ISSN 1003-8035 CN 11-2852/P
  • 中国科技核心期刊
  • CSCD收录期刊
  • Caj-cd规范获奖期刊
  • Scopus 收录期刊
  • DOAJ 收录期刊
  • GeoRef收录期刊
欢迎扫码关注“i环境微平台”

基于AHP-突变理论组合模型的地质灾害危险性评价以河北平山县为例

于开宁, 吴涛, 魏爱华, 武玉璞, 代锋刚, 刘煜

于开宁,吴涛,魏爱华,等. 基于AHP-突变理论组合模型的地质灾害危险性评价−以河北平山县为例[J]. 中国地质灾害与防治学报,2023,34(2): 146-155. DOI: 10.16031/j.cnki.issn.1003-8035.202201012
引用本文: 于开宁,吴涛,魏爱华,等. 基于AHP-突变理论组合模型的地质灾害危险性评价−以河北平山县为例[J]. 中国地质灾害与防治学报,2023,34(2): 146-155. DOI: 10.16031/j.cnki.issn.1003-8035.202201012
YU Kaining,WU Tao,WEI Aihua,et al. Geological hazard assessment based on the models of AHP, catastrophe theory and their combination: A case study in Pingshan County of Hebei Province[J]. The Chinese Journal of Geological Hazard and Control,2023,34(2): 146-155. DOI: 10.16031/j.cnki.issn.1003-8035.202201012
Citation: YU Kaining,WU Tao,WEI Aihua,et al. Geological hazard assessment based on the models of AHP, catastrophe theory and their combination: A case study in Pingshan County of Hebei Province[J]. The Chinese Journal of Geological Hazard and Control,2023,34(2): 146-155. DOI: 10.16031/j.cnki.issn.1003-8035.202201012

基于AHP-突变理论组合模型的地质灾害危险性评价——以河北平山县为例

基金项目: 河北省重点地质灾害勘查项目(2019150);河北省自然科学基金(D2022403032)
详细信息
    作者简介:

    于开宁(1965-),男,山东乳山人,博士,教授,主要从事水资源与环境地质研究工作。E-mail:1211931193@qq.com

    通讯作者:

    刘 煜(1982-),男,河北石家庄人,学士,高级工程师,主要从事地质灾害防治、地质环境监测与演化研究工作。E-mail:16222420@qq.com

  • 中图分类号: P694

Geological hazard assessment based on the models of AHP, catastrophe theory and their combination: A case study in Pingshan County of Hebei Province

  • 摘要:

    河北平山县受地形地貌、地质构造和生态环境等因素的影响,崩滑流等地质灾害频发。选取地形起伏度、坡度、坡向、河网密度、断裂带密度、地层岩性、NDVI、土地利用类型及地质灾害点密度9个评价因子,用AHP和突变理论分别求各评价因子权重,并按最小信息熵权法结合,建立AHP-突变理论组合模型并应用,对比基于三种方法的平山县地质灾害危险性评价结果。结果表明:组合模型的评价结果精度更高,符合该区地质灾害发育特征;组合模型法将主客观结合,综合考虑因子的影响,评价结果可靠。该研究为平山县及类似地区地质灾害危险性评价提供一种新的尝试和方法。

    Abstract:

    Pingshan County, Hebei was affected by topography, geological structure, ecological environment and other factors, geological disasters such as landslides occurred frequently. Nine evaluation factors including topographic relief, slope, aspect, river network density, fault zone density, stratigraphic lithology, NDVI, land use type and geological disaster point density were selected. The weights of each evaluation factor were calculated by AHP and catastrophe theory, and the combination model of AHP and catastrophe theory was established and applied according to the minimum information entropy weight method. The results of geological disaster risk assessment in Pingshan County based on three methods were compared. The results show that the evaluation results of the combined model have higher accuracy and are in line with the development characteristics of geological disasters in this area. Combined model method combines subjective and objective, considering the influence of factors, the evaluation results are reliable. This study provides a new attempt and method for geological disaster risk assessment in Pingshan County and similar areas.

  • 受全球变暖和夏季气温升高影响,多年冻土斜坡活动层融化导致大量水分汇集在冻融交界面,抗剪强度快速下降,活动层沿多年冻土层滑动[1],诱发的浅层冻土滑坡广泛分布于加拿大北极地区[2-4]、美国阿拉斯加北部[5]和中国青藏高原[6]等不连续多年冻土地区,破坏生态环境、制约社会经济发展。因此,研究气温变化对浅层冻土滑坡的影响,对相应灾害的防治工作具有指导意义。

    通过现场调查和野外勘察等手段,现有研究证实了浅层冻土滑坡与气温变化具有密切关联。通过现场调查,Huscroft等[2]认为全球变暖导致森林大火、快速融雪和强降雨等极端事件的概率增加,造成加拿大育空地区浅层冻土滑坡频发。Lewkowicz等[3]的现场调查数据表明1969年以来埃尔斯米尔岛气温呈升高趋势,最大地表加热指数和解冻天数显著增长,浅层冻土滑坡发生频率从每年3~6次上升到每年14次。结合气象观测资料,Lamoureux等[4]得出2007年7月梅尔维尔岛的极端高温导致活动层快速融化,一周内发生浅层冻土滑坡25次。通过野外勘察,Patton等[5]提出气温升高导致冻土融化,持续高温和干旱破坏地表植被、提高坡面蒸发率,导致阿拉斯加浅层冻土滑坡频发。以上研究得出:长时间尺度下全球变暖增加了极端天气事件发生率;短时间尺度下夏季气温升高导致冻土融化、浅层冻土滑坡频发。但是浅层冻土滑坡失稳是一个复杂的水热力耦合过程,气温变化对多年冻土斜坡水热力演化的影响机制不明,本文尝试在这方面模拟讨论。

