cvEPA
United States
Environmental Protection
Agency
Office of Water
(4305)
EPA-823-R-01-007
November 2001
AQUATOX - A Modular Fate and
Effects Model for Aquatic
Ecosystems - Release 1.1:
Volume 2 - Technical Documentation
(Addendum)
Since its first release by EPA in September 2000, there have been several changes made to
AQUATOX, most significantly those that have improved the simulation ofperiphyton (attached
algae) in streams and rivers. Minor enhancements were also made which improve simulation of
macrophytes,fish, and dissolved oxygen. A typographic error was discovered in the documentation
relating to volatilization; the model code was correct. This addendum presents the specific changes
to the Technical Documentation (EPA document number 823-R-01-007).
Periphyton
The following should replace "Washout and Entrainment" on pp. 4-17 and 4-18)
Washout and Sloughing
Phytoplankton are subject to downstream drift. In streams and in lakes and reservoirs with
low retention times this may be a significant factor in reducing or even precluding phytoplankton
populations (LeCren and Lowe-McConnell, 1980). The process is modeled as a simple function of
discharge: •
Washout
phytoplankton
Discharge '.
= — • Biomass
Volume
where:
Washout
Discharge
Volume
Biomass
loss due to downstream drift (g/m3*d),
daily discharge (mVd);
volume of site (m3); and
biomass of phytoplankton (g/m3).
Periphyton may also lose biomass due to high stream velocity. Originally AQUATOX
modeled this as entrainment, being a function of stream discharge and biomass. Attempts at
calibration for periphyton using a high quality data set were unsuccessful because they were unable
to reproduce the buildup and then decline in periphyton biomass. As a result, the formulation for
entrainment was reexamined and a more complex sloughing formulation, extending the approach
of Asaeda and Son (2000), was implemented. This function was able to represent a wide range of
conditions better (Figure 1 and Figure 2).
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o
m
- Diatoms(g/m2) -•- Oth alg(g/m2) Periphyton X Observed
Figure 1. Comparison of predicted biomass of periphyton, constituent algae, and
observed biomass of periphyton (Rosemond, 1993) in Walker Branch, Tennessee,
with addition of both N and P and removal of grazers in Spring, 1989.
16
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D Riotsyrtfiea's D Ftesprafon D Excrefon D IVfcrtalfly • Ptedafon n
Figure 2. Predicted rates for diatoms in Walker Branch, Tennessee, with addition
of both N and P and removal of grazers in Spring, 1989. Note the importance of
periodic sloughing.
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Sloughing is a function of senescence^due to suboptimal conditions and the drag force of
currents acting on exposed biomass. Drag increases as both biomass and velocity increase:
DragForce = Rho • DragCoeff- Vel2 • (BioVol • .UnitAred)2'3 • l(E-6)
where:
DragForce
Rho
DragCoeff
Vel
BioVol
UnitArea
1E-6
drag force (kg m/s2);
density (kg/m3);
drag coefficient (2.53E-4, unitless);
velocity (m/s);
biovolume of algae (mmVmm2);
unit area (mm2);
conversion factor (m2/mm2).
Biovolume is not modeled directly by AQUATOX, so a simplifying assumption is that the
empirical relationship between biomass and biovolume is constant for a given growth form, based
on observed data from Rosemond (1993):
Biomass
Biovol
Dia
BiovolFil =
2.08E-9
Biomass
8.57E-9
where:
BiovolDia
Biovol,
•Fil
Biomass
biovolume of diatoms (mm3/mm2);
biovolume of filamentous algae (mmVmm2);
biomass of given algal group (g/m2).
Suboptimal light and nutrients cause senescence of cells that bind the periphyton and keep
them attached to the substrate. This effect is represented by a factor, Suboptimal, which is computed
in modeling the effects of suboptimal nutrients and light on photosynthesis, and which is multiplied
by 5 to desensitize its effect on sloughing. Suboptimal decreases the critical force necessary to cause
sloughing. If the drag force exceeds the critical force for a given algal group modified by the
Suboptimal factor, then sloughing occurs:
If DragForce > SuboptimalOrg • FCritOrg then Slough = Biomass • FracSloughed
else Slough = 0
where:
SuboptimalOrs = factor for suboptimal nutrient and light effect on senescence of given
periphyton group (unitless);
FCrit0rs = critical force necessary to dislodge given periphyton group (kg m/s2);
Slough = biomass lost by sloughing (g/m3);
FracSloughed = fraction of biomass lost at one time (90%, unitless).
Suboptimal0rg = NutrLimitOrg • LtLimitOrg • 5
If SuboptimalOrg > 1 then Suboptimal ^ - 1
where:
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NutrLimit
LtLimit0rg
nutrient limitation for given algal group (unitless) computed by
AQUATOX;
light limitation for given algal group (unitless) computed by
AQUATOX.
