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Article(id=1149773876554588177, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149773869357167407, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2404086, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1717257600000, receivedDateStr=2024-06-02, revisedDate=1736956800000, revisedDateStr=2025-01-16, acceptedDate=null, acceptedDateStr=null, onlineDate=1752057053936, onlineDateStr=2025-07-09, pubDate=1746633600000, pubDateStr=2025-05-08, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752057053936, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752057053936, creator=13701087609, updateTime=1752057053936, updator=13701087609, issue=Issue{id=1149773869357167407, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='13', pageStart='5273', pageEnd='5704', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752057052207, creator=13701087609, updateTime=1768456769392, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1218559268744253990, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149773869357167407, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1218559268744253991, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149773869357167407, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=5330, endPage=5339, ext={EN=ArticleExt(id=1149773876902715410, articleId=1149773876554588177, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Characteristics and Formation Mechanism of High-altitude and Highly Vegetation-covered Landslides, columnId=1156262729351549255, journalTitle=Science Technology and Engineering, columnName=Papers·Astronomy and Geosciences, runingTitle=null, highlight=null, articleAbstract=

The high-altitude & dense-vegetation landslide is difficult to investigate and lack of data, its appearance and subsurface information also difficult to get. Therefore it is difficult to identify and threat the road greatly. A case study of the Xiaojiapo landslide was presented. Detailed on-site geological surveys were performed, and drone-based oblique and orthophoto imaging techniques were employed to get the landslide's characteristics. Historical deformation of the landslide was analyzed using satellite image, airborne LiDAR was used to collect point cloud and digital imagery data of the landslide surface. A digital elevation model and centimeter-level three-dimensional model of the landslide surface were created following vegetation removal to assess the surface characteristics. The combined investigations reveal that the Xiaojiapo landslide is situated at an elevation of 3 030 m with a vegetation coverage reaching up to 90%. It is a typical landslide with high-altitude and dense vegetation. The key internal factors contributing to the landslide including the unique alpine valley topography, the slope structure with advantageous free faces, and easily erodible geological layers. Precipitation induces internal water infiltration, which reduces the strength of the rock and soil mass. Additionally, freeze-thaw cycles further diminish slope strength, while earthquakes and road constructions disturb the internal structure, weakening it further. These combined internal and external factors drive the landslide deformation. This study offers technical insights for the landslide identifying, early-warning, and mitigation of road landslides in high-altitude regions with dense vegetation.

, correspAuthors=Hong-ling TIAN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Xiao-yan ZENG, Hong-ling TIAN, Cheng-zhi WEN, Xiang GU, Song CHEN), CN=ArticleExt(id=1149773920997434123, articleId=1149773876554588177, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=高原区高植被覆盖型公路滑坡特征及成因机制分析, columnId=1156262730077163858, journalTitle=科学技术与工程, columnName=论文·天文学、地球科学, runingTitle=null, highlight=null, articleAbstract=

高原高植被覆盖型滑坡调查难度大,资料不足,滑坡形态及内部信息获取难,隐蔽性高,对道路威胁大。以四川省小金县肖家坡滑坡为例,在现场详细地质调查的基础上,运用无人机倾斜及正射摄影技术识别滑坡的形态及规模;通过卫星遥感影像分析滑坡的历史变形;并利用机载LiDAR获取滑坡地表点云及数字影像数据,得到去植被后滑坡地表数字高程模型及厘米级滑坡地表三维模型,获取去植被后滑坡地表信息,从而对高原区高植被覆盖滑坡的基本特征及成因机制进行分析。结果表明:肖家坡滑坡顶部海拔3 030 m,植被覆盖度90%,为典型的高原高植被覆盖滑坡,独特的高原沟谷型地貌特征、具有良好临空面、斜坡结构简单地层易滑、雨水易渗透入坡体并形成积水区为诱发滑坡的主要内因;外部因素中长期降水使坡体内部渗水软化,岩土体强度降低,冻融循环进一步弱化其坡体强度,地震与人类工程活动对土体结构扰动一步降低坡体稳定性。在内外诱因的共同驱使下,滑坡变形逐渐加大并产生逐级滑移。研究结果可对高原区高植被覆盖型公路滑坡的预测预报及防灾减灾提供一定的技术支持。

