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气候变化背景下降雨滑坡风险评估研究进展

黄雨, 何正迎

黄雨，何正迎. 气候变化背景下降雨滑坡风险评估研究进展[J]. 中国地质灾害与防治学报，2025，36(2): 13-27. DOI: 10.16031/j.cnki.issn.1003-8035.202501002
引用本文: 黄雨，何正迎. 气候变化背景下降雨滑坡风险评估研究进展[J]. 中国地质灾害与防治学报，2025，36(2): 13-27. DOI: 10.16031/j.cnki.issn.1003-8035.202501002
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HUANG Yu，HE Zhengying. Research progress on rainfall-triggered landslide risk assessment under the context of climate change[J]. The Chinese Journal of Geological Hazard and Control，2025，36(2): 13-27. DOI: 10.16031/j.cnki.issn.1003-8035.202501002
Citation: HUANG Yu，HE Zhengying. Research progress on rainfall-triggered landslide risk assessment under the context of climate change[J]. The Chinese Journal of Geological Hazard and Control，2025，36(2): 13-27. DOI: 10.16031/j.cnki.issn.1003-8035.202501002
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气候变化背景下降雨滑坡风险评估研究进展

  • 1.

    同济大学土木工程学院地下建筑与工程系，上海　200092

  • 2.

    土木工程防灾减灾全国重点实验室（同济大学），上海　200092

基金项目: 国家重点研发计划项目（2024YFC3012600）
详细信息
    作者简介:

    黄　雨（1973—），男，江苏南京人，工学博士，教授，主要从事工程地质教学与科研工作。E-mail：yhuang@tongji.edu.cn

  • 中图分类号: P642.22

Research progress on rainfall-triggered landslide risk assessment under the context of climate change

  • 1.

    Department of Geotechnical Engineering, College of Civil Engineering, Tongji University, Shanghai　200092, China

  • 2.

    State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai　200092, China

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    摘要
  • 摘要:

    随着全球气候变化的加剧，极端降雨事件日益频繁，导致降雨型滑坡灾害频发，造成了巨大的人员伤亡与经济损失。文章系统回顾了气候变化背景下降雨型滑坡风险评估的研究进展，重点讨论了以下三个关键方面：（1）考虑气候变化的降雨作用下边坡可靠度评估；（2）考虑降雨模式不确定性的边坡易损性评估；（3）基于机器学习方法的降雨型滑坡危险性评估。在此基础上，文章进一步分析了气候变化背景下降雨型滑坡风险评估所面临的多维挑战，包括气候变化带来的不确定性、高时空分辨率地质气象数据缺乏以及模型跨区域的适应性等。最后，文章从精细的地质调查、多因素孕灾机理、基于韧性的风险评估等角度，展望了实现降雨型滑坡灾害韧性防灾的未来研究方向。研究旨在为降雨型滑坡灾害的防灾减灾工作提供理论支持和方法参考，促进滑坡灾害风险管理的科学化与精细化发展。

    Abstract:

    With the intensification of global climate change, extreme rainfall events have become increasingly frequent, leading to recurrent rainfall-triggered landslides and causing significant casualties and economic losses. With the context of climate change, this study systematically reviews the research progress on advancements in probabilistic risk assessment of rainfall-triggered landslides, focusing on three key aspects: (1) slope reliability assessment under rainfall conditions considering climate change; (2) vulnerability assessment of slopes considering the uncertainty of rainfall patterns; and (3) rainfall-induced landslide hazard assessment based on machine learning methods. On this basis, this study further analyzes the multidimensional challenges faced by rainfall-triggered landslide risk assessment under climate change, including uncertainties associated with climate change, the lack of high spatio-temporal resolution geological and meteorological data, and the adaptability of models across different regions. Finally, from the perspectives of detailed geological surveys, multi-factor disaster gestation mechanisms, this study looks towards future research directions for enhancing resilience in rainfall-induced landslide disaster prevention, from landslide mechanisms under multiple factors, to resilience-based risk assessment. This study aims to provide theoretical support and methodological references for the disaster prevention and mitigation work of rainfall-triggered landslides, promoting the scientific, systematic, and refined development of landslide risk management.

