Study on stability and reinforcement of a landslide on Ji''''an-Dandong highway

This study clarified the failure mechanism of a landslide on Ji'an-Dandong highway,through the detailed analysis of its geological condition.Then based on the back analysis of the broken landslide,take limit equilibrium method to evaluate the stability of the potential landslide.The result shows that the landslide is lack of safety stock,so anchor rope is designed to reinforce the landslide.     

Rapid geometry analysis for earthquake-induced and rainfall-induced landslide dams in Taiwan

Stability analysis of the dam is important for disaster prevention and reduction. The dam＇s geometry plays an important role in understanding its stability. This study develops a rapid landslide dam geometry assessment method for both earthquake-induced and rainfall-induced landslide dams based on nine real cases collected in Chinese Taipei and 214 cases collected worldwide. For simplification purposes, a landslide dam is classified into triangular or trapezoidal. The rapid landslide dam geometry assessment method in this paper uses only satellite maps and the topographic maps to get landslide area, and then analyze the dam geometry. These maps are used to evaluate the area of the landslide and the slope of the river bed. Based on the evaluation information, the proposed method can calculate dam height, the length of the dam, and the angles of the dam in both upstream and downstream directions. These geometry parameters of a landslide dam provide important information for further dam stability analysis. The proposed methodology is applied to a real landslide dam case at Hsiaolin Village. The result shows that the proposed method can be used to assess the landslide dam geometry.     

Landslide stability for Shuitianba in the Three Gorges area

According to the data of preliminary survey, the authors established a landslide geological model,on the basis of analyses on the sensitivity of landslide, tried to simulate and calculate the landslide stability of Shuitianba with the method of transfer coefficient when it is under different strength parameters, and study the landslide mechanism. The results show that it is sensitive to the effects of shear strength parameters of sliding zone and groundwater level on landslide stability safety coefficient, which provides reliable basis for calculation of landslide stability.     

Hazard and population vulnerability analysis: a step towards landslide risk assessment

In this paper, an attempt to analyse landslide hazard and vulnerability in the municipality of Pahuatlán, Puebla, Mexico, is presented. In order to estimate landslide hazard, the susceptibility,magnitude(area-velocity ratio) and landslide frequency of the area of interest were produced based on information derived from a geomorphological landslide inventory; the latter was generated by using very high resolution satellite stereo pairs along with information derived from other sources(Google Earth,aerial photographs and historical information).Estimations of landslide susceptibility were determined by combining four statistical techniques:(i) logistic regression,(ii) quadratic discriminant analysis,(iii) linear discriminant analysis, and(iv)neuronal networks. A Digital Elevation Model(DEM)of 10 m spatial resolution was used to extract the slope angle, aspect, curvature, elevation and relief.These factors, in addition to land cover, lithology anddistance to faults, were used as explanatory variables for the susceptibility models. Additionally, a Poisson model was used to estimate landslide temporal frequency, at the same time as landslide magnitude was obtained by using the relationship between landslide area and the velocity of movements. Then,due to the complexity of evaluating it, vulnerability of population was analysed by applying the Spatial Approach to Vulnerability Assessment(SAVE) model which considered levels of exposure, sensitivity and lack of resilience. Results were expressed on maps on which different spatial patterns of levels of landslide hazard and vulnerability were found for the inhabited areas. It is noteworthy that the lack of optimal methodologies to estimate and quantify vulnerability is more notorious than that of hazard assessments.Consequently, levels of uncertainty linked to landslide risk assessment remain a challenge to be addressed.     

Numerical simulation of a high-speed landslide in Chenjiaba,Beichuan, China

High-speed landslide is a catastrophic geological disaster in the mountainous area of southwest China. To predict the movement process of landslide reactivation in Chenjiaba town, Beichuan county, Sichuan province, China, we simulated the movement process of two landslide failures in Chenjiaba via rapid mass movement simulation and unmanned aerial vehicle images(UAV), and obtained the movement characteristic parameters of the landslides. According to a back analysis, the most remarkable fitting rheological parameters were friction coefficient(μ=0.18) and turbulence(). The parameter of landslide pressure was applied as the zoning index of landslide hazard to obtain the influence zone and hazard zoning map of the Chenjiaba landslide. Results show that the Duba River was blocked quickly with a landslide accumulation at the maximum height of 44.14 mwhen the Chenjiaba deposits lost stability. The hazard zoning map indicated that the landslide hazard degree is positively correlated with the slope.This landslide assessment is a quantitative hazard assessment method based on a landslide movement process and is suitable for high-speed landslide. Such method can provide a scientific basis for urban construction and planning in the landslide hazard area to avoid hazards effectively.     

