A Coastal Ocean Prediction System for Tampa Bay, Florida

Mark E. Luther, Steven D. Meyers, Sherryl A. Gilbert, Vembu Subramanian, MichelleMcIntyre, Monica Wilson, Heather Havens, and Amanda Linville

University of South Florida College of Marine Science

Abstract: The USF College of Marine Science has developed aCoastal Ocean Prediction System for Tampa Bay based on anintegrated observing system and circulation model as a sub-regionalcomponent of the US Integrated Ocean Observing System. Themodel system ingests real-time observations of the physical forcingfunctions for Tampa Bay to produce three-dimensional fields ofcirculation, temperature, salinity, and water level. The hydrodynamicmodel, based on the ECOM-3D code, is fully operational in either anowcast-forecast mode or a hindcast mode and is described on ourweb site (http:Hompl.marine.usf.edu/TBmodel). Water level,temperature, salinity, surface heat and moisture fluxes, and windscome from the Tampa Bay Physical Oceanographic Real-TimeSystem (TB-PORTS; http:Hompl.marine.usf.edu/ports/ orhttp://tidesandcurrents.noaa.gov/tbports/tbports. shtml?port=tb)augmented with observations from the USF Coastal OceanMonitoring and Prediction System (COMPS;http:Hcomps.marine.usf.edu/). Daily river discharge is obtained fromthe USGS National Water Information System. Precipitation isderived from several gauges operated by the Southwest Florida WaterManagement District, USGS, and NOAA. The raw observational dataundergoes an automated QA/QC procedure before being input intothe model. A water quality module has been developed that producesfields of chlorophyll, nutrients, and dissolved oxygen from time-varying estimates of nutrient and fresh water loading. A wavemodule provides directional wave spectra and bottom stresses basedon the SWAN code. The integrated observing and modeling systemprovides a decision support tool that is used to enhance security,safety, and efficiency of maritime transportation, to guide search andrescue efforts, and to evaluate the bay ecosystem response toenvironmental stressors. Such stressors include severe storms,seasonal and interannual changes in fresh water input, as well ashuman impacts, such as hazardous material spills, river withdrawals,nutrient loading, changing land use patterns, and alterations in baybathymetry. In addition to its routine use by the Tampa Bay Pilotsand the US Coast Guard, the Coastal Ocean Prediction System hasbeen used to support management decisions in several environmentalissues affecting the bay. For example, the model has been used toinvestigate the effects of concentrate discharge from a seawaterdesalination facility recently built on Tampa Bay for the regionalwater supply authority; to simulate the trajectory of wastewaterdischarges and hazardous material spills for the Florida Departmentof Environmental Protection; to predict trajectories of raw sewagespills into the bay for the Pinellas County Health Department; toinvestigate transport and fate of human pathogens in the bay, and toevaluate changes in salinity and estuarine residence time due tonatural variability and to anthropogenic alterations in fresh waterinput and bathymetry of the bay for the Southwest Florida WaterManagement District.

INTRODUCTION

There is growing momentum in the US to develop anIntegrated Ocean Observing System for all global and UScoastal waters (IOOS; see http://www.ocean.us). Such anobserving system is central to the recommendations of the USCommission on Ocean Policy and to the President's OceanAction Plan. The IOOS is the US contribution to the GlobalOcean Observing System GOOS), which in turn is acomponent of the Global Earth Observing System of Systems(GEOSS). The IOOS, like the GOOS, consists of a global anda coastal component. The global component, consisting ofmoored buoys, profiling ARGO floats, drifters, and volunteerobserving ships, is approximately 56% completed, with atarget of 2010 for full implementation. The coastalcomponent is being implemented as a federation of regionalsystems connected by a National Backbone of coreobservations and data management. Regional Associations areforming that will operate the regional coastal ocean observingsystems that will contribute to and supplement the NationalBackbone (see http://www.usnfra.org).

