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.     

Vulnerability assessment of reinforced concrete buildings subjected to seismically triggered slow-moving earth slides

The objective of this paper is to develop an efficient analytical method for assessing the vulnerability of low-rise reinforced concrete buildings subjected to seismically induced slow-moving earth slides. Vulnerability is defined in terms of probabilistic fragility curves, which describe the probability of exceeding a certain limit state of the building, on a given slope, versus the Peak Horizontal Ground Acceleration (PHGA) at the assumed “seismic bedrock”, allowing for the quantification of various sources of uncertainty. The proposed method is based on a two-step, uncoupled approach. In the first step, the differential permanent landslide displacements at the building’s foundation level are estimated using a dynamic non-linear finite difference slope model. In the second step, the calculated differential permanent displacements are statically imposed at the foundation level to assess the building’s response to differing permanent seismic ground displacements using a finite element code. Structural limit states are defined in terms of threshold values of strains for the reinforced concrete structural components. The method is applied to typical low-rise reinforced concrete frame buildings on shallow foundations with varying strength and stiffness characteristics (isolated footings and continuous slab foundation), standing near the crest of a relatively slow-moving earth slide. Two different slope models are selected representing a cohesive and a purely frictional soil material. The paper describes the method and the derived fragility curves for the selected building and slope typologies that could be used in quantitative risk assessment studies at site-specific and local scales.     

A modified approach for semi-quantitative estimation of physical vulnerability of buildings exposed to different landslide intensity scenarios

Landslides are the most common natural disasters in mountainous regions, being responsible for significant loss of life as well as damage to critical infrastructure and properties. As the world population grows, people tend to move to higher locations to construct buildings, thereby making structures vulnerable due to landslides. This paper discusses previous research on the vulnerability assessment of structures exposed to landslides and presents a modified semi-quantitative approach to assess the scenario-based physical vulnerability of buildings based on their resistance ability and landslide intensity. Resistance ability is determined by integrating expert knowledge-based resistance factors assigned to five primary building parameters. Landslide intensity matrix defining different intensity levels is proposed based on combinations of landslide velocity and volume. Physical vulnerability of buildings is estimated and classified as class I, II or III for scenario-based low to very high landslide intensity. Finally, the application of the model is illustrated with a case study of 71 buildings from Garhwal Himalayas, India.     

Experimental investigation on the interaction between the rapid sliding body and exposed element

Laboratory experiments play a key role in establishing rapid sliding models, as they are conducive to providing similar conditions to those in actual mass movement processes and, most importantly, can be conducted repeatedly. In order to elucidate the mass movement mechanisms and assess the landslide intensity as well as the risk of exposed elements following rapid sliding body, laboratory experiments consisting of releasing dry rigid grains or ceramsite debris onto an oblique chute were designed. The intensity and the vulnerability values were evaluated for sand and ceramsite sliding body that impact a single building, a row of buildings, and a group of buildings, respectively. In addition, the sliding characteristics of the mass and the interaction process mechanisms between sliding solid debris and buildings were also able to be obtained. The results show that the velocity of the front-end sliding mass decreases with increasing of the number of buildings. In addition, the vulnerability value of exposed element and the safety distance could be calculated from the recorded data. However, detailed geological factors of the mass, which are also important factors in this experiment, were not taken into account in the model presented in this paper. Nonetheless, this model can be used as a powerful tool for evaluating landslide instability propagation mechanisms.     

A comparison of logistic regression-based models of susceptibility to landslides in western Colorado,USA

The Paonia-McClure Pass area of Colorado has been recognized as a region highly susceptible to mass movement. Because of the dynamic nature of this landscape, accurate methods are needed to predict susceptibility to movement of these slopes. The area was evaluated by coupling a geographic information system (GIS) with logistic regression methods to assess susceptibility to landslides. We mapped 735 shallow landslides in the area. Seventeen factors, as predictor variables of landslides, were mapped from aerial photographs, available public data archives, ETM + satellite data, published literature, and frequent field surveys. A logistic regression model was run using landslides as the dependent factor and landslide-causing factors as independent factors (covariates). Landslide data were sampled from the landslide masses, landslide scarps, center of mass of the landslides, and center of scarp of the landslides, and an equal amount of data were collected from areas void of discernible mass movement. Models of susceptibility to landslides for each sampling technique were developed first. Second, landslides were classified as debris flows, debris slides, rock slides, and soil slides and then models of susceptibility to landslides were created for each type of landslide. The prediction accuracies of each model were compared using the Receiver Operating Characteristic (ROC) curve technique. The model, using samples from landslide scarps, has the highest prediction accuracy (85 %), and the model, using samples from landslide mass centers, has the lowest prediction accuracy (83 %) among the models developed from the four techniques of data sampling. Likewise, the model developed for debris slides has the highest prediction accuracy (92 %), and the model developed for soil slides has the lowest prediction accuracy (83 %) among the four types of landslides. Furthermore, prediction from a model developed by combining the four models of the four types of landslides (86 %) is better than the prediction from a model developed by using all landslides together (85 %).     