    本文通过地质灾害遥感解译总结分析了青海省浅层冻土滑坡发育分布规律和孕灾条件,针对青海省具有发生浅层冻土滑坡隐患的斜坡,基于有限元软件COMSOL Multiphysics建立多年冻土斜坡水热力耦合模型,考虑全球变暖因素模拟了2020—2024年气温变化条件下多年冻土斜坡水热力复杂演化的过程,从而揭示气温变化这一单一因素对浅层冻土滑坡失稳的影响。研究结果对认识浅层冻土滑坡失稳机制和该类地质灾害的防灾减灾提供了理论依据和科学指导。

    青海省内多年冻土区面积3.57×104 km2,占青海省总面积的50%,受气候变化和人类活动影响,当地多年冻土稳定性下降,浅层冻土滑坡灾害频发。基于多源遥感数据调查青海省多年冻土区浅层冻土滑坡灾害分布特征,共解译该类型灾害290处,祁连县、治多县和曲麻莱县为青海省浅层冻土滑坡发育的典型地区(图1),灾害发生时间集中在每年7—9月。通过遥感解译得到祁连县重点工作区浅层冻土滑坡分布如图2所示,该区域发育有54处浅层冻土滑坡,其中,遥感影像呈椭圆状的为滑动型浅层冻土滑坡,活动层呈整体向下滑动的趋势,运动距离较近;遥感影像呈长条状的为流动型浅层冻土滑坡,由于滑体含水率较高,表层土以泥流形式向下运移,运动距离较远。

    图  1  青海省不同类型冻土区浅层冻土滑坡分布
    Figure  1.  Distribution of active layer detachments in different types of permafrost regions in Qinghai Province

    基于实地调查和遥感目视解译结果统计了青海省浅层冻土滑坡灾害分布与多年冻土发育的关系如图1所示,根据年平均地温(MAGT)范围可将多年冻土稳定性分为5类[7],结果表明: 97.24%的浅层冻土滑坡分布在不稳定多年冻土区(−0.5 °C≤MAGT<0.5 °C)、过渡型多年冻土区(−1.5 °C≤MAGT<−0.5 °C)和亚稳定多年冻土区(−3.0 °C≤MAGT<−1.5 °C),仅2.76%的浅层冻土滑坡分布在稳定型多年冻土区(−5.0 °C≤MAGT<−3.0 °C)和极稳定多年冻土区(MAGT<−5.0°C),由此推断,浅层冻土滑坡分布与多年冻土发育密切相关。

    图  2  青海省祁连县重点工作区浅层冻土滑坡分布
    Figure  2.  Distribution of active layer detachments in key working area of Qilian County, Qinghai Province

    大量研究表明气候变化是诱发浅层冻土滑坡的主要外部因素[2-5]。近年来青海省最高线性增温趋势达0.09 °C/a,远超全球平均水平[6-8],气温变化呈正弦函数形式,活动层不断经历冻融循环,土体自3—4月开始融化,8—9月融深达到最大,10—11月开始冻结[9]。青海省降水量季节分配不均,其中5—10月的降水量占全年总降水量的90%以上,7—8月降水量最大[10]。可以得出,研究区活动层融化、降水量增大与浅层冻土滑坡集中发育时间基本吻合,气候变化导致地温梯度改变,破坏冻土发育的连续性和均匀程度[11],对多年冻土斜坡稳定性产生不利影响。

    为进一步揭示研究区地质环境条件对浅层冻土滑坡发育的影响,对灾害发育斜坡进行了现场调查。统计结果显示,原始斜坡的坡向集中在270°~360°和0°~45°,坡度集中在5°~20 °。已有学者指出[12],缓坡地带多年冻土埋藏位置更浅,地下冰含量更高,冻土受外部影响融化对斜坡稳定性产生严重威胁;坡表植被以高原草甸为主,覆盖率大多达到65%以上,灾害发育位置主要为斜坡坡体冲沟部位,分析认为,植被覆盖度高和汇水条件良好的斜坡表层水分充足,阴坡积雪覆盖率高,隔热作用显著,有利于多年冻土发育[13];斜坡表层主要发育第四系坡积物(Qdl),活动层土体多为细粒土和泥炭,相关研究表明[14-15],细粒冻土富含冰晶,冻融循环作用下强度不断损失,融化时有液化的可能,容易诱发浅层冻土滑坡。综上所述,地质环境条件是影响浅层冻土滑坡发育的内在因素,通过控制冻土发育对青海省多年冻土斜坡稳定性产生影响,大量力学性质不良的冻土融化是诱发浅层冻土滑坡的必要条件,浅层冻土滑坡往往发育在植被覆盖率高、活动层土颗粒较细和汇水条件良好的低缓阴坡上。

    为简化土体冻融循环中的水热力演化过程,本文做如下假设:地温变化受热传导和冰水相变控制;水分迁移由基质吸力驱动,孔隙冰对水分迁移具有阻滞作用;水热过程单向影响土体应力应变;土体的破坏行为符合摩尔-库伦屈服准则。

    冻土内水热作用互相影响,水分迁移改变土的热物理参数,土体温度变化影响水力学参数,水热耦合方程选取常用的Harlan模型[16]。变形场以平衡方程和连续性方程为基础,建立冻胀模型描述冻胀融沉对土体应力应变的影响[17]

    青海省祁连县重点调查区某天然斜坡位于汇水面阴面,位置见图2,整体坡度约12°,表层土体为粉质黏土,植被覆盖率约70%,存在发生浅层冻土滑坡的隐患,因此以该斜坡为研究对象模拟2020—2024年气温变化条件下多年冻土斜坡水热力演化过程。

    钻孔资料(图3)显示地表以下0~1.6 m为活动层,土质为粉质黏土;1.6~12.7 m为多年冻土层,土质为黏土,有大量肉眼可见冰晶;12.7 m以下为砂砾岩。根据现场调查和钻孔资料所得典型斜坡地质剖面如图4所示。

    图  3  钻孔地层信息(水)
    Figure  3.  Stratum information based on borehole
    图  4  典型斜坡地质剖面
    Figure  4.  Typical geological section of the slope

