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Carl Friedrichs Virginia Institute of Marine Science Gloucester Point, Virginia, USA

Evaluating Models of Chesapeake Bay Low Oxygen Dead Zones: Helping Federal Agencies Improve Water Quality. Carl Friedrichs Virginia Institute of Marine Science Gloucester Point, Virginia, USA Presented to VIMS Council, 28 January 2011 .

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Carl Friedrichs Virginia Institute of Marine Science Gloucester Point, Virginia, USA

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  1. Evaluating Models of Chesapeake Bay Low Oxygen Dead Zones: Helping Federal Agencies Improve Water Quality Carl Friedrichs Virginia Institute of Marine Science Gloucester Point, Virginia, USA Presented to VIMS Council, 28 January 2011

  2. Evaluating Models of Chesapeake Bay Low Oxygen Dead Zones: Helping Federal Agencies Improve Water Quality Outline 1) Introduction: Chesapeake Bay Dead Zone Effects and Causes 2) SURA Estuarine Hypoxia Testbed: Goals, Participants, Methods 3) Preliminary Results of Oxygen Model Comparison

  3. (UMCES, Coastal Trends)

  4. HYPOXIA DO ≤ ~ 2 mg/L (UMCES, Coastal Trends)

  5. (VIMS, ScienceDaily) (UMCES, Coastal Trends)

  6. Classic Factors Thought to Affect Dead Zones in Chesapeake Bay Classically two primary factors: nutrient input and stratification (www.vims.edu)

  7. Seemingly Contradictory Trends in Bay Oxygen and Related Factors: Hypoxia continually increasing in Chesapeake Bay with a marked jump around 1985 (Kemp et al. 2009)

  8. Seemingly Contradictory Trends in Bay Oxygen and Related Factors: But nutrient loading has been flat to decreasing since 1970. (Kemp et al. 2009)

  9. Seemingly Contradictory Trends in Bay Oxygen and Related Factors: River discharge isn’t changing much. (Kemp et al. 2009)

  10. Seemingly Contradictory Trends in Bay Oxygen and Related Factors: Something that has drastically changed: The “North Atlantic Oscillation Index” (Kemp et al. 2009)

  11. NAO is a climatic shift that controls the direction of summer Bay winds: Since 1980, summer winds over the Chesapeake Bay have been more from the west, which reduces the amount of transport of high DO water from shoals into the deep channel during summer. (It has nothing to do with nutrients, fresh water input or absolute stratification in the deep channel.) (Scully 2010)

  12. Accounting for Change in Wind Explains Dead Zone Growth: (Scully 2010)

  13. Evaluating Models of Chesapeake Bay Low Oxygen Dead Zones: Helping Federal Agencies Improve Water Quality Outline 1) Introduction: Chesapeake Bay Dead Zone Effects and Causes 2) SURA Estuarine Hypoxia Testbed: Goals, Participants, Methods 3) Preliminary Results of Oxygen Model Comparison

  14. NOAA/SURA Estuarine Hydrodynamics and Hypoxia Modeling Testbed • Funded by NOAA through SURA (Southeastern Universities Research Association). Initially one year of funding to VIMS (~$800K) which started June 2010. • Part of a larger NOAA/SURA larger (~$4M) “Super-Regional Testbed to Improve Models of Environmental Processes on the U.S. Atlantic and Gulf of Mexico Coasts”. • Pilot projects in the larger “Super-Regional Testbed” are addressing three chronic issues of high relevance within the U.S. Gulf of Mexico-U.S. Atlantic Coast region: • Coastal Inundation • Estuarine Hypoxia • Shelf Hypoxia

  15. NOAA/SURA Estuarine Hydrodynamics and Hypoxia Modeling Testbed • Carl Friedrichs (VIMS) – Team Leader • Federal partners • David Green (NOAA-NWS) – Transition to operations at NWS • Lyon Lanerole (NOAA-CSDL) – Transition to operations at CSDL; CBOFS2 • Lewis Linker (EPA), Carl Cerco (USACE) – Transition to operations at EPA; CH3D, CE-ICM • Doug Wilson (NOAA-NCBO) – Integration w/observing systems at NCBO/IOOS • Non-federal partners • Marjorie Friedrichs, Aaron Bever (VIMS) – Metric development and model skill assessment • Yun Li, Ming Li (UMCES) – ROMS hydrodynamics in CB • Wen Long, Raleigh Hood (UMCES) – ChesROMS with NPZD water quality model • Scott Peckham, JisammaKallumadikal (CSDMS) – Multiple ROMS grids, forcings, O2 codes • Malcolm Scully (ODU) – ChesROMS with 1 term oxygen respiration model • Kevin Sellner (CRC) – Academic-agency liason; facilitator for model comparison • JianShen, Bo Hong (VIMS) – SELFE, FVCOM, EFDC models in CB • John Wilkin, Julia Levin (Rutgers) – ROMS-Espresso + 7 other MAB hydrodynamic models

