properties. The proposed system uses manifold learning to explore and visualize the manifold structure of orientation data by a two-dimensional kernel density estimation (2D-KDE) technique. It also integrates other parameters into the manifold structure to capture multiple properties. To quantify the manifold structure and reveal the real fractal behaviors of orientation data, a detailed analysis process including monofractal and multifractal models is proposed. The effectiveness of the proposed system is verified by comparison with the stereonet-based system in several aspects. The equivalent manifold structure is also proposed to enhance the engineering applicability of the system, and one of its applications is demonstrated. Finally, the proposed system is applied to a significant road project and further developed by unmanned aerial vehicle (UAV) photogrammetry. The proposed system provides new insights for research on fractured rock masses and has great potential for solving multi-parameter problems in engineering geology.
•Manifold learning is introduced to engineering geology.•Characterization of multiple properties of rock discontinuities by manifold learning.•A new system for multivariate analysis of discontinuities is proposed.•Multifractal models are improved and incorporated into the new system.
The Qinghai–Tibet Plateau is an area with frequent landslide hazards due to its unique geology, topography, and climate conditions, posing severe threats to engineering construction and human ...settlements. The primary purpose of this paper is to map the landslide susceptibility of the Ya’an–Lin branch of the Sichuan–Tibet Railway using two deep learning (DL) algorithms, convolutional neural network (CNN) and deep neural network (DNN). Initially, a geospatial database was generated based on 587 landslide hazards determined by Interferometric Synthetic Aperture Radar (InSAR) Stacking technology and field geological hazard surveys; thus, 18 landslide-influencing factors were selected. Subsequently, the landslides were randomly divided into training (70%) and validation data (30%) for model training and testing. Next, a Pearson correlation coefficient and information gain (IG) method were used to perform the correlation analysis and feature selection of the 18 influencing factors. Afterward, landslide susceptibility maps were generated for the two models. Finally, the performance of the model is validated using the receiver-operating characteristic (ROC) curve and confusion matrix. The results show that the CNN model (AUC = 0.88) provided better performance in both the training and testing phases compared to the DNN model (AUC = 0.84). In addition, the high landslide susceptibility is primarily distributed in the Jinsha, Lancang and Nu River basins along the railway. The slope, altitude and rainfall are the main factors for the formation of the landslides. Furthermore, the two deep learning models can accurately map the landslide susceptibility, providing important information for landslide risk reduction and prevention.
The Sichuan-Tibet railway, which spans many alpine canyon regions, is being built in southwestern China. Investigating the characteristics of rock discontinuity sets is the basis for identifying ...dangerous rock masses above the tunnel portals. The traditional methods of identifying discontinuity sets usually consider orientations and ignore other parameters, which results in incorrect guidance for rock engineering. To this end, the affinity propagation (AP) algorithm based on modified isometric mapping (Isomap) is proposed for partitioning discontinuity sets based on orientation, trace length, and aperture. The new unsupervised algorithm (ISOAP) uses manifold learning to complete the transformation process for orientations from spherical vectors to scalars and avoids selecting the initial clustering center to achieve global optimization. The Silhouette Index is used to intelligently scan the optimal clustering results. The proposed algorithm is tested on a complex artificial data set and on Shanley and Mahtab's data set. Since accurately obtaining discontinuity information is impossible by traditional means (i.e., using geological compasses and measurement tapes) due to the existence of a mass of high and steep slopes, the ISOAP algorithm is combined with semiautomatic technology based on unmanned aerial vehicle (UAV) photogrammetry and applied to a rock slope located along the railway. The introduction of manifold learning is beneficial for quickly applying abundant unmodified clustering algorithms to rock engineering and searching the optimal algorithm suitable for analyzing the structural characteristics of a specific fractured rock mass. The proposed method can simplify rock engineering analyses and provide more reasonable results.
•Manifold learning is applied to rock engineering.•Characterization of multiple properties of rock discontinuities.•A new unsupervised algorithm based on manifold learning.•Using a 3D model, multi-property discontinuity sets are identified by an unsupervised algorithm.
Frequent rockfall events pose a major threat to the safe operation of the Taihang Grand Canyon Scenic Area (GCSA) in China. The traditional techniques for identifying potential rockfall sources and ...hazard assessment methods are often challenged in the alpine canyon landform. This study aims to establish an early identification framework for regional potential rockfall sources applicable to the canyon region and to assess rockfall hazards in potentially hazardous areas using unmanned aerial vehicle (UAV) photogrammetry. Specifically, by incorporating high-precision topographic information and geotechnical properties, the slope angle distribution method was used for static identification of potential rockfall sources. Moreover, SBAS-InSAR technology was used to describe the activity of potential rockfall sources. Finally, taking the key potentially hazardous area of the Sky City scenic spot as an example, the Rockfall Analyst tool was used to analyze the rockfall frequency, bounce height and energy characteristics based on the high-precision UAV 3D real scene model, and the analytic hierarchy process was introduced to achieve quantitative rockfall hazard assessment. The results show that the potential rockfall source areas in the Taihang GCSA is 33.47 km2 (21.47%), mainly distributed in strips on the cliffs on both sides of the canyon, of which the active rockfall source area is 2.96 km2 (8.84%). Taking the scenic spot of Sky City as example, the proposed UAV-based real scene modeling technology was proven to be able to quickly and accurately construct a 3D high-precision model of the canyon area. Moreover, the 3D rockfall simulation showed that the high-energy rockfall area was mainly distributed at the foot of the steep cliff, which mainly threatens the tourist distribution center below. The early identification and quantitative evaluation scheme of rockfall events proposed in this study can provide technical reference for the prevention and control of rockfall hazards in similar alpine valley areas.
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