周秀全, 黄海波, 郑宁, 施晓旺. 基于层次分析法的水库蓄水后滑坡易发性评价[J]. 地质与资源, 2022, 31(6): 804-810. DOI: 10.13686/j.cnki.dzyzy.2022.06.013
    引用本文: 周秀全, 黄海波, 郑宁, 施晓旺. 基于层次分析法的水库蓄水后滑坡易发性评价[J]. 地质与资源, 2022, 31(6): 804-810. DOI: 10.13686/j.cnki.dzyzy.2022.06.013
    ZHOU Xiu-quan, HUANG Hai-bo, ZHENG Ning, SHI Xiao-wang. SUSCEPTIBILITY ASSESSMENT OF LANDSLIDE AFTER RESERVOIR IMPOUNDMENT BASED ON ANALYTIC HIERARCHY PROCESS[J]. Geology and Resources, 2022, 31(6): 804-810. DOI: 10.13686/j.cnki.dzyzy.2022.06.013
    Citation: ZHOU Xiu-quan, HUANG Hai-bo, ZHENG Ning, SHI Xiao-wang. SUSCEPTIBILITY ASSESSMENT OF LANDSLIDE AFTER RESERVOIR IMPOUNDMENT BASED ON ANALYTIC HIERARCHY PROCESS[J]. Geology and Resources, 2022, 31(6): 804-810. DOI: 10.13686/j.cnki.dzyzy.2022.06.013

    基于层次分析法的水库蓄水后滑坡易发性评价

    SUSCEPTIBILITY ASSESSMENT OF LANDSLIDE AFTER RESERVOIR IMPOUNDMENT BASED ON ANALYTIC HIERARCHY PROCESS

    • 摘要: 水库库区地形地质和水位地质条件复杂, 蓄水后受降雨和库水位变动影响容易产生滑坡、崩塌等次生地质灾害, 严重威胁水库安全运行和附近居民安全. 本文依托层次分析法, 以某蓄水水库为研究对象, 在充分收集其地形地质和水文条件资料的基础上, 选取地形地貌、地层岩性、坡度、坡向、地灾点密度、地灾点面积、降雨、库水变动幅度和地震强度等9个致滑因子, 构建评价矩阵和滑坡危险性计算评价方法. 依据评价成果划分4个滑坡危险性等级, 借助MapGIS软件生成库区潜在滑坡危险性分区图. 该分区图与遥感解译的库区滑坡体分布点高度吻合, 验证了评价模型的合理性.

       

      Abstract: Reservoir areas are prone to secondary geological disasters such as landslides and collapses due to complex geological conditions involving topography and water level, which seriously threatens the safety of reservoirs and nearby residents. Taking a certain impoundment reservoir as the research object, 9 sliding factors including landform, stratum lithology, slope gradient, aspect, density and area of geohazard sites, precipitation, water storage variation and earthquake intensity are selected to construct the evaluation matrix and landslide risk calculation method on the basis of adequate data collection of topographic and hydrological conditions through analytic hierarchy process(AHP). Four landslide risk grades are divided according to the evaluation results, which then generate the potential landslide risk zoning map of the reservoir area by MapGIS. The zonation coincides highly with the distribution of landslide bodies interpreted by remote sensing, which proves that the evaluation model is effective.

       

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