长江科学院院报 ›› 2017, Vol. 34 ›› Issue (12): 38-43.DOI: 10.11988/ckyyb.20160889

• 工程安全与灾害防治 • 上一篇    下一篇

基于核密度估计与VaR的甘肃黑方台地区滑坡影响范围估计模型

李骅锦1, 许强1, 何雨森2   

  1. 1.成都理工大学 地质灾害防治与环境保护国家重点实验室,成都 610059;
    2.爱荷华大学 智能系统研究实验室,美国 爱荷华州 爱荷华城 52242
  • 收稿日期:2016-08-31 出版日期:2017-12-01 发布日期:2017-12-22
  • 作者简介:李骅锦(1991-),男,四川达州人,硕士研究生,主要从事地质灾害预测评价方面的研究,(电话)18782959226(电子信箱)286069283@qq.com。
  • 基金资助:
    国家重点基础研究发展计划项目(2014CB744703);国家杰出青年科学基金项目(41225011)

A New Methodology of Landslide Hazard Mappingby Kernel Density Estimation and Value-at-RiskMeasurement in Heifangtai Area,Gansu Province of China

LI Hua-jin1, XU Qiang1, HE Yu-sen2   

  1. 1.State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China;
    2. Intelligent Systems Laboratory, Seamans Center, Mechanical and Industrial Engineering, The University of Iowa, Iowa City 52242, U.S.A.
  • Received:2016-08-31 Online:2017-12-01 Published:2017-12-22

摘要: 滑坡影响的范围主要根据滑坡滑动距离来确定,现阶段的研究空间仍较大。以甘肃黑方台地区所有滑坡的滑动距离作为整体样本,根据研究区实际情况,将滑坡群分为Ⅰ段、Ⅱ段、Ⅲ段、Ⅳ段、Ⅴ段和Ⅵ段;基于核密度估计模型与Value-at-Risk(VaR)模型对研究区滑坡影响范围展开分析。结果表明:MISE窗宽值为68.723 8的核密度估计能较好地表述整体样本的概率分布规律;VaR模型计算得到了符合滑坡分段实情的滑坡风险滑动距离值(DR);结合分区实际情况,可在Ⅰ段、Ⅱ段、Ⅲ段和Ⅵ段的滑坡底部DR处修建简易牢固拦挡措施,以及基于Ⅳ段和Ⅴ段的黄土滑坡样本研究滑坡滑带部位含水量与滑动距离的关系。该模型具有良好的理论基础及应用前景,能在该领域发挥一定积极作用。

关键词: 滑坡影响范围, 核密度估计, VaR模型, 滑坡风险滑动距离, 风险度量滑动距离

Abstract: Hazard mapping is a prevailing part of spatial analysis of landslides. Previous researches use runout distances to map the hazard ranges. In this paper, we present an improved methodology by using the dataset that contains all runout distances of landslide locations in Heifangtai area. According to the runout distances, the landslide locations are categorized into six groups. For each group, the kernel density estimation and Value-at-Risk (VaR) measurement are conducted for statistical modeling. Statistical results indicate a kernel density with MISE=68.7238 fit the probability distributions of runout distances best. Furthermore, for each group, hazards are mapped according to the runout distances at different levels of risks (DR). According to the experimental results, a preventive construction measure is proposed in the location computed as DR for Groups I, II, III and VI. Meanwhile, the correlation between moisture content and runout distance in Group IV and V is derived by further numerical analysis.

Key words: hazard mapping, Kernel density estimation, Value-at-Risk, runout distance of landslide, Value-at-Risk measurements of runout distances

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