Relationships between landslide types and topographic attributes in a loess catchment, China

Topographic attributes have been identified as the most important factor in controlling the initiation and distribution of shallow landslides triggered by rainfall.As a result,these landslides influence the evolution of local surface topography.In this research,an area of 2.6 km 2 loess catchment in the Huachi County was selected as the study area locating in the Chinese Loess Plateau.The landslides inventory and landslide types were mapped using global position system(GPS) and field mapping.The landslide inventory shows that these shallow landslides involve different movement types including slide,creep and fall.Meanwhile,main topographic attributes were generated based on a high resolution digital terrain model(5 m × 5 m),including aspect,slope shape,elevation,slope angle and contributing area.These maps were overlaid with the spatial distributions of total landslides and each type of landslides in a geographic information system(GIS),respectively,to assess their spatial frequency distributions and relative failure potentials related to these selected topographic attributes.The spatial analysis results revealed that there is a close relation between the topographic attributes of the postlandsliding local surface and the types of landslide movement.Meanwhile,the types of landslide movement have some obvious differences in local topographic attributes,which can influence the relative failure potential of different types of landslides.These results have practical significance to mitigate natural hazard and understandgeomorphologic process in thick loess area.     

Preliminary slope stability analysis and discontinuities driven susceptibility zonation along a crucial highway corridor in higher Himalaya,India

Identification of failure susceptible slopes through different rock engineering approach is highly valuable in landslide risk management along crucial highway corridors in the high mountainous region. In this study, a critical highway(NH-5) segment in higher Himalaya has been investigated using the various rock mass characterization schemes based on detailed field observations. Since the highway corridor is highly susceptible to discontinuities-driven failures, consisting of jointed rock masses;Mean and Combined kinematic feasibility analysis has been performed for 20 highway slopes. Observed slope mass classes have been compared to the feasibility percentage of discontinuities driven failures(wedge, toppling, and planar) and accordingly the kinematic feasibility zonation along highway segment has been done for each as well as overall failure types. Based on the slope mass conditions and discontinuities driven failures probability(%), responsive remedial measures have been proposed for individual highway slopes to ensure safe and uninterrupted transportation.     

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 %.     

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 adapt-able for three-dimensional landslide.Assuming the initial slip as the lower part of an ellipsoid ,the 3D critical slip surface in the 3D slper 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 devel-oped 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 topograhical meaning,so its results are more credible,All the calcula-tions are implemented by a computational program,3DSlopeGIS,in which a GIS component s used for fulfilling the GIS spatial analysis function.and all the data for the 3D slope safety factor calculation are in the from 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 algo-rithms and iteration procedures of the 3D problem can also be perfectly implemented.     

Hazard assessment of landslide disaster using information value method and analytical hierarchy process in highly tectonic Chamba region in bosom of Himalaya

The present study is focused on a comparative evaluation of landslide disaster using analytical hierarchy process and information value method for hazard assessment in highly tectonic Chamba region in bosom of Himalaya. During study, the information about the causative factors was generated and the landslide hazard zonation maps were delineated using Information Value Method (IV) and Analytical Hierarchy Process (AHP) using ArcGIS (ESRI). For this purpose, the study area was selected in a part of Ravi river catchment along one of the landslide prone Chamba to Bharmour road corridor of National Highway (NH-154A) in Himachal Pradesh, India. A numeral landslide triggering geoenvironmental factors i.e. slope, aspect, relative relief, soil, curvature, land use and land cover (LULC), lithology, drainage density, and lineament density were selected for landslide hazard mapping based on landslide inventory. Landslide hazard zonation map was categorized namely “very high hazard, high hazard, medium hazard, low hazard, and very low hazard”. The results from these two methods were validated using Area Under Curve (AUC) plots. It is found that hazard zonation map prepared using information value method and analytical hierarchy process methods possess the prediction rate of 78.87% and 75.42%, respectively. Hence, landslide hazard zonation map obtained using information value method is proposed to be more useful for the study area. These final hazard zonation maps can be used by various stakeholders like engineers and administrators for proper maintenance and smooth traffic flow between Chamba and Bharmour cities, which is the only route connecting these tourist places.     

