How Many Floods Have Occurred in China in the Past Decade? A Perspective From Social Media

Abstract Global climate change has led to frequent and widespread flood disasters in China. Traditional flood disaster investigations mainly focus on major flood events, and small‐scale flood events are often overlooked. This study utilized the Sina Weibo social media platform to detect flood events in 370 cities in China from 2012 to 2023. We downloaded 73.52 million Weibo posts and developed a two‐step flood detection algorithm. In the first step, the algorithm initially identifies 956 flood events based on changes in posting frequency. In the second step, an LDA topic model is used to detect topics for these flood events and automatically filter out false events, resulting in 729 flood events. Verification of these events confirmed that 629 of the 729 were real flood events, achieving a detection accuracy of 86.28%. In the end, after excluding all false flood events and reinstating the mistakenly removed real ones, we obtained a total of 674 verified flood events. Among these 370 cities, 194 cities experienced flood disasters, accounting for 52.43% of the total. Additionally, we compared our findings with online news reports, as well as the flood data sets from the GDACS and EM‐DAT. We found that our study had a high detection rate for urban waterlogging events. However, there were cases of missed detection for flash floods and small watershed flood disasters. Nevertheless, this study represents the most comprehensive publicly available detection of flood events in China to date, which is of great significance for the government's flood management and decision‐making.

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Publication Details

Journal
Earth s Future
Published
2025-04-01
DOI
https://doi.org/10.1029/2024ef004775
Citations
5
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
5.53

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article

How Many Floods Have Occurred in China in the Past Decade? A Perspective From Social Media

Dingtao Shen, Hongji Gu, Shuiyuan Xiao, Chunxiao Zhang et al.
5 citations
Earth s Future
Flood Risk Assessment and Management
5.53
article

How Many Floods Have Occurred in China in the Past Decade? A Perspective From Social Media

Dingtao Shen, Hongji Gu, Shuiyuan Xiao, Chunxiao Zhang, Xiaofeng Zhang, Wei Chen
article en
5 citations

Abstract

Abstract Global climate change has led to frequent and widespread flood disasters in China. Traditional flood disaster investigations mainly focus on major flood events, and small‐scale flood events are often overlooked. This study utilized the Sina Weibo social media platform to detect flood events in 370 cities in China from 2012 to 2023. We downloaded 73.52 million Weibo posts and developed a two‐step flood detection algorithm. In the first step, the algorithm initially identifies 956 flood events based on changes in posting frequency. In the second step, an LDA topic model is used to detect topics for these flood events and automatically filter out false events, resulting in 729 flood events. Verification of these events confirmed that 629 of the 729 were real flood events, achieving a detection accuracy of 86.28%. In the end, after excluding all false flood events and reinstating the mistakenly removed real ones, we obtained a total of 674 verified flood events. Among these 370 cities, 194 cities experienced flood disasters, accounting for 52.43% of the total. Additionally, we compared our findings with online news reports, as well as the flood data sets from the GDACS and EM‐DAT. We found that our study had a high detection rate for urban waterlogging events. However, there were cases of missed detection for flash floods and small watershed flood disasters. Nevertheless, this study represents the most comprehensive publicly available detection of flood events in China to date, which is of great significance for the government's flood management and decision‐making.

Earth s FutureVol. 13(4)
China University of Geosciences (Beijing) (CN), Central China Normal University (CN), China Design Group (China) (CN)
National Natural Science Foundation of China, Central China Normal University, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 4%
Flood Risk Assessment and Management
5.53
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