    建立二维有限元模型,采用自由三角形网格进行划分,将活动层网格细化,见图5(a),布置2条测线和8个测点获取水热力时空分布计算结果,见图5(b):斜坡中间剖面布置测线1-1′;斜坡表面布置测线2-2′;坡脚活动层不同深度布置测点A-E;与坡顶水平距离为50 m的地表布置测点F;坡顶地表布置测点G;测点F以下1.68 m处布置测点H。

    图  5  有限元计算模型
    Figure  5.  Finite element computational model

    根据相关研究给出的青海地区粉质黏土、黏土和砂砾岩的物理力学参数[18-19]以及钻孔取样进行土工试验的结果,数值模拟所需参数设置如表1所示,水和冰的相变潜热取334.5 kJ/kg,土体初始冻结温度取−0.5 °C,完全融化温度取0 °C,冻土的比热容和导热系数与土中未冻水含量的关系根据相关研究[20-21]进行设置,土骨架的比热容和导热系数分别取1.4×106 J/(m3·°C)和1.3 W/(m·°C)。

    表  1  地层物理力学参数
    Table  1.  Physical and mechanical parameters of formation
    参数活动层多年冻土层基岩层
    密度/(kg·m−3180020002500
    弹性模量/MPa40305000
    泊松比0.250.30.15
    渗透系数/(m·s−11.2×10−68×10−100
    黏聚力/kPa1235
    内摩擦角/(°)2220
    下载: 导出CSV 
    | 显示表格

    祁连当地年气温线性增长速率为0.037 °C/a[22],根据附面层理论[16]得出模型,见图5(a),上表面温度边界条件表达式:

    $$ T = 2 + \frac{{0.037t}}{{8\;760}} + 13\sin \left(\frac{{2\text{π} t}}{{8\;760}} + \frac{{17\text{π} }}{{12}}\right) $$ (1)

    式中:t——时间/h。

    左右两侧为绝热边界;下表面温度为3 °C,热通量为0.03 W/m2。水分场上表面为自由渗透边界;左右两侧和下表面均为零流量边界。变形场上表面为自由边界,左右两侧水平位移为0,下表面为固定边界。

    图6 (a)为2020年10月地温的钻孔实测值和数值模拟计算值对比图,可以看出数值模拟所得地温与现场钻孔测温结果基本一致。2020年活动层从3月25日开始融化,至8月26日融深达到最大,整个融化过程持续约5个月,符合刘广岳等[9]的水热监测结果。图6 (b)为融深最大时刻(8月26日)斜坡融化程度云图,可知最大融深位于地表以下1.61 m,与图2所示多年冻土上限位置吻合。综上所述,该模型几乎准确地反演了气温变化条件下斜坡地温分布、融深达到最大的时刻和多年冻土上限位置,体现了模型的有效性。

    图  6  模型有效性验证
    Figure  6.  Effectiveness verification of model

    图7 (a)和图7 (b)分别为2020—2024年测点E和G的总体积含水率(含水率和含冰率的总和)变化曲线,对比可知测点E总体积含水率以0.16%/a的速度升高;测点G总体积含水率以0.16%/a的速度下降;根据总体积含水率变化趋势可以将水分迁移分为4个阶段:1月1日—3月15日土体处于冻结状态,孔隙冰的阻隔作用导致水分迁移现象不明显;3月15日—7月20日孔隙冰逐渐融化,土体渗透性提高,水分迁移速率增大;7月20日—10月20日,活动层土体融化程度较高,总体积含水率变化趋势最明显,这一阶段的水分迁移量占全年总迁移量的50%;随着气温降至负温,10月20日—12月31日土体再次冻结,水分迁移速率减小。

    图  7  水分迁移规律
    Figure  7.  Water migration rules

    图7 (c)为2020—2024年8月2-2′测线上总体积含水率分布,可以得出坡顶总体积含水率逐年减小,坡脚总体积含水率逐年增大,经历4个冻融循环后坡脚土体总体积含水率比坡顶大7.4%,说明水分自坡顶向坡脚迁移;越靠近坡顶和坡脚,总体积含水率变化趋势越明显,由于水分自坡顶的补给和向坡脚的运移达到平衡,距坡顶55 m处土体总体积含水率不变。

    图8 (a)和图8 (b)分别为2月1日含冰率分布云图和8月26日融深最大时刻含水率分布云图。由图8 (a)可知2月活动层土体内的水分主要以孔隙冰的形式存在,体积含冰率约16%,多年冻土上限以下体积含冰率呈先减小后增大再减小的趋势,其中活动层以下0~0.5 m范围内土体体积含水率达到28%左右。图8 (b)为8月26日含水率分布云图,可以得出此时活动层土体融化,体积含冰率约26%,且在活动层基底以下高含冰层有一定融化,出现厚度约15 cm、体积含水率达到40%的富水层。

    图  8  斜坡含水率和含冰率分布规律
    Figure  8.  Water content and ice content distribution law of slope

    图9为2020—2024年8月26日1-1'测线地温随深度的分布,融深最大时0 °C地温所在深度可视作多年冻土上限位置,由此得出2020年多年冻土上限位于地表以下161 cm,2024年多年冻土上限位于地表以下171.4 cm,下移10.4 cm,平均退化速率约2.6 cm/a;多年冻土上限下移量逐年增大,下移量的增幅逐年减小,说明气温升高对多年冻土退化的影响程度随深度的增加逐渐减弱。

    图  9  2020—2024年8月26日1-1'测线地温随深度分布
    Figure  9.  Depth distribution of ground temperature of 1-1'section on August 26 from 2020—2024

    图10 (a)和图10 (b)分别为2020—2024年8月26日测点H处地温和体积含水率,可以得出:2020—2024年测点H地温呈升高趋势,升高速率逐年降低,平均升高速率为0.017 °C/a;2020—2022年该处土体仍处于冻结状态,由于土体温度升高导致体积含水率增大3%;2023年多年冻土上限将退化至测点H以下,土体完全融化导致含水率突增,较2022年增大11%;2024年含水率相比2023年未发生明显变化,说明气温升高对含水率的影响随着土体完全融化而消失。

