题名 | Improved data assimilation for algal bloom dynamics simulation in the Three Gorges Reservoir using particle filter |
作者 | |
通讯作者 | He,Guojian |
发表日期 | 2024-05-20
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DOI | |
发表期刊 | |
ISSN | 0048-9697
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EISSN | 1879-1026
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卷号 | 926 |
摘要 | Algal blooms have been increasingly prevalent in recent years, especially in lakes and reservoirs; their accurate prediction is essential for preserving water quality. In this study, the observed chlorophyll a (chl-a) levels were assimilated into the Environmental Fluid Dynamics Code (EFDC) of algal bloom dynamics by using a particle filter (PF), and the state variables of water quality and model parameters were simultaneously updated to achieve enhanced algal bloom predictive performance. The developed data assimilation system for algal blooms was applied to Xiangxi Bay (XXB) in the Three Gorges Reservoir (TGR). The results show that the ensemble mean accuracy and reliability of the confidence intervals of the predicted state variables, including chl-a and indirectly updated phosphate (PO), ammonium (NH), and nitrate (NO) levels, were considerably improved after PF assimilation. Thus, PF assimilation is an effective tool for the dynamic correction of parameters to represent their inherent variations. Increased assimilation frequency can effectively suppress the accumulation of model errors; therefore, the use of high-frequency water quality data for assimilation is recommended to ensure more accurate and reliable algal bloom prediction. |
关键词 | |
相关链接 | [Scopus记录] |
收录类别 | |
语种 | 英语
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学校署名 | 其他
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ESI学科分类 | ENVIRONMENT/ECOLOGY
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Scopus记录号 | 2-s2.0-85189697215
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来源库 | Scopus
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引用统计 |
被引频次[WOS]:1
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成果类型 | 期刊论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/741133 |
专题 | 工学院_海洋科学与工程系 |
作者单位 | 1.State Key Laboratory of Hydro-science and Engineering,Department of Hydraulic Engineering,Tsinghua University,Beijing,100084,China 2.Yangtze Eco-Environment Engineering Research Center,China Three Gorges Corporation,Wuhan,430010,China 3.Department of Ocean Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China 4.State Key Laboratory of Internet of Things for Smart City,Department of Civil and Environmental Engineering,University of Macau,Macao,999078,China |
推荐引用方式 GB/T 7714 |
Huang,Lei,Xu,Xingya,Fang,Hongwei,et al. Improved data assimilation for algal bloom dynamics simulation in the Three Gorges Reservoir using particle filter[J]. Science of the Total Environment,2024,926.
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APA |
Huang,Lei.,Xu,Xingya.,Fang,Hongwei.,He,Guojian.,Gao,Qifeng.,...&Gao,Liang.(2024).Improved data assimilation for algal bloom dynamics simulation in the Three Gorges Reservoir using particle filter.Science of the Total Environment,926.
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MLA |
Huang,Lei,et al."Improved data assimilation for algal bloom dynamics simulation in the Three Gorges Reservoir using particle filter".Science of the Total Environment 926(2024).
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条目包含的文件 | 条目无相关文件。 |
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