New understandings of the June 24th 2017 Xinmo Landslide,Maoxian, Sichuan,China

On June 24, 2017 (21:39 UTC, June 23rd), a catastrophic landslide occurred at Xinmo village of Mao County, Sichuan Province, China. Soon after the event, some research teams carried out field investigations in order to both support the emergency operations and to understand the failure mechanism and possible evolutionary scenarios. Based on further in-depth interpretation of high-resolution remote-sensing images and detailed field surveys, it is newly found that there are at least six old rockfall deposits in the source area that prove the historic activity of the landslide scarp. Seismic data of the event and morphological evidences along the slope indicate that the landslide was preceded by a significant rockfall. Mechanical calculations show that the surface force due to pore water was far less than the impact force due to the rockfall. It means that the subsequent major rock avalanche was more likely due to the impact of the rockfall on the rock slope below, which broke the rock bridges and caused drop of shear resistance along the fractures. According to these new understandings, a different triggering mechanism for the landslide is proposed.     

Charnockite bedrock,Chennai coast,Tamil Nadu: Micromorphology and geochemical signatures in stages of the weathering processes

Occurrences of landslide are most common and critical issue in North-East India. The various types of slope failures have been affected most part of slopes and road section between Malidor to Sonapur area (approx 30 Km) along NH-44 within Jaintia hills district, Meghalaya, India. These slope failures causes considerable loss of life and property along with many inconveniences such as disruption of traffic along highways. The unscientific excavations of rock slopes for road widening or construction purposes may weaken the stability of the slopes. The rocks exposed in the area are highly jointed sandstone and shale of Barail Group of Oligocene age. The Sonapur landslide is most dangerous and destructive rock fall-cum debris flow. The present study includes the kinematic analysis of the slope to assess the potential failure directions as the rocks are highly jointed in some parts of road cut sections. The continuous slope mass rating (CSMR) technique has been applied for slope stability analysis at five vulnerable locations. Kinematic analysis indicates mainly wedge type of failure along with few toppling and planar failures. These failure required immediate treatment to prevent the slide and long term stability of the slope.     

Macro-zonation of landslide susceptibility in Garamaura-Swarghat-Gambhar section of national highway 21, Bilaspur District, Himachal Pradesh (India)

Landslides the most common geo-hazard in hilly terrain are short lived phenomena but cause extraordinary landscape changes and destruction of life and property. The frequency and intensity of landslides occurrences along NH-21 during the rainy season not only disrupts traffic movement but also misbalance the agro-economic and developmental activities of the region frittering away thousand crores of rupees from the exchequer. An assessment of landslide susceptibility is, therefore, a prerequisite for sustainable development of the region. The present study deals with the preparation of macro-zonation maps of landslide susceptibility in an area of about 100 sq km on 1:50,000 scale across Garamaura-Swarghat section of National Highway-21. The map has been prepared by superimposing the terrain evaluation maps in a particular zone such as lithological map, structural map, slope morphometry map, relative relief map, land use and land cover map and hydrological condition map using landslide susceptibility evaluation factor rating scheme and calculating the total estimated susceptibility as per the guidelines of IS: 14496 (Part-2) 1998). Numerical weightages are assigned to the prime causative factors of slope instability such as lithology, structure, slope morphometery, relative relief, land use and groundwater conditions as per the scheme approved by Bureau of Indian Standard for the purpose of landslide susceptibility zonation. The area depicts zones of different instability. The identified susceptibility zones compared with landslide intensity in the area show some congruence with the weightages of the inputs. The incongruence in intensity and frequency of landslide occurrences and the inferred susceptibility zones of BIS scheme allow other geotechnical considerations and causative factors to be incorporated for the landslide susceptibility zonation.     

