重庆市万州区滑坡灾害危险性评价研究

doi:10.13722/j.cnki.jrme.2023.0474

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摘要基于滑坡发生成因选取评价指标，设计客观、合理的评价和分级方法，实现区域滑坡灾害危险性评价对防御滑坡灾害和准确预警具有现实意义。基于现有滑坡危险性评价中，评价指标欠全面、评价指标分级偏主观、评价结果无法直接衡量出不同因子对区域整体及各危险区滑坡影响程度大小的现状，以滑坡灾害严重的重庆万州区为例，在充分考虑评价因子合理性的前提下，应用客观划分评价因子等级的证据权法，对区域滑坡灾害的危险性进行评价，并通过结合滑坡危险性敏感程度指数(SW)、创建的滑坡危险性影响程度指数(SI)及不同危险区影响程度指数(HW)，量化各评价因子整体对区域滑坡发生的敏感程度和影响程度，以及对不同危险区的影响程度的差异，为降低区域滑坡危险性提供更准确和针对性的理论参考，对提高区域滑坡灾害的有效防御能力具有重要意义。研究表明：(1) 经独立性检验确定了剔除地形起伏度的万州区滑坡灾害危险性评价指标体系，该评价体系较全面概括了滑坡发生成因。(2) 在评价指标初分级的基础上，结合证据权值、滑坡面积比和分级面积进行基于证据权法的评价指标终分级，实现证据权法支持下的区域滑坡危险性评价，评价结果经成功率曲线法验证，精度达72%，从指标选取和评价精度上体现出本研究方法的可靠性。(3) SW和SI指数分析得出，高程、道路距离、多年平均降雨量因子的区域整体敏感程度和影响程度均居前三，但其余因子在敏感程度和影响程度的排序上表现出差异性，说明SI指数创建的必要性和科学性。(4) HW指数说明，高、中和低危险区滑坡评价因子表现出与区域整体一致的影响程度特征，但较高危险区以道路距离因子影响程度最大；较低危险区则以归一化植被指数的影响程度上升为第二位，体现出HW指数构建必要性。(5) 低危险区主要位于植被覆盖度较高的高海拔区，此处常绿阔叶林和针叶林对滑坡发生有着抑制作用；高危险区主要位于万州区人类活动集聚特征显著的主城区，沿长江及其支流分布，且降水量多集中在1 213～1 229 mm的低海拔区，该类区域应通过开展合理的减滑工程措施、抗滑支挡工程措施及绿化护坡等，实施工程治理措施，以达到降低区域滑坡危险性的目的。

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	谢晓1
	卢晓宁1
	沈文宇1
	马启民1
	唐云辉2
	杨秋萍1
	刘明林1
	李实康1
	夏志业1

关键词 ：边坡工程, 滑坡, 危险性评价, 证据权法, GIS

Abstract：Based on the factors contributing to landslide occurrence，a well-designed and objective evaluation system is proposed to assess and classify the hazard of regional landslide disasters，which holds practical significance for both landslide disaster prevention and accurate forecasting. This study highlights the limitations of existing landslide hazard evaluation methods，such as incomplete evaluation indicators，subjectivity in the classification of evaluation criteria，and the inability to directly measure the current impact of different factors on the overall region and different hazard landslide areas. Taking the severely landslide-prone Wanzhou District in Chongqing as an example，under the premise of fully considering the rationality of evaluation factors，an objective division of evaluation factor levels using the weights of evidence method is applied to assess the hazard of regional landslide disasters. By combining the landslide hazard sensitivity index(SW) and the newly created landslide hazard impact index(SI)，along with the impact index(HW) for different hazardous areas，the overall sensitivity and impact of each evaluation factor on regional landslide occurrence are quantified. Moreover，the differences in impact on different hazardous areas are measured. This approach provides more accurate and targeted theoretical references for reducing the hazard of regional landslides，and holds significant importance in enhancing the effective defense capability against regional landslide disasters. The study shows that：(1) the evaluation index system for landslide hazard evaluation in Wanzhou District，after removing the topographic relief factor through the test for