Flood modeling prior to the instrumental era reveals limited magnitude of 1931 Yangtze flood
Abstract The global flood risk urges an improved understanding of flood magnitude and its mechanism, which needs insights from pre-instrumental flood investigations. Due to data scarcity, reconstructing pre-instrumental flood magnitudes relies on statistical downscaling, failing to capture nonlinear...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | npj Climate and Atmospheric Science |
| Online Access: | https://doi.org/10.1038/s41612-025-00908-1 |
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| author | Ling Zhang Zhongshi Zhang Lu Li Xiaoling Chen Xijin Wang Entao Yu Pratik Kad Odd Helge Otterå Chuncheng Guo Jianzhong Lu Mingna Wu |
| author_facet | Ling Zhang Zhongshi Zhang Lu Li Xiaoling Chen Xijin Wang Entao Yu Pratik Kad Odd Helge Otterå Chuncheng Guo Jianzhong Lu Mingna Wu |
| author_sort | Ling Zhang |
| collection | DOAJ |
| description | Abstract The global flood risk urges an improved understanding of flood magnitude and its mechanism, which needs insights from pre-instrumental flood investigations. Due to data scarcity, reconstructing pre-instrumental flood magnitudes relies on statistical downscaling, failing to capture nonlinear and dynamic characteristics. We developed a dynamical approach, NorESM-WRF-SWAT, integrating a global climate, a regional, and a hydrologic model to investigate the 1931 Yangtze River flood (the deadliest in the world) and compared it with the 1998’s. Through validation, our method outperforms the statistical method in simulating precipitations and river discharges. For the first time, we presented detailed insights into the intensity and duration of the 1931 flood, revealing a smaller magnitude but associated with an amplified loss, likely due to social vulnerability and reduced societal resilience compared to the 1998’s. While successful simulation can be interfered with by model variability, our dynamical method shows promise for simulating pre-instrumental flood and building a long-term pre-instrumental-hydrology database. |
| format | Article |
| id | doaj-art-caa294eb4a4e4a4f89954c7f44db9ee8 |
| institution | Kabale University |
| issn | 2397-3722 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Climate and Atmospheric Science |
| spelling | doaj-art-caa294eb4a4e4a4f89954c7f44db9ee82025-01-19T12:16:14ZengNature Portfolionpj Climate and Atmospheric Science2397-37222025-01-018111110.1038/s41612-025-00908-1Flood modeling prior to the instrumental era reveals limited magnitude of 1931 Yangtze floodLing Zhang0Zhongshi Zhang1Lu Li2Xiaoling Chen3Xijin Wang4Entao Yu5Pratik Kad6Odd Helge Otterå7Chuncheng Guo8Jianzhong Lu9Mingna Wu10Department of Atmospheric Science, School of Environmental Studies, China University of GeosciencesDepartment of Atmospheric Science, School of Environmental Studies, China University of GeosciencesNORCE Norwegian Research Centre, Bjerknes Centre for Climate ResearchState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan UniversityDepartment of Atmospheric Science, School of Environmental Studies, China University of GeosciencesNansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of SciencesNORCE Norwegian Research Centre, Bjerknes Centre for Climate ResearchNORCE Norwegian Research Centre, Bjerknes Centre for Climate ResearchNORCE Norwegian Research Centre, Bjerknes Centre for Climate ResearchState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan UniversityDepartment of Atmospheric Science, School of Environmental Studies, China University of GeosciencesAbstract The global flood risk urges an improved understanding of flood magnitude and its mechanism, which needs insights from pre-instrumental flood investigations. Due to data scarcity, reconstructing pre-instrumental flood magnitudes relies on statistical downscaling, failing to capture nonlinear and dynamic characteristics. We developed a dynamical approach, NorESM-WRF-SWAT, integrating a global climate, a regional, and a hydrologic model to investigate the 1931 Yangtze River flood (the deadliest in the world) and compared it with the 1998’s. Through validation, our method outperforms the statistical method in simulating precipitations and river discharges. For the first time, we presented detailed insights into the intensity and duration of the 1931 flood, revealing a smaller magnitude but associated with an amplified loss, likely due to social vulnerability and reduced societal resilience compared to the 1998’s. While successful simulation can be interfered with by model variability, our dynamical method shows promise for simulating pre-instrumental flood and building a long-term pre-instrumental-hydrology database.https://doi.org/10.1038/s41612-025-00908-1 |
| spellingShingle | Ling Zhang Zhongshi Zhang Lu Li Xiaoling Chen Xijin Wang Entao Yu Pratik Kad Odd Helge Otterå Chuncheng Guo Jianzhong Lu Mingna Wu Flood modeling prior to the instrumental era reveals limited magnitude of 1931 Yangtze flood npj Climate and Atmospheric Science |
| title | Flood modeling prior to the instrumental era reveals limited magnitude of 1931 Yangtze flood |
| title_full | Flood modeling prior to the instrumental era reveals limited magnitude of 1931 Yangtze flood |
| title_fullStr | Flood modeling prior to the instrumental era reveals limited magnitude of 1931 Yangtze flood |
| title_full_unstemmed | Flood modeling prior to the instrumental era reveals limited magnitude of 1931 Yangtze flood |
| title_short | Flood modeling prior to the instrumental era reveals limited magnitude of 1931 Yangtze flood |
| title_sort | flood modeling prior to the instrumental era reveals limited magnitude of 1931 yangtze flood |
| url | https://doi.org/10.1038/s41612-025-00908-1 |
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