GIS based landslide susceptibility mapping of Tevankarai Ar sub-watershed, Kodaikkanal, India using binary logistic regression analysis

Landslide susceptibility mapping is the first step in regional hazard management as it helps to understand the spatial distribution of the probability of slope failure in an area.An attempt is made to map the landslide susceptibility in Tevankarai Ar subwatershed,Kodaikkanal,India using binary logistic regression analysis.Geographic Information System is used to prepare the database of the predictor variables and landslide inventory map,which is used to build the spatial model of landslide susceptibility.The model describes the relationship between the dependent variable(presence and absence of landslide) and the independent variables selected for study(predictor variables) by the best fitting function.A forward stepwise logistic regression model using maximum likelihood estimation is used in the regression analysis.An inventory of 84 landslides and cells within a buffer distance of 10m around the landslide is used as the dependent variable.Relief,slope,aspect,plan curvature,profile curvature,land use,soil,topographic wetness index,proximity to roads and proximity to lineaments are taken as independent variables.The constant and the coefficient of the predictor variable retained by the regression model are used to calculate the probability of slope failure and analyze the effect of each predictor variable on landslide occurrence in thestudy area.The model shows that the most significant parameter contributing to landslides is slope.The other significant parameters are profile curvature,soil,road,wetness index and relief.The predictive logistic regression model is validated using temporal validation data-set of known landslide locations and shows an accuracy of 85.29 %.     

Optimizing the frequency ratio method for landslide susceptibility assessment: A case study of the Caiyuan Basin in the southeast mountainous area of China

Bivariate statistical analysis of data-driven approaches is widely used for landslide susceptibility assessment, and the frequency ratio(FR) method is one of the most popular. However, the results of such assessments are dominated by the number of classes and bounds of landslide-related causative factors, and the optimal assessment is unknown. This paper optimizes the frequency ratio method as an example of bivariate statistical analysis for landslide susceptibility mapping based on a case study of the Caiyuan Basin, a region with frequent landslides, which is located in the southeast coastal mountainous area of China. A landslide inventory map containing a total of 1425 landslides(polygons) was produced, in which 70% of the landslides were selected for training purposes, and the remaining were used for validationpurposes. All datasets were resampled to the same 5 m × 5 m/pixel resolution. The receiver operating characteristic(ROC) curves of the susceptibility maps were obtained based on different combinations of dominating parameters, and the maximum value of the areas under the ROC curves(AUCs) as well as the corresponding optimal parameter was identified with an automatic searching algorithm. The results showed that the landslide susceptibility maps obtained using optimal parameters displayed a significant increase in the prediction AUC compared with those values obtained using stochastic parameters. The results also showed that one parameter named bin width has a dominant influence on the optimum. In practice, this paper is expected to benefit the assessment of landslide susceptibility by providing an easy-to-use tool. The proposed automatic approach provides a way to optimize the frequency ratio method or other bivariate statistical methods, which can furtherfacilitate comparisons and choices between different methods for landslide susceptibility assessment.     

Using Statistical Learning Algorithms in Regional Landslide Susceptibility Zonation with Limited Landslide Field Data

Regional Landslide Susceptibility Zonation(LSZ) is always challenged by the available amount of field data, especially in southwestern China where large mountainous areas and limited field information coincide. Statistical learning algorithms are believed to be superior to traditional statistical algorithms for their data adaptability. The aim of the paper is to evaluate how statistical learning algorithms perform on regional LSZ with limited field data. The focus is on three statistical learning algorithms, Logistic Regression(LR), Artificial Neural Networks(ANN) and Support Vector Machine(SVM). Hanzhong city, a landslide prone area in southwestern China is taken as a study case. Nine environmental factors are selected as inputs. The accuracies of the resulting LSZ maps are evaluated through landslide density analysis(LDA), receiver operating characteristic(ROC) curves and Kappa index statistics. The dependence of the algorithm on the size of field samples is examined by varying the sizes of the training set. The SVM has proven to be the most accurate and the most stable algorithm at small training set sizes and on all known landslide sizes. The accuracy of SVM shows a steadilyincreasing trend and reaches a high level at a small size of the training set, while accuracies of LR and ANN algorithms show distinct fluctuations. The geomorphological interpretations confirm the strength of SVM on all landslide sizes. Our results show that the strengths of SVM in generalization capability and model robustness make it an appropriate and efficient tool for regional LSZ with limited landslide field samples.     

