地震诱发滑坡的快速评估方法研究:以2017年MS 7.0级九寨沟地震为例

山岳地区强烈地震诱发的滑坡、崩塌等地震次生灾害在造成严重人员伤亡的同时,对社会经济的发展也构成了严重威胁。而震后滑坡分布的快速评估,尤其是滑坡重灾区的确定,则可为救援工作的科学部署和有效开展提供决策支持并减轻地震灾害的损失。2017年8月8日发生于四川省阿坝州九寨沟风景区的MS 7.0级地震诱发了大量的滑坡、崩塌灾害,造成了一定的人员伤亡和财产损失,凸显出进行震后滑坡快速评估的重要性。本文通过对九寨沟地震灾区震前、震后“北京二号”遥感影像的对比分析,解译此次地震诱发的滑坡分布概况。尽管震后影像在局部区域有云团覆盖,影响了震区滑坡解译的详尽程度,但是对于主要发生的滑坡地震高烈度地区(≥Ⅻ度),本文所用影像基本满足解译要求。本文共解译出194个面积大于700 m2的滑坡,这些滑坡主要沿地震烈度长轴方向分布,灾害体平面面积达5.6 km2,影响范围超过600 km2。通过对九寨沟地震灾区的地形、岩性及地震动加速度进行分析,本文采用Newmark刚体滑块模型对该区震后滑坡危险区域进行了预测。预测结果按照危险程度不同划分为5个级别,即高度危险、较高危险、中度危险、较低危险和低度危险。滑坡分布与评估结果呈现出较好的一致性:解译的滑坡主要分布在评估为滑坡高度危险的区域,表明本文所采用方法的有效性。本文对该方法的局限性也进行了讨论,并提出改进建议。     

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。     

2022年MS6.8级泸定地震诱发地质灾害特征与空间分布规律研究

2022年9月5日四川甘孜泸定县发生6.8级地震,诱发了大量地质灾害,造成房屋损毁和多处道路阻断,并导致了严重的人员伤亡。快速预测地震诱发地质灾害空间分布对震后应急救援至关重要。为此,成都理工大学地质灾害防治与地质环境保护国家重点实验室利用已建立的地震诱发滑坡近实时预测模型,在震后2 h内,快速预测了地震诱发滑坡空间分布概率。同时,利用震后重点区域的无人机影像和国产高分六号影像,对地震诱发滑坡进行了智能识别和人工解译及现场调查复核,共解译滑坡3633处,总面积13.78 km2。研究发现本次泸定地震诱发滑坡,较2008年汶川和2017年九寨沟地震滑坡,规模相对较小。本次地震诱发滑坡主要分布于鲜水河断裂带和大渡河两侧,呈带状分布,在磨西镇、得妥镇及王岗坪彝族藏族乡等Ⅸ度烈度区相对集中。对控制滑坡空间分布的地形地貌、地质和地震3类因素9个因子进行分析,发现其主要分布在坡度35°~55°、高程1000~1800 m范围内;受断层控制强烈,主要分布在距断层1 km范围内;在花岗岩中最为发育。上述研究成果获得的地震诱发滑坡及受损道路和房屋分布情况,为震后应急救援提供了重要支撑。     

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...     

