Regional scale rainfall- and earthquake-triggered landslide susceptibility assessment in Wudu County, China

Wudu County in northwestern China frequently experiences large-scale landslide events.High-magnitude earthquakes and heavy rainfall events are the major triggering factors in the region.The aim of this research is to compare and combine landslide susceptibility assessments of rainfalltriggered and earthquake-triggered landslide events in the study area using Geographical Information System(GIS) and a logistic regression model.Two separate susceptibility maps were produced using inventories reflecting single landslide-triggering events,i.e.,earthquakes and heavy rain storms.Two groups of landslides were utilized: one group containing all landslides triggered by extreme rainfall events between 1995 and 2003 and the other group containing slope failures caused by the 2008 Wenchuan earthquake.Subsequently,the individual maps were combined to illustrate the locations of maximum landslide probability.The use of the resulting three landslide susceptibility maps for landslide forecasting,spatial planning and for developing emergency response actions are discussed.The combined susceptibility map illustrates the total landslide susceptibility in the study area.     

Effectiveness analysis of the prediction of regional debris flow susceptibility in post-earthquake and drought site

Debris-flow disasters occurred frequently after the Mw 8.0 Wenchuan earthquake on 12 May 2008 in Sichuan Province, China. Based on historical accounts of debris-flow disaster events, it found that debris flow occurrence is closely related to the impact of earthquakes and droughts, because earthquakedrought activities can increase the loose solid materials, which can transform into debris flows under the effect of rainstorms. Based on the analysis of historical earthquake activity(frequency, magnitude and location), drought indexes and the trend of climate change(amount of rainfall), a prediction method was established, and the regional debris flow susceptibility was predicted. Furthermore, in a debris flow-susceptible site, effective warning and monitoring are essential not only from an economicpoint of view but are also considered as a frontline approach to alleviate hazards. The advantages of the prediction and early monitoring include(1) the acquired results being sent to the central government for policy making;(2) lives and property in mountainous areas can be protected, such as the 570 residents in the Aizi valley, who evacuated successfully before debris flows in 2012;(3) guiding the government to identify the areas of disasters and the preparation for disaster prevention and mitigation, such as predicting disasters in high-risk areas in the period 2012-2017, helping the government to recognize the development trend of disasters;(4) the quantitative prediction of regional debris-flow susceptibility, such as after the Wenchuan earthquake, can promote scientific and sustainable development and socioeconomic planning in earthquake-struck areas.     

小流域山洪灾害危险性分析之降雨指标选取的初步研究

降雨是诱发山洪灾害的直接动力和激发条件,是山洪灾害危险性分析中不可或缺的重要指标。对于不同的研究区,不同频次和历时的降雨对山洪灾害的影响不同,危险性分析所选取的降雨指标也可能不同。本文基于1:5万小流域数据、历史山洪灾害空间分布数据和暴雨图集资料,以江西省婺源县小流域为例,采用相关分析法对初步选取的24个降雨指标进行相关性分析,筛选出相关性不强的降雨指标;利用GIS技术和基于局部Getis-Ord Gi*算法的优化热点分析工具对历史山洪灾害点进行空间聚类分析,获得研究区每个小流域山洪灾害危险度的估值,该值能够较好地反映小流域山洪灾害危险性的空间分布;通过地理探测器模型中的因子探测器和交互探测器对已筛选出的降雨指标和小流域山洪灾害危险度进行综合探测分析,从而获取对该研究区小流域山洪灾害危险性影响较大的降雨指标,即100年一遇最大6 h降雨和100年一遇最大24 h降雨。本文研究对小流域山洪灾害危险性分析降雨指标的定量选取具有参考和指导意义。     

Risk assessment of secondary geological disasters induced by the Yushu earthquake