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  • 0.   引言

    强降雨作用下，山地丘陵区极易发生山洪、崩塌、滑坡、泥石流等地质灾害，并且可能阻断河流，形成堰塞湖，威胁堰塞体上下游人民生命财产安全[1 − 3]。据统计，近年来我国地质灾害造成的年死亡人数达200～400人[4]。山地丘陵地区由降雨引发的滑坡、泥石流灾害频发，造成严重的人员伤亡和经济财产损失[5]。在自然降雨条件下，山区中堆积的松散土体会在强降雨作用下诱发滑坡和泥石流灾害。大体积滑坡和泥石流汇入江河后，极易堵塞河道形成堰塞坝，壅高上游水位，堰塞坝一旦溃决将在下游造成巨大的洪水灾害，形成滑坡/泥石流-堰塞湖-溃决洪水灾害链[6 − 8]。

    降雨是滑坡/泥石流-堰塞湖-溃决洪水灾害链的主要诱发因素，尤其是强度大、持续时间长的降雨往往是引发滑坡/泥石流-堰塞湖-溃决洪水灾害链的关键控制因素[9 − 11]。通过降雨试验揭示降雨诱发滑坡/泥石流-堰塞湖-溃决洪水灾害链的机理对防灾减灾工作具有重要意义。目前，众多学者采用物理模型试验揭示降雨诱发地质灾害的机理，王如宾等[12]基于人工模拟降雨室内大型滑坡模型试验，揭示了降雨诱发滑坡变形破坏机理。胡华等[13]设计了降雨滑坡模拟试验，研究了降雨强度和斜坡坡度对滑塌破坏的影响。部分学者通过现场试验来揭示降雨诱发地质灾害的机理，谭建民等[14]开展了降雨边坡破坏现场试验，探究了降雨作用下花岗岩风化土坡的失稳机制。周中等[15]综合通过人工降雨模拟试验和原位综合监测手段，探究了降雨条件下土石混合体滑坡的失稳机理。王刚等[16]开展降雨型滑坡现场试验研究，探究了不同雨强条件下天然黄土边坡的入渗规律及变形破坏模式。詹良通等[17]对非饱和膨胀土进行了降雨试验和原位监测，揭示了降雨入渗对边坡失稳的影响。综上可知，目前在利用模型试验和现场试验揭示降雨滑坡诱发机理方面已经开展了大量研究，取得了一些新的认识，但是，室内模型试验存在尺寸效应，难以还原灾害的真实情况，而现有现场试验多不是在灾害现场开展的原位试验。因此，在灾害现场开展原位试验对进一步探究降雨诱发滑坡、泥石流灾害机理至关重要。

    本文选取2020年发生在四川省凉山州甘洛县黑西洛沟的山洪-滑坡-泥石流-堰塞湖灾害链残留边坡开展现场人工降雨试验，综合利用三维激光扫描仪、孔隙水压力计、土壤含水率传感器、EDS能谱分析等多种设备和方法，探究降雨诱发该处滑坡的机理，以期为当地的防灾减灾提供有益借鉴。

    1.   灾害概况

    黑西洛沟位于四川省凉山州甘洛县，为尼日河右侧的一条小山沟，长度约5 km。经现场调查，沟道两侧松散物源分布广泛，植被不发育。在非汛期，沟内仅有较小溪流流出，在枯水季节沟内偶尔断流。2020年8月31日上午8时，在持续的降雨作用下，黑西洛沟内发生了山洪-滑坡-泥石流-堰塞湖灾害链。灾害发生时，黑西洛沟内原有松散物源被山洪裹挟带走，并在运移过程中不断铲刮沟道底部物源，导致沟边两侧边坡失稳，逐渐演变为滑坡灾害。沟内通道不断下切过程中，两侧岸坡持续垮塌，崩塌体进入沟道后，滑坡规模急速扩大，最终演变为泥石流灾害。大量泥石流物源几乎呈垂直状态冲入尼日河，形成堰塞坝，堵塞尼日河，如图1（a）所示。经现场测量，形成的堰塞坝沿河道纵向方向长度约200 m，顺河向长度约为400 m，高度约30 m，堰塞坝体积约100×104 m3。堰塞坝自然溃决后冲毁下游场镇、村庄、学校和道路，造成阿兹觉乡一千余名群众受灾，3人失踪，黑西洛沟口的成昆铁路桥梁被冲毁，成昆铁路断道数月，堰塞坝下游的国道G245约1.2 km道路和多处桥梁被掩埋、冲毁，多栋房屋损毁，经济损失严重。堰塞坝材料在下游1 km范围内淤积，导致下游阿兹觉村挖哈组、乃牛组两个组被完全掩埋。

