Chapter I
INTRODUCTION
Cougar Lake is an impoundment that is located on the campus of Southern Illinois
University Edwardsville, Madison County, Illinois. The dam was closed in 1965, and the
lake’s main purpose is to provide cooling water for the SIUE cooling plant, which has an
effluent stream located on the western shore of the lake. The approximate dimensions of
Cougar Lake are as follows: surface area of 31.4 ha, maximum depth of 11 m, mean depth of
3.9 m, total lake volume of 1.22 x 106 m3, and an epilimnetic volume of 1.16 x 106 m3. The
watershed encompasses an area of 242.9 ha, which is primarily composed of grassland,
although the shoreline of the lake is heavily wooded. There are 2 main sources of water to
the lake. Surface runoff comprises the largest influx of water, and the other source is tertiary
treated sewage effluent (recently upgraded from secondary treatment).
Cougar Lake is eutrophic due to nitrogen from the tertiary treated sewage input, and
phosphate input from the time when the plant only performed secondary treatment of
wastewater. The lake has previously been treated annually with copper sulfate for algal
control, but that practice ceased in 2002.
Cougar Lake is also dimictic. During early spring, the lake is fully mixed, with
mixing driven by wind. In summer, the lake is stratified, with 3 distinct layers: the
epilimnion (0-5 m), thermocline (5-7 m), and the hypolimnion (7-11 m). The epilimnion is
the only mixed layer, and since this is where biological activity occurs in the summer
months, most of the focus on biota shifts to this layer. In fall the lake begins to turn over
again, which leads to full mixing during the winter unless the lake becomes covered with ice.
With an ice cover, the lake becomes reverse stratified, with the coldest water located on the
2
surface of the lake. In 2002, Cougar Lake was stocked with fish, most notably largemouth
bass, to improve lake quality and recreational fishing.
Cougar Lake was created by damming off the site of a seasonal stream. That stream
was considered to be waters of the state, and thus is regulated by the Illinois Environmental
Protection Agency. The IEPA has separate sets of rules for artificial cooling ponds, and lake
systems, so when the campus air conditioning plant began to use the lake for cooling, it was
still considered under the jurisdiction of the IEPA. The difference in artificial cooling ponds
and lake systems is the biota. Usually, artificial cooling ponds do not have complex biotic
systems contained in them, and herein lays the problem. When a lake is used for cooling of
mechanical systems, the ecology of the lake, as well as the status of the biota must be
considered. The IEPA’s interest in Cougar Lake stemmed from the impact of heated effluent
on the organisms contained within this system (Robert Washburn, personal communication).
SIUE Cooling Plant:
The SIUE cooling plant is located on the campus of SIU Edwardsville, and works
similarly to a window air conditioning unit. The cooling system of central campus (campus
dormitories and Cougar Village are not cooled by the SIUE cooling plant) is a closed circuit.
There is a large reservoir, put on line in 2002, which keeps cold water in circulation
throughout pipes in the buildings that draws heat from the air (Robert Washburn, personal
communication). The heated water is brought back to the SIUE cooling plant, and lake water
is used to draw the excess heat from the water in the campus circuit.
Water from Cougar Lake is drawn from a depth of 4 meters and pumped into the
SIUE cooling plant. Within the SIUE cooling plant, indirect heat exchange occurs between
the water in the campus circuit and the lake water. The heat exchange machinery, or chillers,
operate based on temperature. At a lower temperature, there isn’t as much water needed to
3
drive the air conditioning system, so, the chillers operate under various speeds that quicken
and slow as needed (Dennis Duncan, personal communication). Running at 100% efficiency
24 hours a day, the SIUE cooling plant could cycle the epilimnion of Cougar Lake through
its system in 311 days. Water used to cool the central campus, not including the residence
halls, is pumped back into the reservoir, and the effluent from the SIUE cooling plant is lake
water plus additional heat (1° C above the surface temperature of the lake). Heated effluent
flows into the lake through an artificial stream, and enters the lake at its surface. The process
of heat exchange mostly occurs at night due to decreased energy costs at that time. With
most of the heated effluent entering the lake during the night, it is possible that as the
temperature rises, the lake may show a higher heat content at night than during the day. The
additional heat added to the solar warming during the day could lead to temporal rises in the
lake’s heat content.
Literature Review:
Over the last 30 years, engineers have been researching means of economically
cooling machinery. One of the solutions to this problem is the cooling reservoir. Cooling
reservoirs are generally defined either as ponds dug specifically for that purpose, or stream
beds dammed off to form an impoundment. Advantages of the cooling reservoir to dispose
of waste heat are: lower capital costs, low consumptive use of water, lower consumption of
energy, dissipation of waste heat over a large area to the atmosphere, and greater thermal
inertia (Majewski and Miller, 1979). A cooling reservoir gives the largest cooling capacity,
but is constrained by the large area needed for construction.
Although there is a large area demand for the construction of these reservoirs, they
are becoming more common. Some of the newest power plants that utilize lakes for cooling
are not building their own lakes, but instead are utilizing larger lakes for their cooling needs.
4
One such example is Cornell University’s cooling plant, which is located on the shore of
Lake Cayuga (Figure 1). The Cornell cooling plant operates similarly to the SIUE cooling
plant, but on a much larger scale. Differences occur in the depth at which water is drawn
from and the temperature difference at which water is put back into the lake. SIUE’s cooling
plant draws its water from 4 meters (in the epilimnion) and puts water back 1° C above the
surface lake temperature, while Cornell’s cooling plant removes its water from 250 ft
(bottom of the lake) and replaces the water at about 8° C above surface lake temperature.
Engineers calculate the design of cooling reservoirs by careful modeling, and rules of
thumb. Some of these rules of thumb are 1-2 acres of lake per megawatt of installed
capacity, or 75-150 btu of heat loss per hour per square foot. Engineers cannot always
strictly follow these rules because meteorological differences in different areas may have
large effects on the rate of heat transfer. Thus, all cases must be considered on an individual
basis (IEPA, 1971).
In addition to rules of thumb, engineering research has shown that certain design
aspects of cooling lakes provide more efficient heat dissipation than others. Research has
determined that lakes with similar surface areas can show great differences in cooling
performance. Heat transfer that occurs within the impoundment governs the amount of
surface cooling that can be attained. The most effective configuration is a deep, wellstratified impoundment. This configuration type exhibits good steady state performance, is
density current dominated, and has excellent thermal inertia (Jirka et al., 1981). Deep,
stratified impoundments are usually wind mixed in the summer, with most of the heat being
contained in the epilimnion. Here, the wind is the agent of mixing, which allows the heat to
be homogenized within the mixed layer (Harleman, 1982). In this case, the ideal cooling
5
Figure 1: Cornell University Plant Function. (The Cornell plant utilizes the same technique
as SIUE, but draws colder water from deeper water in a much deeper lake. From
http://www.utilities.cornell.edu/LSC/News/WhyLSC/default.htm.)
6
lake will have a high length: width ratio as well as a large fetch (Jirka et al., 1981). The fetch
is an uninterrupted length of lake surface that will allow more powerful wind mixing
(Edmunson and Mazumder, 2002).
In some areas, construction of a deep, stratified impoundment may not be feasible. In
such instances, shallow depth cooling ponds are the only alternative. These ponds are not as
effective and tend to have problems with internal recirculation. Recirculation will lead to a
breakdown of the cooling mechanism by not allowing the pond to mix as well, which also
won’t allow for efficient surface cooling. Shallow ponds need an internal arrangement of
baffles, or below water barriers, to prevent internal recirculation zones. If only a shallow
pond design is feasible, the design of the pond should arrange the baffles to decrease the
number of directional flow changes, which will also prevent recirculation, or create a Ushaped pond to offset the large costs of baffle design (Jirka et al., 1981).
Other criteria have been applied to cooling lakes to increase their cooling capacity.
One such method is spray cooling. Placing a fountain into a cooling lake will greatly
increase the amount of evaporative loss that can be gained from a cooling lake (up to a 20
fold increase) (Ryan, 1975). Another possible mechanism of cooling is the addition of
vegetation to the cooling pond. Miller (1974) found that costal mangrove forests may
provide increased cooling by the shade provided to the surface of the lake. The shade from
the trees could increase the turbulent transfer of heat and water vapor from the surface of the
water body. Although this study occurred in a tropical area, the advantages could be seen
throughout the temperate region with additional study.
Heat Budget:
The heat budget of a lake is the total amount of heat that is contained in a body of
water at any given time. The heat budget is calculated based on the premise that 1 calorie of
7
energy will raise 1 cm3 of water 1° C. The heat budget is expressed as the amount of heat
contained in the lake over the lake’s surface area. Studies that contain such data refer to it as
the Birgean Heat budget, named after E.A. Birge, the scientist who first calculated it. Birge
and Juday did the first such studies in 1915 at the Finger Lakes in New York (Stewart, 1974).
Juday (1940) later quantified the amount of energy contained in Lake Mendota in Madison,
Wisconsin. From his data, he contended that energy budgets of lakes at different latitudes
are different due to the amount of solar radiation that they receive. For instance, heat content
of temperate lakes will have a peak heat budget in the warm summer months, with most of
the heat being contained in the mixed epilimnion. There will be a constant amount of heat in
the non-mixed hypolimnion until periods of turnover in fall and spring when the lake is
entirely mixed. A decrease in solar radiation over the summer months should result in a
lower heat budget in a temperate lake. Conversely, a tropical lake will receive direct solar
radiation for a longer period of time. Tropical lakes are continually mixed, thus the heat is
allowed to dissipate throughout the entire lake volume, resulting in a larger heat budget.
Heat budget studies are of importance because the amount of solar radiation received
by a lake over the course of a year is the major determining factor of the changes in the
physical, chemical, and biological cycles that occur in the water column (Juday, 1940).
