甘肃南部武都地区泥石流危险性评价

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.     

基于水文响应单元的泥石流灾害易发性分区方法

以水文响应单元和栅格单元为基础评价单元,运用因子贡献率法和信息量法两种评价模型对安宁河流域进行泥石流灾害易发性评价。研究结果表明,在流域尺度范围内,水文响应单元能够更好体现区域中的微观综合地貌特征,切合区域整体性描述;基于水文响应单元的易发性分区不仅与历史泥石流实际分布情况的契合度较高,而且数学模型方法适应效率较高和区内孕灾条件体现更为明显。由此,建立基于水文响应单元泥石流灾害易发性分区对探求流域尺度范围内泥石流灾害易发性分区方法与评价制图是一个有益的尝试与拓展,可为制定减灾防灾决策提供科学参考。     

横断山区山地灾害的动态风险性评价

对横断山区山地灾害进行科学的动态风险评价,可为区域防灾减灾工作提供重要的科学依据,同时对该区域的社会和谐稳定、经济稳步发展具有重要的现实意义。本文以横断山区为研究区,以五年年际变化为动态变化时间尺度,构建了山地灾害风险动态评价模型。首先选取发育山地灾害的本底因子作为静态危险度评价因子,采用频率比法计算了静态危险度,采用因子叠加法实现了横断山区山地灾害的动态危险性评价;然后选取人口密度、GDP密度和土地利用类型作为动态易损性评价指标,通过简化模型完成了动态易损性评价;最后根据风险评价模型结合动态危险性和动态易损性评价结果,得到了横断山区山地灾害不同年份的风险区划图并完成了动态风险评价。主要结果分述如下:(1)横断山区北部、西北部危险性低,为低和中危险性集中区;南部、东南部危险性高,为高和极高危险性集中区;(2)位于横断山区南部及东北部的高和极高危险区的地区人口较为密集,经济活动性较强,其易损性等级比较高,相应的风险级别同样较高;(3)横断山区受强降雨次数、人口密度、GDP密度和土地利用的动态变化的影响,各年山地灾害的风险性的空间分布范围具有比较明显的差异,横断山区的风险性随时间动态变化。     

基于信息量模型的玉树地震次生地质灾害危险性评价

2010-04-14发生在青海省玉树的Ms7.1级地震引发了大量的地质灾害.基于GIS技术和信息量模型方法,以坡度、坡向、高程、坡形、地貌类型、断层距和地层岩性为评价因子,通过空间分析计算各因子的信息量,分析地质灾害在各因子中的空间分布特征,对各评价因子图层进行空间建模,将获取的信息量图划分为高度、中度、轻度三级危险区,通过遥感解译研究区实际滑坡分布,与危险性分布图叠加表明:本次研究得出的危险等级与实际的滑坡发生情况相吻合,为灾区重建提供参考依据.     

基于粗糙集的范例推理在泥石流危险性评价中的应用

将粗糙集理论和范例推理相结合,建立了基于粗糙集-范例推理的泥石流危险性评价模型.运用粗糙集理论对范例库中的范例进行属性约简和特征向量权值计算,用相似度量理论来实现最相似范例检索,得到泥石流的危险性评价结果.选取了一次泥石流(可能)最大冲出量,泥石流发生频率、流域面积、主沟长度、流域相对高差、流域切割密度、24 h最大降雨量、松散固体物质储量共8个因素作为泥石流危险性的影响因子;选取云南东川和西藏八宿等共14条泥石流沟资料进行建模分析.实例研究表明,基于粗糙集一范例推理的泥石流危险性评价结果与实际状态相吻合,该方法具有简便、高效、直观、实用的特点.     

四川德昌茨达“8·24”群发性滑坡型泥石流之地形条件

2004-08-24,四川省德昌县茨达乡暴发了群发性滑坡型泥石流,给当地居民生活和生产造成了严重的损失。此次群发性泥石流范围较小,地质和水文条件比较接近,由此认为地形条件是控制泥石流发育的关键因素。在分析地形条件对滑坡型泥石流形成的影响基础上,从其形成机理出发,选取研究区各沟谷流域面积A,沟床比降J,沟谷两侧斜坡25°~45°坡度所占百分比S等3个重要地形因子进行研究,对比相互关系,建立起此次泥石流暴发的临界曲线和综合地形因子G,G=S×(A/A0)0.15×J0.8,得出在地质和降雨条件都相近似的情况下,地形因子G越大,地形条件越好,越容易暴发泥石流。因此可用G因子划分区域内沟谷泥石流的易发等级,并为滑坡型泥石流的危险性评价和预警预报提供了新的研究思路。     