南平市红星滑坡泥石流特征及成因

该滑坡泥石流特征为,流域面积小,流程短,规模小,以坡面型为主,多由滑坡崩塌转化而来,发生频率低,突发性强,危害大。文章揭示在植被覆盖的花岗岩地区,持续强降雨引发群发性浅层土质滑坡,在斜坡微凹处或小沟谷,易转化成泥石流,形成灾害链。对该类型滑坡泥石流特征及成因进行分析,为福建省乃至全国同类型滑坡-泥石流的防治提供经验。     

A statistical approach to landslide risk modelling at basin scale: from landslide susceptibility to quantitative risk assessment

A procedure for landslide risk assessment is presented. The underlying hypothesis is that statistical relationships between past landslide occurrences and conditioning variables can be used to develop landslide susceptibility, hazard and risk models. The latter require also data on past damages. Landslides occurred during the last 50 years and subsequent damages were analysed. Landslide susceptibility models were obtained by means of Spatial Data Analysis techniques and independently validated. Scenarios defined on the basis of past landslide frequency and magnitude were used to transform susceptibility into quantitative hazard models. To assess vulnerability, a detailed inventory of exposed elements (infrastructures, buildings, land resources) was carried out. Vulnerability values (0–1) were obtained by comparing damages experienced in the past by each type of element with its actual value. Quantitative risk models, with a monetary meaning, were obtained for each element by integrating landslide hazard and vulnerability models. Landslide risk models showing the expected losses for the next 50 years were thus obtained for the different scenarios. Risk values obtained are not precise predictions of future losses but rather a means to identify areas where damages are likely to be greater and require priority for mitigation actions.     

A seismic landslide susceptibility rating of geologic units based on analysis of characteristics of landslides triggered by the 17 January, 1994 Northridge, California earthquake

One of the most significant effects of the 17 January, 1994 Northridge, California earthquake (M=6.7) was the triggering of thousands of landslides over a broad area. Some of these landslides damaged and destroyed homes and other structures, blocked roads, disrupted pipelines, and caused other serious damage. Analysis of the distribution and characteristics of these landslides is important in understanding what areas may be susceptible to landsliding in future earthquakes. We analyzed the frequency, distribution, and geometries of triggered landslides in the Santa Susana 7.5′ quadrangle, an area of intense seismic landslide activity near the earthquake epicenter. Landslides occurred primarily in young (Late Miocene through Pleistocene) uncemented or very weakly cemented sediment that has been repeatedly folded, faulted, and uplifted in the past 1.5 million years. The most common types of landslide triggered by the earthquake were highly disrupted, shallow falls and slides of rock and debris. Far less numerous were deeper, more coherent slumps and block slides, primarily occurring in more cohesive or competent materials. The landslides in the Santa Susana quadrangle were divided into two samples: single landslides (1502) and landslide complexes (60), which involved multiple coalescing failures of surficial material. We described landslide morphologies by computing simple morphometric parameters (area, length, width, aspect ratio, slope angle). To quantify and rank the relative susceptibility of each geologic unit to seismic landsliding, we calculated two indices: (1) the susceptibility index, which is the ratio (given as a percentage) of the area covered by landslide sources within a geologic unit to the total outcrop area of that unit; and (2) the frequency index [given in landslides per square kilometer (ls/km²)], which is the total number of landslides within each geologic unit divided by the outcrop area of that unit. Susceptibility categories include very high (>2.5% landslide area or >30 ls/km²), high (1.0–2.5% landslide area or 10–30 ls/km²), moderate (0.5–1.0% landslide area or 3–10 ls/km²), and low (<0.5% landslide area and <3 ls/km²).     