independence，comprehensively captures the landslide causative factors. (2) Based on the initial grading of evaluation indicators，the final grading of evaluation indicators is achieved using the weights of evidence，landslide area ratio，and grading area，with the support of the weights of evidence method. This approach enables regional landslide hazard evaluation，and the evaluation results are validated through the success rate curve method，with an accuracy of 72%. Therefore，the reliability of evaluation method in this research is reflected through the favorable evaluation precision. (3) The analysis of SW and SI indices reveals that elevation，road distance，and multi-year average rainfall are the top three factors with the highest overall sensitivity and impact on the region for landslide occurrence. However，the remaining factors show variations in their rankings in terms of sensitivity and impact. The difference in the ranking results of evaluation indicators on two indices indicates the necessity and scientificity of the SI index in this study. (4) The HW index indicates that the evaluation factors for high，medium，and low hazard areas exhibit consistent characteristics with the overall regional landslide occurrence. However，in relatively high hazard areas，the road distance factor has the greatest impact. In contrast，in relatively low hazard areas，the normalized vegetation index shows the second-highest impact，indicating the effectiveness and scientific validity of the HW index constructed in this study. (5) The low hazard areas are mainly located in high-altitude regions with higher vegetation coverage. Here，evergreen broad-leaved forests and coniferous forests play a suppressive role in the occurrence of landslides. On the other hand，the high hazard areas are primarily concentrated in the main urban areas of Wanzhou District，where human activities are significant. These areas are distributed along the Yangtze River and its tributaries，with higher precipitation levels concentrated in the low-altitude regions between 1 213 mm to 1 229 mm. For the high hazard areas，it is essential to implement appropriate measures to reduce the landslide hazard，such as undertaking proper landslide control engineering，anti-slide support measures，and slope greening. The implementation of these engineering measures will help mitigate the landslide hazard and achieve the goal of reducing the overall landslide hazard in the region.

Key words： slope engineering landslide hazard evaluation weights of evidence GIS

引用本文:

谢晓1，卢晓宁1，沈文宇1，马启民1，唐云辉2，杨秋萍1，刘明林1，李实康1，夏志业1. 重庆市万州区滑坡灾害危险性评价研究[J]. 岩石力学与工程学报, 2024, 43(S2): 3936-3950.
XIE Xiao1，LU Xiaoning1，SHEN Wenyu1，MA Qimin1，TANG Yunhui2，YANG Qiuping1，LIU Minglin1，LI Shikang1，XIA Zhiye1. Study on landslide hazard evaluation in Wanzhou District，Chongqing. , 2024, 43(S2): 3936-3950.

