Statistical analysis of an earthquake-induced landslide distribution — the 1989 Loma Prieta, California event

The 1989 Loma Prieta, California earthquake (moment magnitude, M=6.9) generated landslides throughout an area of about 15,000 km² in central California. Most of these landslides occurred in an area of about 2000 km² in the mountainous terrain around the epicenter, where they were mapped during field investigations immediately following the earthquake. The distribution of these landslides is investigated statistically, using regression and one-way analysis of variance (ANOVA) techniques to determine how the occurrence of landslides correlates with distance from the earthquake source, slope steepness, and rock type. The landslide concentration (defined as the number of landslide sources per unit area) has a strong inverse correlation with distance from the earthquake source and a strong positive correlation with slope steepness. The landslide concentration differs substantially among the various geologic units in the area. The differences correlate to some degree with differences in lithology and degree of induration, but this correlation is less clear, suggesting a more complex relationship between landslide occurrence and rock properties.     

Spatial distribution of landslides triggered by the 2008 Ms 8.0 Wenchuan earthquake,China

The Ms 8.0 Wenchuan earthquake of May 12, 2008 is one of the most disastrous earthquakes in China. The earthquake triggered tens of thousands of landslides over a broad area, including shallow, disrupted landslides, rock falls, deep-seated landslides, and rock avalanches, some of which buried large sections of some towns and dammed the rivers. The purpose of this study is to investigate correlations between the occurrence of landslides with geologic and geomorphologic conditions, and seismic parameters. Over 56,000 earthquake-triggered landslides, with a total area of 811 km², are interpreted using aerial photographs and remote sensing images taken following the earthquake. The spatial distribution of these landslides is analyzed statistically using both landslide-point density (LPD), defined as the number of landslides per square kilometer, and landslide-area density (LAD), the percentage of the area affected by landslides, to determine how the occurrence of landslides correlates with distance from the epicenter, distance from the major surface rupture, seismic intensity and peak ground acceleration (PGA), slope angle, slope aspect, elevation, and lithology. It is found that both LAD and LPD have strong positive correlations with slope steepness, distance from the major surface rupture and seismic intensity, and that Pre-Sinian schist, and Cambrian sandstone and siltstone intercalated with slate have the most concentrated landslide activities, followed by the Permian limestone intercalated with shale, and Devonian limestone. Statistical analyses also indicate that the major surface rupture has influence on the spatial distribution of landslides, because LAD and LPD are relatively higher on the hanging wall than on the footwall. However, the correlation between the occurrence of landslides with distance from the epicenter of the earthquake is complicated, rather than a relatively simple negative correlation as found from other reported cases of earthquakes. This is possibly due to complicated rupture processes of the earthquake.     

Analysis of the mechanisms of slope failures triggered by the 2007 Chuetsu Oki earthquake

The 2007 Chuetsu Oki earthquake (M_JMA = 6.6) triggered more than one hundred slope failures in the northwest part of Niigata prefecture, Japan. A reconnaissance survey conducted by the authors revealed that although most of the failures were only a few meters deep, they still caused significant damage to roads, railways, and houses. It was also found that a vast number of shallow slides were concentrated along the coastal line of the Japan Sea, while only few, but relatively larger failures occurred in a mountainous part of the study area, which is located in a considerable distance from the earthquake’s epicenter. This paper summarizes the reconnaissance observations, describes the geologic characteristics of the area covered by landslides, provides characterization of major types of the landslides, and examines the causes and mechanisms of typical failures. In addition, this paper seeks to investigate the mechanism of the Ohzumi landslide, the largest slide triggered by the Chuetsu Oki earthquake. For this purpose, a comprehensive analysis that included field investigation and laboratory testing of soils samples was performed. Results of field investigation suggested that the failure plane of the Ohzumi landslide formed in a saturated layer of sandy soil near a boundary with bedrock. Data from undrained cyclic loading triaxial compression tests indicated that the sandy material was highly susceptible to generation of high excess pore-water pressures during earthquake loading. On the basis of the obtained results and the outcome of seismic response and slope stability analyses, the authors posited an explanation on the mechanism of the Ohzumi landslide.     

