Emergency rapid assessment of landslides induced by the Luding MS6.8 earthquake in Sichuan of China
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摘要:
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MS6.8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结果能够较好地反映同震滑坡的宏观分布特征,但在磨西台地边缘、大渡河干流两岸吻合程度欠佳,后续将通过提升岩性和地形等数据质量进行改进。有关成果可为震后重建规划、震后长期灾害效应分析等提供参考,同时深化了地震崩滑快速评估技术方法,地震崩滑快速评估的可靠性。
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关键词:
- 泸定地震 /
- 地震崩滑危险性 /
- 应急快速评估 /
- Newmark累积位移模型
Abstract:Seismic landslides can seriously aggravate the losses of earthquake disasters. Therefore, it is of great significance to assessment the distribution of earthquake induced landslides for emergency relief. In this paper, based on the 30 m resolution DEM and regional geologic data with a scale of 1∶500 000, emergency rapid assessment of earthquake induced landslides is carried out using the Newmark cumulative displacement model for the 5 September 2022 Luding MS6.8 earthquake, China. The results show that the earthquake induced landslides are relatively serious in this earthquake. The high hazard zones of the coseismic landslides are about 45 km2, which is mainly distributed on the two banks of the nearly east-west tributaries on the west bank of the Dadu River and the west of the Xianshuihe fault, especially along the Yanzigou, Mozigou, Hailuogou, Feishuigou gullies and the Wandong, Shiyue, Tianwan rivers, posing a great threat to the lives of residents and tourists. The rivers and roads in these tributaries are at high risk of being blocked by landslides. The Lengqi, Xinglong, Moxi and Detuo towns in Luding County and Tianwan, Caoke, Xinmin, Xianfeng, Xieluo and Wajiao towns in Shimian County are at high risk of landslides. The S434 Provincial Road and S211 Provincial Road along the Dadu River near the epicenter are more likely to be blocked by landslides. The predicted earthquake landslide hazard in the Gongga Snow Mountain area is medium, but it is necessary to pay attention to the risks of long range