The goals of the IOOS are:

* Detecting and forecasting oceanic components ofclimate variability;

* Facilitating safe and efficient marine operations;* Ensuring national security;* Managing resources for sustainable use;* Preserving and restoring healthy marine ecosystems;* Mitigating natural hazards;* Ensuring public health

A fundamental premise in development and design of theIOOS is to "do no harm" to existing ocean observing andmonitoring programs. Many such programs were establishedto address specific issues and would continue to exist in theabsence of an IOOS. Data from these programs can beaggregated into larger scale regional or sub-regional observingsystems that in turn can be integrated into larger scaleobserving systems in a system of systems approach, with littleor no alteration of the original systems.

The IOOS is integrated in two basic ways. First, it combinesmultiple scales of information, from global to national to

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regional to local. Second, it integrates information from manysensor types and sensor systems through a data managementand communications system to produce useful informationproducts for decision makers in coastal and open oceanwaters. Feedback from end-users keeps the system relevant totheir needs.

The end-users of the IOOS are anyone who makes decisionsaffecting or affected by the ocean, from ship captains tocoastal resource managers to climate scientists to recreationalfishermen. Research scientists are but one of many groups ofend-users. While much basic research needs to be done tobuild and improve the IOOS and much good science willfollow from the continuous, sustained observations providedby the IOOS, scientific research is not the primary goal of theIOOS.

One critical issue is the sustainability of some components ofthe observing system. In particular, satellite missions toobserve sea surface height and ocean color are experimental,even though the data are used operationally, with no path forfollow-on missions or for transition to true operational status.

TAMPA BAY PORTS: A SUCCESS STORY

One example of an operational observing system on a smallscale is the Tampa Bay Physical Oceanographic Real-TimeSystem (TB-PORTS; see http://ompl.marine.usf.edu/PORTS).TB-PORTS was the first real-time operational observingsystem of its kind and the first to post coastal ocean data inreal-time to the web. There are now 13 similar systems in thenational PORTS program. TB-PORTS measures winds,currents, and water levels at critical locations in the main shipchannel and port facilities of the bay. Data are telemetered byline-of-sight radio every 6 minutes and are distributed to theharbor pilots and other maritime interests. Because the bay'stides and currents are influenced strongly by nontidal forcessuch as winds and river flow, TB-PORTS provides importantreal-time information to both recreational boaters andprofessional pilots navigating in Tampa Bay. TB-PORTS dataare used to drive a numerical circulation model of the bay inan operational Coastal Ocean Prediction System, developed atUSF, for mitigation of hazardous material spills, forpermitting and monitoring of waste water discharges and freshwater diversions in the bay, and for tracking human pathogens,harmful algal blooms, and fish larvae. Routine uses and usersof TB-PORTS data and information products include:

* Safe, secure, and Efficient Navigation/Tampa BayPilots, Tampa Port Authority, Shipping Agents,USCG

* Hazardous Material Spill Response/FDEP, NOAA-HAZMAT, USCG

* Environmental Protection&Management/FDEP,FWC, EPCHC, Dept. of Health

* Storm Surge Prediction&Mitigation/CountyEmergency Managers, FDEM

* Red Tide Studies&Prediction/FWC, FDEP

* Fisheries Management/FWC, NMFS

* Sediment Transport Studies&Mitigation/USGS,FDEP, USACOE

TB-PORTS was built in 1990 and became operational in 1992.Since that time, ship groundings have decreased by 60%.Loading of bulk cargo has become much more efficient andthe slack current window for bringing large ships throughcurrent-restricted portions of the channel has been widened byseveral hours. A recent study by Kite-Powell (2006) indicatesthat the quantifiable economic benefits of TB-PORTS(reduced ship groundings, increased draft/cargo loading,reduced delays for commercial vessels, improved spillresponse, reduced distress cases, etc.) exceed the operatingcosts by at least a factor of 20 to 50. One example is that shipgroundings have decreased in the bay by 60% since TB-PORTS became operational. Less tangible benefits (e.g.,educational use, scientific research, environmentalmanagement) are not included in the Kite-Powell study butlikely would add another order of magnitude to these estimatesof benefits.

