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1.
The increasing availability of remotely sensed data offers a new opportunity to address landslide hazard assessment at larger spatial scales. A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that may experience landslide activity. This system combines a calculation of static landslide susceptibility with satellite-derived rainfall estimates and uses a threshold approach to generate a set of ‘nowcasts’ that classify potentially hazardous areas. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale near real-time landslide hazard assessment efforts, it requires several modifications before it can be fully realized as an operational tool. This study draws upon a prior work’s recommendations to develop a new approach for considering landslide susceptibility and hazard at the regional scale. This case study calculates a regional susceptibility map using remotely sensed and in situ information and a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America. The susceptibility map is evaluated with a regional rainfall intensity–duration triggering threshold and results are compared with the global algorithm framework for the same event. Evaluation of this regional system suggests that this empirically based approach provides one plausible way to approach some of the data and resolution issues identified in the global assessment. The presented methodology is straightforward to implement, improves upon the global approach, and allows for results to be transferable between regions. The results also highlight several remaining challenges, including the empirical nature of the algorithm framework and adequate information for algorithm validation. Conclusions suggest that integrating additional triggering factors such as soil moisture may help to improve algorithm performance accuracy. The regional algorithm scenario represents an important step forward in advancing regional and global-scale landslide hazard assessment.  相似文献   

2.
The key to advancing the predictability of rainfall-triggered landslides is to use physically based slope-stability models that simulate the transient dynamical response of the subsurface moisture to spatiotemporal variability of rainfall in complex terrains. TRIGRS (transient rainfall infiltration and grid-based regional slope-stability analysis) is a USGS landslide prediction model, coded in Fortran, that accounts for the influences of hydrology, topography, and soil physics on slope stability. In this study, we quantitatively evaluate the spatiotemporal predictability of a Matlab version of TRIGRS (MaTRIGRS) in the Blue Ridge Mountains of Macon County, North Carolina where Hurricanes Ivan triggered widespread landslides in the 2004 hurricane season. High resolution digital elevation model (DEM) data (6-m LiDAR), USGS STATSGO soil database, and NOAA/NWS combined radar and gauge precipitation are used as inputs to the model. A local landslide inventory database from North Carolina Geological Survey is used to evaluate the MaTRIGRS’ predictive skill for the landslide locations and timing, identifying predictions within a 120-m radius of observed landslides over the 30-h period of Hurricane Ivan’s passage in September 2004. Results show that within a radius of 24 m from the landslide location about 67% of the landslide, observations could be successfully predicted but with a high false alarm ratio (90%). If the radius of observation is extended to 120 m, 98% of the landslides are detected with an 18% false alarm ratio. This study shows that MaTRIGRS demonstrates acceptable spatiotemporal predictive skill for landslide occurrences within a 120-m radius in space and a hurricane-event-duration (h) in time, offering the potential to serve as a landslide warning system in areas where accurate rainfall forecasts and detailed field data are available. The validation can be further improved with additional landslide information including the exact time of failure for each landslide and the landslide’s extent and run out length.  相似文献   

3.
An early warning system has been developed to predict rainfall-induced shallow landslides over Java Island, Indonesia. The prototyped early warning system integrates three major components: (1) a susceptibility mapping and hotspot identification component based on a land surface geospatial database (topographical information, maps of soil properties, and local landslide inventory, etc.); (2) a satellite-based precipitation monitoring system () and a precipitation forecasting model (i.e., Weather Research Forecast); and (3) a physically based, rainfall-induced landslide prediction model SLIDE. The system utilizes the modified physical model to calculate a factor of safety that accounts for the contribution of rainfall infiltration and partial saturation to the shear strength of the soil in topographically complex terrains. In use, the land-surface “where” information will be integrated with the “when” rainfall triggers by the landslide prediction model to predict potential slope failures as a function of time and location. In this system, geomorphologic data are primarily based on 30-m Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, digital elevation model (DEM), and 1-km soil maps. Precipitation forcing comes from both satellite-based, real-time National Aeronautics and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM), and Weather Research Forecasting (WRF) model forecasts. The system’s prediction performance has been evaluated using a local landslide inventory, and results show that the system successfully predicted landslides in correspondence to the time of occurrence of the real landslide events. Integration of spatially distributed remote sensing precipitation products and in-situ datasets in this prototype system enables us to further develop a regional, early warning tool in the future for predicting rainfall-induced landslides in Indonesia.  相似文献   