Detrital Accumulation in Periphyton
In phytoplankton, mortality results in immediate production of detritus, and that transfer is
modeled. However, for purposes of modeling, periphyton are defined as including associated
detritus. The accumulation of non-living biomass is modeled implicitly by not simulating mortality
due to suboptimal conditions. Rather, in the simulation biomass builds up, causing increased self-
shading, which in turn makes the periphyton more vulnerable to sudden loss due to sloughing. The
fact that part of the biomass is non-living is ignored as a simplification of the model, with
compensation through the high internal extinction rate constant.
Macrophvtes
The following equation should replace Eq. 64 on p. 4-19:
dBiomass
di
= Loading + Photosynthesis - Respiration -Excretion
- Mortality - Predation -Breakage
(6)
In the list of definitions for the above variables on p. 4-20, "Washout" should be replaced by:
Breakage = loss due to breakage (g/m2«d)
The following should be inserted after Figures 40 and 41 on p. 4-21 :
Macrophytes are subject to breakage due to higher water velocities; this breakage of live
material is different from the sloughing of dead leaves. Although breakage is a function of shoot
length and growth form as well as currents (Bartell et al, 2000; Hudon et al., 2000), a simpler
construct was developed for AQUATOX (Figure 3):
„ , Velocity - VelMax „.
Breakage = • Biomass
Gradual • UnitTime
where:
Brealaige
Velocity
VelMax
Gradual
UnitTime
Biomass
macrophyte breakage (g/m2 d);
current velocity (cm/s);
velocity at which total breakage occurs (300 cm/s);
velocity scaling factor (-100 cm/s);
unit time for simulation (Id);
macrophyte biomass (g/m2).
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1.2
1
73
0>
I 0.4
OQ
0.2
0
Velocity (cm/s)
Figure 3. Breakage of macrophytes as a function of current velocity.
Fish
The following should be inserted in place ofEq. 77 in "Respiration" on p. 4-27:
Respiration in fish increases with crowding due to competition for spawning sites,
interference in feeding, and other factors. This adverse intraspecific interaction helps to constrain
the population to the carrying capacity; as the biomass approaches the carrying capacity for a given
species the respiration is increased proportionately (Kitchell et al., 1974):
Endogenouspred •= EndogResppred • TCorrpred • Biomassprgd • DensityDep
DensityDep = 1
IncrResp • Biomass
KCap
where:
Endogenous^
EndogResppKd =
TCorr,
pred
Biomass,
'pred
DensityDep =
IncrResp =
KCap
basal respiratory loss modified by temperature.and crowding (g/m3»d);
basal respiration rate at 0° C for given animal (I/day); parameter
input by user as "Respiration Rate;"
Stroganov temperature function (unitless);
concentration of organism (g/m3).
density-dependent respiration factor used in computing endogenous
respiration (unitless);
increase in respiration at carrying capacity (0.25);
carrying capacity (g/m3).
With the IncrResp value of 0.25, which is a conservative estimate, respiration is increased by 25%
at carrying capacity (Kitchell et al., 1974), as shown in Figure 4. Note that the same equation is
used for invertebrates; but, by setting a high carrying capacity, density dependence is not an
important factor for invertebrates.
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1.3
1.25
0)
1.2
a 1.15
a
~ 1.1
w
1.05
J A
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The following note should be inserted on page 7-15, following Eq. 209 and its
accompanying list of definitions:
Because theoretically toxicants can be transferred in either direction across the water-air
interface, Eq. 209 is formulated so that volatilization takes a negative sign when it is a loss term.
References
Asaeda, T., and D.H. Son. 2000. Spatial structure and populations of a periphyton community: a
model and verification. Ecological Modelling, 133:195-207.
Rosemond, A.D. 1993. Seasonality and Control of Stream Periphyton: Effects of Nutrients, Light,
and Herbivores. Dissertation, Vanderbilt University, Nashville, Tenn., 185 pp.
Bartell, S.M., K.R. Campbell, E.P.H. Best, and W.A. Boyd. 2000. Ecological Risk Assessment of
the Effects of the Incremental Increase of Commercial Navigation Traffic (25, 50, 75, and
100% Increase of 1992 Baseline Traffic) on Submerged Aquatic Plants in the Main Channel
and Main Channel Borders. ENV Report 17, prepared for U.S. Army Engineer District,
Rock Island, U.S. Army Engineer District, St. Louis, U.S. Army Engineer District, St. Paul.
109pp.
Hudon, C., S. Lalonde, and P. Gagnon. 2000. Ranking the Effects of Site Exposure, Plant Growth
Form, Water Depth, and Transparency on Aquatic Plant Biomass. Can. J. Fish. Aquat. Sci.
57(Suppl. l):31-42.
Kitchell, J.F., J.F. Koonce, R.V. O'Neill, H.H. Shugart, Jr., J.J. Magnuson, and R.S. Booth. 1974.
Model of Fish Biomass Dynamics. Trans. Am. Fish. Soc. 103:786-798.
Wetzel,R.G. 2001. Limnology: Lake and River Ecosystems. San Diego: Academic Press, 1006pp.
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