Landslide hazard zonation mapping in ghat road section of Kolli hills,India

Landslides are the most common natural disaster in hilly terrain which causes changes in landscape and damage to life and property. The main objective of the present study was to carry out landslide hazard zonation mapping on 1：50,000 scale along ghat road section of Kolli hills using a Landslide Hazard Evaluation Factor（LHEF） rating scheme. The landslide hazard zonation map has been prepared by overlaying the terrain evaluation maps with facet map of the study area. The terrain evaluation maps include lithology, structure, slope morphometry, relative relief, land use and land cover and hydrogeological condition. The LHEF rating scheme and the Total Estimated Hazard（TEHD） were calculated as per the Bureau of Indian Standard（BIS） guidelines（IS： 14496（Part-2） 1998） for the purpose of preparation of Landslide Hazard Zonation（LHZ） map in mountainous terrains. The correction due to triggering factors such as seismicity, rainfall and anthropogenic activities were also incorporated with Total Estimated Hazard to get final corrected TEHD. The landslide hazard zonation map was classified as the high, moderate and low hazard zones along the ghat road section based on corrected TEHD.     

Landslide hazard zonation mapping and comparative analysis of hazard zonation maps

Landslide hazard zonation mapping at regional level of a large area provides a broad trend of landslide potential zones. A macro level landslide hazard zonation for a small area may provide a better insight into the landslide hazards. The main objective of the present work was to carry out macro landslide hazard zonation mapping on 1：50,000 scale in an area where regional level zonation mapping was conducted earlier. In the previous work the regional landslide hazard zonation maps of Srinagar- Rudraprayag area of Garhwal Himalaya in the state of Uttarakhand were prepared using subjective and objective approaches. In the present work the landslide hazard zonation mapping at macro level was carried out in a small area using a Landslide Hazard Evaluation Factor rating scheme. The hazard zonation map produced by using this technique classifies the area into relative hazard classes in which the high hazard zones well correspond with high frequency of landslides. The results of this map when compared with the regional zonation maps prepared earlier show that application of the present technique identified more details of the hazard zones, which are broadly shown in the earlier zonation maps.     

Landslide susceptibility mapping using an integrated model of information value method and logistic regression in the Bailongjiang watershed,Gansu Province,China

Bailongjiang watershed in southern Gansu province, China, is one of the most landslide-prone regions in China, characterized by very high frequency of landslide occurrence. In order to predict the landslide occurrence, a comprehensive map of landslide susceptibility is required which may be significantly helpful in reducing loss of property and human life. In this study, an integrated model of information value method and logistic regression is proposed by using their merits at maximum and overcoming their weaknesses, which may enhance precision and accuracy of landslide susceptibility assessment. A detailed and reliable landslide inventory with 1587 landslides was prepared and randomly divided into two groups, (i) training dataset and (ii) testing dataset. Eight distinct landslide conditioning factors including lithology, slope gradient, aspect, elevation, distance to drainages, distance to faults, distance to roads and vegetation coverage were selected for landslide susceptibility mapping. The produced landslide susceptibility maps were validated by the success rate and prediction rate curves. The validation results show that the success rate and the prediction rate of the integrated model are 81.7 % and 84.6 %, respectively, which indicate that the proposed integrated method is reliable to produce an accurate landslide susceptibility map and the results may be used for landslides management and mitigation.     

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.     

Geospatial susceptibility mapping of earthquake-induced landslides in Nuweiba area,Gulf of Aqaba,Egypt

Earthquake induced landslides are one of the most severe geo-environmental hazards that cause enormous damage to infrastructure, property, and loss of life in Nuweiba area. This study developed a model for mapping the earthquake-induced landslide susceptibility in Nuweiba area in Egypt with considerations of geological, geomorphological, topographical, and seismological factors. An integrated approach of remote sensing and GIS technologies were applied for that target. Several data sources including Terra SAR-X and SPOT 5 satellite imagery, topographic maps, field data, and other geospatial resources were used to model landslide susceptibility. These data were used specifically to produce important thematic layers contributing to landslide occurrences in the region. A rating scheme was developed to assign ranks for the thematic layers and weights for their classes based on their contribution in landslide susceptibility. The ranks and weights were defined based on the knowledge from field survey and authors experiences related to the study area. The landslide susceptibility map delineates the hazard zones to three relative classes of susceptibility: high, moderate, and low. Therefore, the current approach provides a way to assess landslide hazards and serves for geo-hazard planning and prediction in Nuweiba area.     