, correspAuthors=田宏岭, authorNote=null, correspAuthorsNote=
* 田宏岭(1974—),男,汉族,河南太康人,博士,高级工程师。研究方向:滑坡调查评估、监测预警。E-mail:。
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曾小艳(1996—),女,羌族,四川茂县人,硕士研究生。研究方向:滑坡监测预警。E-mail:。

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曾小艳(1996—),女,羌族,四川茂县人,硕士研究生。研究方向:滑坡监测预警。E-mail:。

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曾小艳(1996—),女,羌族,四川茂县人,硕士研究生。研究方向:滑坡监测预警。E-mail:。

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Chinese Journal of Rock Mechanics and Engineering, 2008, 27(12): 2585-2592., articleTitle=Research on the development and distribution law of geological hazards triggered by the “5·12” Wenchuan earthquake, refAbstract=null)], funds=[Fund(id=1175114627299033276, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773876554588177, awardId=2018YFE0100100-4, language=CN, fundingSource=国家重点研发计划(2018YFE0100100-4), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1175114620672032870, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773876554588177, xref=1, ext=[AuthorCompanyExt(id=1175114620680421479, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773876554588177, companyId=1175114620672032870, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 State Key Laboratory of Mountain Hazards and Engineering Resilience, Chengdu 610299, China), 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主滑坡区 次滑坡区 古(老)滑坡区

, figureFileSmall=p5maAaBy4koGd54kdu5J5g==, figureFileBig=vJboNAkU4/TNF5NpfHhz3A==, tableContent=null), ArticleFig(id=1175114625046692006, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773876554588177, language=EN, label=Fig.7, caption=A full view of the landslide and main landslide zoning map, figureFileSmall=bTPCI2Eu60LrgkmBlpzYxQ==, figureFileBig=Ej9EYS3JXIslsj8021INNg==, tableContent=null), ArticleFig(id=1175114625109606567, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773876554588177, language=CN, label=图7, caption=滑坡全貌及主滑坡分区图, figureFileSmall=bTPCI2Eu60LrgkmBlpzYxQ==, figureFileBig=Ej9EYS3JXIslsj8021INNg==, tableContent=null), ArticleFig(id=1175114625193492648, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773876554588177, language=EN, label=Fig.8, caption=Details of the landslide backwall, figureFileSmall=sZF6ZKz1MyhJEVcWH1osPA==, figureFileBig=zeKosuuCongTKbXxt3OvIg==, tableContent=null), 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label=Fig.10, caption=Details of terrace in the sliding zone of landslide, figureFileSmall=4K+UnANkSlMmCdvktmKg9w==, figureFileBig=7LEjY23PIKKEb58s6Vje0A==, tableContent=null), ArticleFig(id=1175114625822638253, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773876554588177, language=CN, label=图10, caption=滑动区部分台坎细节图, figureFileSmall=4K+UnANkSlMmCdvktmKg9w==, figureFileBig=7LEjY23PIKKEb58s6Vje0A==, tableContent=null), ArticleFig(id=1175114625893941422, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773876554588177, language=EN, label=Fig.11, caption=The deposits in the accumulation area, figureFileSmall=cptakA30vNTSCBlDY7peIg==, figureFileBig=u0lu7HJFSBogF2mxSkWR4A==, tableContent=null), ArticleFig(id=1175114625965244591, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773876554588177, language=CN, label=图11, caption=堆积区堆积物, figureFileSmall=cptakA30vNTSCBlDY7peIg==, 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高原区高植被覆盖型公路滑坡特征及成因机制分析
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曾小艳 1, 2, 3 , 田宏岭 1, 2, 3, * , 温成志 1, 2, 3 , 顾乡 4 , 陈松 4
科学技术与工程 | 论文·天文学、地球科学 2025,25(13): 5330-5339
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科学技术与工程 | 论文·天文学、地球科学 2025, 25(13): 5330-5339
高原区高植被覆盖型公路滑坡特征及成因机制分析
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曾小艳1, 2, 3 , 田宏岭1, 2, 3, * , 温成志1, 2, 3, 顾乡4, 陈松4
作者信息
  • 1 山地自然灾害与工程安全全国重点实验室, 成都 610299
  • 2 中国科学院、 水利部成都山地灾害与环境研究所, 成都 610299
  • 3 中国科学院大学, 北京 101408
  • 4 四川阿坝交通建设投资有限责任公司, 马尔康 624000