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https://rockmech.whrsm.ac.cn/CN/10.13722/j.cnki.jrme.2023.0474 或 https://rockmech.whrsm.ac.cn/CN/Y2024/V43/IS2/3936

[1]	卢全中，彭建兵，赵法锁. 地质灾害风险评估(价)研究综述[J]. 灾害学，2003，18(4)：60-64.(LU Quanzhong，PENG Jianbing，ZHAO Fasuo. A review of geological hazard risk assessment(valuation) studies[J]. Journal of Catastrophology，2003，18(4)：60-64.(in Chinese))
[2]	窦杰，向子林，许强，等. 机器学习在滑坡智能防灾减灾中的应用与发展趋势[J]. 地球科学，2023，48(5)：1 657-1 674.(DOU Jie，XIANG Zilin，XU Qiang，et al. Application and development trend of machine learning in landslide intelligent disaster prevention and mitigation[J]. Earth Science，2023，48(5)：1 657-1 674.(in Chinese))
[3]	李媛，孟晖，董颖，等. 中国地质灾害类型及其特征——基于全国县市地质灾害调查成果分析[J]. 中国地质灾害与防治学报，2004，15(2)：32-37.(LI Yuan，MENG Hui，DONG Ying，et al. Main types and characterisitics of geo-hazard in China——Based on the results of geo-hazard survey in 290 counties[J]. The Chinese Journal of Geo-logical Hazard and Control，2004，15(2)：32-37.(in Chinese))
[4]	蒋树，王义锋，刘科，等. 滑坡灾害空间预测方法研究综述[J]. 人民长江，2017，48(21)：67-73.(JIANG Shu，WANG Yifeng，LIU Ke，et al. Review on landslide hazard spatial prediction methods[J]. Yangtze River，2017，48(21)：67-73.(in Chinese))
[5]	吴赛男，田毅. 我国单体滑坡模拟和区域滑坡易发性评价研究进展[J]. 中国地质灾害与防治学报，2019，30(3)：113-119.(WU. Sainan，TIAN Yi. Review on progress of individual landslide simulation and assessment of reginal landslide susceptibility in China[J]. The Chinese Journal of Geological Hazard and Control，2019，30(3)：113-119.(in Chinese))
[6]	张玘恺，凌斯祥，李晓宁，等. 九寨沟县滑坡灾害易发性快速评估模型对比研究[J]. 岩石力学与工程学报，2020，39(8)：1 595-1 610. (ZHANG Qikai，LING Sixiang，LI Xiaoning，et al. Comparison of landslide susceptibility mapping rapid assessment models in Jiuzhaigou County，Sichuan Province，China[J]. Chinese Journal of Rock Mechanics and Engineering，2020，39(8)：1 595-1 610.(in Chinese))
[7]	范强，巨能攀，向喜琼，等. 证据权法在区域滑坡危险性评价中的应用——以贵州省为例[J]. 工程地质学报，2014，22(3)：474-481.(FAN Qiang，JU Nengpan，XIANG Xiqiong，et al. Landslides hazards assessment with weights of evidence ——— a case study in Guizhou，China[J]. Journal of engineering geology，2014，22(3)：474-481.(in Chinese))
[8]	胡燕，李德营，孟颂颂，等. 基于证据权法的巴东县城滑坡灾害易发性评价[J]. 地质科技通报，2020，39(3)：187-194.(HU Yan，LI Deying，MENG Songsong，et al. Landslide susceptibility evaluation in Badong County based on weights of evidence method[J]. Bulletin of Geological Science and Technology，2020，39(3)：187-194.(in Chinese))
[9]	范强，巨能攀，向喜琼，等. 证据权法在滑坡易发性分区中的应用——以贵州桐梓河流域为例[J]. 灾害学，2015，30(1)：124-129.(FAN Qiang，JU Nengpan，XIANG Xiqiong，et al. Landslides susceptibility assessment using weights of evidence in the Tongzi watershed[J]. Journal of Catastrophology，2015，30(1)：124-129.(in Chinese))