4.
The article deals with a tool for landslides susceptibility assessment as a function of the hydrogeological setting at different scales. The study has been applied to a test area located in Southern Italy. First, a 3D groundwater flow model was implemented for a large-scale area. The simulation of several groundwater conditions compared with the landslide activity map allows drawing a hydrogeological susceptibility map. Then, a slope scale analysis was carried out for the Cavallerizzo landslide. For this purpose, a 2D groundwater parametrical modeling was coupled with a slope stability analysis; the simulation was carried out by changing the values of the main hydrogeological parameters (recharge, groundwater supply level, etc.). The results enabled to connect the slope instability to some hydrogeological characteristics that are easy to survey and to monitor (e.g., rainfall, piezometrical level, and spring discharge), pointing out the hazard thresholds with regards to different triggering phenomena.  相似文献   

5.
采用基于网格的瞬态降雨入渗(TRIGRS)模型,以滑坡灾害频发的陕南安康市东部巴山东段白河县为研究区,探讨模型适用性及不同降雨条件下边坡稳定性空间分布规律。根据中国土壤分布图并结合已有研究,选取模拟所需的水土力学参数。将模拟所得研究区稳定性分布图与实际滑坡目录对比分析进行TRIGRS模型精度评估,分别模拟连阴雨和短时间强降雨两种降雨情景,探讨研究区边坡稳定性空间分布规律,结果表明:1)TRIGRS模型在模拟预测降雨诱发型浅层滑坡时,结合受试者特征ROC曲线进行精度评估,曲线下面积为0.752,说明此模型在白河县进行滑坡模拟时具有一定的合理性与准确性,能反应该地区滑坡灾害的空间分布特征;2)连阴雨情景模拟下,极不稳定区域主要集中在北部低山地貌区,以冷水镇和麻虎镇为主,随降雨历时增加向东部和南部增多,西部仓上镇、西营镇和双丰镇的极不稳定区域面积较少,能承受长时间连续性降雨。短时间强降雨对边坡稳定性的影响更为直接,极不稳定区域随降雨强度增大而增加,以冷水镇和麻虎镇为主要防范区域。结合地形分析,极陡峭区域边坡稳定性最差,无法承受持续性降雨和高强度降雨,较陡峭区域更易受到降雨历时和降雨强度的影响,而平缓区域则能承受长时间及高强度的降雨;3)TRIGRS模型根据不同降雨条件预测易发生滑坡灾害的区域,为滑坡实时预报警系统提供了新的可能方法。  相似文献   

6.
This paper describes the potential applicability of a hydrological–geotechnical modeling system using satellite-based rainfall estimates for a shallow landslide prediction system. The physically based distributed model has been developed by integrating a grid-based distributed kinematic wave rainfall-runoff model with an infinite slope stability approach. The model was forced by the satellite-based near real-time half-hourly CMORPH global rainfall product prepared by NOAA-CPC. The method combines the following two model outputs necessary for identifying where and when shallow landslides may potentially occur in the catchment: (1) the time-invariant spatial distribution of areas susceptible to slope instability map, for which the river catchment is divided into stability classes according to the critical relative soil saturation; this output is designed to portray the effect of quasi-static land surface variables and soil strength properties on slope instability and (2) a produced map linked with spatiotemporally varying hydrologic properties to provide a time-varying estimate of susceptibility to slope movement in response to rainfall. The proposed hydrological model predicts the dynamic of soil saturation in each grid element. The stored water in each grid element is then used for updating the relative soil saturation and analyzing the slope stability. A grid of slope is defined to be unstable when the relative soil saturation becomes higher than the critical level and is the basis for issuing a shallow landslide warning. The method was applied to past landslides in the upper Citarum River catchment (2,310 km2), Indonesia; the resulting time-invariant landslide susceptibility map shows good agreement with the spatial patterns of documented historical landslides (1985–2008). Application of the model to two recent shallow landslides shows that the model can successfully predict the effect of rainfall movement and intensity on the spatiotemporal dynamic of hydrological variables that trigger shallow landslides. Several hours before the landslides, the model predicted unstable conditions in some grids over and near the grids at which the actual shallow landslides occurred. Overall, the results demonstrate the potential applicability of the modeling system for shallow landslide disaster predictions and warnings.  相似文献   

