Development of the Neuse Estuary Eutrophication Model:

Background and Calibration

By

James D. Bowen

UNC Charlotte

Neuse River Estuary Model

Neuse Estuary

PamlicoSound

Applied WaterQuality ModelingResearch

Neuse River Estuary

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

Blue-GreenAlgae Bloom near New Bern

0 .0 0

2 .0 0

4 .0 0

6 .0 0

co n c .(m g /l)

J u n e J u ly S ep tem b erA u gu st

S tree tsF erry

N ewB ern

C h erryP o in t

O rien ta l

E stu a ryM o u th

-70

-60

-50

-40

-30

-20

-10

0

Dis

tan

ce D

own

stre

am (

km

)

1997 Bottom Water DO Conc.

Neuse River Problems: Low DO

Low DO and Fish Kills: 94-96

Cherry Point

StreetsFerry

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 EstuaryEutrophicationModel

PhysicalProcesses

P a m lico S o u n d

E x ch an ge

A tm o sp h er e

L oa ding s E x ch an ge

R iver s, C reek s ,G ro u n d w a ter

O rg a n ic M a tter

D isso lvedO x yg en

A lg a eN euse R iver E stu ary

N u tr ien ts

V erticalM ixing

E stu ar in eC irculatio n

Sedim ents

Neuse EstuaryEutrophicationModel

Water ColumnBiological Processes

P a m lico S o u n dA tm o sp h ereR ive r s, C r eek s ,G r o u n d w a te r

O rg a n ic M a tter

D isso lve dO x yg en

A lg a eN euse R iver E stu ary

N u tr ien tsIn o rg a n ic

C a rb o n

G row th/M orta lity /R ecyc ling

Sedim ents

Neuse EstuaryEutrophicationModel

Benthic/Water-Column Interactions

P a m lico S o u n dA tm o sp h ereR ive rs, C reek s ,G ro u n d w a ter

O rg a n ic M a tter

D isso lvedO x yg en

A lg a eN euse R iver E stu ary

N u tr ie n tsIn o rg a n icS ed im en ts

B e n th ic O r g an ic M a tte r

In o rg a n icC a rb o n

Sedim entE x ch an ge

Sedim ents

Neuse Estuary EutrophicationModel

P a m lico S o u n d

E x ch an ge

A tm o sp h ere

L oa ding s E x ch an ge

R ive r s, C r eek s ,G r o u n d w a te r

O rg a n ic M a tter

D isso lve dO x yg en

A lg a eN euse R iver E stu ary

N u tr ien tsIn o rg a n icS ed im en ts

B e n th ic O r g an ic M a tte r

In o rg a n icC a rb o n

Sedim entE x ch an ge

V erticalM ixing

E stu ar in eC irculatio n

G row th/M orta lity /R ecyc ling

Sedim ents

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 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

0

1

/max

Light,Nutrients

= max * min/ max) * T.R.M.

Temperature

0

1

T.R.M.

Topt

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

Layer 1

Layer 4S1S2

S3S4

S1S2

S3Sediment Compartments

• quasi-3d sediment/water-column interaction model

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• 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

H2O & N Inflows - 1991

0

100

200

300

400

0

5,000

10,000

15,000

20,000

59 89.43 119.9 150.3 180.7 211.1 241.6 272

Infl

ow (

m3 /s

) N load (kg/d)

MayApr AugJun Jul SepMar

Flow

Average Flow

Inflow N/P molar ratio - 1991

15

20

25

30

59 89.43 119.9 150.3 180.7 211.1 241.6 272

N t

o P

Rat

io (

mol

N/m

ol P

)

MayApr AugJun Jul SepMar

Redfield Ratio

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 ResultsTransport Model

• Water elevations– time histories

– spectral analysis

• Salinity distributions– time histories @ one segment

– animations

Elevations @ Cherry Point

March April May

Observed

Model

Water Level @ New Bern

Julian Day

MAE = 0.1 m

Elev. Fluctuations - Power Spectrum

Observed

Model

@ Cherry Pointn = 0.020

Frequency (Cycles/day)

Am

pli

tud

e (m

)

Salinities @ Cherry Point

Model: Surface

Model: Bottom

Observed: Top Bottom

Mar May July Sep

Sal

init

y (p

pth

)

0

4

8

12

16

Modeled Salinities - September 1991

1991 Predicted Salinities:May - Sept. animation

Neuse Estuary - 1991 Nitrogen

0.01

0.1

1NB NO

3

NB NH3

CP NO3

CP NH3

59 89.57 120.1 150.7 181.3 211.9 242.4 273

Con

cent

ratio

n (m

g/L

)

Mar Apr May Jun Jul Aug Sep

Neuse Estuary - 1991 Chl-a Conc.’s

0

20

40

60

80

100

NB Chl-aCP Chl-a

59 89.57 120.1 150.7 181.3 211.9 242.4 273

Con

cent

ratio

n (u

g/L

)

Mar Apr May Jun Jul Aug Sep

WQ Conditions: SummarySeasonal/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

• Single parameter displays– Nitrate

– Phytoplankton

– Cumulative chl-a

• Multi-parameter display– New Bern time history

Modeled Nitrate - September 1991

1991 Predicted Nitrates:May - Sept. animation

Modeled DO - September 1991

1991 Predicted DO:May - Sept. animation

Modeled chl-a - September 1991

1991 Predicted chl-a:May - Sept. animation

Water Quality Prediction - New BernSurface

Surface

MiddleSal.

NOx

DO

Chl

Mar May July Sep

Middle

0

6

0

0

.5

4

10

50

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• 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