Statistical analysis of landslides caused by the Mw 6.9 Yushu,China, earthquake of April 14, 2010

The April 14, 2010 Yushu, China, earthquake (Mw 6.9) triggered a great number of landslides. At least 2,036 co-seismic landslides, with a total coverage area of 1.194 km², were delineated by visual interpretation of aerial photographs and satellite images taken following the earthquake, and verified by field inspection. Based on the mapping results, a statistical analysis of the spatial distribution of these landslides is performed using the landslide area percentage (LAP), defined as the percentage of the area affected by the landslides, and landslide number density (LND), defined as the number of landslides per square kilometer. The purpose is to clarify how the landslides correlate the control factors, which are the elevation, slope angle, slope aspect, slope position, distance from drainages, lithology, distance from the surface rupture, and peak ground acceleration (PGA). The results show that both LAP and LND have strongly positive correlations with slope angle and negative correlations with distance from the surface rupture and distance from drainages. The highest LAP and LPD values are in places of elevations from 3,800 to 4,000 m. The slopes producing landslides are mostly facing toward NE, E, and SE. The geological units of Q₄ al-pl, N, and T₃ kn ¹ have the highest concentrations of co-seismic landslides. No apparent correlations are present between LAP and LND values and PGA. On both sides of the surface rupture, the landslide distributions are almost similar except a few exceptions, likely associated with the nature of the strike-slip seismogenic fault for this event. The bivariate statistical analysis shows that, in descending order, the earthquake-triggered landslide impact factors are distance from surface rupture > slope angle > distance from drainages > lithology > PGA. Besides, as the detailed co-seismic landslides inventories related to strike-slip earthquakes are still few compared with that of thrusting-fault earthquakes, this case study would shed new light on the subject. For instance, the landslide spatial distribution on both sides of the strike-slip seismogenic fault is rather different from that of thrusting-fault earthquakes. It reminds us to take different strategies of measures for prevention and mitigation of landslides induced by earthquakes with different mechanisms.     

Susceptibility assessments of the Wenchuan earthquake-triggered landslides in Longnan using logistic regression

In this study a Wenchuan earthquake-induced landslide susceptibility assessment was carried out in the Longnan area in northwestern China using a GIS-based logistic regression model. This region has frequently been affected by landslides in the past, and was intensively affected by the 5.12 Wenchuan earthquake which received considerable international attention. The data used for this study consist of the landslides triggered by the Wenchuan earthquake and a landslide pre-disposing factor database. Information regarding the landslide causative factors came from additional data sources, such as a digital elevation model (DEM) with a 30 × 30 m² resolution, orthophotos, geological and land-use maps, precipitation records, and information on peak ground acceleration data from the 2008 earthquake. The statistical analysis of the relationship between the Wenchuan earthquake-triggered landslides and pre-disposing factors showed the great influence of lithological and topographical conditions on slope failures. The quality of susceptibility mapping was validated by splitting the study area into training and validation sections. The prediction capability analysis demonstrated that the landslide susceptibility map could be used for land planning as well as emergency planning by local authorities.     

Landslides triggered by slipping-fault-generated earthquake on a plateau: an example of the 14 April 2010, Ms 7.1, Yushu, China earthquake

