针对暴雨导致的城市内涝问题,首先基于地理信息系统(Geographic Information System,GIS)的空间数据提取能力,对组成排水系统的排水管网、道路和河道水系等进行合理概化,并利用雨水管理模型(Storm Water Management Model,SWMM)对概化后的城市排水系统进行雨洪过程模拟;其次将从爬虫软件获取的社交媒体数据与模型模拟结果对比,以验证城市雨洪模型的模拟效果;最后利用该城市雨洪模型分别模拟了四个不同重现期的设计暴雨情形下内涝点的空间分布.结果表明:社交媒体数据可以为城市雨洪模型的模拟效果提供新的验证方法.随着降雨重现期的增加,内涝点数量和积水量逐渐增加.四个重现期的暴雨内涝点空间分布表明深圳市龙岗区坂田街道的内涝点主要分布在西北部和南部,并随降雨重现期的增加逐渐呈现均匀分布.
Abstract
Urban waterlogging induced by heavy rainstorms poses significant challenges for hydrologists and policymakers.Here,we generalize the urban drainage system and simulate rainstorms and waterlogging disasters based on the spatial data extraction capability of the Geographic Information System(GIS)and the Storm Water Management Model(SWMM).The simulation results are validated by comparing them with waterlogging observations extracted from social media platforms(e.g.,Weibo)using web scraping techniques.Under different return periods,spatial patterns of urban waterlogging sites induced by rainstorms are simulated,indicating that waterlogging sites are mainly located in the north-west and south of Bantian Street.Spatial analysis of the four return periods shows that waterlogging in Bantian Street,Longgang District,Shenzhen,is primarily concentrated in the northwest and southern areas,and this distribution becomes more uniform as the return period increases.The GIS-SWMM model is thus a powerful tool for the prediction of urban rainstorms and waterlogging disasters and the evaluation of their spatial patterns.
关键词
雨水管理模型/城市内涝/社交媒体数据
Key words
SWMM(Storm Water Management Model)/urban waterlogging/social media
万方数据