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1.
泥石流的发生受控于多种因子,而各因子属性段对泥石流的发生起到不同的作用.以甘肃南部武都地区为研究区,考虑到地震扰动影响并结合当地的地质环境条件,选取了高程、坡度、岩性、土地利用类型、滑坡点密度、地震因子、地质构造缓冲区及归一化植被指数(NDVI)等8个评价因子进行危险性评价.而后基于信息量模型和敏感性分析法对各影响因子属性类进行计算分析,得到各属性类的量化值.最后通过叠置分析,得到泥石流灾害危险性分区.结果表明,在中度、高度及极高度危险区内,信息量模型中分布的泥石流面积占研究区泥石流总面积的百分比为22.5％,24.7％,37.2％,而敏感性模型中占到的比例分别为25.5％,28.1％和36.4％.敏感性模型中中度危险区以上包含的泥石流比例占到90％,大于信息量模型的84.4％,因此,采用敏感性模型得到的危险性分区结果具有更高的精确性,能够为实际应用提供参考依据. 相似文献
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密云水库周边山区滑坡泥石流易发区预估 总被引：4，自引：1，他引：3
滑坡、泥石流等地质灾害的易发度主要是地质灾害自然属性特征的体现,它与孕灾环境的各项因子密切相关。这些因子包括地形地貌、流域水文、构造等内部条件因子以及地震、降雨等外部触发因子。为突出反映滑坡及泥石流主导因子的作用,本文参考了许多研究所采用的评价方法和因子选择,重点选取对该地区滑坡及泥石流发生区域分析评价起一定主导作用的、便于研究区域数据资料与空间资料匹配、关系密切的几个指标,包括地形地貌要素(坡度、坡向、坡形、相对高差、地貌类型)、环境要素(植被指数、河网密度、洪水淹没范围)、构造要素(距断层的距离、断层密度、地质岩性),通过对这些因子的敏感性进行分析,采用专家打分方法确定每种要素及因子的权重,借助因子加权叠加办法得出研究区地质灾害易发程度空间分布,用于表示其可能发生的统计意义上的可能性(概率),该研究对于区域地质灾害预防具有一定的适用价值。 相似文献
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自然灾害的预测预报被认为是主动减灾防灾研究中较为经济有效的方式,其中,滑坡空间预测是滑坡灾害研究的基础工作。以汶川地震重灾区北川县为研究区,选取坡度、高程、岩石类型、地震烈度、水系、道路等6个重要滑坡影响因素作为评价因子,全面分析了地震滑坡分布与各影响因子之间的统计相关性,分别采用多元回归模型与神经网络模型计算滑坡灾害敏感性指数,并进行分级和制图。结果表明,极高和高敏感区主要分布在曲山、陈家坝等乡镇,主要沿着龙门山断裂带周边地区的河流和道路呈带状分布。其中,回归模型的预测精度为73.7%,神经网络模型的预测精度为81.28%,在本区域内,神经网络模型在滑坡灾害空间预测方面更具优势。 相似文献
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基于社区的台风灾害概率风险评估——以上海市杨浦区富禄里居委地区为例 总被引：2，自引：0，他引：2
基于PGIS方法,以上海市杨浦区富禄里居委地区为案例,开展给定概率下的社区台风风险分析。结果表明,近60 a影响上海市区的台风中,最大风速大于17.2 m/s的超越概率(AEP)为12%。在此情景下,共有52幢建筑物(占全部建筑物的15.3%)有台风大风损失。上海市区最大的一次台风过程雨量达306.5 mm,其超越概率为1.8%。在该情景下,研究区地面积水最深处达0.61 m,有115幢建筑物(占全部建筑物的33.8%)有经济损失。在上述情景下,台风大风与过程雨量造成的损失对当地居民尚属可接受风险范围。 相似文献
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确定滑坡敏感性概率的空间分布,可为滑坡防治政策制定和土地利用规划提供科学依据。由于成灾环境的空间差异和滑坡机理的复杂性,基于不同逻辑架构(物理模型、理论模型等)的滑坡敏感性评价针对特定孕灾环境,无法提前确定最优数学评价模型,而基于深度学习法的、融合多种模型的混合算法能较好地解决这个问题。本文以山东省淄博市博山区为研究区域,基于单因素Logistic回归法筛选了滑坡致灾因子,通过频率比法对致灾因子进行了分级;对4种基于贝叶斯网络的改进算法(MMHC、MMPC-Tabu、Fast.iamb-Tabu、Inter.iamb-Tabu)进行验证,引入错误指数确定了建模效果最佳的算法;计算了博山区774 570个栅格的滑坡敏感性概率,绘制了博山区滑坡敏感性分布图;基于GIS的空间叠加和栅格计算器功能,对比了各模型的滑坡敏感性评价结果。研究结果表明：(1)基于Inter.iamb-Tabu开展博山区滑坡敏感性建模时效果最佳。该模型包含10个节点(9个致灾因子节点和1个结局节点)、14条有向边。研究区域可划分为极高敏感区、高敏感区、中敏感区、低敏感区和极低敏感区,分别占总面积的7.30%(49.80... 相似文献
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不完备样本条件下基于支持向量回归模型的滑坡易发性评价 总被引：2，自引：1，他引：1
区域滑坡易发性评价对灾害中长期预测预报具有重要意义,在基于统计模型进行评价过程中,样本选取对评价结果有较大影响,构建较稳健的、受样本数量影响小的分析模型非常重要。本文以马来西亚热带雨林地区为例,选择坡度、坡向、地表曲率、地貌类型、岩性、构造、土地覆盖、道路和排水系统等9大要素作为评价因子,结合支持向量回归(SVR)模型计算研究区滑坡易发性指数,并探讨不完备样本条件下易发性评价方法,分析样本数量和评价精度之间的关系。结果显示,基于SVR模型进行该区滑坡易发性分析评价,其成功率验证法的描述精度约为95.9%;同时,样本数量的增减对分析精度影响较小;SVR方法是一种适于热带雨林地区高植被覆盖条件下的分析模型,可为今后同类地区的滑坡灾害管理工作提供支持。 相似文献
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黑方台黄土滑坡类型与发育规律 总被引：3，自引：0，他引：3
20世纪60年代末期,为了安置刘家峡、盐锅峡库区移民,在黑方台建成了提水灌溉工程,造成地下水位上升,诱发了大量黄土滑坡.作者于2006-04～2007-09先后对黑方台黄土滑坡进行了野外调查.利用IKONOS影像对黄土滑坡进行了遥感解译,将其与研究区数字高程模型(DEM)进行叠加再现了滑坡场景.基于以上工作,首先对黑方台黄土滑坡进行了较为系统的分类,包括黄土泥流、黄土滑动、黄土-泥岩接触面滑坡、黄土-泥岩顺层滑坡和黄土-泥岩切层滑坡.黄土泥流集中发育于野狐狗北部凹地形处;黄土-泥岩滑坡受基岩倾向控制,分布于坡向150°～200°的塬边地段.农业灌溉补给地下水的增湿、软化作用是黑方台黄土滑坡的根本诱发原因.对黑方台黄土滑坡机制的研究进行了展望. 相似文献