    图  1  黑西洛沟堰塞坝全貌和沟内上游影像
    Figure  1.  Overview of the barrier dam and upper reaches image inside Hexilou gully
    下载: 全尺寸图片 幻灯片

    通过现场调查和资料收集，本次滑坡-泥石流-堰塞湖灾害链是一次典型的“小水大灾”灾害，本文聚焦该灾害链中的滑坡灾害，通过现场降雨试验和室内EDS能谱分析，以期揭示降雨作用下边坡侵蚀破坏的发生机理。

    2.   现场试验

    2.1   试验边坡概况

    本次现场模型试验在2020年黑西洛沟灾害后的残余边坡上进行，试验边坡高度约为2.2 m，宽约2.0 m，坡长约3.0 m，天然坡度约为49°，如图1（b）所示。降雨试验前对坡面进行简单平整，清除坡面杂草、大块石等影响坡面径流和入渗的障碍物。现场筛分试验测得黑西洛沟内松散堆积体的颗粒级配曲线如图2所示[18]。

    图  2  黑西洛沟土体颗粒级配曲线
    Figure  2.  Particle size distribution curve of soil in Hexiluo gully
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    2.2   降雨及监测设备

    降雨装置主要包括支架、雨水输送管道、喷头和雨量计。喷头设置在边坡顶部并延伸至坡面，喷头顶部可通过调节流量的方式模拟不同的雨强。

    试验中设计了两排喷头，试验中经过多次调试，最终确定喷头间距约为0.7 m，每排喷头间距约为0.5 m，经现场观察，这一间距能够确保坡面降雨的均匀性。雨量计放置在边坡试验区，位于试验降雨区内，以实时测量坡面的降雨量，测得值能代表试验区的平均雨量，降雨试验装置如图3所示。

    图  3  现场降雨试验装置
    Figure  3.  Field rainfall testing device
    下载: 全尺寸图片 幻灯片

    试验中数据采集设备包括孔隙水压力传感器、土壤含水率传感器、雨量计以及三维激光扫描仪，其中孔隙水压力传感器3个，土壤含水率传感器3个。孔隙水压力传感器量程是10 kPa，准确度误差≤0.5 F∙S，土壤含水率传感器测量范围0～100%。黑西洛沟滑坡灾害的主要原因就是堆积体浅层物源浸水后被冲出，故为了与灾害实际情况相似，本次试验所用传感器埋入边坡表层，深度为0.3 m。孔隙水压力计和土壤含水率传感器放入预挖的孔洞后，利用坡体原样土回填后进行人工夯实，保证夯实后孔内的土体与天然状态一致。边坡尺寸和传感器埋设的位置如图4所示。三维激光扫描仪立于边坡的正面，通过不同阶段的扫描，以获取降雨过程中边坡的三维地形点云数据，由此识别边坡的变形破坏过程。

    图  4  传感器布置示意图（单位：mm）
    Figure  4.  Sensor layout diagram (unit: mm)
    下载: 全尺寸图片 幻灯片

    2.3   降雨试验方案

    根据甘洛县水利局的实测数据，本次灾害发生前后黑西洛沟临近监测站点的降雨数据如图5所示。临近监测站点位于苏雄镇，距离灾害点约500 m，本站点降雨数据可以代表真实的降雨量。灾害发生时当地已连续降雨约15 h，持续降雨导致沟内的松散物源浸水饱和，并最终被沟内山洪裹挟冲出，诱发链生的滑坡、泥石流和堰塞湖灾害，降雨是此次灾害链发生的主要诱因。为了更好地分析灾害链发生机理，试验降雨量尽量保证与灾害实际情况相符。受现场试验条件限制，经雨量计实测，此次现场试验共计降雨量为28 mm，降雨历时150 min，小时降雨量为11.2mm，试验小时降雨量与灾害发生时的降雨量接近，如图5所示。

    图  5  黑西洛沟临近站点实测降雨量过程
    Figure  5.  Process of measured rainfall data at the adjacent site in Hexiluo gully
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    3.   试验结果分析

