CE5504 – Surface Water Quality Modeling
AQUATOX Assignment 1. TSS and Secchi Disk Transparency in Onondaga Lake
Objective. To develop an initial familiarization with the AQUATOX software while
examining the relationship between external loads and lake water quality.
A. Study Setup
Bring up the AQUATOX software.
Select File and then New Simulation Wizard and then Next
Step 1. Simulation Type
Select Create Simulation from Scratch and then Next
Enter name, Onondaga TSS-SD
Select Lake and then Next
Step 2. Simulation Time Period
Enter Start Date 1-1-1996
[you need 1996, otherwise it makes it 2096]
Enter End Date 12-31-1996 and then Next
The year will eventually be student-specific.
Step 3. Nutrients
Enter “0” for all five chemicals and then Next.
Step 4. Detritus
Enter “0” for both categories and then Next.
Enter “0” for both categories and then Next.
Select Organic Matter, then “0”, “0” and “100”.
In order to eliminate detritus from the simulation.
Step 5. Plants
Leave the six Plants screens blank for this simulation.
Enter Next.
Step 6. Invertebrates
Leave the eight Invertebrates screens blank for this simulation.
Enter Next.
Step 7. Fish
Leave the two Fish screens blank for this simulation.
Enter Next.
Step 8. Site Characteristics
Enter Site Name, Onondaga Lake
Enter Site Length, 0.779 km. [we’ll discuss this in more detail in a later assignment]
Enter Surface Area, 12e+06 m2. [Effler, 1996, p. 26]
Enter Mean Depth, 10.9 m. [Effler, 1996, p. 26]
Enter Maximum Depth, 19.5 m. [Effler, 1996, p. 1]
Enter Mean Evaporation, 0 in. / year. [we’ll reconsider this in a later assignment]
Enter Latitude, 43 degrees. [we’ll discuss this in more detail in a later assignment]
Enter Next.
Step 9. Water Volume Data
Select Keep Volume Constant on first screen and then Next.
On second screen, left side, enter 1.308e+08 m3 and select Keep Constant at Initial Level.
On second screen, right side, enter 1.4e+06 m3 [based on 3.9 flushes/year; Effler 1996, p.
108] and select Keep Constant at Initial Level.
Discharge of Water is locked out for constant volume simulations.
Enter Next.
Step 10. Water Temperature
Select Use Mean and Annual Range and then Next.
Enter an Average Temperature of 20 °C and a range of 0 °C for both the epilimnion and
hypolimnion. The system will not stratify. [The simulation is not sensitive to T]
Enter Next.
Step 11. Wind Loadings
Select Enter Constant Wind and then Next.
Enter an Initial Condition of 5 m/s.
Select Use Constant Loading and enter 5 m/s. [The simulation is not sensitive to light]
Enter Next.
Step 12. Light Loadings
Select Enter Constant Light and then Next.
Enter 250 ly/d. [The simulation is not sensitive to light]
Enter Next.
Step 13. ph of Water
Select Enter Constant pH and then Next.
Enter 7.5 pH. [The TSS simulation is not sensitive to pH]
Enter Next.
Step 14. Inorganic Solids
Select, No, Don’t Simulate TSS and then Next.
Step 15. Chemicals to Simulate
Leave the Chemicals screen blank for this simulation.
Enter Next.
Step 16. Inflow Loadings
Leave the Inflow Loadings screen blank for this simulation.
Enter Next.
Step 17. Direct Precipitation Loadings
Leave the Direct Precipitation Loadings screen blank for this simulation.
Enter Next.
Step 18. Point Source Loadings
Leave the Point Source Loadings screen blank for this simulation.
Enter Next.
Step 19. Nonpoint Source Loadings
Leave the Nonpoint Source Loadings screen blank for this simulation.
Enter Next.
This completes the Wizard.
B. Specifying the Simulation Parameters
Secchi Disk transparency, the depth (m) to which a white or black and white disk remains
visible in the water provides a measure of light penetration or water clarity.
Light attenuates in water in the manner of a first order decay,
I z  I 0  e  kd  z
where I0 is incident light (Ly∙d-1), Iz is light at depth z (m) and kd is the vertical+
extinction or attenuation coefficient (m-1).
The overall extinction coefficient is made up of the extinction coefficient due to pure
water (kw), the extinction coefficient due to (dissolved color, kcolor) and the partial
extinction coefficients for phytoplankton (chlorophyll; Chl) and trypton (the non-algal
portion of total suspended solids; trypton),
kd  kw  kcolor   Chl  Chl   trypton  trypton
AQUATOX, includes kw, treats color as a partial extinction coefficient based on
dissolved organic matter (DOM, a state variable), accommodates species-specific partial
extinction coefficients for phytoplankton, and splits trypton into organic and inorganic
fractions. The organic fraction utilizes a partial extinction coefficient based on
particulate detritus (POM, a state variable), and the inorganic fraction utilizes a partial
extinction coefficient based on inorganic sediment (TSS, total suspended solids, less the
algal and POM components).
We will simplify this treatment for the present assignment, where we do not simulate
phytoplankton, DOM or POM, to include extinction due only to water, dissolved color
and inorganic suspended solids.