都汶公路沿线泥石流危险性评价

汶川地震诱发的次生泥石流灾害,已成为灾区防灾减灾工作的突出问题和灾后恢复重建的重要制约因素之一,泥石流危险性评价是泥石流灾害风险管理的核心基础技术。以都汶公路沿线的31条泥石流沟为研究对象,通过野外考察、遥感图像的解译、查阅相关文献资料等手段获取研究区泥石流沟的基础数据,通过选取地质、地形、气象、水文指标,并利用主成分分析法对关键因子进行筛选和灰色系统模型进行权重的确定,建立泥石流危险性评价模型,计算得到每条沟的泥石流危险度值。评价结果表明:公路沿线31条泥石流沟处于不同泥石流危险等级:极高危险占23%,高危险占35%,中度危险占13%,轻度危险占29%;其中红椿沟、肖家沟、烧房沟等沟属于泥石流极高危险沟道,高家沟、牛圈沟等属于高度危险沟道,公路选线须采取避让或充分的防治对策。     

金沙江流域(云南境内)山地灾害危险性评价

云南境内的金沙江流域是斜坡不稳定的敏感区,根据1988-2000年的区域调查和统计,区内发育山地灾害点1697处,其中流域面积大于1km2的泥石流沟808条,体积大于1×104m3的滑坡580处,体积大于1000m3的崩塌309处。用于山地灾害危险性评价的主要敏感因子包括岩土体类型、山坡坡度、降雨、土地利用、地震烈度和人类活动。在对这些因子进行了敏感性评价的基础上,应用GIS对敏感因子集成评价而产生了云南金沙江流域山地灾害危险性评价图。评价结果表明:高危险区面积占全区面积6464km2的8 77%,中危险区占全区总面积的41 51%,低危险区占41 12%,无危险区占8 60%。山地灾害危险性评价图可以帮助规划者或工程师在土地发展规划中选择最佳建设场所,以减轻灾害的影响。     

基于信息量模型和机器学习方法的滑坡易发性评价研究——以四川理县为例

以阿坝藏族羌族自治州地质灾害频发的理县为研究区,从地形地貌、地质环境、水文条件和人类工程活动等方面选取11个影响因子,通过皮尔森相关系数研究各因子之间的相关性,从而构建滑坡易发性评价指标体系。利用信息量模型计算各影响因子的信息量值,从信息量模型得出的极低和低易发性分区中选取非滑坡样本,在此基础上将样本数据代入随机森林和径向基函数神经网络2种机器学习模型开展滑坡易发性评价,并通过接收灵敏度（Receiver Operating Characteristic,ROC）曲线进行精度验证。结果显示：随机森林模型预测出的高易发区单位面积内分布的滑坡点数量更为集中,在仅占6.666%的区域分布了74.026%的灾害点,评价结果优于径向基函数神经网络模型。ROC曲线中两模型AUC（Area Under Curve）值分别为0.893、0.874,说明随机森林模型具有更高的可靠性,比径向基函数神经网络在该区域地质灾害易发性评价中更具优势。     

基于随机森林模型的泥石流易发性评价——以汶川地震重灾区为例

在区域泥石流易发性研究中,科学确定泥石流易发性主控因子及其贡献率既是关键科学问题,也是区域泥石流预警预报和风险管理的重要基础。本研究选取汶川地震重灾区,引入随机森林算法,以小流域为评价单元,集合多元因子指标体系,建立泥石流易发性评价模型,定量分析了汶川地震重灾区内泥石流关键影响因子及贡献率,并探讨了研究区泥石流易发性的空间分布特征。本文初选了63项评价指标,以模型AUC值变化为基础,筛选出35项指标构成易发性评价指标体系,并用于区域内泥石流易发性主控因子的识别,结果表明:流域高差、流域平均坡度、流域内滑坡面积、平均降雨天数是区域内泥石流易发性主控因子,另外,沟长比降、大于10°积温、年均温、人口密度、村落个数、低覆盖度土地利用方式等在泥石流易发性评价中也发挥着重要作用;易发性评价结果显示,极高易发区占比达到了22.94%,主要分布于研究区西部,泥石流易发性较高的小流域主要分布在青藏高原向四川盆地过渡的地形急变带,同时也与地震带、断裂带、干旱河谷区域密切相关。模型验证结果表明,平均AUC值达0.84,模型具有很高的稳定性和准确性,说明随机森林算法非常适用于区域泥石流易发性评价研究,机器学习算法结合小流域为单元的方法对区域泥石流易发性评价有效果良好,可为区域尺度灾害易发性及风险评估提供更为有效的方法参考。     

