Overview
Algal blooming has become a key focus in the study of water body eutrophication, yet its mechanism remains poorly understood. Because algal blooming is closely related to chlorophyll-a, accurately simulating chlorophyll-a concentration trends can support the prediction of bloom events. This study applied the Environmental Fluid Dynamics Code (EFDC), developed by the U.S. Environmental Protection Agency, to simulate the eutrophication process in Daoxiang Lake, Beijing.
Model Setup
To drive the eutrophication model, a field sampling campaign was conducted from March through October of 2008 at intervals of 10–20 days. Algal bloom assessment criteria were reviewed, and chlorophyll-a concentration was selected as the input indicator for predicting algal blooms in the lake. The model was then calibrated and validated, with traditional statistics computed between the modeled results and observed values.
Key Findings
The simulated chlorophyll-a concentration basically agreed with observed concentrations, except for the later period at station 2#, and the average algal bloom prediction accuracy reached 63.43%. These results verified that the EFDC model can be used for chlorophyll-a concentration simulation and algal bloom prediction in Daoxiang Lake.