Numerical Modeling of the Seasonal Dynamic Characteristics of the Koxkar Glacier,in West Tianshan,China

Landslides commonly occurs in hilly areas and causes an enormous loss iof life and property every year. National highway-1D (NH-1D) is the only road link between the two districts (Kargil and Leh) of Ladakh region that connects these districts with Kashmir valley. The landslide failure record of the recent past along this sector of the highway is not available. The present study documents landslide susceptible zones and records occurrence of 60 landslides during the last 4 years showing an increasing trend in the occurrence of landslides over these years in this sector. The landslide susceptibility zonation map has been prepared based on the numerical rating of ten major factors viz. slope morphometry, lithology, structure, relative relief, land cover, landuse, rainfall, hydrological conditions, landslide incidences and Slope Erosion, categorised the area in different zones of instability based on the intensity of susceptibility. The landslide susceptibility map of the area encompassing 73.03 km² is divided into 150 facets. Out of the total of 150 facets, 85 facets fall in low susceptibility zone covering 43.56 km2 which constitute about 59.65% of the total area under investigation with a record of 5 landslides; 40 facets fall in the moderate susceptibility zone covering 16.94km² which constitutes about 23.19% of the study area with a record of 20 landslides; and 25 facets fall in the high susceptibility zone covering 12.53 km² which constitute about 17.15% of the study area with a record of 35 landslides. Most of the facets which fall in HSZ are attributed to slope modification for road widening.     

Landslide hazard mapping along national highway-154A in Himachal Pradesh,India using information value and frequency ratio

For the socio-economic development of a country, the highway network plays a pivotal role. It has therefore become an imperative to have landslide hazard assessment along these roads to provide safety. The current study presents landslide hazard zonation maps, based on the information value method and frequency ratio method using GIS on 1:50,000 scale by generating the information about the landslide influencing factors. The study was carried out in the year 2017 on a part of Ravi river catchment along one of the landslide-prone Chamba to Bharmour road corridor of NH-154A in Himachal Pradesh, India. A number of landslide triggering geo-environmental factors like “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. The landslide inventory has been developed using satellite imagery, Google earth and by doing exhaustive field surveys. A digital elevation model was used to generate slope gradient, slope aspect, curvature, and relative relief map of the study area. The other information, i.e., soil maps, geological maps, and toposheets, have been collected from various departments. The 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 have been validated using area under curve (AUC) method. It has been found that hazard zonation map prepared using frequency ratio model had a prediction rate of 75.37% while map prepared using information value method had prediction rate of 78.87%. Hence, on the basis of prediction rate, the landslide hazard zonation map, obtained using information value method, was experienced to be more suitable for the study area.     

Evaluation of potential landslide damming: Case study of Urni landslide,Kinnaur, Satluj valley,India

This work aims to understand the process of potential landslide damming using slope failure mechanism,dam dimension and dam stability evaluation. The Urni landslide, situated on the right bank of the Satluj River, Himachal Pradesh(India) is taken as the case study. The Urni landslide has evolved into a complex landslide in the last two decade(2000-2016) and has dammed the Satluj River partially since year 2013,damaging ～200 m stretch of the National Highway(NH-05). The crown of the landslide exists at an altitude of ～2180-2190 m above msl, close to the Urni village that has a human population of about 500.The high resolution imagery shows ～50 m long landslide scarp and ～100 m long transverse cracks in the detached mass that implies potential for further slope failure movement. Further analysis shows that the landslide has attained an areal increase of 103,900 ± 1142 m^2 during year 2004-2016. About 86% of this areal increase occurred since year 2013. Abrupt increase in the annual mean rainfall is also observed since the year 2013. The extreme rainfall in the June, 2013; 11 June(～100 mm) and 16 June(～115 mm),are considered to be responsible for the slope failure in the Urni landslide that has partially dammed the river. The finite element modelling(FEM) based slope stability analysis revealed the shear strain in the order of 0.0-0.16 with 0.0-0.6 m total displacement in the detachment zone. Further, kinematic analysis indicated planar and wedge failure condition in the jointed rockmass. The debris flow runout simulation of the detached mass in the landslide showed a velocity of ～25 m/s with a flow height of ～15 m while it(debris flow) reaches the valley floor. Finally, it is also estimated that further slope failure may detach as much as 0.80 ±0.32 million m^3 mass that will completely dam the river to a height of 76±30 m above the river bed.     