and high position landslide disaster (chain), such as ice avalanche and rock avalanche. Comparison between the distribution of induced landslides in zones with intensity VIII and IX obtained from post-earthquake emergency investigation and remote sensing interpretation shows that the obtained displacements can well reflect the macro distribution of coseismic landslides along the tributaries on the west bank of the Dadu River, but cannot be exerted effectively around the edge of the Moxi platform and the banks of the main stream of Dadu River, which can be enhanced through the improvement of large scale of geologic maps and high quality topography data. The results can provide reference for valuable timely reference information on post-earthquake reconstruction planning and long-time activity of post-earthquake geohazard and risk recognition of landslide disaster chains.
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强震几乎在一瞬间诱发大量崩滑灾害,掩埋房屋和人员,直接造成严重的人员伤亡和财产损失,掩埋道路、堵塞河流延误应急救援,增加自救互救难度,加剧灾害损失[1-2]。这种灾害效应在我国频繁而强烈的地震活动、特殊的地形地貌背景下显得尤为突出[3-6]。例如:2008年汶川地震诱发滑坡达数万处[7],仅北川县城城西1处滑坡就导致1 600人被埋死亡,是汶川地震触发的最严重的滑坡灾难[8];主震导致都汶公路10 km以上路段被滑坡完全覆盖而交通中断,导致数万救灾人员滞留都江堰,无法有效利用黄金救援时间进入极震区[9],凸显出地震崩滑灾害快速评估的必要性。此后,2010年玉树地震[10]、2013年芦山地震[11-12]、2014年鲁甸地震[13-14]、2017年九寨沟地震[15-16]等系列强震诱发崩滑形成的灾难事件频繁发生,进一步使人们认识到快速评估地震崩滑分布在服务应急救灾、灾后重建等工作部署中的重要作用。现阶段,国内外有关地震诱发崩滑评估技术方法研究成果十分丰富,从地震崩滑与发震断裂、震级和震中距等地震参数的关系分析,发展到基于专家经验、数据挖掘、统计分析等指标体系方法[17-18],以及基于力学原理的Newmark累积位移方法,相关成果为地震应急救援决策提供了参考依据。其中,Newmark提出的累积位移分析方法基于力学原理定量分析坡体失稳机制,相比指标体系方法具有不受地质背景差异限制的优势,逐步成为国际主流的地震崩滑位移定量评估方法之一[19]。
2022年9月5日,四川省甘孜州泸定县发生 MS6.8级地震,本次地震的一个突出特点是地震引发的地质灾害多且较为严重,造成大量人员伤亡、房屋建筑和基础设施受损,道路、通信、供水供电等生命线多处中断[20-21]。由于传统地面排查易受震后道路交通阻断、卫星遥感被云雾遮盖、无人机难以短时大范围覆盖等多因素的制约,难以在第一时间快速获取震后宏观灾情。本文利用震前获取的震区地形数据和工程地质岩组资料,采用Newmark累积位移方法获得了本次地震崩滑位移分布,进行了地震诱发崩滑快速评估,指出了地震诱发崩滑高危险区分布,并与实际地震崩滑分布进行对比,提出了防灾减灾建议和进一步研究方向,研究结果对震后重建规划、震后长期灾害效应分析具有重要意义。
1. 地震概况
2022年9月5日12时52分,在四川甘孜藏族自治州泸定县磨西镇发生M