    图  10  2020—2024年测点H地温和体积含水率
    Figure  10.  Ground temperature and volumetric water content of monitoring point H on 2020—2024

    图11 (a)和图11 (b)分别为2020—2024年坡脚不同深度5个测点的水平位移和竖直位移变化,可以得出:位移随深度的增加逐渐减小,冻胀融沉循环仅发生在活动层;以测点E为例,土体自10月20日起发生冻胀,1月15日冻胀量达到最大,水平冻胀位移为2.5 cm,竖直冻胀位移为8.0 cm;土体随着气温的回升开始融沉,6月26日融沉量最大,产生1.0 cm的水平融沉位移和6.0 cm的竖直融沉位移。图11 (c)为测点E冻胀融沉位移示意图,E-E1为冻胀变形路径,E1-E2为融沉回退路径,测点E处的土颗粒经历一次冻胀融沉后运动至E2处,产生1.5 cm的水平净位移和2.0 cm的垂直净位移,总位移2.5 cm,与Harris等[22]通过位移监测得出的1.6 cm/a的坡表变形量相近。

    图  11  冻胀融沉位移变化规律
    Figure  11.  Displacement variation of frost heaving and thaw settlement

    图12 (a)为2020—2024年测点E、F、G的塑性应变变化曲线,可以得出塑性应变在每年的冻胀融沉期间发展,4—10月坡表土体完全融化期间塑性应变不发生变化;塑性应变随时间不断增大,且坡脚E点塑性应变增大的速率最大,坡顶G点最小。图12(b)为2024年12月测线2-2’塑性应变曲线,可见塑性应变至坡顶至坡脚逐渐增大,对比图7 (c)可以得出塑性应变的分布与体积含水率的分布有关,5年间坡脚E点产生的塑性应变比坡顶G点大20.98%。

    图  12  塑性应变变化规律
    Figure  12.  Variation of plastic strain

    计算结果显示,随着土体融化程度增大,水分自坡顶至坡脚迁移的现象愈发显著,根据总体积含水率的变化趋势将水分迁移过程分为四个阶段,其中5—10月水分迁移现象尤为显著,此时青海省处于雨季,降雨量占全年的80%以上[11],雨水大量入渗导致融土迅速饱和,土体应力状态改变[23]、孔隙水压力增加,对斜坡稳定性产生威胁。

    已有研究表明土体孔隙冰含量上升导致基质吸力和胶结力增大[24],2月活动层土体含冰量达到18%,此时土体黏聚力较大,冻结期斜坡稳定良好;通过冰分离现象、大气水和融水下渗、冻结初期双向冻结[25],多年冻土上限以下出现0.5 m厚高含冰量层,且含冰量有继续增大的可能[26],8月26日融深达到最大,高含冰量层有一定的融化,产生约15 cm厚的富水层,细粒土排水能力较差,孔隙水压力难以消散[17],发生浅层冻土滑坡的概率增大。

    在当地气温以0.37 °C/a的速度升高的情况下,斜坡多年冻土处于升温退化状态,2020—2024年多年冻土上限将下移10.4 cm,活动层厚度不断增大,夏季上覆融化的土体提供更大的下滑力。随着最大融深的增大,活动层以下的高含冰层有进一步融化的可能,冻融交界面含水量大幅度升高,孔隙水压难以消散、抗剪强度大幅下降,水分聚集产生的润滑作用导致抗滑力下降[6],活动层沿多年冻土层下滑的风险大大上升。

    10月—次年4月活动层土体发生冻胀融沉,坡表土体产生2.5 cm/a的位移,由此产生的塑性应变不断增大,表明土颗粒间胶结作用随冻融循环次数的增加逐渐减弱,抗剪强度有损失至残余值的可能[23],塑性应变从坡顶至坡脚逐渐增大,5a间坡脚产生的塑性应变比坡顶大20.98%,土体力学性质劣化显著,且坡脚处容易产生水分聚集,形成薄弱带,进而诱发牵引式浅层冻土滑坡。

    基于地质灾害遥感解译总结了青海省浅层冻土滑坡分布特征和孕灾条件,采用数值模拟方法考虑当地气候变暖模拟了2020—2024年气温变化条件下多年冻土斜坡水热力演化,探讨了气温变化对浅层冻土滑坡失稳的影响,得出以下结论:

    (1) 气温变化影响冻结程度,改变土体渗透性,从而控制水分迁移。根据总含水率变化趋势可将水分迁移分为四个阶段,当活动层融化后水分自坡顶至坡脚的迁移现象最显著。

    (2) 气温变化影响活动层未冻水的含量,导致土体力学性质存在季节性差异,夏季活动层下的高含冰量层融化产生15 cm厚富水层,冻融交界面孔隙水压大幅上升,且气候变暖导致多年冻土上限以2.6 cm/a的速度下移,富水层厚度有继续增大的可能,诱发浅层冻土滑坡的风险增加。

    (3) 气温周期性变化导致土体水分固液相态不断转换,冰水体积变化导致活动层经历冻胀融沉循环,斜坡表面每年产生数厘米膨胀变形和顺坡位移,表明土体抗剪强度逐渐损失,坡脚土体力学性质劣化程度最明显。

  • 图  1   平山县地理位置

    Figure  1.   Geographical location of Pingshan County

    图  2   石家庄市崩滑流地质灾害隐患点分布

    Figure  2.   Distribution of potential and geological hazard points of collapse, landslide and debris flow in Shijiazhuang

    图  3   平山县灾害点分布

    Figure  3.   Distribution of geological hazard points in Pingshan County

    图  4   地质灾害危险性评价指标体系

    Figure  4.   Geological hazard risk evaluation index system

    图  5   各评价因子分级

    Figure  5.   Classification of each evaluation factor

    图  6   基于AHP平山县地质灾害危险性分区

    Figure  6.   Geological hazard zoning in Pingshan County based on AHP

    图  7   基于突变理论平山县地质灾害危险性分区

    Figure  7.   Geological hazard zoning in Pingshan County based on catastrophe theory