汶川震区植被恢复与同震滑坡活动性动态演化分析

强烈的山区地震往往会引发大量同震滑坡,对当地植被覆盖和生长造成直接破坏。作为表现滑坡活动强度的重要指标,同震滑坡体表面的植被恢复情况对评估震后地质灾害的活动情况具有重要意义。然而,受观测资料所限,当前对于震区植被恢复进程的研究多为小尺度范围,而对大区域内植被演化机制以及植被与地质灾害活动性的关系认识不足。因此,采用多时相、长时序（2000—2020年）的高精度遥感影像对汶川地震强震区大范围内的植被恢复过程进行研究,计算得到不同时期植被恢复率,以此探究大范围内植被恢复的普适性规律,同时分析植被恢复与滑坡活动强度变化的关系。研究发现：截至2020年,71.34%区域的同震滑坡表面植被已处于恢复程度较好阶段;高活动强度、中活动强度、低活动强度和基本稳定的滑坡面积比分别为17.6%、12.4%、17.7%和52.3%。同震滑坡地表恢复趋势表明,汶川震区植被预计在震后约17 a恢复至震前平均水平。然而,植被恢复过程和滑坡活动性的变化往往受多种因素的综合影响。虽然滑坡地表植被恢复在一定程度上反映了地震后滑坡活动性的下降,但地震对滑坡活动性的影响将比地表植被恢复到震前水平所持续的时间更长。参考前人研...     

四川汶川地震诱发滑坡与峰值速度的关系

利用汶川地震诱发的滑坡资料和得到的地震动数据,对地震诱发滑坡与峰值速度的关系进行了分析,得到一些基本认识：①地震诱发滑坡与地震动峰值速度(PGV)存在明显的正相关性,可以利用PGV作为判别地震滑坡的判据;②汶川地震龙门山震区可以触发地震滑坡的PGV下限约为0.5m/s;③龙门山震区可以触发地震滑坡的PGV上限约为1.5m/s;④建立了汶川地震龙门山震区PGV衰减关系,可用以估计地震滑坡致灾的范围。利用地震动参数研究地震诱发滑坡具有很好的一致性,可以克服应用烈度时存在的不足。上述研究结果可以应用于震后灾害快速评估工作中,为应急救援方案的制定提供参考信息。     

泸定MS6.8地震同震地质灾害特点及防控建议

强震区同震地质灾害特点、震后地震效应研究是支撑灾后重建和防灾减灾的关键。本文基于震后重点区无人机高清遥感影像解译、震后地质灾害应急排查、极震区地质灾害详查数据,研究了同震地质灾害的数量、空间分布、控制因素,详细分析了震后地质灾害防治工作面临的3个重要风险,并针对灾后重建中关于地质灾害防治工作提出了4点建议。研究结果显示：(1)同震次生地质灾害规模以小型为主,中型次之,大型较少,主要沿大渡河两岸、交通道路沿线、大渡河右岸支流、发震断裂和其他断裂沿线等部位密集分布;(2)控制同震次生地质灾害的主要因素由强至弱分别是地震动、断裂带、地形坡度、地层岩性和强震区工程设防标准不够;(3)震后地质灾害防治主要面临降雨加剧已有灾害点变形和诱发新的灾害、震裂山体可能演变为高位远程灾害链的风险源区、巨量沟道斜坡物源构成泥石流的潜在物源并形成灾害;(4)建议加强“人技结合”的隐患识别体系机制,构建依靠科技的点面结合监测预警机制,统筹各要素科学实施避让搬迁,提高地震活跃强震区工程建设抗灾标准,构建农村切坡建房的技术支撑机制。     

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MS 8.0级地震为例

以汶川MS8.0级地震重灾区的11县市为例,初步提出了基于简化Newmark位移模型的地震滑坡危险性应急快速评估方法。利用汶川地震即时地震动参数、工程地质岩性经验分组及地形坡度数据,借助ArcGIS空间数据建模工具编制了地震滑坡危险性快速评估流程模块。计算了区域浅表层饱和岩土体斜坡的静态安全系数Fs、临界加速度ac,并借此分析了地震滑坡易发性。利用经验式获得了汶川地震Arias强度和区域滑坡位移DN分布,实现了汶川地震重灾区地震滑坡危险性的快速评估,为应急救灾决策提供了参考。通过对比评估结果和震后滑坡调查成果,可知数十处灾难性滑坡绝大部分位于-高危险区的龙门山主中央断裂带两侧约20km地带中,显示了评估方法的可靠性; 同时,分析指出了空间数据精度及更新不足导致局部评估结果欠佳的局限性,并提出了改进建议。     