The Yushu Ms 7.1 earthquake occurred on April 14,2010 in Qinghai Province,China.It induced a mass of secondary geological disasters,such as collapses,landslides,and debris flows.Risk assessment maps are important for geological disaster prevention and mitigation,and also can serve as a guide for post-earthquake reconstruction.Firstly,a hazard assessment index system of secondary geological disasters in the earthquake region was built in this paper,which was based on detailed analysis of environmental and triggering factors closely related to geological disasters in the study area.GIS technology was utilized to extract and analyze the assessment index.Hazard assessment maps of secondary geological disasters were obtained by spatial modeling and overlaying analysis.Secondly,an analysis of the vulnerability of hazard bearing bodies in the area was conducted,important information,such as, population density,percentage of arable land, industrial and agricultural outputs per unit area were regarded as assessment indices to evaluate socioeconomic vulnerability.Thirdly,the risk level of secondary geological disasters of the area was obtained by the formula:Risk=Hazard×Vulnerability. Risk assessment maps were categorized into four levels,including"low","moderate","high"and"very high".These results show that some urban areas are at very high risk,including Jiegu,Chengwen,Xiaxiula and Sahuteng towns.This research can provide some references and suggestions to improve decisionmaking support for emergency relief and post- earthquake reconstruction in the study area.     

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.     

基于三种机器学习算法的山洪灾害风险评价

依据洪灾风险概念模型,从触发因子、孕灾环境和承灾体3方面选取江西省的12个洪灾风险指标,采用k近邻、随机森林、AdaBoost 3种机器学习算法构建洪灾风险评价模型。利用精度、Kappa系数、ROC曲线（AUC值）3种定量评估指标评价洪灾风险模型,基于随机森林和Boruta特征提取算法共同分析指标重要性,最后对比3种模型绘制的江西省山洪灾害风险分区图并分析山洪灾害分布特征。结果表明：① AdaBoost模型的精度、Kappa系数和AUC值的平均值为别为0.902、0.870和0.826,精度和Kappa系数略优于随机森林,AUC值与随机森林相当,而k近邻模型的3种性能指标均低于前2种算法;② 农田生产潜力、年最大6 h暴雨均值、年最大1 h暴雨均值、归一化差值植被指数、年降雨量均值这5个指标对最终的洪灾风险形成具有非常重要作用;③ 江西省较高风险区与最高风险区的面积和约占江西省总面积的34.4%,且主要分布于高降雨量、高暴雨量、农田生产潜力大的山区。     

基于数据级任务分解的大范围地质灾害预警并行计算架构设计与应用

为实现大范围地质灾害预警实时分析计算,搭建了地质灾害预警并行计算架构。结合地质灾害隐患点的现状和监测设备的实际情况,以地质灾害隐患点为分析计算单元,采用数据级并行计算方式对地质灾害计算任务进行分解,实现了任务生成、分解、派发、计算等功能;采用MPI和Socket套接字相结合的方式,达到了并行计算与高效通信的目的;将该并行计算架构应用于某省2016年8月2~4日台风造成的大范围强降雨状况下的地质灾害预警计算实验验证。结果表明:在大范围地质灾害预警中,该并行计算架构随着执行进程数增加而获得一定的加速比,当执行进程达到16个时加速比可达5.652,明显缩短了传统串行计算所需要的时间,实现了地质灾害的实时预警。     

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.     

GIS-based evaluation on the fault motion-induced coseismic landslides

Earthquake-induced potential landslides are commonly estimated using landslide susceptibility maps. Nevertheless, the fault location is not identified and the ground motion caused by it is unavailable in the map. Thus, potential coseismic landslides for a specific fault motion-induced earthquake could not be predicted using the map. It is meaningful to incorporate the fault location and ground motion characteristics into the landslide predication model. A new method for a specific fault motion-induced coseismic landslide prediction model using GIS (Geographic Information System) is proposed herein. Location of mountain ridges, slope gradients over 45 o , PVGA (Peak Vertical Ground Accelerations) exceeded 0.15 g, and PHGA (Peak Horizontal Ground Accelerations) exceeded 0.25 g of slope units were representing locations that initiated landslides during the 1999 Chi-Chi earthquake in Taiwan. These coseismic landslide characteristics were used to identify areas where landslides occurred during Meishan fault motion-induced strong ground motions in Chiayi County in Taiwan. The strong ground motion (over 8 Gal in the database, 1 Gal = 0.01 m/s 2 , and 1 g = 981 Gal) characteristics were evaluated by the fault length, site distance to the fault, and topography, and their attenuation relations are presented in GIS. The results of the analysis show that coseismic landslide areas could be identified promptly using GIS. The earthquake intensity and focus depth have visible effects on ground motion. The shallower the focus depth, the larger the magnitude increase of the landslides. The GIS-based landslide predication method is valuable combining the geomorphic characteristics and ground motion attenuation relationships for a potential region landslide hazard assessment and in disaster mitigation planning.     

