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1.
Representative rainfall thresholds for landslides in the Nepal Himalaya   总被引：14，自引：0，他引：14  
Measuring some 2400 km in length, the Himalaya accommodate millions of people in northern India and Pakistan, Nepal, Bhutan, and parts of other Asian nations. Every year, especially during monsoon rains, landslides and related natural events in these mountains cause tremendous damage to lives, property, infrastructure, and environment. In the context of the Himalaya, however, the rainfall thresholds for landslide initiation are not well understood. This paper describes regional aspects of rainfall thresholds for landslides in the Himalaya. Some 677 landslides occurring from 1951 to 2006 were studied to analyze rainfall thresholds. Out of the 677 landslides, however, only 193 associated with rainfall data were analyzed to yield a threshold relationship between rainfall intensity, rainfall duration, and landslide initiation. The threshold relationship fitted to the lower boundary of the field defined by landslide-triggering rainfall events is I = 73.90D− 0.79 (I = rainfall intensity in mm h− 1 and D = duration in hours), revealing that when the daily precipitation exceeds 144 mm, the risk of landslides on Himalayan mountain slopes is high. Normalized rainfall intensity–duration relationships and landslide initiation thresholds were established from the data after normalizing rainfall-intensity data with respect to mean annual precipitation (MAP) as an index in which NI = 1.10D− 0.59 (NI = normalized intensity in h− 1). Finally, the role of antecedent rainfall in causing landslides was also investigated by considering daily rainfall during failure and the cumulative rainfall to discover at what point antecedent rainfall plays an important role in Himalayan landslide processes. Rainfall thresholds presented in this paper are generalized so they can be used in landslide warning systems in the Nepal Himalaya.  相似文献   

2.
Chun-Hung Wu  Su-Chin Chen   《Geomorphology》2009,112(3-4):190-204
This work provides a landslide susceptibility assessment model for rainfall-induced landslides in Central Taiwan based on the analytical hierarchy process method. The model considers rainfall and six site factors, including slope, geology, vegetation, soil moisture, road development and historical landslides. The rainfall factor consists of 10-day antecedent rainfall and total rainfall during a rainfall event. Landslide susceptibility values are calculated for both before and after the beginning of a rainfall event. The 175 landslide cases with detailed field surveys are used to determine a landslide-susceptibility threshold value of 9.0. When a landslide susceptibility assessment value exceeds the threshold value, slope failure is likely to occur. Three zones with different landslide susceptibility levels (below, slightly above, and far above the threshold) are identified. The 9149 landslides caused by Typhoon Toraji in Central Taiwan are utilized to validate the study's result. Approximately, 0.2%, 0.4% and 15.3% of the typhoon-caused landslides are located in the three landslide susceptibility zones, respectively. Three villages with 6.6%, 0.4% and 4.9% of the landslides respectively are used to validate the accuracy of the landslide susceptibility map and analyze the main causes of landslides. The landslide susceptibility assessment model can be used to evaluate susceptibility relative to accumulated rainfall, and is useful as an early warning and landslide monitoring tool.  相似文献   

3.
The purpose of the present study is the analysis of landslide risk for roads and buildings in a small test site (20 km2) in the area north of Lisbon (Portugal). For this purpose, an evaluation is performed integrating into a GIS information obtained from multiple sources: (i) landslide hazard; (ii) elements at risk; and (iii) vulnerability. Landslide hazard is assessed on a probabilistic basis for three different types of slope movement (shallow translational slides, translational slides and rotational slides), based on some assumptions such as: (i) the likelihood of future landslide occurrence can be measured through statistical relationships between past landslide distribution and specified spatial data sets considered as landslide predisposing factors; and (ii) the rainfall combination (amount–duration) responsible for past slope instability within the test site will produce the same effects (i.e. same type of landslides and similar total affected area), each time they occur in the future. When the return period of rainfall triggering events is known, different scenarios can be modelled, each one ascribed to a specific return period. Therefore, landslide hazard is quantitatively assessed on a raster basis, and is expressed as the probability for each pixel (25 m2) to be affected by a future landslide, considering a rainfall triggering scenario with a specific return period. Elements at risk within the test site include 2561 buildings and roads amounting to 169 km. Values attributed to elements at risk were defined considering reconstruction costs, following the guidelines of the Portuguese Insurance Institute. Vulnerability is considered as the degree of loss to a given element resulting from the occurrence of a landslide of a given magnitude. Vulnerability depends not only on structural properties of exposed elements, but also on the type of process, and its magnitude; i.e., vulnerability cannot be defined in absolute terms, but only with respect to a specific process (e.g. vulnerability to shallow translational slides). Therefore, vulnerability was classified for the three landslide groups considered on hazard assessment, taking into account: (i) landslide magnitude (mean depth, volume, velocity); (ii) damage levels produced by past landslide events in the study area; and (iii) literature. Finally, a landslide risk analysis considering direct costs was made in an automatic way crossing the following three layers: (i) Probabilistic hazard map for a landslide type Z, considering a particular rainfall triggering scenario whose return period is known; (ii) Vulnerability map (values from 0 to 1) of the exposed elements to landslide type Z; and (iii) Value map of the exposed elements, considering reconstruction costs.  相似文献   

