Detection of flood trends and drivers in the Taihu Basin, China
Study region: Taihu Basin, China Study focus: Floods threaten humans, the environment, economic activity, and infrastructure. In this study, a new trend test and flood-frequency methods were adopted to detect extreme floods and their distributions based on flood-event identification. To fully unders...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Journal of Hydrology: Regional Studies |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581824003392 |
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| author | Yu Xu Yulu Zhang Kaixin Liu Yanjuan Wu Chao Gao |
| author_facet | Yu Xu Yulu Zhang Kaixin Liu Yanjuan Wu Chao Gao |
| author_sort | Yu Xu |
| collection | DOAJ |
| description | Study region: Taihu Basin, China Study focus: Floods threaten humans, the environment, economic activity, and infrastructure. In this study, a new trend test and flood-frequency methods were adopted to detect extreme floods and their distributions based on flood-event identification. To fully understand the phased process of the influence of human activities on extreme hydrological processes, 12 copula functions were employed creatively in combined static and dynamic time-varying correlation aspects between extreme precipitation and floods. New hydrological insights for the region: Although both significant and insignificant increasing trends of the annual maximum water level in all three hydrological districts were examined, the periodic oscillations of all the stations were similar. Thus, it was significant to fully detect the periodical variation of floods. Extreme floods occurred mainly in the 1990s, as measured by frequency estimates. Generally, the nonstationary response relationship between heavy rain and an extreme water level was gradually strengthened; that is, a certain magnitude precipitation seemed to induce a greater-intensity flood event as time passed. Through the identification of historical flood events and the analysis of the rise and fall processes of floods, we found that the main reason for variation in the response relationship was the increase in the water level before the rising stage, rather than the water level rising in the Taihu Basin. Our study findings further existing knowledge on the regional flood-control design standard and can ensure the coexistence of humans and water systems in the future. |
| format | Article |
| id | doaj-art-c7d3fdd302394fd18f3c40f2224eb7a9 |
| institution | OA Journals |
| issn | 2214-5818 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Hydrology: Regional Studies |
| spelling | doaj-art-c7d3fdd302394fd18f3c40f2224eb7a92025-08-20T02:30:55ZengElsevierJournal of Hydrology: Regional Studies2214-58182024-12-015610199010.1016/j.ejrh.2024.101990Detection of flood trends and drivers in the Taihu Basin, ChinaYu Xu0Yulu Zhang1Kaixin Liu2Yanjuan Wu3Chao Gao4Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China; Zhejiang Collaborative Innovation Center & Ningbo Universities Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research, Ningbo University, Ningbo 315211, China; Donghai Academy, Ningbo University, Ningbo 315211, ChinaDepartment of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, ChinaDepartment of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, ChinaDepartment of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, ChinaDepartment of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China; Correspondence to: Ningbo University, 818 Fenghua Road, Ningbo city, Zhejiang Province, ChinaStudy region: Taihu Basin, China Study focus: Floods threaten humans, the environment, economic activity, and infrastructure. In this study, a new trend test and flood-frequency methods were adopted to detect extreme floods and their distributions based on flood-event identification. To fully understand the phased process of the influence of human activities on extreme hydrological processes, 12 copula functions were employed creatively in combined static and dynamic time-varying correlation aspects between extreme precipitation and floods. New hydrological insights for the region: Although both significant and insignificant increasing trends of the annual maximum water level in all three hydrological districts were examined, the periodic oscillations of all the stations were similar. Thus, it was significant to fully detect the periodical variation of floods. Extreme floods occurred mainly in the 1990s, as measured by frequency estimates. Generally, the nonstationary response relationship between heavy rain and an extreme water level was gradually strengthened; that is, a certain magnitude precipitation seemed to induce a greater-intensity flood event as time passed. Through the identification of historical flood events and the analysis of the rise and fall processes of floods, we found that the main reason for variation in the response relationship was the increase in the water level before the rising stage, rather than the water level rising in the Taihu Basin. Our study findings further existing knowledge on the regional flood-control design standard and can ensure the coexistence of humans and water systems in the future.http://www.sciencedirect.com/science/article/pii/S2214581824003392Trend detectionFlood frequencyPeak-over-threshold modelGeneralized Pareto DistributionThe Taihu Basin |
| spellingShingle | Yu Xu Yulu Zhang Kaixin Liu Yanjuan Wu Chao Gao Detection of flood trends and drivers in the Taihu Basin, China Journal of Hydrology: Regional Studies Trend detection Flood frequency Peak-over-threshold model Generalized Pareto Distribution The Taihu Basin |
| title | Detection of flood trends and drivers in the Taihu Basin, China |
| title_full | Detection of flood trends and drivers in the Taihu Basin, China |
| title_fullStr | Detection of flood trends and drivers in the Taihu Basin, China |
| title_full_unstemmed | Detection of flood trends and drivers in the Taihu Basin, China |
| title_short | Detection of flood trends and drivers in the Taihu Basin, China |
| title_sort | detection of flood trends and drivers in the taihu basin china |
| topic | Trend detection Flood frequency Peak-over-threshold model Generalized Pareto Distribution The Taihu Basin |
| url | http://www.sciencedirect.com/science/article/pii/S2214581824003392 |
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