A geotechnical investigation of the retrogressive Yaka Landslide and the debris flow threatening the town of Yaka (Isparta,SW Turkey)

In this study the factors affecting the retrogressive Yaka Landslide, its mechanism and the hazard of debris flow on the town of Yaka are investigated. In the landslide area, the first landslide was small and occurred in March 2006 on the lower part of the Alaard?ç Slope near the Gelendost District town of Yaka (Isparta, SW Turkey). The second, the Yaka Landslide, was large and occurred on 19 February 2007 in the soil-like marl on the central part of Alaard?ç Slope. The geometry of the failure surface was circular and the depth of the failure surface was about 3 m. Following the landslide, a 85,800 m³ of displaced material transformed to a debris flow. Then, the debris flow moved down the Eglence Valley, traveling a total distance of about 750 m. The town of Yaka is located 1,600 m downstream of Eglence Creek and hence poses a considerable risk of debris flow, should the creek be temporarily dammed as a result of further mass movement. Material from the debris accumulation has been deposited on the base of Eglence Valley and has formed a debris-dam lake behind a debris dam. Trees, agricultural areas, and weirs in the Eglence Creek have seen serious damage resulting from the debris flow. The slope angle, slope aspect and elevation of the area in this study were generated using a GIS-based digital elevation model (DEM). The stability of the Alaard?ç Slope was assessed using limit equilibrium analysis with undrained peak and residual shear strength parameters. In the stability analyses, laboratory test results performed on the soil-like marls were used. It was determined that the Alaard?ç Slope is found to be stable under dry conditions and unstable under completely saturated conditions. The Alaard?ç Slope and its vicinity is a paleolandslide area, and there the factor of safety for sliding was found to be about 1.0 under saturated conditions. The Alaard?ç Slope and the deposited earthen materials in Eglence Creek could easily be triggered into movement by any factors or combination of factors, such as prolonged or heavy rainfall, snowmelt or an earthquake. It was established that the depth of the debris flow initiated on the Yaka Landslide reached up to 8 m in Eglence Creek at the point it is 20 m wide. If this deposited material in Eglence Creek is set into motion, the canal that passes through Yaka, with its respective width and depth of 7 and 1.45 m, could not possibly discharge the flow. The destruction or spillover of this canal in Yaka could bring catastrophic loss to residents which are located within 3–5 m of the bank of the canal. Furthermore, if material present in the landslide source area slides and this displaced material puts pressure on the unstable deposited material in Eglence Creek, even more catastrophic loss would occur to the town of Yaka. In this study, it was determined that debris flows are still a major hazard to Yaka and its population of 3,000. The results provided in this study could help citizens, planners, and engineers to reduce losses caused by existing and future landslides and debris flow in rainfall and snowmelt conditions by means of prevention and mitigation.     

Landslide hazards triggered by the 2008 Wenchuan earthquake, Sichuan, China

The 2008 Wenchuan earthquake (M _s = 8.0; epicenter located at 31.0° N, 103.4° E), with a focal depth of 19.0 km was triggered by the reactivation of the Longmenshan fault in Wenchuan County, Sichuan Province, China on 12 May 2008. This earthquake directly caused more than 15,000 geohazards in the form of landslides, rockfalls, and debris flows which resulted in about 20,000 deaths. It also caused more than 10,000 potential geohazard sites, especially for rockfalls, reflecting the susceptibility of high and steep slopes in mountainous areas affected by the earthquake. Landslide occurrence on mountain ridges and peaks indicated that seismic shaking was amplified by mountainous topography. Thirty-three of the high-risk landslide lakes with landslide dam heights greater than 10 m were classified into four levels: extremely high risk, high risk, medium risk, and low risk. The levels were created by comprehensively analyzing the capacity of landslide lakes, the height of landslide dams, and the composition and structure of materials that blocked rivers. In the epicenter area which was 300 km long and 10 km wide along the main seismic fault, there were lots of landslides triggered by the earthquake, and these landslides have a common characteristic of a discontinuous but flat sliding surface. The failure surfaces can be classified into the following three types based on their overall shape: concave, convex, and terraced. Field evidences illustrated that the vertical component of ground shaking had a significant effect on both building collapse and landslide generation. The ground motion records show that the vertical acceleration is greater than the horizontal, and the acceleration must be larger than 1.0 g in some parts along the main seismic fault. Two landslides are discussed as high speed and long runout cases. One is the Chengxi landslide in Beichuan County, and the other is the Donghekou landslide in Qingchuan County. In each case, the runout process and its impact on people and property were analyzed. The Chengxi landslide killed 1,600 people and destroyed numerous houses. The Donghekou landslide is a complex landslide–debris flow with a long runout. The debris flow scoured the bank of the Qingjiang River for a length of 2,400 m and subsequently formed a landslide dam. This landslide buried seven villages and killed more than 400 people.     

