刘艳辉, 张振兴, 苏永超. 2018: 地质灾害承灾载体脆弱性评价方法研究. 工程地质学报, 26(5): 1121-1130. DOI: 10.13544/j.cnki.jeg.2017-560
    引用本文: 刘艳辉, 张振兴, 苏永超. 2018: 地质灾害承灾载体脆弱性评价方法研究. 工程地质学报, 26(5): 1121-1130. DOI: 10.13544/j.cnki.jeg.2017-560
    LIU Yanhui, ZHANG Zhenxing, SU Yongchao. 2018: CASE STUDY OF VULNERABILITY EVALUATION FOR GEO-HAZARDS BEARING CAPACITY OF A REGION. JOURNAL OF ENGINEERING GEOLOGY, 26(5): 1121-1130. DOI: 10.13544/j.cnki.jeg.2017-560
    Citation: LIU Yanhui, ZHANG Zhenxing, SU Yongchao. 2018: CASE STUDY OF VULNERABILITY EVALUATION FOR GEO-HAZARDS BEARING CAPACITY OF A REGION. JOURNAL OF ENGINEERING GEOLOGY, 26(5): 1121-1130. DOI: 10.13544/j.cnki.jeg.2017-560

    地质灾害承灾载体脆弱性评价方法研究

    CASE STUDY OF VULNERABILITY EVALUATION FOR GEO-HAZARDS BEARING CAPACITY OF A REGION

    • 摘要: 中国地质灾害严重,地质灾害承灾载体的脆弱性直接决定着灾害造成损失的严重程度,开展脆弱性定量评价方法研究具有重要意义。(1)本文构建了地质灾害承灾载体脆弱性评价指标体系,包括4个一级指标和19个二级指标。一级指标包括生命类、物质类、生态环境类和社会经济类指标。(2)以青川县为例,分别采用TOPSIS模型和加权求和模型,分别以乡镇单元和行政村单元为最小单元,开展了地质灾害承灾载体脆弱性评价,将青川县承灾载体脆弱性分为高、较高、中等、较低和低5个脆弱性等级。(3)两种模型评价结果对比显示,总体一致性较好,73%的区域脆弱性结果完全一致,27%的区域存在一个等级的差别;高、低脆弱性等级区两种模型结果一致,吻合度100%;较高和中等脆弱性等级区两种模型结果吻合度分别为86%和73%;较低脆弱性区两种模型结果吻合度略差,为54%。(4)两种单元评价结果对比显示,在总体规律上保持了较好的一致性。半数以上的乡镇单元与行政村单元脆弱性等级完全相同或总体一致;以行政村为评价单元的评价结果明显更加精细,原因在于不同行政村的各类指标值具有明显的差异性,而乡镇单元消除了各个行政村之间的差异。

       

      Abstract: Geological hazards lead to great threatens in China. The vulnerability of geo-hazards bearing capacity directly determines the severe of geological disasters. Its corresponding quantitative assessment of vulnerability is very importance. This paper presents the index system of the vulnerability for geo-hazards bearing capacity. The system includes four indexes and nineteen sub-indexes. The four indexes are life index, material index, ecological environment index and social economy index. A case study is performed in Qingchuan County, China. The township units and administrative village units are used as the basic unit in GIS. Both TOPSIS model and Weighted Sum model are adopted to evaluate the vulnerability of geo-hazards bearing capacity in this area. Five vulnerability levels are classified and include high vulnerability level, relatively high vulnerability level, moderate vulnerability level, relatively low vulnerability level, and low vulnerability level. Comparative study of these two models indicates that the results derived from the two models are consistent as a whole. 73 percent of the area has the same vulnerability level. The rest 27 percent area differs with a gap of one vulnerability level. In the areas of high, low vulnerability levels derived by the two models are quite consistent with each other. The agreements between two models in relatively high and medium level are 86% and 73%respectively, while in relatively low vulnerability level was slightly worse(54%). An evaluated comparison of township unit and administrative village unit presents the good consistency at the whole. Approximately above half level of vulnerability of two units are exact the same or general same. The evaluation results of administrative villages are apparently more accurate. The reason is that there are obvious differences among various administrative villages in their index values, while the township standard eliminates the differences among administrative villages.

       

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