汶川地震强震区地震诱发滑坡与后期降雨诱发滑坡控制因子耦合分析

本文以汶川地震强震区北川县典型研究区为例,利用高分辨率航片、SPOT5卫星图像对北川县典型研究区进行了512地震之后和924降雨之后诱发的滑坡解译,解译结果显示:512地震诱发滑坡1999个,924强降雨诱发滑坡828个,924强降雨导致原有地震滑坡面积扩大的滑坡150个。研究表明:地震和强降雨都是诱发滑坡的动力成因,924强降雨诱发的滑坡面积是512地震诱发滑坡面积的1/4倍,强降雨诱发滑坡的数量增加了41.4%; 强降雨不仅诱发新的滑坡,而且促使原来地震滑坡复活,并扩大其面积,强降雨导致地震诱发的滑坡面积扩大了原面积的68.7%。同时,在遥感解译数据基础之上,开展地震诱发滑坡与降雨诱发滑坡规模对比和控制因子耦合分析及地震与降雨耦合灾害链模式研究,为进一步分析研究地震灾区滑坡的产生、发展趋势、危险性和风险评价等预测预报提供科学依据,也为汶川震区恢复重建中的减灾防灾提供决策参考。     

地震滑坡危险性概念和基于力学模型的评估方法探讨

在我国大陆地区运用基于力学模型的Newmark位移分析方法开展地震滑坡危险性定量评估,尚处在起步阶段.为了进一步明确地震滑坡危险性概念和改进推广基于力学模型的评估方法,首先阐明了狭义的地震滑坡危险性预测评估与震后反演评估的关系; 同时为了应对地震应急、震后重建及潜在地震条件下的不同评估需求,初步提出了广义的地震滑坡危险性评估框架.随后申述了基于Newmark位移分析的地震滑坡危险性评估方法的理论基础、方法分类及最新进展,并以汶川地震滑坡危险性快速评估为例,剖析了目前影响评估有效性的不确定性及空间数据质量等问题,指出了基于力学模型的地震滑坡危险性评估方法的改进方向.建议开展潜在地震及其诱发滑坡危险性的耦合评估,建立适用于我国大陆地区地震滑坡位移分析的经验模型,以便为国家层面的地震滑坡危险性区划服务.     

基于不同位移预测模型的地震滑坡危险性评估研究-以天水地区为例

近年来,Newmark累积位移分析方法经过不断的改进和应用成为国际主流的地震滑坡危险性评估方法之一,众多学者基于位移预测模型开展区域地震滑坡危险性评估,然而鲜有针对不同位移模型对评估结果影响的定量研究。以天水地区为例,基于不同的位移预测模型开展地震滑坡危险性评估,对比位移模型对地震滑坡危险性评估的影响,探讨建立适用于我国的Newmark位移预测模型。结果表明:基于不同位移预测模型评估所得的地震滑坡危险性结果整体趋势一致,均能区分区域地震滑坡危险性等级的相对差异,但在同样的危险性分级标准下,所得中、高危险区的分布范围有较大差异。这与位移模型的函数形式及其区域相关性有关,在引入Newmark累积位移分析方法开展地震滑坡危险性评估的同时,应尽快建立考虑地震动衰减特征和工程地质背景的Newmark位移预测模型,为中国潜在地震滑坡危险性预测评估、震后滑坡快速评估等提供技术支撑。      

四川九寨沟Ms7.0级地震滑坡应急快速评估

基于地震滑坡危险性评估的Newmark累积位移模型,利用震前获取的震区地形数据、区域地质资料,结合地震动近实时获取技术,开展了四川九寨沟M_s7.0级地震诱发滑坡的应急快速评估。地震滑坡位移分析结果表明,同震滑坡活动的中—高强度区分布在断层两侧宽约4 km的带状区域内,整体沿北西方向延伸。其中,极震区的丰雪塘、日则和干海子等城镇驻地及附近道路的滑坡强度相对较高;震前、震后影像对比表明九寨沟地震诱发的滑坡类型以浅表型碎屑流及小规模崩塌为主,且同震碎屑流多是在震前已有碎屑流的基础上进一步活动扩展而来,震后汛期泥石流隐患也不容忽视;通过典型地区滑坡位移分析结果与震前、震后影像对比,表明滑坡位移分析结果能够较好的反映同震滑坡的宏观分布特征,但在场地尺度上吻合程度欠佳,后续将通过提升岩性和地形等数据质量进行改进。研究结果可为灾情研判提供宝贵信息,对提高灾害应急救援效率具有重要意义。     

地震滑坡研究现状与展望

在高山峡谷地区,强烈地震诱发的滑坡灾害数量多、规模大,部分地区造成的危害比地震大,故分析研究地震滑坡对防震减灾工作极重要。本文系统总结了地震滑坡发育分布特征和地震参数与斜坡环境参数关系;地震滑坡动力响应特征与稳定性分析方法;地震滑坡危险性评价等方面研究现状。同时对比了目前滑坡危险性评价中较常用的机器学习算法优劣。     

