黄土区滑坡研究中地形因子的选取与适宜性分析

黄土高原是中国生态较为脆弱的地区,也是滑坡发育的地层之一。黄土滑坡发育是孕灾环境、致灾因子和承灾体等多种因素联合作用的结果,其中作为重要孕灾环境因素的地形因子的选取是黄土滑坡风险研究的基础。本文选取黄土滑坡灾害多发的甘谷县作为研究区,综合利用敏感性指数、确定性系数和相关系数方法进行地形因子在滑坡灾害研究中的适宜性分析,得出以下结论：基于确定性系数法、敏感性分析模型和相关系数法,最终筛选出适宜于本区域滑坡灾害评价的地形因子为：坡度、坡度变率、坡形和地表粗糙度;确定性系数法、敏感性分析模型都基于分析单一因子与滑坡之间的关系进行致灾因子选取,忽视地形因子之间的相关性。实验结果表明,研究区稳定性较差的区域与已发生滑坡灾害分布数量具有较好的对应关系,并深入分析了滑坡与地形因子分级范围的关系,发现地形因子分级范围对地质灾害风险研究具有重要的影响,是导致部分区域的差异性主要原因之一。实地调查发现,河网切割密度及人类工程活动也对研究区危险性具有重要的控制作用,是重要的地形因素。     

基于信息量模型的中国滑坡灾害风险区划研究

基于信息论发展起来的信息量模型是进行区域滑坡灾害风险评估的一种有效方法。GIS技术为滑坡灾害在不同模型条件下的风险评估提供了有效地技术支持。经过研究，开发出了基于MapGIS软件平台的滑坡灾害风险分析系统。在该系统支持下．采用信息量模型对中国范围内的滑坡灾害进行危险性分析。进而进行区域社会经济易损性分析。并在此基础上进行最终的滑坡灾害风险评估。     

约束条件对滑坡涌浪特征影响的室内试验研究

水库滑坡约束条件影响其运动过程的几何形态, 是滑坡涌浪预测的重要参数之一。为了探究约束条件对滑坡涌浪特征(波高、波幅与周期)的影响, 采用正交试验设计法开展了54组滑坡涌浪室内模型试验, 并基于统计学理论对约束散体和半约束散体的涌浪特征进行了分析。结果表明: 涌浪波周期基本不受滑体约束条件的影响; 而半约束散体模型的波高和波幅小于约束散体的波高和波幅, 半约束散体的初始涌浪波高约为约束散体的0.95倍, 半约束散体模型的最大波峰波幅约为约束散体模型的0.9倍。因此, 在开展滑坡涌浪快速预测时, 虽然滑体入水形态与破坏前形态差异巨大, 但基于滑坡初始几何形态参数对其初始涌浪波高和最大涌浪波幅的预测结果是偏安全的。研究结论可以为更准确地预测水库滑坡涌浪提供理论依据。      

考虑地震危险性的倾倒变形边坡风险定量分析

风险分析与评估是解决边坡固有不确定性的重要工具, 但同时考虑外在荷载和内在岩土力学参数的不确定性, 对边坡进行系统定量风险分析的研究较少。以西藏扎拉水电站厂后倾倒变形边坡为例, 基于场地地震峰值加速度概率密度函数和不同地震峰值加速度下边坡失稳概率拟合函数, 采用数值积分计算了边坡在设计基准期的失稳概率, 并采用离散元方法对边坡失稳后的影响范围进行了数值模拟, 在此基础上进行了承灾体易损性分析及定量风险计算, 最后采用ALARP准则进行了风险评价。研究表明, 考虑地震危险性条件下, 扎拉水电站厂后倾倒变形边坡在50 a设计基准期内失稳概率为0.061 9;边坡对水电站地面厂房存在较大威胁, 相应财产风险为5 482万元; 根据ALARP准则, 边坡风险处于不可接受区, 需采取措施防范或规避风险。研究成果对于边坡治理工程决策及风险管理具有指导意义。      