4.
GIS支持下三峡库区秭归县滑坡灾害空间预测   总被引：3，自引：1，他引：2  
彭令  牛瑞卿  陈丽霞 《地理研究》2010,29(10):1889-1898
基于GIS空间分析和统计模型相结合进行区域评价与空间预测是滑坡灾害研究的重要方向之一。以三峡库区秭归县为研究区,选择坡度、坡向、边坡结构、工程岩组、排水系统、土地利用和公路开挖作为评价因子。为提高模型的预测精度、可信度和推广能力,利用窗口采样规则降低训练样本之间的空间相关性。建立Logistic回归模型,对滑坡灾害与评价因子进行定量相关性分析。计算研究区滑坡灾害易发性指数,对其进行聚类分析,绘制滑坡易发性分区图,其中高、中易发区占整个研究区面积的38.9%,主要分布在人类工程活动频繁和靠近排水系统的区域。经过验证,该模型的预测精度达到77.57%。  相似文献   

5.
Many studies have documented major landslide events in mountain areas following heavy rainfall amounts. In the Himalaya, landslides occur during every monsoon period, but the role of rainfall in triggering these failures is not clear. This paper reports the results of a three-year study (1991-1993) into landsliding in the Likhu Khola drainage basin, Middle Hills, Nepal. Considerable annual variability in numbers, types and sizes of landslides was noted. Some of this variability can be explained by fluctuations in rainfall amounts and intensities, but many landslides were explained more easily by other controlling factors. In situations where slopes are extensively terraced for agriculture, with some terraces being intensely irrigated and others not, relationships between landsliding and rainfall amounts are complex and no simple explanations can be made.  相似文献   

6.
GIS and ANN model for landslide susceptibility mapping   总被引：1，自引：0，他引：1  
XU Zeng-wang 《地理学报》2001,11(3):374-381
Landslide hazard is as the probability of occurrence of a potentially damaging landslide phenomenon within specified period of time and within a given area. The susceptibility map provides the relative spatial probability of landslides occurrence. A study is presented of the application of GIS and artificial neural network model to landslide susceptibility mapping, with particular reference to landslides on natural terrain in this paper. The method has been applied to Lantau Island, the largest outlying island within the territory of Hong Kong. A three-level neural network model was constructed and trained by the back-propagate algorithm in the geographical database of the study area. The data in the database includes digital elevation modal and its derivatives, landslides distribution and their attributes, superficial geological maps, vegetation cover, the raingauges distribution and their 14 years 5-minute observation. Based on field inspection and analysis of correlation between terrain variables and landslides frequency, lithology, vegetation cover, slope gradient, slope aspect, slope curvature, elevation, the characteristic value, the rainstorms corresponding to the landslide, and distance to drainage line are considered to be related to landslide susceptibility in this study. The artificial neural network is then coupled with the ArcView3.2 GIS software to produce the landslide susceptibility map, which classifies the susceptibility into three levels: low, moderate, and high. The results from this study indicate that GIS coupled with artificial neural network model is a flexible and powerful approach to identify the spatial probability of hazards.  相似文献   

