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

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.

Research highlights▶ We model the trends of chllorophyll-a and algal blooms in the Daoxiang Lake by using the EFDC model. ▶ We summarize and discuss the algal bloom criterion, then the criterion is used for the evaluation of algal bloom levels in the Daoxiang Lake. ▶ The EFDC model could provide acceptable reproduction of chlorophyll-a concentration and algal prediction in the Daoxiang Lake. ▶ The predicted precision of the EFDC model for short simulation period is better than that for long simulation period.