金沙江上游沃达滑坡发育特征与堵江危险性分析

金沙江上游沃达滑坡自1985年开始出现变形,现今地表宏观变形迹象明显,存在进一步失稳滑动和堵江的风险。采用遥感解译、地面调查、工程地质钻探和综合监测等方法,分析了沃达滑坡空间结构和复活变形特征,阐明了滑坡潜在复活失稳模式,并采用经验公式计算分析了滑坡堵江危险性。结果表明:沃达滑坡为一特大型滑坡,体积约28.81×106 m3,推测其在晚更新世之前发生过大规模滑动;滑坡堆积体目前整体处于蠕滑变形阶段,局部处于加速变形阶段;复活变形范围主要集中在中前部,且呈现向后渐进变形破坏特征,复活区右侧变形比左侧强烈。滑坡存在浅层和深层两级滑面,平均埋深分别约15.0,25.5 m,相应地可能出现两种潜在失稳模式:滑坡强变形区沿浅层滑带滑动失稳时,形成的堵江堰塞坝高度约87.2 m;滑坡整体沿深层滑带滑动失稳时,形成的堵江堰塞坝高度约129.2 m。沃达滑坡存在形成滑坡-堵江-溃决-洪水链式灾害的危险性,建议进一步加强滑坡监测,针对性开展排水、加固等防治工程。     

Landslide databases in the Geological Surveys of Europe

Landslides are one of the most widespread geohazards in Europe, producing significant social and economic impacts. Rapid population growth in urban areas throughout many countries in Europe and extreme climatic scenarios can considerably increase landslide risk in the near future. Variability exists between European countries in both the statutory treatment of landslide risk and the use of official assessment guidelines. This suggests that a European Landslides Directive that provides a common legal framework for dealing with landslides is necessary. With this long-term goal in mind, this work analyzes the landslide databases from the Geological Surveys of Europe focusing on their interoperability and completeness. The same landslide classification could be used for the 849,543 landslide records from the Geological Surveys, from which 36% are slides, 10% are falls, 20% are flows, 11% are complex slides, and 24% either remain unclassified or correspond to another typology. Most of them are mapped with the same symbol at a scale of 1:25,000 or greater, providing the necessary information to elaborate European-scale susceptibility maps for each landslide type. A landslide density map was produced for the available records from the Geological Surveys (LANDEN map) showing, for the first time, 210,544 km² landslide-prone areas and 23,681 administrative areas where the Geological Surveys from Europe have recorded landslides. The comparison of this map with the European landslide susceptibility map (ELSUS 1000 v1) is successful for most of the territory (69.7%) showing certain variability between countries. This comparison also permitted the identification of 0.98 Mkm² (28.9%) of landslide-susceptible areas without records from the Geological Surveys, which have been used to evaluate the landslide database completeness. The estimated completeness of the landslide databases (LDBs) from the Geological Surveys is 17%, varying between 1 and 55%. This variability is due to the different landslide strategies adopted by each country. In some of them, landslide mapping is systematic; others only record damaging landslides, whereas in others, landslide maps are only available for certain regions or local areas. Moreover, in most of the countries, LDBs from the Geological Surveys co-exist with others owned by a variety of public institutions producing LDBs at variable scales and formats. Hence, a greater coordination effort should be made by all the institutions working in landslide mapping to increase data integration and harmonization.     

Diagnosis of landslide risk for individual buildings: insights from Prahova Subcarpathians,Romania

The aim of this study is to quantify the landslide risk for individual buildings using spatial data in a GIS environment. A landslide-prone area from Prahova Rivers’ Subcarpathian Valley was chosen because of its associated landslide hazards and its impact upon human settlements and activities. The bivariate landslide susceptibility index (LSI) was applied to calculate the spatial probability of landslides occurrence. The Landslide Susceptibility Index map was produced by numerically adding the weighted thematic maps for slope gradient and aspect, water table, soil texture, lithology, built environment and land use. Validation curves were obtained using the random-split strategy for two combinations of variables: (a) all seven variables and (b) three variables which showed highest individual success rates with respect to landslides occurrences (slope gradient, water table and land use). The principal pre-disposing factors were found to be slope steepness and groundwater table. Vulnerability was established as the degree of loss to individual buildings resulting from a potential damaging landslide with a given return period in an area. Risk was calculated by multiplying the spatial probability of landslides by the vulnerability for each building and summing up the losses for the selected return period.     

A GIS method for landslide inventory and susceptibility mapping in the Río El Estado watershed,Pico de Orizaba volcano,México

In volcanic terrains, dormant stratovolcanoes are very common and can trigger landslides and debris flows continually along stream systems, thereby affecting human settlements and economic activities. It is important to assess their potential impact and damage through the use of landslide inventory maps and landslide models. In Mexico, numerous geographic information systems (GIS)-based applications have been used to represent and assess slope stability. However, there is no practical and standardized landslide mapping methodology under a GIS. This work provides an overview of the ongoing research project from the Institute of Geography at the National Autonomous University of Mexico that seeks to conduct a multi-temporal landslide inventory and produce a landslide susceptibility map by using GIS. The Río El Estado watershed on the southwestern flank of Pico de Orizaba volcano, the highest mountain in Mexico, is selected as a study area. The geologic and geomorphologic factors in combination with high seasonal precipitation, high degree of weathering, and steep slopes predispose the study area to landslides. The method encompasses two main levels of analysis to assess landslide susceptibility. First, the project aims to derive a landslide inventory map from a representative sample of landslides using aerial orthophotographs and field work. Next, the landslide susceptibility is modelled by using multiple logistic regression implemented in a GIS platform. The technique and its implementation of each level in a GISs-based technology is presented and discussed.     