The formation of the Wulipo landslide and the resulting debris flow in Dujiangyan City,China

The Wulipo landslide, triggered by heavy rainfall on July 10, 2013, transformed into debris flow,resulted in the destruction of 12 houses, 44 deaths, and 117 missing. Our systematic investigation has led to the following results and to a new understanding about the formation and evolution process of this hazard. The fundamental factors of the formation of the landslide are a high-steep free surface at the front of the slide mass and the sandstone-mudstone mixed stratum structure of the slope. The inducing factor of the landslide is hydrostatic and hydrodynamic pressure change caused by heavy continuous rainfall. The geological mechanical model of the landslide can be summarized as "instability-translational slide-tension fracture-collapse" and the formation mechanism as "translational landslide induced by heavy rainfall". The total volume of the landslide is 124.6×104 m3, and 16.3% of the sliding mass was dropped down from the cliff and transformed into debris flow during the sliding process, which enlarged 46.7% of the original sliding deposit area. The final accumulation area is found to be 9.2×104 m2. The hazard is a typical example of a disaster chain involving landslide and its induced debris flow. The concealment and disaster chain effect is the main reason for the heavy damage. In future risk assessment, it is suggested to enhance the research onpotential landslide identification for weakly intercalated slopes. By considering the influence of the behaviors of landslide-induced debris flow, the disaster area could be determined more reasonably.     

湖南省山丘区小流域山洪灾害危险性评价

本文采用信息量模型法研究湖南省山丘区小流域山洪灾害的危险性程度。信息量模型的最大意义是能从影响山洪灾害发生的众多因素中找到“最佳因素组合”。基于湖南省1955-2015年近60年的历史山洪灾害数据,结合地形、下垫面以及降雨条件,利用信息量模型按危险性程度高低划分出湖南省山丘区山洪灾害危险性的分布情况。研究结果表明,湖南省山丘区山洪灾害容易发生在坡度小于10°,高程小于100 m,起伏度小于30 m,土地覆被为人工表面,土壤类型为粘土以及降雨量在1584.3~1662.0 mm之间的区域。湖南省山丘区危险等级较高的地级市有永州市、郴州市、株洲市、岳阳市、娄底市以及长沙东部山区,经过混淆矩阵验证后,通过信息量方法建立的山洪灾害危险性评价模型准确率为75.36%,基本可信。     

基于信息量模型的地质灾害易发性评价:以川东南古蔺县为例

地质灾害威胁着山区人民生命财产安全, 进行地质灾害易发性评价有助于山区城镇进行规划与建设时规避灾害风险。以川东南古蔺县为例, 基于ArcGIS空间分析获取了研究区高程、坡度、岩性、斜坡结构、植被指数、距断层距离和距道路距离7个评价因子, 采用信息量模型分别对滑坡和崩塌灾害进行易发性评价后, 进一步利用ArcGIS单元统计功能对比了滑坡和崩塌易发性的信息量值, 选取相对更大的信息量值作为该栅格的最终信息量值, 绘制了研究区综合地质灾害易发性图, 利用自然断点法将古蔺县按信息量值的大小划分为极低、低、中、高和极高易发区。结果表明: 地质灾害主要分布在断层和道路附近, 断层和人类工程活动是造成研究区地质灾害频发的主要原因; 高易发区与极高易发区面积之和为1 315.62 km2, 占全区总面积的41.32%;预测模型性能经ROC曲线检验, AUC值为0.812 5, 说明栅格最大值法预测的古蔺县综合地灾易发性效果良好。      