TB-PORTS is a small scale model of how a RegionalAssociation for IOOS might work. TB-PORTS wasdeveloped by the National Oceanic and AtmosphericAdministration (NOAA) National Ocean Service (NOS) incollaboration with the local maritime community and theUniversity of South Florida College of Marine Science. TB-PORTS is operated by a non-profit 501-c(3) corporation, theGreater Tampa Bay Marine Advisory Council-PORTS, Inc.(GTBMAC-PORTS), through a cooperative agreement withthe NOAA National Ocean Service. The non-profitcorporation is governed by a board of directors that includesrepresentatives from all the primary end-users of data andinformation products from the system. GTBMAC-PORTS hasagreements with private-sector contractors to provide routineoperations and maintenance on the system. Local operationsand maintenance of TB-PORTS is funded entirely by local andstate agencies, primarily from trust funds that are derived fromfees on petroleum and phosphate shipping with contributionsfrom some primary users, like the Tampa Bay PilotsAssociation. The system is housed in the USF College ofMarine Science through a separate cooperative agreement withGTBMAC-PORTS. This cooperative agreement provides astipend and tuition for a graduate student to conduct researchusing TB-PORTS data and allows for reimbursement of theuniversity for any direct costs incurred in housing the system.NOS provides continuous operational data qualityassurance/quality control and technical support as in-kindcontributions. This model is scalable to an IOOS RegionalAssociation. The RA might be set up as a non-profitcorporation with a board representing the end users of theRCOOS. The RA would derive funding from local, state, andfederal agencies as well as from end-user contributions andwould have the authority to operate the RCOOS through

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cooperative agreements with NOAA. The RA would providefor operation of the RCOOS through cooperative agreementsand/or contracts with both pubic and private sector entities.

TAMPA BAY COASTAL OCEAN PREDICTION SYSTEM

The USF College of Marine Science has developed CoastalOcean Prediction System for Tampa Bay by combining theTB-PORST data stream with an integrated circulation, wave,sediment transport, and water quality model for the bay. Themodel system ingests real-time observations of the physicalforcing functions for Tampa Bay to produce three-dimensionalfields of circulation, temperature, salinity, wave spectra,sediment resuspension and transport, turbidity, primaryproduction, chlorophyll, nutrients, dissolved oxygen, and otherbiogeochemical quantities. The need for a detailed three-dimensional integrated water quality model has becomeapparent in Tampa Bay management issues. Thehydrodynamic model is fully operational in either a nowcast-forecast mode or a hindcast mode and is described on our website (http://ompl.marine.usf.edu/TBmodel). The wave andsediment transport component of the model has beenimplemented (Shi et al., 2006) and tested against observationsmade in December 2001 and January 2002 and in Maythrough August 2002. The water quality model component isbeing used to evaluate the effects of regional water supplyprojects and phosphate discharges into the bay. The integratedmodel has been and will continue to be calibrated andvalidated against extensive observational data available forTampa Bay collected by the Tampa Bay Estuary Program(TBEP), the Environmental Protection Commission ofHillsborough County (EPCHC), the US Geological Survey,and others. The integrated model provides a management toolthat can be used to evaluate the bay ecosystem response tosevere storms or to seasonal and interannual changes in freshwater input, as well as to changes due to human impacts, suchas river withdrawals, nutrient loading, changing land usepatterns, or alterations in bay bathymetry. The model systemhas been used to support management decisions in severalenvironmental issues affecting the bay. For example, themodel was used to simulate the trajectory of the dischargefrom the Piney Point phosphate plant that occurred in Octoberand November of 2001 for the Florida Department ofEnvironmental Protection (Figure 1) and to evaluate changesin salinity and estuarine residence time in the Palm River andMcKay Bay for the Southwest Florida Water ManagementDistrict (Figure 2).