Dynamic process-based risk assessment of debris flow on a local scale

After the Wenchuan earthquake in China, debris flows have been more frequent. Multiple debris flows commonly occur in earthquake-affected areas during heavy rainfall, often causing losses of lives and property. We analyzed the dynamic movement of debris flows and proposed a quantitative method of debris flow hazard assessment, based on kinetic energy. Validated using field study of an actual debris flow disaster, these analyzes help determine the type, quantity, distribution, economic worth, and susceptibility of elements at risk. We established a method to determine vulnerability of elements at risk and we propose a systematic and quantitative method for local risk analysis of debris flows. We applied the proposed method to a debris flow in Qipan gully, which caused serious damages for Duwen Highway and Qipan settlements of Sichuan Province in 2013. With the support of a debris-flow movement numerical simulation, remote sensing, and GIS techniques, the proposed method analyzed disaster effects and divided the hazardous areas into three risk zones. Calculated risk zones coincided with the actual distribution and severity of damage of the event, suggesting that the risk assessment generated by the proposed method is consistent with results from the actual disaster.     

基于GIS技术的泥石流风险评价研究

为了满足对自然灾害预测不断增长的紧迫要求，泥石流风险评价成为帮助决策过程重要的基础工具之一。即使泥石流风险性各组分的评价很困难，但地理信息系统可辅助提出这种风险性制图的有关方法。我们以云南省为研究区，选取6个成因因子参与泥石流危险度敏感性分析，通过将研究区易损性评价图与危险性评价图叠加分析，编制出云南省泥石流风险评价图。该图描述了在现有自然条件和人类活动下的泥石流风险敏感区。研究成果为全面反映灾情，确定减灾目标，优化防御措施，进行减灾决策提供了重要依据。     

GIS支持下的东川区泥石流危险度区划

在建立东川区泥石流信息系统的基础上,根据泥石流形成原因,初步选择面积、相对切割度、主沟沟床比降、相对高差、主沟长度、圆状率作为评价指标,利用东川区21条典型泥石流沟的数据,通过主成分分析,选择出面积、圆状率、相对高差三个指标,由主成分载荷得到危险度评价公式,在ARC／INFO和ARCVIEW软件的支持下,把东川区划分为60个评价单元,计算出各个单元内的危险度总分值,依据分值划分为四个级别,重度危险区、危险区、轻度危险区和基本无危险区,最后根据泥石流危险度区划原则,得到东川区泥石流危险度区划图。     

Detailed debris flow hazard assessment in Andorra: A multidisciplinary approach

In many mountainous areas, the rapid development of urbanisation and the limited space in the valley floors have created a need to construct buildings in zones potentially exposed to debris flow hazard. In these zones, a detailed and coherent hazard assessment is necessary to provide an adequate urban planning. This article presents a multidisciplinary procedure to evaluate the debris flow hazard at a local scale. Our four-step approach was successfully applied to five torrent catchments in the Principality of Andorra, located in the Pyrenees. The first step consisted of a comprehensive geomorphologic and geologic analysis providing an inventory map of the past debris flows, a magnitude–frequency relationship, and a geomorphologic–geologic map. These data were necessary to determine the potential initiation zones and volumes of future debris flows for each catchment. A susceptibility map and different scenarios were the principal outcome of the first step, as well as essential input data for the second step, the runout analysis. A one-dimensional numerical code was applied to analyse the scenarios previously defined. First, the critical channel sections in the fan area were evaluated, then the maximum runout of the debris flows on the fan was studied, and finally simplified intensity maps for each defined scenario were established. The third step of our hazard assessment was the hazard zonation and the compilation of all the results from the two previous steps in a final hazard map. The base of this hazard map was the hazard matrix, which combined the intensity of the debris flow with its probability of occurrence and determined a certain hazard degree. The fourth step referred to the hazard mitigation and included some recommendations for hazard reduction. In Andorra, this four-step approach is actually being applied to assess the debris flow hazard. The final hazard maps, at 1 : 2000 scale, provide an obligatory tool for local land use planning. Experience achieved during the study showed that the collaboration between geologists, geomorphologists, engineers, and decision makers is essential and that only a multidisciplinary approach allows for solving all the problems of such a complex process as debris flows. Finally, we propose that our approach may be applied to other mountainous areas, adapting the hazard matrix to new local conditions.     