Changes in this heating pattern could alter these cycles greatly. Therefore, by calculating the
amount of energy gained from solar radiation and calculating the loss of surface energy due
to evaporation, it is possible to measure and quantify extraneous sources of heat such as
thermal pollution from industrial plants that use water bodies as a depository for waste heat.
A study done by Stewart (1974) utilized Birgean heat budget data to assess variation
in the heat content in lakes in Madison, Wisconsin. He assessed the impact of a power plant
thermal discharge into a dimictic lake, Lake Monona. Jets discharge heated effluent into the
8
lake at a temperature 10° C above the lake surface temperature. The power plant operated at
a capacity that would cycle the entire volume of the lake over the span of one year, but
Stewart found that the heated effluent did not cause an increase in the heat content of Lake
Monona when compared to 2 lakes without a thermal discharge. Stewart also determined
that the major influence of the heat content of Lake Monona is the local climate. Average
rise in the temperature in Lake Monona was 0.03° C per day, which is small compared with
the day-to-day variation in mean temperature (Hoopes el al., 1968). Although there is a
heated effluent released into Lake Monona, the quick dissipation of heat throughout the
volume of the lake would suggest that the impact of the power plant discharge only affects
the local discharge area (Stewart, 1974). Stewart also contends that since the climatological
variation controls the heat content of the lake, concerns about the overall impact of thermal
discharge (except at the point source discharge) in Lake Monona may be over estimated.
Thermal Pollution:
Thermal pollution is a well-documented phenomenon. Usually it is associated with
large-scale power plant cooling systems, but it can also be associated with small-scale
systems such as SIUE’s cooling plant. Addition of large quantities of waste heat into a lake
could have a very noticeable impact on the biota of that lake through physical change of the
lake shape around the discharge due to erosion from cooling plant effluent, entrapment of
organisms at the area of water intake, stress on organisms due to temperature rise, and in
some cases cooling systems may have an effect on the local climate.
If the thermal discharge is at a great enough force, such as thermal jets, the discharge
area may be structurally altered. Changes in substrate and altered currents have been
noteworthy near the discharge area in some cooling lake systems (Majewski and Miller,
1979). If these systems require a powerful intake system, any organism, most notably (but
9
not limited to) fish, will be affected within a close proximity to the intake pipe. Intake pipes
are usually fitted with screens to prevent larger organisms from entering the system, but this
does not mean that they cannot be harmed in the process. If the intake is powerful enough,
fish could be trapped onto the screens, which could cause them to be killed if they cannot
sufficiently fight the current. Impacts could be costly to the ecosystem and to fisheries if the
lake is used in this manner (Majewski and Miller, 1979; Sill and Gnilka, 1975; Voigtlander,
1980).
There are many ways that aquatic organisms could be negatively affected by thermal
discharges. Phytoplankton, zooplankton, invertebrates, and juvenile fish will be able to pass
through the entire system, which can cause death, and lessen recruitment of these organisms
(Majewski and Miller, 1979). Thermal tolerance of organisms can be exceeded.
Developmental stages of fish eggs may be especially vulnerable. If fish eggs encounter a
large increase in temperature early enough in development, the result could be abnormal
development or death. The ranges of thermal tolerance of fish eggs vary with species, and
need to be evaluated on a species by species basis (Frank, 1974). Organisms are also not
always directly harmed by heated effluent. Thermal discharges have been shown to increase
the number and abundance of pathogens in water systems. Examples of this are increases in
pathonogenic amoeba (Coutant, 1980), alteration of parasite host relationships (Bourque and
Esch, 1974), and even increased human pathogens in waters directly associated with cooling
systems (Lewis, 1980). The greatest effect, though, would be as a result of a combination of
the above factors.
Climate change could also be an expected effect of a cooling lake. Evaporative
surface cooling is an important mechanism for removal of heat from a cooling lake
(Hoffmann, 1980). Large lake systems, such as Lake Michigan, have a direct effect on the
10
climate of the surrounding environment. Large amounts of heated effluent added to larger
lakes could increase effects such as: ground level fog and ice, clouds and precipitation, and
severe weather effects (Majewski and Miller, 1979). These atmospheric effects are more
likely on a large scale, and most likely will not be seen at Cougar Lake due to the small-scale
operation of the SIUE cooling plant.
Despite many negative effects associated with thermal inputs to water systems, there
are also benefits. Fisheries could be positively impacted by an increase in water temperature.
In Cougar Lake, the best fishing is found in one of the warmest, shallowest areas of the lake
(Robert Washburn, personal communication). Thermal discharge areas have also been found
to create preferential habitat for fishes. Cooke et al. (2004) found that smallmouth bass spent
their time in the warmest areas of the water in the summer, and resided within the thermal
effluent in the winter. This example provides support that increased water temperature could
positively impact the productivity of fisheries.
Hypothesis:
I believe that the epilimnion of Cougar Lake is the major determinant of the overall
heat budget of the lake. Because Cougar Lake is dimictic, the major impact of the SIUE
cooling plant will be seen in the upper 5 meters. There is no cooling demand over the winter
months when the lake is fully mixed, whereas the bulk of the demand for cooling will be in
the summer months when the lake is stratified. Since the hypolimnion will not be affected
during the peak-cooling season, the epilimnion is where the interaction between organisms
and waste heat will take place. An addition of large amounts of heat could potentially have
an adverse impact on the top 5 meters of Cougar Lake. My hypothesis is that during the
summer months, the heat put into Cougar Lake by the SIUE cooling plant will raise the
overall heat budget of the lake.
11
Chapter II
METHODS:
Data on the heat budget of Cougar Lake were collected over a period of two years
(2003-2004). In 2003, measurements were taken during the period from March 12 –
December 15, and in 2004 from March 31 – December 16. HOBO© data loggers, 6 x 4
centimeter microprocessors, were used to take water temperature measurements every two
hours during the study period. To prevent water damage, data loggers were placed in water
tight containers with drying packs after being enclosed in whirl pack bags.
Data loggers were placed in a string of pearls configuration using buoys as a float and
marker, a 2.5 kg circular plate as an anchor, rock-climbing clips to attach containers to the
rope, and fishing weights to prevent the sensors from floating outside the desired depth
(Figure 2). In 2003 the measured depths were: 0, 1, 3, 5, 6, 7, 9, and 11 meters. In 2004 the
measured depths were from 0 – 11 meters with a sensor present at each meter interval.
Measurements of air temperature were also obtained by placing a data logger in a whirl pack
bag and a plastic container, which was then attached to the shaded side of a tree on the lake
shore. This sensor was placed in the shade to prevent excess heating from direct sunlight.
My primary sampling site was located near the outflow spillway in the northernmost
arm of Cougar Lake (Figure 3). The array was placed in the deepest part of the lake (12
meters), located northeast of the SIUE cooling plant discharge stream. The array was
stationary except during periods of inclement weather (high winds), where it tended to move
in the range of ~ 5 – 10 meters. The area of each lamina, 1-meter deep increment, of the lake
was calculated by first taking 40 – 50 depth samples throughout the lake. Depth samples
12
Figure 2: Sensor Array. (Sensors were attached to rope using rock climbing clips at 1 m
intervals from 0-11 m. The array was anchored using a 2.5 kg circular weight, and
floated using a buoy.)
13
11
8
2
5
0
0.2
0.4
kilometers
Figure 3: Sampling Site Location. (Sample site, indicated by a star, and depth contours for
2, 5, 8, and 11 meters. My sampling site was located in the deepest part of Cougar
Lake.)
14
were completed by R. Brugam and C. Guo and are reported in Guo (2001). Each sampling
point was marked with GPS coordinates. The measured coordinates were placed on a map of
Cougar Lake in the MapInfo© computer program, and contour lines were drawn around
coordinates with similar depth measurements. Areas of each lamina were then calculated
using the MapInfo© GIS System (Richard Brugam, personal communication).
My sampling site was reached using a boat equipped with a 6 horsepower motor.
Once in place, the boat was anchored in position and the sensor array was removed from the
water for downloading. Care was taken not to remove the array from its position during
times when measurements were being taken. Data from the sensors were downloaded using
an Onset Computer Corporation HOBO Shuttle© data transporter. After sensors were
downloaded, point measurements of light, dissolved oxygen, temperature, and secchi disc
transparency were taken before returning to the lab to download data onto the computer.
Data from the HOBO shuttle© was downloaded to the Onset Boxcar© computer
program, and then exported to a Microsoft excel spreadsheet as a text file. Data from 3/12 –
8/15/2003 were obtained from a previous study by Micah Miranda to complete the
temperature profile for that year. Temperature profiles for both 2003 and 2004 were graphed
in degrees Celsius as a line graph and an isopleth diagram. For some particular days,
temperature was plotted as a line graph to show anomalies in data.
Temperatures in degrees Celsius were first converted to energy for all measured
laminae in cal/cm3 using the formula:
(1) Thickness of lamina (m)* Area of lamina (m)* temperature (Celsius) * 106 (cm)
The thickness of the lamina for equation 1 would be 1 for both 1 and 6 meters deep because
they were only one m thick. The thickness of the lamina 3, 5, 7, 9, and 11 meters deep would
be 2 because these sensors were used to calculate heat for laminae without sensors.
15
Summation of the energy for the laminae was then used to generate the heat budget for 2003
and 2004. Heat budgets were then calculated in Kcal/ cm2 for the entire lake using the
equation:
(2)
∑ energy of laminas (Kcal*cm-3)
(surface area of lake (m2)* (1 * 106 cm)
In 2004, all laminas were measured, so equation I from above was used to generate the
energy for each lamina because there were no unmeasured laminas to account for. A heat
budget for the epilimnion (0 – 5 meters) was calculated for 2003 and 2004 using equation 2
from above.