单体滑坡灾害财产风险定量评估模型

目前承灾体易损性评估尚处于经验评估阶段,制约了单体滑坡灾害财产风险评估的定量化程度。为此,针对典型承灾体（建筑结构物）,提出一种单体滑坡灾害财产风险评估模型。认为财产风险是坡体失稳概率、承灾体在滑坡作用下的失效概率以及承灾体价值的乘积。避开了易损性评估,从一个新的角度来评估滑坡灾害财产风险。通过研究,验证了该模型正确反映了滑坡成灾过程中各种因素对财产风险的影响,从而为单体滑坡灾害财产风险的定量化评估提供了新的途径。另外以该模型应用研究为基础,提出承灾体安全范围的概念,对于每一个承灾体而言,将单体滑坡灾害影响范围划分为：危险区域、相对危险区域和安全区域,为建设工程选址或场地风险评估提供了实用指标,具有一定的工程实用价值。     

Distribution and characteristics of landslides induced by the Iwate–Miyagi Nairiku Earthquake in 2008 in Tohoku District, Northeast Japan

The Iwate–Miyagi Nairiku Earthquake in 2008, whose seismic intensity was M. 7.2 in Japan Meteorological Agency (JMA) scale, induced innumerable landslides on the southern flank of Mt. Kurikoma volcano allocated along the Ou Backbone Range in Northeast Japan. Most landslides are detected in a hanging wall side of the seismic fault. Those landslides are classified into five types: deep-seated slide, debris slide, shallow debris slide, secondary shallow debris slide, and debris flow. Most common landslide types induced by the earthquake are shallow debris slides and subsequent debris flows. They are intensively distributed along steep gorges incising a volcanic skirt of Mt. Kurikoma, consisting of welded ignimbrite of the Pleistocene age. Debris flows are also distributed even along gentle river floors in the southern lower flank of the volcano. The area of densely distributed debris slides, shallow debris slides, and debris flows is concordant with that of severe seismic tremor. Thus, genetic processes of landslides induced by the Iwate–Miyagi Nairiku Earthquake in 2008 are attributed to multiple causative factors such as geology, topography, and seismic force.     

NARX neural network approach for the monthly prediction of groundwater levels in Sylhet Sadar,Bangladesh

Groundwater is important for managing the water supply in agricultural countries like Bangladesh. Therefore, the ability to predict the changes of groundwater level is necessary for jointly planning the uses of groundwater resources. In this study, a new nonlinear autoregressive with exogenous inputs(NARX) network has been applied to simulate monthly groundwater levels in a well of Sylhet Sadar at a local scale. The Levenberg-Marquardt(LM) and Bayesian Regularization(BR) algorithms were used to train the NARX network, and the results were compared to determine the best architecture for predicting monthly groundwater levels over time. The comparison between LM and BR showed that NARX-BR has advantages over predicting monthly levels based on the Mean Squared Error(MSE), coefficient of determination(R~2), and Nash-Sutcliffe coefficient of efficiency(NSE). The results show that BR is the most accurate method for predicting groundwater levels with an error of ± 0.35 m. This method is applied to the management of irrigation water source, which provides important information for the prediction of local groundwater fluctuation at local level during a short period.     

Influence of the sediment delivery ratio index on the analysis of silting and break risk in the Plasencia reservoir (Central System,Spain)

The random forest method was used to generate susceptibility maps for debris flows, rock slides, and active layer detachment slides in the Donjek River area within the Yukon Alaska Highway Corridor, based on an inventory of landslides compiled by the Geological Survey of Canada in collaboration with the Yukon Geological Survey. The aim of this study is to develop data-driven landslide susceptibility models which can provide information on risk assessment to existing and planned infrastructure. The factors contributing to slope failure used in the models include slope angle, slope aspect, plan and profile curvatures, bedrock geology, surficial geology, proximity to faults, permafrost distribution, vegetation distribution, wetness index, and proximity to drainage system. A total of 83 debris flow deposits, 181 active layer detachment slides, and 104 rock slides were compiled in the landslide inventory. The samples representing the landslide free zones were randomly selected. The ratio of landslide/landslide free zones was set to 1:1 and 1:2 to examine the results of different sample ratios on the classification. Two-thirds of the samples for each landslide type were used in the classification, and the remaining 1/3 were used to evaluate the results. In addition to the classification maps, probability maps were also created, which served as the susceptibility maps for debris flows, rock slides, and active layer detachment slides. Success and prediction rate curves created to evaluate the performance of the resulting models indicate a high performance of the random forest in landslide susceptibility modelling.     