7.
Geomorphological information can be combined with decision-support tools to assess landslide hazard and risk. A heuristic model was applied to a rural municipality in eastern Cuba. The study is based on a terrain mapping units (TMU) map, generated at 1:50,000 scale by interpretation of aerial photos, satellite images and field data. Information describing 603 terrain units was collected in a database. Landslide areas were mapped in detail to classify the different failure types and parts. Three major landslide regions are recognized in the study area: coastal hills with rockfalls, shallow debris flows and old rotational rockslides denudational slopes in limestone, with very large deep-seated rockslides related to tectonic activity and the Sierra de Caujerí scarp, with large rockslides. The Caujerí scarp presents the highest hazard, with recent landslides and various signs of active processes. The different landforms and the causative factors for landslides were analyzed and used to develop the heuristic model. The model is based on weights assigned by expert judgment and organized in a number of components such as slope angle, internal relief, slope shape, geological formation, active faults, distance to drainage, distance to springs, geomorphological subunits and existing landslide zones. From these variables a hierarchical heuristic model was applied in which three levels of weights were designed for classes, variables, and criteria. The model combines all weights into a single hazard value for each pixel of the landslide hazard map. The hazard map was then divided by two scales, one with three classes for disaster managers and one with 10 detailed hazard classes for technical staff. The range of weight values and the number of existing landslides is registered for each class. The resulting increasing landslide density with higher hazard classes indicates that the output map is reliable. The landslide hazard map was used in combination with existing information on buildings and infrastructure to prepare a qualitative risk map. The complete lack of historical landslide information and geotechnical data precludes the development of quantitative deterministic or probabilistic models.  相似文献   

8.
GIS and ANN model for landslide susceptibility mapping   总被引：4，自引：0，他引：4  
1 IntroductionThe population growth and the expansion of settlements and life-lines over hazardous areas exert increasingly great impact of natural disasters both in the developed and developing countries. In many countries, the economic losses and casualties due to landslides are greater than commonly recognized and generate a yearly loss of property larger than that from any other natural disasters, including earthquakes, floods and windstorms. Landslides in mountainous terrain often occur a…  相似文献   

9.
During the last decade, slope failures were reported in a 500 km2 study area in the Geba–Werei catchment, northern Ethiopia, a region where landslides were not considered an important hazard before. Field observations, however, revealed that many of the failures were actually reactivations of old deep-seated landslides after land use changes. Therefore, this study was conducted (1) to explore the importance of environmental factors controlling landslide occurrence and (2) to estimate future landslide susceptibility. A landslide inventory map of the study area derived from aerial photograph interpretation and field checks shows the location of 57 landslides and six zones with multiple landslides, mainly complex slides and debris flows. In total 14.8% of the area is affected by an old landslide. For the landslide susceptibility modelling, weights of evidence (WofE), was applied and five different models were produced. After comparison of the models and spatial validation using Receiver Operating Characteristic curves and Kappa values, a model combining data on elevation, hillslope gradient, aspect, geology and distance to faults was selected. This model confirmed our hypothesis that deep-seated landslides are located on hillslopes with a moderate slope gradient (i.e. 5°–13°). The depletion areas are expected on and along the border of plateaus where weathered basalts rich in smectite clays are found, and the landslide debris is expected to accumulate on the Amba Aradam sandstone and upper Antalo limestone. As future landslides are believed to occur on inherently unstable hillslopes similar to those where deep-seated landslides occurred, the classified landslide susceptibility map allows delineating zones where human interventions decreasing slope stability might cause slope failures. The results obtained demonstrate that the applied methodology could be used in similar areas where information on the location of landslides is essential for present-day hazard analysis.  相似文献   

10.
A landslide-hazard map is intended to show the location of future slope instability. Most spatial models of the hazard lack reliability tests of the procedures and predictions for estimating the probabilities of future landslides, thus precluding use of the maps for probabilistic risk analysis. To correct this deficiency we propose a systematic procedure comprising two analytical steps: “relative-hazard mapping” and “empirical probability estimation”. A mathematical model first generates a prediction map by dividing an area into “prediction” classes according to the relative likelihood of occurrence of future landslides, conditional by local geomorphic and topographic characteristics. The second stage estimates empirically the probability of landslide occurrence in each prediction class, by applying a cross-validation technique. Cross-validation, a “blind test” here using non-overlapping spatial or temporal subsets of mapped landslides, evaluates accuracy of the prediction and from the resulting statistics estimates occurrence probabilities of future landslides. This quantitative approach, exemplified by several experiments in an area near Lisbon, Portugal, can accommodate any subsequent analysis of landslide risk.  相似文献   

