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。     

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。     

汶川地震中擂鼓镇地区的滑坡崩塌规律及预测

地震滑坡影响因素与滑坡崩塌分布关系的研究,有助于认识地震滑坡崩塌的发育规律,进而对潜在的地震滑坡危险区段进行划分,为土地的合理使用提供支持.5.12汶川地震引发了大量的滑坡、崩塌、碎屑流等次生灾害,造成了严重的人员伤亡和经济财产损失.以受滑坡、崩塌灾害影响严重的北川县擂鼓镇约180 km2的地区作为研究对象,选取坡度、高程、坡向等影响因素进行确定性及面积发育率分析,探讨它们与滑坡、崩塌等灾害空间分布之间的关系.研究结果表明:在高程低于1 km的地段,滑坡崩塌的发生频率达13.5%,高于其它地段;坡向为东向、北东向、南东向的坡体的滑坡崩塌发生率较其它方向大;随着坡度的增大,滑坡、崩塌的分布也在增大,坡度大于30°的区域滑坡发生频率较高.采用2种方法对研究区进行地震滑坡危险性区划,获得大体一致的划分结果:①基于综合确定性系数与面积发育率方法分析的地震滑坡危险性区划结果中,约有66%的滑坡崩塌落入较高危险和高危险区域;②采用判别分析法获得的地震滑坡危险性区划结果中,约有73%的滑坡崩塌判定为不稳定区域.其中,判别分析法选用的地震动、坡度、曲率等因素在不同地区都对滑坡分布具普遍的影响作用.     

2010年4月14日玉树地震滑坡空间分布与控制变量分析

2010年4月14日07时49分,青藏高原中部,青海省玉树县发生了Ms7.1级大地震(玉树地震).震后遥感影像目视解译与实地调查结果表明,本次地震触发了2036处滑坡,总面积约1.194km2,这些滑坡大概分布在一个面积约1455.3km2的矩形区域内.本文分别使用滑坡数量与滑坡面积这2个标准,对玉树地震滑坡的地震控制...     

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。     

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。     

基于DInSAR-BP神经网络的震后区域滑坡危险性综合评价研究

地震对人类的威胁不仅是发生时直接造成的人员伤亡和财产损失, 更体现在地震所产生的高隐蔽性、高危险性滑坡隐患体带来的危害, 震后区域滑坡隐患体的快速识别和科学评价在震后抢险、排险工作中至关重要。以九寨沟地区“川主寺—九寨沟”公路沿线区域为研究对象, 建立了基于DInSAR-BP神经网络技术的震后区域滑坡危险性综合评价模型。研究结果显示, 九寨沟地区震后的滑坡高危险性区域面积约为2602.35 km2, 是震前的3.4倍, 并且这些区域主要分布在震中东北方向约20 km附近、九寨沟景区内以及川九路前70 km, 符合震后调查情况; 使用多元非线性回归法可以有效计算震后地表形变值对滑坡危险性的影响, 使震后危险性评价结果精度提高了13.9%, 证明了模型在研究区域内具有良好的适用性。     

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。     

鲁甸8.03地震区甘家寨特大型滑坡发育特征及演化过程研究

2014年8月3日鲁甸县M_S6.5级地震造成了617人死亡,并诱发了大量次生滑坡崩塌灾害。其中红石岩滑坡堆积体方量最大,甘家寨滑坡造成的人员伤亡最多。根据笔者对甘家寨特大型滑坡的实地调查和遥感影像解译,分析了该滑坡堆积体的发育特征及演化期次,从活断层破裂角度研究了滑坡的主控因素,认为甘家寨滑坡分为两个发育期次,最新一期滑坡体（本次地震诱发）长约700m,宽约250m,滑体面积约18×104m2,体积约140×104m3,是在20kaBP前发生的古崩塌堆积体在地震诱发下的复活型滑坡,受控于NW向的下水沟断层。最后建议进一步防范鲁甸8.03地震次生灾害的可能危险,加强该地区活动断层的复发周期研究,为灾害恢复重建中的地质环境安全提供基础依据。     