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在GIS技术的支持下,以三峡库区忠县-石柱河段为研究区域(面积260.9km2,滑坡分布面积5.3km2),建立了地质、地形数据库等滑坡因子空间数据库和滑坡空间分布数据库(数据比例尺均为1∶10万);在进行滑坡影响因子敏感性分析的基础上;对双变量分析模型进行了改进应用,对滑坡影响定量因子采用滑坡种子网格数据驱动的分级新方法。在GIS系统中进行了滑坡危险度评价成果图制图,将评价结果分为很低、低、中等、高、很高5个等级,依次占研究区域19.9%、31.69%、27.95%、17.1%和3.6%。评价结果显示危险性高和很高的区域主要分布在长江两岸,这与实际的滑坡分布吻合。研究结果对在三峡库区推广应用、防灾减灾具有实际指导意义。 相似文献
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河流对岸坡的侵蚀作用是滑坡失稳的重要因素之一,特别是在中国黄土地区。因此,探讨河流水位的季节性变化对黄土边坡稳定性的影响规律,对早期黄土滑坡灾害预警具有重要作用。论文以甘肃省天水市清泉村滑坡为例,分析5年内沿岸边坡形变速率与季节性水位变化之间的关系。基于SBAS-InSAR技术获取滑坡时序形变信息,借助MNDWI与DEM获取边坡底部时序水位信息,并结合GPM降雨数据进行相关性分析,研究发现随着降雨增多、河流水位的上涨,清泉村滑坡的形变速率明显增大,在夏季时滑坡形变量增长较快,并且边坡形变相较于水位季节变化具有一定的滞后性;经相关性分析,得出水位与滑坡形变的相关性系数为0.46,降雨与滑坡形变的相关性系数为0.39,表明清泉村滑坡的形变速率与水位变化更相关。因此,河流的季节性变化对滑坡形变速率具有一定影响,进而造成河流对沿岸滑坡的侵蚀作用呈现出季节性变化。研究揭示的黄土滑坡与河流水位的季节性变化关系,对揭示河岸边坡的演化过程、滑坡识别与灾害防治具有重要意义。 相似文献
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地形对黄土高原滑坡的影响 总被引：4，自引：0，他引：4
高分辨率地形与影像数据的缺乏已成为研究地表现象、特征与过程的重要瓶颈。低成本无人机设备和摄影测量技术的发展,打开了地学领域获取高分辨率数据的大门,大大提高了地质灾害野外调查与灾害编目的精度与效率。本文通过无人机野外调查和遥感室内目视解译,构建了一个包含307个黄土滑坡属性的数据库。在此基础上,通过数字地形分析和数理统计等方法,总结归纳了黄土滑坡样本数据的分布规律,探讨了地形对黄土滑坡分布的影响,阐述了地形相对高差对最长滑动距离、滑坡周长、滑坡面积的影响,提出了基于传统经验公式拟合的滑坡规模快速预测公式。结果表明：① 滑坡规模—频率分布具有明显的规律性,不同最大长度、最大宽度和周长的黄土滑坡数量分布均呈现正偏态分布,而不同面积的滑坡数量分布则服从幂函数分布;② 地形对黄土滑坡发育控制作用明显,不同地形高差、平均坡度、坡形的斜坡单元滑坡发育数量差异较大;③ 地形相对高差与滑坡的最长滑距、周长和面积的拟合曲线很好地符合幂律分布规律,但不同地形区的拟合效果有所差异,黄土丘陵区拟合效果最好,黄土高原全区次之,黄土台塬区最差;④ 本文建立的黄土滑坡规模快速预测模型,为黄土滑坡灾害调查提供了经验公式支撑。 相似文献
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基于专家知识的滑坡危险性模糊评估方法 总被引：6，自引：0，他引：6
滑坡发生的影响因素众多, 其危险性与各因素之间的关系多呈非线性关系, 同时各因素之 间也存在或强或弱的相关性, 而目前的危险性评价方法难以体现这些要求。本文提出了一种借助 滑坡专家知识并利用模糊推理理论进行滑坡危险性评价的方法。该方法通过建立了①坡度与岩 层倾角之差和坡向与岩层倾向之差、②坡度和岩性、③临空面和岩性、④坡形和岩性等四种环境 因子组合, 以此将不同环境因子之间的相关性融入各组合模型中, 并将四种组合所得的模糊危险 度进行叠加用于滑坡危险度的模糊评价。环境组合模型中的参数利用专家经验给出。将该方法应 用于三峡库区云阳- 巫山段, 得到了滑坡危险性的分级分布图。从滑坡危险性分布图上可清楚发 现, 本方法所计算出的危险性值在滑坡发生的地区明显高于未发生滑坡的地区, 该结果可以用于 城镇建设和重要基础规划设施的参考。 相似文献
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A qualitative landslide susceptibility zonation map (scale 1:100,000) of a sector of the Río Mendoza Valley was prepared by overlapping thematic maps of conditioning factors. The main parameters affecting the distribution of landslides in the area were ranked according to slope instability. Geomorphological surveys and field observations enabled identification of 300 historical or prehistoric landslides. A landslide inventory was developed classifying the processes involved in slope instability, and analysing the degree of activity. The two most influential factors in decreasing slope stability were lithology and slope angle. 相似文献
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Determining landslide susceptibility in Central Taiwan from rainfall and six site factors using the analytical hierarchy process method 总被引：6，自引：0，他引：6
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
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黄土地区灌溉水诱发滑坡群的研究 总被引：13，自引：4，他引：13
以甘肃省刘家峡、盐锅峡、八盘峡库区的黑方台台缘灌溉水诱发黄土滑坡群为例。论述了此类型滑坡在黄土高原的普遍性、滑坡的特征、形成机理、运动特征、斜坡稳定性以及适用于当地的防治措施。 相似文献
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Pece V. Gorsevski Paul E. Gessler Jan Boll William J. Elliot Randy B. Foltz 《Geomorphology》2006,80(3-4):178-198
