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《Journal of Fudan University(Natural Science)》 2018-02
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Studies on the Influencing Factors and Multiple Regression Model of Urban Waterlogging Based on GIS——A Case of Shanghai,China

XU Yiyang;LI Kun;XIE Yujing;LING Huanran;QIAN Minlei;WANG Xiangrong;LU Yi;Department of Environmental Science and Engineering,Fudan University;Forrin Technology (Shanghai)Co.,Ltd.;Yushan Xingfu Management District,Changshu;  
Flooding and waterlogging have become one of the optimal-related disasters and one of the most sensitive issues in the world,while global climate change has led to an increase in extreme events.By taking the city of Shanghai,China as an example,the influencing factors and multiple regression model of urban waterlogging were studied in this paper,based on GIS techniques and modeling methods.The historical data and GIS spatial analysis,precipitation,urban construction lands expansion,population distribution,digital elevation model(DEM),infrastructure drainability and other factors were analyzed in the study to carry out a conclusion of the impacts of these factors on rainstorm waterlogging in downtown Shanghai.Meanwhile a multiple logistic regression model was constructed based on the scikit-learn machine learning module in Python,which was used to judge the occurrence of flood-waterlog according to the above factors,and the accuracy rate was above 90%.The results showed that the DEM,impervious surface distribution and population distribution of downtown in Shanghai significantly affect the incidence of rainstorm waterlogging.
【Fund】: 国家社科基金重大项目(14ZDB140);国家社科基金重点项目(13AZD075);; “十三五”国家重点研发计划项目(2016YFC0502700)
【CateGory Index】: P208;TU992
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