On 14 April 2010 at 07:49 (Beijing time), a catastrophic earthquake with Ms 7.1 struck Yushu County, Qinghai Province, China. A total of 2,036 landslides were interpreted from aerial photographs and satellite images, verified by selected field checking. These landslides cover about a total area of 1.194 km². The characteristics and failure mechanisms of these landslides are presented in this paper. The spatial distribution of the landslides is evidently strongly controlled by the locations of the main co-seismic surface fault ruptures. The landslides commonly occurred close together. Most of the landslides are small; there were only 275 individual landslide (13.5 % of the total number) surface areas larger than 1,000 m². The landslides are of various types. They are mainly shallow, disrupted landslides, but also include rock falls, deep-seated landslides, liquefaction-induced landslides, and compound landslides. Four types of factors are identified as contributing to failure along with the strong ground shaking: natural excavation of the toes of slopes, which mean erosion of the base of the slope, surface water infiltration into slopes, co-seismic fault slipping at landslide sites, and delayed occurrence of landslides due to snow melt or rainfall infiltration at sites where slopes were weakened by the co-seismic ground shaking. To analyze the spatial distribution of the landslides, the landslide area percentage (LAP) and landslide number density (LND) were compared with peak ground acceleration (PGA), distance from co-seismic main surface fault ruptures, elevation, slope gradient, slope aspect, and lithology. The results show landslide occurrence is strongly controlled by proximity to the main surface fault ruptures, with most landslides occurring within 2.5 km of such ruptures. There is no evident correlation between landslide occurrences and PGA. Both LAP and LND have strongly positive correlations with slope gradient, and additionally, sites at elevations between 3,800 and 4,000 m are relatively susceptible to landslide occurrence; as are slopes with northeast, east, and southeast slope aspects. Q₄ al-pl, N, and T₃ kn ¹ have more concentrated landslide activity than others. This paper provides a detailed inventory map of landslides triggered by the 2010 Yushu earthquake for future seismic landslide hazard analysis and also provides a study case of characteristics, failure mechanisms, and spatial distribution of landslides triggered by slipping-fault generated earthquake on a plateau.     

Pre-conditioning factors and susceptibility assessments of Wenchuan earthquake landslide at the Zhouqu segment of Bailongjiang basin, China

In this study, we present a landslide susceptibility assessment carried out after the devastating 2008 Wenchuan earthquake. For the Zhouqu segment in the Bailongjiang basin in north-western China landslide susceptibility was computed by a logistic regression method. This region has been experiencing landslides for a long time, and numerous additional slope failures were triggered by the 2008 Wenchuan earthquake. The data used for this study consists of slope failures attributed to the 2008 earthquake, the 878 post Wenchuan earthquake landslides and collapses inventory build up by combination the field investigation, monoscopic manual interpretation, image classification and texture analysis using SPOT 5 and ALOS remote-sensing image data. All data derived from remote sensing images are validated during field investigations. The landslide pre-disposing factor database was constructed. A digital elevation model (DEM) with a 30 × 30 m resolution, orthophotos, geological and land-use maps and information on peak ground acceleration data from the 2008 earthquake is used. The statistical analysis of the relation between Wencuan earthquake-triggered landslides and pre-disposing factors show the great influence of lithological and topographical conditions for earthquake-triggered slope failures. The quality of susceptibility mapping was validated by splitting the study area into a training and validation set. The prediction capability analysis showed that the landslide susceptibility map could be used for land planning as well as emergency planning by local authorities in this region.     

Landslides triggered by the 2016 Mj 7.3 Kumamoto,Japan, earthquake

The aim of this study is to establish a detailed and complete inventory of the landslides triggered by the Mj 7.3 (Mw 7.0) Kumamoto, Japan, earthquake sequence of 15 April 2016 (16 April in JST). Based on high-resolution (0.5–2 m) optical satellite images, we delineated 3,467 individual landslides triggered by the earthquake, occupying an area of about 6.9 km². Then they were validated by aerial photographs with very high-resolution (better than 0.5 m) and oblique field photos. Of them, 3,460 landslides are distributed in an elliptical area about 6000 km², with a NE-SW directed 120-km-long long axis and a 60-km-long NW-SE trending short axis. Most of the landslides are shallow, disrupted falls and slides, with a few flow-type slides and rock and soil avalanches. The analysis of correlation between the landslides and several control factors shows the areas of elevation 1000–1200 m, stratum of Q₃-Hvf, seismic intensity VIII and VIII+, and peak ground acceleration (PGA) 0.4–0.6 g register the highest landslide abundance. This study also discussed the relationship between the spatial pattern of the landslides and the seismotectonic structure featured by a strike-slip fault with a normal component and the volcanism in the study area.     