Landslide on glaciers: an example from Western Alps(Cogne-Italy)

In the warm summer of 2017,a landslide failed from the south-east side of the Col des Clochettes on the top of the underlying Trajo Glacier.The study area is at an elevation of about 3500 m a.s.l.in the Gran Paradiso Massif and can be hardly reached by walking from Cogne(Aosta Valley,NW Italy).Studies conducted by field surveys,photogrammetry(structure from motion)and satellite images analysis,integrated with the evaluation of data from meteorological stations have been used to reconstruct the phenomenon and infer its causes.The site is very complex to be studied especially due to logistic problems,therefore,measurements and observations that are common practice in other landslides are very difficult to apply here.So,many of the results achieved are not adequately supported by field studies.Anyway,the following factors could have affected the stability of the slope:i)the tectonic structure of the area,which is reflected on the morphology and on the geomechanics characteristics of the rock masses;ii)the meteorological conditions during 3 months before the main failure,resulting in an extremely high temperature compared to historical data.Moreover,the analysis of multitemporal satellite images allowed to recognize that it was not a single landslide but that the phenomenon is articulated over time in at least five failures in about 2 months.Moreover,several predisposing factors may have been playing an important role in causing the instability:the degradation of permafrost(probably affecting rock mass due to the circulation of warm air and water in the discontinuity systems),the alternance of the freeze-thaw cycles and the availability of a considerable amount of water from rainfalls and nival fusion infiltrating deeply in the rock mass.More common causes such as rains and earthquakes have been excluded.     

Reliability analysis method applied in slope stability： slope prediction and forecast on stability analysis

Landslide is one kind of geologic hazards that often happens all over the world.It brings huge losses to human life and property;therefore,it is very important to research it.This study focused in combination between single and regional landslide,traditional slope stability analysis method and reliability analysis method.Meanwhile,methods of prediction of slopes and reliability analysis were discussed.     

Building vulnerability evaluation in landslide deformation phase

Building vulnerability evaluation is important in the risk assessment on earthquake and flood hazards. But for landslide hazard, it is also a very important part for the people in buildings. Most discussions or researches about building vulnerability are for landslide failure, few for landslide in deformation phase. For this objective, this paper discussed about building vulnerability evaluation using Zhaoshuling landslide as an example Zhaoshuling landslide named located in the Three Gorges Reservoir Area, China. After a field survey on the geological condition of landslide, detailed field investigation on the buildings’ location and structure is carried out. To get landslide surface deformation, numerical simulation method is used under the combining condition of water fluctuation and rainfall. Then building deformation and probable damage degree is analyzed according to landslide surface deformation and the relative theory in mining. Based on the national standard building damage classification system, the vulnerability of all the buildings on the landslide is semi-quantitatively evaluated.     

Probabilistic seismic landslide hazard assessment: a case study in Tianshui,Northwest China

Probabilistic analysis in the field of seismic landslide hazard assessment is often based on an estimate of uncertainties of geological, geotechnical,geomorphological and seismological parameters.However, real situations are very complex and thus uncertainties of some parameters such as water content conditions and critical displacement are difficult to describe with accurate mathematical models. In this study, we present a probabilistic methodology based on the probabilistic seismic hazard analysis method and the Newmark's displacement model. The Tianshui seismic zone(105°00′-106°00′ E, 34°20′-34°40′ N) in the northeastern Tibetan Plateau were used as an example. Arias intensity with three standard probabilities of exceedance(63%, 10%, and 2% in 50 years) in accordance with building design provisions were used to compute Newmark displacements by incorporating the effects of topographic amplification.Probable scenarios of water content condition were considered and three water content conditions(dry,wet and saturated) were adopted to simulate the effect of pore-water on slope. The influence of 5 cm and 10 cm critical displacements were investigated in order to analyze the sensitivity of critical displacement to the probabilities of earthquake-induced landslide occurrence. The results show that water content in particular, have a great influence on the distribution of high seismic landslide hazard areas. Generally, the dry coverage analysis represents a lower bound for susceptibility and hazard assessment, and the saturated coverage analysis represents an upper bound to some extent. Moreover, high seismic landslide hazard areas are also influenced by the critical displacements. The slope failure probabilities during future earthquakes with critical displacements of 5 cm can increase by a factor of 1.2 to 2.3 as compared to that of 10 cm. It suggests that more efforts are required in order to obtain reasonable threshold values for slope failure. Considering the probable scenarios of water content condition which is varied with seasons, seismic landslide hazard assessments are carried out for frequent, occasional and rare earthquake occurrences in the Tianshui region, which can provide a valuable reference for landslide hazard management and infrastructure design in mountainous seismic zones.     