基于Newmark模型的尼泊尔M_s8.1级地震滑坡危险性快速评估

在研究分析地震灾区地形地貌、地层岩性、地质构造、气象水文和典型地区滑坡的基础上,采用Newmark斜坡累积位移模型对2015年4月25日尼泊尔M_s8.1级地震诱发的滑坡危险性的空间分布状况进行了快速评估,通过典型地区的滑坡遥感解译结果验证表明评估结果具有较好的可信度,初步反映了尼泊尔地震诱发滑坡危险性分布的基本特征。然后考虑降雨作用对震后滑坡危险性的影响,对地震叠加降雨诱发滑坡危险性分布进行了快速预测。研究结果对地震应急救灾中的地质灾害防灾减灾具有重要的参考意义。     

2010年玉树7.1级地震诱发滑坡特征及其地震地质意义

2010年玉树7.1级地震造成了一系列次生地质灾害。笔者在玉树灾区地震地质灾害调查基础上,结合Quickbird高分辨率遥感影像数据和航片影像数据,以目视解译为主,共提取了542处地震滑坡,并首次发现了11处古地震滑坡。调查研究结果显示,玉树地震滑坡主要包括崩塌、狭义的滑坡和土溜等三种类型。其中地震崩塌占到了90%以上,按其物质成分可进一步划分为碎屑型崩塌、碎屑流型崩塌和岩崩等三类。地震滑坡的空间展布特征显示,该区80%以上的地震滑坡集中分布在以玉树活动断层为轴的长约95km、两侧宽2km的廊带区内,并与发震断层距离和宏观震中有很好的相关性,其高密度区与同震地表破裂的空间分段性也有很好的对应关系,体现出典型的走滑型发震断层的控灾特点。同时,还进一步分析了山体坡度、坡体形态、临空面高度和地层岩石与岩体完整度等因素对地震滑坡总体分布的影响。对古地震滑坡的初步研究发现,古地震滑坡的规模、期次和分布特征间接地反映出玉树断裂带在全新世期间曾发生过多次震级强度明显大于本次玉树7.1级地震的古地震事件,这为更深入探索玉树断裂带古地震事件提供了另一种重要的研究途径。此外,地震滑坡分布与地表破裂和极震区破坏程度之间的密切空间关系指示,地震滑坡也可以成为快速圈定宏观震中以及开展极震区地震烈度评价等方面的重要指标。     

GIS支持下CF与Logistic回归模型耦合的九寨沟景区滑坡易发性评价

2017年8月8日九寨沟M_S7.0地震诱发了数以千计的崩滑体,产生的大量松散固体碎屑在降雨作用下极易启动转化为新的滑坡或泥石流形成次生灾害,因此对九寨沟景区进行滑坡易发性评价尤为必要。基于震前、震后高精度遥感影像对比分析结合现场调查,共获取1047处滑坡,总面积为3.88 km2。在分析滑坡发育分布与影响因素关系的基础上,本文选取了构造因子、地形因子、地质因子及其他因子等9个指标,采用确定性系数(CF)模型、逻辑回归(Logistic)模型以及两种模型耦合分析进行滑坡易发性评价。研究结果表明,坡度、坡向、高程和地层岩性是影响滑坡分布的主要因子;研究区被划分为低易发区(60.72%)、中度易发区(24.18%)、高易发区(9.89%)和极高易发区(5.21%),高-极高易发区基本沿沟谷分布,面积为99 km2,其中熊猫海、老虎海周边均为滑坡极高易发区;采用耦合模型比单一模型评价结果更加合理,其结果可作为景区滑坡防治和分段分时开放的参考依据。     

Coseismic landslides triggered by the 8th August 2017 <Emphasis Type="Italic">M</Emphasis><Subscript>s</Subscript> 7.0 Jiuzhaigou earthquake (Sichuan,China): factors controlling their spatial distribution and implications for the seismogenic blind fault identification