7.
The objective of this study is to explore and compare the least square support vector machine (LSSVM) and multiclass alternating decision tree (MADT) techniques for the spatial prediction of landslides. The Luc Yen district in Yen Bai province (Vietnam) has been selected as a case study. LSSVM and MADT are effective machine learning techniques of classification applied in other fields but not in the field of landslide hazard assessment. For this, Landslide inventory map was first constructed with 95 landslide locations identified from aerial photos and verified from field investigations. These landslide locations were then divided randomly into two parts for training (70 % locations) and validation (30 % locations) processes. Secondly, landslide affecting factors such as slope, aspect, elevation, curvature, lithology, land use, distance to roads, distance to faults, distance to rivers, and rainfall were selected and applied for landslide susceptibility assessment. Subsequently, the LSSVM and MADT models were built to assess the landslide susceptibility in the study area using training dataset. Finally, receiver operating characteristic curve and statistical index-based evaluations techniques were employed to validate the predictive capability of these models. As a result, both the LSSVM and MADT models have high performance for spatial prediction of landslides in the study area. Out of these, the MADT model (AUC = 0.853) outperforms the LSSVM model (AUC = 0.803). From the landslide study of Luc Yen district in Yen Bai province (Vietnam), it can be conclude that the LSSVM and MADT models can be applied in other areas of world also for and spatial prediction. Landslide susceptibility maps obtained from this study may be helpful in planning, decision making for natural hazard management of the areas susceptible to landslide hazards.  相似文献   

8.
A landslide database for Nicaragua: a tool for landslide-hazard management   总被引：3，自引：1，他引：3  
A digital landslide database has been created for Nicaragua to provide the scientific community and national authorities with a tool for landslide-hazard assessment, emergency management, land-use planning, development of early warning systems, and the implementation of public and private policies. The Instituto Nicaragüense de Estudios Territoriales (Nicaraguan Geosciences Institute, INETER) began to compile the database in a digital format in 2003 as part of a comprehensive geographical information system for all types of geohazards. Landslide data have been obtained from a variety of sources including newspapers, technical reports, and landslide inventory maps. Inventory maps are largely based on fieldwork and aerial-photo analyses conducted by foreign development agencies in collaboration with INETER and other Nicaraguan institutions. This paper presents the sources of landslide information, introduces the database, and presents the first analyses of the data at national and regional scales. The database currently contains spatial information for about 17,000 landslides that occurred in mountainous and volcanic terrains. Information is mainly recorded for the period 1826–2003, with a large number of events that occurred during the disastrous Hurricane Mitch in October 1998. The oldest historical event is dated at 1570, some events are recorded as prehistorical, and other events have unknown dates of occurrence. Debris flows have been the most common types of landslides, both in volcanic and nonvolcanic areas, but other types, including rockfalls and slides, have also been identified. Intense and prolonged rainfall, often associated with tropical cyclones, and seismic and volcanic activity represent the most important landslide triggers. At a regional scale, the influence of topographic (elevation, slope angle, slope aspect) and lithologic parameters on the occurrence of landslides was analyzed. The development of the database allowed us to define the state of knowledge on landslide processes in the Nicaragua and to provide a preliminary identification of areas affected by landslides.  相似文献   

9.
This paper is focussed on the hazard impact of landslides in the Three Gorges, and represents the progression of our ongoing study on regional land instability assessment in the Three Gorges area using imagery data from the Advanced Spaceborne Thermal Emission Radiometer (ASTER). The key development here is the establishment of a model that integrates land instability with several factors that can relate hazard to human life, such as slope failures occurring in proximity to built-up areas and roads, and areas of high landslide risk along the bank of Yangtze and its major tributaries. The method correctly identifies some of the known destructive landslides in the region, like Qianjiangping and Huangtupo, as belonging to areas of potentially high landslide impact. Our results suggest that several population centres, including the towns of Wushan and Badong, are rated at high landslide hazard levels. This study highlights the importance of differentiating between landslide types within susceptibility assessment, and identifies those locations in the Three Gorges where the probability of landslide occurrence with negative impact to life and property is greatest.  相似文献   