未受河流阻止的滑坡水平运动距离与滑坡堵江判别

滑坡堵江是滑坡诱发的次生灾害之一,常导致堰塞湖、洪水等次生的灾害链,其根本原因在于滑坡与河流的空间区域小于滑坡运动的距离。如果滑坡的运动未受河流的显著阻止,滑坡的水平运动距离主要受控于滑坡的诱发机制、滑坡体积和滑坡的垂直运动距离。因此,根据未受河流明显阻止的地震和降雨滑坡的水平运动距离与滑坡体积和垂直运动距离的相关性以及预测模型,可对滑坡堵江的危险性进行判别。由此,根据我国西南地区降雨和汶川地震诱发的无明显受阻的滑坡数据,在分析了滑坡等效摩擦系数与体积关系的基础上,分别建立地震和降雨滑坡水平运动距离的预测模型。研究结果表明在不同体积等级滑坡水平运动距离的预测分布图上,地震和降雨诱发的堵江滑坡都明显的偏离其对应的体积曲线,根据建立的经验关系可对滑坡堵江的危险性进行判别。     

西南地区地震滑坡坡度分布特征研究

西南是我国地震滑坡多发区。根据汶川地震、庐霍地震、松潘一平武地震和昭通地震诱发的典型地震滑坡的调查和资料分析,结果表明不同地震诱发的滑坡坡度频率分布存在一定的差异,而地震滑坡与降雨滑坡坡度频率分布的差异较大,其分布规律遵循Logistic分布。通过Logistic分布函数分别建立了典型地震滑坡和区域地震滑坡坡度分布的定量评价方法,可为滑坡影响因子的定量计算、评价提供参考。     

实际滑坡是滑坡危险性评价结果合理性检验最好的标准

王涛等基于简化Newmark位移模型的区域地震滑坡危险性快速评估以汶川MS8.0级地震为例一文的地震滑坡危险性快速评价结果与2008年汶川地震触发实际滑坡空间分布的相关性较低。本文试图通过对该文中基础数据、分析处理过程、研究结果的分析与讨论,找出这种相关性较低的原因。结果表明值得针对王涛等文章中的Arias烈度分布数据的准确性、工程地质岩组的划分情况、汶川地震滑坡危险性评价结果的客观性共三个方面开展更深入的分析与研究。本文对探索与发掘更客观的地震滑坡危险性评价模型起到了积极的作用。     

灾难性地震和降雨滑坡的体积与运动距离研究

为预测和评价灾难性滑坡的致灾机制,基于国内近年来地震和降雨诱发的灾难性滑坡资料,对地震和降雨滑坡的等价摩擦系数H/L、最大水平运动距离L、最大垂直运动距离H与滑坡体积V的关系进行分析。研究灾难性地震和降雨滑坡的远程运动特征以及不同规模滑坡最大水平运动和垂直运动的优势距离。研究结果表明,滑坡的H/L、L、H与V具有幂律关系,其中H/L与V具有负幂律关系,L、H与V具有正幂律关系。同一规模等级的地震和降雨诱发灾难性滑坡的水平和垂直运动距离不同。以H/L＝0.42作为滑坡远程运动的标准,地震诱发的灾难性滑坡与滑坡远程运动的关系较小,而降雨诱发灾难性滑坡与滑坡的远程运动的关系较大。根据滑坡运动距离的累积分布表,以80%滑坡的运动距离所分布的范围,建立了滑坡不同规模等级的优势运动距离区间,同规模等级的地震滑坡和降雨滑坡在水平和垂直运动的优势距离区间上存在差异。灾难性滑坡的运程不仅受滑坡体积的控制还与其诱发机制相关,其研究成果可为由地震和降雨诱发的灾难性滑坡的致灾区域和致灾强度的预测和评价提供参考依据。     

基于降雨响应的黄土丘陵区滑坡危险性预测研究——以宝鸡市麟游县为例

极端降雨易造成群发滑坡灾害,难以作为单体预测.为预测评估黄土丘陵区不同降雨强度诱发滑坡灾害危险性,论文在区域滑坡灾害特征研究的基础上,分析降雨强度特征及滑坡分布特征.以岭南滑坡为代表分析降雨诱发黄土-丘陵区滑坡的形成机制,介绍了无限斜坡模型原理、参数选取,利用GIS空间建模与分析功能,定量完成了无降雨、25 mm、50...     