[10]	张俊，殷坤龙，王佳佳，等. 三峡库区万州区滑坡灾害易发性评价研究[J]. 岩石力学与工程学报，2016，35(2)：284-296.(ZHANG Jun，YIN Kunlong，WANG Jiajia，et al. Evaluation of landslide susceptibility for Wanzhou district of Three Gorges Reservoir[J]. Chinese Journal of Rock Mechanics and Engineering，2016，35(2)：284-296.(in Chinese))
[11]	侯亚斌. 基于GIS的安徽省地质灾害危险性分区及评价研究[硕士学位论文][D]. 西安：长安大学，2021.(HOU Yabin. Based on GIS Anhui Province geological hazard zoning and assessment[M. S. Thesis][D]. Xi?an：Chang?an University，2021.(in Chinese))
[12]	王佳佳，殷坤龙，肖莉丽. 基于GIS和信息量的滑坡灾害易发性评价——以三峡库区万州区为例[J]. 岩石力学与工程学报，2014，33(4)：797-808.(WANG Jiajia，YIN Kunlong，XIAO Lili. Landslide susceptibility assessment based on GIS and weighted information value：a case study of Wanzhou district，Three Gorges Reservoir[J]. Chinese Journal of Rock Mechanics and Engineering，2014，33(4)：797-808.(in Chinese))
[13]	赵腾跃，何政伟. 基于信息量的金川县斜坡地质灾害易发性评价[J]. 物探化探计算技术，2022，44(2)：203-212.(ZHAO Tengyue，HE Zhengwei. Slope geological hazard susceptibility based on information quantity in Jinchuan county[J]. Computing Techniques for Geophysical and Geochemical Exploration，2022，44(2)：203-212. (in Chinese))
[14]	于淼，邢会歌，胡士瑜. 基于信息量-逻辑回归模型的泥石流易发性评价——以四川省石棉县为例[J]. 人民长江，2021，52(12)：107-114.(YU Miao，XING Huige，HU Shiyu. Debris flow susceptibility assessment based on information value and logistic regression coupled model：Case of Shimian County，Sichuan Province[J]. Yangtze river，2021，52(12)：107-114.(in Chinese))
[15]	郭子正，殷坤龙，付圣，等. 基于GIS与WOE-BP模型的滑坡易发性评价[J]. 地球科学，2019，44(12)：4 299-4 312.(GUO Zizheng，YIN Kunlong，FU Sheng，et al. Evaluation of landslide susceptibility based on GIS and WOE-BP model[J]. Earth Science，2019，44(12)：4 299-4 312.(in Chinese))
[16]	宋渊，江南，张恩博，等. 基于证据权法的湖北省兴山县滑坡灾害易发性评价[J]. 地质与资源，2023，32(3)：352-359.(SONG Yuan，JIANG Nan，ZHANG Enbo，et al. Susceptibility evaluation of landslide hazard in Xingshan county of Hubei province based on weights-of-evidence method [J]. Geology and Resources，2023，32(3)：352-359.(in Chinese))
[17]	孙德亮，马祥龙，唐小娅，等. 基于不同因子分级的滑坡易发性区划对比——以万州区为例[J]. 重庆师范大学学报：自然科学版，2021，38(5)：43-54.(SUN Deliang，MA Xianglong，TANG Xiaoya，et al. Comparison of landslide susceptibility mapping based on different factor classifications Taking Wanzhou district as an example[J]. Journal of Chongqing Normal University：Natural Science，2021，38(5)：43-54.(in Chinese))
[18]	李霞，宿星，张满银，等. 基于证据权法与多源数据的陇中生态脆弱区滑坡敏感性评价——以天水市为例[J]. 冰川冻土，2023，45(1)：67-79.(LI Xia，SU Xing，ZHANG Manyin，et al. Landslide susceptibility using weights-of-evidence approach and multi-source data in Longzhong ecologically vulnerable area：A case study of Tianshui City[J]. Journal of Glaciology and Geocryology，2023，45(1)：67-79.(in Chinese))
[19]	肖婷. 三峡库区万州区及重点库岸段滑坡灾害风险评价[博士学位论文][D]. 武汉：中国地质大学，2020.(XIAO Ting. Landslide risk Assessment in Wanzhou District and a key section，Three Gorges Reservoir[Ph. D. Thesis][D]. Wuhan：China University of Geosciences，2020.(in Chinese))