10.
黄土丘陵地区地质环境脆弱,每到雨季极易诱发浅层黄土滑坡,对居民的生命和财产安全构成威胁也阻碍着当地经济的发展。对浅层滑坡进行稳定性评价,不仅有助于认识浅层滑坡的发生发展过程,而且对防灾减灾和地区规划建设具有十分重要的指导意义。本研究选择SINMAP模型作为评价浅层黄土滑坡的重要工具,评价了陕西省延安市志丹县黄土丘陵区浅层滑坡的稳定性,评价结果表明:1)研究区整体稳定性程度较高,在降雨量为8.6 mm、15 mm、25 mm、50 mm和100 mm时不稳定区域(包括极不稳定、不稳定和潜在不稳定)面积分别占研究区总面积的9.12%、18.93%、23.17%、30.94%和38.67%,不稳定区域的面积不超过整个研究区面积的一半,极不稳定区域的滑坡密度最大,其次为不稳定区域和潜在不稳定区域;2)随着降雨量的增大,潜在不稳定和不稳定区域的面积会逐渐扩大,极不稳定区始终位于坡度大且水流侵蚀强烈的地方,变化幅度小;3)浅层滑坡的稳定性很大程度上依赖于当地的地形条件:坡度分布为20°~51°,高程分布范围为1302~1606 m,在坡向上阴坡的发生数量多于阳坡,西向和西北向浅层滑坡最为发育;4)流域内的滑坡多属降雨诱发的山体滑坡,确定性模型SINMAP为预测这一类滑坡提供了强大的工具,不仅评估了现有的已发生的滑坡的稳定性,也预测了未来在不同降雨条件下可能发生滑坡的地区。分析结果可为预防和减轻滑坡灾害带来的损失,合理的城市规划和道路选址等提供参考。  相似文献   

11.
In Taiwan, the hillside is about 70 % of total area. These areas also have steep topography and geological vulnerability. When an event of torrential rain comes during a typhoon, the landslide disasters usually occur at these areas due to the long duration and high intensity of rainfall. Therefore, a design which considers the potential landslide has become an important issue in Taiwan. In this study, a temporal characteristic of landslide fragility curve (LFC) was developed, based on the geomorphological and vegetation factors using landslides at the Chen-Yu-Lan watershed in Taiwan, during Typhoon Sinlaku (September 2008) and Typhoon Morakot (August 2009). This study addressed an effective landslide hazard assessment process, linking together the post-landslide damage and post-rainfall data for LFC model. The Kriging method was used to interpolate the rainfall indices (R 0, R, I) for numerical analysis. Remote sensing data from SPOT images were applied to analyze the landslide ratio and vegetation conditions. The 40-m digital elevation model was used for slope variation analysis in the watershed, and the maximum likelihood estimate was conducted to determine the mean and standard deviation parameters of the proposed empirical LFC model. This empirical model can express the probability of exceeding a damage state for a certain classification (or conditions) of landslides by considering a specific hazard index for a given event. Finally, the vulnerability functions can be used to assess the loss from landslides, and, in the future, to manage the risk of debris flow in the watershed.  相似文献   

12.
黄土高原是我国地质灾害最为发育的地区之一,其中降雨诱发的浅层黄土滑坡又最为典型。以典型黄土地貌区-柳林县为例,应用SINMAP模型,探讨模型在黄土地区的适用性,分析了随着研究区内降雨量的增加,滑坡变形失稳区域的面积变化、分布位置和扩展趋势。研究表明,随着降雨量的增加,滑坡所处位置逐渐由稳定状态向失稳状态发展,位于失稳分区的滑坡数量逐渐增加,说明降雨对该研究区的斜坡稳定性影响较为明显。通过将模拟结果与实际发生的由降雨触发的滑坡灾害进行对比分析,可以得出SINMAP模型在黄土地区,对区域性降雨诱发浅层黄土滑坡稳定性的模拟预测有效,可以用于黄土地区浅层滑坡的稳定性评价研究。  相似文献   

