Contribution Rate and Susceptibility Evaluation of Influencing Factors of Consequent Bedding Rock Landslides Development in Daba Mountain Area

Yi Jingsong; Zhang Yong; Cheng Yingjian; Miao Zhao

doi:10.13961/j.cnki.stbctb.2019.04.043

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Contribution Rate and Susceptibility Evaluation of Influencing Factors of Consequent Bedding Rock Landslides Development in Daba Mountain Area

- Contribution Rate and Susceptibility Evaluation of Influencing Factors of Consequent Bedding Rock Landslides Development in Daba Mountain Area
- Bulletin of Soiland Water Conservation Vol. 39, Issue 4, Pages: 275-280(2019)
- 作者机构：
  
  中国地质科学院探矿工艺研究所/中国地质调查局地质灾害防治技术中心,四川,成都,611734
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2019.04.043
  CLC： P642.22
- Published：2019
- 稿件说明：
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Yi Jingsong, Zhang Yong, Cheng Yingjian, et al. Contribution Rate and Susceptibility Evaluation of Influencing Factors of Consequent Bedding Rock Landslides Development in Daba Mountain Area[J]. Bulletin of Soiland Water Conservation, 2019, 39(4): 275-280.
DOI：

Yi Jingsong, Zhang Yong, Cheng Yingjian, et al. Contribution Rate and Susceptibility Evaluation of Influencing Factors of Consequent Bedding Rock Landslides Development in Daba Mountain Area[J]. Bulletin of Soiland Water Conservation, 2019, 39(4): 275-280. DOI： 10.13961/j.cnki.stbctb.2019.04.043.

摘要

[目的]顺层岩质滑坡是大巴山区极其发育的一类灾害，通过对其发育影响因素的贡献率及易发性评价研究，构建预测评价模型，为该区防灾预灾工作提供科学支撑。[方法]基于GIS和数量化理论Ⅱ，选取21个研究区基岩顺层滑坡的样本，利用GIS技术提取高程、坡度、斜坡结构等9个影响因素的基础数据，通过数量化理论计算方法对学习样本进行学习，确定各因子类目得分，得到各项基础数据的易发性评价系数，然后通过GIS将各图层叠加，进行全范围的易发性预测。[结果]对滑坡贡献率较高的影响因素有：斜坡坡度约10°~20°，顺向坡斜坡结构、砂质硬岩夹软岩的岩体结构、汇流面积，水流冲蚀；基于数量化理论Ⅱ建立的易发性预测方法可以较准确地划分区域易发性的高低。[结论]位于大巴山区的南江县南部、巴州区北部、苍溪县南东部、宣汉县南西侧地等区域为顺层岩质滑坡的高易发区，这也与调查结果相符，GIS和数量化理论Ⅱ相结合的滑坡易发性预测方法适用于该地区滑坡易发性、危险性等相关领域的研究。

Abstract

[Objective] Bedding rock landslide is one of the most developed disasters in daba mountain areas. A prediction evaluation model is constructed to provide scientific support for disaster prevention and pre-disaster work in this area

by studying the contribution rate and vulnerability of its development factors.[Methods] This paper selects the sample of 21 bedrock bedding landslides in the study area

and the basic data of nine influencing factors such as elevation

slope and slope structure were extracted by GIS technology. The samples were calculated by quantitative theoretical calculation methods to determine the category score of the factors

and then evaluates the whole range.[Results] The factors affecting the high contribution rate of landslide are:slope around 10°~20°

beding slope structure

rock mass structure of sandy hard rock with soft rock

confluence area

water erosion; The susceptibility prediction method established by quantitative theory Ⅱ can accurately divide the regional susceptibility.[Conclusion] The landslide susceptibility prediction method combined with GIS and quantitative theory Ⅱ is suitable for the study of landslide susceptibility and risk in this area.

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