Eutrophication And Sediment Nutrient Flux Modeling Primer · Sediment Nutrient Flux Modeling Primer Science Advisory Panel Meeting April 26, 2013. Overall Modeling Framework Models

EutrophicationEutrophicationAndAnd

Sediment Nutrient FluxSediment Nutrient FluxModeling PrimerModeling Primer

Science Advisory Panel MeetingScience Advisory Panel MeetingApril 26, 2013April 26, 2013

Overall Modeling FrameworkOverall Modeling Framework

Models based on continuity and mass balances

Phytoplankton, Light, Nutrients Phytoplankton, Light, Nutrients and Eutrophication Modelingand Eutrophication Modeling

PHYTOPLANKTON GROWTHPHYTOPLANKTON GROWTH

l The time rate of change of algal biomass is a balance between phytoplankton growth and loss processes

l The latter of which include transport-related losses (settling or sinking and dispersion) and kinetic losses (respiration and predation)

l The growth rate itself is a function of environmental factors such as temperature, light, and nutrients

PGHv

TrNITudtdP

Z

s ])(),,([max

−−−=

PHYTOPLANKTON GROWTH PHYTOPLANKTON GROWTH TEMPERATURETEMPERATURE

l Different approaches: linear, Arrenhius (theta), optimal

opt

opt

optT

opt

opt

optT

T

T

T

ref

refT

T

TTTTTTTuu

TTTTTTTuu

TTu

uu

TTTTTTuu

TTu

≤≤−−=

≤≤−−=

≤=

Θ=

>−−=

≤=

−

min

max

max

max,max,

min

min

min

max,max,

minmax,

20

20max,max,

min

min

min

max,max,

minmax,

0

0–Linear

–Theta

–Optimal

0

2

4

6

8

0 5 10 15 20 25 30 35 40

Temperature (deg C)

Gro

wth

Rat

e (/d

ay)

Linear Arrenhius Optimal

PHYTOPLANKTON GROWTH PHYTOPLANKTON GROWTH TEMPERATURETEMPERATURE

l More than one functional algal group

opt

TT

optT

opt

TT

optT

TTeuu

TTeuuopt

opt

≥=

≤=−−

−−

22

21

)(

max,max,

)(

max,max,

β

β

Effect of Temperature Correction Formulation and Temperature on Maximum Algal Growth Rate

0

0.5

1

1.5

2

2.5

0 5 10 15 20 25 30

Temperature (deg C)

Fra

ctio

n G

Pm

ax

Winter Group Summer Group Arrenhius

Algal Growth Rates Used in SWEM

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0 5 10 15 20 25 30

Temperature (deg C)

Gro

wth

Rat

e (/

day

)

Winter Diatoms Summer Assemblage Arrenhius

PHYTOPLANKTON GROWTH PHYTOPLANKTON GROWTH LIGHTLIGHT

l Photoinhibition…

l Can be expressed mathematically …

}1exp)( { +−=SS

II

II

IF0.0

0.2

0.4

0.6

0.8

1.0

0 200 400 600 800 1000

Light (I)

Gro

wth

Att

enua

tion

Fact

or -

R(L

)

Is=200 Is=400


l How much light is available for growth …

– seasonal patterns

– diurnal patterns

Incident Solar Radiation (fraction of daylight = 0.5)

0

50

100

150

200

250

300

350

0 4 8 12 16 20 24

Time (hrs)

Lig

ht I

nte

nsi

ty


l How much light is available for growth …

– vertical attenuationl Vertical attenuation can

be modeled by the Beer-Lambert law

-20-18-16-14-12-10-8-6-4-20

0 0.2 0.4 0.6 0.8 1

Light Attenuation Factor

Dep

thKe=0.6 /m Ke=0.25 /m

zk

z

eeII −=0

where z = depthKe = light extinction coefficient


Extinction coefficient, Ke, is a function of phytoplankton biomass (chl-a), dissolved organic matter, and inert suspended solids

However, we usually just model it as a base value plus the algal component

a-ChlKK

KKK

baseeobse

algalebaseeobse

⋅+=

+=

−−

−−−

α

Literature values of α range from 0.01 - 0.02 m2/mg Chl-a

PHYTOPLANKTON GROWTH PHYTOPLANKTON GROWTH NUTRIENTSNUTRIENTS

• Michaelis-Menten kinetics

CKC

NRMN +

=)(

CKC

NRMN +

=)(

0

0.10.20.3

0.4

0.50.6

0.70.8

0.91

0 0.02 0.04 0.06 0.08 0.1

Nutrient Concentration (mg/L)

R(N

)

Kmn=0.010 mg/L

Kmn=0.020 mg/L

PHYTOPLANKTON GROWTH PHYTOPLANKTON GROWTH NUTRIENTSNUTRIENTS

• Early eutrophication models used fixed nutrient stoichiometry (usually based on Redfield ratio)

