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地理探测器在判别滑坡稳定性影响因素中的应用

支泽民 陈琼 张强 周强 刘峰贵 赵富昌 陈永萍

支泽民, 陈琼, 张强, 周强, 刘峰贵, 赵富昌, 陈永萍. 2021: 地理探测器在判别滑坡稳定性影响因素中的应用. 中国地质灾害与防治学报, 32(2): 19-26. doi: 10.16031/j.cnki.issn.1003-8035.2021.02.03
引用本文: 支泽民, 陈琼, 张强, 周强, 刘峰贵, 赵富昌, 陈永萍. 2021: 地理探测器在判别滑坡稳定性影响因素中的应用. 中国地质灾害与防治学报, 32(2): 19-26. doi: 10.16031/j.cnki.issn.1003-8035.2021.02.03
Zemin ZHI, Qiong CHEN, Qiang ZHANG, Qiang ZHOU, Fenggui LIU, Fuchang ZHAO, Yongping CHEN. 2021: Application of geographic detector in identifying influencing factors of landslide stability: A case study of the Jiangda County, Tibet. The Chinese Journal of Geological Hazard and Control, 32(2): 19-26. doi: 10.16031/j.cnki.issn.1003-8035.2021.02.03
Citation: Zemin ZHI, Qiong CHEN, Qiang ZHANG, Qiang ZHOU, Fenggui LIU, Fuchang ZHAO, Yongping CHEN. 2021: Application of geographic detector in identifying influencing factors of landslide stability: A case study of the Jiangda County, Tibet. The Chinese Journal of Geological Hazard and Control, 32(2): 19-26. doi: 10.16031/j.cnki.issn.1003-8035.2021.02.03

地理探测器在判别滑坡稳定性影响因素中的应用

doi: 10.16031/j.cnki.issn.1003-8035.2021.02.03
基金项目: 第二次青藏高原综合科学考察研究(2019QZKK0906);国家重点研发计划(2019YFA0606902)
详细信息
    作者简介:

    支泽民(1994-),男,山西朔州人,硕士研究生,主要从事土地利用与灾害风险研究。E-mail:zhizemin@126.com

    通讯作者:

    陈 琼(1975-),女,浙江诸暨人,博士,副教授,硕士生导师,主要从事土地科学研究。E-mail:qhchenqiong@163.com

  • 中图分类号: P642

Application of geographic detector in identifying influencing factors of landslide stability: A case study of the Jiangda County, Tibet

  • 摘要: 高山峡谷区是滑坡灾害频发地区,随着气候变化和人类活动加剧,滑坡呈多发、频发态势。本文选择坐落于横断山高山峡谷区的西藏江达县作为研究区,利用野外调查获取的85个滑坡数据,选取坡度、河流密度、地貌类型、降水量、距断层距离、道路密度、地震动峰值加速度、岩性等8个稳定性影响因素,运用地理探测器对滑坡稳定性的影响因素进行了探测。结果表明:(1)按滑坡体体积划分等级,江达县滑坡主要以中、小型滑坡为主;按其稳定性划分,50%以上的滑坡处于稳定状态;按危险等级划分,以Ⅲ级、Ⅳ级为主;江达县滑坡主要沿河流与道路分布,全县地面调查发现85处滑坡全部分布于河流附近,其中71.76%的滑坡分布于道路两侧。(2)江达县滑坡稳定性的主要影响因子为地貌类型、河流密度、道路密度和距断层距离,其贡献率分别为0.501,0.477,0.465,0.332;当影响因子两两相互作用时,因子解释力总是大于单个因子对滑坡稳定性的解释力,即当两种影响因子相互作用时,对于滑坡的失稳具有促进作用。
  • 图  1  研究区概况图

    Figure  1.  Overview map of study area

    图  2  最优离散分类流程图

    Figure  2.  Flowchart of optimal discrete classification

    图  3  影响因子最优离散分类

    Figure  3.  Optimal discrete classification of each factor

    表  1  地层岩性硬度划分表

    Table  1.   Stratum lithology hardness division table

    类别代表岩石稳定性赋值
    极硬岩花岗岩、二长花岗岩、闪长岩、
    辉长岩、石英闪长岩、玄武玢岩、
    硅质岩、超镁铁质岩类
    4
    次硬岩碳酸盐岩、碎屑岩、大理岩、白云岩、
    石灰岩、中酸性基性火山岩、
    赤铁矿、夹灰岩、地层并层等
    3
    次软岩千枚岩、板岩、灰岩、石膏等2
    极软岩页岩、黏土岩、泥岩、
    砂岩、砾岩及各种土体等
    1
    下载: 导出CSV