11.
This paper proposes a statistical decision-tree model to analyze landslide susceptibility in a wide area of the Akaishi Mountains, Japan. The objectives of this study were to validate the decision-tree model by comparing landslide susceptibility and actual landslide occurrence, and to reveal the relationships among landslide occurrence, topography, and geology. Landslide susceptibility was examined through ensemble learning with a decision tree. Decision trees are advantageous in that estimation processes and order of important explanatory variables are explicitly represented by the tree structures. Topographic characteristics (elevation, slope angle, profile curvature, plan curvature, and dissection and undissection height) and geological data were used as the explanatory variables. These topographic characteristics were calculated from digital elevation models (DEMs). The objective variables were landslide occurrence and reactivation data between 1992 and 2002 that were depicted by satellite image analysis. Landslide susceptibility was validated by comparing actual data on landslides that occurred and reactivated after the model was constructed (between 2002 and 2004).This study revealed that, from 2002 to 2004, landslides tended to occur and reactivate in catchments with high landslide susceptibility. The landslide susceptibility map thus depicts the actual landslide occurrence and reactivation in the Akaishi Mountains. This result indicates that the decision-tree model has appropriate accuracy for estimating the probabilities of future landslides. The tree structure indicates that landslides occurred and reactivated frequently in the catchments that had an average slope angle exceeding ca. 29° and a mode of slope angle exceeding 33°, which agree well with previous studies. A decision tree also quantitatively expresses important explanatory variables at the higher order of the tree structure.  相似文献   

12.
Landslides triggered by rainfall are the cause of thousands of deaths worldwide every year. One possible approach to limit the socioeconomic consequences of such events is the development of climatic thresholds for landslide initiation. In this paper, we propose a method that incorporates antecedent rainfall and streamflow data to develop a landslide initiation threshold for the North Shore Mountains of Vancouver, British Columbia. Hydroclimatic data were gathered for 18 storms that triggered landslides and 18 storms that did not. Discriminant function analysis separated the landslide-triggering storms from those storms that did not trigger landslides and selected the most meaningful variables that allow this separation. Discriminant functions were also developed for the landslide-triggering and nonlandslide-triggering storms. The difference of the discriminant scores, ΔCS, for both groups is a measure of landslide susceptibility during a storm. The variables identified that optimize the separation of the two storm groups are 4-week rainfall prior to a significant storm, 6-h rainfall during a storm, and the number of hours 1 m3/s discharge was exceeded at Mackay Creek during a storm. Three thresholds were identified. The Landslide Warning Threshold (LWT) is reached when ΔCS is −1. The Conditional Landslide Initiation Threshold (CTLI) is reached when ΔCS is zero, and it implies that landslides are likely if 4 mm/h rainfall intensity is exceeded at which point the Imminent Landslide Initiation Threshold (ITLI) is reached. The LWT allows time for the issuance of a landslide advisory and to move personnel out of hazardous areas. The methodology proposed in this paper can be transferred to other regions worldwide where type and quality of data are appropriate for this type of analysis.  相似文献   

13.
Landslides are frequent natural disasters in mountainous regions, particularly in the Himalayas in India during the southwest monsoon season. Although scientific study of landslides has been in progress for years, no significant achievement has been made to preclude landsliding and allay disasters. This research was undertaken to understand the areal distribution of landslides based on geological formations and geomorphological processes, and to provide more precise information regarding slope instability and mechanisms of failure. After completing a landslide inventory, prepared through field investigation and satellite image analysis, 493 landslides, comprising 131 investigated in the field and 362 identified from satellite imagery, were identified and mapped. The areal distribution of these landslides shows that sites more prone to landsliding have moderate to steep slopes, the lithology of the Lesser Himalayan formations, and excavations for road corridors. Landslide susceptibility zones were delineated for the area using the weight-of-evidence method on the basis of the frequency and distribution of landslides. Weights of selected variables were computed on the basis of severity of triggering factors. The accuracy of landslide susceptibility zones, calculated statistically (R2 = .93), suggests high accuracy of the model for predicting landsliding in the area.  相似文献   