基于GIS的贫困地区降雨诱发型地质灾害风险评估————以湖北省恩施州为例

湖北省恩施土家族苗族自治州(简称恩施州)地处中国14个集中连片特困区之一的武陵山区内,州内少数民族聚居多,贫困人口分布广,地质灾害频发,"因灾致贫,因灾返贫"现象较为突出.本文根据灾害系统学原理和灾害风险分析理论,综合考虑恩施州降雨诱发型地质灾害的致灾因子,孕灾环境和承灾体,构建了降雨诱发型地质灾害风险评价指标体系,基于灾害系统学原理的风险评估模型,对该区的降雨诱发型地质灾害风险进行评估.主要结论如下:(1)降雨诱发型地质灾害的诱发因子为强降雨,恩施州降水丰沛,恩施市中部与鹤峰县东南部属于致灾因子高危险性区域;(2)选取地形地貌,基础地质,水文条件,人类工程活动等孕灾环境要素,耦合信息量法和层次分析法,构建恩施州孕灾环境敏感性评价指标体系,结果表明恩施州孕灾环境敏感性较高,高区域主要分布在巴东县,恩施市和鹤峰县;(3)选取工程建筑,居民人口,社会经济,耕地等承灾体进行脆弱性评估,结果表明承灾体脆弱性较高区域与人口集中地区在空间上重合,利川市和来凤县有更多的高脆弱性区域;(4)综上可知,恩施州的降雨诱发型地质灾害风险总体较高,其较高,高风险区域主要分布在巴东县和恩施市.     

水库滑坡成因机制研究进展与展望

滑坡是水库库区主要地质灾害类型之一,开展水库滑坡成因机制研究具有重要理论意义和工程应用价值.利用WebofScience(WoS)数据库和VOSviewer文献计量工具对1999-2018年已发表的969篇以水库滑坡为主题的相关论文进行研究趋势分析.文献计量分析表明三峡库区滑坡稳定性和变形研究是未来水库滑坡成因机制研究主要趋势.从库水对滑坡的宏观力学作用方式、库水作用下岩土体渗流应力耦合机理和库水对岩土体劣化作用过程等方面,对国内外水库滑坡成因机制研究的主要成果与进展进行了综述.综合现有的研究成果指出水库滑坡在精细化地质建模、岩土体多场耦合特征参数获取和岸坡长期演化评价等方面尚存在不足.基于上述问题,提出水库滑坡成因机制研究应以多场信息监测为重要手段,立足多学科交叉,采用大数据融合与挖掘和人工智能技术等解决水库滑坡长期演化趋势难题.考虑水库滑坡所处地质环境的复杂性,建议未来应在水库滑坡立体精细地质建模、多场关联监测、地质结构多场多尺度演变过程、基于监测数据大数据分析的滑坡预警阈值确定和原位试验综合平台构建等方面进一步深入研究.     

自然灾害综合风险防范信息服务技术体系构建及展望

构建自然灾害综合风险防范信息服务业务技术体系是支撑新时代防灾减灾救灾工作的必然要求。文章聚焦全链条、多主体、多灾种综合风险防范信息服务需求,建立了自然灾害综合风险防范信息服务的技术体系框架,构建了涵盖常态减灾和灾前预防、灾中救援、灾后恢复重建等非常态救灾全过程的综合风险防范信息服务产品体系,建立了信息产品开发、行业数据协同、网络大数据挖掘、信息服务平台集成等方面的关键技术。其中,信息产品体系构建从灾害管理过程、主要业务类型和工作任务方面进行三级分类。信息产品开发方面研发了基于致灾、灾情、救灾3类标准灾害信息要素的灾害信息产品制作、表达和动态定制技术;行业数据协同方面研发了双向自适应的部门微服务数据共享新机制及多部门多源异构数据接入、融合处理技术;网络大数据挖掘领域研发了基于网页、移动通信、社交网络、物联网等网络大数据的致灾、灾情、救灾要素信息挖掘与融合分析技术;信息服务集成平台搭建领域研发了基于云服务架构的时空分布式大数据管理、业务工具模型集成、“云+端”多渠道信息服务技术。该技术体系解决灾害信息服务时效性不高、完备性不足等问题,为开辟与政府部门统计并行的灾害信息数据获取新途径提供了技术支撑。     

