Articles | Volume 29, issue 3
https://doi.org/10.5194/hess-29-767-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-767-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
13 Feb 2025
Research article | Highlight paper |
| 13 Feb 2025
| 13 Feb 2025
Creating a national urban flood dataset for China from news texts (2000–2022) at the county level
Shengnan Fu
School of Infrastructure Engineering, Dalian University of Technology, Dalian, 116024, China
David M. Schultz
Centre for Crisis Studies and Mitigation, The University of Manchester, M13 9PL, United Kingdom
Department of Earth and Environmental Sciences, Centre for Atmospheric Science, The University of Manchester, M13 9PL, United Kingdom
Heng Lyu
CORRESPONDING AUTHOR
School of Infrastructure Engineering, Dalian University of Technology, Dalian, 116024, China
Zhonghua Zheng
Centre for Crisis Studies and Mitigation, The University of Manchester, M13 9PL, United Kingdom
Department of Earth and Environmental Sciences, Centre for Atmospheric Science, The University of Manchester, M13 9PL, United Kingdom
Chi Zhang
School of Infrastructure Engineering, Dalian University of Technology, Dalian, 116024, China
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Total article views: 9,747 (including HTML, PDF, and XML)
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Total article views: 1,491 (including HTML, PDF, and XML)
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Cited
16 citations as recorded by crossref.
- A process-informed framework linking temperature-rainfall projections and urban flood modeling W. Zou et al. https://doi.org/10.5194/hess-30-5097-2026
- The spatiotemporal pattern characteristics of extreme precipitation-induced flood disaster risk in Chinese counties L. Huang et al. https://doi.org/10.1007/s10584-026-04233-1
- Utilizing Geoparsing for Mapping Natural Hazards in Europe T. Yu et al. https://doi.org/10.3390/w17243520
- Monitoring reservoir storage using remote sensing and large language models I. Daliakopoulos https://doi.org/10.1016/j.jenvman.2026.129400
- From Concept to Practice: Evidence and Lessons from Sponge City Implementation in Shenzhen, China H. Pinto et al. https://doi.org/10.3390/urbansci10030135
- Rainfall Pressure, Stormwater Pipe Network Scale, and Urban Flood Disaster Occurrence in Guangdong Province S. Zhao et al. https://doi.org/10.3390/w18151806
- Policy learning pathways in disaster management: evolution of flood prevention systems in China’s megacity J. Qian et al. https://doi.org/10.3389/fenvs.2026.1784152
- Advancements in the application of large language models in urban studies: A systematic review J. Xia et al. https://doi.org/10.1016/j.cities.2025.106142
- Multimodal retrieval of flood-related remote sensing big data with semantic augmentation from flood events Y. Zhou et al. https://doi.org/10.1080/20964471.2026.2689766
- Social media sentiment exposure to climate-induced floods and risk responses to the 2022 flood in Pakistan S. Soomro et al. https://doi.org/10.1016/j.jenvman.2026.129413
- Retrospective Assessment of Urban Flooding Susceptibility on the Qinghai–Tibet Plateau Under Data Scarcity Y. Liu et al. https://doi.org/10.3390/ijgi15070309
- Attribution of Urban Flood Hydrological Processes and Prioritisation of Nature‐Based Solutions Based in Pakistan Using Sentiment Analysis N. Soomro et al. https://doi.org/10.1002/hyp.70452
- Chikungunya waves in 2025 signal risk of endemicity in China K. Tee et al. https://doi.org/10.1371/journal.pntd.0014685
- Interpretable machine learning framework for urban flood susceptibility assessment: a multi-model comparison with spatial heterogeneity analysis in Yancheng X. Zhang & D. Guo https://doi.org/10.1038/s41598-026-47925-5
- Research on Urban Flooding Water Level Prediction Integrating Mechanism-Heuristic Temporal Feature Engineering 家. 金 https://doi.org/10.12677/aep.2026.165089
- Assessing the impact of sponge cities on urban eco-efficiency: Integration of ArcGIS and econometric analysis Y. Han et al. https://doi.org/10.1007/s10668-025-06882-1
16 citations as recorded by crossref.
- A process-informed framework linking temperature-rainfall projections and urban flood modeling W. Zou et al. https://doi.org/10.5194/hess-30-5097-2026
- The spatiotemporal pattern characteristics of extreme precipitation-induced flood disaster risk in Chinese counties L. Huang et al. https://doi.org/10.1007/s10584-026-04233-1
- Utilizing Geoparsing for Mapping Natural Hazards in Europe T. Yu et al. https://doi.org/10.3390/w17243520
- Monitoring reservoir storage using remote sensing and large language models I. Daliakopoulos https://doi.org/10.1016/j.jenvman.2026.129400
- From Concept to Practice: Evidence and Lessons from Sponge City Implementation in Shenzhen, China H. Pinto et al. https://doi.org/10.3390/urbansci10030135
- Rainfall Pressure, Stormwater Pipe Network Scale, and Urban Flood Disaster Occurrence in Guangdong Province S. Zhao et al. https://doi.org/10.3390/w18151806
- Policy learning pathways in disaster management: evolution of flood prevention systems in China’s megacity J. Qian et al. https://doi.org/10.3389/fenvs.2026.1784152
- Advancements in the application of large language models in urban studies: A systematic review J. Xia et al. https://doi.org/10.1016/j.cities.2025.106142
- Multimodal retrieval of flood-related remote sensing big data with semantic augmentation from flood events Y. Zhou et al. https://doi.org/10.1080/20964471.2026.2689766
- Social media sentiment exposure to climate-induced floods and risk responses to the 2022 flood in Pakistan S. Soomro et al. https://doi.org/10.1016/j.jenvman.2026.129413
- Retrospective Assessment of Urban Flooding Susceptibility on the Qinghai–Tibet Plateau Under Data Scarcity Y. Liu et al. https://doi.org/10.3390/ijgi15070309
- Attribution of Urban Flood Hydrological Processes and Prioritisation of Nature‐Based Solutions Based in Pakistan Using Sentiment Analysis N. Soomro et al. https://doi.org/10.1002/hyp.70452
- Chikungunya waves in 2025 signal risk of endemicity in China K. Tee et al. https://doi.org/10.1371/journal.pntd.0014685
- Interpretable machine learning framework for urban flood susceptibility assessment: a multi-model comparison with spatial heterogeneity analysis in Yancheng X. Zhang & D. Guo https://doi.org/10.1038/s41598-026-47925-5
- Research on Urban Flooding Water Level Prediction Integrating Mechanism-Heuristic Temporal Feature Engineering 家. 金 https://doi.org/10.12677/aep.2026.165089
- Assessing the impact of sponge cities on urban eco-efficiency: Integration of ArcGIS and econometric analysis Y. Han et al. https://doi.org/10.1007/s10668-025-06882-1
Saved (final revised paper)
Latest update: 09 Sep 2026
Editorial statement
This paper uses information from news sites with natural language processing tools to infer data on a hydrological process at the regional scale (flooding). The paper demonstrates the technique's applicability and opens new avenues to use advanced computing techniques and web resources to improve the understanding of hydrological processes.
This paper uses information from news sites with natural language processing tools to infer data...
Short summary
We create China’s first open county-level urban flood dataset (2000–2022) using news media data with the help of deep learning. The dataset reflects both natural and societal influences and includes 7595 urban flood events across 2051 counties, covering 46 % of China’s land area. It reveals the predominance of summer floods, an upward trend since 2000, and a decline from southeast to northwest. Notably, some highly developed regions show a decrease, likely due to improved flood management.
We create China’s first open county-level urban flood dataset (2000–2022) using news media data...