[20]	裴婵. 基于生态敏感性的万州区景观安全格局构建研究[硕士学位论文][D]. 重庆：西南大学，2021.(PEI Chan. Research on the construction of landscape security pattern in Wanzhou District based on ecological sensitivity[M. S. Thesis][D]. Chongqing：Southwest University，2021.(in Chinese))
[21]	王汉东，黄瓅瑶，朱思蓉，等. 三峡区间面雨量空间插值方法对比分析[J]. 水利信息化，2021，(1)：26-29.(WANG Handong，HUANG Liyao，ZHU Sirong，et al. Intercomparison of area rainfall spatial interpolation in Sanxia Region[J]. Water Resources Informatization. 2021，(1)：26-29.(in Chinese))
[22]	陈宇. 金沙江旭龙水电站近坝区滑坡分形特征及危险性评价[硕士学位论文][D]. 长春：吉林大学，2016.(CHEN Yu. Fractal characteristics of landslide and risk assessment in the near dam region of Xulong hydropower station in Jinsha River[M. S. Thesis][D]. Changchun：Jilin University，2016.(in Chinese))
[23]	侯峰媛. 丽香铁路金沙江大桥峡谷区滑坡危险性分区[硕士学位论文][D]. 成都：西南交通大学，2019.(HOU Fengyuan. The landslide hazard assessment in Jinsha River Grand Bridge Canyon Areas of Lixiang Railway[M. S. Thesis][D]. Chengdu：Southwest Jiaotong University，2019.(in Chinese))
[24]	刘磊，殷坤龙，王佳佳，等. 降雨影响下的区域滑坡危险性动态评价研究——以三峡库区万州主城区为例[J]. 岩石力学与工程学报，2016，35(3)：558-569.(LIU Lei，YIN Kunlong，WANG Jiajia，et al. Dynamic evaluation of regional landslide hazard due to rainfall：a case study in Wanzhou central district，Three Gorges Reservoir[J]. Chinese Journal of Rock Mechanics and Engineering，2016，35(3)：558-569.(in Chinese))
[25]	袁湘秦，赵法锁，段钊. 河流作用诱发黄土滑坡机制[J]. 煤田地质与勘探，2018，46(4)：154-160.(YUAN Xiangqin，ZHAO Fasuo，DUAN Zhao. Mechanism of loess landslide induced by river action[J]. Coal Geology and Exploration，2018，46(4)：154-160.(in Chinese))
[26]	邱海军. 区域滑坡崩塌地质灾害特征分析及其易发性和危险性评价研究————以宁强县为例[博士学位论文][D]. 西安：西北大学，2012.(QIU Haijun. Study on the regional landslide characteristic analysis and hazard assessment：a case study of Ningqiang County[Ph. D. Thesis][D]. Xi?an：Northwest University，2012.(in Chinese))
[27]	夏辉. 三峡库区重庆库段区域滑坡风险评价[硕士学位论文][D]. 武汉：中国地质大学，2018.(XIA Hui. Landslide risk assessment in Chongqing section，Three Gorges Reservoir[M. S. Thesis][D]. Wuhan：China University of Geosciences，2018.(in Chinese))
[28]	王得双. 渭河上游陇西段斜坡灾害易发性评价[硕士学位论文][D]. 兰州：兰州大学，2019.(WANG Deshuang. Slope disasters susceptibility assessment in Longxi section of Weihe River upstream[M. S. Thesis][D]. Lanzhou：Lanzhou University，2019.(in Chinese))
[29]	李牧阳. 考虑植被因素的浅表层滑坡分布及雨量阈值研究——以秦巴山地西段构造强烈区为例[硕士学位论文][D]. 北京：北京林业大学，2021. (Mu Yang Li. Study on shallow landslides distribution and rainfall threshold considering vegetation factors—example of strong tectonic area in the Western Qinba Mountains[M. S. Thesis][D]. Beijing：Beijing Forestry University，2021.(in Chinese))