四川省滑坡灾害气象预警模型建立与验证

四川省滑坡灾害严重,特别是2008年之后,灾情显著加剧,如何预防滑坡灾害是保护人民生命财产安全的有效途径。滑坡灾害的预警模型研究是滑坡灾害预防领域的核心课题。本文对四川省滑坡灾害危险性进行了评价,并开展了滑坡灾害气象风险预警模型研究。①以确定性系数的方法量化坡度、地形起伏度、水文地质岩性、植被覆盖度、地震烈度和年均降雨量因子,建立逻辑回归模型,定量地进行四川省滑坡灾害危险性区划,并对结果进行验证。结果表明,四川省滑坡灾害高危险性区域成“Y”字型分布,此外川中、川东北地区滑坡灾害危险性也非常高,这与四川省滑坡灾害的空间分布情况相符。②在前期滑坡灾害与降雨量统计分析、滑坡灾害危险性评价的基础上,以滑坡灾害危险性评价为静态因子,日降雨量数据为动态因子,通过逻辑回归模型的结果,确定以当日降雨量概率化值、滑坡灾害危险性值、前一日降雨概率化值、前两日降雨概率化值、前三日降雨概率化值为临灾模型影响因子,各因子对预警结果影响程度按上述顺序递减,建立了地质-气象耦合的临灾气象预警模型。通过检验区数据对模型的检验表明,该预警模型能成功预警80%以上的滑坡灾害;通过滑坡灾害群发个例检验发现,该预警模型与四川省现用模型相比,预警区域明显减小,空报率和漏报率显著降低。     

水库滑坡涌浪风险研究现状和灾害链风险管控实践

滑坡作为水库库区主要地质灾害类型之一,其风险研究一直是近年来的研究热点。水库滑坡涌浪的产生使滑坡灾害的影响范围由滑坡源本身扩散到上下游数千米,极大地扩大了滑坡风险的承灾体类型与数量以及灾害损失程度。因涉及交叉学科领域,滑坡涌浪风险评估是滑坡风险灾害链评价的难点与前沿课题。本文综合了前人近几十年来的研究成果,首先从危险性、易损性以及风险3个方面出发,对国内外的滑坡涌浪风险研究现状和常用的研究方法进行了概述,并对重点代表性研究成果进行了述评分析,针对滑坡涌浪风险研究方面的新进展进行了介绍,包括考虑实际河道地形复杂性的试验研究、聚焦于滑坡-水体相互作用机制的多种数值模拟方法耦合研究,以及基于多种承灾体类型的易损性评价体系等。然后对近年来三峡库区发生过的多起滑坡涌浪风险管控实例的过程与后果进行了详细的阐述。最后基于多年的研究经验提出了滑坡涌浪灾害链风险研究的新方向和新思路,即涌浪风险应与滑坡风险评价体系相互融合,并沿着定量化、规范化、精细化的方向发展。      