    • 曾小艳(1996—),女,羌族,四川茂县人,硕士研究生。研究方向:滑坡监测预警。E-mail:。

通讯作者:

* 田宏岭(1974—),男,汉族,河南太康人,博士,高级工程师。研究方向:滑坡调查评估、监测预警。E-mail:。
Characteristics and Formation Mechanism of High-altitude and Highly Vegetation-covered Landslides
Xiao-yan ZENG1, 2, 3 , Hong-ling TIAN1, 2, 3, * , Cheng-zhi WEN1, 2, 3, Xiang GU4, Song CHEN4
Affiliations
  • 1 State Key Laboratory of Mountain Hazards and Engineering Resilience, Chengdu 610299, China
  • 2 Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610299, China
  • 3 University of Chinese Academy of Sciences, Beijing 101408, China
  • 4 Sichuan Aba Transportation Construction Investment Co. , Ltd. , Maerkang 624000, China
出版时间: 2025-05-08 doi: 10.12404/j.issn.1671-1815.2404086
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摘要
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高原高植被覆盖型滑坡调查难度大,资料不足,滑坡形态及内部信息获取难,隐蔽性高,对道路威胁大。以四川省小金县肖家坡滑坡为例,在现场详细地质调查的基础上,运用无人机倾斜及正射摄影技术识别滑坡的形态及规模;通过卫星遥感影像分析滑坡的历史变形;并利用机载LiDAR获取滑坡地表点云及数字影像数据,得到去植被后滑坡地表数字高程模型及厘米级滑坡地表三维模型,获取去植被后滑坡地表信息,从而对高原区高植被覆盖滑坡的基本特征及成因机制进行分析。结果表明:肖家坡滑坡顶部海拔3 030 m,植被覆盖度90%,为典型的高原高植被覆盖滑坡,独特的高原沟谷型地貌特征、具有良好临空面、斜坡结构简单地层易滑、雨水易渗透入坡体并形成积水区为诱发滑坡的主要内因;外部因素中长期降水使坡体内部渗水软化,岩土体强度降低,冻融循环进一步弱化其坡体强度,地震与人类工程活动对土体结构扰动一步降低坡体稳定性。在内外诱因的共同驱使下,滑坡变形逐渐加大并产生逐级滑移。研究结果可对高原区高植被覆盖型公路滑坡的预测预报及防灾减灾提供一定的技术支持。

高原  /  高植被覆盖  /  公路滑坡  /  成因机制

The high-altitude & dense-vegetation landslide is difficult to investigate and lack of data, its appearance and subsurface information also difficult to get. Therefore it is difficult to identify and threat the road greatly. A case study of the Xiaojiapo landslide was presented. Detailed on-site geological surveys were performed, and drone-based oblique and orthophoto imaging techniques were employed to get the landslide's characteristics. Historical deformation of the landslide was analyzed using satellite image, airborne LiDAR was used to collect point cloud and digital imagery data of the landslide surface. A digital elevation model and centimeter-level three-dimensional model of the landslide surface were created following vegetation removal to assess the surface characteristics. The combined investigations reveal that the Xiaojiapo landslide is situated at an elevation of 3 030 m with a vegetation coverage reaching up to 90%. It is a typical landslide with high-altitude and dense vegetation. The key internal factors contributing to the landslide including the unique alpine valley topography, the slope structure with advantageous free faces, and easily erodible geological layers. Precipitation induces internal water infiltration, which reduces the strength of the rock and soil mass. Additionally, freeze-thaw cycles further diminish slope strength, while earthquakes and road constructions disturb the internal structure, weakening it further. These combined internal and external factors drive the landslide deformation. This study offers technical insights for the landslide identifying, early-warning, and mitigation of road landslides in high-altitude regions with dense vegetation.