[30]	张钟远，邓明国，徐世光，等. 镇康县滑坡易发性评价模型对比研究[J]. 岩石力学与工程学报，2022，41(1)：157-171.(ZHANG Zhongyuan，DENG Mingguo，XU Shiguang，et al. Comparison of landslide susceptibility assessment models in Zhenkang County，Yunnan Province，China[J]. Chinese Journal of Rock Mechanics and Engineering，2022，41(1)：157-171.(in Chinese))
[31]	楚敬龙，杜加强，滕彦国，等. 基于GIS的重庆市万州区滑坡灾害危险性评价[J]. 地质通报，2008，27(11)：1 875-1 881.(CHU Jinglong，DU Jiaqiang，TENG Yanguo，et al. Landslide hazard evaluation for Wanzhou District，Chongqing City，China，using GIS[J]. Geological bulletin of China，2008，27(11)：1 875-1 881.(in Chinese))
[32]	孙晓倩，刘飞，闫士民，等. 徐州市某土质边坡稳定性评价与防治[J]. 能源技术与管理，2023，48(1)：119-121.(SUN Xiaoqian，LIU Fei，YAN Shimin，et al. Stability evaluation and prevention of a soil slope in Xuzhou city[J]. Energy Technology and Management，2023，48(1)：119-121.(in Chinese))
[33]	林炫歆，肖桂荣，周侯伯. 顾及土地利用动态变化的滑坡易发性评估方法[J]. 地球信息科学学报，2023，25(5)：953-966.(LIN Xuanxin，XIAO Guirong，ZHOU Houbo. Landslide susceptibility assessment method considering land use dynamic change[J]. Journal of Geo-Information Science，2023，25(5)：953-966.(in Chinese))
[34]	朱赛楠，魏英娟，王平，等. 大型单斜层状基岩滑坡变形特征与失稳机制研究——以重庆石柱县龙井滑坡为例[J]. 岩石力学与工程学报，2021，40(4)：739-750.(ZHU Sainan，WEI Yingjuan，WANG Ping，et al. Research on deformation characteristics and instability mechanisms of large monoclinal layered bedrock landslides：A case study of the Longjing landslide in Shizhu county，Chongqing[J]. Chinese Journal of Rock Mechanics and Engineering，2021，40(4)：739-750.(in Chinese))
[35]	张洪岩. 深圳市罗湖建成区地质灾害特征及防治对策[J]. 绿色科技，2021，23(12)：182-186.(ZHANG Hongyan. Geological disaster characteristics and prevention countermeasures in Luohu Built-up area of Shenzhen city[J]. Journal of Green Science and Technology，2021，23(12)：182-186.(in Chinese))
[36]	李祎博. 公路边坡根土复合体力学性能及护坡作用研究[博士学位论文][D]. 哈尔滨：东北林业大学，2023.(LI Weibo. Study on the mechanical properties and slope protection of root-soil complex at highway slope [Ph. D. Thesis][D]. Harbin：Northeast Forestry University，2023.(in Chinese))
[37]	姚鑫，许冲，戴福初，等. 四川汶川Ms 8级地震引发的滑坡与地层岩性、坡度的相关性[J]. 地质通报，2009，28(8)：1 156-1 162. (YAO Xin，XU Chong，DAI Fuchu，et al. Contribution of strata lithology and slope gradient to landslides triggered by Wenchuan Ms 8 earthquake，Sichuan，China[J]. Geological Bulletin of China，2009，28(8)：1 156-1 162.(in Chinese))
[38]	王佳佳. 三峡库区万州区滑坡灾害风险评估研究[博士学位论文][D]. 武汉：中国地质大学，2015.(WANG Jiajia. Landslide risk assessment in Wanzhou County，Three Gorges Reservoir[Ph. D. Thesis][D]. Wuhan：China University of Geosciences，2015.(in Chinese))
[39]	张庆飞，冯宇凇，吕改杰，等. 基于数值模拟的含软弱夹层高边坡稳定性分析[J]. 山西建筑，2021，47(21)：9-11.(ZHANG Qingfei，FENG Yusong，LV Gaijie，et al. Stability analysis of high slopes with weak interlayer based on numerical simulation[J]. Shanxi Architecture，2021，47(21)：9-11.(in Chinese))