Early warning system for shallow landslides using rainfall threshold and slope stability analysis

A combined cluster and regression analysis were performed for the first time to identify rainfall threshold that triggers landslide events in Amboori, Kerala, India. Amboori is a tropical area that is highly vulnerable to landslides. The 2, 3, and 5-day antecedent rainfall data versus daily rainfall was clustered to identify a cluster of critical events that could potentially trigger landslides. Further, the cluster of critical events was utilized for regression analysis to develop the threshold equations. The 5-day antecedent (x-variable) vs. daily rainfall (y-variable) provided the best fit to the data with a threshold equation of y = 80.7–0.1981x. The intercept of the equation indicates that if the 5-day antecedent rainfall is zero, the minimum daily rainfall needed to trigger the landslide in the Amboori region would be 80.7 mm. The negative coefficient of the antecedent rainfall indicates that when the cumulative antecedent rainfall increases, the amount of daily rainfall required to trigger monsoon landslide decreases. The coefficient value indicates that the contribution of the 5-day antecedent rainfall is ∼20% to the landslide trigger threshold. The slope stability analysis carried out for the area, using Probabilistic Infinite Slope Analysis Model (PISA-m), was utilized to identify the areas vulnerable to landslide in the region. The locations in the area where past landslides have occurred demonstrate lower Factors of Safety (FS) in the slope stability analysis. Thus, rainfall threshold analysis together with the FS values from slope stability can be suitable for developing a simple, cost-effective, and comprehensive early-warning system for shallow landslides in Amboori and similar regions.     

Spatial distribution of landslides induced by the 2004 Mid-Niigata prefecture earthquake,Japan

On October 23, 2004, an earthquake with a moment magnitude of 6.8 occurred in the Chuetsu area of Niigata prefecture in Japan. This earthquake is known as the 2004 Mid-Niigata prefecture earthquake; the event was followed by severe aftershocks and caused many types of landslides such as surficial slides, shallow slides, and deep slides. A large number of landslides occurred in the upland village of Yamakoshi, destroying the entire village; in addition, a huge number of houses collapsed in Kawaguchi town. This study investigates the correlations between each type of landslide and the bedding plane orientation and dip, and other geomorphologic conditions. The landslide occurrence ratio (LOR) is used as an index to determine the correlation between the 2004 Mid-Niigata prefecture earthquake-induced landslides and the slope angle, slope aspect, rock type, and bedding plane orientation and dip. This work also proposes a methodology to determine the geometric alignment between the topography and the orientation of geological bedding planes. The method provides an efficient means of estimating the topography/bedding plane relationship over large areas.     

Analysis of the relationship of landslide occurrence with rainfall: a case study of Wudu County,China

Landslides are a significant hazard in many parts of the world and represent an important geohazard in China. Rainfall is the primary triggering agent for landslides and often used for prediction slope failures. However, the relationship between rainfall and landslide occurrences is very complex. Great efforts have been made on the study of regional rainfall-induced landslide forecasting models in recent years; still, there is no commonly accepted method for rainfall-induced landslide prediction. In this paper, the quantitative antecedent soil water status (ASWS) model is applied to investigate the influence of daily and antecedent rainfall on the triggering of landslides and debris flows. The study area is Wudu County in Gansu Province, an area which exhibits frequent landslide occurrences. The results demonstrate a significant influence of high intensity rainfall events on landslide triggering. Still, antecedent rainfall conditions are very important and once a threshold of approximately 20 mm is exceeded, landslides and debris flows can occur even without additional rainfall. The study presented could also facilitate the implementation of a regional forecasting scheme once additional validation has been carried out.     