high-altitude  /  dense vegetation cover  /  highway landslide  /  formation mechanism
曾小艳, 田宏岭, 温成志, 顾乡, 陈松. 高原区高植被覆盖型公路滑坡特征及成因机制分析. 科学技术与工程, 2025 , 25 (13) : 5330 -5339 . DOI: 10.12404/j.issn.1671-1815.2404086
Xiao-yan ZENG, Hong-ling TIAN, Cheng-zhi WEN, Xiang GU, Song CHEN. Characteristics and Formation Mechanism of High-altitude and Highly Vegetation-covered Landslides[J]. Science Technology and Engineering, 2025 , 25 (13) : 5330 -5339 . DOI: 10.12404/j.issn.1671-1815.2404086
正文
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一般海拔超过1 000 m的区域即可称为高原,高原区高植被覆盖型滑坡是在海拔高度大于1 000 m,相对高度大于500 m的地区,其植被覆盖度大于 75%的滑坡,其主要分布在中国西南山区。 该类滑坡具有很强的隐蔽性与复杂性,灾害历史数据缺乏,调查、识别难度高。近年一些灾难性滑坡如茂县新磨村滑坡属于高原高植被覆盖型滑坡,由于其隐蔽性及复杂性前期未能识别滑坡的表面裂缝及变形信息,灾害发前无任何预警信息,滑坡造成10人死亡和73人失踪[1-2]。因此在进行滑坡调查的过程中,容易漏掉一些具有较大危害性的滑坡。尤其在公路或交通线路中该类滑坡若未能识别或危险程度评估不到位,极易导致公路断道甚至造成重大人员伤亡。
目前,国内外学者对高植被覆盖的区域性滑坡进行了研究,张为等[3]基于遥感数据及航片信息对高植被覆盖区滑坡的孕灾环境进行分析,在区域内解译出滑坡灾害及隐患40处; Xu等[4-5]、Nichol等[6]利用遥感卫星影像对区域性高植被覆盖区的滑坡进行了解译与分析。对于植被覆盖较密集的地区或复杂的地形条件,遥感数据的解译可能会受到限制,影响解译效果,进而影响滑坡特征及稳定性的判别。一部分学者对高原区滑坡进行现场调查[7],综合运用无人机航拍[8]、卫星遥感[9]机载LiDAR[10]等方法对其滑坡基本特征及成因进行研究[11-17],但对高原高植被覆盖区的单体滑坡特征及成因分析很少。因此,现以肖家坡滑坡为例,通过公路勘查资料的收集及现场地面调查,查明滑坡的地质环境及细节特征,结合卫星影像、无人机摄影等技术手段查明滑坡外部形态、规模尺寸、表面堆积特征等相关参数,再运用机载LiDAR获取滑坡点云数据,通过后处理分离植被及地表点云,构建能够刻画滑坡地表真实特征的数字高程模型(digital elevation model,DEM)及厘米级高分辨率滑坡地表三维模型。综合以上结果分析滑坡的基本特征及成因,为高原高植被覆盖型滑坡的识别与监测预警提供相应的技术支持。
1 研究区概况
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1.1 地理位置
肖家坡滑坡位于四川省阿坝藏族羌族自治州小金县抚边乡庄房村,地理坐标为北纬31°18'56″,东经102°27'05″,紧邻拟建省道451公路,大致垂直此公路走向,离肖家坡滑坡坡脚5~10 m处为庄家河。若该滑坡破坏导致坡体下滑将严重影响道路施工及后期公路运营。
1.2 气象水文
滑坡区系大渡河上游河谷地带,属于高原型季风气候区。昼夜温差较大,有时达20 ℃以上,年平均气温12.2 ℃。常年干燥,雨量稀少,全年平均降水量为623.4 mm。
1.3 地质构造
肖家坡滑坡大地构造单元处于松潘—甘孜褶皱系,区内主要为抚边河断裂带,沿抚边河河谷有一条隐伏的NW向断裂,肖家坡滑坡距抚边河断裂带约10 km。
