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Development of the Neuse Estuary Eutrophication Model: Background and Calibration By James D. Bowen UNC Charlotte Neuse River Estuary Model Pamlico Sound Applied Water Quality Modeling Research Neuse Estuary Neuse River Estuary Facts About the Neuse River

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Development of the Neuse Estuary Eutrophication Model: Background and Calibration


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development of the neuse estuary eutrophication model background and calibration

Development of the Neuse Estuary Eutrophication Model: Background and Calibration

By

James D. Bowen

UNC Charlotte

neuse river estuary model
Neuse River Estuary Model

Pamlico

Sound

Applied Water

Quality Modeling

Research

Neuse

Estuary

facts about the neuse river
Facts About the Neuse River
  • 3rd Largest River Basin in NC (6,234 mi2)
  • 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
neuse river problems algal blooms
Neuse River Problems: Algal Blooms

Blue-GreenAlgae Bloom near New Bern

low do and fish kills 94 96
Low DO and Fish Kills: 94-96

Cherry Point

Streets

Ferry

water quality research project
Water Quality Research Project

MODMON = MODeling and MONitoring

  • Interdisciplinary Applied Research
    • Water Quality and Biological Monitoring
    • Water Quality Modeling to predict w.q. improvement (30% nutr. red.)
neuse estuary eutrophication model10
Neuse EstuaryEutrophicationModel

Water Column

Biological Processes

special features of modeling
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
neuse estuary eutrophication model14
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
w2 phytoplankton growth model

1

m /mmax

0

Light,

Nutrients

W2 Phytoplankton Growth Model

1

T.R.M.

0

Topt

Temperature

m = mmax * min(m / mmax) * T.R.M.

w2 x section representation

S1

S1

S2

S2

S3

S3

S4

W2 X-section Representation
  • trapezoidal cross-sections for each segment

Layer 1

Layer 4

Sediment

Compartments

  • quasi-3d sediment/water-column interaction model
w2 sediment submodel
W2 Sediment Submodel
  • simple sediment diagenesis model
    • 1 constituent: Sediment organic carbon (SOC)
    • SOC fate processes:
      • redistribution, decomposition
    • SOD decomposition rate determines fluxes:
      • O2 demand, PO4 release, NH3 release
    • N, P, S, Fe redox reactions not considered
      • e.g. NH3/NO3, NO3/N2, SO4/H2S
    • can simulate sediment “clean-up”
1991 simulation description
1991 Simulation Description
  • Time Period:
    • March 1 - September 27, 1991
  • Boundary Data Frequency
    • Daily Flow and NO3, 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
other model characteristics
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
neuse estuary model results transport model
Neuse Estuary Model Results Transport Model
  • Water elevations
    • time histories
    • spectral analysis
  • Salinity distributions
    • time histories @ one segment
    • animations
elevations @ cherry point
Elevations @ Cherry Point

Observed

Model

March

April

May

water level @ new bern
Water Level @ New Bern

MAE = 0.1 m

Julian Day

elev fluctuations power spectrum
Elev. Fluctuations - Power Spectrum

Observed

@ Cherry Point

n = 0.020

Amplitude (m)

Model

Frequency (Cycles/day)

salinities @ cherry point

0

4

8

12

16

Salinities @ Cherry Point

Model: Surface

Observed: Top

Bottom

Salinity (ppth)

Model: Bottom

May

Sep

Mar

July

slide31

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
1991 wq simulations
1991 WQ Simulations
  • Single parameter displays
    • Nitrate
    • Phytoplankton
    • Cumulative chl-a
  • Multi-parameter display
    • New Bern time history
water quality prediction new bern

Sal.

NOx

DO

Chl

Water Quality Prediction - New Bern

0

Surface

Middle

6

.5

0

Surface

10

Middle

4

50

0

May

Sep

Mar

July

calibration summary
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
summary continued
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