GPS在滑坡监测中的应用研究

本文主要介绍GPS用于地质灾害滑坡监测的技术和方法,并通过在中国四川雅安峡口滑坡示范区布设的GPS监测网的测量试验,阐述了在地形复杂、观测条件恶劣的山区进行GPS滑坡监测时,监测点位选择、监测网布设、数据处理的方法。监测结果表明,GPS滑坡监测的精度达到毫米级,完全可以应用于滑坡监测。      

四川茂县周场坪滑坡发育特征与变形监测分析

位于四川茂县南新镇的周场坪滑坡是一大型古滑坡,曾于1982年发生大规模快速复活,目前滑体半堰塞岷江。野外地质调查表明,周场坪滑坡在平面上呈不规则长舌形,长约850 m,滑体前后缘高差约350 m;在剖面上发育3级滑动,钻探揭露滑带埋深以50~70 m为主,推测潜在失稳滑坡体积为1 500×10 ⁴~2 000×10 ⁴ m ³。周场坪滑坡在平面上分为4个变形区,在滑体中后部和前缘坡脚发育大量拉裂缝与下错陡坎,拉裂缝宽度以0.2~3.0 m为主,陡坎下错高度2~10 m。在野外调查和钻探分析的基础上,对该滑坡开展了地表位移(GNSS)、深部蠕滑变形(钻孔测斜仪)和雨量等监测。监测分析表明,目前周场坪滑坡后缘变形速率达0.80 m/a,中部和前缘分别为0.69 m/a和0.51 m/a,呈推移式滑动变形,整体向NW310°方向滑动;地表位移速率在监测期内基本在1~3 mm/d之间波动,波动主要受降雨量影响,且略滞后于降雨量;滑移加速度基本在0~6 mm/d ²范围波动。ZK2钻孔测斜仪监测数据表明,滑坡在80 m深度内主要沿2层滑带蠕滑,其中浅层滑带埋深在22 m左右,深层滑带埋深在46 m左右,滑移速率在0~5 mm/d范围波动。综合研究认为,周场坪滑坡目前处于缓慢变形的深层蠕滑中,其变形速率受降雨和河流侵蚀等因素的影响,在极端内、外动力条件下,可能会加速滑动,并再次整体复活,造成堵塞岷江等危害。     

贵州省六盘水水城高位远程滑坡流态化运动过程分析

高位远程滑坡是中国西南山区常见的一类灾难性地质灾害,其发生往往伴随有碰撞解体效应,导致滑体碎裂化,转化为碎屑流或泥石流,具有流化运动堆积的特征。2019年7月23日发生于中国贵州省六盘水市水城县的鸡场镇滑坡是典型的高位远程流态化滑坡,滑坡前后缘高差430 m,水平运动距离1340 m,堆积体体积200×104 m3,导致21幢房屋被掩埋,51人遇难。基于野外详细调查和滑前滑后地形对比,采用DAN-W软件对水城滑坡的整个运动堆积过程进行了模拟,结果显示:水城滑坡在滑源区残留堆积体厚度最大为27 m,堆积区最大堆积厚度为15 m,滑坡碎屑流前缘最大运动速度为27 m/s,最大动能为6.57×106 J;滑坡高位剪出,由于势能转化为动能,滑坡快速达到速度峰值,并铲刮地表松散土层;由于强降雨,滑体高速运动使基底孔隙水来不及排出,导致基底摩擦力下降,降低能量损耗,滑体解体促进颗粒流化运动,减少了摩擦,也是滑坡远程运动的重要原因。      

Extraction and application analysis of landslide influential factors based on LiDAR DEM: a case study in the Three Gorges area,China

The aim of this study was to identify some new factors that may impact the occurrence and distribution of landslides based on light detection and ranging digital elevation model (LiDAR DEM), and to examine whether these factors can apply to distinguish between landslide and non-landslide pixels. Twenty-one landslide influential factors were identified. Thereinto, there were ten novel factors, namely the texture factors of slope and surface roughness, including the contrast (Con), correlation (Cor), angular second moment, entropy, and homogeneity (Hom) textures. Qualitative and quantitative analysis and feature selection method were applied to examine the application of these factors. The analysis results indicate that these factors have certain abilities to distinguish between landslide and non-landslide objects. And the selected optimal factors combination that derived from feature selection method was DEM, slope, Hom_d, Con_s, Cor_s, Hom_s, Con_r, Cor_r, and Hom_r (_d, _s, and _r represent DEM, slope, and surface roughness textures, respectively). In conclusion, the identified landslide influential factors can provide effective information for landslide identification. And the new texture factors of slope and surface roughness could act as important measurements that can improve the precision of landslide inventory mapping, susceptibility mapping, and risk assessment.     

