A Simple Model for a Fast Forewarning System of Brown Tide in the Coastal Waters of Qinhuangdao in the Bohai Sea, China

Qinhuangdao, a famous coastal resort city in northeastern China, has been affected by the rapid growth of harmful algae. The brown tide induced by Aureococcus anophagefferens (A. anophagefferens) first occurred along Qinhuangdao’s coastline in 2009, and it then developed into a harmful alga for the...

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Bibliographic Details
Main Authors: Fan, J. (Author), Kuang, C. (Author), Ou, L. (Author), Qin, R. (Author), Wang, J. (Author), Zhang, Q. (Author), Zou, Q. (Author)
Format: Article
Language:English
Published: MDPI 2022
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Online Access:View Fulltext in Publisher
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Summary:Qinhuangdao, a famous coastal resort city in northeastern China, has been affected by the rapid growth of harmful algae. The brown tide induced by Aureococcus anophagefferens (A. anophagefferens) first occurred along Qinhuangdao’s coastline in 2009, and it then developed into a harmful alga for the Bohai Sea. Based on MIKE 21, we construct a 2D coupled hydrodynamic and transport model to study the variation and distribution of total nitrogen (TN), and establish the relationship between A. anophagefferens, dissolved organic nitrogen (DON), and TN to provide a fast forewarning system for brown tide in Qinhuangdao. This model considers the decay, diffusion, and settling of TN, and the model results are in good agreement with the measured tidal level, current, and TN, indicating that the model is capable of capturing the observed TN distribution during the brown tide period. The transfer function relating TN to A. anophagefferens leads to a reliable fast forewarning and monitoring system. Moreover, the transferred A. anophagefferens cell density can be used to forecast the regional risk level of brown tide with a specific color indicator. The implementation of national policy relating to marine ecosystems decreases the nearshore concentration of N, P, and other nutrients, and therefore decreases harmful algal blooms. The fast routine assessment of brown tide by the present warning system provides robust guidance for the government to take action. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
ISBN:20763417 (ISSN)
DOI:10.3390/app12136477