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Jamie Vaudrey, Department of Marine Sciences, UConnjamie.vaudrey@uconn.edu CHRP EPA WorkshopModel Skill in Predicting Hypoxia in Narragansett BayJuly 7, 2015Using EcoGEM to Predict HypoxiaMotivation, Rationale & ObjectivesAs part of a NOAA Coastal Hypoxia Research Program project:Apply a novel, reduced complexity, parsimonious ecological model to predict hypoxia in Narragansett Bay.Implement within a fast running, coarse boxed scheme linked to a fine resolution hydrodynamic model. Simulate responses to nutrient reductions and climate change.Make the model available for direct use by managers.

Motivation2

Highly resolved hydrodynamic model (ROMS) linked to a coarse boxed scheme.figure courtesy of Dave Ullman, URIlinking ROMS to EcoGEMhydrodynamic forcing of the model, the link to ROMSgrids, how the two models are linked3

figure courtesy of Dave Ullman, URIDye initialized in an element at 12am each day, allowed to mix for 24h, fate of dye yields exchange coefficient for the day. Gross Exchange Matrix (GEM) is a 3-d array detailing exchange among all elements for each day.time = 0:00time = 24:00linking ROMS to EcoGEMhydrodynamic forcing of the model, the link to ROMSgrids, how the two models are linked4linking ROMS to EcoGEM

1 / dmany / dPhysicalBiologicalStructure of program: boxes are mixed at start of each day biology state variables are formulated as differential equations biology is allowed to integrate for 24 h (Runge-Kutte 3,4 integration scheme)hydrodynamic forcing of the model, the link to ROMSgrids, how the two models are linked

5DO2 N PNLand-useAtmosphericdepositionN PProductivityTemp, Light,Boundary ConditionsChl, N, P, SalinityPhytoplankton.. PhysicsSurface layer

- - - - - - - - -

Deep layer

- - - - - - - - - Bottom sedimentFlux tobottomPhotic zoneheterotrophyBenthicheterotrophyDenitri-ficationO2 coupledstoichiometricallyBZI(Chl2d)[Chl](OM,T)%Processes of the model & basis for formulations: mixing flushingonly 17 constants and coefficientsBenthic Cmodel diagram, in Odum Energy Systems Language; https://en.wikipedia.org/wiki/Energy_Systems_Language overview of ecological model6

TDNTDPDINDIP

organic nutrientsinorganic and organic nutrients enter via rivers and groundwater10% of dissolved organic nutrients are available (labile)*within the estuary, results are compared to inorganic nutrientsmodel coverts organic to inorganicorganic nutrients in estuarine waters are largely refractoryExplanation of when DON is used for boundary, but not for in-water comparisonsAssume 10% of DON is labile

7organic nutrients

Valiela, I., S. Mazzilli, J.L. Bowen, K.D. Kroeger, M.L. Cole, G. Tomasky, and T. Isaji. 2004. ELM, An Estuarine Nitrogen Loading Model: Formulation and Verification of Predicted Concentrations of Dissolved Inorganic Nitrogen. Water, Air, & Soil Pollution 157(1-4): 365-91.groundwater: 10% of initial DON is labileatmospheric deposition: 40% of initial DON is labileExplanation of when DON is used for boundary, but not for in-water comparisonsAssume 10% of DON is labile

8Perry, R. and J.M.P. Vaudrey (2015, in prep) Fate of organic N in a small, shallow estuary. technical report, Dept. of Marine Sciences, UConn.organic nutrientsExplanation of when DON is used for boundary, but not for in-water comparisonsAssume 10% of DON is labile9Perry, R. and J.M.P. Vaudrey (2015, in prep) Fate of organic N in a small, shallow estuary. technical report, Dept. of Marine Sciences, UConn.organic nutrientsDON refractory in estuarine water10% lability for DON may be highExplanation of when DON is used for boundary, but not for in-water comparisonsAssume 10% of DON is labile10forcing conditionsForcing ConditionsROMS forcing functions described by Dave Ullman--------------------------------------------------------------------light from Eppley Labs, Newport, RIwind from T.F. Green Airportfor exchange of oxygen with the atmosphereprecipitation from T.F. Green Airportfor nutrient loads from wet and dry depositionwater temperature from ROMS

forcings sources and methods11Boundary Conditionsassume salt = 0 ppt in riversbenthic carbon is not transferred among elements-------------------------------------------------------------------N and P = river concentration * flow (m3)phytoplankton = surface buoy data at boundaryoxygen = surface buoy data at boundaryboundary conditionsboundary conditions sources and methods12

boundary conditionsN and P

concentration from NBC data ( ) or WWTF data linear interpolation between dates for missing days

flow from ROMS model, partitioned based on USGS river flow databoundary conditions sources and methods13

boundary conditionswidth of arrows indicate relative magnitude of volume inputboundary conditions sources and methods14boundary conditionsrivers from Phillipsdale buoy, surfaceboundary conditions sources and methods15Skill AssessmentData DiscrepancyModel predicts a box-wide, daily average. Field data are not strictly comparable:buoys a fixed location, 15 minute data (can get daily average)CTD surveys many locations, but infrequent (can get box-wide average)nutrient and productivity surveys few locations, few datesA perfect skill is not expected and is highly unlikely.

