A Modeling Analysis of the Clear Water Phase CE5504 - Surface Water Quality Modeling Case History.
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Transcript of A Modeling Analysis of the Clear Water Phase CE5504 - Surface Water Quality Modeling Case History.
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A Modeling Analysisof the Clear Water Phase
CE5504 - Surface Water Quality ModelingCase History
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Chlorophyll
Secchi Disc
A widespread phenomenon, following a pattern …
A distinct period of clear water typical of spring algal succession in many temperate mesotrophic and eutrophic lakes.Lampert, W. et al. 1986. Phytoplankton control by grazing zooplankton: A study on the spring clear water phase. Limnology and Oceanography.
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The PEG “Model”
“ … it is assumed that events in the plankton are neither random not chaotic but that there is a seasonal development which is a predictable consequence of previous events.”
The Plankton Ecology Group, a working body associated with SIL, sought to construct a word model of the seasonal events which occur in the phytoplankton of an idealized ‘standard’ lake.
Sommer et al. 1986
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… well described by the Phytoplankton Ecology Group (PEG) Model
PEG 1. Towards the end of winter, nutrient availability and increased light permit unlimited growth of the phytoplankton. A spring crop of small, fast-growing algae such as Cryptophyceae and small centric diatoms develops.
Data for Onondaga LakeAuer et al. 1990
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… well described by the Phytoplankton Ecology Group (PEG) Model
Data for Onondaga LakeAuer et al. 1990Spada et al. 2004
PEG 4. Herbivore populations increase exponentially up to the point at which their density is high enough to produce a community filtration rate, and thus cropping rate, that exceeds the reproduction rate of the phytoplankton.
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… well described by the Phytoplankton Ecology Group (PEG) Model
Data for Onondaga LakeAuer et al. 1990
PEG 5. As a consequence of herbivore grazing, the phytoplankton biomass decreases rapidly to very low levels. There then follows a ‘clear-water’ equilibrium phase which persists until inedible algal species develop in significant numbers.
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… well described by the Phytoplankton Ecology Group (PEG) Model
Data for Onondaga LakeSpada et al. 2004
PEG 6. Herbivorous zooplanktonic species become food-limited and both their body weight per unit length and their fecundity declines. This results in a decrease in their population densities and biomasses.
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… well described by the Phytoplankton Ecology Group (PEG) Model
Data for Onondaga LakeSpada et al. 2004
PEG 7. Fish predation accelerates the decline of herbivorous planktonic populations to very low levels and this trend is accompanied by a shift towards smaller average body size amongst surviving crustaceans.
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… well described by the Phytoplankton Ecology Group (PEG) Model
Data for Onondaga LakeAuer et al. 1990
PEG 8. Under conditions of reduced grazing pressure and sustained non-limiting concentration of nutrients, the phytoplankton summer crops start to build up. The composition of the phytoplankton becomes complex both due to the increase in species richness and to the functional diversification into those species available to filter-feeders and those only consumed by specialist feeders.
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… well described by the Phytoplankton Ecology Group (PEG) Model
Data for Onondaga LakeAuer et al. 2004
PEG 10. From this time onward, the algal growth becomes nutrient-limited and this prevents an explosive growth of ‘edible’ algae. Grazing by predator-controlled herbivores balances the nutrient-limited growth rate of edible algal species.
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modeling … from words to equations
PEG 1…, PEG 4…, PEG 5…, PEG 7…, PEG 8…
AQUATOX 2.0
Park, R.A., Clough, J.S. and M. Coombs Wellman. 2004. AQUATOX: Modeling Environmental Fate and Ecological Effects in Aquatic Ecosystems. Release 2. U.S. Environmental Protection Agency, Office of Water, Washington, DC.
...dc
Vdt
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edible algae: flagellate greens
small diatoms
cryptomonads
inedible algae:large diatoms
large greens
cyanobacteria
dinoflagellates
ceaspub.eas.asu.edu serc5.si.edu www.biology.mcgill.ca
www.microscopy-uk.org.uk biodidac.bio.uottawa.ca www.bio.mtu.edu
modeling … organisms
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modeling … organisms
cladoceran: Daphnia
planktivore:gizzard shad
prefedible = 1
prefinedible = 0
prefcladoceran = 1
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modeling … species composition
0%
20%
40%
60%
80%
100%
0%
20%
40%
60%
80%
100%
smdiat
crypto
dino
cyano
lggr
edible
inedible
Data for Onondaga LakeUFI; Cliff Siegrfried
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modeling kinetic coefficients
edible algae
Kp = 0.005 mg/LTopt = 16 °C
C0 = 0.4 mg/L
inedible algae:
Kp = 0.025 mg/LTopt = 25 °C
C0 = 0.05 mg/LValues for other coefficients used in the calibration process (Pmax, Kresp, Kmort, Ksettle) were identical for both groups.
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modeling … nutrients
0.0
0.2
0.4
0.6
0.8
1.0
A M J J A S
0.0
0.1
0.2
0.3
N
P
Set initial conditions and loads to achieve saturation.
Nit
rog
en
(m
gN
∙L-1)
Ph
osp
horu
s (
mg
P∙L
-1)
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modeling … temperature
0
100
200
300
400
500
A M J J A S
Incid
en
t Lig
ht
(ly∙d
-1)
Latitude-specific seasonal pattern.0
5
10
15
20
A M J J A S
Tem
pera
ture
(°C
)
Latitude-specific seasonal pattern.