Probability Prediction Model for Landslide Occurrences in Xi’an,Shaanxi Province,China

Landslides are increasing since the 1980s in Xi’an, Shaanxi Province, China. This is due to the increase of the frequency and intensity of precipitation caused by complex geological structures, the presence of steep landforms, seasonal heavy rainfall, and the intensifcation of human activities. In this study, we propose a landslide prediction model based on the analysis of intraday rainfall （IR） and antecedent effective rainfall （AER）. Primarily, the number of days and degressive index of the antecedent effective rainfall which affected landslide occurrences in the areas around Qin Mountains, Li Mountains and Loess Tableland was established. Secondly, the antecedent effective rainfall and intraday rainfall were calculated from weather data which were used to construct critical thresholds for the 10%, 50% and 90% probabilities for future landslide occurrences in Qin Mountain, Li Mountain and Loess Tableland. Finally, the regions corresponding to different warning levels were identified based on the relationship between precipitation and the threshold, that is; “A” region is safe, “B” region is on watch alert, “C” region is on warning alert and “D” region is on severe warning alert. Using this model, a warning program is proposed which can predict rainfall-induced landslides by means of real-time rain gauge data and real-time geo-hazard alert and disaster response programs. Sixteen rain gauges were installed in the Xi’an region by keeping in accordance with the regional geology and landslide risks. Based on the data from gauges, this model accurately achieves the objectives of conducting real-time monitoring as well as providing early warnings of landslides in the Xi’an region.     

Rapid prediction models for 3D geometry of landslide dam considering the damming process

The geometry of a landslide dam plays a critical role in its stability and failure mode, and is influenced by the damming process. However, there is a lack of understanding of the factors that affect the 3D geometry of a landslide dam. To address this gap,we conducted a study using the smoothed particle hydrodynamics numerical method to investigate the evolution of landslide dams. Our study included 17 numerical simulations to examine the effects of several factors on the geometry of landslide d...     

Study on distribution rule of sliding pushing force and remnant resistant sliding force acting on anti-sliding pile

Anti-slide pile is one of the important methods to administer landslide geological disaster because of its advantages.It plays important role in administering landslide.It is a premise of reasonable economy and technological advance to know the distribution rule and feature of the force between anti-sliding pile and surrounding rock.To determine the sliding force and remnant resistant sliding force,according to need of study,this paper sets up the geological model and mechanics model in term of a typical landslide,and analyzes the effect rule of sliding body distortion,strength and gravity to the pushing force and remnant resistant sliding force by use of the numerical model.The distribution rule of pushing force and remnant resistant sliding force of the type of landslide is given.     

Numerical modeling of bed deposition in rapid flow-like landslides: a case study of the Gaolou landslide in Shaanxi Province,China

Some flow-like landslides tend to lose materials while moving on a relatively dry sliding surface.This phenomenon is called bed deposition.In contrast to the bed entrainment phenomenon,bed deposition is relatively poorly understood.Therefore,an improved depth-averaged model is proposed to quantify this phenomenon.The deposition depth is calculated according to the momentum conservation of the deposited mass,and the rheological property of the sliding mass on the bottom is modified considering an abrupt increase in the depth of the sliding surface after deposition.Utilizing the proposed model,the Gaolou landslide,a typical flowlike landside occurring on October 6 th,2006 with an obvious bed deposition phenomenon in Shaanxi Province of China,is simulated to investigate the influence of bed deposition on its propagation process.The results indicate that the proposed model can effectively depict the bed deposition phenomenon in the Gaolou landslide.Bed deposition dissipates part of the kinetic energy of this landslide;thus,the simulated debris inundation area would likely be overestimated when this effect is neglected.On the other hand,the thin liquefied layer formed by the bed deposition process reduces the friction energy dissipation,contributing to the high mobility of this landslide.     