    本研究通过对试验数据的分析，揭示降雨条件下黑西洛沟内残余边坡内部的孔隙水压力和土壤含水率变化规律，同时通过三维激光扫描仪精准识别边坡表面的变形破坏过程。

    3.1   孔隙水压力监测结果分析

    根据现场监测结果，得出降雨过程中边坡内孔隙水压力随降雨历时的变化规律，如图6所示。

    图  6  孔隙水压力随降雨历时的变化规律
    Figure  6.  Variation of pore water pressure with rainfall duration in Hexiluo gully
    下载: 全尺寸图片 幻灯片

    由图6可知，边坡体内孔隙水压力的变化过程大致可分为三个阶段：加速上升、下降和趋于稳定。降雨初期，雨水未入渗至坡体内部，孔隙水压力传感器监测数据未发生明显变化。随着降雨的持续进行，雨水在入渗过程中逐渐汇聚在坡面，形成坡面径流和坡内渗流，导致孔隙水压力开始变化，其中A1和A3孔隙水压力传感器在40 min至50 min陡然增加，边坡表面出现冲刷痕迹。继续降雨，边坡表面产生拉裂缝，雨水通过裂缝

    不断渗入坡体内部，孔隙水压力持续上升，致使边坡的抗剪强度由于有效应力的减少而降低。降雨后期，边坡表面出现局部塌陷，坡体内部渗透路径发生变化，导致孔隙水压力开始下降。

    降雨35～50 min时间段内，A1和A3传感器的孔隙水压力开始增加，坡面有明显的降雨冲蚀痕迹。继续降雨，A1和A3传感器的数据持续上升。降雨65 min后，A2孔隙水压力传感器才开始快速增加，并且此位置的含水率传感器也有明显响应，含水率曲线开始发生变化，土体的含水率开始逐渐上升，含水率和孔隙水压力变化一致。此时坡面的雨水冲蚀痕迹加深，侵蚀破坏范围扩大，土体颗粒被水流带走堆积在坡脚，整个坡面有明显的冲刷破坏。继续进行降雨，边坡土体开裂，雨水沿着拉裂缝进入坡体内部，孔隙水软化了边坡土体，土体有效应力减少，边坡稳定性下降，坡面产生了明显的局部塌陷，内部渗流场发生变化，孔隙水压力开始下降，直至不再改变。

    不同位置的孔隙水压力传感器变化有明显差异，原因是，A3传感器位于坡顶，A1传感器位于边坡中部，降雨过程中，A1传感器由于受到降雨入渗和上部土体水分沿拉裂缝入渗的补给，上升速度更快，孔隙水压力相较更大。A2孔隙水压力传感器数据明显滞后，因为该传感器周围有无法清理的大块石，降雨过程中，雨水流经坡面，块石改变了雨水的渗流路径，导致其渗透速度变慢。

    3.2   土壤含水率监测结果分析

    持续降雨条件下边坡不同位置的土壤含水率变化规律如图7所示。

    图  7  土壤含水率随降雨历时的变化规律
    Figure  7.  Variation of soil water content with rainfall duration in Hexiluo gully
    下载: 全尺寸图片 幻灯片

    由图7可知，降雨过程中，含水率持续增大，并最终趋于稳定。土体含水率随降雨历时共经历3个变化阶段：基本不变、加速增大和保持稳定。在降雨初期，边坡雨水入渗量较少，各个监测点的土壤含水率均无明显变化，坡体处在基本稳定状态。随着降雨历时的增加，雨水逐渐从坡面向

    坡体内部渗透，土壤含水率开始增加，降雨入渗使得土体由非饱和状态向饱和状态过渡，坡面土体遇水软化，强度降低，表面出现多处裂缝，在土体内部形成渗流通道，B2和B3位置的土壤含水率处于快速增长阶段，降雨后期，B1传感器才有明显的变化，最后土壤含水率都保持平稳状态。出现这种现象的原因是，雨水流经坡体表面，表层土体被冲刷而流失，水分子与土粒在表面形成阻碍入渗的结合水膜，土体内部气体无法排出，使得雨水难以下渗，边坡内的水分保持平衡，土壤含水率达到稳定，但此时边坡土体并未达到饱和状态。

