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陈玉敏、硕士生方涛的论文在WATER刊出
发布时间:2019-12-11 16:28:07     发布者:易真     浏览次数:

标题: Flood Risk Evaluation in the Middle Reaches of the Yangtze River Based on Eigenvector Spatial Filtering Poisson Regression

作者: Fang, T (Fang, Tao); Chen, YM (Chen, Yumin); Tan, HY (Tan, Huangyuan); Cao, JP (Cao, Jiping); Liao, JX (Liao, Jiaxin); Huang, LH (Huang, Liheng)

来源出版物: WATER  : 11  : 10  文献号: 1969  DOI: 10.3390/w11101969  出版年: OCT 2019  

摘要: A Poisson regression based on eigenvector spatial filtering (ESF) is proposed to evaluate the flood risk in the middle reaches of the Yangtze River in China. Regression analysis is employed to model the relationship between the frequency of flood alarming events observed by hydrological stations and hazard-causing factors from 2005 to 2012. Eight factors, including elevation (ELE), slope (SLO), elevation standard deviation (ESD), river density (DEN), distance to mainstream (DIST), NDVI, annual mean rainfall (RAIN), mean annual maximum of three-day accumulated precipitation (ACC) and frequency of extreme rainfall (EXE) are selected and integrated into a GIS environment for the identification of flood-prone basins. ESF-based Poisson regression (ESFPS) can filter out the spatial autocorrelation. The methodology includes construction of a spatial weight matrix, testing of spatial autocorrelation, decomposition of eigenvectors, stepwise selection of eigenvectors and calculation of regression coefficients. Compared with the pseudo R squared obtained by PS (0.56), ESFPS exhibits better fitness with a value of 0.78, which increases by approximately 39.3%. ESFPS identifies six significant factors including ELE, DEN, EXE, DIST, ACC and NDVI, in which ACC and NDVI are the first two main factors. The method can provide decision support for flood risk relief and hydrologic station planning.

入藏号: WOS:000495598400014

语言: English

文献类型: Article

作者关键词: spatial autocorrelation; Poisson regression; eigenvector spatial filtering method; flood risk evaluation

地址: [Fang, Tao; Chen, Yumin; Tan, Huangyuan; Cao, Jiping; Liao, Jiaxin; Huang, Liheng] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China.

通讯作者地址: Chen, YM (通讯作者)Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China.

电子邮件地址: fountaintop@whu.edu.cn; ymchen@whu.edu.cn; tanhuangyuan@whu.edu.cn; caojiping@whu.edu.cn; 2018282050169@whu.edu.cn; 2014301110077@whu.edu.cn

影响因子:2.524


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