I then obtained temperature data from two previous studies done by Rosen (1978) and
Brugam (personal communication). Data from these previous studies were used to calculate
a heat budget for both the entire lake and the epilimnion for 1975 and 1990. Equation 1 was
used to generate energies for each lamina because all were measured, and equation 2 was
used to generate heat budgets. After all heat budgets were calculated, scatter graphs were
made showing heat budgets for the entire lake and the epilimnion. Next separate heat budget
compilation graphs were made for the Cougar Lake, which contained data from 1975, 1990,
2003, and 2004.
When the final temperature data were calculated, I obtained data from the SIUE
cooling plant. Lee Hoffmeier, manager of the SIUE cooling plant, was contacted and
reported that at 100% efficiency, 12000 btu of heat per hour would be produced for each of
the 3 chillers. The amount of heat produced by the SIUE cooling plant in Kcal/ cm2 for both
2003, and 2004 was calculated using the equation:
(3) Total hours running * operating efficiency * 18.3 million btu * 252 (calories/ btu) * 0.001
(Kcal/cal)
(Surface area of the lake (m2)* 1 * 106 cm)
16
After the amount of heat contributed per day from the SIUE cooling plant was calculated, it
was totaled to determine the amount of heat contributed by the SIUE cooling plant over the
course of the year.
Total heat input from the SIUE cooling plant for 2003 and 2004 was then compared
to heat loss from the lake. Pan evaporation data from Belleville, IL were obtained from Jim
Angel, Illinois State Climatologist, and the total evaporative loss from the pan was then used
to calculate the amount of heat lost from the lake per month (Kcal/cm2) using following
equation:
(4) Water evaporated from pan (cm) * pan evaporation coefficient * latent heat of
vaporization of water (cal/cm3) * 0.001 Kcal/ cal
Heat rise per day of Cougar Lake was calculated for 2003 and 2004 by subtracting the
maximum heat budget of a given day from the maximum heat budget of the previous day.
A multiple regression analysis was done to determine the effect of both mean daily
temperature and SIUE cooling plant output on the heat rise in Cougar Lake from one day to
the next. The multiple regression analysis was done on a day by day basis within the year for
both 2003 and 2004. Daily mean temperature and SIUE cooling plant output were lagged by
two days for each year to ensure that there were no effects of either variable on the heat rise
of Cougar Lake for following days. In addition to the time lag analysis, scatter graphs were
made for both years comparing the epilimnetic heat budget to the daily heat input from the
SIUE cooling plant to further assess any effect from the SIUE cooling plant.
Finally, data loggers were placed horizontally from the SIUE cooling plant effluent
stream for one week starting on 3/31/2005 and ending on 4/14/2005. Data loggers were
placed in an arc and their locations were marked using GPS positioning (Figure 4). I wanted
to determine if a temperature input from the plant could be detected. Detection of a plume of
17
Figure 4: Sensor placement for Horizontal Temperature Profile. (Sensors radiated outward
from the effluent stream marked by stars.)
18
heated effluent would be determined by increased temperature of the water near the SIUE
cooling plant effluent stream, and lower temperatures away from the effluent stream. Timing
of placement of data loggers was picked so that there would be a period of SIUE cooling
plant inactivity followed by a period of activity. This particular timing was chosen because it
would mark the initial activation of the SIUE cooling plant for the year 2005. If there was a
plume of heated effluent, I would expect to see increased water temperatures closest to the
effluent stream between 4/1 and 4/3/2005. Data were then collected, downloaded, and
plotted in a line graph.
19
Chapter III
RESULTS
2003:
The vertical temperature profile for 2003 shows a maximum temperature of 32.76° C
at 1 m on 7/8, and a minimum temperature of 4.57° C at 11 m on 12/14. The upper
temperature limit was taken from 1 m because the sensor located at 0 m was partially
exposed at the water surface, and was influenced by direct solar radiation (Figure 5). The
heat budget showed a maximum heat content of 13.85 kcal/cm2 on 8/26, and a minimum heat
content of 2.439 kcal/cm2 on 3/13 (Figure 6). Most of the heat in Cougar Lake is contained
within the epilimnion (first 5 meters). Figure 6 shows that the heat budget of the epilimnion
closely follows the contours of the heat budget for the entire lake, and the hypolimnion heat
budget does not. Thus, the majority of the heat in the lake is contained in the epilimnion,
which drives the warming and cooling of the lake. The hypolimnion (6-11 m) little effect on
the heat budget of Cougar Lake in the summer because it remains constant. It becomes
increasingly important during fall turnover, because its heat budget rises as Cougar Lake
turns over, allowing a greater range of habitat for biota.
The heat input from the SIUE cooling plant shows a maximum of 0.071 Kcal/cm2 on
8/20, which coincides with the return of students to campus after summer break. The
minimum heat input from the SIUE cooling plant, on days when it was running, was 0.0044
Kcal/cm2 on 11/26. Minimal cooling is needed in the cooler months of the year. The total
amount of heat that was added to Cougar Lake from the SIUE cooling plant in 2003 was 6.6
Kcal/cm2 (Figure 7).
20
20 20
2
5
30
3030
30 30
30
30
20
25
2020
10
30
15
20
25
30 30
15
20
20
20
10
20
20
10
10
4
10
25
15
5
25
15
Depth (m)
20
6
55
10
5
5
20
15
10
10
25
10
5
15
20
15
10
20
10
10
15
10
15
8
15
10
5
10
10
5
5
10
10
10
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Day
Figure 5: 2003 Vertical Temperature Profile. (Data for 0 meters was omitted in the diagram
(isopleth) because the sensors were exposed to direct solar radiation.)
21
16
Total Lake
Epilimnion
Hypolimnion
2
2003 Heat Budget (Kcal/cm )
14
12
10
8
6
4
2
0
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan
Day
Figure 6: 2003 Heat Budget. (The epilimnion curve closely follows the curve for the entire
lake, suggesting the driving force in heat content for 2003 is the epilimnion (0-5 m).
Data points were calculated using equation 2.)
Running total of Plant Heat Input per day (Kcal/ cm2
22
7
6
5
4
3
2
1
0
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Day
Figure 7: 2003 Air Conditioning Plant Output. (The total amount of heat that could have
been added by the air conditioning plant in 2003 was 6.6 Kcal/cm2. Heat addition
data were calculated by taking a running sum of the values from equation 3.)
23
Multiple regression analysis showed that the heat rise in the lake per day is not
correlated with the heat input From the SIUE cooling plant for that day (p = 0.671). The
mean daily temperature, though, is correlated with the rise in lake temperature for that day (p
= 0.00005). The multiple regression when daily mean temperature and SIUE cooling plant
heat were lagged for 1 and 2 days shows that the heat added from the SIUE cooling plant
does not affect the temperature in the lake for the days following the heated effluent release
into Cougar Lake( p = 0.459, 0.770) (Figure 8). Mean daily temperature correlated with the
mean daily air temperature for the following day (p = 0.026), but loses its correlation with the
heat rise of the lake after 2 days (p = 0.324) (Figure 8). The r-values for the multiple
regressions were as follows: 0.12 for the same day, 0.02 lagged one day, and 0.006 lagged 2
days. These r-values show that for the same day, only 12% of the variation is explained on
the same day, 2% is explained lagged one day, and < 1% is explained by the regression when
lagged 2 days. The overall heat budget of Cougar Lake shows a similar pattern to the heat
input of the SIUE cooling plant per day, because warmer days will increase cooling demand
(Figure 9).
Table 1: SIUE Cooling Plant Output. (Maximum and minimum output values from the
SIUE cooling plant in 2003 and 2004 which were calculated using equation III.)
2003
Heat
(Kcal/cm2)
Maximum Plant
Input
Minimum Plant
Input
Maximum Plant
Input
Minimum Plant
Input
0.071
0.004
2004
Heat
(Kcal/cm2)
Date
8/20/2003
11/26/2003
Date
0.082
6/18/2004
0.004
3/29/2004
24
2.0
2
a.)
d.)
Residual Heat Rise
2
Lake Heat Rise (Kcal/cm )
1.5
1.0
0.5
0.0
-0.5
-1.0
1
0
-1
-2
-3
0
50
100
150
200
-5
250
0
SIUE Cooling Plant Output (cal * 106)
5
10
15
20
25
30
35
30
35
Daily Mean Temperature (Deg C)
2.0
2
b.)
e.)
Residual Heat Rise + 1
2
Lake Heat Rise + 1 (Kcal/cm )
1.5
1.0
0.5
0.0
-0.5
-1.0
1
0
-1
-2
-3
0
50
100
150
200
250
-5
0
SIUE Cooling Plant Operation (cal * 106)
10
15
20
25
Daily Mean Temperature (Deg C)
2.0
2
c.)
f.)
Lake Heat Rise + 2 (Kcal/cm2)
1.5
Residual Heat Rise + 2
5
1.0
0.5
0.0
-0.5
-1.0
1
0
-1
-2
-3
0
50
100
150
200
SIUE Cooling Plant Operation (cal * 106)
250
-5
0
5
10
15
20
25
30
35
Daily Mean Temperature (Deg C)
Figure 8: 2003 Multiple Regression Analysis. (Letters a-c show residual heat rise of
Cougar Lake vs. SIUE cooling plant operation. The SIUE cooling plant has no effect
on the heat rise in the lake for any day (p = 0.671, 0.459, 0.770). Letters d-f show
lake heat rise vs. daily mean temperature. Daily mean temperature has an effect on
the heat rise of Cougar Lake for 1 day (p = 0.00005, 0.026), but loses its correlation
at 2 days (p = 0.324).)