西藏帕里河2004-06-22滑坡卫星监测

2004-06-22滑坡位于我国西藏自治区的最西端,中印边界附近的帕里河流域中部。以多时相高分辨率卫星图像为信息源,以Orbview立体像对制作的高精度DEM为地理控制,采用数字滑坡技术研究和监测该滑坡自滑坡前至2007年7月的活动。遥感解译表明,滑坡前该处为由弧形裂缝与山体分割的滑前危岩,2004-06-22发生的堵河事件为一高速顺层基岩滑坡,基于RS+GIS求得滑坡体积为63。7万m3。遥感监测显示自2004年9月至2007年7月共35个月内,滑坡边界及滑面各细部均没有明显变化,期间该处未见发生过任何新的滑坡活动。该滑坡是一次在新构造活动强烈的高山峡谷区自然形成的重力侵蚀活动过程,能量释放充分,近期除原滑体四周有一些泄荷及调整活动外不会有大的活动。     

Description of dynamics of the Tuzla Landslide and its implications for further landslides in the northern slope and shelf of the Cinarcik Basin (Marmara Sea, Turkey)

Seismic and multi-beam bathymetric data from the northern shelf and slope of the Cinarcik Basin, which is generated by the North Anatolian Fault Zone (NAFZ) located in the easternmost basin in the Marmara Sea, were re-interpreted to better understand the future sub-marine landslide susceptibility. Seismic data indicate that upper surface of the sub-marine extension of the Paleozoic rocks has an NNE–SSW oriented basin and a ridge type morphology controlled by the secondary faults of the NAFZ. Basins are fulfilled by Plio-Quaternary sediments, which are cut by strike-slip faults on the shelf and slope. The thickness of basin deposits reaches up to 130 m toward the linear northern slope of the Cinarcik Basin. A relatively recent sub-marine landslide, the Tuzla Landslide, cuts the slope of the Cinarcik Basin. The detailed morphological investigation indicates that the Tuzla Landslide is a deep-seated rotational landslide, which was likely triggered by activity of the NAFZ. Morphological analyses also indicate that the thick Plio-Quaternary deposits on the Paleozoic basement slid during the Tuzla Landslide event. This landslide is considered as a key event to understand the dynamics of the potential landslides on the northern shelf and slope of the Cinarcik Basin. Two areas locating on the eastern and the western sides of the Tuzla Landslide are considered as the potential areas for future sliding due to similarities of geological and geomorphological features with the Tuzla Landslide such as similar thick Plio-Quaternary deposits, similar slope morphology, and similar fault activity cutting the sediments. Considering this information, the purposes of the present study are to determine the dynamics of the possible landslide areas and to discuss their effects on the sub-marine morphology. In the light of the interpretations, the amounts of possible displaced material are obtained. Three different landslide scenarios due to possible slide surfaces for future landslides are developed and assessed. The first scenario is sliding of the sediments at the shelf break. The third scenario is a mass movement of almost whole basin deposits on the Paleozoic rocks. The latter one is evaluated as less important because of the volume of the displaced material, and the latter one is accepted as lowest possible event. Among the scenarios, the second scenario is accepted as the most critical and possible because of the amount of the slipped material and existence of faults rupture, which is considered as further sliding surfaces. These landslides will result in important changes in shelf, slope and basin floor in the study area.     