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modeling … optics
Secci disc transparency is estimated from the model-calculatedextinction coefficient, based on a polynomial published by Effler et al. (1996):
The extinction coefficient is calculated as the sum of partial extinctioncoefficients provided by Effler et al. (1996):
gelbstoff chlorophy sll fwd skk k k k 1 10.39 (0.65 ; .1996)gelbstoffw m m Effler et alk k
2
0.011 ( .1996)chl
mChl Effler et al
mg Chlk
2
0.344 ( .1996)fss
mfss Effler et al
mg fssk
2 3 41 1 1 10 1 2 3 4d d d dSD a a k a k a k a k
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modeling … transparency
0
2
4
6
8
A M J J A S
Set detritus to achieve ‘clearwater’ transparency.
Secch
i D
isk (
m)
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0
1
2
3
4
5
6
7
8
1975 1980 1985 1990 1995 2000 2005
modeling … target data sets
Data for Onondaga LakeSpada et al. 2004
Max
imu
m S
ecch
i D
isc
(m)
return oflarge-bodiedDaphniids
relapse
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Oh … now we get to see the snake eat the rabbits!
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1985 data set ... chlorophyll and transparency
0
20
40
60
80
Ch
loro
ph
yll
(µ
g/L
)
M J J A S O N
0
1
2
3
4
5
6
7
Se
cc
h d
isk
(m
)
M J J A S O N
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0
20
40
60
80
Ch
loro
ph
yll
(µ
g/L
)
1985 calibration … chlorophyll
M J J A S O N
dominant
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1985 calibration … transparency
0
1
2
3
4
5
6
7
Se
cc
h d
isk
(m
)
M J J A S O N
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1985 calibration … zooplankton
absent in 1985
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0
1
2
3
4
5
6
7S
ec
ch
i dis
c (
m)
1999 data set … chlorophyll and transparency
A M J J A S O
A M J J A S O
0
20
40
60
80
Ch
loro
ph
yll
(µg
/L)
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1999 data set … daphniids
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Da
ph
niid
s (
mg
/L)
A M J J A S O
daphniids
Gmax = 1.6 g/g·dTopt = 20 °C
C0 = 0.01 mg/L
Other coefficients usedin the calibration processincluded Kresp and Kmort.
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1999 calibration … daphniids
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
Da
ph
niid
s (
mg
/L)
A M J J A S O
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1999 performance … chlorophyll
0
20
40
60
80
Ch
loro
ph
yll
(µg
/L)
A M J J A S O
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1999 performance … transparency
0
1
2
3
4
5
6
7
Se
cch
i dis
c (m
)
A M J J A S O
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1999 performance … species composition
0%
20%
40%
60%
80%
100%
0%
20%
40%
60%
80%
100%
model
data
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2003 simulation …planktivore added
0
1
2
3
A M J J A S
0
1
2
3
4
5
6
7
8
9
10
• cladocerans essentially eliminated• much slower attenuation of edible forms• dominated by edible algae
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2003 simulation …planktivore added
0
5
10
15
20
25
30
35
A M J J A S
0
1
2
3
4
5
6
• absence of clear water phase
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What about the rabbits that got away?
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… rabbits running, Part 1: time-variable TSS
0
1
2
3
4
5
6
7
Se
cc
hi d
isc
(m
)
0
1
2
3
4
5
6
7
Se
cc
hi d
isc
(m
)
TSS = 3 mg/L
TSS = 0.3 mg/L
The base case TSS is ramped down from 3 mg/L to 0.3 mg/L during the clearing event,
Neither level, held constant permits successful simulation of transparency over the season.
This suggest that non-specific grazing (tripton consumption) may play a role in the magnitude of the transparency increase observed in clearing events.
time-variable TSS
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… rabbits running, Part 2: Aphanizomenon
0
20
40
60
80
Ch
loro
ph
yll
(µg
/L)
A M J J A S O
… the model fails to capture a late June crash in chlorophyll
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… rabbits running, Part 2: Aphanizomenon
0%
20%
40%
60%
80%
100%
the population crashing was a genus of cyanobacteria, Aphanizomenon, an inedible form. The crash freed resources for two edible groups (small diatoms and cryptomonads) …
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… rabbits running, Part 2: Aphanizomenon
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
Da
ph
niid
s (
mg
/L)
and a second daphniid peak resulted …
A M J J A S O
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… rabbits running, Part 2: Aphanizomenon
0
20
40
60
80
Ch
loro
ph
yll
(µg
/L)
A M J J A S O
… bottoming out the chlorophyll
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… rabbits running, Part 2: Aphanizomenon
0
1
2
3
4
5
6
7
Se
cch
i dis
c (m
)
A M J J A S O
… an yielding a second clearing event
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… we have our ways to deal with running rabbits
“Pay no attention to themodeler behind the curtain.”
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Conclusions
The PEG word model and the AQUATOX software package provide a framework for the successful simulation of the clearing event phenomenon and for phytoplankton-transparency relationships in non-clearing event years.
Certain features of the simulation, particularly the demise of cyanobacteria populations and the role of non-specific grazing in driving clearing events, are not well understood … reminding us that nature remains the master modeler.