1.4 地层岩性
该区主要出露地层为三叠系上统西康群侏倭组(T3zh)以及三叠系中统杂谷脑组(T2z)。覆盖层为第四系人工素填土,以碎石、砾砂为主,一般厚约1.5 m,其下为第四系崩坡积碎石土,碎石母岩以板岩、变质砂岩为主,厚度约为1.5 m,该滑坡下伏基岩为三叠系杂谷脑组变质砂岩夹板岩,其中基岩强风化带一段厚约2.3 m,中风化带厚5~6 m。
1.5 地形地貌
肖家坡滑坡地处青藏高原东南缘的高山峡谷地带,地势东北高西南低,河流切割强烈,地面起伏大。地势以高山峡谷为主。区内山脉呈南北和北东走向,如图 1所示。区内岩层倾角49°~75°,海拔2 800~3 500 m的山坡坡顶及坡面植被以林木为主,植被茂盛。
2 技术方法
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肖家坡滑坡位于正在建设的省道451公路西南侧,滑动方向垂直于该公路,如果发生滑坡将影响公路的施工和运营。通过分析滑坡的历史变形、滑坡特征及成因机制等为公路提供安全保障。研究中使用的主要数据资料和采用的技术方法流程如图 2所示。
研究中,首先对肖家坡滑坡进行了详细的现场调查,获取滑坡的细部特征。然后利用Google Earth平台获取卫星遥感影像以得到滑坡区历史变形,由于滑坡区地处高原,遥感影像受天气影响较大,滑坡区遥感影像被云雾遮挡,因此只获取到滑坡区2013年2月、2013年10月、2019年10月、2021年6月四期高分辨率的正射校正后历史遥感影像,如图3所示,对遥感影像进行空间位置匹配,将坐标系统一为CGCSS2000坐标系。通过对历史遥感影像进行对比分析,在植被较少的主滑坡区,能够观测到滑坡具有一定的变形及下滑趋势,由于滑坡区域植被覆盖度较高且遥感影像分辨率较低,无法准确判断其历史变形及具体的位移数据。
由于卫星影像的不足,利用低空无人机航拍获取多期滑坡高分辨率影像,如图4所示,2023年9月时正值夏季,滑坡表面树木茂盛,影像无法反映滑坡地表裂缝及变形情况,2024年3月春季时,坡体上树木还未长出新叶。通过机载LiDAR获取了高分辨率影像与原始点云数据,后对获取数据进行处理,数据处理流程如图5所示,先将原始激光数据与GPS数据、IMU数据及数码航片解算出轨迹数据,将轨迹数据结合数码航片进行空间三维测量,空间三维重建及模型拼合后生成厘米级高分辨率滑坡三维实景模型,将激光测距数据与轨迹数据集合生成LAS激光点云数据,再根据点云的回波次数将其分为植被点云、地面点云及地表真彩点云,最后生成数字表面模型(DSM)及数字高程模型,如图6所示。
3 滑坡特征
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根据DEM及滑坡地表点云数据可得,肖家坡滑坡整体为一古(老)滑坡如图6(d)所示,滑体厚度5.8~20.5 m,总体积约160万m3,属大型土质滑坡,其前缘为新发育的3个小型滑坡。根据滑坡三维实景模型及现场调查,前缘滑坡区长约347 m,宽约443.2 m,主滑坡位于两个次滑坡的中部,主滑坡长约186.1 m,宽约105.3 m,其东侧次滑坡长约122.2 m,宽约90.7 m,西侧次滑坡长约134.9 m,宽约71.8 m。多年来受多因素影响形成顺滑坡运动方向约438.4 m,顺河长方向约513.2 m,平均厚度大于5 m,体积约为160×104 m3的滑坡堆积体。
根据滑坡植被点云图如图 6(b)所示测量,肖家坡滑坡植被覆盖率达90%,乔木高度5~7 m。根据中部主滑坡的运动及堆积特征将主滑坡划分为滑源区(Ⅰ)、滑动区(Ⅱ)及堆积区(Ⅲ)三部分如图7、图8所示。
3.1 滑源区
滑源区位于主滑坡南部,滑坡后壁明显且坡度较大,约为79°,出露的后壁平均高度约4.2 m,西侧出露明显[图 8(b)、图 8(d)],滑体平均宽108.7 m,滑体体积约5.75万 m3,表面已出现少量长度1~2 cm的裂缝如图8(a)所示,受外界因素(强风、降雨、暴晒)影响产生扰动,从滑坡后壁滑落,部分崩滑体堆积于滑壁之上,呈松散状,滑坡后壁表面的土体处于欠稳定状态,在其底部形成小型的坡积堆积区,其面积约813.16 m2,厚度2~3 m,其中块状碎砾石较多,约占堆积总体积的60%。滑源区堆积体表层保留了大量原有坡体的植土层和植被,有大量马刀树,如图8(f)所示,部分植被已经滑移至滑动的缓冲平台上。
