Influence of Multi Algal Groups in the Calibration of a Water Quality Model

A management tool based on scientific inquiry rather than politics is needed for policy makers to make environmentally sound decisions regarding difficult issues, which will only occur more frequently as coastal populations continue to increase. Typically, a well-calibrated hydrodynamic and water quality model is used as the management tool. The development of a water quality and circulation model is based on field data that encompasses the factors affecting the water body, and the model is used to evaluate the potential effects of changing point source loadings under varying operational and environmental conditions. The level of predictability depends on the goodness of field data needed for model calibration and for setting up input data, assuming all the relevant water quality processes are simulated correctly. But there are times when good field data are available, yet the calibration is not good. In such a situation, it is conventional to revisit the algorithms used for the various water quality processes. This approach was attempted in a recent project where a three-dimensional hydrodynamic and water quality model called GEMSS was applied to predict the quality of water in the Budd Inlet, located in the Southern Puget Sound (Washington, USA). Within GEMSS, the use of the water quality model called WQDPM, which is a modified version of EPA's Eutro5 water quality model, did not predict the vertical structure of dissolved oxygen and phytoplankton at different locations in the Budd Inlet. The phytoplankton was modeled in Eutro5 as a single algal group. In order to improve the calibration, the alternate water quality model called WQCBM available in GEMSS was used. This model includes different forms of organic carbon that can be related to sediment exchange processes. WQCBM simulates five interacting sub-systems: net phytoplankton production, the phosphorus cycle, the nitrogen cycle, the dissolved oxygen balance, and the particulate organic carbon balance. The carbon based model was updated to include dinoflagellates and diatoms for the simulation of phytoplankton dynamics.