Rainfall patterns for shallow landsliding in perialpine Slovenia

This paper presents two types of analysis: an antecedent rainfall analysis based on daily rainfall and an intensity-duration analysis of rainfall events based on hourly data in perialpine Slovenia in the ?kofjelo?ko Cerkljansko hills. For this purpose, eight rainfall events that are known to have caused landslides in the period from 1990 to 2010 were studied. Over the observed period, approximately 400 records of landslides were collected. Rainfall data were obtained from three rain gauges. The daily rainfall from the 30 days before landslide events was investigated based on the type of landslides and their geo-environmental setting, the dates of confirmed landslide activity and different consecutive rainfall periods. The analysis revealed that the rainfall events triggering slope failure can be divided into two groups according to the different antecedent periods. The first group of landslides typically occurred after short-duration rainstorms with high intensity, when the daily rainfall exceeded the antecedent rainfall. The second group comprises the rainfall events with a longer antecedent period of at least 7 days. A comparison of the plotted peak and mean intensities indicates that the rainfall patterns that govern slope failure are similar but do not necessarily reflect the rainfall intensity at the time of shallow landslides in the Dav?a or Poljane areas, where the majority of the landslides occurred. Because of several limitations, the suggested threshold cannot be compared and evaluated with other thresholds.     

The determination of statistical and deterministic hydrological landslide-triggering thresholds

 Hydrological landslide-triggering thresholds separate combinations of daily and antecedent rainfall or of rainfall intensity and duration that triggered landslides from those that failed to trigger landslides. They are required for the development of landslide early warning systems. When a large data set on rainfall and landslide occurrence is available, hydrological triggering thresholds are determined in a statistical way. When the data on landslide occurrence is limited, deterministic models have to be used. For shallow landslides directly triggered by percolating rainfall, triggering thresholds can be established by means of one-dimensional hydrological models linked to the infinite slope model. In the case of relatively deep landslides located in topographic hollows and triggered by a slow accumulation of water at the soil-bedrock contact, simple correlations between landslide occurrence and rainfall can no longer be established. Therefore real-time failure probabilities have to be determined using hydrological catchment models in combination with the infinite slope model. Received: 15 October 1997 · Accepted: 25 June 1997     

Statistical evaluation of the effect of earthquake with other related factors on landslide susceptibility: using the watershed area of Shihmen reservoir in Taiwan as a case study

Landslide susceptibility evaluation is one of the most important issues in watershed management. After an earthquake, the landslide susceptibility decreases functionally with increases in the distance from the epicenter. Under the same rainfall intensity, landslides are more likely to occur in an area where earthquakes occur more frequently. However, the questions of how much an earthquake should be weighted and how to evaluate the effects of an earthquake still need to be studied. To understand how earthquakes affect rainfall-triggered landslides, the horizontal peak ground acceleration (PGA) data from the Central Weather Bureau Seismic Network is used as the earthquake factor and combined with other factors to determine the weight of earthquakes in landslide susceptibility using logistic regression. The results indicate that the ability of landslide prediction is better when considering the earthquake factor. This study also proved that although there are no co-seismic landslides (after earthquakes) in the study area, the earthquake factor is still required to increase the model accuracy. PGA has been described as a usable factor. In areas with frequent earthquakes and high geological activity, when using historical data to evaluate landslide susceptibility, the earthquake factor should be taken into consideration to prevent errors.     

Do landslides follow landslides? Insights in path dependency from a multi-temporal landslide inventory

Landslides are a major category of natural disasters, causing loss of lives, livelihoods and property. The critical roles played by triggering (such as extreme rainfall and earthquakes), and intrinsic factors (such as slope steepness, soil properties and lithology) have previously successfully been recognized and quantified using a variety of qualitative, quantitative and hybrid methods in a wide range of study sites. However, available data typically do not allow to investigate the effect that earlier landslides have on intrinsic factors and hence on follow-up landslides. Therefore, existing methods cannot account for the potentially complex susceptibility changes caused by landslide events. In this study, we used a substantially different alternative approach to shed light on the potential effect of earlier landslides using a multi-temporal dataset of landslide occurrence containing 17 time slices. Spatial overlap and the time interval between landslides play key roles in our work. We quantified the degree to which landslides preferentially occur in locations where landslides occurred previously, how long such an effect is noticeable, and how landslides are spatially associated over time. We also investigated whether overlap with previous landslides causes differences in landslide geometric properties. We found that overlap among landslides demonstrates a clear legacy effect (path dependency) that has influence on the landslide affected area. Landslides appear to cause greater susceptibility for follow-up landslides over a period of about 10  years. Follow-up landslides are on average larger and rounder than landslides that do not follow earlier slides. The effect of earlier landslides on follow-up landslides has implications for understanding of the landslides evolution and the assessment of landslide susceptibility.     