14
5e+8
plant day vs plant heat
day vs epilimnion heat budget
12
4e+8
10
3e+8
8
6
2e+8
4
1e+8
2
0
Daily Plant Heat Output (Kcal)
2
2003 Epilimnion Heat Budget (Kcal/cm )
25
0
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Julian Day
Figure 9: 2003 Epilimnion Heat Budget and Daily Plant Heat Output. (On warmer days,
there is an increased demand for cooling, so there will be more plant activity, thus
more heat output from the plant.)
26
Evaporative heat loss from Cougar Lake showed a maximum of 8.99 Kcal/cm2 for the
month of July, and a minimum of 5.571 Kcal/cm2 for the month of September. Total
evaporative heat loss for Cougar Lake in 2003 was 36.54 Kcal/cm2 (Figure 10). Evaporative
heat loss from the lake surface far exceeds the heat input from the SIUE cooling plant when
comparing the total amount of heat that could have been contributed to the lake from the
SIUE cooling plant (6.6 Kcal/cm2) to that of the evaporative loss of the lake (36.54
Kcal/cm2). On 7/18, the maximum heat budget of Cougar Lake was reached at 12 am
(Figure 11). Thus the SIUE cooling plant may have a small warming effect on Cougar Lake
on particular nights.
2004:
The vertical temperature profile for 2004 shows a maximum temperature of 34.43º C
at 1 m on 7/22, and a minimum temperature of 5.4º C at 11 m on 12/16. Again, the upper
temperature limit was taken from 1 m because the sensor located at 0 m was partially
exposed at the water surface, and was easily influenced by solar radiation (Figure 12). The
heat budget showed a maximum heat content of 14.39 Kcal/cm2 on 7/22 and a minimum heat
content of 2.94 Kcal/cm2 on 12/16 (Figure 13). Again most of the heat in the lake is
contained in the epilimnion, and there is little to no contribution to the heat budget by the
hypolimnion (Figure 13). The same patterns were seen as 2003, where the hypolimnion heat
content continued to rise as the Cougar Lake’s heat budget decreased, which signals that the
hypolimnion is warming due to fall turnover.
Heat input from the SIUE cooling conditioning plant shows a maximum of 0.082
Kcal/cm2 on 6/18, and a minimum for days it was running was 0.0044 Kcal/cm2 on 3/29.
The total amount of heat that could have been added to Cougar Lake in 2004 from the SIUE
cooling plant was 5.806 Kcal/cm2 (Figure 14).
Lake Surface Evaporative Loss (Kcal/ cm2)
27
40
2003
2004
30
20
10
0
MAY
JUN
JUL
AUG
SEP
total
Month
Figure 10: Evaporative Loss from Lake Surface. (The total surface area evaporation in
Cougar Lake was 36.54 Kcal/cm2 for 2003, and 35.65 Kcal/cm2 for 2004. Monthly
surface evaporative loss was calculated using equation 4, and the total evaporative
loss was calculated by summing the monthly totals.)
28
Heat Budget (Kcal/ cm2)
12.8
12.7
12.6
12.5
12.4
12.3
16
17
18
19
20
21
Day in July 2003
Figure 11: Heat Budget from 7/ 16 – 7/ 21/ 2003. (The maximum heat content of Cougar
Lake on 7/18 was attained at 12am, suggesting that the campus air conditioning plant
may raise the heat of Cougar Lake on some nights. Heat budget calculated using
equation 2.)
29
0
1010
15
15 25
2525
2525
25
25
15
15
30
Depth
20
15
25
25
25
10
30 30
15
4
15
30
25
2
5
25
25
15
20
10
10
20
10
20
25
6
10
15
15
15
15
8
10
10
10
10
10
15
10
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Day
Figure 12: 2004 Vertical Temperature Profile. (Data for 0 meters was omitted in the
diagram (isopleth) because the sensors were exposed to direct solar radiation.)
30
16
Total Lake
Epilimnion
Hypolimnion
2
2004 Heat Budget (Kcal/cm )
14
12
10
8
6
4
2
0
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan
Day
Figure 13: 2004 Heat Budget. (The epilimnion curve closely follows the curve for the
entire lake, suggesting the driving force of the heat content of the lake in 2004 is the
epilimnion. Heat Budgets calculated using equation 2.)
2
Heat Added From Plant Per Day (Kcal/cm )
31
7
6
5
4
3
2
1
0
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan
Day
Figure 14: 2004 Air Conditioning Plant Output. (The total amount of heat that could have
been added to Cougar Lake by the plant in 2004 was 5.964 Kcal/cm2. Heat addition
data were calculated by taking a running sum of the values from equation 3. )
32
Multiple regression analysis showed that the heat rise in the lake per day is not
correlated with the heat input from the SIUE cooling plant for that day (p = 0.852), but the
mean daily temperature was correlated with the rise in lake temperature for that day (p =
0.0068). The multiple regression when daily mean temperature and SIUE cooling plant heat
were lagged for 1 and 2 days showed similar results to 2003. The heat added from the SIUE
cooling plant does not affect the temperature in the lake for the days following the heated
effluent release into Cougar Lake (p = 0.254, 0.150) (Figure 15). Mean daily temperature
loses its correlation with heat rise of the lake on the following day, a shorter time period than
in 2003 (p = 0.704) (Figure 15). The r-values for the multiple regressions were as follows:
0.04 for the same day, 0.009 lagged one day, and 0.01 lagged 2 days. These r-values show
that for the same day, only 4% of the variation is explained on the same day, < 1% is
explained lagged one day, and 1% is explained by the regression when lagged 2 days.
Similarly to 2003, heat input from the SIUE cooling plant showed a similar increase to the
overall heat budget of the lake, because warmer days would require a larger cooling demand
(Figure 16).
Sensors were placed horizontally outward from the SIUE cooling plant effluent
stream (Figure 4) to attempt to detect a plume of warm water entering Cougar Lake (Figure
17). Sensors 1 and 3 were omitted due to a mechanical malfunction. There is a daily
temperature cycle in Cougar Lake, with the maximum temperature peaking between 11am –
2pm, which can be attributed to the natural daily warming rather than SIUE cooling plant
effluent.
Evaporative loss from Cougar Lake in 2004 showed a maximum of 8.39 Kcal/cm2 for
July, and a minimum of 5.964 Kcal/cm2 for September. Total evaporative loss from the lake
in 2004 was 35.65 Kcal/cm2 (Figure 10). These numbers were slightly lower than
33
3
2
c.)
Lake Heat Rise + 2 (Kcal/cm2)
a.)
Residual Heat Rise
2
1
0
-1
-2
1
0
-1
-2
-3
0
50
100
150
200
250
300
-5
0
5
SIUE Cooling Plant Operation (Cal * 106)
15
20
25
30
35
3
3
b.)
d.)
Lake Heat Rise + 1 (Deg C)
2
Residual Heat Rise + 1
10
Daily Mean Temperature (Deg C)
1
0
-1
-2
2
1
0
-1
-2
0
50
100
150
200
250
6
SIUE Cooling Plant Operation (cal * 10 )
300
5
10
15
20
25
30
35
Daily Mean Temperature (Deg C)
Figure 15: 2004 Multiple Regression Analysis. (Letters a and b mark the residual heat rise
of Cougar Lake vs. SIUE cooling plant operation. The SIUE cooling plant has no
effect on the heat rise in the lake for either day (p = 0.852, 0.254). Letters c and d
show lake heat rise vs. daily mean temperature. Daily mean temperature has an
effect on the heat rise of Cougar Lake for the day the measurement was taken (p =
0.0068), but loses its correlation the following day (p = 0.704).)
5e+8
14
Daily Plant Heat Input
Epilimnion Heat Budget
12
4e+8
10
3e+8
8
6
2e+8
4
1e+8
2
Daily Plant Heat Input (Kcal)
2004 Epilimnion Heat Budget (Kcal/cm2)
34
0
0
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan
Day
Figure 16: 2004 Epilimnion Heat Budget and Daily Plant Heat Output. (On warmer days,
there is an increased demand for cooling, so there will be more plant activity, thus
more heat output from the plant.)
35
Temperature (Deg C)
18
sensor 6
sensor 7
16
14
12
sensor 2
sensor 4
sensor 5
10
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Day
Figure 17: Horizontal Temperature Profile from 3/ 31 – 4/ 14 2004. (Each peak appears
between 11am and 2pm indicating that the variation temperature in Cougar Lake is a
factor of the local climate.)
36
evaporative loss in 2003. Total evaporative loss of Cougar Lake far exceeded the input from
the SIUE cooling plant when comparing the total amount of heat that could have been added
by the SIUE cooling plant (5.806 Kcal/cm2) and the total evaporative loss of Cougar Lake
(35.65 Kcal/cm2).
1975, 1990, 2003, and 2004 Comparison:
Figure 18 compares heat budgets from 1975, 1990, 2003, and 2004. Data for 1975
and 1990 were collected using temperature probe data taken approximately once monthly.
For each year, heat budgets follow a similar pattern of warming and cooling. The major
differences between the years are the rapidity of the increase in lake heat content and the time
of peak heat content.
In 1975, the lake showed a similar warming and cooling pattern as 2003. The
rapidity of the increase and decrease in heat content was similar, although 1975 shows lower
values at most points sampled. Data points for 1975 also show similar peaks to 2003, with
data points following similar patterns of variation throughout the year. There were not as
many data points sampled in 1975, so we cannot determine the maximum heat content.
Very few data points were available for 1990, but heat content values for this year are
consistently lower for this year than all other years. The increase and decrease of heat
content shows similar patterns to each other year, and maximum heat content seems to peak
around the same time as 2003.