Spatial distribution analysis and susceptibility mapping of landslides triggered before and after Mw7.8 Gorkha earthquake along Upper Bhote Koshi,Nepal

The 2015 Mw7.8 Gorkha earthquake triggered thousands of landslides of various types scattered over a large area. In the current study, we utilized pre- and post-earthquake high-resolution satellite imagery to compile two landslide inventories before and after earthquake and prepared three landslide susceptibility maps within 404 km² area using frequency ratio (FR) model. From the study, we could map about 519 landslides including 178 pre-earthquake slides and 341 coseismic slides were identified. This study investigated the relationship between landslide occurrence and landslide causative factors, i.e., slope, aspect, altitude, plan curvature, lithology, land use, distance from streams, distance from road, distance from faults, and peak ground acceleration. The analysis showed that the majority of landslides both pre-earthquake and coseismic occurred at slope >30°, preferably in S, SE, and SW directions and within altitude ranging from 1000 to 1500 m and 1500 to 3500 m. Scatter plots between number of landslides per km^?2 (LN) and percentage of landslide area (LA) and causative factors indicate that slope is the most influencing factor followed by lithology and PGA for the landslide formation. Higher landslide susceptibility before earthquake is observed along the road and rivers, whereas landslides after earthquake are triggered at steeper slopes and at higher altitudes. Combined susceptibility map indicates the effect of topography, geology, and land cover in the triggering of landslides in the entire basin. The resultant landslide susceptibility maps are verified through AUC showing success rates of 78, 81, and 77%, respectively. These susceptibility maps are helpful for engineers and planners for future development work in the landslide prone area.     

1920年海原8.5级地震高烈度区滑坡编录与分布规律

发生在黄土高原的1920年12月16日的海原M_S8.5级大地震触发了大量的滑坡,这些滑坡直接造成了大量的人员伤亡。近年来,出现了一些关于本次地震触发滑坡的专题研究,然而,这些研究多是基于局部震区或者个别单体滑坡进行,极少有关于该地震触发滑坡详细全面的成果出现。这种情况已经成为了深入理解海原地震触发滑坡的规模与程度、发育规律等的障碍。本研究拟基于谷歌地球平台,采用人工目视解译方法,以海原地震高烈度区（Ⅸ~Ⅺ）为研究区,开展地震滑坡解译工作,并分析这些滑坡的分布规律与影响因子之间的关系。结果表明本次地震在Ⅸ~Ⅺ度区内触发了至少5384处滑坡,滑坡总面积为218.78 km2。滑坡密度最高的区域为Ⅸ烈度圈的北西部分。通过分析这些滑坡与地形、地震、地质等因子的关系发现,高程1700~2000 m为滑坡的高发与高易发区间;大多数滑坡集中发育在坡度15°~25°范围内,滑坡密度随着坡度的增加而显著增加;坡位越低,也就是距离河流越近,滑坡密度越大;新生代地层、尤其是第四系黄土覆盖地区是海原地震滑坡发生的主要区域,也是高易发区域。本文为探索黄土地区地震滑坡发育规律、减轻黄土地震滑坡灾害等提供了科学参考。     

Characteristics and numerical runout modeling of the heavy rainfall-induced catastrophic landslide–debris flow at Sanxicun,Dujiangyan, China,following the Wenchuan Ms 8.0 earthquake

The 2008 Ms 8.0 Wenchuan earthquake triggered a large number of extensive landslides. It also affected geologic properties of the mountains such that large-scale landslides followed the earthquake, resulting in the formation of a disaster chain. On 10 July 2013, a catastrophic landslide–debris flow suddenly occurred in the Dujiangyan area of Sichuan Province in southeast China. This caused the deaths of 166 people and the burying or damage of 11 buildings along the runout path. The landslide involved the failure of ≈1.47 million m³, and the displaced material from the source area was ≈0.3 million m³. This landslide displayed shear failure at a high level under the effects of a rainstorm, which impacted and scraped an accumulated layer underneath and a heavily weathered rock layer during the release of potential and kinetic energies. The landslide body entrained a large volume of surface residual diluvial soil, and then moved downstream along a gully to produce a debris flow disaster. This was determined to be a typical landslide–debris flow disaster type. The runout of displaced material had a horizontal extent of 1200 m and a vertical extent of 400 m. This was equivalent to the angle of reach (fahrböschung angle) of 19° and covered an area of 0.2 km². The background and motion of the landslide are described in this study. On the basis of the above analysis, dynamic simulation software (DAN3D) and rheological models were used to simulate the runout behavior of the displaced landslide materials in order to provide information for the hazard zonation of similar types of potential landslide–debris flows in southeast China following the Wenchuan earthquake. The simulation results of the Sanxicun landslide revealed that the frictional model had the best performance for the source area, while the Voellmy model was most suitable for the scraping and accumulation areas. The simulations estimated that the motion could last for ≈70 s, with a maximum speed of 47.7 m/s.     