14.
ABSTRACT

An attempt is made to explain the relationship of landslides to litho-tectonic and precipitation regimes. The possible influence of these factors on the dimensional pattern of landslides is also inferred. The Yamuna River valley, NW Himalaya, which traverses the Higher Himalaya (HH) and Lesser Himalaya (LH) rock mass, endures disastrous landslides and hence is taken as the case for study. To achieve the objectives, proxies like stream length gradient, topographic profile, steepness index, and ratio of valley floor width to valley height were used to infer a spatially varying tectonic regime, whereas rainfall data and Normalized Difference Vegetation Index were used to determine spatial differences in precipitation and vegetation variability, respectively. Dimensional patterns of landslides utilized the landslide area and volume. The higher reaches of the HH and lowest part of the LH show rockfall dominance associated with relatively high tectonic activity, whereas most of the debris slides coincide with regional thrusts. Total area and volume occupied by the landslides are ~1.5 ± 0.16 × 106 m2 and ~4.7 ± 1.2 × 106 m3, respectively. Dimensions of debris slides were found to be less influenced by the litho-tectonic and precipitation regimes, whereas the dimensions of rockfalls were found to be more sensitive to these conditions.  相似文献   

15.
Comparing landslide inventory maps   总被引：10，自引：1，他引：9  
Landslide inventory maps are effective and easily understandable products for both experts, such as geomorphologists, and for non experts, including decision-makers, planners, and civil defense managers. Landslide inventories are essential to understand the evolution of landscapes, and to ascertain landslide susceptibility and hazard. Despite landslide maps being compiled every year in the word at different scales, limited efforts are made to critically compare landslide maps prepared using different techniques or by different investigators. Based on the experience gained in 20 years of landslide mapping in Italy, and on the limited literature on landslide inventory assessment, we propose a general framework for the quantitative comparison of landslide inventory maps. To test the proposed framework we exploit three inventory maps. The first map is a reconnaissance landslide inventory prepared for the Umbria region, in central Italy. The second map is a detailed geomorphological landslide map, also prepared for the Umbria region. The third map is a multi-temporal landslide inventory compiled for the Collazzone area, in central Umbria. Results of the experiment allow for establishing how well the individual inventories describe the location, type and abundance of landslides, to what extent the landslide maps can be used to determine the frequency-area statistics of the slope failures, and the significance of the inventory maps as predictors of landslide susceptibility. We further use the results obtained in the Collazzone area to estimate the quality and completeness of the two regional landslide inventory maps, and to outline general advantages and limitations of the techniques used to complete the inventories.  相似文献   

16.
在对金沙江流域内的部分大型水电站工程区内的滑坡分析基础上,以两个滑坡为例,针对水电站工程区讨论了单体滑坡的风险评价方法。选取滑坡稳定性,规模和可能造成的涌浪高度3个指标进行危险性评价;并且定性地将大坝的易损性确定为高、中、低三个等级。在此基础上,对研究区的牛滚函滑坡和东岳庙滑坡进行了危险性分析和易损性评价,得出这两个单体滑坡的风险分析结果：牛滚函滑坡为低度风险,东岳庙滑坡为中度风险。研究成果为水电站工程区滑坡减灾防灾与风险管理提供了科学依据。  相似文献   