The Todagin Creek landslide of October 3, 2006, Northwest British Columbia, Canada

The Todagin Creek landslide is located at 57.61° N 129.98° W in Northwest British Columbia. A seismic station 90 km north of the landslide recorded the event at 1643 hours coordinated universal time (UTC; 0943 hours Pacific daylight time (PDT)) on October 3, 2006. The signal verifies the discovery and relative time bounds provided by a hunting party in the valley. The landslide initiated as a translational rock slide on sedimentary rock dipping down slope at 34° and striking parallel to the valley. The landslide transformed into a debris avalanche and had a total volume estimated at 4 Mm³. An elevation drop of 771 m along a planar length of 1,885 m resulted in a travel angle (fahrb?schung) of 21.3°. The narrowest part of the landslide through the transport zone is 345 m. The widest part of the divergent toe of the landslide reaches a width of 1,010 m. Landslide debris impounded a lake of approximately 32 ha and destroyed an additional 67 ha of forest. The impoundment took 7 to 10 days to fill, with muddied waters observed downstream on October 13. No clear linkage exists with precipitation and temperature records preceding the landslide, but strong diurnal temperature cycles occurred in the days prior to the event. The Todagin Creek area appears to have an affinity for large landslides with the deposits of three other landslides >5 Mm³ observed in the valley.     

Topographical features of rainfall-triggered landslides in Mon State,Myanmar, August 2019: spatial distribution heterogeneity and uncommon large relative heights

Continuous 5-day (August 4–9, 2019) torrential rainfall in the monsoon season triggered more than 90 landslides on northwest-southeast extended mountain range of Mon State, Myanmar. In this study, remote sensing images, DEM, and limited fieldworks were used to create the landslide inventory. The topography features of these landslides are analyzed via ArcGIS. The largest one occurred on 9 August 2019 and caused 75 deaths and 27 buildings were damaged. This landslide occurred on gentle topography (slope angle, 23°) with long run-out, in which the angle of reach was relatively low (10°). The volume was 111,878 m³ was mainly composed of weathered granite and red soil and the sliding depth was approximately 7.5 m. Topographic characteristics including the relative slope height, angle of reach, and slope angle of source area of 35 landslides with areas?>?4000 m² were analyzed. The spatial distribution characteristics and topographic features of the 35 landslides below are distinguished: (1) the concentration of most of landslides on southwest-facing slopes showing the heterogeneous spatial distribution of landslide; (2) an uncommon landslide distribution in which more than half of landslide originates from upper slope; (3) the range of the angle of the source area (17°–38°) compatible with the internal friction angle of soils in tropical regions (17°–33°); and (4) the tangent of the angle of reach is generally smaller than 0.5 (angle of reach?<?27°) shows a relative high mobility and the relation between landslide mobility and the slope angle of the landslide source area is similar to the one of earthquake-triggered landslides, even though the triggering mechanism, landslide type, and landslide volume are dramatically different.

     

数字滑坡技术及其应用

“数字滑坡”技术,就是以遥感（RS）和空间定位方法为主,结合其他勘探、试验、调查手段获取数字形式的、与地理坐标配准的滑坡基本信息;并利用GIS技术存贮和管理这些数字信息;在此基础上,根据滑坡地学原理进行空间分析,研制各类模型,并服务于滑坡调查、监测、研究、滑坡灾害评价、危险预测、灾情评估、滑坡防治等。通过金龙山三维数字模型,卫星监测易贡滑坡、三峡库区重点城镇滑坡及千将坪滑坡等地的遥感调查说明数字滑坡技术的实际应用。     

Data Mining for Landslide Genetic Mechanism Analysis in the Yunnan Province of China

Landslide susceptibility analysis based on the strong ability of data mining of Geographic Information System (GIS) has become a hot topic in international landslide research. This paper used optimized decision tree and GIS databases to analyze the sensitivity in the northwest mountain areas of Yunnan province of China, and then discussed the formation mechanism of the landslide happened in the area. The translational landslide located in the area with an average gradient less than or equal to 28.7° was reclassified as a higher level 3 sensitive area than before according to the normalized different fault index (NDFI). The results showed that the data mining based on GIS 3D space–time information database can help to find the unique topography, geology hydrology and the other typical spatial information of some special typed of landslides such as translational landslides, thus it can illustrate the relationship between the landslides and their sensitivity factors. The improved landslide susceptibility analysis will provide a new method for identifying the genetic mechanism of landslide, and play an important role in the government regional planning and disaster prevention measures.