Landslides triggered by the 1949 Khait earthquake, Tajikistan, and associated loss of life

Earthquake-triggered landslides are a major geological hazard in Central Asia. In July 1949, the M7.4 Khait earthquake triggered many hundreds of landslides in a mountainous region near the southern limit of the Tien Shan Mountains, central Tajikistan. These landslides involved widespread rock-slope failure as well as large numbers of flowslides in loess that mantles the steep slopes of the region. In the Yasman valley hundreds of loess landslides coalesced to form a massive loess flow (est. vol. 245 Mm³) that travelled up to 20 km on a slope of only 2°. In an adjacent valley, the Khait landslide involved transformation of an earthquake-triggered rockslide into a very rapid flow by the entrainment of saturated loess into its movement. It travelled 7.41 km over a vertical distance of 1421 m with an estimated average velocity of ~30 m/s. We estimate its volume as 75 Mm³, an order of magnitude less that previously published estimates. The Khait landslide was simulated using DAN. The number of casualties due to earthquake-triggered landslides in the epicentral region was considerable. Approximately 4000 people were killed in the Yasman valley loess flow as 20 villages (kishlaks) were overwhelmed. In the Khait landslide alone we estimate ca. 800 people lost their lives when the villages of Khait and Khisorak were overrun by rapidly moving debris. Our data indicates that a total of approximately 7200 people were killed by earthquake-triggered landslides in the epicentral region of the Khait earthquake and that, in terms of loss of life, the 1949 Yasman valley loess flow was one of the most destructive landslides in recent history.     

2008年汶川地震滑坡详细编目及其空间分布规律分析

最新研究成果表明, 2008年5月12日汶川MS 8.0级地震触发了超过197000处滑坡。首先,基于GIS与遥感技术构建了汶川地震滑坡的3类编目图,分别为单体滑坡面分布数据、滑坡中心点位置和滑坡后壁点位置。构建方法为基于地震前后高分辨率遥感影像的目视解译方法,区分单体滑坡并圈定其边界,对滑坡后壁进行识别与定点,并开展了部分滑坡的野外验证工作。这些滑坡分布在一个面积大约为110000km2的区域内,滑坡总面积约为1160km2。选择一个面积约为44031km2的区域作为研究区,区内滑坡数量为196007个,滑坡面积为1150.622km2,这是最详细完整的汶川地震滑坡编录成果,也是单次地震事件触发滑坡最多的记录。其次,开展研究区内的地震滑坡空间分布规律的研究。基于滑坡面与滑坡中心点分别构建滑坡空间分布面积密度图与点密度图,结果表明:滑坡多沿着映秀北川断裂分布,多发生在断裂的上盘。滑坡的高密度区位于映秀北川同震地表破裂的南西段(映秀镇与北川县之间)的上盘区域,这一区域恰对应着逆冲分量为主的断裂上盘,表明逆冲断裂对上盘区域发生滑坡的极强烈的控制作用,而该区域正是形变最大的区域,因此说明是地震滑坡发生的强烈控制作用。基于滑坡面密度(LAP)、滑坡中心点密度(LCND)与滑坡后壁点密度(LTND)这3个衡量指标,使用统计分析方法,评价了汶川地震滑坡与地震参数、地质参数、地形参数的关系。结果表明:LAP、LCND与LTND这3个衡量指标与坡度、地震烈度与PGA存在明显的正相关关系; 与距离震中、距离映秀北川同震地表破裂存在负相关关系; 斜坡曲率越接近0,滑坡越不易发生; LAP、LCND与LTND的高值高程区间为1200～3000m; 滑坡发生的优势坡向为E、SE、S方向; 滑坡发育的易发岩性为砂岩与粉砂岩(Z)、花岗岩; 滑坡与坡位的相关关系不太明显。统计结果还表明LCND与LTND两个衡量指标的差异对地震与地质因子不敏感,而对地形因子较敏感。最后将本文的统计结果与以往的汶川地震滑坡空间分布规律统计成果进行了一些对比,对比结果表明,对于某些因子,如高程、岩性、距离震中、距离映秀北川断裂的统计分析结果,采用不完整的滑坡分布数据或点数据,与采用较完整的滑坡分布面数据会有一定的差异,这种差异并未出现在针对坡度与坡向等因子的统计对比结果中。总之,作者认为一个完备、详细的地震滑坡分布面要素编目图是地震滑坡空间分布规律定量分析、危险性定量分析与滑坡控制的地震区地貌演化研究的重要基础,否则,与实际情况相比,得到统计结果会有一定的偏差,本文的研究成果与以往成果的对比结果证明了这一点。     

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.