Pressure characteristics of landslide-generated impulse waves

The destructiveness of impulse waves generated by landslides(IWL) originates from the wave's movement and load, wherein the impulse wave's load is the major cause of sub-aerial building damage and casualties. In this study, an experiment involving 16 groups of physical tests for the wave pressure generated by a landslide was designed, consisting of 4 sets of IWL and 4 opposite bank slope angles. A high-frequency strain system was used to measure the total pressure of the impulse wave in a water tank. The tests showed that the dynamic pressure caused by the IWL can be divided into two types: impact pressure generated by the jetflow and the pulsating pressure caused by the wave. Under the same impulse wave conditions, the maximum run-up becomes smaller as the opposite bank's slope angle increases, and the jetflow maximum impact pressure experienced by the opposite bank increases, while the maximum pulsating pressure caused by the impulse wave is slightly decreased. Different from previous studies, the spatial maximum pressure distributions of the wave generated by landslide were concluded that the position of the maximum pulsating pressure appears adjacent to the still water surface, and the overall spatial distribution pattern of maximum wave pressure is presented as an inclined "M" shape.Meanwhile, this study is the first to quantitatively analyzed that impact pressure has a very short action time, is even 7 times of the pulse pressure value, and there is a simple mathematical linear relationship between the two. Currently, some wave-load formulas for wind waves and tides are not applicable to calculating the loads of IWL. Research on the load of IWL will explain the hazard of impulse wave very clearly, and will greatly contribute to hazard prevention, mitigation and risk assessment work associated with IWL.     

基于信息量模型和数据标准化的滑坡易发性评价

本文以北川曲山-擂鼓片区为研究区,将坡度、坡向、高程、地层、距断层的距离、距水系的距离和距道路的距离作为该区域滑坡易发性评价因子。采用信息量模型计算了各项评价因子的信息量值,并运用4种标准化模型对信息量值进行标准化处理。各评价因子的权重由层次分析法（AHP）确定。在GIS中将权重值和各评价因子的标准化信息量值,进行叠加计算得到区域滑坡总信息量值,并基于自然断点法对其进行重分类,将研究区划分为极高易发区、高易发区、中易发区、低易发区和极低易发区5级易发区。将基于4种标准化模型和信息量模型得到的滑坡易发性评价结果进行了对比分析,结果表明：基于最值标准化信息量模型的滑坡易发性评价结果的ROC曲线下面积AUC值为0.807,高于其余模型的AUC值,说明最值标准化信息量模型的滑坡易发性评价效果最好。极高易发区面积占研究区面积的20.03%,离断层和水系较近,主要分布地层为寒武系、志留系和三迭系。研究结果可为区内滑坡风险评价和灾害防治提供参考。     

山地灾害致贫风险初步分析————以湖北省恩施州为例

中国的贫困地区主要分布在山区,山地灾害的多发,易发在某种程度上成为制约贫困地区经济发展的因素之一.目前,山地灾害的研究集中于动力学研究,缺乏风险尤其是灾害致使贫困风险的研究.本文对山地灾害特有灾害与一般地质灾害的概念进行了区分;根据贫困的内涵与可量测性,定义了山地灾害的贫困脆弱性及山地灾害致贫风险;以贫困脆弱性分布和灾害危险性分布,构建区域山地灾害致贫风险评价模型,并基于此模型对少数民族特困地区--湖北省恩施土家族苗族自治州(简称恩施州)进行应用研究.在示例分析中,首先利用确定性系数模型和频率比例法对山地灾害的危险性进行了评价;然后,从暴露性和应对能力2个方面选取了经济,社会及自然指标,以进行脆弱性评价;最后,利用通用灾害风险评价公式对研究区由于山地灾害导致的贫困风险在空间的分布进行评价,得到了研究区的山地灾害致贫风险分布与分级图.     

Centrifuge model test of an irrigation-induced loess landslide in the Heifangtai loess platform,Northwest China

The Heifangtai platform in Northwest China is famous for irrigation-induced loess landslides. This study conducted a centrifuge model test with reference to an irrigation-induced loess landslide that occurred in Heifangtai in 2011. The loess slope model was constructed by whittling a cubic loess block obtaining from the landslide site. The irrigation water was simulated by applying continuous infiltration from back of the slope. The deformation, earth pressure, and pore pressure were investigated during test by a series of transducers. For this particular study, the results showed that the failure processes were characterized by retrogressive landslides and cracks. The time dependent reductions of cohesion and internal friction angle at basal layer with increasing pore-water pressure were responsible for these failures. The foot part of slope is very important for slope instability and hazard prevention in the study area, where concentration of earth pressure and generation of high pore-water pressures would form before failures. The measurements of earth pressure and pore-water pressure might be effective for early warning in the study area.     