3.2 滑动区
滑动区(Ⅱ)位于主滑坡的中部,为崩滑体在底部堆积区堆积起到铺垫作用,部分滑体在滑动范围内堆积停留,该平面呈斜向长条形搌布,面积约4 254.57 m2,长约118.38 m,厚度3~6 m,体积约为19.2×103 m3,该区域平均坡度约为45°。钻孔显示此处有5 m左右的覆土层,覆土层以下为碎石层,碎石层下为基岩,如图9所示。滑面可能位于覆土层和碎石层之间,且深度小于6 m,因此该滑坡属于浅层滑坡,覆土层碎石居多,约占总体积的60%,土体遇水变得松软,压缩性强,干燥后土体松散易松动滑落,在滑动区表面土层有明显的阶梯状下错台坎,如图 10所示,此为滑坡在滑动过程中缓慢形成。
3.3 堆积区
堆积区为滑体向前运动过程中,在其惯性和后部滑体的挤推作用下继续向前运动而形成的堆积区域,位于滑动区下方,主滑坡区的北侧。平面形状呈横向长条形,面积约为4 147.39 m2,表面覆盖大量的碎石及土体,覆盖厚度约9 m,体积约为 4.52万 m3,堆积体前缘距东侧一处村民房屋仅170 m,紧贴省道451公路。威胁到公路的建设,2023年9月,建设单位在主滑坡前缘已经设置了一个宽166 m,高6 m的挡土墙, 2024年3月20日调查时,挡土墙后壁已经堆积了大量土石堆积体,如图 11所示,堆积体由于受到后部滑体的挤推作用向前方滑移,滑移的土体直接堆积于挡土墙后部,并随着堆积体体积逐渐增加,土体漫过挡土墙并堆积于挡土墙上部。经现场调查可知堆积物超过挡土墙6~7 m。堆积物在东侧堆积较多,堆积高度超出挡土墙高度约7 m,右侧堆积物较少,超出挡土墙高度5~6 m。堆积体松散,调查时发现有多处由降雨入渗导致的空洞,继续发展将会产生新的滑动。
4 成因机制分析
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结合滑坡上述的基本特征,分析肖家坡滑坡发生的原因主要为内在的制性因素及外在的诱发因素。其中内在因素包括肖家坡滑坡独特的地形地貌、坡体自身的斜坡结构及地层岩性;外在因素为降水、冻融循环、地震及人类工程活动。内因与外因的共同作用形成滑坡。根据滑坡的影响因素分析其演化规律为3个阶段:倾倒弯曲阶段、推移-加速变形阶段及蠕滑-锁固阶段。
4.1 影响因素
4.1.1 独特的高原沟谷地貌特征
肖家坡滑坡地处青藏高原东缘的高山峡谷区,在距抚边河断裂带约10 km的沟谷之中,整个滑坡高差近300 m,由去植被后数字高程模型可见,古(老)滑坡特征明显,其前缘形成新滑坡,如图12所示,前缘的临空条件较好,为进一步失稳破坏提供了有利条件。
4.1.2 坡体自身斜坡结构
根据图12可知,古(老)滑坡北侧已经产生滑移,形成明显的滑坡后壁,古滑坡中部还未见明显滑动,其原因可以根据如图13所示的滑坡坡度图中获知,从图13中能够得出滑坡平均坡度约45°,古滑坡上部及下部坡度45°~70°,中部20°~45°。因此,由于古滑坡下部及上部坡度较陡峭,中部较平缓,使得古滑坡下部及中部的滑动距离差异明显。
滑源区附近变质砂岩岩体风化强烈,如图14所示,受节理裂隙面及层面控制,岩层被分割为块裂状、碎裂状,较为松散破碎。滑坡区节理面发育,变质砂岩岩体发育有次生块状节理,研究区内发育2组有利于坡体失稳破坏的优势结构面,一组为与坡面相交的陡倾坡外结构面产状23°~30°∠20°~25°,该组结构面将滑动岩体与斜坡母岩切割分离。从滑坡后壁可以看出该组结构面长大、贯通性好,在斜坡浅表层已具有一定的变形张裂现象,为雨水的入渗提供了通道。此外,岩体中还存在一组与滑动方向几乎平行的结构面,产状为300°~303°∠40°~45°。该结构面为纵向拉裂面,将滑动岩体与斜坡母岩纵向切割分离。两组结构面的结合为滑坡的形成提供了内在条件。
4.1.3 地层岩性对滑坡的影响