skillskill assessmentissues with relating a box-wide daily average to point samples in space (buoy data) or time (CTD surveys)16

Relative Operating Characteristic (ROC) curveused for evaluating models in many fieldscompares the hit rate to the false alarm rate> 0.5 = skilled; 1 = perfect skillevaluates all elements at once whole model

Mason, S. J., and N. E. Graham. 1999. Conditional probabilities, relative operating characteristics, and relative operating levels. Weather and Forcasting 14: 713-725.Sheng, Y. P., and T. Kim. 2009. Skill assessment of an integrated modeling system for shallow coastal and estuarine ecosystems. J. Mar. Syst. 76: 212-243.

hit rate =mod+obs+thresholds every 5.4 ppt, yielding 20 evaluationsfalse alarm rate =mod+obs-salinity0.97skillMason, S. J., and N. E. Graham. 1999. Conditional probabilities, relative operating characteristics, and relative operating levels. Weather and Forcasting 14: 713-725.Sheng, Y. P., and T. Kim. 2009. Skill assessment of an integrated modeling system for shallow coastal and estuarine ecosystems. J. Mar. Syst. 76: 212-243.17

O2 buoy0.89O2 CTD0.80Phyto buoy0.69N survey0.88Skill ROC, whole model> 0.5 = skilled; 1 = perfect skillskill

Skill by element (just O2 shown)skill

Water Column Productionskill

Water Column Respirationskillskill assessmentissues with relating a box-wide daily average to point samples in space (buoy data) or time (CTD surveys)21Sediment Rates

blue = modelgreen = core dataonly 25 data points, from 2005 & 2006model data are from corresponding element on corresponding daydata from: Fulweiler, R.W., S.W. Nixon, B.A. Buckley, and S.L. Granger. 2007. Reversal of the net dinitrogen gas flux in coastal marine sediments. Nature 448, no. 7150: 180-82.skillPredicting Hypoxiawant to compare the model prediction of a box-wide daily average to a minimum daily value for the box

use the buoy data to develop this relationshippredictions of hypoxia method23

regression equation relates average daily O2 to minimum O2 using buoy dataSurface and Bottom for Buoy Data:

(1/2) - BR(3/4) - BRBullocks R. (5/6)Conimicut P. (5/6)N. Prudence (7/8)(9/10) CP + PPGreenw. B. (11/12)Sally Rock (13/14)Mt. View (15/16)Pop. Pt. (17/18)Mt. Hope B. (19/20)Quons. Pt. (21/22)(23/24) - PPpredictions of hypoxia method24

11225261424281717102002006(281)Predicted # of days below 2.9 mg/L.

Estimated using regression relationship between buoy daily minimum and buoy daily average.predictions of hypoxia - results25

1122526142428171710200

12163018344000002007(198)2006(281)predictions of hypoxia - results26

1011016518293710002009 worst(194)1122004160000002009 best(138)predictions of hypoxia - results27What EcoGEM can and cannot doCannot utilize new physical forcings to get at effects of changes in river flow or stratification needs ROMS for this.2006 and 2007 were good years in terms of differences so able to predict new years by bracketing (as for 2009). -- need to apply appropriate nutrient reduction, relative to 06-07 -- if boundary conditions for the year are available, use This model can be used to explore the effects of nutrient reductions and temperature changes associated with climate change.Publications and ProductsVaudrey, J.M.P., M.J. Brush, and D. Ullman (in prep) Chapter 5: Modeling estuarine hypoxia in Narragansett Bay, R.I. with an intermediate-complexity approach. in: Modeling Coastal Hypoxia: Numerical Simulations of Patterns, Controls and Effects of Dissolved Oxygen Dynamics, eds: J. Dubravko, K.A. Rose, R.D. Hetland, K. Fennel. Springer Publishing.Ganju, N.K., M. J. Brush, B. Rashleigh, A.L. Aretxabaleta, P. del Barrio, M. Forsyth, J.S. Grear, L.A. Harris, S.J. Lake, G. McCardell, J. ODonnell, D.K. Ralston, R.P. Signell, J.M. Testa, and J.M.P. Vaudrey (in press) Progress and challenges in coupled hydrodynamic-ecological estuarine modeling. Estuaries and Coasts.Kremer, J.N., J.M.P. Vaudrey, D.S. Ullman, D.L. Bergondo, N. LaSota, C. Kincaid, D.L. Codiga, and M.J. Brush (2010) Simulating property exchange in estuarine ecosystem models at ecologically appropriate scales. Ecological Modelling. 221: 1080-1088.Vaudrey, J.M.P. and J.N. Kremer (2015) Narragansett Bay EcoGEM Model. technical report. Department of Marine Sciences, University of Connecticut.Vaudrey, J.M.P. (2015) EcoGEM Hybrid Physical-Ecological Model of Narragansett Bay, RI. NarrBayEcoGEM.exeVaudrey, J.M.P. (2015) Users Guide to NarrBayEcoGEM.exe

publications and products29