1920年海原8.5级地震高烈度区滑坡编录与分布规律

发生在黄土高原的1920年12月16日的海原M_S8.5级大地震触发了大量的滑坡,这些滑坡直接造成了大量的人员伤亡。近年来,出现了一些关于本次地震触发滑坡的专题研究,然而,这些研究多是基于局部震区或者个别单体滑坡进行,极少有关于该地震触发滑坡详细全面的成果出现。这种情况已经成为了深入理解海原地震触发滑坡的规模与程度、发育规律等的障碍。本研究拟基于谷歌地球平台,采用人工目视解译方法,以海原地震高烈度区（Ⅸ~Ⅺ）为研究区,开展地震滑坡解译工作,并分析这些滑坡的分布规律与影响因子之间的关系。结果表明本次地震在Ⅸ~Ⅺ度区内触发了至少5384处滑坡,滑坡总面积为218.78 km2。滑坡密度最高的区域为Ⅸ烈度圈的北西部分。通过分析这些滑坡与地形、地震、地质等因子的关系发现,高程1700~2000 m为滑坡的高发与高易发区间;大多数滑坡集中发育在坡度15°~25°范围内,滑坡密度随着坡度的增加而显著增加;坡位越低,也就是距离河流越近,滑坡密度越大;新生代地层、尤其是第四系黄土覆盖地区是海原地震滑坡发生的主要区域,也是高易发区域。本文为探索黄土地区地震滑坡发育规律、减轻黄土地震滑坡灾害等提供了科学参考。     

Landslides triggered by the 1949 Khait earthquake, Tajikistan, and associated loss of life

Earthquake-triggered landslides are a major geological hazard in Central Asia. In July 1949, the M7.4 Khait earthquake triggered many hundreds of landslides in a mountainous region near the southern limit of the Tien Shan Mountains, central Tajikistan. These landslides involved widespread rock-slope failure as well as large numbers of flowslides in loess that mantles the steep slopes of the region. In the Yasman valley hundreds of loess landslides coalesced to form a massive loess flow (est. vol. 245 Mm³) that travelled up to 20 km on a slope of only 2°. In an adjacent valley, the Khait landslide involved transformation of an earthquake-triggered rockslide into a very rapid flow by the entrainment of saturated loess into its movement. It travelled 7.41 km over a vertical distance of 1421 m with an estimated average velocity of ~30 m/s. We estimate its volume as 75 Mm³, an order of magnitude less that previously published estimates. The Khait landslide was simulated using DAN. The number of casualties due to earthquake-triggered landslides in the epicentral region was considerable. Approximately 4000 people were killed in the Yasman valley loess flow as 20 villages (kishlaks) were overwhelmed. In the Khait landslide alone we estimate ca. 800 people lost their lives when the villages of Khait and Khisorak were overrun by rapidly moving debris. Our data indicates that a total of approximately 7200 people were killed by earthquake-triggered landslides in the epicentral region of the Khait earthquake and that, in terms of loss of life, the 1949 Yasman valley loess flow was one of the most destructive landslides in recent history.     

2013年7月22日岷县漳县MS6.6级地震滑坡编录与空间分布规律分析

2013年7月22日,中国甘肃省岷县漳县交界地区发生MS6.6级地震。地震触发了大量的滑坡,主要类型为小型的黄土崖崩、滑、倾,还有一些深层连贯型滑坡、大型土质流滑、侧向滑移等地震滑坡类型。本文主要基于地震滑坡野外考察与高分辨卫星影像人工目视解译方法,开展本次地震触发滑坡的编录图制作工作,并基于编录成果开展地震滑坡空间分布规律分析工作。滑坡编录结果表明此次地震至少触发了2330处滑坡。基于GIS平台下开展了地震滑坡与地形控制因子、地质控制因子与地震控制因子的关系统计。结果表明岷县漳县地震滑坡受地形因子的控制作用较小; 受地层岩性的控制作用较大。其中1401处滑坡(占总滑坡的60.13%)分布在下伏基岩为古近系下统地层(Eb)砾岩与砂岩的区域内,其中滑坡密度是所有地层分类中最高的,达到22.78个km-2。地震滑坡与PGA的统计关系并不明显。地震滑坡主要集中在一个与发震断层走向一致的长条形区域内,长约14km,宽约5km。该区域内滑坡数量为1864个,占所有滑坡数量的80%,表明了岷县漳县地震滑坡空间分布的密集特征。文章获得的基于地震事件的区域滑坡编录成果是后续地震滑坡相关科学研究的重要基础与核心数据; 空间分布规律分析成果可为地震区滑坡与泥石流防灾减灾提供科学参考。     

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。     

Pre-conditioning factors and susceptibility assessments of Wenchuan earthquake landslide at the Zhouqu segment of Bailongjiang basin, China