四川省滑坡灾害气象预警模型建立与验证

四川省滑坡灾害严重,特别是2008年之后,灾情显著加剧,如何预防滑坡灾害是保护人民生命财产安全的有效途径。滑坡灾害的预警模型研究是滑坡灾害预防领域的核心课题。本文对四川省滑坡灾害危险性进行了评价,并开展了滑坡灾害气象风险预警模型研究。①以确定性系数的方法量化坡度、地形起伏度、水文地质岩性、植被覆盖度、地震烈度和年均降雨量因子,建立逻辑回归模型,定量地进行四川省滑坡灾害危险性区划,并对结果进行验证。结果表明,四川省滑坡灾害高危险性区域成“Y”字型分布,此外川中、川东北地区滑坡灾害危险性也非常高,这与四川省滑坡灾害的空间分布情况相符。②在前期滑坡灾害与降雨量统计分析、滑坡灾害危险性评价的基础上,以滑坡灾害危险性评价为静态因子,日降雨量数据为动态因子,通过逻辑回归模型的结果,确定以当日降雨量概率化值、滑坡灾害危险性值、前一日降雨概率化值、前两日降雨概率化值、前三日降雨概率化值为临灾模型影响因子,各因子对预警结果影响程度按上述顺序递减,建立了地质-气象耦合的临灾气象预警模型。通过检验区数据对模型的检验表明,该预警模型能成功预警80%以上的滑坡灾害;通过滑坡灾害群发个例检验发现,该预警模型与四川省现用模型相比,预警区域明显减小,空报率和漏报率显著降低。     

浙江省滑坡灾害风险性区划信息图谱研究

将地学信息图谱理论运用在浙江省滑坡灾害风险区划中,结合已有的滑坡灾害风险研究,选取DEM、坡度、坡向、断裂、土石工程地质分组、土地利用类型等空间环境因子和不同时间段的降水量等作为评价子系统,实现从不同角度对浙江省滑坡灾害进行综合评价,并得出浙江省滑坡灾害风险区划图谱。一方面,地学信息图谱的运用使得滑坡灾害形成的动因和过程更加易于理解,另一方面,同时显示滑坡灾害的时间和空间差异的滑坡灾害风险区划图谱能够为浙江省的滑坡灾害防治提供更科学的参考依据。     

贵州省雷电灾害易损性分析及区域划分

根据贵州省近8年的雷电灾害统计资料和30年的雷暴日观测统计资料,从灾害易损性的角度出发,以雷暴日数、雷电灾害频度、经济易损模数、生命易损模数作为评价指标。对贵州省各设区市的雷灾易损性进行了综合分析,初步形成贵州省雷灾易损性区划。结果表明,某一地区雷击灾害的发生及其造成的损失情况既与该地所处的雷电环境特征有关,也与该地人口密度、经济发展状况有关。     

Hazard and population vulnerability analysis: a step towards landslide risk assessment

In this paper, an attempt to analyse landslide hazard and vulnerability in the municipality of Pahuatlán, Puebla, Mexico, is presented. In order to estimate landslide hazard, the susceptibility,magnitude(area-velocity ratio) and landslide frequency of the area of interest were produced based on information derived from a geomorphological landslide inventory; the latter was generated by using very high resolution satellite stereo pairs along with information derived from other sources(Google Earth,aerial photographs and historical information).Estimations of landslide susceptibility were determined by combining four statistical techniques:(i) logistic regression,(ii) quadratic discriminant analysis,(iii) linear discriminant analysis, and(iv)neuronal networks. A Digital Elevation Model(DEM)of 10 m spatial resolution was used to extract the slope angle, aspect, curvature, elevation and relief.These factors, in addition to land cover, lithology anddistance to faults, were used as explanatory variables for the susceptibility models. Additionally, a Poisson model was used to estimate landslide temporal frequency, at the same time as landslide magnitude was obtained by using the relationship between landslide area and the velocity of movements. Then,due to the complexity of evaluating it, vulnerability of population was analysed by applying the Spatial Approach to Vulnerability Assessment(SAVE) model which considered levels of exposure, sensitivity and lack of resilience. Results were expressed on maps on which different spatial patterns of levels of landslide hazard and vulnerability were found for the inhabited areas. It is noteworthy that the lack of optimal methodologies to estimate and quantify vulnerability is more notorious than that of hazard assessments.Consequently, levels of uncertainty linked to landslide risk assessment remain a challenge to be addressed.     

Spatial prediction of landslide for Badong County in the Three Gorges reservoir district

By using the landslide risk evaluating model and the advantages of GIS technology in image processing and space analysis, the relative landslide hazard and risk evaluating system of the new county site of Badong is built up. The system is mainly consisted of four subsystems: Information management subsystem, hazard assessment subsystem, vulnerability evaluation subsystem and risk prediction subsystem. In the system, landslide hazard assessment, vulnerability evaluation, risk predictions are carried out automatically based on irregular units. At last the landslide hazard and risk map of the study area is compiled. During the whole procedure, Matter-Element Model, Artificial Neural Network, and Information Model are used as assessment models. This system provides an effective way for the landslide hazard information management and risk prediction of each district in the Reservoir of Three Gorge Project. The result of the assessment can be a gist and ensure for the land planning and the emigration project in Badong.     

