Modeling Physical and Biogeochemical Controls on Dissolved Oxygen in Chesapeake Bay: Lessons Learned from Simple and Complex Approaches
We compared multiple modeling approaches in Chesapeake Bay to understand the processes controlling dissolved oxygen (O2) cycling and compare the advantages and disadvantages of the different models. Three numerical models were compared, including: (1) a 23-compartment biogeochemical model coupled to a regional scale, salt- and water-balance box model, (2) a simplified, four-term model formulation of O2 uptake and consumption coupled to a 3D-hydrodynamic model, and (3) a 23-compartment biogeochemical model coupled to a 3D-hydrodynamic model. All three models reproduced reasonable spatial and temporal patterns of dissolved O2, leading us to conclude that the model scale and approach one chooses to apply depends on the scientific questions motivating the study. From this analysis, we conclude the following: (1) Models of varying spatial and temporal scales and process resolution have a role in the scientific process. (2) There is still much room for improvement in our ability to simulate dissolved O2 dynamics in coastal ecosystems. (3) An ever-increasing diversity of models, three of which are presented here, will vastly improve our ability to discern physical versus biogeochemical controls on O2 and hypoxia in coastal ecosystems.
KeywordsPhysical modeling Biogeochemical modeling Dissolved oxygen Hypoxia Coastal ecosystems Chesapeake Bay
We are grateful for the constructive comments from two anonymous reviewers and to Jim Hagy for sharing his box model code that we adapted for this analysis. Support from several grants and contracts have made this chapter possible, including the US National Science Foundation grants (i) DEB1353766 (OPUS; Kemp and Boynton) and (ii) CBET1360415 (WSC; Testa and Kemp), US National Oceanic and Atmospheric Administration (NOAA) grants (iii) NAO7NOS4780191, (Coastal Hypoxia Research Program; Kemp, M. Li, Di Toro) and (iv) NA15NOS4780184 (Testa, M. Li, Kemp), and (v) National Aeronautics and Space Administration grant NNX14AM37G (Kemp). This paper is contribution #5200 of the University of Maryland Center for Environmental Science and CHRP Publication number 211.
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