基于修正Green-Ampt模型的降雨诱发区域浅层斜坡失稳灾害分析

由于具有类似的工程地质和水文地质条件, 在高度相关的降雨作用下, 同一个区域中的降雨诱发浅层斜坡失稳灾害常成群出现。在区域尺度预测浅层斜坡失稳灾害对滑坡灾害的防灾减灾工作具有重要的意义。为此, 提出了一种基于力学原理的降雨诱发浅层斜坡失稳灾害预测新模型RARIL。该模型采用修正Green-Ampt模型进行降雨入渗分析, 采用无限体边坡模型进行安全系数计算, 利用可靠度原理考虑区域斜坡稳定性分析中的参数不确定性。该模型具有可考虑降雨诱发浅层斜坡的失稳力学机理、可考虑区域内斜坡土体参数不确定性, 以及计算效率高、易于在GIS平台上实现等优点。案例分析表明, RARIL模型较为准确地预测了2010年8月12日11∶00至2010年8月14日9∶00期间强降雨在四川省汶川县映秀镇附近的303省道K0-K20段沿线区域引发的滑坡灾害, 研究结果证明RARIL模型在预测降雨诱发区域斜坡失稳灾害方面有很好的应用前景。      

日照市地质灾害现状及防治建议

日照市地质灾害隐患点共计90处,灾害规模以小型为主。利用地质灾害危害程度评价、地质灾害稳定性、危险性评价及地质灾害易发程度综合分区评价,查明了地质灾害点分布位置,将地质灾害点的基本单元格进行现状、潜在地质灾害强度分析,其他基本单元格进行潜在地质灾害强度分析,确定各基本单元格易发程度。通过MapGIS软件,将相同易发程度的基本单元格合并连接成区,将地质灾害易发程度划分为高易发区、中易发区、低易发区,依据地质环境条件、地质灾害发育现状、灾害变化趋势、灾害危害特征,划分为重点、次重点和一般防治区,提出详细的地质灾害防治目标及对策建议,为日照市开展地质灾害预警预报示范区的建设工作提供了技术支撑。     

基于多源卫星遥感的暴雨灾情时空动态信息的提取

强暴雨淹没耕地形成灾害的同时,对耕地作物的生长也产生着极大的影响,而暴雨灾害对耕地作物生长的影响是一个渐变过程,需要由时空动态的观测进行监测。多源卫星遥感观测技术具有捕捉地面瞬间状态和刻画过程的优势。论文利用Terra/MODIS、Landsat和Sentinel卫星观测数据,挖掘多源卫星遥感观测数据,提出了一种利用NDVI变化的特征值进行灾情动态信息提取方法;并以2016年发生暴雨灾害的巢湖地区为实验区进行了方法的应用和讨论。结果表明,基于MODIS多时相NDVI变化结果提取的信息能够获得受灾害影响开始时期和持续时长等丰富的时空动态信息,根据这些信息可以统计得出大范围区域中受灾害影响的面积。另外,结合利用30 m和10 m的Landsat和Sentinel观测数据提取的水淹区,可为在暴雨致灾范围方面提供准确的参考信息。多源遥感作为评估灾情信息的依据之一,其获取的灾情动态信息能够为灾后耕地的恢复情况以及国家灾后损失评估和救助决策提供科学的数据依据。     

湖北省黄冈市降雨型滑坡气象预警判据

黄冈市是湖北省汛期地质灾害频发区之一, 地质灾害类型以滑坡为主, 其中75%为降雨型滑坡。通过统计分析黄冈市近10年滑坡与降雨的相关关系, 在考虑黄冈市地质灾害易发性分区基础上, 研究黄冈市降雨型滑坡的降雨阈值, 利用逻辑回归模型建立滑坡发生的概率预测模型, 再针对不同等级易发区提出对应的气象预警判据。最后以历史降雨及其滑坡事件检验预警判据的合理性与可信度。结果表明, 所建立的气象预警判据在时间尺度上由以往依托气象部门的中长期预警精细到了24 h的短临预警, 在空间尺度上确定了不同等级易发区的降雨型滑坡气象预警判据。预警准确率大幅提升, 显著提高了黄冈市降雨型滑坡气象预警精度, 可为临灾转移提供精细化的技术指导, 有效降低降雨型滑坡灾害带来的生命财产损失。      

陇东黄土区地质灾害气象预警方法与应用——以泾川县为例

在地质灾害详细调查的基础上,基于GIS平台以地质灾害点密度为依据生成初步地质灾害易发性区划图.从诱发地质灾害的内部因素出发将地层岩性、地形坡度、地貌类型、植被覆盖率、多年降雨量分级后,叠加到初步易发性区划图中,生成了地质灾害气象预警区划基图.以降雨作为诱发地质灾害的主导外在因素,重新对泾川县进行了地质灾害气象预警区划,...     