肖家坡滑坡覆土层覆盖层为第四系人工素填土,以碎石、砾砂为主,其下为第四系崩坡积碎石土,碎石母岩以板岩、变质砂岩为主,土体松散破碎,易受雨水及冰雪融水侵蚀与渗透。基岩为三叠系杂谷脑组变质砂岩夹板岩,岩性软弱,抗剪强度较低,多存在于软弱结构面。降雨及冰雪融水使地下水位升高,不断渗入基岩的层间错动面或节理裂隙中,使岩体结构软化形成软弱滑动面,为滑坡的滑移提供了有利条件。
4.1.4 降水对滑坡的影响
降水是影响滑坡的重要因素,肖家坡滑坡的地下水补给主要来源于大气降水,根据1951—2000年降水资料统计,如图15所示,小金县平均月降水量较多的为5—9月,其降水量占全年累计降水量的77.2%,其中6月降水量达126.9 mm,占全年累计降水量的20.4%。降水产生的地表径流一部分蒸发,一部分缓慢渗入坡体内部,地下水持续软化下伏岩层,使岩层饱水后强度降低,滑坡体后缘裂缝在饱水后具有较大动水压力,使山体沿着下伏层岩体产生滑移变形。
4.1.5 冻融循环对滑坡的影响
肖家坡滑坡位于川西高原东部寒冷地带,其春冬两季温度较低,根据2020年1月—2023年12月4年的气象资料统计显示,小金县月平均最低气温≤0 ℃的月份为1—2月及11—12月,占全年的33.3%,其中1月份月平均气温最低为-4 ℃,后气温回升,如图16所示。因此,肖家坡滑坡处存在明显的季节性冻融作用,根据2024年3月现场调查时滑坡表面还覆盖有少量积雪,如图17所示。由于该滑坡为阴坡,古(老)滑坡底部长时间得不到光照,加之地面温度相对于空气温度的滞后性,使得该处坡体长时间处于冻结状态,土体强度降低。古(老)坡脚由于长时间的冻结,坡体上部的水流无法顺利通过坡脚使得坡脚排水受阻,导致地下水位升高,坡体静水压力增大,当气温回升坡脚土体解冻后,坡脚的支撑作用降低,并向下滑移,冻融作用可导致斜坡内地下水的富集和疏散,富集可造成边坡土体的软化,疏散导致静水压力和动水压力突变[18],从而造成滑坡的发生。因此,冻融循环对滑坡的形成具有积极影响。
4.1.6 地震及人类工程活动
据统计,肖家坡滑坡所处地区附近曾发生多次地震,2022年6月马尔康6.0级地震,震中距滑坡区直线距离81.5 km,滑坡区受到波及;2017年8月九寨沟7.0级地震,震中距滑坡区直线距离294.5 km,滑坡区受地震影响较大;2008年5月汶川8.0级地震,震中距滑坡区直线距离114.2 km,滑坡区受地震影响较大[19]。地震作用改变了滑坡体内岩土体的结构,使坡体更加松散易破碎,加速滑源区裂缝的发育,同时加快雨水及冰雪融水的渗透作用,从而降低坡体的稳定性。
滑坡正下方为省道451公路,开挖边坡导致临空面更加突出,公路在修建过程中产生的施工扰动直接作用于坡体,加速坡体内部及地表裂缝的形成,雨水与冰雪融水更容易侵入裂缝使土体内部渗水软化,加速坡体的下滑。
4.2 滑坡变形演化过程
通过对影响滑坡形成的影响因素进行分析,结合无人机及机载LiDAR数据综合分析,肖家坡滑坡滑源区东侧是滑坡主要变形区域,为滑坡主要的物质来源,根据上述对滑坡诱发因素中滑坡内因及外因对滑坡的影响,认为肖家坡滑坡为推移-蠕滑变形机制,其主要分为3个阶段。
(1)初始微小变形阶段。肖家坡滑坡边界临空条件较好,其主滑坡的滑源区分布有部分细小的张拉裂缝,该裂缝在降雨及冰雪融水入渗的条件下,土体饱和,滑源区表层土体出现较大的拉裂缝,在后部土体重力作用下坡体向下滑动,变形后的坡体表面岩土体松散破碎,呈散状分布。
(2)推移-加速变形阶段。由于第一阶段的铺垫作用,随着滑源区土体的滑动,滑坡后壁的土体在重力作用下向前推移,同时在地震和施工扰动作用及降水与冻融循环的共同作用下,坡体裂缝加速形成,冬季坡体内部受低温冻结,春季温度回升而融化,土体强度降低,冰雪融水与降水侵入坡体导致坡体静水压力增大,使得坡体加速向前滑移,根据现场测量及机载LiDAR三维实景模型两者相互验证测得滑坡体平均位移约2.5 m,局部最大位移达5.2 m。
(3)蠕滑阶段。受坡体自身结构与所处的高原沟谷地形影响,滑源区第二阶段形成的滑体在坡度变缓情况下滑移速率缓慢,进入蠕滑阶段,滑落的松散岩土体进入堆积区,由于滑坡体前缘已设置了挡土墙,使岩土体在挡土墙后部挤压堆积,堆积高度约10 m。 滑坡的变形使其地形地貌发生改变,顺滑动方向的变形形成坡体滑源区的滑坡陡坎及滑动区的阶梯状台坎,垂直于滑动方向的变形形成环向冲沟。
