基于二元Logistic对城市内涝风险区预测研究

Research on the Prediction of Urban Waterlogging Risk Area Based on Binary Logistic

在气候变化和快速城市化背景下,城市内涝已经成为一种“城市病”。为了识别内涝风险区及预测研究,从城市空间因素的角度,以北京城六区作为研究区域,收集整理内涝信息和城市空间因素数据。采用二元Logistic回归分析,探究内涝风险区的特点,得出影响内涝的主要城市空间因素依次为汛期降雨量、综合径流系数、高速路网、雨水排放系统及涝点与桥梁的距离,并建立城六区内涝风险区预测模型,使用网络积水地图的积水点进行验证,结果表明预测模型结果准确,在现实中暴雨天气可以根据预测模型在高风险地区或是内涝发生高概率区域地点做好内涝防治措施。

Under the background of climate change and rapid urbanization,urban waterlogging has become an“urban disease”.For identifying waterlogging risk area and prediction research,this paper explores the characteristics of waterlogging risk area,the main urban space factors affecting the waterlogging of flood season rainfall,runoff coefficient,highway system,drainage system and flood point distance and bridge from the perspectives of urban space factors,six areas as the study area,north of the capital collected waterlogging data information and the urban space factors,the binary logistic regression analysis,and waterlogging risk area prediction model is established by using the network map of water of water points for validation,results show that the prediction model is correct.In reality,rainstorm weather can be based on the forecast model in high-risk areas or areas with high probability of waterlogging prevention and control measures.