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基于斜坡单元灾害强度的滑坡灾害易损性评价

陈宾 魏娜 张联志 李颖懿 刘宁 屈添强

陈宾,魏娜,张联志,等. 基于斜坡单元灾害强度的滑坡灾害易损性评价−以湖南省湘乡市为例[J]. 中国地质灾害与防治学报,2023,34(0): 1-9 doi: 10.16031/j.cnki.issn.1003-8035.202211901
引用本文: 陈宾,魏娜,张联志,等. 基于斜坡单元灾害强度的滑坡灾害易损性评价−以湖南省湘乡市为例[J]. 中国地质灾害与防治学报,2023,34(0): 1-9 doi: 10.16031/j.cnki.issn.1003-8035.202211901
CHEN Bin,WEI Na,ZHANG Lianzhi,et al. Vulnerability assessment of landslide hazards based on hazard intensity at slope level: A case study in Xiangxiang county of Hunan[J]. The Chinese Journal of Geological Hazard and Control,2023,34(0): 1-9 doi: 10.16031/j.cnki.issn.1003-8035.202211901
Citation: CHEN Bin,WEI Na,ZHANG Lianzhi,et al. Vulnerability assessment of landslide hazards based on hazard intensity at slope level: A case study in Xiangxiang county of Hunan[J]. The Chinese Journal of Geological Hazard and Control,2023,34(0): 1-9 doi: 10.16031/j.cnki.issn.1003-8035.202211901

基于斜坡单元灾害强度的滑坡灾害易损性评价

doi: 10.16031/j.cnki.issn.1003-8035.202211901
基金项目: 湖南省创新性省份建设专项(2019RS1059);国家自然科学基金项目(51774131;41972282)。
详细信息
    作者简介:

    陈宾(1977—),男,博士,副教授,主要从事地质灾害防治方面的研究工作。E-mail:403021235@qq.com

    通讯作者:

    张联志(1988—),男,硕士,工程师,主要从事水工环地质工作。E-mail:2149859375@qq.com

  • 中图分类号: P642.2

Vulnerability assessment of landslide hazards based on hazard intensity at slope level: A case study in Xiangxiang county of Hunan

  • 摘要: 以斜坡为单元,基于潜在灾害强度的区域性易损性评价是地质灾害防治亟待解决的重要问题之一。以湖南省湘乡市为研究区,在采用加权信息量方法进行易发性区划的基础上,逐个提取斜坡单元最高易发值点的高程、坡高、坡度、坡向、月平均降雨量为特征参数,分别代入BP神经网络、PSO-BP神经网络、随机森林及支持向量机模型。通过训练与精度测试对比,构建基于PSO优化BP神经网络算法的滑坡体积预测模型,建立以灾害体积为灾害强度指标,以建筑密度、人口密度、财产密度等为脆弱性指标的易损性综合评价模型。针对研究区开展基于潜在灾害强度的区域性易损性评价,完成高易损区(面积占比1.5%)、中易损区(面积占比28.5%)和低易损区(面积占比70%)的区划,实现了区域性易损性评价过程中致灾体灾害强度与承灾体脆弱性的有机结合,增强了评价的客观性和科学性。
  • 图  1  斜坡单元灾害强度评价流程图

    Figure  1.  Flow chart of the slope unit disaster intensity assessment

    图  2  湘乡市地质灾害易发性分区图

    Figure  2.  Zoning map of geological hazard susceptibility in the city of Xiangxiang

    图  3  各模型测试集预测误差统计曲线

    Figure  3.  Statistical curves of prediction error for each model test set

    图  4  湘乡市斜坡单元灾害强度分布图

    Figure  4.  Disaster intensity distribution map of slope units in the city of Xiangxiang

    图  5  湘乡市斜坡单元脆弱性分布图

    Figure  5.  Vulnerability distribution map of slope units in the city of Xiangxiang

    图  6  湘乡市斜坡单元易损性分区图

    Figure  6.  Vulnerability distribution map of slope units in the city of Xiangxiang