     

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.     

The 2010 Yushu earthquake triggered landslide hazard mapping using GIS and weight of evidence modeling

The Yushu County, Qinghai Province, China, April 14, 2010, earthquake triggered thousands of landslides in a zone between 96°20′32.9″E and 97°10′8.9″E, and 32°52′6.7″N and 33°19′47.9″N. This study examines the use of geographic information system (GIS) technology and Bayesian statistics in creating a suitable landslide hazard-zone map of good predictive power. A total of 2,036 landslides were interpreted from high-resolution aerial photographs and multi-source satellite images pre- and post-earthquake, and verified by selected field checking before a final landslide-inventory map of the study area could be established using GIS software. The 2,036 landslides were randomly partitioned into two subsets: a training dataset, which contains 80 % (1,628 landslides), for training the model; and a testing dataset 20 % (408 landslides). Twelve earthquake triggered landslide associated controlling parameters, such as elevation, slope gradient, slope aspect, slope curvature, topographic position, distance from main surface ruptures, peak ground acceleration, distance from roads, normalized difference vegetation index, distance from drainages, lithology, and distance from all faults were obtained from variety of data sources. Landslide hazard indices were calculated using the weight of evidence model. The landslide hazard map was compared with training data and testing data to obtain the success rate and predictive rate of the model, respectively. The validation results showed satisfactory agreement between the hazard map and the existing landslide distribution data. The success rate is 80.607 %, and the predictive rate is 78.855 %. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low and very low. The landslide hazard evaluation map should be useful for environmental recovery planning and reconstruction work.     

Landslides triggered by the 22 July 2013 Minxian–Zhangxian,China, Mw 5.9 earthquake: Inventory compiling and spatial distribution analysis

On July 22, 2013, an earthquake of Ms. 6.6 occurred at the junction area of Minxian and Zhangxian counties, Gansu Province, China. This earthquake triggered many landslides of various types, dominated by small-scale soil falls, slides, and topples on loess scarps. There were also a few deep-seated landslides, large-scale soil avalanches, and fissure-developing slopes. In this paper, an inventory of landslides triggered by this event is prepared based on field investigations and visual interpretation of high-resolution satellite images. The spatial distribution of the landslides is then analyzed. The inventory indicates that at least 2330 landslides were triggered by the earthquake. A correlation statistics of the landslides with topographic, geologic, and earthquake factors is performed based on the GIS platform. The results show that the largest number of landslides and the highest landslide density are at 2400 m–2600 m of absolute elevation, and 200 m–300 m of relative elevation, respectively. The landslide density does not always increase with slope gradient as previously suggested. The slopes most prone to landslides are in S, SW, W, and NW directions. Concave slopes register higher landslide density and larger number of landslides than convex slopes. The largest number of landslides occurs on topographic position with middle slopes, whereas the highest landslide density corresponds to valleys and lower slopes. The underlying bedrocks consisting of conglomerate and sandstone of Lower Paleogene (E^b) register both the largest number and area of landslides and the highest landslide number and area density values. Correlations of landslide number and landslide density with perpendicular- and along-strike distance from the epicenter show an obvious spatial intensifying character of the co-seismic landslides. The spatial pattern of the co-seismic landslides is strongly controlled by a branch of the Lintan-Dangchang fault, which indicates the effect of seismogenic fault on co-seismic landslides. In addition, the area affected by landslides related to the earthquake is compared to the relationship of “area affected by landslides vs. earthquake magnitude” constructed based on earthquakes worldwide, and it is shown that the area affected by landslides triggered by the Minxian–Zhangxian earthquake is larger than that of almost all other events with similar magnitudes.     