Spatial prediction of landslide for Badong County in the ThreeGorges reservoir district

By using the landslide risk evaluating model and the advantages of GIS technology in image processing and space analysis, the relative landslide hazard and risk evaluating system of the new county site of Badong is built up. The system is mainly consisted of four subsystems： Information management subsystem, hazard as- sessment subsystem, vulnerability evaluation subsystem and risk prediction subsystem. In the system, landslide hazard assessment, vulnerability evaluation, risk predictions are carried out automatically based on irregular units. At last the landslide hazard and risk map of the study area is compiled. During the whole procedure, Matter-Element Model, Artificial Neural Network, ancl Information Model are used as assessment models. This system provides an effective way for the landslide hazard information management and risk prediction of each district in the Reservoir of Three Gorge Project. The result of the assessment can be a gist and ensure for the land planning and the emigration project in Badong.     

高温热浪风险评估研究综述

在全球气候变化大背景下,极端高温事件发生频率及强度明显增多。据相关气象数据统计,若任由灾害肆虐,越来越多的人将死于全球热效应、疟疾、登革热和其他热相关疾病。本文根据近年来国内外学者研究进展,梳理了高温热浪风险评估的基本步骤,讨论了高温热浪风险评估的风险性框架,提出未来可利用遥感技术构建高温热浪风险的空间评估体系,将孕灾环境的暴露度、危险性、系统脆弱性及适应性相结合,综合构建风险评估体系。针对评估因子的选择进行论述,探讨了图层叠置法、主观赋权法、客观赋权法及组合赋权法等多种确定各指标权重的方法,分析比较了不同方法的利弊,将H-AHP与图层叠置结合的方法与简单的加减、乘除法进行对比,论述其在综合评价模型构建中的优势,并针对高温热浪风险等级的划分方法进行了对比,论述了不同方法适用的不同情况及其优势,为未来建立合理高温热浪灾害风险评估体系提供了方法参考,为进一步了解高温热浪危害,建立高温热浪监测、评估、报告制度,进一步完善建立高温热浪灾害预警体系提供有利依据。     

Building vulnerability evaluation in landslide deformation phase

Building vulnerability evaluation is important in the risk assessment on earthquake and flood hazards. But for landslide hazard, it is also a very important part for the people in buildings. Most discussions or researches about building vulnerability are for landslide failure, few for landslide in deformation phase. For this objective, this paper discussed about building vulnerability evaluation using Zhaoshuling landslide as an example Zhaoshuling landslide named located in the Three Gorges Reservoir Area, China. After a field survey on the geological condition of landslide, detailed field investigation on the buildings’ location and structure is carried out. To get landslide surface deformation, numerical simulation method is used under the combining condition of water fluctuation and rainfall. Then building deformation and probable damage degree is analyzed according to landslide surface deformation and the relative theory in mining. Based on the national standard building damage classification system, the vulnerability of all the buildings on the landslide is semi-quantitatively evaluated.     

山地灾害致贫风险初步分析————以湖北省恩施州为例

中国的贫困地区主要分布在山区,山地灾害的多发,易发在某种程度上成为制约贫困地区经济发展的因素之一.目前,山地灾害的研究集中于动力学研究,缺乏风险尤其是灾害致使贫困风险的研究.本文对山地灾害特有灾害与一般地质灾害的概念进行了区分;根据贫困的内涵与可量测性,定义了山地灾害的贫困脆弱性及山地灾害致贫风险;以贫困脆弱性分布和灾害危险性分布,构建区域山地灾害致贫风险评价模型,并基于此模型对少数民族特困地区--湖北省恩施土家族苗族自治州(简称恩施州)进行应用研究.在示例分析中,首先利用确定性系数模型和频率比例法对山地灾害的危险性进行了评价;然后,从暴露性和应对能力2个方面选取了经济,社会及自然指标,以进行脆弱性评价;最后,利用通用灾害风险评价公式对研究区由于山地灾害导致的贫困风险在空间的分布进行评价,得到了研究区的山地灾害致贫风险分布与分级图.     