We will incorporate attenuation due to color in the water extinction coefficient, kw,
which may be user-specified in AQUATOX. Effler (1996) reports minimum values of kd
of 0.42-0.51 m-1 for Onondaga Lake, suggesting a value of ~0.4 m-1 for a kw that includes
extinction due both to water and dissolved color. This value can be entered by, selecting
Site from the study screen and then Underlying Site Data on the Site: Onondaga Lake
screen. The value 0.4 may then be entered for Extinct. Coeff Water on the Site Data
screen.
The partial extinction for inorganic suspended sediment (= TSS – Chl – POM) is hardwired in AQUATOX at 0.17 m-1∙g-1∙m3. Thus extinction due to inorganic suspended
sediment increases with concentration (g∙m-3), e.g.
ktrypton   trypton  trypton
m1  m1 g 1m3  g  m3
Finally, Secchi disk transparency (m) is computed as,
SD 
1.9
kd
In this exercise, we will examine the behavior of SD in response to changes in the
external loading of TSS. The AQUATOX software does not model TSS per se, i.e. a
mass balance on loads, outflow and settling, but rather permits user-specification of inlake concentration. We will circumvent this issue by ‘constructing’ a TSS state variable
from one of the biological components.
On the AQUATOX: Study Information screen, select Add under State and Driving
Variables in Study. Then scroll down and pick OtherAlg1 and then OK. On the Select
Database Entry screen select Cryptomonas and then OK.
We have added a state variable and now need to configure it to behave like TSS. Double
click on OtherAlg1 under State and Driving Variables in Study and then select Edit
Underlying Data. Here, change the Plant name from Cryptomonas to TSS Surrogate.
Then set the five coefficients from Max. Photosynthetic Rate through Exponential Mort.
Coeff. to “0”, eliminating all growth and death kinetics … we have created an inanimate
material. TSS will settle, however, so set the Sedimentation Rate to 1 m∙d-1 (Effler, 1996,
p. 514) and the Exp. Sedimentation Coeff to “0”. The latter coefficient accounts for the
effects of metabolic stress on phytoplankton settling velocities, a consideration which
doesn’t apply here. Hit OK and then OK to return to the AQUATOX Study Information
screen.
C. Evaluating Model Performance
Check 1. Under TSS Surrogate, set loads and initial conditions = 0. Under Site, set
Extinct. Coeff Water = 0. This should yield a lake with TSS = 0 and a very large SD. On
the AQUATOX Study Information screen, select Control to run the model and then
Output to view the results. From the Output Window, select Control Graph, Change
Variables and Use Two Axes. Then select TSS Surrogate for the Y1 axis and Secchi d for
the Y2 axis and then OK. This shows the expected result. To confirm this finding, let’s
look at some tabular data. Select Control Simulation, then Change Variables, add the
TSS Surrogate and Secchi d to the list and select OK. This confirms our findings. Select
Exit Output.
Check 2. Change the value for kw from 0 to 0.4 and re-run the control. Predict the
impact on SD before examining the output. Does this make sense?
Check 3. Add some TSS now by specifying an initial condition of 1 mg/L and a
sedimentation rate of ‘0’and re-running the control. The output will be easier to visualize
here if you specify the plot ranges. Select Change Variables and Use Below Values for
both parameters (with TSS = 0-2 and SD = 3-5). Explain, mechanistically, the behavior
of TSS and SD. Change the TSS sedimentation rate to 1 m∙d-1 and run the model again.
Is the result as expected?
Check 4. Add a TSS load of 1 mg∙L-1. How does this change the TSS response? Verify
the SS TSS with a long hand calculation, i.e. solve,
V
dC
 W  Q  C  v  As  C
dt
for TSS at steady state and compare it with the model prediction.
Check 5. Examine model sensitivity to loads by doubling first the TSS load (note there is
a special button to do this) then flow and determine that the model performs
appropriately. If this doesn’t work out exactly right, check it with the SS solution.
Finally, let’s settle on an average in-lake TSS 5 mg/L as an initial condition and
determine, by iteration, the TSS load required load to maintain that concentration. Is
there another way (other than brute force iteration) to determine the required load?
Check your result both ways and take one last look at the predicted Output for TSS and
SD for constant loads.
D. Model Application
Our objective here is to develop an annual time series of loads for TSS and to apply those
loads in examining changes in Secchi disk transparency over the annual cycle. To do
this, we need to determine daily values for flow and TSS concentration for the input to
Onondaga Lake.
A file is attached, detailing the sum of all tributary inputs for 1996. Import these data to
the Inflow of Water screen, run the model and examine an Output plot of flow. Also take
a look at the TSS and SD plots. Of course these are not complete, because the loading
TSS varies with flow, so we must accommodate this.
Effler (1996) reports a relationship between TSS and flow of,
TSS  14.76  Q0.558
with TSS in mg∙L-1 and flow (Q) in m3∙s-1.
Use this to calculate the daily tributary TSS concentration and import it to AQUATOX.
Run the model and examine Output for TSS and SD. Consider the implications and
feedback effects associated with adding phytoplankton to the simulation.