S6.8级地震,震中29.59°N,102.08°E,震源深度16 km,极震区最高烈度Ⅸ度。震中周边20 km内的乡镇有磨西镇、得妥镇、燕子沟镇。震中距泸定县39 km,距康定市47 km,距石棉县48 km、距汉源县62 km,距甘孜藏族自治州52 km。 根据地震部门资料,泸定6.8级地震为主震-余震型地震,通过区域构造、历史地震活动、地震序列类型等资料分析,判定此次地震为走滑型地震,推断发震断裂为鲜水河断裂磨西段[22]。截至9月12日8时0分,共记录到余震2715次,其中3.0级以下余震2699次,3.0级及以上余震16次,3.0~3.9级地震14次;4.0~4.9级地震2次。分析表明:余震呈NNW向分布,震源深度集中在4~15 km。
2. 区域地质背景
泸定MS6.8级地震位于鲜水河断裂带南东段的磨西断裂,地处川滇地块与扬子地块的挤压边界带;该断裂带位于青藏高原东南部,是我国大陆内部地震活动性最强的左行走滑活动断裂带[23]。震区周边历史地震活动强烈,自1720年以来共发生破坏性地震10余次,其中包括7级以上大地震8次,最大地震为1786年康定-泸定
级地震[24-25],震中距此次地震震中约35 km。磨西断裂总体走向NNW—SE,长约150 km,晚第四纪以来的平均水平滑动速率为6.0~9.9 mm/a,为全新世强活动断裂。该区地处青藏高原向四川盆地的过渡区,属于高山峡谷地貌,东靠邛崃山,西依大雪山;邛崃山海拔介于3 000~4 500 m,夹金山主峰4 930 m;大雪山海拔介于4 500~5 500 m,贡嘎山主峰7 556 m。震区高山林立,谷深壁陡,岭谷相间,地形地貌侵蚀切割强烈,不利于斜坡稳定。震中区5 km范围内海拔介于2 680~2 720 m,震中区50 km范围内平均海拔3 266 m,最高海拔7 142 m,最低海拔844 m,相对高差介于2 000~3 000 m,最高达6 500 m。
基于全国1∶50万公开版地质图,分析显示震区地层从下震旦统到第四系均有分布,强烈构造活动导致岩体结构破碎、强度劣化明显,且风化卸荷显著,不利于斜坡稳定。在距震中约50 km范围内(Ⅷ度及以上烈度主要分布区),发育的主要地层包括:中元古界、震旦系、古近系的岩浆岩等,集中在震区西北和东南大部分地区;三叠系雷口坡组、杂谷脑组、侏倭组、宝顶组的碳酸盐岩、碎屑岩及其变质岩等,集中在震区西部和东北部大部分地区;元古界康定岩群的斜长角闪岩、混合片麻岩等,集中在震区北部局部地区;泥盆系和侏罗系的碎屑岩等,集中在震区东部和西部局部地区;第四系松散沉积物沿河谷及谷坡分布,冲洪积物集中在沟口、河床及阶地处,残坡积、冰川、冰水堆积物集中在山顶平台及缓坡地带。本文将前期开展全国地震崩滑危险性评估工作中构建的全国1∶50万工程地质岩组参数数据集[26]作为泸定地震诱发崩滑评估基础数据之一(图1)。该工程地质岩组参数数据集是根据岩性、岩性组合及结构面的性质,将岩组由硬到软划分为5组,即坚硬岩组、较坚硬岩组、较软弱岩组、软弱岩组和松散土体组,每1组内根据软硬程度细分为3小类。
3. 地震崩滑快速评估
Newmark累积位移模型是基于极限平衡理论提出的[26-27],滑块永久位移是在地震作用下,滑体沿最危险滑动面发生瞬时失稳后位移不断累积所产生的;当施加于潜在滑面处的加速度超过临界加速度(ac)时,滑体即发生滑动。由极限平衡原理可得:
(1) (2) 式中:Fs——静态安全系数;
c、
、 ——分别为斜坡岩土体等效黏聚力/kPa、 内摩擦角/(°)和岩土体重度/(kN·m−3);θ——斜坡坡度/(°);
t——潜在滑体厚度/m;
——水的重度/(kN·m−3);m——潜在滑体饱和部分厚度占滑体总厚度的比值。
在数据准备方面,快速搜集整理了区域地层岩性资料、中国地震局发布的最新震源参数,以及美国航空航天局与日本经济产业省发布的最新数字高程模型ASTER GDEM(30 m分辨率)。在快速评估方面,利用自主知识产权的“区域同震滑坡危险性应急评估系统(软著登字第1653463号)”,融合区域地震动经验快速模拟技术和基于Newmark位移模型的滑坡危险性定量评估技术,开展了泸定MS6.8级地震Ⅵ度及以上烈度区同震滑坡分布的快速评估。获得震区斜坡临界加速度(ac)、地震动峰值加速度场(PGA)和地震崩滑位移(Dn)分布结果,评估了地震崩滑对震区主要乡镇和道路等的影响。
3.1 震区斜坡临界加速度( ac)分布特征
斜坡临界加速度是表征斜坡维持自身稳定能力的重要指标,其物理含义是指在地震作用下使坡体产生滑动所需要的最小地震动加速度。斜坡坡度(θ)通过30 m 的DEM数据计算获取,鉴于地震崩滑数量上以浅层为主,取滑体厚度(t)为3 m,震前未经历显著降雨过程,不考虑孔隙水压力的影响取m值为0,岩土体强度参数参考相关技术规范及试验参数进行经验赋值[28]。利用式(1)(2)计算了ac,结果如图2所示:ac较高值(>0.4 g)主要分布在大渡河沿线稍宽缓的河谷盆地及周缘地区,相对不易变形失稳;ac较低值(<0.1 g)主要分布在大渡河右岸新兴乡至冶勒乡沿线的高山峡谷区,相对更易变形失稳。