• However …

Nutrient CyclingNutrient Cycling

• Nutrients are utilized by phytoplankton for growth (nutrient uptake)

• As a consequence of respiration and death and grazing (fecal pellets or unassimilated particulate matter) nutrients are returned (in various forms) to the water column

LPOM

RDOM

LDOM

Algal Cell DIN

RPOM

RPOM – Refractory Particulate Organic Matter

LPOM – Labile Particulate Organic Matter

RDOM – Refractory Dissolved Organic Matter

LDOM – Labile Dissolved Organic Matter

DIN – Dissolved Inorganic Nutrient

frpom

flpom

frdom

fdin

fldom

klpom

krpom

kldom

krdom

kuptake

Why So Complex?Why So Complex?

l Early eutrophication models were considerably less complex when it came to modeling nutrient pools

Why So Complex?Why So Complex?l While a portion of the organic matter was settled

(representing the particulate fraction), it soon became obvious that just treating organic matter as a single state-variable would not work in many modeling applications ? initial split into particulate and dissolved pools

l With the development of the sediment flux model, which includes labile (“fast”), refractory (“slow”), and inert organic matter pools in the sediment bed, it became necessary to include labile and refractory particulate fractions in the water column

l With coastal applications and in systems that contain “tea-colored” waters (mangrove forests, bayous, etc.), it became necessary to partition dissolved organic matter into labile and refractory pools

Sediment Flux ModelingSediment Flux Modeling

• Why do it?

• Historically, the sediment bed was treated as a boundary condition, with sediment oxygen demand (SOD) and nutrient fluxes specified based on observed data

• Early modeling in Chesapeake Bay changed all that

Chesapeake Bay Projection AnalysisChesapeake Bay Projection Analysis

Chesapeake Bay Projection AnalysisChesapeake Bay Projection Analysis• Oops! Not good to find out that reducing point source

nutrient inputs has no effect on Bay water quality

• What went wrong?

• Model did not account for the fact that the input of particulate organic matter (POM) to the sediments would be reduced due to reduced levels of primary production associated with reduced nutrient inputs,

• Which in turn would reduce SOD and nutrient fluxes back to water column

• Developed an approach that adjusted SOD and nutrient fluxes either in proportion to reductions in the deposition of POM to the sediment

Chesapeake Bay Projection AnalysisChesapeake Bay Projection Analysis

Sediment Flux Model (SFM) FrameworkSediment Flux Model (SFM) Framework

(1) Deposition of POM

(2) Diagenesis –decomposition of POM

(3) Flux of SOD and inorganic end-products back to OWC

(4) Burial to deep sediments

1-5 mm

10 cm

Sediment Oxygen DemandSediment Oxygen Demand

O2NO3 SO4

CH4(aq)

CH4(sat) CH4(gas)

Zone of oxygen reduction

Zone of nitrate reduction

Zone of sulfate reduction

H2S

H2S(entrainment)

Zone of methanogenesis

diffusion

Examples of SFM BehaviorExamples of SFM Behavior

0

15

30

45

60

75

90

105

120

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Time (days)

Nit

rog

en F

luxe

s (m

g N

/m2-

day

)

JNH4 JNO3 JN2

Nitrogen Flux Components

Reduce Loading 75%Reduce Loading 75%

0

15

30

45

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Time (days)

Nit

rog

en F

luxe

s (m

g N

/m2-

day

)

JNH4 JNO3 JN2

Reduce NH4 and NO3 Fluxes and Enhance Denitrification (N2) Flux

Reduce Loading 75%Reduce Loading 75%

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Time (days)

SO

D (

gm

/m2-

day

)

Total SOD CSOD NSOD JH2S JCH4AQ JCH4G

Time to Equilibrium for SOD – Also Eliminate CH4 Production

James River HABsJames River HABs• Modifications to phytoplankton kinetics:

• Addition of HAB groups

üDiel migration for freshwater cyanobacteria and marine dinoflagellates

üCyanobacteria migration – buoyancy

üDinoflagellate migration – swimming

üBoth driven by light and nutrients

üDinoflagellates – heterotrophy – utilization of labile form of organic nitrogen as NH4 and NO3 are utilized

üReduced pelagic/benthic grazing pressure

James River HABsJames River HABs

Brookes et al., 1999

James River HABsJames River HABs

Visser et al., 1996

Vertical Depths: 0-2m, 2.5-4.5 m, 5-7 m, and 7-10 m

Vertical Depths: 0-2m, 2.5-4.5 m, 5-7 m, 7-10 m, 11-15m, 16-20m, 21-25m, and 27 m

Effect of Vertical Mixing on Microcystis

Eutrophication And Sediment Nutrient Flux Modeling Primer · Sediment Nutrient Flux Modeling Primer Science Advisory Panel Meeting April 26, 2013. Overall Modeling Framework Models

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