     

Landslide dam formation susceptibility analysis based on geomorphic features

Global climate change has increased the frequency of abnormally high rainfall; such high rainfall events in recent years have occurred in the mountainous areas of Taiwan. This study identifies historical earthquake- and typhoon-induced landslide dam formations in Taiwan along with the geomorphic characteristics of the landslides. Two separate groups of landslides are examined which are classified as those that were dammed by river water and those that were not. Our methodology applies spatial analysis using geographic information system (GIS) and models the geomorphic features with 20?×?20 m digital terrain mapping. The Spot 6 satellite images after Typhoon Morakot were used for an interpretation of the landslide areas. The multivariate statistical analysis is also used to find which major factors contribute to the formation of a landslide dam. The objective is to identify the possible locations of landslide dams by the geomorphic features of landslide-prone slopes. The selected nine geomorphic features include landslide area, slope, aspect, length, width, elevation change, runout distance, average landslide elevation, and river width. Our four geomorphic indexes include stream power, form factor, topographic wetness, and elevation–relief ratio. The features of the 28 river-damming landslides and of the 59 non-damming landslides are used for multivariate statistical analysis by Fisher discriminant analysis and logistic regression analysis. The principal component analysis screened out eleven major geomorphic features for landslide area, slope, aspect, elevation change, length, width, runout distance, average elevation, form factor, river width, stream power, and topography wetness. Results show that the correctness by Fisher discriminant analysis was 68.0 % and was 70.8 % by logistic regression analysis. This study suggests that using logistic regression analysis as the assessment model for identifying the potential location of a landslide dam is beneficial. Landslide threshold equations applying the geomorphic features of slope angle, angle of landslide elevation change, and river width (H _L/W _R) to identify the potential formation of natural dams are proposed for analysis. Disaster prevention and mitigation measures are enhanced when the locations of potential landslide dams are identified; further, in order to benefit such measures, dam volume estimates responsible for breaches are key.     

Impact of the Trans-Himalayan Landslide Lake Outburst Flood (LLOF) in the Satluj catchment, Himachal Pradesh, India

Landslide Lake Outburst Floods (LLOFs) are common in the Himalayan river basins. These are caused by breaching of lakes created by landslides. The active and palaeo-landslide mapping along the Satluj and Spiti Rivers indicate that these rivers were blocked and breached at many places during the Quaternary period. In the present article, we document LLOFs during 2000 and 2005 caused by the breaching of landslide lakes created in the Trans-Himalayan region along the Satluj River and Paree Chu (stream), respectively, both in the Tibetan region of China and its impact on the channel and infrastructure in the Kinnaur district of Himachal Pradesh, India. It has been observed that the loss of life and property due to these LLOFs is directly related to the disposition of the Quaternary materials and the different morphological zones observed in the area.     

Landslide risk assessment using concepts of danger pixels and fuzzy set theory in Darjeeling Himalayas

Landslide risk assessment (LRA) is a key component of landslide studies. The landslide risk can be defined as the potential for adverse consequences or loss to human population and property due to the occurrence of landslides. The LRA can be regional or site-specific in nature and is an important information for planning various developmental activities in the area. LRA is considered as a function of landslide potential (LP) and resource damage potential (RDP). The LP and RDP are typically characterized by the landslide susceptibility zonation map and the resource map (i.e., land use land cover map) of the area, respectively. Development of approaches for LRA has always been a challenge. In the present study, two approaches for LRA, one based on the concept of danger pixels and the other based on fuzzy set theory, have been developed and implemented to generate LRA maps of Darjeeling Himalayas, India. The LRA map based on the first approach indicates that 1,015 pixels of habitation and 921 pixels of road section are under risk due to landslides. The LRA map derived from fuzzy set theory based approach shows that a part of habitat area (2,496 pixels) is under very high risk due to landslides. Also, another part of habitat area and a portion of road network (7,204 pixels) are under high risk due to landslides. Thus, LRA map based on the concept of danger pixels gives the pixels under different resource categories at risk due to landslides whereas the LRA map based on the concept of fuzzy set theory further refines this result by defining the degree of severity of risk to these categories by putting these into high and low risk zones. Hence, the landslide risk assessment study carried out using two approaches in this paper can be considered in cohesion for assessing the risks due to landslides in a region.     

