Prepared by Alexandria Lake Area Sanitary District
UNDERSTANDING THE LAKE WINONA TOTAL MAXIMUM DAILY LOAD
What is a TMDL?
The State of Minnesota has established water quality
standards for Minnesota’s lakes to protect recreation and
aquatic life (Table 1). The current standards set targets for
deep and shallow lakes by ecoregion to account for
differences in soils, vegetation, and other factors between
these areas. The standards are set for total phosphorus,
chlorophyll-a and Secchi disk transparency. Total phosphorus
is used because it is the limiting growth nutrient for algae
meaning the more total phosphorus available in the lake, the
more algae one can expect to see. Chlorophyll-a is a measure
of the amount of algae growing in a lake and Secchi disk
transparency is a measure of water clarity.
A Total Maximum Daily Load or TMDL is a calculation of
the maximum amount of a pollutant that a water body can
receive while still meeting established state water quality
standards. The purpose of these studies is to determine what
levels of pollutant load is acceptable while still protecting
aquatic life and recreation.
Table 1. Numeric criteria for Lakes in the
North Central Hardwood Forest Ecoregion
North Central Hardwood
Forest Ecoregion –
Parameters
Shallow Lake1 Standard
Phosphorus
60
Concentration (g/L)
Chlorophyll-a
20
Concentration (g/L)
Secchi disk
>1
transparency (meters)
Lake Winona, Alexandria, MN
Why use Models?
TMDL developers typically apply a numerical model to
lakes to predict the impact of nutrient load on in-lake
water quality. These models are known as lake response
models. The lake response model can be used to not
only predict in-lake total phosphorus concentrations, but
also the amount of algae (chlorophyll-a) and water
clarity (Secchi depth) expected to occur under those
nutrient concentrations. The purpose of these models in
developing lake TMDL studies is to better understand
1
Shallow lakes are defined as lakes with a
the cause and effect of nutrients delivered to the system.
maximum depth of 15 feet or less, or with 80% or
more of the lake area shallow enough to support
For example, a lake response model will predict the inemergent and submerged rooted aquatic plants
lake growing season average total phosphorus
(littoral zone).
concentration based on the amount of phosphorus
coming into the lake. These models are then used to determine the amount of nutrients that can enter a
lake and still meet the state water quality standards.
For these models to be applied effectively, the models must first reasonably represent the cause
and effect relationship in Lake Winona. These relationships are often developed using a
statistical technique known as regression analysis. A regression attempts to predict one variable
based on another variable. In the case of Lake Winona, the modeler is attempting to predict the
Prepared by Alexandria Lake Area Sanitary District
amount of algae that can be expected with different levels of total phosphorus. Because
phosphorus is the limiting nutrient for algal growth, it is expected that the more phosphorus
available in the lake, the higher the algae levels will be. At a certain point, typically when the
concentration of total phosphorus exceeds 300µg/L, the amount of algae in the water limits the
amount of light that can penetrate the water column slowing the further growth of algae and
other aquatic plants.
Why are shallow lakes difficult to model?
Figure 1. Carp exclusion on Lake Wingra, WI
(LakeLine, Winter, 2005). The enclosed area is free of
carp and has good water clarity while the area outside
the barrier and subject to carp has poor water clarity
and high algal biomass.
Shallow lakes are difficult to model because they
tend to contain smaller volumes of water to
assimilate nutrients, have increased interactions
with sediments, and are affected more readily by
fish, zooplankton and vegetation living in the
lake. So, when trying to establish the cause and
effect of increased (or decreased) nutrient loads
to the lake, these factors need to be addressed in
the model. One of the more important factors
that have been demonstrated to affect in-lake
conditions is the presence of carp. Carp can be
very destructive to a lake by rooting up aquatic
vegetation and stirring up sediments (Figure 1)
which releases phosphorus and fuels algal
blooms.
Furthermore, shallow lakes tend to exist in either a clear-water, submerged aquatic vegetation
dominated state or a turbid-water, algae dominated state. The challenge in developing a model
for a shallow lake is that the model developer often only has data from the turbid water state but
must project the cause-effect relationship expected to exist when the lake is in the clear water
state. To do this, the modeler must attempt to account for some of the biological effects such as
the presence or absence of carp.
The Lake Winona Model
The current TMDL model for Lake Winona attempts to establish the cause and effect between
in-lake nutrients (total phosphorus) and algae (chlorophyll-a) in Lake Winona using data
collected from 2005 through 2009. However, this period is characterized by a significant carp
infestation introduced in 2005. Using data collected prior to the introduction of carp, the cause
and effect relationship between nutrients and algae is quite different (Figure 2). Annual average
phosphorus loading from the Alexandria Lakes Area Sanitary District wastewater treatment plant
was actually lower during the post-carp period, yet water quality is significantly worse during
this period. This relationship needs to represent a fully restored Lake Winona which includes
elimination of the carp population and establishing the clear-water state. Therefore, the use of
the relationship when a carp infestation is dominant in Lake Winona is not appropriate for
establishing the relationship between nutrients and algae in a restored Lake Winona.
Prepared by Alexandria Lake Area Sanitary District
300
WITH CARP (2,104 lbs./yr
ALASD TP Load)
250
Chlorophyll-a (µg/L)
Another issue with modeling shallow lakes is
that the modeler is often trying to project
conditions expected to occur in the clear water
state using data from the turbid water state. In
Figure 2, there are no data available below 150
µg/L total phosphorus, yet the modeler is trying
to predict the water quality under these
phosphorus conditions. Without data it is
impossible to reasonably project algal response
under those conditions and there are a number of
possible outcomes (Figure 3). Furthermore, it is
unlikely that phosphorus levels below 75 to100
µg/L will ever be achieved with the presence of
carp in Lake Winona.
200
150
100
50
WITHOUT CARP (3,222 lbs./yr
ALASD TP load)
0
What are the appropriate next steps?
0
50
100
150
200
250
300
Total Phosphorus (µg/L)
1. The Lake Winona TMDL model must be
updated to reflect the pre-carp conditions.
Furthermore, the restoration of a clear
water state in Lake Winona cannot occur
with the current carp population in Lake
Winona
2. Because of the uncertainty in project lake
response where no data are available,
implementation must occur under adaptive
management where nutrient levels are
incrementally reduced until the desired
beneficial use is restored
Figure 2. Model equations for predicting algae (chlorophylla) from nutrients (total phosphorus) before and after carp
infestation. Open boxes are post 2005 and solid boxes are
prior to 2004.
150
Total Phosphorus levels
unachievable with Carp
WITH CARP RESPONSE?
125
Chlorophyll-a (µg/L)
Modeling shallow lakes is a difficult challenge
requiring the modeler to attempt to predict
relationships between nutrients and algae in a
restored lake using data from an impaired lake
condition. It is up to the modeler to diligently
strive to create the best representation of the cause
and effect relationship under the restored
condition. Failure to meet this challenge can
result in millions of restoration dollars being
wasted on unnecessary and ineffective
management actions. The following challenges
must be addressed in development of the Lake
Winona TMDL:
100
75
Current TMDL
Model
50
25
WITHOUT CARP RESPONSE
0
0
25
50
75
100
125
150
Total Phosphorus (µg/L)
Figure 3. A graphical representation of uncertainty in algal
response (chlorophyll-a) to nutrient concentrations (total
phosphorus) with the presence of carp. The three red lines
represent the possible responses of algae under the carp
dominated system. The gray box represents total
phosphorus conditions likely unachievable with carp.
Extending the projected response under carp-dominated
conditions into the gray area suggests that these conditions
can be achieved with a dominant carp population, which is
unlikely.