    图  8   基于AHP-突变组合模型平山县地质灾害危险性分区

    Figure  8.   Geological hazard zoning in Pingshan County based on AHP - catastrophe combination model

    表  1   各评价方法求得权重对比

    Table  1   Weight comparison of each evaluation method

    目标层准则层评价因子层AHP权重w1突变理论权重w2AHP-突变组合模型权重w3
    A平山县地质
    灾害危害性评价
    B1 地形地貌C1 地形起伏度0.17610.07950.1359
    C2 坡度0.37310.07170.1880
    C3 坡向0.08150.07950.0925
    C4 河网密度0.03800.08180.0641
    B2 地质构造C5 断裂带密度0.04050.10650.0755
    C6 地层岩性0.20260.24860.2579
    B3 生态环境C7 NDVI0.02490.11820.0624
    C8 土地利用类型0.05670.12200.0956
    C9 灾害点密度0.00650.09210.0281
    下载: 导出CSV

    表  2   状态变量的突变模型

    Table  2   Catastrophe model of state variable

    突变模型控制变量维数势函数归一化公式
    折叠突变1$ \dfrac{1}{3}{x^3} + ax $$ {x_a} = \sqrt a $
    尖点突变2$\dfrac{1}{4}{x^4} + \dfrac{1}{2}a{x^2} + bx$$ {x_a} = \sqrt a $;$ {x_b} = \sqrt[3]{b} $
    燕尾突变3$\dfrac{1}{5}{x^5} + \dfrac{1}{3}a{x^3} + \dfrac{1}{2}b{x^2} + cx$$ {x_a} = \sqrt a $;$ {x_b} = \sqrt[3]{b} $;$ {x_c} = \sqrt[4]{c} $
    蝴蝶突变4$\dfrac{1}{6}{x^6} + \dfrac{1}{4}a{x^4} + \dfrac{1}{3}b{x^3} + \dfrac{1}{2}c{x^2} + dx$$ {x_a} = \sqrt a $;$ {x_b} = \sqrt[3]{b} $;$ {x_c} = \sqrt[4]{c} $;$ {x_d} = \sqrt[5]{d} $
    下载: 导出CSV

    表  3   危险性分区统计与对比

    Table  3   Risk zoning statistics and comparison

    评价方法危险性等级面积占比/%
    AHP25.14
    33.37
    27.16
    极高14.33
    突变理论13.96
    26.36
    28.16
    极高31.51
    AHP-突变理论组合模型18.39
    32.61
    27.49
    极高21.51
    下载: 导出CSV
  • [1] 高泽民,丁明涛,杨国辉,等. 川藏铁路孜热—波密段泥石流灾害危险性评价[J]. 工程地质学报,2021,29(2):478 − 485. [GAO Zemin,DING Mingtao,YANG Guohui,et al. Hazard assessment of debris flow along zire-Bomi section of Sichuan-Tibet railway[J]. Journal of Engineering Geology,2021,29(2):478 − 485. (in Chinese with English abstract) DOI: 10.13544/j.cnki.jeg.2021-0160

    GAO Zemin, DING Mingtao, YANG Guohui, et al. Hazard assessment of debris flow along zire-Bomi section of Sichuan-Tibet railway[J]. Journal of Engineering Geology, 2021, 29(2): 478-485. (in Chinese with English abstract) DOI: 10.13544/j.cnki.jeg.2021-0160

    [2] 洪增林,李永红,张玲玉,等. 一种基于主成分分析法的区域性地质灾害危险性评估方法[J]. 灾害学,2020,35(1):118 − 124. [HONG Zenglin,LI Yonghong,ZHANG Lingyu,et al. A method of regional geological hazard assessment based on principle component analysis[J]. Journal of Catastrophology,2020,35(1):118 − 124. (in Chinese with English abstract) DOI: 10.3969/j.issn.1000-811X.2020.01.022

    HONG Zenglin, LI Yonghong, ZHANG Lingyu, et al. A method of regional geological hazard assessment based on principle component analysis[J]. Journal of Catastrophology, 2020, 35(1): 118-124. (in Chinese with English abstract) DOI: 10.3969/j.issn.1000-811X.2020.01.022

    [3]

    MEJIA-NAVARRO M,WOHL E E. Geological hazard and risk evaluation using GIS:methodology and model applied to Medellin,Colombia[J]. Environmental & Engineering Geoscience,1994(4):459 − 481.

    [4] 魏会龙, 施秋华, 周金文, 等. 基于层次分析法的深圳市地面坍塌危险性评价[J]. 中国矿业, 2021, 30(增刊2): 110 − 116

    WEI Huilong, SHI Qiuhua, ZHOU Jinwen, et al. Risk assessment of ground collapse in Shenzhen based on analytic hierarchy process[J]. China Mining Magazine, 2021, 30(Sup 2): 110 − 116. (in Chinese with English abstract)

    [5] 王磊,常鸣,邢月龙. 基于信息量法模型与GIS的滑坡地质灾害风险性评价[J]. 地质灾害与环境保护,2021,32(2):14 − 20. [WANG Lei,CHANG Ming,XING Yuelong. Risk assessment of landslide geological hazards based on information method model and GIS[J]. Journal of Geological Hazards and Environment Preservation,2021,32(2):14 − 20. (in Chinese with English abstract) DOI: 10.3969/j.issn.1006-4362.2021.02.003

    WANG Lei, CHANG Ming, XING Yuelong. Risk assessment of landslide geological hazards based on information method model and GIS[J]. Journal of Geological Hazards and Environment Preservation, 2021, 32(2): 14-20. (in Chinese with English abstract) DOI: 10.3969/j.issn.1006-4362.2021.02.003

    [6]

    YU Kaining, FAN Cunliang, LI Jian, et al. Formation Characteristic and Comprehensive Classification of Debris Flow in Typical Mountain Area of the North of China[C]. The XVIII Kerulien International Conference on Geology. Geological Engineering and Mining Exploration in Central Asia. Australia: Aussino Academic Publishing House, 2013: 819-826.