Mapping of landslide susceptibility in forested watersheds is important for management decisions. In forested watersheds, especially in mountainous areas, the spatial distribution of relevant parameters for landslide prediction is often unavailable. This paper presents a GIS-based modeling approach that includes representation of the uncertainty and variability inherent in parameters. In this approach, grid-based tools are used to integrate the Soil Moisture Routing (SMR) model and infinite slope model with probabilistic analysis. The SMR model is a daily water balance model that simulates the hydrology of forested watersheds by combining climate data, a digital elevation model, soil, and land use data. The infinite slope model is used for slope stability analysis and determining the factor of safety for a slope. Monte Carlo simulation is used to incorporate the variability of input parameters and account for uncertainties associated with the evaluation of landslide susceptibility. This integrated approach of dynamic slope stability analysis was applied to the 72-km2 Pete King watershed located in the Clearwater National Forest in north-central Idaho, USA, where landslides have occurred. A 30-year simulation was performed beginning with the existing vegetation covers that represented the watershed during the landslide year. Comparison of the GIS-based approach with existing models (FSmet and SHALSTAB) showed better precision of landslides based on the ratio of correctly identified landslides to susceptible areas. Analysis of landslide susceptibility showed that (1) the proportion of susceptible and non-susceptible cells changes spatially and temporally, (2) changed cells were a function of effective precipitation and soil storage amount, and (3) cell stability increased over time especially for clear-cut areas as root strength increased and vegetation transitioned to regenerated forest. Our modeling results showed that landslide susceptibility is strongly influenced by natural processes and human activities in space and time; while results from simulated outputs show the potential for decision-making in effective forest planning by using various management scenarios and controlling factors that influence landslide susceptibility. Such a process-based tool could be used to deal with real-dynamic systems to help decision-makers to answer complex landslide susceptibility questions. 相似文献
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Spatial patterns of old, deep-seated landslides: A case-study in the northern Ethiopian highlands 总被引：1，自引：0，他引：1
M. Van Den Eeckhaut J. Moeyersons J. Nyssen Amanuel Abraha J. Poesen Mitiku Haile J. Deckers 《Geomorphology》2009,105(3-4):239-252
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
18.
Analysis of casualties due to landslides from 2000 to 2012 revealed that their spatial pattern was affected by terrain and other natural environmental factors, which resulted in a higher distribution of landslide casualty events in southern China than in northern China. Hotspots of landslide-generated casualties were in the western Sichuan mountainous area and Yunnan-Guizhou Plateau region, southeast hilly area, northern part of the loess hilly area, and Tianshan and Qilian Mountains. However, local distribution patterns