1. Development of the Neuse Estuary Eutrophication Model: Background and Calibration By James D. Bowen UNC Charlotte

2. Neuse River Estuary Model Neuse Estuary Pamlico Sound Applied Water Quality Modeling Research

3. Neuse River Estuary

4. Facts About the Neuse River 3rd Largest River Basin in NC (6,234 mi 2 ) 200 miles long, 3000 stream miles Estuary in lower 50 miles 1.5 million people in basin, mostly near headwaters Nutrient loading has doubled since 70’s

5. Neuse River Problems: Algal Blooms Blue-GreenAlgae Bloom near New Bern

6. 1997 Bottom Water DO Conc. Neuse River Problems: Low DO

7. Low DO and Fish Kills: 94-96 Cherry Point Streets Ferry

8. Water Quality Research Project MODMON = MOD eling and MON itoring Interdisciplinary Applied Research –Water Quality and Biological Monitoring –Water Quality Modeling to predict w.q. improvement (30% nutr. red.)

9. Neuse Estuary Eutrophication Model Physical Processes

10. Neuse Estuary Eutrophication Model Water Column Biological Processes

11. Neuse Estuary Eutrophication Model Benthic/Water- Column Interactions

12. Neuse Estuary Eutrophication Model

13. Special Features of Modeling Unusually challenging system to model intermittent, weak stratification (wind driven) no strong tidal forcing sediments have important effects on nutrient and DO dynamics blooms of several different phytoplankton groups @ different times and places

14. Neuse Estuary Eutrophication Model based upon 2-d laterally averaged model CE-Qual-W2 Nutrient, phytoplankton, organic matter, DO model 3 phytoplankton groups (V.3) –summer assemblage, diatoms, dinoflagellates

15. W2 Phytoplankton Growth Model 0 1  /  max Light, Nutrients  =  max * min  /  max ) * T.R.M. Temperature 0 1 T.R.M. T opt

16. W2 X-section Representation trapezoidal cross-sections for each segment Layer 1 Layer 4 S1S2S3 S4 S1S2S3 Sediment Compartments quasi-3d sediment/water-column interaction model

17. W2 Sediment Submodel simple sediment diagenesis model –1 constituent: Sediment organic carbon (SOC) –SOC fate processes: redistribution, decomposition –SOD decomposition rate determines fluxes: O 2 demand, PO 4 release, NH 3 release –N, P, S, Fe redox reactions not considered e.g. NH 3 /NO 3, NO 3 /N 2, SO 4 /H 2 S –can simulate sediment “clean-up”

18. 1991 Simulation Description Time Period: –March 1 - September 27, 1991 Boundary Data Frequency –Daily Flow and NO 3, monthly WQ Hydrodynamic Calibration Data –hrly. water elevations, salinities, velocities @ 3 estuary stations WQ Calibration Data –monthly mid-water nutrients, DO, chl-a @ 4 estuary stations

19. H 2 O & N Inflows - 1991

20. Inflow N/P molar ratio - 1991 Redfield Ratio

21. Other Model Characteristics 62 horizontal segments, 18 layers execution time step = 10 min. 2 branches: Neuse & Trent Rivers 12 tributaries: 9 creeks, 3 WWTP’s 16 state variables Boundary Conditions: Flow @ Streets Ferry, Elevation @ Oriental

22. Neuse Estuary Model Results Transport Model Water elevations –time histories –spectral analysis Salinity distributions –time histories @ one segment –animations

23. Elevations @ Cherry Point MarchAprilMay Observed Model

24. Water Level @ New Bern Julian Day MAE = 0.1 m

25. Elev. Fluctuations - Power Spectrum Observed Model @ Cherry Point n = 0.020 Frequency (Cycles/day) Amplitude (m)

26. Salinities @ Cherry Point Model: Surface Model: Bottom Observed: Top Bottom Mar May July Sep Salinity (ppth) 0 4 8 12 16

27. Modeled Salinities - September 1991

28. 1991 Predicted Salinities: May - Sept. animation

29. Neuse Estuary - 1991 Nitrogen

30. Neuse Estuary - 1991 Chl-a Conc.’s

31. WQ Conditions: Summary Seasonal/Spatial Trends nutrients decreasing downstream April mid-estuary phytoplankton bloom June upper-estuary phytoplankton bloom several pulses of high NOx conc. @ New Bern August high-flow event –high nutrients, low chl-a @ New Bern –high Sept. chl-a @ New Bern

32. 1991 WQ Simulations Single parameter displays –Nitrate –Phytoplankton –Cumulative chl-a Multi-parameter display –New Bern time history

33. Modeled Nitrate - September 1991

34. 1991 Predicted Nitrates: May - Sept. animation

35. Modeled DO - September 1991

36. 1991 Predicted DO: May - Sept. animation

37. Modeled chl-a - September 1991

38. 1991 Predicted chl-a: May - Sept. animation

39. Water Quality Prediction - New Bern Surface Middle Sal. NOx DO Chl Mar May July Sep Middle 0 6 0 0.5 4 10 50

40. Calibration Summary Transport Model –elevation variations predicted within 0.1 m –salinity variations within 2 ppth –dynamics nicely represented Water Quality Model –blooms of phytoplankton well represented –seasonal variations also represented –New Bern chl-a shows influence of physical processes

41. Summary, continued Water Quality Model –DO dynamics fit expectations based on 1997 monitoring Overall model performance –consistent with previous modeling efforts –sufficient for water quality improvement predictions