Subaqueous landslide-triggered tsunami hazard for Lake Zurich,Switzerland

Subaqueous landslides can induce potentially damaging tsunamis. Tsunamis are not restricted to the marine environment, but have also been documented on lakes in Switzerland and worldwide. For Lake Zurich (central Switzerland), previous work documented multiple, assumedly earthquake-triggered landslides. However, no information about past tsunamis is available for Lake Zurich. In a back-analysis, we model tsunami scenarios as a consequence of the earthquake-triggered landslides in the past. Furthermore, on the basis of a recent map of the earthquake-triggered subaqueous landslide hazard, we present results of a tsunami hazard assessment. The subaqueous landslide progression, wave propagation and inundation are calculated with a combination of open source codes. Although no historic evidence of past tsunamis has been documented for Lake Zurich, a tsunami hazard exists. However, only earthquakes with long return periods are assumed to cause considerable tsunamis. An earthquake with an exceedance probability of 0.5% in 50 years (corresponding to an earthquake with a return period of 9975 years) is assumed to cause tsunamigenic landslides on most lateral slopes of Lake Zurich. A hypothetical tsunami for such an event would create damage especially along the shores of the central basin of Lake Zurich with estimated peak flow depths of up to ~?4.6 m. Our results suggest that for an earthquake with an exceedance probability of 10% in 50 years (i.e., mean return period of 475 years), no considerable tsunami hazard is estimated. Even for a worst-case scenario, the cities of Zurich and Rapperswil, located at the northern and southern ends of the lake, respectively, are assumed to experience very little damage. The presented first-order results of estimated wave heights and inundated zones provide valuable information on tsunami-prone areas that can be used for further investigations and mitigation measures.     

俯冲带地区压扭断裂型地震触发滑坡及其剥蚀厚度空间分布规律分析

2010年1月12日海地MW 7.0级地震触发了大量的滑坡。我们基于GIS与遥感技术构建了3类详细完备的海地地震滑坡编录图,分别为单体滑坡面分布数据,滑坡中心点位置数据与滑坡后壁点位置数据。结果表明海地地震触发了30828处滑坡,这些滑坡大致分布在一个面积为3192.85km2的区域内,滑坡覆盖面积为15.736km2。基于滑坡中心点密度(LCND)、滑坡后壁点密度(LTND)、滑坡面积百分比(LAP)与滑坡剥蚀厚度(LET)这4个衡量指标,使用统计分析方法,分析了海地地震滑坡及其剥蚀厚度与地震参数、地形参数、公路参数的关系。分析结果表明滑坡与坡度、地震动峰值加速度(PGA)存在大致的正相关关系; 与距离恩里基约芭蕉园断裂、距离水系存在大致的负相关关系; 滑坡沿着恩里基约芭蕉园断裂距离的统计结果表明,震中以西距离震中22~26km与8~12km的区域,与震中以东距离震中6~18km的区域是地震滑坡易发区域; 斜坡曲率值越接近0,也就是坡面较平的斜坡越不容易在地震条件下发生滑动; LCND、LTND、LAP与LET高值对应的高程区间为200~1200m; 滑坡发生的优势坡向为E方向; 滑坡的发生与距离震中、距离公路没有太明确的关系。     

Application of an incomplete landslide inventory, logistic regression model and its validation for landslide susceptibility mapping related to the May 12, 2008 Wenchuan earthquake of China

The main purpose of this paper is to present the use of multi-resource remote sensing data, an incomplete landslide inventory, GIS technique and logistic regression model for landslide susceptibility mapping related to the May 12, 2008 Wenchuan earthquake of China. Landslide location polygons were delineated from visual interpretation of aerial photographs, satellite images in high resolutions, and verified by selecting field investigations. Eight factors, including slope angle, slope aspect, elevation, distance from drainages, distance from roads, distance from main faults, seismic intensity and lithology were selected as controlling factors for earthquake-triggered landslide susceptibility mapping. Qualitative susceptibility analyses were carried out using the map overlaying techniques in GIS platform. The validation result showed a success rate of 82.751 % between the susceptibility probability index map and the location of the initial landslide inventory. The predictive rate of 86.930 % was obtained by comparing the additional landslide polygons and the landslide susceptibility probability index map. Both the success rate and the predictive rate show sufficient agreement between the landslide susceptibility map and the existing landslide data, and good predictive power for spatial prediction of the earthquake-triggered landslides.     