Deterministic Landslide Risk Assessment at a Past Landslide Site

The slope failure and landslide hazard will possess the same properties within a range including the same engineering geological conditions. To assess the landslide risk of a mountainous area, the study of landslides previously having occurred is very important to evaluate the landslide risk around the area in which they took place. Based on the study of the mechanism of a previous landslide recorded in Kumamoto, Japan, this study initially proposes mechanical parameters for evaluating the landslide hazard using a 3D slope stability method. For each slope unit in the study area, the critical slip surface, which reveals the minimum safety factor of a slope, can be obtained. The affected streams and range of possible landslide masses are analyzed based on the debris flow simulation. This is initially applied to simulate the past landslide event and the result shows the landslide-deduced debris flow effectively re-displayed. Overlayered with layers of infrastructure in Geographic Information Systems (GIS), this risk map indicates which houses and road sections remain in dangerous areas.     

新疆伊犁某移民新区黄土滑坡成因分析及防治对策

移民新区东坡滑坡发育于小吉尔格朗河东岸二级残留阶地,坡面中部,坡体平均坡度35°,均为小型土质滑坡。因滑坡剪出口位置较高,滑动后,多为快速滑动,极易成灾,对沙尕村移民新区构成较大威胁。通过研究发现,滑坡主要受地形地貌、地层岩性、地质构造等原生地质条件控制,受大气降水、地下水、地震、人类工程活动等外界条件影响,其中大气降水和地下水为滑坡成因的主要影响因素。结合滑坡成因及影响因素,提出抗滑桩板墙和挡土墙相结合并辅以排水措施的防治方案,对该地区的滑坡防治具有较好的指导意义。     

Landslide Research at the British Geological Survey:Capture,Storage and Interpretation on a National and Site-Specific Scale

Abstract: Landslide research at the British Geological Survey (BGS) is carried out through a number of activities, including surveying, database development and real-time monitoring of landslides. Landslide mapping across the UK has been carried out since BGS started geological mapping in 1835. Today, BGS geologists use a combination of remote sensing and ground-based investigations to survey landslides. The development of waterproof tablet computers (BGS·SIGMAmobile), with inbuilt GPS and GIS for field data capture provides an accurate and rapid mapping methodology for field surveys. Regional and national mapping of landslides is carried out in conjunction with site-specific monitoring, using terrestrial LiDAR and differential GPS technologies, which BGS has successfully developed for this application. In addition to surface monitoring, BGS is currently developing geophysical ground-imaging systems for landslide monitoring, which provide real-time information on subsurface changes prior to failure events. BGS’s mapping and monitoring activities directly feed into the BGS National Landslide Database, the most extensive source of information on landslides in Great Britain. It currently holds over 14?000 records of landslide events. By combining BGS’s corporate datasets with expert knowledge, BGS has developed a landslide hazard assessment tool, GeoSure, which provides information on the relative landslide hazard susceptibility at national scale.     

Landslide Susceptibility Zoning North of Yenice (NW Turkey) by Multivariate Statistical Techniques

Dramatic effects resulting from landslides on human life and economy of many nations are observed sometimes throughout the world. Landslide inventory and susceptibility mapping studies are accepted as the first stage of landslide hazard mitigation efforts. Generally, these landslide inventory studies include identification and location of landslides. The main benefit is to provide a basis for statistical susceptibility zoning studies. In the present study, a landslide susceptibility zoning near Yenice (NW Turkey) is carried out using the factor analysis approach. The study area is approximately 64 km² and 57 landslides were identified in this area. The area is covered completely by Ulus Formation that has a flysh-like character. Slope angle, elevation, slope aspect, land-use, weathering depth and water conditions were considered as the main conditioning factors while the heavy precipitation is the main trigger for landsliding. According to the results of factor analysis, the importance weights for slope angle, land-use, elevation, dip direction, water conditions and weathering depth were determined as 45.2%, 22.4%, 12.5%, 8.8%, 8.1% and 3.0% respectively. Also, using these weights and the membership values of each conditioning factor, the membership value for landslide susceptibility was introduced. In the study area, the lowest membership value for landslide susceptibility was calculated as 0.20. Consequently, combining all results, a landslide susceptibility map was obtained. Compared with the obtained map, a great majority of the landslides (86 %) identified in the field were found to be located in susceptible and highly susceptible zones.     