Rainfall thresholds for prediction of shallow landslides around Chamoli-Joshimath region,Garhwal Himalayas,India

Majority of landslides in the Indian sub-continent are triggered by rainfall. Several attempts in the global scenario have been made to establish rainfall thresholds in terms of intensity-duration and antecedent rainfall models on global, regional and local scales for the occurrence of landslides. However, in the context of the Indian Himalayas, the rainfall thresholds for landslide occurrences are not yet understood fully. Neither on regional scale nor on local scale, establishing such rainfall thresholds for landslide occurrences in Indian Himalayas has yet been attempted. This paper presents an attempt towards deriving local rainfall thresholds for landslides based on daily rainfall data in and around Chamoli-Joshimath region of the Garhwal Himalayas, India. Around 128 landslides taken place in last 4 years from 2009 to 2012 have been studied to derive rainfall thresholds. Out of 128 landslides, however, rainfall events pertaining to 81 landslides were analysed to yield an empirical intensity–duration threshold for landslide occurrences. The rainfall threshold relationship fitted to the lower boundary of the landslide triggering rainfall events is I?=?1.82 D ^?0.23 (I?=?rainfall intensity in millimeters per hour and D?=?duration in hours). It is revealed that for rainfall events of shorter duration (≤24 h) with a rainfall intensity of 0.87 mm/h, the risk of landslide occurrence in this part of the terrain is expected to be high. Also, the role of antecedent rainfall in causing landslides was analysed by considering daily rainfall at failure and different period cumulative rainfall prior to failure considering all 128 landslides. It is observed that a minimum 10-day antecedent rainfall of 55 mm and a 20-day antecedent rainfall of 185 mm are required for the initiation of landslides in this area. These rainfall thresholds presented in this paper may be improved with the hourly rainfall data vis-à-vis landslide occurrences and also data of later years. However, these thresholds may be used in landslide warning systems for this particular region of the Garhwal Himalayas to guide the traffic and provide safety to the tourists travelling along this pilgrim route during monsoon seasons.     

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。     

Characteristics of rapid giant landslides in China

Factual data for 70 rapid, giant landslides since 1900 show that the occurrence of these landslides was largely predisposed by tectonics, geological structures, lithology and topography, and often triggered by rainfall and earthquakes. In terms of mobile behavior, the giant landslides can be classified into three types: slides, slide-flows and flows. It is found that each type of landslide was constrained to certain geologic and topographic regimes. There are good correlations between kinematic parameters of landslides and slope geometries, which confirm the important role played by topographical condition in the mobile behavior of landslides. Moreover, it is also found that each type of landslide presents distinct geotechnical characteristics in terms of nature of the slip zone and properties of sliding mass. Brief analyses of five typical cases illustrate that landslide mechanisms can be conceptually depicted by failure mechanisms of their slip zones prior to onset of movement and following energy conversion during movement. Problems and questions related to experience in China suggest that comprehensive and systematic investigation and study on rapid giant landslides are urgently needed.     