    表  1  斜坡单元易损性综合评价

    Table  1.   Comprehensive evaluation of the vulnerability of slope units

    易损性等级脆弱性等级
    低脆弱性中脆弱性高脆弱性
    灾害强度等级弱灾害强度
    中灾害强度
    强灾害强度
    下载: 导出CSV

    表  2  研究区基础数据

    Table  2.   Basic data of the study area

    名称类型精度
    遥感影像栅格0.5 m
    DEM栅格1∶10 000
    工程地质图、土地利用类型图矢量1∶50 000
    断层图、路网图矢量1∶50 000
    行政区划图矢量1∶10 000
    降雨数据数据表
    历史灾害点数据表
    GDP数据表湘乡市
    人口、建筑面积、道路、财产数据表斜坡单元
    斜坡单元面积数据表斜坡单元
    下载: 导出CSV

    表  3  易发性评价指标分区结果

    Table  3.   Partition results of the susceptibility evaluation indicators

    评价指标二级指标区间
    高程/m32~<101;101~<171;171~<267;267~<409;≥409
    坡度/(°)0~<6;6~<17;17~<28;28~<40;≥40
    坡向平面;北;东北;东;东南;南;西南;西;西北
    工程地质岩组硅质岩、硅质板岩;浅变质砂岩夹板岩;板岩;砂岩、砂砾岩;碳酸盐岩与碎屑岩互层;碳酸盐岩;岩浆岩;土体;红色碎屑岩;砂岩、页岩;硅质岩、硅质页岩
    距断层距离/m<100;100~<200;200~<300;300~<400;≥400
    距道路距离/m<100;100~<200;200~<300;300~<400;≥400
    土地利用情况耕地;林地;草地;水域;城乡、工矿居民用地;未利用土地类型
    月平均降雨量/mm<100;100~<150;150~<200;≥200
    下载: 导出CSV

    表  4  湘乡市地质灾害易发性分区结果

    Table  4.   Results of geological hazard susceptibility zoning in the city of Xiangxiang

    易发性分区面积比例/%灾害点数量/个灾害点比例/%灾积比
    高易发8.221671.31.43
    中易发39.37524.80.10
    低易发52.5123.90.012
    下载: 导出CSV

    表  5  指标因子相关性分析

    Table  5.   Correlation of the controlling factors

    指标因子高程坡高坡度坡向工程地质岩组距断层距离距道路距离土地利用情况月平均降雨量滑坡体积
    高程10.057−0.055−0.036−0.169−0.3580.3280.1030.0130.239
    坡高10.042−0.028−0.31−0.26−0.1990.1680.0340.333
    坡度1−0.027−0.428−0.1040.2450.051−0.133−0.205
    坡向10.0030.007−0.066−0.493−0.1230.196
    工程地质岩组10.070.208−0.0240.0430.003
    距断层距离1−0.211−0.1020.207−0.026
    距道路距离10.2840.0220.06
    土地利用情况1−0.047−0.102
    月平均降雨量1−0.313
    滑坡体积1
    下载: 导出CSV

    表  6  各模型预测结果精度对比

    Table  6.   Comparison of prediction accuracy of each model

    测试集结果预测正确样本量/个预测错误样本量/个预测精度/%
    BP神经网络211558.33
    PSO-BP神经网络29780.56
    随机森林181850.00
    支持向量机251169.44
    下载: 导出CSV

    表  7  斜坡单元灾害强度等级分区结果

    Table  7.   Results of disaster intensity classification of slope units

    预测体积分区/m³灾害强度等级
    <15 000弱灾害强度
    15 000~45 000中灾害强度
    >45 000强灾害强度
    下载: 导出CSV

    表  8  脆弱性评价指标组合权重结果

    Table  8.   Combined weight results of vulnerability assessment indicators

    评价因子权重值
    人口密度0.3072
    建筑密度0.2160
    道路密度0.2141
    GDP密度0.1607
    财产密度0.1026
    下载: 导出CSV

    表  9  斜坡单元脆弱性等级分区结果

    Table  9.   Results of vulnerability classification of slope units

    脆弱性值分区脆弱性等级
    <0.0845低脆弱性
    0.0845 ~ 0.1750中脆弱性
    >0.1750高脆弱性
    下载: 导出CSV

    表  10  斜坡单元易损性统计结果

    Table  10.   Statistical results of slope unit vulnerability

    易损性分区斜坡单元数量/个斜坡单元数量占比/%
    高易损区1242.6
    中易损区2 02342.7
    低易损区2 58754.7
    下载: 导出CSV
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  • 收稿日期:  2022-11-09
  • 修回日期:  2023-04-04
  • 网络出版日期:  2023-06-09

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