Topographic and geologic controls on landslides induced by the 2015 Gorkha earthquake and its aftershocks: an example from the Trishuli Valley,central Nepal

The devastating Gorkha earthquake (M _w 7.8) on April 25, 2015 and its aftershocks triggered numerous landslides across the Lesser and Higher Himalayas of central Nepal. This study aims to characterize these landslides, based on the local topography and geology, and to develop data for landslide hazard zoning. This study focused on a mountainous catchment of the Trishuli River, where a digital elevation model was used to examine hilllslope and river profiles, aerial photos were used to identify 155 coherent landslides, and satellite images were used to map 912 earthquake-induced landslides. The topography of this area is mainly characterized by incised V-shaped inner gorges and steep (> 35°) SW-facing scarp slopes. Although most of the coherent landslides were not reactivated by the earthquakes, the Gogane landslide was affected by the earthquake and partly failed. A majority of the earthquake-induced landslides (91%) were new landslides, while the others were enlarged old landslides. The earthquake-induced landslides occurred mainly on the steep slopes of V-shaped inner gorges and scarp slopes, in gneiss and quartzite strata of the Lesser Himalayas, and they were primarily associated with fractured rock masses. This analysis provides a framework for zoning areas vulnerable to earthquake-induced landslides.     

The 2010 Yushu earthquake triggered landslide hazard mapping using GIS and weight of evidence modeling

The Yushu County, Qinghai Province, China, April 14, 2010, earthquake triggered thousands of landslides in a zone between 96°20′32.9″E and 97°10′8.9″E, and 32°52′6.7″N and 33°19′47.9″N. This study examines the use of geographic information system (GIS) technology and Bayesian statistics in creating a suitable landslide hazard-zone map of good predictive power. A total of 2,036 landslides were interpreted from high-resolution aerial photographs and multi-source satellite images pre- and post-earthquake, and verified by selected field checking before a final landslide-inventory map of the study area could be established using GIS software. The 2,036 landslides were randomly partitioned into two subsets: a training dataset, which contains 80 % (1,628 landslides), for training the model; and a testing dataset 20 % (408 landslides). Twelve earthquake triggered landslide associated controlling parameters, such as elevation, slope gradient, slope aspect, slope curvature, topographic position, distance from main surface ruptures, peak ground acceleration, distance from roads, normalized difference vegetation index, distance from drainages, lithology, and distance from all faults were obtained from variety of data sources. Landslide hazard indices were calculated using the weight of evidence model. The landslide hazard map was compared with training data and testing data to obtain the success rate and predictive rate of the model, respectively. The validation results showed satisfactory agreement between the hazard map and the existing landslide distribution data. The success rate is 80.607 %, and the predictive rate is 78.855 %. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low and very low. The landslide hazard evaluation map should be useful for environmental recovery planning and reconstruction work.     

四川泸定MS6.8级地震诱发崩滑灾害快速评估

强震诱发崩滑灾害可严重加剧地震灾害损失,快速评估地震诱发崩滑分布对于应急救灾工作部署具有重要意义。利用2022年9月5日泸定M_S6.8级地震震前30 m分辨率地形数据结合1∶50万比例尺地质图,采用Newmark累积位移方法开展了泸定地震诱发崩滑灾害快速评估。结果显示：(1)地震诱发崩滑灾害较为严重,崩滑高危险区面积约为45 km²,主要分布在鲜水河断裂以西大渡河西岸近东西向支沟两岸,其中以燕子沟、磨子沟、海螺沟、飞水沟、湾东河、什月河、田湾河等崩滑危险性较高,对沟内居民及游客生命安全威胁较大,沟内公路受崩滑阻断风险较高,局部河道有被崩滑堵塞风险;(2)泸定县冷碛镇、兴隆镇、磨西镇、得妥乡等4个乡镇及石棉县田湾乡、草科乡、新民乡、先锋乡、蟹螺乡、挖角乡等6个乡镇崩滑危险性较高;(3)震中附近地区大渡河沿线省道S434和S211受崩滑阻断可能性较大;(4)贡嘎雪山一带预测地震崩滑危险性为中等,但需关注冰崩型、岩崩型高位远程灾害(链)风险。通过与震后应急排查、遥感解译等获取的地震Ⅷ度、Ⅸ度区内发生的崩滑分布对比,表明在大渡河西岸各支沟滑坡位移分析...     