    [7] 张晓敏,李辉,刘海南,等. 基于灰色系统理论的陕西省地质灾害趋势预测[J]. 中国地质灾害与防治学报,2018,29(5):7 − 12. [ZHANG Xiaomin,LI Hui,LIU Hainan,et al. Trend prediction of geological hazards in Shaanxi Province based on Grey System Theory[J]. The Chinese Journal of Geological Hazard and Control,2018,29(5):7 − 12. (in Chinese with English abstract) DOI: 10.16031/j.cnki.issn.1003-8035.2018.05.02

    ZHANG Xiaomin, LI Hui, LIU Hainan, et al. Trend prediction of geological hazards in Shaanxi Province based on Grey System Theory[J]. The Chinese Journal of Geological Hazard and Control, 2018, 29(5): 7-12. (in Chinese with English abstract) DOI: 10.16031/j.cnki.issn.1003-8035.2018.05.02

    [8] 郭学飞,王志一,焦润成,等. 基于层次分析法的北京市地质环境质量综合评价[J]. 中国地质灾害与防治学报,2021,32(1):70 − 76. [GUO Xuefei,WANG Zhiyi,JIAO Runcheng,et al. Comprehensive evaluation method of geological environment quality in Beijing based on AHP[J]. The Chinese Journal of Geological Hazard and Control,2021,32(1):70 − 76. (in Chinese with English abstract) DOI: 10.16031/j.cnki.issn.1003-8035.2021.01.10

    GUO Xuefei, WANG Zhiyi, JIAO Runcheng, et al. Comprehensive evaluation method of geological environment quality in Beijing based on AHP[J]. The Chinese Journal of Geological Hazard and Control, 2021, 32(1): 70-76. (in Chinese with English abstract) DOI: 10.16031/j.cnki.issn.1003-8035.2021.01.10

    [9] 李小龙,宋国虎,向灵芝,等. 基于不同评价单元和灾害熵的泥石流危险性分析—以白龙江流域武都段为例[J]. 中国地质灾害与防治学报,2021,32(6):107 − 115. [LI Xiaolong,SONG Guohu,XIANG Lingzhi,et al. Hazard analysis of debris flows based on different evaluation units and disaster entropy:A case study in Wudu section of the Bailong River Basin[J]. The Chinese Journal of Geological Hazard and Control,2021,32(6):107 − 115. (in Chinese with English abstract) DOI: 10.16031/j.cnki.issn.1003-8035.2021.06-13

    LI Xiaolong, SONG Guohu, XIANG Lingzhi, et al. Hazard analysis of debris flows based on different evaluation units and disaster entropy: a case study in Wudu section of the Bailong River Basin[J]. The Chinese Journal of Geological Hazard and Control, 2021, 32(6): 107-115. (in Chinese with English abstract) DOI: 10.16031/j.cnki.issn.1003-8035.2021.06-13

    [10] 何珊,李志军,董富权,等. 基于层次分析法的多元信息成矿预测研究—以西藏洛扎地区为例[J]. 地质与勘探,2018,54(1):148 − 157. [HE Shan,LI Zhijun,DONG Fuquan,et al. Multiple information metallogenic prediction based on the analytic hierarchy process:A case study of the lhozhag area in Tibet[J]. Geology and Exploration,2018,54(1):148 − 157. (in Chinese with English abstract) DOI: 10.13712/j.cnki.dzykt.2018.01.016

    HE Shan, LI Zhijun, DONG Fuquan, et al. Multiple information metallogenic prediction based on the analytic hierarchy process: a case study of the lhozhag area in Tibet[J]. Geology and Exploration, 2018, 54(1): 148-157. (in Chinese with English abstract) DOI: 10.13712/j.cnki.dzykt.2018.01.016

    [11]

    KAYASTHA P,DHITAL M R,DE SMEDT F. Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping:a case study from the Tinau watershed,west Nepal[J]. Computers & Geosciences,2013,52:398 − 408.

    [12] 侯圣山,曹鹏,陈亮,等. 基于数值模拟的耳阳河流域泥石流灾害危险性评价[J]. 水文地质工程地质,2021,48(2):143 − 151. [HOU Shengshan,CAO Peng,CHEN Liang,et al. Debris flow hazard assessment of the Eryang River watershed based on numerical simulation[J]. Hydrogeology & Engineering Geology,2021,48(2):143 − 151. (in Chinese with English abstract) DOI: 10.16030/j.cnki.issn.1000-3665.202003057

    HOU Shengshan, CAO Peng, CHEN Liang, et al. Debris flow hazard assessment of the Eryang River watershed based on numerical simulation[J]. Hydrogeology & Engineering Geology, 2021, 48(2): 143-151. (in Chinese with English abstract) DOI: 10.16030/j.cnki.issn.1000-3665.202003057

    [13]

    WICAKSONO Y S,SIHOMBING F H,INDRA T L. Landslide susceptibility map of Bogor Area using analytical hierarchy process[J]. IOP Conference Series:Earth and Environmental Science,2020,538(1):012050. DOI: 10.1088/1755-1315/538/1/012050

    [14] 陈绪新,秦哲,付厚利,等. 基于尖点突变模型饱水边坡稳定性分析[J]. 地质与勘探,2018,54(2):376 − 380. [CHEN Xuxin,QIN Zhe,FU Houli,et al. Analysis on stability of water-saturation slopes based on the cusp catastrophic model[J]. Geology and Exploration,2018,54(2):376 − 380. (in Chinese with English abstract) DOI: 10.13712/j.cnki.dzykt.2018.02.016

    CHEN Xuxin, QIN Zhe, FU Houli, et al. Analysis on stability of water-saturation slopes based on the cusp catastrophic model[J]. Geology and Exploration, 2018, 54(2): 376-380. (in Chinese with English abstract) DOI: 10.13712/j.cnki.dzykt.2018.02.016

    [15] 冯平,李绍飞,李建柱. 基于突变理论的地下水环境风险评价[J]. 自然灾害学报,2008,17(2):13 − 18. [FENG Ping,LI Shaofei,LI Jianzhu. Catastrophe theory-based risk evaluation of groundwater environment[J]. Journal of Natural Disasters,2008,17(2):13 − 18. (in Chinese with English abstract) DOI: 10.3969/j.issn.1004-4574.2008.02.003