地震诱发滑坡的快速评估方法研究:以2017年MS 7.0级九寨沟地震为例

山岳地区强烈地震诱发的滑坡、崩塌等地震次生灾害在造成严重人员伤亡的同时,对社会经济的发展也构成了严重威胁。而震后滑坡分布的快速评估,尤其是滑坡重灾区的确定,则可为救援工作的科学部署和有效开展提供决策支持并减轻地震灾害的损失。2017年8月8日发生于四川省阿坝州九寨沟风景区的MS 7.0级地震诱发了大量的滑坡、崩塌灾害,造成了一定的人员伤亡和财产损失,凸显出进行震后滑坡快速评估的重要性。本文通过对九寨沟地震灾区震前、震后“北京二号”遥感影像的对比分析,解译此次地震诱发的滑坡分布概况。尽管震后影像在局部区域有云团覆盖,影响了震区滑坡解译的详尽程度,但是对于主要发生的滑坡地震高烈度地区(≥Ⅻ度),本文所用影像基本满足解译要求。本文共解译出194个面积大于700 m2的滑坡,这些滑坡主要沿地震烈度长轴方向分布,灾害体平面面积达5.6 km2,影响范围超过600 km2。通过对九寨沟地震灾区的地形、岩性及地震动加速度进行分析,本文采用Newmark刚体滑块模型对该区震后滑坡危险区域进行了预测。预测结果按照危险程度不同划分为5个级别,即高度危险、较高危险、中度危险、较低危险和低度危险。滑坡分布与评估结果呈现出较好的一致性:解译的滑坡主要分布在评估为滑坡高度危险的区域,表明本文所采用方法的有效性。本文对该方法的局限性也进行了讨论,并提出改进建议。     

Mechanism of two rapid and long-runout landslides in the 16 April 2016 Kumamoto earthquake using a ring-shear apparatus and computer simulation (LS-RAPID)

Around hundred landslides were triggered by the Kumamoto earthquakes in April 2016, causing fatalities and serious damage to properties in Minamiaso village, Kumamoto Prefecture, Japan. The landslides included many rapid and long-runout landslides which were responsible for much of the damage. To understand the mechanism of these earthquake-triggered landslides, we carried out field investigations with an unmanned aerial vehicle to obtain DSM and took samples from two major landslides (Takanodai landslide and Aso-ohashi landslide) to measure parameters of the initiation and the motion of landslides. A series of ring-shear tests and computer simulations were conducted using a measured Kumamoto earthquake acceleration record from KNet station KMM005, 10 km west of Aso-ohashi landslide. The research results supported our assumed mechanism of sliding-surface liquefaction for the rapid and long-runout motion of these landslides.     

An open dataset for landslides triggered by the 2016 Mw 7.8 Kaikōura earthquake,New Zealand

On November 14, 2016, the northeastern South Island of New Zealand was hit by the magnitude Mw 7.8 Kaikōura earthquake, which is characterized by the most complex rupturing mechanism ever recorded. The widespread landslides triggered by the earthquake make this event a great case study to revisit our current knowledge of earthquake-triggered landslides in terms of factors controlling the spatial distribution of landslides and the rapid assessment of geographic areas affected by widespread landsliding. Although the spatial and size distributions of landslides have already been investigated in the literature, a polygon-based co-seismic landslide inventory with landslide size information is still not available as of June 2021. To address this issue and leverage this large landslide event, we mapped 14,233 landslides over a total area of approximately 14,000 km². We also identified 101 landslide dams and shared them all via an open-access repository. We examined the spatial distribution of co-seismic landslides in relation to lithologic units and seismic and morphometric characteristics. We analyzed the size statistics of these landslides in a comparative manner, by using the five largest co-seismic landslide inventories ever mapped (i.e., Chi-Chi, Denali, Wenchuan, Haiti, and Gorkha). We compared our inventory with respect to these five ones to answer the question of whether the landslides triggered by the 2016 Kaikōura earthquake are less numerous and/or share size characteristics similar to those of other strong co-seismic landslide events. Our findings show that the spatial distribution of the Kaikōura landslide event is not significantly different from those belonging to other extreme landslide events, but the average landslide size generated by the Kaikōura earthquake is relatively larger compared to some other large earthquakes (i.e., Wenchuan and Gorkha).