国内外地震滑坡研究：现状、问题与展望

地震滑坡一直是地学界关注的研究热点之一,特别是2005年10月8日克什米尔M_s 7.8地震、2008年5月12日汶川M_s 8.0地震、2010年玉树M_s 7.1地震、2014年云南鲁甸M_s 6.5地震、2015年4月25日尼泊尔M_s 8.1地震以及2017年8月8日九寨沟M_s 7.0地震等一系列强震活动,都不同程度地触发了大量地震滑坡,并伴生了许多次生灾害,从而促进地震滑坡研究进入了新的阶段。本文通过总结国内外地震滑坡研究现状,归纳了地震滑坡的特征和分布规律、地震动参数与地震滑坡关系、边坡地质条件与地震滑坡关系、地震滑坡的动力响应特征、地震滑坡预测以及地震滑坡危险性与风险区划等6方面的研究现状,在此基础上进一步提出了未来地震滑坡应关注的主要研究方向和重点。     

A new approach of combining aerial photography with satellite imagery for landslide detection

Subsequent rainfall after a strong earthquake can easily trigger landslides. Aerial photography is always available after a strong earthquake but not always available in a timely manner after a subsequent rainfall following the earthquake. Sometimes, only panchromatic imagery is available because of its relatively low cost and large cover capacity. To detect multi-temporal landslides induced by earthquake and its post long-term effect, in company of other factors such as subsequent rainfall, traditionally, it needs to carry out image classification multi-times to calculate the variance information. Therefore, the accuracy will be affected by accumulated errors from multi-classification, and the process is very time-consuming. In this paper, a new semi-automatic approach combing aerial photograph with satellite imagery was proposed for rapid mapping of multi-temporal landslides. The approach can enhance the change information of each landslide event in one detection process. In addition, slope units were introduced to separate the detected conjoint landslides. Chenjiaba area, which located in the highest seismic intensity zone of Wenchuan earthquake in Beichuan, China, and had a strong rainfall 4 months later, was selected as a case study to demonstrate the usefulness of this methodology. Accuracy assessment was carried out by comparing those extracted ones with a manually prepared landslide inventory map. Correctly detected were 90.1 and 94.2 % for earthquake-induced landslides and new landslides, respectively. Results show that this approach is capable of mapping different temporal landslides efficiently and quickly.     

Susceptibility mapping of landslides in Beichuan County using cluster and MLC methods

Cluster analysis and maximum likelihood classification (MLC) are exploited to map the post-earthquake landslide susceptibility in Beichuan County that was affected by the Ms 8.0 Wenchuan earthquake. The methodology is applicable even if there is short of training data. Six effective factors are chosen for mapping the susceptibility, including land use, seismic intensity, average annual rainfall, relative relief, slop gradient and lithology. Four clusters are grouped from sampling grid cells by k-means clustering approach. MLC classifies all the cells in the study area into the four clusters according to their statistical characteristics. Four susceptibility classes (extreme low, low, moderate and high) are assigned to these clusters applying expert experience and hazard density. The final map gives a reasonable assessment of post-earthquake landslide susceptibility in Beichuan County. Comparing with the pre-earthquake susceptibility map made in Beichuan County geological disaster survey project, the result t using cluster and MLC classification has a better agreement with the dot density value of post-earthquake landslides in Beichuan County. The susceptibility map can be used to identify safety spots within the high danger area, which are suitable for habitations and facilities. It is also found that more landslides are densely concentrated at the boundary between high and moderate regions, and between high and extreme low regions.     

GIS技术在区域地震滑坡危险性预测中的应用以龙陵地震滑坡为例

地震滑坡是一种有着严重危害的次生地震灾害形式,形成机制复杂,涉及因素众多。运用G IS丰富的空间分析功能,对地震滑坡的影响因素进行研究,并进行潜在地震滑坡区的预测,是地震滑坡研究领域的一种新的发展趋势。本文在对1976年龙陵地震引发的地震滑坡分布特征研究的基础上,结合前人有关中国西南地区地震滑坡特征的研究成果,应用G IS对该区潜在地震滑坡危险区进行了预测。     

地震诱发滑坡空间分布概率近实时预测研究——以2022年6月1日四川芦山地震为例

2022年6月1日17时00分,继2013年芦山地震,时隔9年四川省雅安市芦山县再次发生M_S6.1级地震。地震是诱发山区地质灾害的重要因素之一,往往造成大量的人员伤亡和财产损失。快速准确地获取地震诱发滑坡的空间分布范围对震后应急救援和临时安置点选取至关重要。本文基于全球地震诱发滑坡数据库,采用深度森林算法,建立了地震诱发滑坡空间分布概率近实时预测模型。将该模型应用于“6·1”芦山地震诱发滑坡的快速预测,在震后1 h内获取了滑坡空间分布概率预测结果,并第一时间到达震区进行地质灾害应急调查与模型复核。调查表明,本次地震诱发地质灾害以小型崩塌、滑坡为主,高易发区主要分布在芦山县北部和宝兴县西部的交汇区,断层上盘滑坡数量明显高于下盘。对比模型预测结果与宝兴东河流域地质灾害现场调查数据,发现模型预测准确率达80%以上,特别是相对较大规模的滑坡均发生在模型预测的高易发区,说明模型可以弥补震后现场调查与遥感数据获取时效性方面的不足,为震后应急救援提供科学支撑。