3.2 地震动峰值加速度场(PGA)分布特征
鉴于极震区台站分布及密度相对稀疏,难以获得精细的震区强震动分布,采用考虑断层投影距的地震动峰值加速度经验衰减关系[29],考虑土层场地效应及震后强震动台站记录修正方法[30-31],估算了水平向地震动峰值加速度分布场(图3),初判极震区Ⅷ度及以上烈度区(PGA>0.2 g)面积约2 038 km2。对比实际强震动记录,台站观测值与预测值整体较为接近,对比断层距50 km以内的17处强震动观测台站,其实测地震动峰值加速度与预测值基本接近,平均误差15.49%(表1),表明预测结果较为可靠。
表 1 泸定地震峰值加速度预测值与断层距50 km以内强震台站观测值对比Table 1. Comparison between the predicted and the observed PGA values of stations with rupture distance less than 50 km台站编码 观测值/g 预测值/g 相对误差(绝对值)/% CNXJ 0.76 0.69 9.35 VL002 0.42 0.40 4.78 V2203 0.19 0.23 16.33 T2471 0.65 0.48 26.51 T2307 0.16 0.17 2.77 T2371 0.18 0.18 1.12 HYYD 0.05 0.07 38.66 VL001 0.16 0.16 2.30 TS003 0.19 0.22 13.24 T2405 0.19 0.22 15.33 T2311 0.11 0.12 11.78 T2408 0.11 0.16 45.96 T2406 0.39 0.36 8.35 TT001 0.11 0.13 16.57 V0172 0.04 0.05 26.06 TY001 0.18 0.17 5.56 SMML 0.17 0.20 18.65 平均值 15.49 3.3 地震崩滑位移( Dn)分布
根据泸定地震预测地震动峰值加速度分布,在获取震区斜坡临界加速度基础上,结合目前对国内外地震崩滑发育规律的经验认识,针对本次地震Ⅵ度及以上烈度区,利用Newmark位移模型[32]计算了地震崩滑位移。该位移表征斜坡在地震作用下的潜在破坏程度,位移值越大表明地震崩滑危险性越高(图4)。Wieczorek等[33]通过室内土体残余强度试验分析提出5 cm是斜坡整体失稳的临界位移值;王秀英等[34]在汶川地震研究中考虑震区地质环境非常脆弱,斜坡覆盖层比较破碎,取2 cm作为地震崩滑临界位移值。本文参考上述有关地震崩滑分布与Newmark临界位移的定量认识进行地震崩滑危险性等级划分。评估结果显示:本次地震诱发崩滑灾害较为严重,地震崩滑高危险区(Dn≥5 cm)面积约为45 km2,主要分布在鲜水河断裂以西大渡河右岸近EW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、田湾河等沿线地震崩滑危险性较高,预测地震崩滑灾害较为严重,对燕子沟、海螺沟冰川森林公园等沟内居民及游客生命安全威胁较大,沟内道路受崩滑阻断风险较高,局部河道有被崩滑堵塞风险;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个乡镇周边地震崩滑危险性较高;震中附近大渡河沿线省道S434和省道S211受地震崩滑阻断可能性较大。地震崩滑中危险区(2 cm≤Dn<5 cm)总面积约为115 km2,主要分布在鲜水河断裂以西各支沟上游斜坡中上部,例如贡嘎雪山一带,需关注冰崩、岩崩型高位远程灾害(链)风险,同时该区域内除同震崩滑以外,受强震震裂的山体可形成局部变形的不稳定斜坡,后续在地震、降雨作用下有失稳危险。
在震后排查阶段,受道路交通阻断、云雾遮盖等多因素的制约,地面排查、卫星遥感解译、无人机航拍等工作范围不能覆盖整个震区,尚未产出此次地震诱发崩塌的完整编录数据。Huang等[35]基于3 m分辨率的Planet卫星图像,对泸定地震度VI以上烈度区同震滑坡进行目视解译,获取5000余处滑坡空间编录,但由于地震后的云层覆盖,尚有部分核心区域未能解译(图4)。铁永波等[21]重点针对有威胁对象的地质灾害隐患点,开展震后应急地面排查和遥感解译等,获取了此次地震Ⅷ度、Ⅸ度区部分区域内的同震诱发崩滑灾害点分布(图4)。本文将同震地震崩滑位移与这两类同震滑坡分布数据进行对比分析,表明在大渡河西岸海螺沟、湾东河、什月河、田湾河等支沟流域滑坡位移分析结果能够较好地反映同震滑坡的宏观分布特征(图5),但在磨西台地边缘、大渡河干流两岸吻合程度欠佳(图4)。