滑坡灾害预测预报信息共享平台

 滑坡是最常见的一种地质灾害,其主要诱因是降雨。滑坡灾害多发生在雨量充沛地域或洪水季节。南京市受自然环境和地质环境的影响,滑坡是其最主要的地质灾害类型之一,为了有效地预测滑坡的发生情况并最大限度地减少滑坡灾害为南京带来的损失,本文在已有的南京市地质灾害易发区等研究的成果上,结合南京市历史滑坡数据、气象资料和地质灾害预测数学模型构建了南京市滑坡灾害预测方法并确定了南京市滑坡灾害预测预报技术流程。在该预测方法和技术流程的基础上,本文同时应用了数据库技术、ArcGIS Server技术、AJAX远程调用技术、网页局部刷新技术和地图缓存技术等,融合地理信息系统功能与滑坡灾害预测预报业务功能,开发了南京市滑坡灾害预测预报信息共享平台。该平台可以对滑坡灾害基础数据和实时气象数据动态、科学地管理,结合南京市实时降雨数据可实现滑坡灾害预测预报并将灾害信息实时在线发布,同时提供对滑坡灾害信息的查询、检索、统计分析等功能,最终通过该信息共享平台,为南京市滑坡灾害的防灾减灾提供决策支持,为其他需要建立滑坡灾害预测信息共享平台的城市提供参考。     

Risk Assessment of Disaster Chain: Experience from Wenchuan Earthquake-induced Landslides in China

This paper deals with the formative process of the Wenchuan earthquake disaster chain risk. Selected earthquake-landslides chain risk is critically evaluated by the probability of landslide displacement failure based on the Newmark's permanent-deformation model. In this context, a conceptual model of regional disaster chain risk assessment was proposed, in which the hazardformative environments sensitivity was the core factor as well as the main difference compared with single disaster risk assessment. The disaster chain risk is accumulation of primary disaster risk and the secondary disasters risks. Results derived from the Wenchuan case proved that the conceptual model was suitable for the disaster chain risk assessment, especially the sudden disaster chain. This experience would offer greater potential in application of conceptual model of disaster chain risk assessment, in the process of large-scale disaster risk governance.     

Non-structural mitigation programs for sediment-related disasters after the Chichi Earthquake in Taiwan

Following the Chichi Earthquake (M_L=7.3) in 1999, sediment-related disasters, such as landslides and debris flows, have become more frequent in Taiwan. Because engineering structures cannot be fully and rapidly emplaced, the government has initiated non-structural hazard mitigation programs. Initially, community debris flow evacuation drills were promoted in 2000. Typhoon Toraji caused numerous debris flow events in July 2001, and some communities evacuated according to the drills, significantly reducing the numbers of possible casualties. Based on that result, the government expanded the program for evacuation drills. Secondly, the early warning system created after the Chichi Earthquake will prevent many potential future casualties. Rainfall threshold values for debris flow warnings in different areas are determined from information received from local weather stations and modified for local geomorphologic situations. Realtime information is gradually being integrated to create a debris flow disaster warning system, the goal of which is to provide warnings to zones in which debris flows are likely. The warning system was launched in 2005 and has two levels of alarms: yellow and red. The final, red alarm triggers enforced evacuation. Overall, the decrease in casualties from debris flows during the decade after the Chichi Earthquake is not the result of a decrease in number or severity of sediment related disasters, but is more directly related to the gradually improved early warning and evacuation system. However, the compound hazards resulting from Typhoon Morakot in 2009 remind us of the ongoing need for improving the existing mitigation system.