Journal cover Journal topic
Biogeosciences An interactive open-access journal of the European Geosciences Union
Journal topic
Volume 13, issue 7
Biogeosciences, 13, 2011–2028, 2016
https://doi.org/10.5194/bg-13-2011-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Biogeosciences, 13, 2011–2028, 2016
https://doi.org/10.5194/bg-13-2011-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 06 Apr 2016

Research article | 06 Apr 2016

Challenges associated with modeling low-oxygen waters in Chesapeake Bay: a multiple model comparison

Isaac D. Irby1, Marjorie A. M. Friedrichs1, Carl T. Friedrichs1, Aaron J. Bever2, Raleigh R. Hood3, Lyon W. J. Lanerolle4,5, Ming Li6, Lewis Linker7, Malcolm E. Scully8, Kevin Sellner9, Jian Shen1, Jeremy Testa6, Hao Wang3, Ping Wang10, and Meng Xia11 Isaac D. Irby et al.
  • 1Virginia Institute of Marine Science, College of William & Mary, P.O. Box 1346, Gloucester Point, VA 23062, USA
  • 2Anchor QEA, LLC, 130 Battery Street, Suite 400, San Francisco, CA 94111, USA
  • 3Horn Point Laboratory, University of Maryland Center for Environmental Science, P.O. Box 775, Cambridge, MD 21613, USA
  • 4NOAA/NOS/OCS Coast Survey Development Laboratory, 1315 East–West Highway, Silver Spring, MD 20910, USA
  • 5ERT Inc., 14401 Sweitzer Lane Suite 300, Laurel, MD 20707, USA
  • 6Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science, P.O. Box 38, Solomons, MD 20688, USA
  • 7US Environmental Protection Agency Chesapeake Bay Program Office, 410 Severn Avenue, Annapolis, MD 21403, USA
  • 8Woods Hole Oceanographic Institution, Applied Ocean Physics and Engineering Department, Woods Hole, MA 02543, USA
  • 9Chesapeake Research Consortium, 645 Contees Wharf Road, Edgewater, MD 21037, USA
  • 10VIMS/Chesapeake Bay Program Office, 410 Severn Avenue, Annapolis, MD 21403, USA
  • 11Department of Natural Sciences, University of Maryland Eastern Shore, MD, USA

Abstract. As three-dimensional (3-D) aquatic ecosystem models are used more frequently for operational water quality forecasts and ecological management decisions, it is important to understand the relative strengths and limitations of existing 3-D models of varying spatial resolution and biogeochemical complexity. To this end, 2-year simulations of the Chesapeake Bay from eight hydrodynamic-oxygen models have been statistically compared to each other and to historical monitoring data. Results show that although models have difficulty resolving the variables typically thought to be the main drivers of dissolved oxygen variability (stratification, nutrients, and chlorophyll), all eight models have significant skill in reproducing the mean and seasonal variability of dissolved oxygen. In addition, models with constant net respiration rates independent of nutrient supply and temperature reproduced observed dissolved oxygen concentrations about as well as much more complex, nutrient-dependent biogeochemical models. This finding has significant ramifications for short-term hypoxia forecasts in the Chesapeake Bay, which may be possible with very simple oxygen parameterizations, in contrast to the more complex full biogeochemical models required for scenario-based forecasting. However, models have difficulty simulating correct density and oxygen mixed layer depths, which are important ecologically in terms of habitat compression. Observations indicate a much stronger correlation between the depths of the top of the pycnocline and oxycline than between their maximum vertical gradients, highlighting the importance of the mixing depth in defining the region of aerobic habitat in the Chesapeake Bay when low-oxygen bottom waters are present. Improvement in hypoxia simulations will thus depend more on the ability of models to reproduce the correct mean and variability of the depth of the physically driven surface mixed layer than the precise magnitude of the vertical density gradient.

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A comparison of eight hydrodynamic-oxygen models revealed that while models have difficulty resolving key drivers of dissolved oxygen (DO) variability, all models exhibit skill in reproducing the variability of DO itself. Further, simple oxygen models and complex biogeochemical models reproduced observed DO variability similarly well. Future advances in hypoxia simulations will depend more on the ability to reproduce the depth of the mixed layer than the degree of the vertical density gradient.
A comparison of eight hydrodynamic-oxygen models revealed that while models have difficulty...
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