王欣等[36]基于深度森林算法,选取地形、岩性、距断层距离、土地覆盖类型、距河流距离、地震动参数等指标构建了地震诱发滑坡空间分布概率的预测模型。对比可以看出,由于指标体系评估方法基于已有的同震滑坡数据库建立,利用泸定地震实际滑坡优化后模型精度提升,显示出指标体系方法不同地区指标适用性有待深化以及区划效果较好而高危险区评估面积较高的不足。本文开展地震崩滑快速评估,采用的是震前全国30 m分辨率地形数据和1∶50万比例尺工程地质岩性分组,本次既是深化地震崩滑快速评估技术方法,也是验证此类数据用于全国地震崩滑快速评估的可靠性。本次评估结果在磨西台地边缘、大渡河干流两岸吻合程度欠佳,这是由两方面原因造成的:一是本次地震诱发类型以浅表层中小型崩塌、碎屑流和滚石灾害为主,以Huang等[35]的编录数据为例,面积≤900 m2的灾害数量占比为27.8%(1393处),900 m2<面积≤3000 m2的灾害数量占比为42.6%(2143处),3000 m2<面积≤5000 m2的灾害数量占比为12.3%(617处),面积>5000 m2的灾害数量占比为17.2%(863处),表现出灾害面积小、数量多的特点,相对于此类小规模崩滑,30 m地形分辨率的地形数据稍显粗略;二是此类灾害物源多为沟谷两岸坡体表面的第四纪堆积物,主要包括冲洪积物、崩坡积物和残积物,含有较多碎石土,本文利用1∶50万比例尺工程地质岩性分组,鲜水河断裂以东的磨西台地边缘及大渡河干流两岸岩性为早震旦世花岗岩和古元古代石英闪长岩,被划分为坚硬岩组,与实际的地震崩滑物源差异较大导致。
4. 结论及建议
4.1 结论
(1)本文利用2022年9月5日泸定MS6.8级地震震前30 m分辨率地形数据结合1∶50万比例尺工程地质岩性分组,采用Newmark累积位移方法开展了泸定地震诱发崩滑快速评估。评估显示鲜水河断裂以西大渡河西岸近EW向支沟两岸地震崩滑危险性较高,其中燕子沟、磨子沟、海螺沟、飞水沟、湾东河、什月河、田湾河等沟内居民及游客生命安全受威胁较大,沟内公路受崩滑阻断风险较高。
(2)通过与此次地震Ⅷ度、Ⅸ度区内震后应急排查、遥感解译等获取的崩滑灾害分布对比,表明在大渡河西岸各支沟Newmark位移分析结果能够较好地反映同震崩滑的宏观分布特征。但在磨西台地边缘、大渡河干流两岸吻合程度欠佳。
4.2 建议
(1)加快构建高质量的地震崩滑快速评估数据集,例如搜集第四纪堆积物分布、提升岩性等数据精度,建立中~大比例尺工程地质岩性参数数据集,提升地震地质灾害应急防御能力。
(2)国内少量Newmark位移模型研究成果以现有模型参数的拟合分析为主,亟需进一步开展Newmark 累积位移与地震动参数的优化组合关系研究,建立适用于我国地震工程地质背景的Newmark位移预测模型。
(3)大渡河西岸各支沟多数区域仍缺乏完整的地震崩滑灾害编录数据,应及时关注获取卫星遥感和无人机航拍影像,进一步开展同震地质灾害的解译制图,服务地震诱发地质灾害规律分析和危险性定量评估。
(4)本次评估显示鲜水河断裂以西各支沟上游斜坡中上部,如嘎山雪山、海螺沟等后缘山体地震崩滑Newmark位移可达2 cm以上,表明该区受强震震裂山体极有可能形成局部变形的不稳定斜坡,建议可采用InSAR、机载LiDAR等手段进行精细识别与监测,防范震后链式风险。
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表 1 泸定地震峰值加速度预测值与断层距50 km以内强震台站观测值对比
Table 1 Comparison between the predicted and the observed PGA values of stations with rupture distance less than 50 km
台站编码 观测值/g 预测值/g 相对误差(绝对值)/% CNXJ 0.76 0.69 9.35 VL002 0.42 0.40 4.78 V2203 0.19 0.23 16.33 T2471 0.65 0.48 26.51 T2307 0.16 0.17 2.77 T2371 0.18 0.18 1.12 HYYD 0.05 0.07 38.66 VL001 0.16 0.16 2.30 TS003 0.19 0.22 13.24 T2405 0.19 0.22 15.33 T2311 0.11 0.12 11.78 T2408 0.11 0.16 45.96 T2406 0.39 0.36 8.35 TT001 0.11 0.13 16.57 V0172 0.04 0.05 26.06 TY001 0.18 0.17 5.56 SMML 0.17 0.20 18.65 平均值 15.49 -
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