Circulation Model

The circulation model has been under development at USFsince 1990. It is a three-dimensional time-dependent model ofthe hydrodynamics of circulation in Tampa Bay (Galperin etal., 1992a,b; Vincent, et al., 1997, 2000), based upon anadvanced version of the Princeton Ocean Model (Blumbergand Mellor, 1987). The governing equations consist ofconservation of mass and momentum and conservation

equations for thermal energy and salt. Equations are alsosolved for the turbulence kinetic energy and turbulencemacroscale. Salient features include a curvilinear orthogonalgrid in the horizontal plane and a bed and free surfacefollowing sigma coordinate system in the vertical axis.Turbulence closure is provided by an embedded Mellor-Yamada 2.5 level closure submodel (Mellor and Yamada,1982) as modified by Galperin. Time splitting allows for thefast external or barotropic waves to be solved for explicitly,and the slower internal baroclinic waves implicitly. Specifiedforcing boundary conditions include the free surface elevationand temperature/salinity profiles at the open water boundary;the flow rate, temperature, salinity and level of inflows oroutflows; surface heat flux; surface wind stress, precipitation,and evaporation. Among the important parameters computedare free surface height, magnitude and direction of currentvelocity fields, and temperature and salinity fields.

Figure 1: Simulated trajectory of the discharge plume from thePiney Point phosphate plant into Bishops Harbor. Color is time inhours past 0 UTC on November 15, 2001 (color scale to right). Thecentroid of all particles is indicated by the black symbols and theposition is given in latitude and longitude in the columns to the farright. No particles exit Bishops Harbor for the first 75 hours. Afterthis time, two groups of particles exit Bishops Harbor and aretransported toward the southwest. The first group of particles quicklyleaves Tampa Bay through Southwest Passage within 90 hours. Thesecond group recirculates within the bay and are trapped to the southof the Skyway Bridge and just north of Anna Maria Island.

The present version of the Tampa Bay model uses a 70-by-O00horizontal curvilinear grid (Figure 3) with 11 sigma levels inthe vertical (Figure 4). Boundary conditions for the TampaBay model are provided by the PORTS data stream. InNowcast/Forecast mode, the model is automatically updatedevery 12 minutes to provide a "nowcast" of present conditionsin the bay. Every 4 hours, a 25 hour forecast is performed

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using winds from the National Weather Service ETA modeland water levels at the mouth of the bay extrapolated frompresent observations and forecasts of offshore conditions.Model nowcast and forecast fields are presented in graphicalformat and can be viewed on the OMPL Web site(http://ompl.marine.usf.edu/TBmodel) and can be obtained viaa DODS (Distributed Ocean Data System) server. The DODSinterface to the model fields was designed in collaborationwith the NOAA HAZMAT office to assist in hazardousmaterial spill response and contingency planning.

Figure 3: 70 x 100 horizontal curvilinear orthogonal grid withTampa Bay PORTS observing sites

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Figure 2: Salinity in McKay Bay and Palm River for the baselinecase (top), the Tampa Bay Water permitted withdrawal (middle), andan intermediate withdrawal case (bottom). The vertical axis is depthin meters and the horizontal axis is distance along the section.Structure 160 is at the far right of the figure and the 22nd St. Causwayis at the far left edge. Both withdrawal cases show salinities elevatedby 0.5 to 1 psu (or part per thousand) throughout the water column.

Trajectory Model

The hydrodynamic model output velocity fields drive atrajectory model to predict the movement of hazardousmaterial spills or persons or objects in the water in TampaBay. Trajectories are treated as a cloud of a large number ofLagrangian particles, each modeled by a first order Markovprocess using instantaneous velocities from the hydrodynamicmodel and a dispersion coefficient calibrated using observeddrifter tracks. Trajectory predictions have been verified by alimited number of GPS and radio-tracked drifters.

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-19_Figure 4: Typical cross section of 11 sigma layers in the verticaldimension

The information on contaminant distribution from thetrajectory model can be ingested into the Florida Fish andWildlife Research Institute's Marine Spill Assessment andResponse System (FMSAS), a GIS-based spill mitigation tool.The predicted distribution of contaminant from the spill modelforms a layer in the FMSAS database and can be used as a

template to cut through the resources-at-risk data layers toarrive at an inventory of resources exposed. Predictedtrajectories can be generated in real-time via a web-based formthat is linked to the USCG Area Contingency Plan foremergency response or for search and rescue.

