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.
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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Executive editor
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...