On 8th August 2017, a magnitude M_s 7.0 earthquake struck the County of Jiuzhaigou, in Sichuan Province, China. It was the third M_s ≥?7.0 earthquake in the Longmenshan area in the last decade, after the 2008 M_s 8.0 Wenchuan earthquake and the 2013 M_s 7.0 Lushan earthquake. The event did not produce any evident surface rupture but triggered significant mass wasting. Based on a large set of pre- and post-earthquake high-resolution satellite images (SPOT-5, Gaofen-1 and Gaofen-2) as well as on 0.2-m-resolution UAV photographs, a polygon-based interpretation of the coseismic landslides was carried out. In total, 1883 landslides were identified, covering an area of 8.11 km², with an estimated total volume in the order of 25–30?×?10⁶ m³. The total landslide area was lower than that produced by other earthquakes of similar magnitude with strike-slip motion, possibly because of the limited surface rupture. The spatial distribution of the landslides was correlated statistically to a number of seismic, terrain and geological factors, to evaluate the landslide susceptibility at regional scale and to identify the most typical characteristics of the coseismic failures. The landslides, mainly small-scale rockfalls and rock/debris slides, occurred mostly along two NE-SW-oriented valleys near the epicentre. Comparatively, high landslide density was found at locations where the landform evolves from upper, broad valleys to lower, deep-cut gorges. The spatial distribution of the coseismic landslides did not seem correlated to the location of any known active faults. On the contrary, it revealed that a previously-unknown blind fault segment—which is possibly the north-western extension of the Huya fault—is the plausible seismogenic fault. This finding is consistent with what hypothesised on the basis of field observations and ground displacements.     

Distribution and characteristics of landslides induced by the Iwate–Miyagi Nairiku Earthquake in 2008 in Tohoku District, Northeast Japan

The Iwate–Miyagi Nairiku Earthquake in 2008, whose seismic intensity was M. 7.2 in Japan Meteorological Agency (JMA) scale, induced innumerable landslides on the southern flank of Mt. Kurikoma volcano allocated along the Ou Backbone Range in Northeast Japan. Most landslides are detected in a hanging wall side of the seismic fault. Those landslides are classified into five types: deep-seated slide, debris slide, shallow debris slide, secondary shallow debris slide, and debris flow. Most common landslide types induced by the earthquake are shallow debris slides and subsequent debris flows. They are intensively distributed along steep gorges incising a volcanic skirt of Mt. Kurikoma, consisting of welded ignimbrite of the Pleistocene age. Debris flows are also distributed even along gentle river floors in the southern lower flank of the volcano. The area of densely distributed debris slides, shallow debris slides, and debris flows is concordant with that of severe seismic tremor. Thus, genetic processes of landslides induced by the Iwate–Miyagi Nairiku Earthquake in 2008 are attributed to multiple causative factors such as geology, topography, and seismic force.     

Surface recovery of landslides triggered by 2008 <Emphasis Type="Italic">Ms</Emphasis>8.0 Wenchuan earthquake (China): a case study in a typical mountainous watershed

The Ms8.0 Wenchuan earthquake that occurred on 12 May 2008 in southwestern China and triggered numerous landslides is one of the stronger ones in the steep eastern margins of the Tibetan Plateau. The surfaces of these landslides have recovered gradually with vegetation, which provide useful information about the evolution of geologic environment as well as the long-term assessment of landslides after earthquake. The Mianyuanhe watershed shows many co-seismic landslides. The active fault passing through its center is selected as a study area aiming to analyze the annual surface recovery rate (SRR) of landslides by interpretation of remote-sensing images in five periods from 2008 to 2013. The results are here described. (1) Although a large amount of loose deposits were transformed into debris flows, the surfaces of the landslides recovered rapidly with vegetation and almost no landslides occurred at new sites after the Wenchuan earthquake. In the year 2008, the exposed surface projected area (ESPA) of the landslides showed a total area of 56.3 km² and covered 28.9 % of the study area, which was reduced rapidly to 19.1 % in 2011 and 15.8 % in 2013. (2) The study area was divided into four geologic units, including clastic rocks, melange zone, carbonate rocks, and magmatic rocks. Smaller ESPAs and higher SRRs were found in the former two units versus the latter ones. (3) A single large landslide shows an SRR lower than a group of smaller ones having an equal total surface, while the SRRs of debris flows are lower than those of rockfalls and landslides. (4) The vegetation cover would return to the pre-earthquake level in 2020 approximately, which indicates that the impact of the Wenchuan earthquake on landslides and debris-flows activities would cease almost completely.     