    表  2  按滑坡体体积划分的滑坡等级

    Table  2.   Landslide grade divided by volume

    规模标准/(104 m3)数量/个占比/%
    小型V<104552.94
    中型10≤V<1002630.59
    大型100≤V<10001112.94
    特大型1000≤V33.53
    总计85100.00
    下载: 导出CSV

    表  3  按稳定性划分的滑坡等级

    Table  3.   Landslide grade divided by stability

    稳定性评价数量/个占比/%
    稳定1416.47
    较稳定2934.12
    稳定性较差44.71
    不稳定3338.82
    易发55.88
    总计85100.00
    下载: 导出CSV

    表  4  按危险性划分的滑坡等级

    Table  4.   Landslide grade divided by danger

    险情等级数量/个占比/%
    Ⅰ级00.00
    Ⅱ级22.35
    Ⅲ级1720.00
    Ⅳ级6677.65
    总计85100.00
    下载: 导出CSV

    表  5  因子探测结果

    Table  5.   Factor detection results

    坡度 X1距断层距离 X2岩性 X3河流密度 X4地貌类型 X5道路密度 X6降水量 X7地震动峰值加速度 X8
    q0.1680.3320.1010.4770.5010.4650.1220.129
    下载: 导出CSV

    表  6  交互作用探测结果

    Table  6.   Interaction detection results

    交互因素交互值交互值比较交互结果
    坡度∩距断层距离0.728>q(坡度)+q(距断层距离)非线性增强
    坡度∩岩性0.418>q(坡度),q(岩性)非线性增强
    坡度∩河流密度0.677>q(坡度)+q(河流密度)非线性增强
    坡度∩地貌0.827>q(坡度),q(地貌)非线性增强
    坡度∩道路密度0.748>q(坡度),q(道路密度)非线性增强
    坡度∩降水量0.424>q(坡度)+q(降水量)非线性增强
    坡度∩地震动峰值加速度0.404>q(坡度)+q(地震动峰值加速度)非线性增强
    距断层距离∩岩性0.433>q(距断层距离)+q(岩性)非线性增强
    距断层距离∩河流密度0.739>Max(q(距断层距离),q(河流密度))双因子增强
    距断层距离∩地貌0.938>q(距断层距离),q(地貌)非线性增强
    距断层距离∩道路密度0.783>Max(q(距断层距离),q(道路密度))双因子增强
    距断层距离∩降水量0.413>Max(q(距断层距离),q(降水量))双因子增强
    距断层距离∩地震动峰值加速度0.445>Max(q(距断层距离),q(地震动峰值加速度))双因子增强
    岩性∩河流密度0.557>q(岩性)+q(河流密度)非线性增强
    岩性∩地貌0.781>q(岩性)+q(地貌)非线性增强
    岩性∩道路密度0.547>Max(q(岩性),q(道路密度))双因子增强
    岩性∩降水量0.221>Max(q(岩性),q(降水量))双因子增强
    岩性∩地震动峰值加速度0.339>q(岩性)+q(地震动峰值加速度)非线性增强
    河流密度∩地貌0.831>Max(q(河流密度),q(地貌))双因子增强
    河流密度∩道路密度0.700>Max(q(河流密度),q(道路密度))双因子增强
    河流密度∩降水量0.540>Max(q(河流密度),q(降水量))双因子增强
    河流密度∩地震动峰值加速度0.559>q(河流密度)+q(地震动峰值加速度)非线性增强
    地貌∩道路密度0.815>Max(q(地貌),q(道路密度))双因子增强
    地貌∩降水量0.735>q(地貌)+q(降水量)非线性增强
    地貌∩地震动峰值加速度0.544>Max(q(地貌),q(地震动峰值加速度))双因子增强
    道路密度∩降水量0.617>q(道路密度)+q(降水量)非线性增强
    道路密度∩地震动峰值加速度0.521>Max(q(道路密度),q(地震动峰值加速度))双因子增强
    降水量∩地震动峰值加速度0.267>Max(q(降水量),q(地震动峰值加速度))双因子增强
    下载: 导出CSV

    表  7  生态探测结果

    Table  7.   Ecological detection results

    坡度X1距断层距离X2岩性X3河流密度X4地貌X5道路密度X6降水量X7地震动峰加速度X8
    坡度
    距断层距离N
    岩性NY
    河流密度YNY
    地貌YNYN
    道路密度YNYNN
    降水量NYNYYY
    地震动峰加速度NNNYYYN
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-06-15
  • 修回日期:  2020-12-17
  • 刊出日期:  2021-04-27

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