17.
Sanjit K. Deb  Aly I. El-Kadi   《Geomorphology》2009,108(3-4):219-233
The deterministic Stability INdex MAPping (SINMAP) model, which integrates a mechanistic infinite-slope stability model and a hydrological model, was applied to assess susceptibility of slopes in 32 shallow-landslide-prone watersheds of the eastern to southern areas of Oahu, Hawaii, USA. Input to the model includes a 10-m Digital Elevation Model (DEM), an inventory of storm-induced landslides that occurred from 1949 to 2006, and listings of soil-strength and hydrological parameters including transmissivity and steady-state recharge. The study area of ca. 384 km2 was divided into four calibration regions with different geotechnical and hydrological characteristics. All parameter values were separately calibrated using observed landslides as references. The study used a quasi-dynamic scenario of soil wetness resulting from extreme daily rainfall events with a return period of 50 years. The return period was based on almost-90-year-long (1919–2007) daily rainfall records from 26 raingauge stations in the study area. Output of the SINMAP model includes slope-stability-index-distribution maps, slope-versus-specific-catchment-area charts, and statistical summaries for each region.The SINMAP model assessed susceptibility at the locations of all 226 observed shallow landslides and classified these susceptible areas as unstable. About 55% of the study area was predicted as highly unstable, highlighting a critical island problem. The SINMAP predictions were compared to an existing debris-flow-hazard map. Areas classified as unstable in the current study were classified as low-to-moderate and moderate-to-high debris-flow hazard risks by the prior mapping. The slope-stability maps provided by this study will aid in explaining the causes of known landslides, making emergency decisions, and, ultimately mitigating future landslide risks. The maps may be further improved by incorporating heterogeneous and anisotropic soil properties and spatial and temporal variation of rainfalls as well as by improving the accuracy of the DEM and the locations of shallow landslide initiation.  相似文献   

18.
This paper presents a statistical approach to study the spatial relationship between landslides and their causative factors at the regional level. The approach is based on digital databases, and incorporates such methods as statistics, spatial pattern analysis, and interactive mapping. Firstly, the authors propose an object-oriented conceptual model for describing a landslide event, and a combined database of landslides and environmental factors is constructed by integrating the various databases within such a conceptual framework. The statistical histogram, spatial overlay, and dynamic mapping methods are linked together to interactively evaluate the spatial pattern of the relationship between landslides and their causative factors. A case study of an extreme event in 1993 on Lantau Island indicates that rainfall intensity and the migration of the center of the rainstorm greatly influence the occurrence of landslides on Lantau Island. A regional difference in the relationship between landslides and topography is identified. Most of the landslides in the middle and western parts of the island occurred on slopes with slope angles of 25–35°, while in the eastern part, the corresponding range is 30–35°. Overlaying landslide data with land cover reveals that a large number of landslides occurred in the bareland and shrub-covered area, and in the transition zones between different vegetation types. The proposed approach can be used not only to analyze the general characteristics of such a relationship, but also to depict its spatial distribution and variation, thereby providing a sound basis for regional landslide prediction.  相似文献   

19.
Considering damage to man-made structures by natural hazards in Turkey, landslides are the second most important hazard after earthquakes. For this reason, a large-scale study titled Turkish Landslide Inventory Project, has been carried out since 1998. During this project, some special, susceptibility, hazard and risk assessments have been performed. In this study, a landslide susceptibility map of a part of tectonic Kelkit Valley in the north of central Turkey was produced, employing binary logistic regression analyses. To achieve the most appropriate results some sensitivity analyses were also carried out. For this purpose, four different data sets were constructed considering conditioning factors used and sampling strategies applied for the training data sets in this study. As a consequence of the analyses, the most proper outcomes were obtained by using the data set in which continuous topographical parameters and lithological dummy variables were implemented together and 50% of training data set was taken from seed cells at random. Correct classification percentage and Root Mean Square Error (RMSE) values for the validation data for that case were estimated as 84.16% and 0.36, respectively. This prediction capability shows that the landslide susceptibility map produced in this research paper can be used for the planning of protective and mitigation measures in the region.  相似文献   

20.
Monitoring and assessment of landslide hazard is an important task for decision making and policy planning in the landslide area. Massive landslides, caused by the catastrophic Chi‐Chi earthquake in 1999, occurred in Central Taiwan, especially at Chiufenershan area in Nantou county. This study proposed two useful indicators coupled with the Self‐organizing map (SOM) neural network and the Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE) technique to quickly extract accurate post‐quake landslides from multi‐temporal Système Probatoire de l'Observation de la Terre (SPOT) images. A GIS‐based system was developed to simplify and integrate the procedures such as image pre‐processing, the SOM training, the PROMETHEE calculation, landslide extraction and accuracy assessment. The evaluated result shows that the landslide area soon after the earthquake is 209.50 ha (Kappa coefficient 96.88%). Over seven years of vegetation recovery, the denudation area has declined to 112.64 ha (Kappa coefficient 90.64%). Most earthquake‐induced landslides could be restored by natural vegetation succession. The developed system is a useful decision‐making tool for landslide area planning.  相似文献   

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