Landslide identification using machine learning

Landslide identification is critical for risk assessment and mitigation.This paper proposes a novel machinelearning and deep-learning method to identify natural-terrain landslides using integrated geodatabases.First,landslide-related data are compiled,including topographic data,geological data and rainfall-related data.Then,three integrated geodatabases are established;namely,Recent Landslide Database(Rec LD),Relict Landslide Database(Rel LD)and Joint Landslide Database(JLD).After that,five machine learning and deep learning algorithms,including logistic regression(LR),support vector machine(SVM),random forest(RF),boosting methods and convolutional neural network(CNN),are utilized and evaluated on each database.A case study in Lantau,Hong Kong,is conducted to demonstrate the application of the proposed method.From the results of the case study,CNN achieves an identification accuracy of 92.5%on Rec LD,and outperforms other algorithms due to its strengths in feature extraction and multi dimensional data processing.Boosting methods come second in terms of accuracy,followed by RF,LR and SVM.By using machine learning and deep learning techniques,the proposed landslide identification method shows outstanding robustness and great potential in tackling the landslide identification problem.     

曲石湾滑坡体成因分析及防治措施研究

滑坡的形成对周围环境造成很大的影响，并严重制约地方经济发展，威胁人民生命财产安全，因此，滑坡成因及防治措施的研究具有重要意义。本文通过实际资料，分析曲石湾滑坡体的形成机理，有针对性的提出曲石湾滑坡的防治措施。     

湖北省香溪河流域白家堡滑坡稳定性分析与评价

三峡大坝建成蓄水后,将导致库岸部分古滑体复活、新滑体产生,香溪河流域白家堡滑坡就是其中之一。文章在对该滑坡的工程地质条件、深部位移及伸缩计监测资料的研究基础上,分析了滑坡变形机理,得出白家堡滑坡只有一个滑动面,其总体变形趋势为推移式,目前仍具有微小的变形。滑坡变形与降雨及库水有密切联系。结合试验资料,针对滑坡变形的实际情况,采用反演分析方法进行了滑移面抗剪强度参数的反演计算。利用反演结果,在三峡水库蓄水4种不同水位工况下进行稳定性计算。结果表明,滑坡的稳定性系数经历了大→小→大的过程。正常蓄水位时稳定性处于较低状态。滑坡体饱水处于蠕滑或失稳状态,需尽快进行治理。     

Analysis of the 2003 Varunawat Landslide,Uttarkashi, India using Earth Observation data

Mass movements such as landslides in mountainous terrains are natural degradation processes and one of the most important landscape-building factors. Varunawat Parbat overlooking Uttarkashi town witnessed a series of landslides on 23 September 2003 and the debris slides and rock falls continued for 2 weeks. This landslide complex was triggered due to the incessant rainfall prior to the event, and its occurrence led to the blockage of the pilgrim route to Gangotri (source of the Ganges river) and evacuation of thousands of people to safer places. Though there was no loss of lives due to timely evacuation, heavy losses to the property were reported. High-resolution stereoscopic earth observation data were acquired after the incidence to study the landslide in detail with emphasis on the cause of the landslide and mode of failure. Areas along the road and below the Varunawat foothill region are mapped for landslide risk. It was found that the foothill region of the Varunawat Parbat was highly disturbed by man-made activities and houses are dangerously located below steep slopes. The potential zones for landslides along with the existing active and old landslides are mapped. These areas are critical and their treatment with priority is required in order to minimise further landslide occurrences.     

Mapping of landslide hazard zonation using GIS at Golestan watershed, northeast of Iran

Landslide hazard zonation is essential for planning future developmental activities. At the present study, after the preparation of a landslide inventory of the study area, nine factors as well as sub-data layers of factor class weights were tested for an integrated analysis of landslide hazard in the region. The produced factor maps were weighted with the analytic hierarchy process method and then classified into four classes—negligible, low, moderate, and high. The final produced map for landslide hazard zonation in Golestan watershed revealed that: (1) about 53.85 % of the basin is prone to moderate and high threats of landslides. (2) Landslide events at the Golestan watershed were strongly correlated to the slope angle of the basin. It was observed that the active landslide zones, including moderate to high landslide hazard classes, have a high correlation to slope classes over 30° (R ²?=?0.769). (3) The regions most susceptible to landslide hazard are those located south and southwest of the watershed, which included rock topples, falls, and debris landslides.