地球科学进展 ›› 2020, Vol. 35 ›› Issue (10): 1064 -1072. doi: 10.11867/j.issn.1001-8166.2020.082

研究论文 上一篇    下一篇

基于 GISLogistic回归模型的洪涝灾害区划研究
王鹏( ),邓红卫( )   
  1. 中南大学 资源与安全工程学院,湖南 长沙 410083
  • 收稿日期:2020-08-04 修回日期:2020-09-18 出版日期:2020-10-10
  • 通讯作者: 邓红卫 E-mail:1170310531@qq.com;denghw208@126.com
  • 基金资助:
    国家自然科学基金项目“寒区岩质散体冻胀裂解孕育排土场灾变机理及干预机制研究”(51874352);中南大学研究生自主探索创新项目“GIS视域下湘江长沙—株洲河段水环境承载力分析研究”(2019zzts992)

Study on Flood Hazard Risk Zoning Based on GIS and Logistic Regression Model

Peng Wang( ),Hongwei Deng( )   

  1. School of Resources and Safety Engineering,Central South University,Changsha 410083,China
  • Received:2020-08-04 Revised:2020-09-18 Online:2020-10-10 Published:2020-11-30
  • Contact: Hongwei Deng E-mail:1170310531@qq.com;denghw208@126.com
  • About author:Wang Peng (1995-), male, Enshi City, Hubei Province, Master student. Research areas include water resources carrying capacity and water disaster prevention. E-mail: 1170310531@qq.com
  • Supported by:
    the National Natural Science Foundation of China “Study on the atastrophic mechanism and intervention mechanism of frost heave cracking of broken rocks in cold regions”(51874352);The Independent Exploration and Innovation Project for Graduate Students of Central South University “Analysis and research on water environmental carrying capacity of Xiang River from Changsha to Zhuzhou under GIS”(2019zzts992)

洪涝灾害危险性区划对于洪涝灾害的控制和预防具有重要的意义。以汉江湖北河段沿线为例,在构建洪涝灾害危险性评价指标体系基础上,利用ArcGIS将各项评价指标进行归一化处理,建立研究区的格网并与历史灾害点相连接,得到每个网格内各项评价指标的数据和相应的灾害发生情况。然后,根据二元Logistic回归原理,利用SPSS进行二元逻辑回归分析,从而得出各评价指标与洪涝发生情况的关联性。在此基础上,应用Logistic回归模型确定的危险性概率计算方法,在ArcGIS中绘制研究区的洪涝灾害危险性区划图。将洪涝灾害危险性划分为高危险区、较高危险区、中等危险区、较低危险区和低危险区5个等级,各风险区面积占比依次为8.3%、12.5%、20.6%、19.2%和39.4%。

The flood hazard risk zonation is of great importance to the control and prevention of flood disaster. Taking the catchment area along Han River in Hubei Province as an example, based on the flood hazard risk evaluation index system, ArcGIS was used to normalize each evaluation index. The grid of the research area connected with the historical flood disaster point was accordingly established in order to obtain the statistics of each evaluation index and the corresponding disaster occurrences in each grid. Afterwards, according to the binary Logistic regression principle, SPSS was used for binary logistic regression analysis, so as to obtain the correlation between each evaluation index and the occurrence of flood disaster. On the basis of the above, the risk probability calculation method of Logistic regression model was applied to draw the flood hazard zoning map of the study area in ArcGIS. The results showed that flood hazard risk in the study area coexisted with the two aggregation modes of high and low value. And flood hazard risk was divided into five levels: The highest, higher, moderate, lower and the lowest regions. The area proportion of each risk region was 8.3%, 12.5%, 20.6%, 19.2% and 39.4%, respectively.

中图分类号: 

图1 汉江在湖北省境内河段的示意图
Fig.1 Map showing the study area of the Han River in Hubei Province
图2 洪涝灾害危险性评价指标体系
Fig.2 Risk assessment index system of flood disaster
图3 洪涝灾害危险性评价因子分布图
Fig.3 Distribution map of risk assessment factors of flood disaster
表1 水系缓冲赋值标准
Table 1 Water system buffer assignment criteria
表2 Logistic回归分析结果输出表
Table 2 Output table of Logistic regression analysis results
表3 ROC分析曲线输出表
Table 3 ROC analysis curve output table
图4 受试者工作特征曲线
Fig.4 Receiver operating characteristic curve
图5 洪涝灾害危险性概率(a)及区划(b)图
Fig.5 Probabilityaand zoningbof flood hazard
表4 研究区洪水灾害危险性区划
Table 4 Study area flood hazard zoning
表5 县市内各洪灾风险区面积百分比 (%)
Table 5 Percentage of flood risk areas in county and city
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