5 结论及建议
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(1)肖家坡滑坡地处青藏高原东缘的高山峡谷地带,河流切割强烈,地面起伏大,新构造运动强烈,滑坡区最高处海拔3 030 m。滑坡区出露的地层主要为三叠系上统西康群侏倭组(T3zh)以及三叠系中统杂谷脑组(T2z),通过现场调查得到滑坡区长约443.2 m,宽约105.3 m,滑体厚度5.8~20.5 m,体积约160万m3。主滑坡长约186.1 m,宽约105.3 m。根据滑坡的滑动及堆积特征将滑坡区划分为滑源区、滑动区及堆积区3个部分。
(2)肖家坡滑坡植被覆盖率高达90%,属于高植被覆盖型滑坡。仅凭常规的无人机航拍及卫星遥感影像难以查明其该类型滑坡基本特征、形态及地表裂缝、台坎等信息。在树木树叶稀疏时期通过机载LiDAR获取滑坡点云数据,对点云数据进行去植被处理后生成滑坡DEM数字高程模型后发现,该滑坡为古滑坡,新滑坡位于古滑坡底部。在滑动区表面土层有明显的阶梯状下错台坎,通过LiDAR获取植被下滑坡地表真实地形,为滑坡的成因分析、稳定性评价等提供准确的基础资料。
(3)肖家坡滑坡是在内部及外部因素的共同作用下形成的。其中,独特的高原沟谷型地貌、坡体自身的斜坡结构及地层岩性是肖家坡滑坡的内部影响因素;降水、冻融循环、地震及人类工程活动是肖家坡滑坡形成的重要外部诱发因素。
(4)肖家坡滑坡为推移-蠕滑变形机制,其变形演化分3个阶段,分别是初始微小变形阶段、推移-加速变形阶段及蠕滑阶段。
(5)在中国西南山区广泛发育肖家坡滑坡这类高原高植被覆盖型滑坡,具有现场调查难、成本高、高隐蔽性等特点,要准确分析其基本特征与成因,可以通过冬季激光雷达获取坡体的精确特征数据,结合地面调查与物探钻探深入研究其的诱发因素及机理。
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  • 国家重点研发计划(2018YFE0100100-4)
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2025年第25卷第13期
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doi: 10.12404/j.issn.1671-1815.2404086
  • 接收时间：2024-06-02
  • 首发时间：2025-07-09
  • 出版时间：2025-05-08
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  • 收稿日期：2024-06-02
  • 修回日期：2025-01-16
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国家重点研发计划(2018YFE0100100-4)
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    1 山地自然灾害与工程安全全国重点实验室, 成都 610299
    2 中国科学院、 水利部成都山地灾害与环境研究所, 成都 610299
    3 中国科学院大学, 北京 101408
    4 四川阿坝交通建设投资有限责任公司, 马尔康 624000

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* 田宏岭(1974—),男,汉族,河南太康人,博士,高级工程师。研究方向:滑坡调查评估、监测预警。E-mail:。
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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