indicated that landslide casualty events were also influenced by economic activity factors. To quantitatively analyse the influence of natural environment and human-economic activity factors, the Probability Model for Landslide Casualty Events in China (LCEC) was built based on logistic regression analysis. The results showed that relative relief, GDP growth rate, mean annual precipitation, fault zones, and population density were positively correlated with casualties caused by landslides. Notably, GDP growth rate ranked only second to relative relief as the primary factors in the probability of casualties due to landslides. The occurrence probability of a landslide casualty event increased 2.706 times with a GDP growth rate increase of 2.72%. In contrast, vegetation coverage was negatively correlated with casualties caused by landslides. The LCEC model was then applied to calculate the occurrence probability of landslide casualty events for each county in China. The results showed that there are 27 counties with high occurrence probability but zero casualty events. The 27 counties were divided into three categories: poverty-stricken counties, mineral-rich counties, and real-estate overexploited counties; these are key areas that should be emphasized in reducing landslide risk. 相似文献
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Analysis of casualties due to landslides from 2000 to 2012 revealed that their spatial pattern was affected by terrain and other natural environmental factors, which resulted in a higher distribution of landslide casualty events in southern China than in northern China. Hotspots of landslide-generated casualties were in the western Sichuan mountainous area and Yunnan-Guizhou Plateau region, southeast hilly area, northern part of the loess hilly area, and Tianshan and Qilian Mountains. However, local distribution patterns indicated that landslide casualty events were also influenced by economic activity factors. To quantitatively analyse the influence of natural environment and human-economic activity factors, the Probability Model for Landslide Casualty Events in China(LCEC) was built based on logistic regression analysis. The results showed that relative relief, GDP growth rate, mean annual precipitation, fault zones, and population density were positively correlated with casualties caused by landslides. Notably, GDP growth rate ranked only second to relative relief as the primary factors in the probability of casualties due to landslides. The occurrence probability of a landslide casualty event increased 2.706 times with a GDP growth rate increase of 2.72%. In contrast, vegetation coverage was negatively correlated with casualties caused by landslides. The LCEC model was then applied to calculate the occurrence probability of landslide casualty events for each county in China. The results showed that there are 27 counties with high occurrence probability but zero casualty events. The 27 counties were divided into three categories: poverty-stricken counties, mineral-rich counties, and real-estate overexploited counties; these are key areas that should be emphasized in reducing landslide risk. 相似文献