Operational Environmental Prediction: Nearshore Water Quality in the Great Lakes

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Operational Environmental Prediction Nearshore
Water Quality in the Great Lakes
David J. Schwab NOAA Great Lakes Environmental
Research Laboratory Ann Arbor, MI
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Factors Contributing to Nearshore Water Quality
in the Great Lakes
Climate Meteorology Hydrology Hydrodynamics
Biology/Chemistry
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Beach Closings or HABs
Meteorology
Meteorology
Change in Land-use
Change in Land-use
Change in Land-use
Hydrology/Water Flow Bacterial Fate
Hydrology/Water Flow Bacterial Fate
Beach Closings
Circulation and Bacterial Fate
Circulation and Bacterial Fate
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• Outline
• Lake Michigan tributary modeling using
  nested-grid hydrodynamic models - application to
  beach water quality forecasting
• Lake Erie coupled physical/biological model -
  application to HAB and hypoxia forecasting

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Beach Closures

• Major health risk of microbial contamination by
  bacteria, viruses and protozoa in recreational
  waters
• E.Coli requires a 24 hour incubation period
• People may unintentionally swim in contaminated
  water

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Lake Michigan Beach Quality Forecasting
Lakewide grid (POM model)
Coupled models nested grids

Burns Ditch nested model grid
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Princeton Ocean Model (Blumberg and Mellor,
1987) - Fully three-dimensional nonlinear
Navier-Stokes equations - Flux form of
equations - Boussinesq and hydrostatic
approximations - Free upper surface with
barotropic (external) mode - Baroclinic
(internal) mode - Turbulence model for vertical
mixing - Terrain following vertical coordinate
(ltsigmagt-coordinate) - Generalized orthogonal
horizontal coordinates - Smagorinsky horizontal
diffusion - Leapfrog (centered in space and time)
time step - Implicit scheme for vertical mixing -
Arakawa-C staggered grid - Fortran code optimized
for vectorization Application to the Great
Lakes - No open boundary - No tides - Uniform
salinity - Seasonal thermal structure - Uniform
rectangular grid - XDR used for input and output

• Nested grid considerations
• 3d boundary condition for u, v, and T
  interpolated from coarse grid at each boundary
  point
• Vertically integrated velocity is specified for
  external mode
• Internal mode velocity and temperature are
  specified from 3-d boundary condition for inflow,
  use radiation condition for outflow
• Water level is adjusted to maintain zero mean in
  nested grid subdomain

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Nested grid hydrodynamic models in Lake Michigan
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Burns Ditch 100m computational grid
24 km
6 km
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Web site www.glerl.noaa.gov/res/glcfs/bd
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Great Lakes Coastal Forecasting System -
Operational Nowcast 20 day sample using
vertically averaged currents
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• Lake Erie Coupled Physical/Biological model

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The Problem - Excessive nutrient loading in the
1960s led to massive algal blooms, oxygen
depletion, and diminished water quality in Lake
Erie. - 1972 Water Quality Agreement between the
US and Canada limited P loads from municipal,
industrial, and agricultural sources. - With
controls, P levels decreased to acceptable levels
and water quality improved. - In recent years, P
levels in Lake Erie appear to be increasing,
despite controls.
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The Problem - Excessive nutrient loading in the
1960s led to massive algal blooms, oxygen
depletion, and diminished water quality in Lake
Erie. - 1972 Water Quality Agreement between the
US and Canada limited P loads from municipal,
industrial, and agricultural sources. - With
controls, P levels decreased to acceptable levels
and water quality improved. - In recent years, P
levels in Lake Erie appear to be increasing,
despite controls.
Our Approach - Incorporate phosphorus transport
and fate dynamics into high resolution (hourly
time scale, 2 km horizontal resolution)
hydrodynamic model of Lake Erie as a first step
toward spatially explicit model of entire lower
food web
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Lake Erie Physical Characteristics Surface
Area 25800 km2 Throughflow 6000
m3s-1 Volume 480 km3 Retention time 2.5
yrs Mean Depth 18.6 m
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Ecosystem Forecasting of Lake Erie Hypoxia

• What are the Causes, Consequences, and Potential
  Remedies of Lake Erie Hypoxia?
• Linked set of models to forecast
• changes in nutrient loads to Lake Erie
• responses of central basin hypoxia to multiple
  stressors
• P loads, hydrometeorology, dreissenids
• potential ecological responses to changes in
  hypoxia
• Approach
• Models with range of complexity
• Consider both anthropogenic and natural stressors
• Use available data IFYLE, LETS, etc.
• Will assess uncertainties in both drivers and
  models
• Apply models within an Integrated Assessment
  framework to inform decision making for policy
  and management

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Hypoxia Forecasting Modeling Approach

• Model ranging in complexity
• Correlation-based models
• 1D hydrodynamics with simple mechanistic WQ model
• Vertical profiles extracted from full
  hydrodynamic model
• TP, Carbon, Solids
• 3D hydrodynamics with simple mechanistic WQ model
• Physics from full hydrodynamic model
• 3D hydrodynamics with complex mechanistic WQ
  model
• WQ framework similar to Chesapeake Bay ICM model
• Multi-class phyto- and zooplankton, organic and
  inorganic nutrients, sediment digenesis, etc
• Addition of zebra mussels and other improvements

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Chapra, S.C. 1980. J. Great Lakes Res.
6(2)101-112.
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Effect of Phosphorus Controls on Lake Erie
Central Basin Springtime P Concentration (Ryan et
al., 1999)
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Lake Erie 1994 physical/biological model

• Hydrodynamics
• - Great Lakes version of POM
• 20 vertical levels, 2 km horizontal grid (6500
  cells)
• Hourly meteorology (1994, JD 1-365)
• Realistic tributary flows
• Accounts for ice cover
• Mass balance for P
• POM hydrodynamics (2d for now)
• Realistic P loading
• Constant settling velocity (for now)

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• Computer animation of model results
• Starts in January, 1994
• Uses 2d currents from hydrodynamic model
• Time dependent P loads
• Combination Lax-Wendroff and upwind advection
  scheme
• No horizontal diffusion
• Initial condition C 10 ug/L
• Settling velocity 6.8E-7 m/s (21 m/yr)

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Questions?