Integrated Toolset for Water Quality Modeling in the Great Lakes
Brown, Scott D.
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The focus of this research effort was the construction of an ecosystem modeling framework capable of providing researchers from multiple disciplines with a modeling environment to integrate a diverse set of data and models so that various resource management proposals could be tested and compared. In addition to supporting "one off" studies, this modeling framework is also designed and implemented to support persistent modeling services where a model of a given ecosystem is kept constantly up-to-date with data provided by a diverse set of sources. These persistent modeling services can be leveraged to support "nowcasting" (filling gaps between current observations) and forecasting (prediction of future observations) of lake conditions. This modeling framework integrates a variety of multi-disciplinary models including hydrodynamic models, suspended sediment models, water chemistry models and biological community models. Specifically, the latest hydrodynamic modeling capabilities developed at the National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) were integrated with a flexible spatially resolved numerical modeling engine capable of supporting a diverse set of user-defined in-water and in-sediment processes. The resulting capability allows the researcher to explore the complexity of various processes at different spatial and temporal scales and to test hypotheses regarding how complex ecosystems will react to proposed management plans. In addition, improved Lagrangian methods for mass tracking that leverage a novel bi-directional random particle walking method are presented for evaluating specific source/target coupling problems.