Landslide susceptibility revealed by LIDAR imagery and historical records,Seattle, Washington

Light detection and ranging (LIDAR) data were used to visually map landslides, headscarps, and denuded slopes in Seattle, Washington. Four times more landslides were mapped than by previous efforts that used aerial photographs. The mapped landforms (landslides, headscarps, and denuded slopes) were created by many individual landslides. The spatial distribution of mapped landforms and 1308 historical landslides show that historical landslide activity has been concentrated on the mapped landforms, and that most of the landslide activity that created the landforms was prehistoric. Thus, the spatial densities of historical landslides on the landforms provide approximations of the landforms' relative susceptibilities to future landsliding. Historical landslide characteristics appear to be closely related to landform type so relative susceptibilities were determined for landslides with various characteristics. No strong relations were identified between stratigraphy and landslide occurrence; however, landslide characteristics and slope morphology appear to be related to stratigraphic conditions.Human activity is responsible for causing about 80% of historical Seattle landslides. The distribution of mapped landforms and human-caused landslides suggests the probable characteristics of future human-caused landslides on each of the landforms. The distribution of mapped landforms and historical landslides suggests that erosion of slope-toes by surface water has been a necessary condition for causing Seattle landslides. Human activity has largely arrested this erosion, which implies that landslide activity will decrease with time as hillsides naturally stabilize. However, evaluation of glacial-age analogs of areas of recent slope-toe erosion suggests that landslide activity in Seattle will continue for the foreseeable future.     

Landslide susceptibility analysis based on ArcGIS and Artificial Neural Network for a large catchment in Three Gorges region,China

A landslide susceptibility map is very important and necessary to efficiently prevent and mitigate the losses brought by natural hazard for a large area. For the purpose of landslide susceptibility analysis for the whole Xiangxi catchment (3,209 km²), Artificial Neural Network (ANN) analysis was applied as the main method. The whole catchment was divided into two parts: the training area and the implementation area. The backwater area (559 km²) of Xiangxi catchment was used as the training area for the ANN method. In the training area the correlations between the landslide distribution and its causative factors, which includes lithology, slope angle, slope curvature and river network, have been analyzed based on the geological map and digital elevation model (DEM). The back-propagation training algorithm in ANN was selected to train the sample data from the training area, which were composed of input data (causative factors) and target output data (landslide occurrence), in order to find the correlations between them. Based on these correlations and input data in the implementation area (causative factors), the network output data were obtained for the implementation area. In the end, a map of landslide susceptibility, which was established by network output data, was presented for Xiangxi catchment. ArcGIS was applied to extract and quantify input information from a DEM for susceptibility analysis and also to present the result visually. As a result, a landslide susceptibility map, in which 70 % of all landslides are rightly classified in the training area (backwater area), was created for Xiangxi catchment.     

Mechanism of the giant Seimareh Landslide,Iran, and the longevity of its landslide dams

Seimareh Landslide (SL) is globally recognized as one of the largest rock mass movements in the world. It is located along the border of Ilam and Lorestan provinces in southwest Iran, in the heart of the Zagros Mountain Range. There are controversial findings about the mechanism of the landslide formation. This field work study reviewed the possible mechanisms of failure and analyzed post-failure geomorphic features. Drainage pattern disturbance in the depositional region and consequent dammed lake formation are among the most significant characteristics of these features. Seimareh, Jaidar and Balmak are three large landslide-dammed lakes. The present study analyzed the processes responsible for the formation and erosion of the Jaidar and Seimareh Landslide dams using the available annual sedimentation and field measurements of the sediment deposited in these lakes. The results showed that the SL dam has been formed about 935 years after the landslide event. Detailed field investigations indicated a specific hydro-morphological condition in the landslide area. The results implied that the main causes of the failure were probably the particular hydro-morphological characteristic of the landslide source area together with the enormous eroding energy resulted from merging of two high-flow rivers which eroded the base of the southern flank of Kabir-kuh Mountain. However, the unusual size of the landslide suggests that an external factor, e.g., a huge earthquake, might have triggered the failure.     