山洪泥石流风险评估与风险管理理论与方法

山洪泥石流是中国常见的自然灾害,充分认识其形成机制与潜在风险是防灾减灾的关键。本文阐述了山洪泥石流形成机理,以及风险分析与管理的方法和内容,系统认识了地表产流流量激增、土体破坏物质供给激增、沟道堵塞体级联溃决流量放大和动床侵蚀规模增大等4个山洪泥石流的形成过程,介绍了基于动力过程的山洪泥石流风险评估方法和承灾体易损性评估方法,构建了基于灾害动力过程的风险评估与风险制图方法。进而,基于风险评估结果,提出可用于具体灾害点减灾的风险管理内容和风险调控技术、灾害防治的工程与非工程措施与制技术方案。最后,重点讨论了包括灾害风险预测、临灾预案、灾害防治工程方案等内容的风险处置对策,并形成一套基于山洪泥石流动力过程的风险评估与风险管理理论与方法体系。     

基于SVM的泥石流危险度评价研究

选取泥石流一次(可能)最大冲出量(L₁)、泥石流发生频率(L₂)、流域面积(S₁)、主沟长度(S₂)、流域最大相对高差(S₃)、流域切割密度(S₆)和泥沙补给段长度比(S₉)7个因子作为泥石流沟谷危险度评价因子,运用支持向量机理论,以云南省37条泥石流沟的259个基础数据为样本进行学习训练和测试,建立泥石流危险度评价的支持向量机模型,通过实例验证,取得良好效果。     

流团模型在泥石流危险度分区中的应用

应用王光谦等发展的流团模型，在泥石流摩阻为速度的二次多项式的条件下，根据一定的地形条件、流量过程线及泥石流体的一些参数，模拟了泥石流在堆积扇上的扩散堆积运动。由数值模拟结果，以泥石流的最大动能为分区指标，建立了泥石流危险度分区模型。最后将该方法应用到云南东川尼拉姑沟，取得了该沟50a一遇泥石流的泛滥范围和危险度分区。     

A method for assessing regional debris flow risk: an application in Zhaotong of Yunnan province (SW China)

Based on the definitions of the United Nations, the assessment of risk involves the evaluation of both hazard and vulnerability. This forms the basis of a generalized assessment model of debris flow risk. Hazard is a measure of the threatening degree of an extreme event and is expressed theoretically as a function of event magnitude and frequency of occurrence. Mathematically, it is the definite integral area under the magnitude–frequency curve. Based on the need for a model applicable in regions that lack data, a new method that incorporates theoretical concepts with empirical analysis is presented to calculate the regional hazardousness of debris flows. Debris flow hazard can be estimated from gully density, mean annual rainfall and percentage of cultivated land on steep slope. Vulnerability is defined as the potential total maximum losses due to a potential damaging phenomenon for a specified area and during a reference period. On a regional scale, it is dependent on the fixed assets, gross domestic product, land resources and population density, as well as age, education and wealth of the inhabitants. A nonlinear, power-function model to compute the vulnerability degree is presented. An application of the proposed method to Zhaotong prefecture of Yunnan province, SW China, provides high accuracy and reasonable risk estimates. The highest risk of debris flow is in Zhaotong county with a value of 0.48; the lowest risk of debris flow is in Yanjin county with a value of 0.16. The other counties have debris flow risks ranging from 0.22 to 0.46. This provides an approach for assessing the regional debris flow risk and a basis for the formulation of a regional risk management policy in Zhaotong prefecture.     

GIS‐based modeling of glacial hazards and their interactions using Landsat‐TM and IKONOS imagery

Hazard interactions in glacial and periglacial environments are of crucial importance due to their potential for causing major catastrophes. Nevertheless, glacial and periglacial hazards have usually been modeled separately to date. In this study, we therefore propose a methodological strategy for modeling and assessing glacial and periglacial hazard interactions on a regional scale, including ice avalanches, lake outbursts and periglacial debris flows. Due to climate‐related rapid changes in glacial and periglacial areas, methods which incorporate monitoring capacities are needed. Hence, the methods presented here are based on remote sensing data, which are particularly powerful for monitoring tasks, and GIS modeling. For ice avalanche and lake‐outburst hazard detection and modeling, we applied recently published methods based on Landsat‐TM imagery, terrain modeling and flow routing. For detection of potential debris‐flow initiation zones in steep debris reservoirs, we present a novel method based on image processing of IKONOS data and terrain modeling, followed by flow modeling. Using this method, we achieve the synthesis of the individual process modeling in order to assess the potential interactions. The modeling is applied to a study region in the central Swiss Alps. The results show that systematic modeling based on remote sensing and GIS is suitable for first‐order assessment of glacial and periglacial hazard interactions as well as assessments of possible consequences, including impacts on traffic routes and other infrastructure. Based on this, critical cases can be detected and analyzed by subsequent detailed studies.