水科学进展2025，Vol.36Issue(4)：566-580,15.DOI:10.14042/j.cnki.32.1309.2025.04.003
基于社交媒体大数据的城市洪涝识别与模拟验证
Urban flood identification with simulation validation based on social media big data
摘要
Abstract
The insufficient reliability of conventional monitoring methods under extreme rainfall conditions has resulted in an urgent need for new monitoring methods This study proposes an urban flood identification method that uses crawler technology(BeautifulSoup4)to extract flood-related terms from social media big data.The geographic information of water accumulation points was identified by combining BERT(Bidirectional Encoder Representations from Transformers)and CRF(Conditional Random Field)named entity recognition technology.Considering the extreme rainstorm and flood disaster in Zhengzhou on July 20,2021 as an example,the accuracy of the identification method was verified by comparing it with the spatial distribution of the investigated water accumulation points and the numerical simulation of urban flooding.Results showed that the spatial distribution of the water accumulation points identified based on social media big data was basically consistent with that of the investigated water accumulation points,with a spatial overlap rate of 89.4%.Among the identified water accumulation points with spatial overlap,the proportions of water depths(H)proportions of 30≤H＜50,50≤H＜100,100≤H＜200,200≤H＜300 and H≥300 cm were 49.6%,36.8%,8.2%,4.1%and 1.3%,respectively.The simulation results of the 50-year and 100-year design rainfall scenarios,as well as the measured rainfall scenarios on August 1,2019,and July 22,2024,demonstrate the rationality of the identification results in terms of spatial trends.Urban flood monitoring inversion based on social media big data is an important supplement to flood monitoring under extreme conditions and can be used as a crucial data support for validating numerical simulations on urban floods and emergency decision-making during flood disasters.关键词
城市洪涝模拟/洪涝识别/社交媒体大数据/命名体识别Key words
urban flood simulation/flood identification/social media big data/named entity recognition分类
建筑与水利引用本文复制引用
张克寒,梅超,刘家宏,王佳,宋天旭,石虹远..基于社交媒体大数据的城市洪涝识别与模拟验证[J].水科学进展,2025,36(4):566-580,15.基金项目
国家重点研发计划项目(2022YFC3090600 （）
2022YFE0205200)The study is financially supported by the National Key R&D Program of China(No.2022YFC3090600 （）
No.2022YFE0205200). （）