The heat budget for 2004 was the least similar to the other 3 years. Each year the
maximum heat content was shown at around day 250, but in 2004 the peak was seen 50 days
earlier. The lake seemed to accumulate heat more quickly in 2004 than the other 3 years, and
also showed a sharper peak during the period of maximum heat content. Each other year
showed a more gradual incline to the maximum heat content. In 2004, the heat content of the
37
16
2003
2004
Heat Budget (Kcal/ cm2)
14
1990
1975
12
10
8
6
4
2
0
50
100
150
200
250
300
350
400
Julian Day
Figure 18: Heat Budget Comparison: 1975, 1990, 2003, and 2004. (Data for the years
1975, 1990, and 2003 follow similar patterns of increase, decrease, and peak heat
budgets The year 2004 shows a similar pattern of decrease as the other years, but a
quicker increase in total heat budget and an earlier peak heat budget. Heat budgets
were calculated using equation 2.)
38
lake sharply decreased after the maximum heat occurs. The heat content then stayed
relatively constant during the period where maximum heat is attained in 2003, 1990, and
1975. The decrease in heat content for 2004 then closely follows that of 2003.
39
Chapter IV
DISCUSSION
If the heat budget of Cougar Lake is to be measured accurately, all factors regarding
heat flux into and out of the lake must be taken into account. These factors are defined in the
following equation:
(5) ∆ Heat in Cougar Lake (Kcal/cm2) = Solar Radiation (Kcal/cm2) + Heat from plant
(Kcal/cm2) – atmospheric heat loss (Kcal/cm2)
There are other processes that also can account for thermal energy in a lake, but were
neglected in Cougar Lake due to their minimal impact. These processes are: conduction of
heat from the earth’s crust, transformation of kinetic energy into heat, heating due to
chemical processes, and heating due to biological activity (Saur and Anderson, 1955). We
have also ignored possible heat input from sewage effluent. The above equation was
modified from Saur and Anderson’s by the removal of the gain of heat by advection. Cougar
Lake does not have a constant input from a tributary, so this term does not apply. If my
results are calculated according to equation 5, solar radiation entering the lake can be
determined (Table 2). For both study years, loss of heat to the atmosphere exceeds the
amount of heat added by the SIUE cooling plant by a factor of six. The large discrepancy
between heat added by solar radiation and from the SIUE cooling plant indicates that a
majority of the heat budget of Cougar Lake is a result of solar radiation, which agrees with
Dutton and Bryson’s (1962) findings that the flux of heat through the interface with the
atmosphere is the major source of the heat involved in internal thermal processes of a lake.
40
Although there seems to be no effect on the lake’s heat budget for 2003 and 2004, the
heat budget data suggest that the SIUE cooling plant may have had an impact on the lake
from 1975-2004. From 1975-2004, 205188.6 m3 of building space was added to SIUE
(Washburn, Personal Communication). Thus, the large amount of additional cooling load
may have increased the heat budget of the lake because of the additional SIUE cooling plant
effluent. Although this may seem to be intuitive, the maximum heat budget for 1990 (11.44
Kcal/cm2) is lower than that of 1975, but with 132903.4 m3 of additional building space
requiring cooling. The discrepancy in heat budget from 1975 (12.47 Kcal/cm2) and 1990 to
2004 (14.39 Kcal/cm2) seems to be large, but most likely is a result of insufficient data from
1975 and 1990. For the years 2003 and 2004, I was able to obtain heat measurements from
the lake every 2 hours. In 1975 and 1990, the technology wasn’t available to do such
detailed temperature sampling, so the data for those years were taken once weekly, or even
once monthly. The large gaps of data in 1975 and 1990 may have missed the peak heat
budget for those years, and if the same amount of data was obtained, there might not have
been such a large discrepancy in heat budget values.
Table 2: Calculated Solar Radiation Values. (Show that a majority of the heat flux in Cougar
Lake stems from the interaction of the lake surface and the atmosphere. Both
evaporative loss and solar input greatly exceed the amount of heat generated by the
campus air conditioning plant. Solar radiation was calculated using equation 5.)
Year
Heat
Contained
in Cougar
Lake
(Kcal/cm2)
Solar
Radiation
(Calculated)
(Kcal/cm2)
Heat From
Plant
(Kcal/cm2)
Heat Lost to
atmosphere
(Kcal/cm2)
2004
13.85
43.79
6.6
36.54
2003
14.39
44.234
5.806
35.65
1990
11.44
N/A
N/A
N/A
1975
12.47
N/A
N/A
N/A
41
Although solar radiation is one of the major determinants of the heat budget of a lake
(Benson et al., 2000), morphometry is also important when looking at the lake’s heat budget
(Timms, 1975; Mazumder and Taylor, 1994; Gorham, 1964). The most important aspects of
the morphometry of a lake are surface area, fetch, and mean depth. The surface area of a
lake determines the amount of solar radiation that enters that lake. A lake with a larger
surface area, in general, should have a higher heat budget due to an increased amount of solar
penetration. Also, a larger surface area will, in most cases, create a larger fetch.
In a lake, wind induced mixing determines the depth of the epilimnion and
thermocline and along with evaporative loss, determines the amount of heat retained in the
water column (Ambrosetti and Barbanti, 2001). Therefore, if the fetch is larger, more heat
can be retained in the lake because powerful wind mixing will allow heat to be dissipated
over a larger volume of water.
Mean depth is cited as one of the most important morphometric characteristics of a
lake in many studies (Timms, 1975; Mazumder and Taylor, 1994; Gorham, 1964). Deeper
water columns provide larger capacity to store heat, so a deeper lake with a cold hypolimnion
potentially stores more heat than a shallow lake. Although a deeper lake may have a greater
potential to store heat, it also has to have a large surface area and fetch for there to be a
marked increase in heat content. Without a long fetch, the wind mixing will be less
powerful, decreasing both the depth of the epilimnion and the heat content of the lake. A
large surface area will also allow for larger amounts of heat penetration (through solar
radiation), and a large amount of surface evaporation, which potentially could increase the
heat content of the lake. Both Cougar Lake, and on a larger scale, Cayuga Lake fit this
model.
42
Due to financial constraints, we were not able to obtain heat data from a similarly
sized lake without a thermal input. Although we do not have a full data set, Cougar Lake’s
maximum heat budget can be compared to the maximum heat budget of Lake Waubesa,
Madison, Wisconsin (Stewart, 1973). My reason to compare the heat budgets of these 2
lakes is because of the similarity of their mean depths (Cougar Lake 3.9 m, Lake Waubesa
4.6m). Maximum heat budget of Cougar Lake (13.85 Kcal/cm2 in 2003, 14.39 Kcal/cm2 in
2004) was larger than the mean heat budget of Lake Waubesa over a 3-year period, even
though Lake Waubesa has a larger mean depth. Mean depth is usually directly correlated
with heat content; with a higher mean depth being associated with increased heat content. In
this case, the larger mean depth of Lake Waubesa does not signify larger heat content.
The difference in the heat content of Cougar Lake and Lake Waubesa can result from
many variables. The first is solar radiation. Solar radiation becomes less intense the farther
north of the equator a site is. Thus, less direct solar radiation will mean less heat input to the
lake (Benson et al., 2000). Similarly, at higher latitudes, the temperature could be lower,
potentially lessening the influence of atmospheric heat exchange with the lake surface.
Stewart’s (1973) data also shows variation in the heat budget between years in Lake
Waubesa similar to the heat budget variation in Cougar Lake from 2003 to 2004. From
1962-1963, Lake Waubesa had an increase in the maximum heat budget from 10.95
Kcal/cm2 to 11.74 Kcal/cm2, an increase of 0.8 Kcal/cm2. From 2003-2004, Cougar Lake
showed an increase in the heat budget from 13.85 Kcal/cm2 to 14.39, an increase of 0.54
Kcal/cm2. The increase in the heat budget of Lake Waubesa, a lake without thermal input, in
that 2 year period exceeded the heat budget increase for Cougar Lake over the period from
2003-2004, which suggests that the heat content of both lakes is driven by local climatic
conditions. Even though there is a varying amount of thermal discharge (5.964-6.6
43
Kcal/cm2) in Cougar Lake between years, the change in the heat budget is less than the
change in the heat budget of Lake Waubesa, which would suggest that there is no large-scale
impact of the SIUE cooling plant on the heat budget of Cougar Lake.
Multiple regression analysis showed that for both years, the heat input from the SIUE
cooling plant did not correlate with the heat rise in Cougar Lake. The mean daily
temperature and heat input from the SIUE cooling plant were lagged to assess the impact of
the heated effluent and daily temperature for 2 days. There was no correlation with the input
from the SIUE cooling plant for any of the days following discharge, which shows that there
must be another factor that influences the rise in heat content of Cougar Lake. One factor
that could play a role in influencing lake heat content is the mean daily temperature. In 2003,
the mean daily temperature positively correlated with the temperature of the day the
measurement was taken, as well as the next day. In 2004, the mean daily temperature
positively correlated with the temperature of the day the measurement was taken, but lost its
correlation the following day.
The multiple regression results show that daily mean temperature is a major
determinant of the heat content of Cougar Lake, but it isn’t the only factor. The r-values that
were generated from the multiple regression showed a maximum of .12 and a minimum of
< 0.001. This means that only 12% of the variation in the heat rise in Cougar Lake is
explained by the regression of daily mean temperature and SIUE cooling plant heat against
the heat rise in Cougar Lake. Therefore there are other factors that I have not measured that
have an impact on the change in heat content of Cougar Lake. Examples of such factors are,
but not limited to: rain input, differing amounts of solar radiation input, and humidity in the
air. Any of these factors could contribute to the amount of heat contained in Cougar Lake, or
44
lost to the atmosphere. So, to have an accurate assessment of the driving force of the heat
content of Cougar Lake, these other factors must be taken into account.