    FENG Ping, LI Shaofei, LI Jianzhu. Catastrophe theory-based risk evaluation of groundwater environment[J]. Journal of Natural Disasters, 2008, 17(2): 13-18. (in Chinese with English abstract) DOI: 10.3969/j.issn.1004-4574.2008.02.003

    [16] 李绍飞,孙书洪,王向余. 突变理论在海河流域地下水环境风险评价中的应用[J]. 水利学报,2007,38(11):1312 − 1317. [LI Shaofei,SUN Shuhong,WANG Xiangyu. Application of catastrophe theory to risk assessment of groundwater environment for river basin[J]. Journal of Hydraulic Engineering,2007,38(11):1312 − 1317. (in Chinese with English abstract) DOI: 10.3321/j.issn:0559-9350.2007.11.007

    LI Shaofei, SUN Shuhong, WANG Xiangyu. Application of catastrophe theory to risk assessment of groundwater environment for river basin[J]. Journal of Hydraulic Engineering, 2007, 38(11): 1312-1317. (in Chinese with English abstract) DOI: 10.3321/j.issn:0559-9350.2007.11.007

    [17] 袁颖,李佳玉. 岩质边坡稳定性评价的尖点突变理论模型[J]. 地质与勘探,2021,57(1):183 − 189. [YUAN Ying,LI Jiayu. A cusp catastrophe theory model for evaluation of rock slope stability[J]. Geology and Exploration,2021,57(1):183 − 189. (in Chinese with English abstract)

    YUAN Ying, LI Jiayu. A cusp catastrophe theory model for evaluation of rock slope stability[J]. Geology and Exploration, 2021, 57(1): 183-189. (in Chinese with English abstract)

    [18] 尚志海,蔡文慧,欧先交,等. 基于突变理论的梅州市地质灾害灾度评估[J]. 安全与环境工程,2014,21(3):55 − 59. [SHANG Zhihai,CAI Wenhui,OU Xianjiao,et al. Geological hazard degree assessment of Meizhou City based on catastrophe theory[J]. Safety and Environmental Engineering,2014,21(3):55 − 59. (in Chinese with English abstract) DOI: 10.3969/j.issn.1671-1556.2014.03.011

    SHANG Zhihai, CAI Wenhui, OU Xianjiao, et al. Geological hazard degree assessment of Meizhou City based on catastrophe theory[J]. Safety and Environmental Engineering, 2014, 21(3): 55-59. (in Chinese with English abstract) DOI: 10.3969/j.issn.1671-1556.2014.03.011

    [19] 温晓艺,郑秀清,陈军锋,等. 基于突变理论的地质灾害风险性评价[J]. 山东农业大学学报(自然科学版),2019,50(4):575 − 581. [WEN Xiaoyi,ZHENG Xiuqing,CHEN Junfeng,et al. Risk assessment of geological disaster based on catastrophe theory[J]. Journal of Shandong Agricultural University (Natural Science Edition),2019,50(4):575 − 581. (in Chinese with English abstract) DOI: 10.3969/j.issn.1000-2324.2019.04.008

    WEN Xiaoyi, ZHENG Xiuqing, CHEN Junfeng, et al. Risk assessment of geological disaster based on catastrophe theory[J]. Journal of Shandong Agricultural University (Natural Science Edition), 2019, 50(4): 575-581. (in Chinese with English abstract) DOI: 10.3969/j.issn.1000-2324.2019.04.008

    [20] 陈菊艳,朱斌,彭三曦,等. 基于AHP和GIS的矿区岩溶塌陷易发性评估—以贵州林歹岩溶矿区为例[J]. 自然灾害学报,2021,30(5):226 − 236. [CHEN Juyan,ZHU Bin,PENG Sanxi,et al. Assessment of susceptibility to Karst collapse in mining area based on AHP and GIS:A case study in Lindai Karst mining area in Guizhou[J]. Journal of Natural Disasters,2021,30(5):226 − 236. (in Chinese with English abstract) DOI: 10.13577/j.jnd.2021.0522

    CHEN Juyan, ZHU Bin, PENG Sanxi, et al. Assessment of susceptibility to Karst collapse in mining area based on AHP and GIS: a case study in Lindai Karst mining area in Guizhou[J]. Journal of Natural Disasters, 2021, 30(5): 226-236. (in Chinese with English abstract) DOI: 10.13577/j.jnd.2021.0522

    [21] 杜国梁,杨志华,袁颖,等. 基于逻辑回归-信息量的川藏交通廊道滑坡易发性评价[J]. 水文地质工程地质,2021,48(5):102 − 111. [DU Guoliang,YANG Zhihua,YUAN Ying,et al. Landslide susceptibility mapping in the Sichuan-Tibet traffic corridor using logistic regression-information value method[J]. Hydrogeology & Engineering Geology,2021,48(5):102 − 111. (in Chinese with English abstract)

    DU Guoliang, YANG Zhihua, YUAN Ying, et al. Landslide susceptibility mapping in the Sichuan-Tibet traffic corridor using logistic regression-information value method[J]. Hydrogeology & Engineering Geology, 2021, 48(5): 102-111. (in Chinese with English abstract)

    [22] 李博. GRA—FAHP模型的煤层底板突水危险性评价[J]. 地质论评,2015,61(5):1128 − 1134. [LI Bo. Risk assessment model of coal floor water-irruption based on GRA-FAHP[J]. Geological Review,2015,61(5):1128 − 1134. (in Chinese with English abstract) DOI: 10.16509/j.georeview.2015.05.015

    LI Bo. Risk assessment model of coal floor water-irruption based on GRA-FAHP[J]. Geological Review, 2015, 61(5): 1128-1134. (in Chinese with English abstract) DOI: 10.16509/j.georeview.2015.05.015