Landslide susceptibility analysis of Karakoram highway using analytical hierarchy process and scoops 3D

Landslides are prevalent, regular, and expensive hazards in the Karakoram Highway(KKH) region. The KKH connects Pakistan with China in the present China-Pakistan Economic Corridor(CPEC) context. This region has not only immense economic importance but also ecological significance. The purpose of the study was to map the landslide-prone areas along KKH using two different techniquesAnalytical Hierarchy Process(AHP) and Scoops 3 D model. The causative parameters for running AHP include the lithology, presence of thrust, land use land cover, precipitation, and Digital Elevation Model(DEM) derived variables(slope, curvature, aspect, and elevation). The AHP derived final landslide susceptibility map was classified into four zones, i.e., low, moderate, high, and extremely high. Over 80% of the study area falls under the moderate(43%) and high(40%) landslide susceptible zones. To assess the slope stability of the study area, the Scoops 3 D model was used by integrating with the earthquake loading data. The results of the limit equilibrium analysis categorized the area into four groups(low, moderate, high, and extremely high mass) of slope failure. The areas around Main Mantle Thrust(MMT) including Dubair, Jijal, and Kohistan regions, had high volumes of potential slope failures. The results from AHP and Scoops 3 D techniques were validated with the landslides inventory record of the Geological Survey of Pakistan and Google Earth. The results from both the techniques showed similar output that coincides with the known landslides areas. However, Scoops 3 D provides not only susceptible zones but also the range of volume of the potential slope failures. Further, these techniques could be used in other mountainous areas, which could help in the landslide mitigation measures.     

GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms

In this study, a novel approach of the landslide numerical risk factor(LNRF) bivariate model was used in ensemble with linear multivariate regression(LMR) and boosted regression tree(BRT) models, coupled with radar remote sensing data and geographic information system(GIS), for landslide susceptibility mapping(LSM) in the Gorganroud watershed, Iran. Fifteen topographic, hydrological, geological and environmental conditioning factors and a landslide inventory(70%, or 298 landslides) were used in mapping. Phased array-type L-band synthetic aperture radar data were used to extract topographic parameters. Coefficients of tolerance and variance inflation factor were used to determine the coherence among conditioning factors. Data for the landslide inventory map were obtained from various resources, such as Iranian Landslide Working Party(ILWP), Forestry, Rangeland and Watershed Organisation(FRWO), extensive field surveys, interpretation of aerial photos and satellite images, and radar data. Of the total data, 30% were used to validate LSMs, using area under the curve(AUC), frequency ratio(FR) and seed cell area index(SCAI).Normalised difference vegetation index, land use/land cover and slope degree in BRT model elevation, rainfall and distance from stream were found to be important factors and were given the highest weightage in modelling. Validation results using AUC showed that the ensemble LNRF-BRT and LNRFLMR models(AUC = 0.912(91.2%) and 0.907(90.7%), respectively) had high predictive accuracy than the LNRF model alone(AUC = 0.855(85.5%)). The FR and SCAI analyses showed that all models divided the parameter classes with high precision. Overall, our novel approach of combining multivariate and machine learning methods with bivariate models, radar remote sensing data and GIS proved to be a powerful tool for landslide susceptibility mapping.     

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.     

GIS based spatial data analysis for landslide susceptibility mapping

Landslide susceptibility map delineates the potential zones for landslides occurrence. The paper presents a statistical approach through spatial data analysis in GIS for landslide susceptibility mapping in parts of Sikkim Himalaya. Six important causative factors for landslide occurrences were selected and corresponding thematic data layers were prepared in GIS. Topographic maps,satellite image,field data and published maps constitute the input data for thematic layer preparation. Numerical weights for different categories of these factors were determined based on a statistical approach and the weighted thematic layers were integrated in GIS environment to generate the landslide susceptibility map of the area. The landslide susceptibility map classifies the area into five different landslide susceptible zones i.e.,very high,high,moderate,low and very low. This map was validated using the existing landslide distribution in the area.