The amount of heat cycled through Cougar Lake is much larger than both the amount
of heat contained in the lake and produced by the SIUE cooling plant. Table 1 shows that the
amount of solar radiation exceeds the amount of heat put into the lake by the SIUE cooling
plant by a factor of 7-8 for both years. The amount of evaporative loss for both years
exceeds the amount of heat from the SIUE cooling plant by a factor of ~ 6. Evaporative loss
from the surface of Cougar Lake in a single month is almost equal to, or exceeds, the amount
of heat generated by the SIUE cooling plant over the entire growing season. The large
surface area of Cougar Lake allows for a large amount of evaporation, which leads to a high
amount of heat loss from the evaporated water. The loss of heat through evaporation is the
major reason that allows the heat budget of Cougar Lake to resist changes in heat content that
would be associated with the input of heat from the SIUE cooling plant.
To further assess any impact from the SIUE cooling plant, we determined the
horizontal temperature profile stretching outward from the SIUE cooling plant’s effluent
stream. The SIUE cooling plant, if operating at 100%, would be able to cycle the epilimnion
of Cougar Lake within 311 days. The hypolimnion would not be considered here because the
SIUE cooling plant operates from late spring to fall when the lake is stratified. Therefore, the
mixed layer will not affect water in the hypolimnion, with most heat being contained in the
epilimnion. Water entering the lake from the SIUE cooling plant is only 1° C above the
surface temperature of the lake. The large amount of time it would take to cycle the entire
epilimnion, as well as the small difference in temperature between the surface of the lake and
the effluent, would suggest there should be little to no difference in the temperature readings
of the sensors as the water radiates outward from the SIUE cooling plant effluent stream.
45
Figure 17 shows that there is a temporal cycle for temperature, with peaks occurring each day
between 11am – 2 pm. These peaks are consistent with the maximum temperature and solar
radiation over the course of the day. If an effect of the SIUE cooling plant were to be seen,
peaks would likely occur between 11 pm – 2 am coinciding with the hours of the most
intense SIUE cooling plant operation. There is no plume of heat that is detected from the
effluent stream, the heat from the SIUE cooling plant is most likely dissipated quickly
throughout the epilimnion and lost to evaporation.
Although we did not detect a heat plume outward from the SIUE cooling plant
effluent stream, there may still be a detectible plume present. Sensors 1 and 3, which were
two of the closest sensors to the SIUE cooling plant effluent, malfunctioned and we were
unable to gather data from them. Sensor 1, being closest to the effluent stream, was the most
likely sensor to detect a plume of heat from the effluent stream. Because I could not obtain
these data, it still may be possible that there is a slight temperature plume present. Sensor 7
shows a slightly higher temperature than the rest of the array, which may suggest for some
days when the wind is blowing to the north, the heated effluent reaches sensor 7. Another
possible explanation for the higher temperature reading at sensor 7 may be lake
morphometry. Sensor 7 is in a shallower basin than the other sensors, and if the solar
radiation could penetrate deep enough to warm the substrate of the lake, the temperature at
that spot in the lake would be warmer than in deeper areas.
When Cougar Lake is assessed using the criteria outlined by Jirka et al (1981), it
seems that it is a well-engineered cooling lake. The first such criterion is that the best
cooling lake would be a deep, well-stratified impoundment. Cougar Lake is deep enough to
become stratified, and most of the heat contained in the lake in the summer months is in the
epilimnion, which makes the heat available for evaporation from the surface. Other criteria
46
included a large fetch, which allows for wind mixing allowing the heat to be homogenized
throughout the epilimnion to create a deeper epilimnion (Strub et al., 1985). Cougar Lake
has a long fetch, which allows for a deeper epilimnion, and a continuous cycling of the water
throughout the epilimnion in the summer months (depending on weather patterns). Research
had shown that lakes with similar surface areas showed differences in their ability to
dissipate heat to the atmosphere. Cougar Lake has a large surface area, and when combined
with the long fetch and deep epilimnion, will allow it to dissipate a larger amount of heat
than a shallower lake with a shorter fetch and a similar surface area.
Because a majority of Cougar Lake’s heat comes from solar radiation, it is highly
unlikely that the SIUE cooling plant has a large-scale effect on the heat content of the lake.
Although there may not be any large changes in the heat content of Cougar Lake, there still is
a possibility that there is a small effect of the SIUE cooling plant. Linear regressions for both
2003 and 2004 show a slight upward slope, which indicates that there may be a slight effect
from the SIUE cooling plant, even though the overall data wouldn’t lead to that conclusion.
In 2004, heat input of the SIUE cooling plant was less than 2003, but the heat budget in 2004
was higher. Those heat budget data suggest that the SIUE cooling plant isn’t having an
effect because by that logic, an increased heat load from the SIUE cooling plant would also
show an increased heat content in the lake. Although the heat maximum data for the year
may be inconsistent with the idea that the SIUE cooling plant is affecting the lake, the heat
content for some days may suggest otherwise.
For some nights, the heat content of Cougar Lake reaches the maximum between 10
pm and 2 am. The maximum heat peaking at midnight opposes the view that the maximum
heat content should occur at the time of the maximum air temperature and solar radiation
(between 12-2 pm). Maximum heat content occurring at midnight is consistentnt with the
47
operation of the SIUE cooling plant. The SIUE cooling plant mainly operates at night, due to
lower energy costs. If the SIUE cooling plant operates heavily at night, there should be a
visible effect during the nighttime hours. So, even though a large scale effect is not seen as a
result of the heat input from the SIUE cooling plant, it is still possible that there may be a
small scale effect on the heat content of Cougar Lake at some times of the day and year.
From our data, it seems that concerns over the effect of the SIUE cooling plant on Cougar
Lake may be overestimated.
48
Chapter V
CONCLUSION
Various techniques were utilized to assess the impact, if any; the SIUE cooling plant
has on Cougar Lake. Although there was an increase in the heat content in the lake from
2003 to 2004, it is unlikely that the variation in heat is a result of the SIUE cooling plant’s
activities. Multiple regression analyses determined that the SIUE cooling plant effluent does
not correlate with the rise in the heat content of the lake following discharge for either year
(p = 0.671, 0.459 lagged one day in 2003, 0.852, 0.254 lagged one day in 2004). There also
was not a detectable plume radiating outward from the SIUE cooling plant’s effluent stream.
Climatic variation (temperature and solar radiation) is the major determining factor of
the heat content of Cougar Lake. Multiple regression analysis showed that the mean daily air
temperature correlated with the heat rise in the lake for the day the measurement was
recorded, and for the following day in 2003 (p = 0.00005, 0.026 lagged one day and 0.324
lagged 2 days). The mean daily air temperature correlated with the heat rise in for the day
the measurement was taken, but lost its correlation the following day (0.0068, 0.704 lagged
one day).
The amount of solar radiation that enters the lake, as well as the amount of heat that
evaporated from the surface is considerably larger than the heat discharged from the SIUE
cooling plant. The heat that the SIUE cooling plant discharges is most likely quickly
dissipated throughout the epilimnion, and then lost through evaporation.
Although I did not detect a large-scale effect from the SIUE cooling plant, there may
be a small-scale effect. Such an effect may be detected in the shallow area nearest the SIUE
49
cooling plant’s effluent stream. Overall, the concerns of the impact of the SIUE cooling
plant may be overestimated.
I reject my hypothesis that during the summer months, the heat put into Cougar Lake
by the SIUE cooling plant will raise the overall heat budget of the lake. Climatological
variation, such as solar radiation and daily temperature, is the major determinant of the heat
content of Cougar Lake.
50
LITERATURE CITED
Ambrosetti, W., and Barbanti, L. 2001. Temperature, Heat Content, Mixing, and Stability in
Lake Orta: A Pluriannual Investigation. J. Limnol. 60 (1): 60-68.
Benson, B. J., Lenters, J. D., Magnuson, J. J., Stubbs, M., Kratz, T. K., Dillon, P. J., Hecky,
R. E., and Lathrop, R. C. 2000. Regional Coherence of Climatic and Lake Thermal
Variables of Four Lake Districts in the Upper Great Lakes Region of North America.
Freshwater Biology. 43: 517-527.
Coutant, C. 1980. Pathogenetic Amoebae. In: Internal Atomic Energy Agency Environment
effects of Cooling Systems. IAEA, Austria. P 121-124.
Cooke, S. J., Bunt, C. M., and Schreer, J. F. 2004. Understanding Fish Behavior,
Distribution, and Survival in Thermal Effluents Using Fixed Telemetry Arrays: A
Case Study of Smallmouth Bass in a Discharge Canal During Winter.
Environmental Management, 33 (1): 140-150.
Dutton, J. A., and Bryson, R. A. 1962. Heat Flux in Lake Mendota. Limnol. Oceanogr. 7:
80-97.
Edmunson, J. A., and Mazumder, A. 2002. Regional and Hierarchical Perspectives of
Thermal Regimes in Subarctic, Alaskan Lakes. Freshwater Biology, 47: 1-17.
Harleman, D. R. F. 1982. Hydrothermal Analysis of Lakes and Rivers. Proceedings of the
ASCE. 108: 302-323.
Frank, M. L. 1974. Relative Sensitivity of Different Developmetnal Stages of Carp Eggs to
Thermal Shock. In: Thermal Ecology. Editor: Gibbons, J. W., and Sharitz, R. R.
Technical Information Center US Atomic Energy Commission, Virginia. P 171-176.
Gorham, E. 1964. Morphometric Control of Annual Heat Budgets in Temperate Lakes.
Limnol. Ocanogr. 26: 525-529.