A catastrophic natural disaster chain of typhoon–rainstorm–landslide–barrier lake–flooding in Zhejiang Province,China

On August 10, 2019, due to the effect of a rainstorm caused by Super Typhoon Lekima, a landslide occurred in Shanzao Village, China. It blocked the Shanzao stream, forming a barrier lake, and then the barrier lake burst. This is a rare natural disaster chain of typhoon–rainstorm–landslide–barrier lake–flooding. This study was built on field surveys, satellite image interpretation, the digital elevation model(DEM), engineering geological analysis and empirical regression. The purpose was to reveal the characteristics and causes of the landslide, the features and formation process of the barrier lake and the dam break flooding discharge. The results show that the volume of the landslide deposit is approximately 2.4 × 105 m3. The burst mode of the landslide dam is overtopping, which took only 22 minutes from the formation of the landslide dam to its overtopping. The dam-break peak flow was 1353 m3/s, and the average velocity was 2.8-3.0 m/s. This study shows that the strongly weathered rock and soil slope has low strength and high permeability under the condition of heavy rainfall, which reminds us the high risk of landslides and the importance of accurate early warning of landslides under heavy rainfalls in densely populated areas of Southeast China, as well as the severity of the disaster chain of typhoon–rainstorm–landslide–barrier lake–flooding.     

Characteristics and failure mechanism of an ancient earthquake-induced landslide with an extremely wide distribution area

The Lamuajue landslide is located in Lamuajue village on the right bank of the Meigu River,Sichuan Province, China. This landslide is an ancient landslide with an extremely wide distribution area,covering an area of 19 km~2 with a maximum width of5.5 km and an estimated residual volume of 3×10~8 m~3.The objectives of this study were to identify the characteristics and failure mechanism of this landslide. In this study,based on field investigations,aerial photography, and profile surveys, the boundary,lithology, structure of the strata, and characteristics of the landslide deposits were determined. A gently angled weak interlayer consisting of shale was the main factor contributing to the occurrence of the Lamuajue landslide. The deposition area can be divided into three zones: zone A is an avalanche deposition area mainly composed of blocks,fragments, and debris with diameters ranging from0.1 m to 3 m; zone B is a residual integrated rock mass deposition area with large blocks,boulders and "fake bedrock"; and zone C is a deposition zone of limestone blocks and fragments. Three types of failure mechanism were analyzed and combined to explain the Lamuajue landslide based on the features of the accumulation area. First, a shattering-sliding mechanism caused by earthquakes in zone A. Second,a sliding mechanism along the weak intercalation caused by gravity and water in zone B. Third,a shattering-ejection mechanism generated by earthquakes in zone C. The results provide a distinctive case for the study of gigantic landslides induced by earthquakes, which is very important for understanding and assessing ancient earthquakeinduced landslides.     

Mechanical analysis for progressive failure of debris landslide

It is of significance to research failure mechanism of debris landslides that are widespread in the Three Gorges Reservoir Area. Based on the statistical analysis of the developmental law and failure mode of debris landslides in the Three Gorges Reservoir, the mode of progressive failure is found. The mechanical model for progressive failure of debris landslides with two slip bands is also established by applying slice method. According to the results of the downslide force between adjacent slices, if the downslide force of lower slice is larger than zero, the slice fails along the major sliding surface, otherwise it is stable. In result, the failure range is obtained. The stress function can be determined through dimensional analysis of failure slice. According to static boundary conditions of the slice, stress state of any point in the slice can be obtained. Then stress state of any point in the secondary slip band can also be established. The failure of the secondary slip band is judged on the basis of Mohr-Coulomb failure criterion. Therefore, a mechanical method is proposed to analyze the progressive failure of debris landslide with two slip bands.     

Stability analysis and treatment of No. 2 dump of Nanfen iron mine

On the basis of the study on the engineering geological characteristics of No. 2 dump of Nanfen iron mine and the analysis of the failure mode of dump landslide, the stability of the present dump, the stability of the dump 20 years later and the stability of double-bench dump are analyzed. Then, the debris flow risk is evaluated by fuzzy mathematics method. Finally, the comprehensive treatment for the dump is suggested. It is concluded that ① In rainy and snowmelt period, the stability would be decreasing sharply when ground water is not drained out in time; ② Double-bench dumping mode will improve stability of the dump little;③ Debris flow risk is middle danger. The interim debris flow with medium scale may occur. ④ Monitoring, draining and baffling work ought to be well done. ⑤In order to prevent the damage of landslide and debris flow, three measures are adopted, including setting rockfall net, setting the debris flow barrier and removing the residents.