汶川震区成兰铁路关键段多尺度滑坡危险性评估

以穿越汶川震区的成兰铁路龙门山关键段为例, 探索提出了强震扰动背景下重大工程场区多尺度滑坡危险性评估方法。利用信息量模型反演评估了汶川地震诱发的同震滑坡空间分布特征, 以此为前提开展了区域和局地两种空间尺度的滑坡危险性预测评估。在区域廊带尺度上, 分别利用可能最大降雨量预测方法和信息量模型, 进行了日超越概率10%的最大降雨量时空分布预测及其诱发滑坡的危险性评估; 同时, 结合地震危险性区划成果, 开展了50年超越概率10%的基本地震动诱发滑坡的危险性评估。在局地场站尺度上, 利用基于崩塌运动过程模拟的Rockfall Analyst软件, 开展了柿子园大桥周边崩塌运动学特征(Runout)模拟和危险性评估。滑坡和崩塌危险性评估的结果分别为铁路规划选线和场站防护设计提供了不同尺度的地质安全依据。      

四川安县高川乡政府滑坡特征及稳定性分析

2008年汶川"5.12"特大地震诱发了为数众多的崩塌、滑坡、泥石流等次生地质灾害,安县高川乡政府滑坡就是其中之一。本文在综合分析滑坡区地质环境条件、滑坡灾害体特征的基础上,进行了滑坡稳定性计算,给出了滑坡稳定性影响因素。     

A seismic landslide susceptibility rating of geologic units based on analysis of characteristics of landslides triggered by the 17 January, 1994 Northridge, California earthquake

One of the most significant effects of the 17 January, 1994 Northridge, California earthquake (M=6.7) was the triggering of thousands of landslides over a broad area. Some of these landslides damaged and destroyed homes and other structures, blocked roads, disrupted pipelines, and caused other serious damage. Analysis of the distribution and characteristics of these landslides is important in understanding what areas may be susceptible to landsliding in future earthquakes. We analyzed the frequency, distribution, and geometries of triggered landslides in the Santa Susana 7.5′ quadrangle, an area of intense seismic landslide activity near the earthquake epicenter. Landslides occurred primarily in young (Late Miocene through Pleistocene) uncemented or very weakly cemented sediment that has been repeatedly folded, faulted, and uplifted in the past 1.5 million years. The most common types of landslide triggered by the earthquake were highly disrupted, shallow falls and slides of rock and debris. Far less numerous were deeper, more coherent slumps and block slides, primarily occurring in more cohesive or competent materials. The landslides in the Santa Susana quadrangle were divided into two samples: single landslides (1502) and landslide complexes (60), which involved multiple coalescing failures of surficial material. We described landslide morphologies by computing simple morphometric parameters (area, length, width, aspect ratio, slope angle). To quantify and rank the relative susceptibility of each geologic unit to seismic landsliding, we calculated two indices: (1) the susceptibility index, which is the ratio (given as a percentage) of the area covered by landslide sources within a geologic unit to the total outcrop area of that unit; and (2) the frequency index [given in landslides per square kilometer (ls/km²)], which is the total number of landslides within each geologic unit divided by the outcrop area of that unit. Susceptibility categories include very high (>2.5% landslide area or >30 ls/km²), high (1.0–2.5% landslide area or 10–30 ls/km²), moderate (0.5–1.0% landslide area or 3–10 ls/km²), and low (<0.5% landslide area and <3 ls/km²).