基于特征筛选与差分进化算法优化的滑坡危险性评估方法

突发性地质灾害危险性评估对灾害防治与风险管理具有重要意义。由于不同地区影响灾害发生的因子各不相同,实际评估过程中难以全面客观地选取适宜的评估因子。机器学习对处理灾害系统的高维非线性问题独具优势,但因模型难以调优而评估效果有限。本文尝试提出一种双向优化的滑坡危险性评估方法：在构建因子敏感性指数开展定量敏感性分析的基础上,结合重要性分析、相关性分析、共线性分析构建四维(Four-Dimensional, 4D)特征筛选法用于评估因子综合优选;为克服模型难以调优的问题,引入差分进化(Differential Evolution, DE)算法优化支持向量机(Support Vector Machine, SVM)与多层感知机(Multi-Layer Perceptron, MLP) 2种推广能力较强的机器学习模型。最后,以福建省滑坡为例,开展评估方法研究。研究表明：4D特征筛选法能更加客观全面地选取适宜性更高的危险性评估因子,从而降低数据维度、减少信息冗余以提升评估模型性能;DE算法对SVM与MLP具有显著的优化效果,有益于增强模型滑坡危险性的评估准确度,DE-SVM、DE-MLP相较于未优化前模型的AUC值分别提升了4.43%与4.37%;基于双向优化的滑坡危险性评估结果表明,降雨与土地利用类型对福建省滑坡发生具有重要影响作用,福建省滑坡极高危险区普遍年均降雨较高、地形复杂多变,极低危险区主要位于东南沿海一带及闽江流域两侧。本研究为滑坡危险性评估中的影响因子客观选取与机器学习模型调优提供了一定思路。     

Hazard assessment of landslide disaster using information value method and analytical hierarchy process in highly tectonic Chamba region in bosom of Himalaya

The present study is focused on a comparative evaluation of landslide disaster using analytical hierarchy process and information value method for hazard assessment in highly tectonic Chamba region in bosom of Himalaya. During study, the information about the causative factors was generated and the landslide hazard zonation maps were delineated using Information Value Method (IV) and Analytical Hierarchy Process (AHP) using ArcGIS (ESRI). For this purpose, the study area was selected in a part of Ravi river catchment along one of the landslide prone Chamba to Bharmour road corridor of National Highway (NH-154A) in Himachal Pradesh, India. A numeral landslide triggering geoenvironmental factors i.e. slope, aspect, relative relief, soil, curvature, land use and land cover (LULC), lithology, drainage density, and lineament density were selected for landslide hazard mapping based on landslide inventory. Landslide hazard zonation map was categorized namely “very high hazard, high hazard, medium hazard, low hazard, and very low hazard”. The results from these two methods were validated using Area Under Curve (AUC) plots. It is found that hazard zonation map prepared using information value method and analytical hierarchy process methods possess the prediction rate of 78.87% and 75.42%, respectively. Hence, landslide hazard zonation map obtained using information value method is proposed to be more useful for the study area. These final hazard zonation maps can be used by various stakeholders like engineers and administrators for proper maintenance and smooth traffic flow between Chamba and Bharmour cities, which is the only route connecting these tourist places.     

Analysing post-earthquake landslide susceptibility using multi-temporal landslide inventories——a case study in Miansi Town of China

The earthquake that occurred on May 12, 2008, in Wenchuan County aroused a great deal of research on co-seismic landslide susceptibility assessment, but there is still a lack of an evaluation method that considers the activity state of the landslide itself. Therefore, this paper establishes a new susceptibility evaluation model that superimposes the active landslide state based on previous susceptibility evaluation models. Based on a multi-phase landslide database, the probabilistic approach was used to evaluate landslide susceptibility in the Miansi town over many years. We chose the elevation, slope, aspect, and distance from the channel as trigger factors and then used the probability comprehensive discrimination method to calculate the probability of landslide occurrence. Then, the susceptibility results of each period were calculated by superposition with the activity rate. The results show that between 2008 and 2014, the proportion of areas with low landslide susceptibility in the study area was the largest, and the proportionof areas with the highest susceptibility was minimal. The landslide area with highest susceptibility gradually decreased from 2014 to 2017. However, in 2017, 15.06% of the area was still with high susceptibility, and relevant disaster prevention and reduction measures should be taken in these areas. The larger area under the receiver operating characteristic curve(AUC) indicates that the results of the landslide susceptibility assessment in this study are more objective and reliable than those of previous models. The difference in the AUC values over many years shows that the accuracy of the evaluation results of this model is not constant, and a greater number of landslides or higher landslide activity corresponds to a higher accuracy of the evaluation results.