  16. Methods: Multiple Hydrodynamic models CBOFS2 (L. Lanerolle, NOAA-CSDL) CH3D (EPA/USACE Chesapeake Bay Program)

  17. Methods: Dissolved Oxygen Models Two dissolved DO models highlighted today: (1) 1-term DO model in ROMS model: single respiration term (not dependent on nutrients; M. Scully/NOAA) (2) CE-QUAL-ICM Multi-component model: includes wathershed, nutrients, algae, zooplankton, SAV, benthos, fish… (CBP/EPA/USACE)

  18. EPA/USACE CE-QUAL-ICM forced by CH3D and detailed watershed inputs • Final run = 1985 – 2005. • It is not practical to rerun the final 57K grid CH3D model with alternate forcing. • EPA CBP plans next “release” of updated hydrodynamic model by 2017. • Successor hydrodynamic model has not been chosen, although USACE favors adding third dimension to an existing finite element inundation model. • Timing is ideal for Estuarine Hypoxia Team to provide guidance to CBP concerning favorable attributes of CB (Slide courtesy Rich Batiuk, EPA)

  19. EPA/USACE CE-QUAL-ICM model (cont.) (Slide courtesy C. Cerco, USACE)

  20. Methods: Dissolved Oxygen from ~50 CBP/EPA Monitoring Station Locations http://www.eco-check.org/

  21. Evaluating Models of Chesapeake Bay Low Oxygen Dead Zones: Helping Federal Agencies Improve Water Quality Outline 1) Introduction: Chesapeake Bay Dead Zone Effects and Causes 2) SURA Estuarine Hypoxia Testbed: Goals, Participants, Methods 3) Preliminary Results of Oxygen Model Comparison

  22. Observed and Modeled Top-to-Bottom DS and Bottom DO in Central Chesapeake Bay NOAA/UMCES/ODU ROMS model plus 1-term DO model Variability in DO is easier to model than and unrelated to stratification. This is true for both the simple 1-term model (above) and the more complex EPA model. (by M. Scully)

  23. Observed and Modeled Chesapeake Bay Hypoxic Volume for 2004 10 5 0 Multi-term DO model Hypoxic Volume in km3 1-term DO model EPA observations Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Date in 2004 One-term DO model does about as well as much more complex model. (by M. Scully, L. Lanerolle, A. Bever, M. Friedrichs)

  24. 2004 Hypoxic Volume Sensitivity Tests (1-term model) 20 10 0 Base Case Hypoxic Volume in km3 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Date in 2004 One-term DO model does about as well as much more complex model. (by M. Scully)

  25. 2004 Hypoxic Volume Sensitivity Tests (1-term model) 20 10 0 Base Case Hypoxic Volume in km3 Constant River discharge Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Date in 2004 Seasonal changes in hypoxia are not a function of seasonal changes in freshwater. (by M. Scully)

  26. 2004 Hypoxic Volume Sensitivity Tests (1-term model) 20 10 0 July wind year-round Base Case Hypoxic Volume in km3 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Date in 2004 Seasonal changes in hypoxia are almost entirely due to seasonal changes in wind. (by M. Scully)

  27. 2004 Hypoxic Volume Sensitivity Tests (1-term model) 20 10 0 Base Case Hypoxic Volume in km3 January wind year-round Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Date in 2004 Seasonal changes in hypoxia are almost entirely due to seasonal changes in wind. (by M. Scully)

  28. Evaluating Models of Chesapeake Bay Low Oxygen Dead Zones: Helping Federal Agencies Improve Water Quality Conclusions -- Dead zones are highly detrimental to Chesapeake Bay living resources. -- Seasonal and interannual variability in the Chesapeake Bay dead zone is controlled largely by variability in the wind. -- Simple models that largely neglect biology appear to predict CB seasonal dead zone variability as well as much more complex ecosystem models. -- Improved forecasts of CB dead zone extent in response to land use and climate change would benefit from the use of better wind models and multiple ecosystem models (i.e., “ensemble models” similar to hurricane prediction).

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