Operational Environmental Prediction: Nearshore Water Quality

in the Great Lakes

David J. SchwabDavid J. SchwabNOAA Great Lakes Environmental Research NOAA Great Lakes Environmental Research LaboratoryLaboratoryAnn Arbor, MIAnn Arbor, MI

Climate – Meteorology – Hydrology – Climate – Meteorology – Hydrology – Hydrodynamics – Biology/ChemistryHydrodynamics – Biology/Chemistry

Factors Contributing to Nearshore Water Quality in the Great Lakes

Beach Closings

Change in Land-use

Circulation and Bacterial Fate

Meteorology

Hydrology/Water FlowBacterial FateForecastingForecasting

Beach Closings or Beach Closings or HABsHABs

Change in Land-use

Circulation and Bacterial Fate

Meteorology

Hydrology/Water FlowBacterial Fate

Change in Land-use

Outline

1. Lake Michigan tributary modeling using nested-grid hydrodynamic models - application to beach water quality forecasting

2. Lake Erie coupled physical/biological model - application to HAB and hypoxia forecasting

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

+

Lakewide grid(POM model)

Burns Ditch nested model grid

Coupled modelsnested grids

Lake Michigan Beach Quality Forecasting

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 (<sigma>-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

Nested grid hydrodynamic models in Lake Michigan

Burns Ditch 100m computational grid

24 km

6 km

Web site: www.glerl.noaa.gov/res/glcfs/bd

Great Lakes Coastal Forecasting System - Operational Nowcast20 day sample using vertically averaged currents

Lake Erie Coupled Physical/Biological model

The Problem:

- Excessive nutrient loading in the 1960’s 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.

The Problem:

- Excessive nutrient loading in the 1960’s 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

Lake Erie Physical Characteristics:

Surface Area: 25800 km2 Throughflow ~ 6000 m3s-1

Volume: 480 km3 Retention time: 2.5 yrsMean Depth: 18.6 m

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

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

Chapra, S.C. 1980. J. Great Lakes Res. 6(2):101-112.

Effect of Phosphorus Controls on Lake Erie Central Basin Springtime P Concentration (Ryan et al., 1999)

Lake Erie 1994 physical/biological modelHydrodynamics- 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)

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)

QuickTime™ and aCinepak decompressor

are needed to see this picture.

Questions?