基于CF模型的斜坡地质灾害孕灾因子敏感性分析——以湖南省新宁县为例

doi:10.19388/j.zgdzdc.2023.04.13

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摘要在不同的区域及地质背景下,斜坡地质灾害的主控因子及其影响程度各不相同,分析孕灾因子的敏感性,有利于提高斜坡地质灾害预测的准确性。在资料收集和实地调查工作的基础上,选取了坡度、高程、剖面曲率、地层、斜坡结构、断裂、河流和归一化植被指数(normalized difference vegetation index,NDVI)共8个因子作为斜坡地质灾害的孕灾因子; 基于GIS平台,采用确定性系数(certainty factor, CF)模型进行敏感性分析,并通过敏感性指数评价各因子的敏感性大小并划分敏感性分区。结果表明: 坡度≥40°、高程[600,700 m)、剖面曲率≥0.6、三叠系和二叠系、顺向坡、距断层距离[0,500) m、距河流距离[0,200) m以及NDVI为[0.233, 0.595)最容易发生灾害,由高到底划分为极高、高、中、低和极低5个敏感区,同时采用2020—2021年的灾害数据进行了验证,87.50%的灾害位于高敏感区和极高敏感区内,证实了敏感性分析的合理性。研究成果为下一步风险评价工作奠定了基础,为防灾减灾工作提供了参考,也可为湖南省其他县区提供借鉴。

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	刘中楠
	高银梅
	姜河
	黄勇炜
	丁华栋
	颜智强

关键词 ：斜坡地质灾害, 孕灾因子, CF模型, 敏感性分析, 新宁县

Abstract：The main controlling factors of slope geological hazards and their influence degrees are different in different regions and geological backgrounds. Analyzing the sensitivity of hazard inducing factors is beneficial to improve the accuracy of slope geological hazards prediction. On the basis of data collection and field investigation, the authors in this research selected eight factors, including slope, elevation, profile curvature, stratum, geolo-gical time, slope structure, fault, river and normalized difference vegetation index (NDVI), as the inducing factors of slope geological hazards. The sensitivity analysis is conducted by the certainty factor (CF) model based on GIS platform, and the sensitivity index was used to analyze the sensitivity of each factor and divide the sensitivity zones. The results show that areas with the most prone to disasters included characteristics of slope ≥40°, elevation [600,700) m, profile curvature ≥0.6, Triassic and Permian, along slope, [0, 500) m from the fault, [0, 200) m from the river and NDVI between [0.233, 0.595). The sensitivity was divided into five sensitive zones, namely extremely high, high, medium, low and extremely low. At the same time, the disaster data from 2020 to 2021 were used to verify that 87.50% of the disasters were located in extremely high and high sensitive areas, verifying the rationality of this study. The research results lay a foundation for the next step of risk assessment, and provide a reference for disaster prevention and for other counties and districts in Hunan Province.

Key words： slope geological disaster hazards inducing factors CF model sensitivity analysis Xinning County

收稿日期: 2022-12-01

中图分类号:

P694

基金资助:中央财政项目“湖南省宁县1∶10 000地质灾害调查和风险评价(编号: 2022430032)”资助

作者简介: 刘中楠(1992—),男,工程师,主要从事地质灾害调查及研究工作。Email: 443149421@qq.com。

引用本文:

刘中楠, 高银梅, 姜河, 黄勇炜, 丁华栋, 颜智强. 基于CF模型的斜坡地质灾害孕灾因子敏感性分析——以湖南省新宁县为例[J]. 中国地质调查, 2023, 10(4): 107-115.
LIU Zhongnan, GAO Yinmei, JIANG He, HUANG Yongwei, DING Huadong, YAN Zhiqiang. Sensitivity analysis of inducing factors of slope geological hazards based on CF Model: A case study of Xinning County in Hunan Province. , 2023, 10(4): 107-115.

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