The trajectory model has been used to evaluate the fate of an

accidental release of raw phosphate process water into Tampa

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Section across bay (not to scale)

Bay during Hurricane Frances in September 2004 (Wilson etal. 2006) and to study the transport of harmful algal bloomsand enteroviruses in the bay (Figure 5; Havens et al., 2007).

Residence Time

Estuarine residence time is estimated by seeding each modelgrid cell with large numbers of particles or with a passivetracer, as described above for the trajectory module (Burwellet al., 2000). The e-folding time for particle concentration iscomputed in each grid cell under a variety of boundaryconditions observed in the bay (Figure 6). The resultingresidence times vary widely in space and time. Residencetime is most sensitive to variations in wind forcing and tovariations in fresh water input.

Residence time is controlled by the non-tidal residual axialcurrent, which is dominated by the buoyancy-driven barocliniccirculation with an outflow (southwestward) at the surface andto the sides of the shipping channel, and an inflow(northeastward) usually occurring subsurface within or abovethe shipping channel. The strength of the non-tidal circulationvaries greatly with changes in fresh water input and windstress, from 3 times the mean value to essentially zero.Residence time similarly is modulated by changes in freshwater inflow and winds. The effects of human alterations onthe flushing of the bay are investigated by replacing themodem bathymetry with one based on depth soundings from1879. Present day flushing times are increased inside ofcauseways but decreased in the dredged ship channel relativeto pre-development conditions.

Wave Model

The SWAN wave model is coupled to the circulation modeland computes wave spectra at each model grid cell underobserved wind conditions and modeled water velocity (Shi etal., 2006). Wind stress forcing and bathymetry for the wavemodel are the same as that used for the hydrodynamic model.Bed stresses are computed as a superposition of stresses due towave orbital velocity and those computed by thehydrodynamic model. The information on bed stresses arecombined with data on sediment type, compiled by USGS, tocompute sediment resuspension. The velocity field from thehydrodynamic model is combined with the information onsediment resuspension and settling velocity to computesediment transport. Turbidity and nutrient flux due tosediment resuspension will provide input to the water qualitymodel component.

During December 2001 and January 2002, four Sea BirdElectronics SeaGauge wave and tide recorders were deployedin Tampa Bay in each major bay segment. Since May 2002, aSeaGauge has been continuously deployed at a site in middleTampa Bay as a component of the Bay Regional AtmosphericChemistry Experiment (Mizak et al., 2007; Sopkin et al.,2007) (BRACE; see http://ompl.marine.usf.edu/BRACE).

Preliminary analyses of these wave data show good agreementwith modeled wave spectra at each site.

Water Quality Model

The water quality component of the model system takesinformation from the circulation and wave components tocompute primary production, chlorophyll, turbidity, nutrients,dissolved oxygen, and other biogeochemical quantities. Thewater quality model code has been implemented by JanickiEnvironmental, Inc. Higher resolution sub-model grids have

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0.000 0.160 0.320 0.480 0.640 0.800Figure 5: Transport quotient (a measure of probability) of modeledred tide distribution over 30 day periods from June-August 2005. a-c:

particles released in Egmont Channel. d-f: particles released inSouthwest Pass.

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Figure 6: Residence time based on the Lagrangian particle trajectorymethod for boundary conditions observed during the fall and winterof 1997-98. Color represents e-folding time in days, or the timerequired for the number of particles in a grid cell to decrease by 65%.Residence times in Lower Tampa Bay and in areas adjacent to themain channels are 10 to 20 days or less, while on shoals and in areasrestricted by causeways, they exceed 140 days.

been developed to better resolve the main channels andimportant sub-basins of the bay, like the McKay Bay-PalmRiver system. In the integrated model, waves, sedimentresuspension and transport, and water quality variables arecomputed on the same grid as used by the three-dimensionalhydrodynamic circulation model. The water qualitycomponent utilizes the CEQUAL/ICM code. Much of thismodel was developed with EPA funding and is considered thestate-of-the-art in water quality modeling. Data from EPCHC,TBEP, BRACE, and the US Geological Survey are used formodel calibration/validation and to set the boundaryconditions for nutrient loading of the bay. The integratedmodel is being used to evaluate phosphate process waterdischarges into Bishops Harbor and to evaluate Tampa BayWater's Downstream Augmentation proposals.