Measuring precursory movements of the recent Xinmo landslide in Mao County,China with Sentinel-1 and ALOS-2 PALSAR-2 datasets

The Xinmo landslide occurred in the early morning of 24 June 2017 at about 5:38 am local time. This catastrophic event caused enormous casualties and huge economic losses in Xinmo Village, Mao County, Sichuan Province, China. In this study, Synthetic Aperture Radar (SAR) datasets acquired by X-band TerraSAR-X, Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) aboard the Advanced Land Observing Satellite-2 (ALOS-2), and C-band Sentinel-1 over the disaster area were collected and analyzed to characterize this landslide. The high-resolution TerraSAR-X intensity images were used to evaluate the landslide disaster and delineate the sliding area. Afterwards, two ALOS-2 PALSAR-2 image pairs and a stack of 45 Sentinel-1 images were processed to detect precursory movements of the landslide surface, using the conventional differential InSAR (DInSAR) method and advanced time series InSAR analysis. The unstable source area near the ridge was identified from the displacement rate map derived from Sentinel-1 datasets. The maximum displacement rate detected at the source area was ?35mm/year along the radar line of sight (LOS) direction. The time series of LOS displacements over 2 years presents an easily discerned seasonal evolution pattern. In particular, a sudden acceleration of the displacement, dozens of days before the collapse was clearly captured by the Sentinel-1 observations, which might suggest that early warning of landslide disasters is possible given the availability of operational SAR data acquired in frequent repeat-pass mode, such as the Sentinel-1 twin-satellite constellation.     

长江三峡黄腊石和黄土坡滑坡分形分维分析

为了探索复杂滑坡轨迹结构演化及其稳定性定量分析计算的新途径, 利用分形分维理论, 分析三峡库首区黄腊石滑坡和黄土坡滑坡边界轨迹的几何分形结构, 并采用盒维数法分别求得黄腊石滑坡西部活动性滑坡群、东部小滑坡群和整个滑坡系统及黄土坡滑坡分形结构的特征性斜率曲线和分维值.计算结果表明: 每个滑坡群的轨迹结构具有其特征性的分维值, 轨迹结构越复杂, 结构层次越清楚, 分维值越高.其中, 黄腊石滑坡西部活动性滑坡群的分维值最高, D =1.483, 黄土坡滑坡的分维值最低, D =1.111.主要结论包括: (1) 滑坡边界轨迹存在统计上的自相似性, 具有分形结构特征; (2) 滑坡轨迹结构的宏观扩展变形过程是一个增维过程, 而不是降维过程; (3) 滑坡轨迹结构越复杂, 有序性越好, 分维值越高, 其稳定性越差; 因此, 分数维可作为衡量滑坡轨迹结构复杂性和稳定性的重要标志.      

基于快速聚类-信息量模型的汶川及周边两县滑坡易发性评价

滑坡灾害易发性评价研究对规划灾害区域、制定防灾策略等方面具有十分重要的意义。以滑坡灾害频发的汶川及周边两县（理县和茂县）为例,提出滑坡灾害易发性评价的快速聚类-信息量模型。选取坡度、高程、坡向、距构造的距离、距水系的距离、地层岩性和土地利用情况为对滑坡有重要影响的7个影响因子,并在二级因子的分类上,对上述前5个影响因子依据159处滑坡样本分别开展快速聚类分析,同时也给出了传统的等距分类法,以便与快速聚类方法形成对比,对后2个影响因子则以定性方法分类。根据上述二级分类方法的不同,以及滑坡样本是否考虑面积因素,将信息量模型细分为四类（模型a:快速聚类-数量模型、模型b:等距分类-数量模型、模型c:快速聚类-面积模型、模型d:等距分类-面积模型）,分别计算各二级指标信息量,并通过ArcGIS空间叠加分析得到研究区域信息量分布,然后通过自然断点法将研究区滑坡易发性划分为五个等级。以易发性递增原则和线下面积（Area Under Curve,AUC）作为精度评价指标,结果表明:①快速聚类模型（模型a和模型c）整体效果优于等距分类模型（模型b和模型d）;②相同分类方法下,面积模型（模型c与模型d）整体优于数量模型（模型a和模型b）;③在上述两项优势的加持下,模型c相较于模型b,评价精度明显提升,其AUC值从80.46%提高到87.25%。     