Integrating intensity–duration-based rainfall threshold and antecedent rainfall-based probability estimate towards generating early warning for rainfall-induced landslides in parts of the Garhwal Himalaya,India

In order to generate early warning for landslides, it is necessary to address the spatial and temporal aspects of slope failure. The present study deals with the temporal dimension of slope failures taking into account the most widespread and frequent triggering factor, i.e. rainfall, along the National Highway-58 from Rishikesh to Mana in the Garhwal Himalaya, India. Using the post-processed three-hourly rainfall intensity and duration values from the Tropical Rainfall Measuring Mission-based Multi-satellite Precipitation Analysis and the time-tagged landslide records along this route, an intensity–duration (I–D)-based threshold has been derived as I?=?58.7D ^?1.12 for the rainfall-triggered landslides. The validation of the I–D threshold has shown 81.6 % accuracy for landslides which occurred in 2005 and 2006. From this result, it can be inferred that landslides in the study area can be initiated by continuous rainfall of over 12 h with about 4-mm/h intensity. Using the mean annual precipitation, a normalized intensity–duration relation of NI?=?0.0612D ^?1.17 has also been derived. In order to account for the influence of the antecedent rainfall in slope failure initiation, the daily, 3-day cumulative, and 15- and 30-day antecedent rainfall values associated with landslides had been subjected to binary logistic regression using landslide as the dichotomous dependent variable. The logistic regression retained the daily, 3-day cumulative and 30-day antecedent rainfall values as significant predictors influencing slope failure. This model has been validated through receiver operating characteristic curve analysis using a set of samples which had not been used in the model building; an accuracy of 95.1 % has been obtained. Cross-validation of I–D-based thresholding and antecedent rainfall-based probability estimation with slope failure initiation shows 81.9 % conformity between the two in correctly predicting slope stability. Using the I–D-based threshold and the antecedent rainfall-based regression model, early warning can be generated for moderate to high landslide-susceptible areas (which can be delineated using spatial integration of preconditioning factors). Temporal predictions where both the methods converge indicate higher chances of slope failures for areas predisposed to instability due to unfavourable geo-environmental and topographic parameters and qualify for enhanced slope failure warning. This method can be verified for further rainfall seasons and can also be refined progressively with finer resolutions (spatial and temporal) of rainfall intensity and multiple rain gauge stations covering a larger spatial extent.     

Probabilistic modeling of seismically triggered landslides using Monte Carlo simulations

The 2004 Chuetsu earthquakes of Niigata (Japan) triggered numerous landslides, and the most widespread types of landslides were highly disrupted, relatively shallow slides and soil (debris) flows. This paper presented a method to evaluate slope instability using Newmark displacement on a pixel-by-pixel basis in a given area. The proposed method was able to integrate Newmark displacement modeling and Monte Carlo simulations within geographical information systems. In the modeling, an empirical attenuation relationship was utilized to calculate Arias intensity over this study area, and the variability of geotechnical parameters was taken into account to calculate coseismic landslide displacement. Before deriving the displacement from related inputs, the Monte Carlo simulations ran 1,500 times and generated 1,500 displacement values for each grid cell, and then means and standard deviations of displacement were calculated and probabilistic distributions can be obtained. Finally, given 10 cm as a threshold value of displacement, estimated probabilities of displacement exceeding 10 cm were shown as a map of seismic landslide hazards. The resulting hazard map was classified into four categories from very low to high level.     

汶川地震强震区地震诱发滑坡与后期降雨诱发滑坡控制因子耦合分析

本文以汶川地震强震区北川县典型研究区为例,利用高分辨率航片、SPOT5卫星图像对北川县典型研究区进行了512地震之后和924降雨之后诱发的滑坡解译,解译结果显示:512地震诱发滑坡1999个,924强降雨诱发滑坡828个,924强降雨导致原有地震滑坡面积扩大的滑坡150个。研究表明:地震和强降雨都是诱发滑坡的动力成因,924强降雨诱发的滑坡面积是512地震诱发滑坡面积的1/4倍,强降雨诱发滑坡的数量增加了41.4%; 强降雨不仅诱发新的滑坡,而且促使原来地震滑坡复活,并扩大其面积,强降雨导致地震诱发的滑坡面积扩大了原面积的68.7%。同时,在遥感解译数据基础之上,开展地震诱发滑坡与降雨诱发滑坡规模对比和控制因子耦合分析及地震与降雨耦合灾害链模式研究,为进一步分析研究地震灾区滑坡的产生、发展趋势、危险性和风险评价等预测预报提供科学依据,也为汶川震区恢复重建中的减灾防灾提供决策参考。     

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.     