Guo, C. 2002. Accumulation of Copper Algaecide in the Sediment of Cougar Lake, a Small
Illinois Reservoir. M.S. Thesis, Southern Illinois University Edwardsville. P 1–75.
Hoopes, J. A., Zeller, R. W., and Rohlich, G. A. 1968. Heat Dissipation and Induced
Circulations From Condensor Cooling Water Discharges into Lake Monona. Univ.
Wis. Agr. Exp. Sta. Res. Rep. 35. 204.
IEPA. 1971. Effect of Geographic Location on Cooling Pond Requirements and
Performance. US Government Printing Office, Washington DC.
51
Jirka, G. H., Cerco, C. F., and Harleman, D. R. F. 1981. Efficient Cooling Ponds: Design.
Proceedings of the ASCE. 107: 1547-1563.
Juday, C. 1940. The Annual Energy Budget of and Inland Lake. Ecology. 21(4): 138-150.
Lewis, B. G. 1980. Human Disease Organisms in Aerosols From Cooling Towers and
Cooling Sprays. In: Internal Atomic Energy Agency Environment effects of Cooling
Systems. IAEA, Austria. P 124-129.
Majewski, W., and Miller, D. C. 1979. Predicting Effects of Power Plant Once-Through
Cooling on Aquatic Systems. United Nations Educational, Scientific, and Cultural
Organization, Paris.
Mazumder, A., and Taylor, W. D. 1994. Thermal Structure of Lakes Varying in Size and
Water Calrity. Limnol. Oceanogr. 39 (4), 968-976.
Miller, P. C. 1974. Potential Use of Vegetation to Enhance Cooling in holding Ponds In:
Thermal Ecology. Editor: Gibbons, J. W., and Sharitz, R. R. Technical
Information Center US Atomic Energy Commission, Virginia. P 610-627.
Rosen, M. G. 1978. A Limnological Survey of Tower Lake, Madison County, Illinois, with
Special Reference to Artificial Aeration. M.S. Thesis, Southern Illinois University
Edwardsville. P 1-166.
Ryan, P. J. 1975. Heat Dissipation by Spray Cooling. In: Thermal Pollution Analysis.
Editor: Schetz, J. A. MIT Press. Cambridge. P 139-152.
Saur, J. F. T., and Anderson, E. R. 1956. The Heat Budget of a body of Water of Varying
Volume. Limnol. Oceanogr. 1: 247-521.
Sill, B. L., and Gnitka, A. 1975. Optimal Discharge of Power Plant Cooling Waters. In:
Thermal Pollution Analysis. Editor: Schetz, J. A. MIT Press. Cambridge. P 281293.
Stewart, K. M. 1974. Detailed Time Variations in Mean Temperature and heart Content of
Some Madison Lakes. Limnol. and Ocean. 18(2): 218-226.
Strub, P. T., Powell, T., and Goldman, C. R. 1985. Climatic Forcing: Effects of El Nino on a
Small, Temperate Lake. Science. 227: 55-57.
Timms, B. V. 1975. Morphometric Control of Variation in Annual Heat Budgets. Limnol.
Oceanogr. 20: 110-112.
Voigtlander, C. 1980. Effects of Cooling Water Intakes on Fish Populations: Entrainment
and Impingement. . In: Internal Atomic Energy Agency Environment effects of
Cooling Systems. IAEA, Austria. P 60-78.
52
APPENDIX
2003
Day
12Mar
13Mar
14Mar
15Mar
16Mar
17Mar
18Mar
19Mar
20Mar
21Mar
22Mar
23Mar
24Mar
25Mar
26Mar
27Mar
28Mar
29Mar
30Mar
31Mar
Heat
Content
2004
Heat From
SIUE
Cooling Plant
Daily Mean
Air
Temperature
Day
Heat
Content
Heat From
SIUE
Cooling Plant
Daily Mean
Air
Temperature
3.0017
0
14.492
1-Apr
5.1930
13834800
4.59
2.4971
0
11.27
2-Apr
5.3711
85314600
6.58
2.9651
0
5.603
3-Apr
5.4526
101455200
7.81
3.1948
0
11.4675
4-Apr
5.5970
36892800
9.48
3.7821
0
13.2295
5-Apr
5.8019
46116000
6.44
3.4678
9223200
14.127
6-Apr
5.9192
73785600
8.88
3.4849
59950800
15.665
7-Apr
6.0662
0
14.90
3.7189
59950800
14.595
8-Apr
6.1579
92232000
16.96
3.7189
59950800
11.932
6.3126
0
12.47
3.5337
59950800
9.0665
6.1991
78397200
11.31
3.7013
41504400
9.8035
6.1348
0
10.01
3.9276
55339200
14.7625
5.8432
64562400
8.21
4.3836
59950800
16.894
5.8452
36892800
7.88
3.9127
59950800
9.812
6.1411
55339200
7.48
4.2603
41504400
9.9645
6.4678
92232000
10.57
5.1282
23058000
14.5265
6.5971
110678400
15.36
4.8054
18446400
10.2015
7.0606
94076640
21.96
4.1201
55339200
2.3855
9.6535
64562400
23.40
4.2004
9223200
2.6125
50727600
24.60
4.5346
32281200
8.7715
103299840
22.17
1-Apr
6.2168
73785600
19.885
9-Apr
10Apr
11Apr
12Apr
13Apr
14Apr
15Apr
16Apr
17Apr
18Apr
19Apr
20Apr
21Apr
50727600
20.63
2-Apr
6.4266
76091400
20.055
22Apr
72402120
18.69
53
3-Apr
7.0862
101455200
23.22
4-Apr
6.6564
92232000
15.5255
5-Apr
6.1949
92232000
5.973
6-Apr
6.3694
32281200
2.5145
7-Apr
6.2186
11529000
8.4695
8-Apr
5.9959
34587000
3.1485
9-Apr
10Apr
11Apr
12Apr
13Apr
14Apr
15Apr
16Apr
17Apr
18Apr
19Apr
20Apr
21Apr
22Apr
23Apr
24Apr
25Apr
26Apr
27Apr
28Apr
29Apr
5.8539
0
5.3795
6.0945
9223200
7.3385
6.1686
55339200
11.4315
27669600
14.7275
80703000
15.3285
9223200
19.42
73785600
20.99
101455200
17.86
64562400
10.84
0
14.33
46116000
17
50727600
14.93
53033400
11.045
36892800
10.7415
36892800
11.2
46116000
12.295
23058000
10.81
36892800
11.901
83008800
14.6935
73785600
18.26
106066800
19.69
23Apr
24Apr
25Apr
26Apr
27Apr
28Apr
29Apr
30Apr
1May
2May
3May
4May
5May
6May
7May
8May
9May
10May
11May
12May
13May
14May
15May
16May
17May
18May
19May
64562400
13.31
55339200
12.11
0
14.14
59950800
11.27
122207400
12.97
64562400
10.94
0
19.04
46116000
18.73
80703000
17.93
23058000
11.41
46116000
9.61
7.8681
53033400
8.88
8.1109
110678400
13.91
8.6505
0
18.50
8.7480
110678400
23.32
9.2464
209827800
23.40
9.3914
41504400
23.03
9.4864
0
23.30
9.6845
0
22.03
9.7046
0
22.83
9.6339
0
20.34
9.2980
69174000
19.64
9.0917
36892800
13.88
9.3107
87620400
14.54
9.4989
71479800
15.20
9.7026
46116000
21.80
9.5722
73785600
22.70
54
30Apr
1May
2May
3May
4May
5May
6May
7May
8May
9May
10May
11May
12May
13May
14May
15May
16May
17May
18May
19May
20May
21May
22May
23May
24May
25May
26May
27May
115290000
21.625
103761000
18.795
94537800
12.835
64562400
13.3645
66868200
13.175
25363800
20.855
106066800
19.09
106066800
18.655
99149400
16.24
110678400
25.28
115290000
21.485
64562400
14.435
20May
21May
22May
23May
24May
25May
26May
27May
28May
29May
30May
31May
39198600
15.5
48421800
10.0865
9.8932
0
22.77
10.3038
0
25.66
10.4510
138348000
25.52
10.3077
27669600
24.03
10.4631
0
22.46
10.5099
119901600
22.46
10.3188
0
20.67
10.3235
78397200
15.77
10.1392
0
22.76
10.4839
110678400
22.20
10.5979
83008800
20.37
10.5421
73785600
23.13
1-Jun
10.4079
0
18.14
16.7
2-Jun
10.4651
117595800
18.60
99149400
18.225
3-Jun
10.4738
110678400
18.17
10.2461
73785600
18.29
4-Jun
10.3558
0
18.27
10.1787
73785600
16.1
5-Jun
10.5209
0
18.51
10.1946
64562400
17.235
6-Jun
10.5517
0
19.84
10.3770
92232000
20.585
7-Jun
10.7442
0
21.66
10.3784
73785600
21.795
8-Jun
11.0587
119901600
24.03
10.2648
110678400
14.34
10.9326
83008800
26.46
10.5328
83008800
13.17
11.0612
145265400
22.10
10.7015
57645000
13.4665
11.2089
124513200
24.92
10.7348
69174000
14.1365
11.2893
175240800
26.56
10.6401
59950800
14.505
11.3871
18446400
23.14
10.4277
18446400
15.7
11.4635
78397200
23.86