折射法和高密度电法在古滑坡勘探中的应用

古滑坡体地球物理调查方法技术的选择对勘探效果至关重要。以吉林省通化市拟建集安—通化高速公路滑坡体为例,采用折射波法和高密度电法,利用二维反演技术进行数据处理。结合地质信息,确定了滑坡体的形态及厚度变化,厚度最大约20 m,滑坡性质为堆积层滑坡。研究结果表明折射波法和高密度电法进行古滑坡勘探,效果较好。     

Development of an empirical model for rainfall-induced hillside vulnerability assessment: a case study on Chen-Yu-Lan watershed,Nantou, Taiwan

In Taiwan, the hillside is about 70 % of total area. These areas also have steep topography and geological vulnerability. When an event of torrential rain comes during a typhoon, the landslide disasters usually occur at these areas due to the long duration and high intensity of rainfall. Therefore, a design which considers the potential landslide has become an important issue in Taiwan. In this study, a temporal characteristic of landslide fragility curve (LFC) was developed, based on the geomorphological and vegetation factors using landslides at the Chen-Yu-Lan watershed in Taiwan, during Typhoon Sinlaku (September 2008) and Typhoon Morakot (August 2009). This study addressed an effective landslide hazard assessment process, linking together the post-landslide damage and post-rainfall data for LFC model. The Kriging method was used to interpolate the rainfall indices (R ₀, R, I) for numerical analysis. Remote sensing data from SPOT images were applied to analyze the landslide ratio and vegetation conditions. The 40-m digital elevation model was used for slope variation analysis in the watershed, and the maximum likelihood estimate was conducted to determine the mean and standard deviation parameters of the proposed empirical LFC model. This empirical model can express the probability of exceeding a damage state for a certain classification (or conditions) of landslides by considering a specific hazard index for a given event. Finally, the vulnerability functions can be used to assess the loss from landslides, and, in the future, to manage the risk of debris flow in the watershed.     

河北省顺平县李思庄滑坡稳定性分析

李思庄滑坡为河北省顺平县境内潜在危险性最大的一残坡积堆积层滑坡,近年由于削坡建房,滑坡稳定性降低,极端降雨条件下存在复活可能。在野外调查确定滑坡结构特征的基础上,采用改进Mein-Larson降雨入渗模型分析不同降雨强度及持时对李思庄滑坡安全系数影响,运用有限差分软件FLAC3D计算分析该滑坡在天然和极端降雨工况下的稳定状态。研究结果表明:天然状态下,边坡潜在滑移面为基岩与残坡积层分界面,边坡安全系数为1.18,未发生失稳破坏;随降雨历时增加,潜在滑移面由基岩与残坡积层分界面转移到湿润峰面,当湿润峰达到基岩与残坡积层分界面,边坡安全系数为0.83,属不稳定状态。并对李思庄滑坡初步提出设置挡土墙和截排水沟的治理建议。      

舟曲泄流坡滑坡变形特征及其形成机理

以甘肃舟曲泄流坡滑坡的野外详细调查和变形监测资料为基础,探讨泄流坡滑坡蠕滑变形特征和形成机理。研究表明,舟曲泄流坡滑坡发育于坪定—化马断裂内,属典型的巨型断裂带滑坡。该滑坡由多个次级滑坡组成,表现为蠕滑变形特点,且一直处于不稳定状态。该滑坡是在内外动力耦合作用下形成的,断裂破碎带是泄流坡滑坡发生的充分条件,断裂活动导致坡体发生塑性流动变形;而降雨是滑坡发生大规模下滑的主要诱发因素;地震、坡脚开挖等对滑坡的发展、演化起到促进作用。因此,进一步研究断裂带滑坡的形成机理和成灾模式,对此类滑坡的防治预警有重要意义。