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Prediction of algal blooming using EFDC model: Case study in the Daoxiang Lake

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  • Wu, Guozheng
  • Xu, Zongxue

Abstract

Algal blooming has become one of the key fields of study on eutrophication of water body recently. The mechanism of algal blooming is still not understood well. However, it is obvious to understand that algal blooming has close relationship with chlorophyll-a. Therefore, if the trends of chlorophyll-a concentration can be simulated accurately, it will be helpful for the prediction of algal bloom events. In this study, a model named Environmental Fluid Dynamics Code (EFDC), which was developed by U.S. Environmental Protection Agency, was described and used to simulate the eutrophication process in the Daoxiang Lake, Beijing. To run the eutrophication model for the Lake, a field sampling was conducted in March–October of 2008 with interval of 10–20 days. Meanwhile, the algal bloom assessment criteria were investigated and the indicator of chlorophyll-a concentration was selected as input for the prediction of algal bloom in the Daoxiang Lake. After model calibration and validation, traditional statistics has been done between modeled results and observed values. The modeled results show that the simulated chlorophyll-a concentration basically agrees with the observed concentration except the later period of station 2# and the average algal bloom prediction accuracy is 63.43%. It was verified that the EFDC model can be used for chlorophyll-a concentration simulation and algal blooming prediction in the Daoxiang Lake.

Suggested Citation

  • Wu, Guozheng & Xu, Zongxue, 2011. "Prediction of algal blooming using EFDC model: Case study in the Daoxiang Lake," Ecological Modelling, Elsevier, vol. 222(6), pages 1245-1252.
    • Handle: RePEc:eee:ecomod:v:222:y:2011:i:6:p:1245-1252
    DOI: 10.1016/j.ecolmodel.2010.12.021
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    References listed on IDEAS

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    4. Md. Islam & Daisuke Kitazawa & Thomas Hamill & Ho-Dong Park, 2013. "Modeling mitigation strategies for toxic cyanobacteria blooms in shallow and eutrophic Lake Kasumigaura, Japan," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 18(4), pages 449-470, April.
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    12. Kim, Jaeyoung & Seo, Dongil & Jones, John R., 2022. "Harmful algal bloom dynamics in a tidal river influenced by hydraulic control structures," Ecological Modelling, Elsevier, vol. 467(C).
    13. Li-kun, Yang & Sen, Peng & Xin-hua, Zhao & Xia, Li, 2017. "Development of a two-dimensional eutrophication model in an urban lake (China) and the application of uncertainty analysis," Ecological Modelling, Elsevier, vol. 345(C), pages 63-74.
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