基于降雨响应的黄土丘陵区滑坡危险性预测研究——以宝鸡市麟游县为例

极端降雨易造成群发滑坡灾害,难以作为单体预测.为预测评估黄土丘陵区不同降雨强度诱发滑坡灾害危险性,论文在区域滑坡灾害特征研究的基础上,分析降雨强度特征及滑坡分布特征.以岭南滑坡为代表分析降雨诱发黄土-丘陵区滑坡的形成机制,介绍了无限斜坡模型原理、参数选取,利用GIS空间建模与分析功能,定量完成了无降雨、25 mm、50...     

Landslide susceptibility and hazard assessment in San Ramón Ravine, Santiago de Chile, from an engineering geological approach

Debris flows and soil and rock slides are among the main geological hazards in the mountain foothills of Central Chile. Geological risk associated with the development of landslides, especially debris flows triggered in the basins of ravines that drain into the capital city, Santiago, has increased in time due to accelerated urban expansion. A landslide hazard evaluation in the San Ramón Ravine, located within the foothills of Santiago is presented. Hazard evaluation is based on a methodology that combines the determination of landslide susceptibility calculated by integration of conditioning factors, with the assessment of slope failure and runout probabilities incorporating geotechnical engineering approaches. The methodology is appropriate for medium or subregional scale studies with limited data. The results show that in San Ramón Ravine the landslide hazard consists mainly of debris flows, rock block slides, rock falls and shallow soil slides. Among these, debris flows are the most important due to the urban area that can be affected. Other case studies show that the method can be used in other regions with minor adaptations for territorial planning or for engineering and environmental purposes.     

Empirical fragility and vulnerability curves for buildings exposed to slow-moving landslides at medium and large scales

Slow-moving landslides yearly induce huge economic losses worldwide in terms of damage to facilities and interruption of human activities. Within the landslide risk management framework, the consequence analysis is a key step entailing procedures mainly based on identifying and quantifying the exposed elements, defining an intensity criterion and assessing the expected losses. This paper presents a two-scale (medium and large) procedure for vulnerability assessment of buildings located in areas affected by slow-moving landslides. Their intensity derives from Differential Interferometric Synthetic Aperture Radar (DInSAR) satellite data analysis, which in the last decade proved to be capable of providing cost-effective long-term displacement archives. The analyses carried out on two study areas of southern Italy (one per each of the addressed scales) lead to the generation, as an absolute novelty, of both empirical fragility and vulnerability curves for buildings in slow-moving landslide-affected areas. These curves, once further validated, can be valuably used as tools for consequence forecasting purposes and, more in general, for planning the most suitable slow-moving landslide risk mitigation strategies.     

Assessment of rainfall-induced shallow landslides in Phetchabun and Krabi provinces,Thailand

Shallow landslides are a common type of rainfall-induced landslide, and various methods are currently used to predict their occurrence on a regional scale. Physically based models, such as the shallow landslide instability prediction (SLIP) model, have many advantages because these models can assess the hazards of shallow landslides dynamically, based on physical stability equations that consider rainfall as a triggering factor. The main objective of this research is to test the SLIP model’s potential to predict shallow landslide hazards in Thailand. To achieve this goal, the SLIP model was applied to two massive landslide events in Thailand. The results predicted by the SLIP model for the two study areas are outlined, and the model prediction capabilities were evaluated using the receiver operating characteristic plot. The Phetchabun results showed that the western part of the catchment had the lowest factor of safety (F _S) value, whereas the Krabi results showed that the slopes surrounding the peak of Khao Panom Mountain had the lowest F _S value, explaining the highest potentials for shallow landslides in each area. The SLIP model showed good performance: The global accuracies were 0.828 for the Phetchabun area and 0.824 for the Krabi area. The SLIP model predicted the daily time-varying percentage of unstable areas over the analyzed periods. The SLIP model simulated a negligible percentage of unstable areas over all considered periods, except for expected dates, suggesting that the prediction capability is reasonably accurate.