REFERENCES

Blumberg, A. and G. L. Mellor, 1987. A description of athree-dimensional coastal ocean circulation model. In:Three-Dimensional Coastal Ocean Models, N. S. Heaps,Ed., American Geopgys. Union, Washington, DC, pp 1-

Galperin, B., A. Blumberg, and R. Weisberg. 1992a. A time-dependent three dimensional model of circulation inTampa Bay. Pages 77-97 in S. Treat and P. Clark, eds.,Proceedings of the Tampa Bay Area ScientificInformation Symposium 2, Tampa, FL, February 27-March 1, 1991.

Galperin, B., A. Blumberg, and R. Weisberg. 1992b. Theimportance of density-driven circulation in well-mixedestuaries: The Tampa Bay experience. Pages 332-343 inthe Proceedings of the 2nd International Conference onEstuarine and Coastal Modeling, Tampa, FL, November13-15, 1991.

Havens, H. H., M. E. Luther, S. A. Meyers, and C. Heil, 2007.Lagrangian analysis of a harmful algal bloom within theTampa Bay estuary. Geophys. Res. Lett. (Submitted).

Husick, C., 1999: Tampa Bay setting the pace withAutomatic Identification System. Professional Mariner,38, 37-79.

Meyers, S., M. Luther, M. Wilson, H. Havens, A. Linville,and K. Sopkin, 2007. A Numerical Simulation ofResidual Circulation in Tampa Bay. Part I: Low-Frequency Temporal Variations. Estuaries and Coasts (Inpress).

Mizak, C., S. Campbell, K. Sopkin, S. Gilbert, M. Luther, andN. Poor, 2007. Effect of shoreline meteorologicalmeasurements on NOAA buoy model predictions of air-sea gas transfer. Atmospheric Environment, 41, 4304-4309.

Shi, J. Z., M. E. Luther, and S. Meyers, 2006. Modelling ofwind wave-induced bottom processes during slack waterperiods in Tampa Bay, Florida. International Journal forNumerical Methods in Fluids, 52:1277-1292.

Sopkin K., C. Mizak, S. Gilbert, V. Subramanian, M. Luther,and N. Poor, 2007. Modeling Air/Sea Flux Parameters ina Coastal Area: A Comparative Study of Results from theTOGA COARE Model and the NOAA Buoy Model.Atmospheric Environment, doi: 10.10 16/j .atmosenv.2006.08.059.

Vincent, M., D. Burwell, M. Luther, and B. Galperin, 1998.Real-time data acquisition and modeling in Tampa Bay.in Estuarine and Coastal Modeling, M. Spaulding and A.Blumberg, eds., ASCE, Reston, VA, pp 427-440.

Vincent, M., D. Burwell, and M. Luther, 2000. The TampaBay Nowcast-Forecast system. in Estuarine and CoastalModeling, M. Spaulding and H. Butler, eds., ASCE,Reston, VA, pp 765-780.

Wilson, M., S.D. Meyers and M. Luther 2006. Changes in theCirculation of Tampa Bay Due to Hurricane Frances asrecorded by ADCP measurements and reproduced with aNumerical Ocean Model. Estuaries and Coasts, Vol 29,No 6A, P 914-918.

16.Burwell, D., Vincent, M., Luther, M., Galperin, B., 2000.

Modeling Residence Times: Eulerian vs Lagrangian. In:Estuarine and Coastal Modeling, M. L. Spaulding and H.L. Butler, eds., ASCE, Reston, VA, pp 995-1009.

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