蒙特卡罗模拟在区域地震滑坡灾害评价中应用

2004年10月23日,日本新泻中越地区发生史上最强地震之一,震级达到Mw6.6。这次地震诱发上千个规模大小不一、形式各样的滑坡,造成一定的灾害损失和人员伤亡。因此,为了有效地避免和减轻这方面的灾害,有必要有效地、科学地预测和评价地震诱发滑坡的空间发生规律。为此以一定的地区作为研究对象,提出了蒙特卡罗随机模拟和Newmark滑动体位移分析法在区域地震斜坡失稳概率分析中的应用。该法充分考虑到岩土参数和相关地震参数空间变异性,结合地理信息系统空间分析的优势,以网格模型为基础,分析该区斜坡滑动体位移分布规律,并以2cm为失稳临界值探讨网格斜坡破坏的概率。实例证明,所提出的模型有效地预测了滑坡发生的空间分布规律。     

Overcoming source limitations in drainage delineation by combining the streams of toposheet and DEM in river morphometric studies

A potential head ward retreat landslide area was identified in Munnar, a hill station in Western Ghats of Kerala, India. This imminent landslide was suspected to be formed in three different stages viz., evolution of plateau region, upliftment of the plateau region and the consequent slope modification which ultimately facilitated landslide occurrence. Geophysical study through vertical electrical sounding reveals that more than 11 m thick soil is still left in an overhanging position in the crown portion of the landslide and the thickness continues to the top of that ridge. In the event of high rainfall, the land can fail as there is no toe support, and the slope angle is >40º. This area is adjacent to a college building and in the event of any further landslide, the consequence will be high. Slope stability analysis using one-dimensional infinite slope stability model reveals that the entire area occupied by the college and the adjacent areas are unstable even in dry conditions. Rainfall threshold analysis shows that the landslide occurred due to very high amount of a 5-day antecedent rainfall rather than a daily rainfall during the monsoon. All these point towards a pressing requirement of landslide management practices in this area. This study also attempts to suggest a few management practices to minimize the effect of landslides.     

Landslides in the North of Lisbon Region (Portugal): Conditioning and triggering factors

Detailed geomorphological mapping carried out in 5 sample areas in the North of Lisbon Region allowed us to collect a set of geological and geomorphological data and to correlate them with the spatial occurrence of landslide. A total of 597 slope movements were identified in a total area of 61.7 km², which represents about 10 landslides per km².The main landslide conditioning factors are: lithology and geological structure, slope angle and slope morphology, land use, presence of old landslides, and human activity.The highest landslide density occurs in Cretaceous marls and marly limestones, but the largest movements are in Jurassic clays, marls and limestones.The landslide density is higher on slopes with gradients above 20 °, but the largest unstable area is found on slopes of 10 ° to 15 °, thus reflecting the presence of the biggest slope movements. There is a correlation between landslides and topographical concavities, a fact that can be interpreted as reflecting the significance of the hydrological regime in slope instability.Concerning land use, the highest density of landslides is found on slopes covered with shrub and undergrowth vegetation.About 26% of the total number of landslides are reactivation events. The presence of old landslides is particularly important in the occurrence of translational slides and complex and composite slope movements.20% of the landslide events were conditioned by anthropomorphic activity. Human's intervention manifests itself in ill-consolidated fills, cuts in potentially unstable slopes and, in a few cases, in the changing of river channels.Most slope movements in the study area exhibit a clear climatic signal. The analysis of rainfall distribution in periods of recognised slope instability allows the distinction of three situations: 1) moderate intensity rainfall episodes, responsible for minor slope movements on the bank of rivers and shallow translational slides, particularly in artificial trenches; 2) high intensity rainfall episodes, originating flash floods and most landslides triggered by bank erosion; 3) long-lasting rainfall periods, responsible for the rise of the groundwater table and triggering of landslides with deeper slip surfaces.