    土壤含水率明显变化的这段时间内，含水率传感器埋设位置的孔隙水压力也在迅速上升。降雨50 min左右，雨水流过坡面形成冲沟，坡面产生侵蚀破坏，如图8（a）所示。B3土壤含水率传感器开始快速增加，此时该位置的孔隙水压力也处在快速上升阶段，土体抗侵蚀性下降，坡体表面出现雨水冲蚀痕迹，发生降雨侵蚀破坏；降雨90 min左右，B3含水率传感器达到最大值并保持不变，此时土体孔隙水压力也达到稳定值，不再改变，边坡上部土体侵蚀破坏范围扩大，土体稳定性降低。降雨后期，B1传感器才开始加速上升。整个坡面的侵蚀进一步扩大，表面出现局部塌陷，如图8（b）所示。整个降雨过程中，雨水聚集在边坡表面，流经边坡使其受到侵蚀破坏，同时在降雨过程中，坡面产生裂缝，形成渗流优势通道，更有利于雨水的入渗，使得土体含水率不断增大。

    图  8  降雨过程中边坡变形破坏特征
    Figure  8.  Slope deformation and failure characteristics during rainfall
    下载: 全尺寸图片 幻灯片

    3.3   边坡破坏过程分析

    降雨试验过程中的边坡坡面形态变化过程如图9所示。试验过程中，分别在持续降雨45，90，135 min三个时间点对坡面的三维形体进行扫描，获取坡面点云数据，经多期作差后，可以识别出边坡不同阶段的坡面三维形态变化，降雨过程中坡面形态变化云图如图10所示。

    图  9  降雨过程中坡面形态图
    Figure  9.  Morphology map of the Slope surface during rainfall
    下载: 全尺寸图片 幻灯片
    图  10  边坡坡面变形云图（负值表示冲刷，正值表示淤积）
    Figure  10.  Nephogram of side slope deformation (negative values indicate erosion, positive values indicate deposition)
    下载: 全尺寸图片 幻灯片

    由图10可知，持续降雨过程中，边坡的破坏过程具体表现为：持续降雨45 min后，坡面出现了侵蚀破坏，雨水在坡面聚集，形成表面径流，带走坡体表面的松散颗粒。从边坡坡面变形云图可以看到，边坡表面有明显的冲刷区域，被冲刷掉的土体堆积在了坡脚。随着时间与累计降雨量的增大，试验边坡坡面破坏开始逐渐明显，坡面的冲刷痕迹不断加深，冲刷范围不断扩大，边坡上部土体流失，在边坡中部位置发生局部垮塌现象，如图9所示。这段时间，土体内部孔隙水压力也在迅速增大，变形破坏与孔隙水压力之间响应关系明显。降雨120 min后，如图9（b）所示，边坡前缘的冲沟逐渐加宽加深，表面出现多处拉裂缝，雨水沿着裂缝进入土体内部，边坡变形破坏范围不断扩大，此时土壤含水率陡然增加，边坡产生局部垮塌，土体内部渗透路径发生改变，孔隙水压力开始下降。持续降雨135 min后，由图10可知，边坡表面有更多的土体流失且在坡脚堆积。从坡面形态图中可以看出，位移变化的对应位置有裂缝产生和局部小范围的塌陷，雨水的冲蚀痕迹明显，坡脚堆积土体明显增多。

    基于多次三维激光扫描获取的点云数据，通过计算得到本次整个降雨试验过程中边坡坡面的冲刷物源体积约为10.0 dm3。

    3.4   EDS测试结果分析

    为进一步揭示该残余边坡的变形破坏原因，对试验土样开展了X射线能谱分析（EDS）测试。能谱仪配合扫描电子显微镜与透射电子显微镜的

    使用，可以获取土样成分的元素种类及含量，其测试结果如表1所示。

    表  1  边坡物质成分组成表
    Table  1.  Composition of slope material components
    元素 质量百分比/% 原子百分比/% 标准样品标签
    C 8.08 12.91 C
    O 49.38 59.23 SiO2
    Na 1.84 1.54 Albite（钠长石）
    Mg 0.39 0.31 MgO
    Al 6.96 4.95 Al2O3
    Si 26.51 18.11 SiO2
    K 3.72 1.82 KBr
    Ca 0.28 0.14 Wollastonite（硅石灰）
    Ti 0.36 0.14 Ti
    Fe 2.49 0.86 Fe
    总量 100 100
    下载: 导出CSV 
    | 显示表格

