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Estuaries Coast. 2016 Mar;39(2):311-332. Epub 2015 Jul 7.

Progress and challenges in coupled hydrodynamic-ecological estuarine modeling.

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U.S. Geological Survey, Woods Hole, MA 02543.
Virginia Institute of Marine Science, Gloucester Point, VA.
U.S. Environmental Protection Agency, Narragansett, RI.
IH-Cantabria, Santander, Spain.
University of Maryland, Chesapeake Biological Laboratory, Solomons, MD.
University of Connecticut, Groton, CT.
Woods Hole Oceanographic Institution, Woods Hole, MA.


Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear, because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a "theory of everything" for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.


ecological modeling; ecosystem modeling; hydrodynamics; numerical modeling; skill assessment

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