13.
Liu  Chun  Li  Weiyue  Wu  Hangbin  Lu  Ping  Sang  Kai  Sun  Weiwei  Chen  Wen  Hong  Yang  Li  Rongxing 《Natural Hazards》2013,69(3):1477-1495

Landslides are occurring more frequently in China under the conditions of extreme rainfall and changing climate, according to News reports. Landslide hazard assessment remains an international focus on disaster prevention and mitigation, and it is an important step for compiling and quantitatively characterizing landslide damages. This paper collected and analyzed the historical landslide events data of the past 60 years in China. Validated by the frequencies and distributions of landslides, nine key factors (lithology, convexity, slope gradient, slope aspect, elevation, soil property, vegetation coverage, flow, and fracture) are selected to construct landslide susceptibility (LS) empirical models by back-propagation artificial neural network method. By integrating landslide empirical models with surface multi-source geospatial and remote sensing data, this paper further performs a large-scale LS assessment throughout China. The resulting landslide hazard assessment map of China clearly illustrates the hot spots of the high landslide potential areas, mostly concentrated in the southwest. The study implements a complete framework of multi-source data collecting, processing, modeling, and synthesizing that fulfills the assessment of LS and provides a theoretical basis and practical guide for predicting and mitigating landslide disasters potentially throughout China.

  相似文献   

14.
Loss of life and property caused by landslides triggered by extreme rainfall events demonstrates the need for landslide-hazard assessment in developing countries where recovery from such events often exceeds the country's resources. Mapping landslide hazards in developing countries where the need for landslide-hazard mitigation is great but the resources are few is a challenging, but not intractable problem. The minimum requirements for constructing a physically based landslide-hazard map from a landslide-triggering storm, using the simple methods we discuss, are: (1) an accurate mapped landslide inventory, (2) a slope map derived from a digital elevation model (DEM) or topographic map, and (3) material strength properties of the slopes involved. Provided that the landslide distribution from a triggering event can be documented and mapped, it is often possible to glean enough topographic and geologic information from existing databases to produce a reliable map that depicts landslide hazards from an extreme event. Most areas of the world have enough topographic information to provide digital elevation models from which to construct slope maps. In the likely event that engineering properties of slope materials are not available, reasonable estimates can be made with detailed field examination by engineering geologists or geotechnical engineers. Resulting landslide hazard maps can be used as tools to guide relocation and redevelopment, or, more likely, temporary relocation efforts during severe storm events such as hurricanes/typhoons to minimize loss of life and property. We illustrate these methods in two case studies of lethal landslides in developing countries: Tegucigalpa, Honduras (during Hurricane Mitch in 1998) and the Chuuk Islands, Micronesia (during Typhoon Chata'an in 2002).  相似文献   

15.
The crucial and difficult task in landslide susceptibility analysis is estimating the probability of occurrence of future landslides in a study area under a specific set of geomorphic and topographic conditions. This task is addressed with a data-driven probabilistic model using likelihood ratio or frequency ratio and is applied to assess the occurrence of landslides in the Tevankarai Ar sub-watershed, Kodaikkanal, South India. The landslides in the study area are triggered by heavy rainfall. Landslide-related factors—relief, slope, aspect, plan curvature, profile curvature, land use, soil, and topographic wetness index proximity to roads and proximity to lineaments—are considered for the study. A geospatial database of the related landslide factors is constructed using Arcmap in GIS environment. Landslide inventory of the area is produced by detailed field investigation and analysis of the topographical maps. The results are validated using temporal data of known landslide locations. The area under the curve shows that the accuracy of the model is 85.83%. In the reclassified final landslide susceptibility map, 14.48% of the area is critical in nature, falling under the very high hazard zone, and 67.86% of the total validation dataset landslides fall in this zone. This landslide susceptibility map is a vital tool for town planning, land use, and land cover planning and to reduce risks caused by landslides.  相似文献   