In this study, we present a landslide susceptibility assessment carried out after the devastating 2008 Wenchuan earthquake. For the Zhouqu segment in the Bailongjiang basin in north-western China landslide susceptibility was computed by a logistic regression method. This region has been experiencing landslides for a long time, and numerous additional slope failures were triggered by the 2008 Wenchuan earthquake. The data used for this study consists of slope failures attributed to the 2008 earthquake, the 878 post Wenchuan earthquake landslides and collapses inventory build up by combination the field investigation, monoscopic manual interpretation, image classification and texture analysis using SPOT 5 and ALOS remote-sensing image data. All data derived from remote sensing images are validated during field investigations. The landslide pre-disposing factor database was constructed. A digital elevation model (DEM) with a 30 × 30 m resolution, orthophotos, geological and land-use maps and information on peak ground acceleration data from the 2008 earthquake is used. The statistical analysis of the relation between Wencuan earthquake-triggered landslides and pre-disposing factors show the great influence of lithological and topographical conditions for earthquake-triggered slope failures. The quality of susceptibility mapping was validated by splitting the study area into a training and validation set. The prediction capability analysis showed that the landslide susceptibility map could be used for land planning as well as emergency planning by local authorities in this region.     

Susceptibility assessments of the Wenchuan earthquake-triggered landslides in Longnan using logistic regression

In this study a Wenchuan earthquake-induced landslide susceptibility assessment was carried out in the Longnan area in northwestern China using a GIS-based logistic regression model. This region has frequently been affected by landslides in the past, and was intensively affected by the 5.12 Wenchuan earthquake which received considerable international attention. The data used for this study consist of the landslides triggered by the Wenchuan earthquake and a landslide pre-disposing factor database. Information regarding the landslide causative factors came from additional data sources, such as a digital elevation model (DEM) with a 30 × 30 m² resolution, orthophotos, geological and land-use maps, precipitation records, and information on peak ground acceleration data from the 2008 earthquake. The statistical analysis of the relationship between the Wenchuan earthquake-triggered landslides and pre-disposing factors showed the great influence of lithological and topographical conditions on slope failures. The quality of susceptibility mapping was validated by splitting the study area into training and validation sections. The prediction capability analysis demonstrated that the landslide susceptibility map could be used for land planning as well as emergency planning by local authorities.     

Seismic landslides hazard zoning based on the modified Newmark model: a case study from the Lushan earthquake,China

Seismically triggered landslides can cause great damage to the road construction in mountainous areas. The permanent displacement analysis based on Newmark sliding-block model can evaluate risk of these landslides from the perspective of deformation damage and overall failure probability of slopes. However, the sliding-block model does not consider the attenuation effect of the shear strength on the sliding surface during earthquake, causing the calculated value of Jibson method to be less than the actual value. Therefore, the Newmark model was modified by adding attenuation coefficients to the effective internal friction angle and the effective cohesion of geologic units. The landslide areal density was proposed for hazard zoning with the Wenchuan earthquake data. The results showed that the predicted values agreed well with the real distribution of the landslides triggered by the Lushan earthquake. The proposed hazard zoning method in this paper can predict the severity of seismic landslides in consideration of the environmental changes in mountainous regions after the earthquake and provide support for the site selection in highly seismic areas.

     

An open dataset for landslides triggered by the 2016 Mw 7.8 Kaikōura earthquake,New Zealand

On November 14, 2016, the northeastern South Island of New Zealand was hit by the magnitude Mw 7.8 Kaikōura earthquake, which is characterized by the most complex rupturing mechanism ever recorded. The widespread landslides triggered by the earthquake make this event a great case study to revisit our current knowledge of earthquake-triggered landslides in terms of factors controlling the spatial distribution of landslides and the rapid assessment of geographic areas affected by widespread landsliding. Although the spatial and size distributions of landslides have already been investigated in the literature, a polygon-based co-seismic landslide inventory with landslide size information is still not available as of June 2021. To address this issue and leverage this large landslide event, we mapped 14,233 landslides over a total area of approximately 14,000 km². We also identified 101 landslide dams and shared them all via an open-access repository. We examined the spatial distribution of co-seismic landslides in relation to lithologic units and seismic and morphometric characteristics. We analyzed the size statistics of these landslides in a comparative manner, by using the five largest co-seismic landslide inventories ever mapped (i.e., Chi-Chi, Denali, Wenchuan, Haiti, and Gorkha). We compared our inventory with respect to these five ones to answer the question of whether the landslides triggered by the 2016 Kaikōura earthquake are less numerous and/or share size characteristics similar to those of other strong co-seismic landslide events. Our findings show that the spatial distribution of the Kaikōura landslide event is not significantly different from those belonging to other extreme landslide events, but the average landslide size generated by the Kaikōura earthquake is relatively larger compared to some other large earthquakes (i.e., Wenchuan and Gorkha).