    [23] 刘璐瑶,高惠瑛,李照. 基于CF与Logistic回归模型耦合的永嘉县滑坡易发性评价[J]. 中国海洋大学学报(自然科学版),2021,51(10):121 − 129. [LIU Luyao,GAO Huiying,LI Zhao. Landslide susceptibility assessment based on coupling of CF model and logistic regression model in Yongjia County[J]. Periodical of Ocean University of China,2021,51(10):121 − 129. (in Chinese with English abstract)

    LIU Luyao, GAO Huiying, LI Zhao. Landslide susceptibility assessment based on coupling of CF model and logistic regression model in Yongjia County[J]. Periodical of Ocean University of China, 2021, 51(10): 121-129. (in Chinese with English abstract)

    [24]

    SHAHINUZZAMAN M,HAQUE M N,SHAHID S. Delineation of groundwater potential zones using a parsimonious concept based on catastrophe theory and analytical hierarchy process[J]. Hydrogeology Journal,2021,29(3):1091 − 1116. DOI: 10.1007/s10040-021-02322-2

    [25] 宁娜,马金珠,张鹏,等. 基于GIS和信息量法的甘肃南部白龙江流域泥石流灾害危险性评价[J]. 资源科学,2013,35(4):892 − 899. [NING Na,MA Jinzhu,ZHANG Peng,et al. Debris flow hazard assessment for the Bailongjiang River,southern Gansu[J]. Resources Science,2013,35(4):892 − 899. (in Chinese with English abstract)

    NING Na, MA Jinzhu, ZHANG Peng, et al. Debris flow hazard assessment for the Bailongjiang River, southern Gansu[J]. Resources Science, 2013, 35(4): 892-899. (in Chinese with English abstract)

    [26] 覃乙根,杨根兰,江兴元,等. 基于确定性系数模型与逻辑回归模型耦合的地质灾害易发性评价—以贵州省开阳县为例[J]. 科学技术与工程,2020,20(1):96 − 103. [QIN Yigen,YANG Genlan,JIANG Xingyuan,et al. Geohazard susceptibility assessment based on integrated certainty factor model and logistic regression model for Kaiyang,China[J]. Science Technology and Engineering,2020,20(1):96 − 103. (in Chinese with English abstract) DOI: 10.3969/j.issn.1671-1815.2020.01.015

    QIN Yigen, YANG Genlan, JIANG Xingyuan, et al. Geohazard susceptibility assessment based on integrated certainty factor model and logistic regression model for Kaiyang, China[J]. Science Technology and Engineering, 2020, 20(1): 96-103. (in Chinese with English abstract) DOI: 10.3969/j.issn.1671-1815.2020.01.015

    [27] 杨宁, 陶志斌, 高松, 等. 基于AHP的DRASTIC模型对莱州地区地下水脆弱性研究[J]. 地质学报, 2019, 93(增刊 1): 133 − 137

    YANG Ning, TAO Zhibin, GAO Song, et al. Study of groundwater vulnerability in Laizhou using AHP-based DRASTIC model[J]. Acta Geologica Sinica, 2019, 93(Sup 1): 133 − 137. (in Chinese with English abstract)

    [28]

    YING X,ZENG G M,CHEN G Q,et al. Combining AHP with GIS in synthetic evaluation of eco-environment quality—a case study of Hunan Province,China[J]. Ecological Modelling,2007,209(2/3/4):97 − 109.

    [29] 夏兴生,朱秀芳,李月臣,等. 基于AHP-PCA熵组合权重模型的三峡库区(重庆段)农业生态环境脆弱性评价[J]. 南方农业学报,2016,47(4):548 − 556. [XIA Xingsheng,ZHU Xiufang,LI Yuechen,et al. Evaluation for vulnerability of agroecological environment in Three Gorges Reservoir area(Chongqing section)based on AHP-PCA entropy combination weight mode[J]. Journal of Southern Agriculture,2016,47(4):548 − 556. (in Chinese with English abstract) DOI: 10.3969/j:issn.2095-1191.2016.04.548

    XIA Xingsheng, ZHU Xiufang, LI Yuechen, et al. Evaluation for vulnerability of agroecological environment in Three Gorges Reservoir area(Chongqing section)based on AHP-PCA entropy combination weight mode[J]. Journal of Southern Agriculture, 2016, 47(4): 548-556. (in Chinese with English abstract) DOI: 10.3969/j:issn.2095-1191.2016.04.548

    [30] 杨康,薛喜成,段钊,等. 基于AHP-LR熵组合模型的子长市地质灾害危险性评价[J]. 科学技术与工程,2021,21(27):11551 − 11560. [YANG Kang,XUE Xicheng,DUAN Zhao,et al. Risk assessment of geological hazards in Zichang County based on AHP-LR entropy combined model[J]. Science Technology and Engineering,2021,21(27):11551 − 11560. (in Chinese with English abstract) DOI: 10.3969/j.issn.1671-1815.2021.27.013

    YANG Kang, XUE Xicheng, DUAN Zhao, et al. Risk assessment of geological hazards in Zichang County based on AHP-LR entropy combined model[J]. Science Technology and Engineering, 2021, 21(27): 11551-11560. (in Chinese with English abstract) DOI: 10.3969/j.issn.1671-1815.2021.27.013

  • 期刊类型引用(2)

    1. 王伯昕,高银龙,王清,刘佳奇. 冻融循环对季冻土区粉质黏土-混凝土界面剪切性能的影响. 吉林大学学报(地球科学版). 2024(05): 1592-1603 . 百度学术
    2. 张士俊,王宏宇,唐莉. 黄河流域陕西段地质灾害空间分布特征及其对极端气温的响应. 水利水电技术(中英文). 2024(12): 54-65 . 百度学术

    其他类型引用(3)

图(8)  /  表(3)
计量
  • 文章访问数:  5109
  • HTML全文浏览量:  3224
  • PDF下载量:  516
  • 被引次数: 5
出版历程
  • 收稿日期:  2022-01-16
  • 修回日期:  2022-04-07
  • 网络出版日期:  2023-01-09
  • 刊出日期:  2023-04-24

目录

/

返回文章
返回