    由表1可知，边坡的物质成分较为复杂，主要化学成分为SiO2和Al2O3，含少量Mg、Fe、Na元素。物质组成表明边坡土体中含有伊利石和高岭石等黏土矿物，而伊利石和高岭石是影响膨胀土性质的主要矿物。膨胀土吸水膨胀，遇水崩解或软化，抗冲刷性能差。因此，含有伊利石和高岭石等黏性矿物的边坡表面极易吸水膨胀，抗冲刷能力降低，导致边坡表层土体强度急剧衰减，在降雨作用下极易冲刷破坏。

    由图9可知，降雨120 min后，边坡表面出现了侵蚀破坏和局部塌陷，土体被雨水带走堆积在坡脚，整体稳定性受到影响，原因在于：非饱和膨胀土在长时间的持续降雨作用下，雨水入渗会使得浅表层土体孔隙水压力上升和吸力降低。孔隙水压力的升高会导致坡体滑动力增加，且土体的有效应力下降，边坡强度降低，边坡坡面发生侵蚀冲刷。同时吸力下降将使得土层发生膨胀，含有高岭石、伊利石等黏性矿物的边坡土体会因为吸水膨胀而软化，导致土体的抗冲刷性能下降，土颗粒之间的黏聚力随时间而降低，在重力和雨水裹挟作用下，导致边坡出现了多处拉裂缝，拉裂缝的产生使得雨水进一步入渗，雨水充满裂缝产生水压力导致边坡强度降低，加剧边坡的破坏，最终边坡坡面产生冲刷破坏和局部塌陷。

    4.   结论

    （1）降雨作用下，边坡土壤含水率发生明显增加；同时孔隙水压力在降雨期间也会增大，后期土体发生变形破坏，孔隙水压力开始下降。

    （2）三维激光扫描结果表明：边坡表面有明显的冲刷区域且范围不断扩大，持续降雨导致边坡的抗侵蚀能力变弱，土体被雨水冲刷而流失，流失的土颗粒堆积在坡脚。整个降雨试验过程中，边坡坡面的冲刷物源体积约为10.0 dm3。

    （3）EDS测试结果表明边坡土体含有伊利石和高岭石等黏性矿物，遇水后极易发生膨胀而软化，导致土体黏聚力降低，边坡抗侵蚀能力变弱，边坡产生拉裂缝，雨水充满裂缝产生水压力加剧边坡破坏，恶化了边坡稳定性，最终发生冲刷破坏和局部塌陷。

    （4）试验对揭示降雨作用下边坡侵蚀破坏机理具有重要意义。降雨入渗使得边坡土体内的含水率和孔隙水压力发生波动陡增，导致土体基质吸力减小，土体软化，从而导致边坡土体强度降低是边坡发生侵蚀破坏的主要原因。

  • 图  1   考虑气候变化的降雨作用下边坡可靠度评估框架（改自He等[33]）

    Figure  1.   Framework for reliability assessment of rainfall-triggered landslides considering climate change (adapted from He et al. [33])

    下载: 全尺寸图片 幻灯片

    图  2   考虑降雨模式及岩土性质不确定性的边坡易损性评估框架示意图 （改自He等[32]）

    Figure  2.   Framework for slope fragility assessment considering uncertainties in rainfall patterns and geotechnical properties (adapted from He et al. [32])

    下载: 全尺寸图片 幻灯片

    图  3   基于机器学习的降雨型滑坡危险性评估框架示意图 （改自文献[91 − 92]）

    Figure  3.   Framework for rainfall-induced landslide hazard assessment based on machine learning (adapted from references [91 − 92])

    下载: 全尺寸图片 幻灯片
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  • 收稿日期:  2025-01-01
  • 修回日期:  2025-02-16
  • 网络出版日期:  2025-03-16
  • 刊出日期:  2025-04-24

目录

摘要
HTML全文

  • 0.   引言

  • 1.   灾害概况

  • 2.   现场试验

  • 2.1   试验边坡概况

  • 2.2   降雨及监测设备

  • 2.3   降雨试验方案

  • 3.   试验结果分析

  • 3.1   孔隙水压力监测结果分析

  • 3.2   土壤含水率监测结果分析

  • 3.3   边坡破坏过程分析

  • 3.4   EDS测试结果分析

  • 4.   结论

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