16.
Although intense rainfall and localized flooding occurred as Hurricane Isabel tracked inland northwestardly across the Blue Ridge Mountains of central Virginia on September 18–19, 2003, few landslides occurred. However, the hurricane reactivated a dormant landslide along a bluff of an incised alluvial fan along Meadow Run on the western flanks of the Blue Ridge Mountains. Subsequent monitoring showed retrogressive movement involving several landslide blocks for the next several months. Using dendrochronology, aerial photography, and stream discharge records revealed periods of landslide activity. The annual variation of growth rings on trees within the landslide suggested previous slope instability in 1937, 1972, 1993, 1997, and 1999, which correlated with periods of local flood events. The avulsive and migrating nature of Meadow Run, combined with strong erosional force potential during flood stages, indicates that landslides are common along the bluff-channel bank interface, locally posing landslide hazards to relatively few structures within this farming region.  相似文献   

17.
For the assessment of shallow landslides triggered by rainfall, the physically based model coupling the infinite slope stability analysis with the hydrological modeling in nearly saturated soil has commonly been used due to its simplicity. However, in that model the rainfall infiltration in unsaturated soil could not be reliably simulated because a linear diffusion-type Richards’ equation rather than the complete Richards’ equation was used. In addition, the effect of matric suction on the shear strength of soil was not actually considered. Therefore, except the shallow landslide in saturated soil due to groundwater table rise, the shallow landslide induced by the loss in unsaturated shear strength due to the dissipation of matric suction could not be reliably assessed. In this study, a physically based model capable of assessing shallow landslides in variably saturated soils is developed by adopting the complete Richards’ equation with the effect of slope angle in the rainfall infiltration modeling and using the extended Mohr–Coulomb failure criterion to describe the unsaturated shear strength in the soil failure modeling. The influence of rainfall intensity and duration on shallow landslide is investigated using the developed model. The result shows that the rainfall intensity and duration seem to have similar influence on shallow landslides respectively triggered by the increase of positive pore water pressure in saturated soil and induced by the dissipation of matric suction in unsaturated soil. The rainfall duration threshold decreases with the increase in rainfall intensity, but remains constant for large rainfall intensity.  相似文献   

18.
基于实例推理系统的滑坡预警判据研究   总被引：1，自引：0，他引：1  
为研究滑坡预警预报指标,建立了31个典型岩质滑坡组成的滑坡数据库,基于滑坡数据库、工程类比和模糊综合评判方法开发了滑坡实例推理系统。首先将滑坡特征属性分为6大项:破坏模式、滑面倾角、滑面类型、边坡岩体结构、边坡倾角、滑坡的诱发因素(降雨、地下水、水库蓄水、开挖、爆破、地震),用11个特征值表示边坡的特征属性;其次采用比值法相似度计算理论在滑坡数据库中搜索与目标边坡最相似的滑坡,通过工程类比给出滑坡预警判据建议值;最后依据模糊综合评判模型修正建议值,得到预警判据确认值,形成滑坡实例推理系统。以锦屏一级水电站为例,通过计算找到了滑坡数据库中与锦屏一级水电站左岸边坡最为相似的5个滑坡实例;其中大冶铁矿狮子山滑坡和安家岭露天矿滑坡有较为完整的变形监测数据,深入分析类似边坡变形破坏过程,分4个阶段给出了锦屏一级水电站左岸边坡预警判据建议值;并建立边坡预警判据修正的模糊综合评判模型,修正相似边坡预警判据,给出锦屏一级水电站左岸边坡进入加速变形阶段的位移速率阀值的精确区间为1.0～1.2 mm/d。  相似文献   

19.
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.  相似文献   

20.
In different areas of the world, shallow landslides represent a remarkable hazard inducing fatalities and economic damages. Then, the evaluation about potential variation in frequency of such hazard under the effect of climate changes should be a priority for defining reliable adaptation measurements. Unfortunately, current performances of climate models on sub-daily scales, relevant for heavy rainfall events triggering shallow landslides, are not reliable enough to be used directly for performing slope stability analysis. In an attempt to overcome the constrains by gap in time resolution between climate and hazard models, the paper presents an integrated suitable approach for estimating future variations in shallow landslide hazard and managing the uncertainties associated with climate and sub-daily downscaling models. The approach is tested on a small basin on Amalfi coast (southern Italy). Basing on available basin scale critical rainfall thresholds, the paper outlines how the projected changes in precipitation patterns could affect local slope stability magnitude scenarios with different relevances as effect of investigated time horizon and concentration scenario. The paper concludes with qualitative evaluations on the future effectiveness of the local operative warning system in a climate change framework.  相似文献   

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