10.6137
59950800
15.395
11.5525
119901600
25.43
10.6850
73785600
17.73
9-Jun
10Jun
11Jun
12Jun
13Jun
14Jun
15Jun
16Jun
11.5145
166017600
24.76
55
28May
29May
30May
31May
8.7789
0
19.16
8.7977
101455200
18.36
9.2009
96843600
19.595
8.8627
73785600
17.605
1-Jun
8.8185
83008800
13.995
2-Jun
8.7931
11529000
11.68
3-Jun
8.5767
39198600
12.835
4-Jun
8.5119
11529000
16.035
5-Jun
8.7533
73785600
16.925
6-Jun
8.7139
64562400
14.835
7-Jun
8.8766
55339200
20.46
8-Jun
9.0818
0
19.09
9-Jun
10Jun
11Jun
12Jun
13Jun
14Jun
15Jun
16Jun
17Jun
18Jun
19Jun
20Jun
21Jun
22Jun
23Jun
24Jun
9.0221
46116000
19.66
9.1972
87620400
21.66
17Jun
18Jun
19Jun
20Jun
21Jun
22Jun
23Jun
24Jun
25Jun
26Jun
27Jun
28Jun
29Jun
30Jun
9.4143
103761000
21.355
9.3663
89926200
9.6475
11.6454
156794400
25.26
11.7299
258249600
25.56
11.5406
175240800
23.57
11.4873
46116000
18.21
11.3711
92232000
18.00
11.2808
92232000
20.90
11.0880
119901600
17.24
11.1986
129124800
18.87
11.0524
87620400
22.80
10.9668
87620400
16.88
11.0539
87620400
17.87
11.1147
46116000
18.81
11.1627
147571200
20.50
11.2862
0
20.20
1-Jul
11.4346
179852400
21.54
23.115
2-Jul
11.5696
0
23.73
96843600
22.32
3-Jul
11.5108
89926200
25.23
9.5279
106066800
22.025
4-Jul
11.6176
221356800
23.40
9.8031
73785600
22.625
5-Jul
11.6270
106066800
25.96
9.8442
69174000
22.76
6-Jul
11.6806
119901600
24.66
10.0887
69174000
23.155
7-Jul
11.6116
119901600
24.33
10.1539
119901600
23.59
8-Jul
11.6626
119901600
21.90
10.1108
110678400
20.225
11.8394
119901600
23.53
10.4244
64562400
16.895
12.0088
156794400
26.83
10.4585
110678400
18.93
13.3213
64562400
26.26
10.4917
64562400
20.16
13.3692
124513200
27.56
10.5250
108372600
22.36
13.5484
166017600
26.66
10.6564
119901600
24.185
9-Jul
10Jul
11Jul
12Jul
13Jul
14Jul
13.7059
161406000
29.09
56
25Jun
26Jun
27Jun
28Jun
29Jun
30Jun
10.9779
110678400
25.06
10.7539
115290000
18.755
10.9886
76091400
19.765
11.0737
101455200
22.525
10.9836
59950800
23.925
11.2414
92232000
23.755
1-Jul
11.3345
115290000
24.085
2-Jul
11.3469
112984200
25.345
3-Jul
11.6576
115290000
26.815
4-Jul
11.8535
110678400
28.45
5-Jul
11.8471
55339200
27.95
6-Jul
12.0766
124513200
27.885
7-Jul
12.1720
101455200
27.78
8-Jul
12.4500
140653800
28.12
9-Jul
10Jul
11Jul
12Jul
13Jul
14Jul
15Jul
16Jul
17Jul
18Jul
19Jul
20Jul
21Jul
22Jul
12.3120
140653800
27.82
12.2236
133736400
23.825
12.3733
135581040
23.565
12.2594
124513200
23.33
12.3419
87620400
22.525
12.4364
101455200
23.69
12.4040
110678400
25.79
12.5665
129124800
24.125
12.6347
119901600
27.015
12.5757
221356800
22.665
12.6958
110678400
24.59
12.8917
101455200
25.925
12.9350
159100200
24.965
12.7416
168784560
21.895
15Jul
16Jul
17Jul
18Jul
19Jul
20Jul
21Jul
22Jul
23Jul
24Jul
25Jul
26Jul
27Jul
28Jul
29Jul
30Jul
31Jul
1Aug
2Aug
3Aug
4Aug
5Aug
6Aug
7Aug
8Aug
9Aug
10Aug
11Aug
13.7824
110678400
23.64
13.7010
0
23.17
13.5109
202910400
24.27
13.4372
119901600
22.00
13.5318
92232000
22.03
13.5365
92232000
22.66
13.9708
89926200
26.87
14.0362
92232000
29.19
13.8423
0
28.03
13.4666
32281200
24.13
12.5579
0
18.60
12.5743
142959600
16.28
12.7294
119901600
19.47
11.7658
119901600
19.54
11.8324
0
20.07
11.6310
0
21.34
11.5811
110678400
19.17
11.7382
101455200
24.20
11.8719
92232000
24.60
11.9685
0
25.37
12.2204
0
28.16
11.9735
101455200
25.14
11.8113
0
19.28
11.8476
83008800
17.67
11.9041
83008800
18.64
11.8903
41504400
20.24
11.9689
110678400
22.27
11.8840
83008800
21.17
57
23Jul
24Jul
25Jul
26Jul
27Jul
28Jul
29Jul
30Jul
31Jul
1Aug
2Aug
3Aug
4Aug
5Aug
6Aug
7Aug
8Aug
9Aug
10Aug
11Aug
12Aug
13Aug
14Aug
15Aug
16Aug
17Aug
18Aug
19Aug
12.6975
110678400
20.36
12.7765
166939920
20.36
12.7979
154488600
21.86
12.7701
101455200
24.195
12.7768
115290000
28.98
12.8390
147110040
23.49
12.8415
140653800
22.525
12.7289
85314600
22.195
12.9410
138348000
24.56
12.8187
103761000
25.355
12.8252
59950800
24.125
12.9013
94076640
23.765
12.7656
93615480
24.795
12.8658
178930080
24.16
12.8817
134197560
23.56
12.8619
126819000
24.265
12.9243
107911440
23.495
12.9802
140192640
22.525
12.9780
83008800
22.59
12.9643
64562400
22.625
12.9243
64562400
21.895
12.9597
138348000
22.595
12.9150
111600720
26.085
13.0193
101455200
26.945
13.1460
149877000
28.05
13.1922
101455200
29.315
13.4637
119901600
27.58
13.4065
159100200
26.75
12Aug
13Aug
14Aug
15Aug
16Aug
17Aug
18Aug
19Aug
20Aug
21Aug
22Aug
23Aug
24Aug
25Aug
26Aug
27Aug
28Aug
29Aug
30Aug
31Aug
1Sep
2Sep
3Sep
4Sep
5Sep
6Sep
7Sep
8Sep
11.5784
73785600
16.21
11.2958
69174000
14.22
11.1666
69174000
15.65
11.1053
36892800
16.84
11.1211
46116000
17.57
11.2550
83008800
18.51
11.4516
133736400
22.73
11.5209
142959600
26.07
11.4986
92232000
24.73
11.4009
124513200
17.48
11.5504
110678400
20.57
11.7124
124513200
20.74
11.6314
161406000
23.20
11.4863
119901600
23.37
11.6245
244414800
23.97
11.8033
149877000
27.03
11.7841
124513200
26.90
11.5439
96843600
24.17
11.4024
101455200
16.62
11.5076
96843600
18.97
11.5355
119901600
21.84
11.6806
221356800
21.77
11.6730
126819000
21.38
11.7890
142959600
21.87
11.9395
87620400
24.43
11.8302
32281200
23.87
11.5712
83008800
20.31
11.4032
96843600
18.28
58
20Aug
21Aug
22Aug
23Aug
24Aug
25Aug
26Aug
27Aug
28Aug
29Aug
30Aug
31Aug
1Sep
2Sep
3Sep
4Sep
5Sep
6Sep
7Sep
8Sep
9Sep
10Sep
11Sep
12Sep
13Sep
14Sep
15Sep
16Sep
13.5925
224123760
28.515
13.6039
142037280
31.785
13.6516
132814080
26.395
13.5934
82086480
24.025
13.6203
62717760
24.925
13.7552
135119880
27.86
13.6135
207522000
29.85
13.7490
147571200
25.985
13.6729
157255560
27.785
13.6555
84392280
24.565
13.5870
48998250
23.69
13.3529
110678400
25.45
13.2904
64562400
20.27
12.9574
128202480
18.505
12.8909
110678400
22.125
12.7020
107450280
18.805
12.6158
87620400
18.265
12.4676
124513200
18.265
12.4204
64562400
19.435
12.5454
46577160
20.035
12.5454
104222160
20.5
12.6107
133275240
21.665
9Sep
10Sep
11Sep
12Sep
13Sep
14Sep
15Sep
16Sep
17Sep
18Sep
19Sep
20Sep
21Sep
22Sep
23Sep
24Sep
25Sep
26Sep
27Sep
28Sep
29Sep
30Sep
12.7162
149877000
22.86
12.6060
140653800
12.5336
11.2928
80703000
17.81
11.3323
27669600
17.81
11.4058
136042200
19.91
11.3734
64562400
20.57
11.4528
110678400
20.87
11.5383
136042200
22.57
11.6888
103761000
22.97
11.6381
92232000
23.60
11.4887
110678400
20.87
11.4505
0
18.77
11.3337
0
18.87
11.2431
36892800
20.41
11.1181
110678400
18.21
11.0297
96843600
17.94
11.0863
66868200
19.13
11.0274
193687200
20.34
11.0147
83008800
20.70
10.9956
78397200
21.10
10.8296
55339200
18.37
10.6943
221356800
16.44
10.5105
96843600
16.11
10.4163
50727600
13.28
1-Oct
10.3531
69174000
15.37
22.165
2-Oct
10.0978
55339200
16.47
110678400
21.47
3-Oct
9.8791
23058000
10.37
12.3417
59950800
17.91
4-Oct
9.6618
103761000
13.24
12.1326
71940960
18.47
5-Oct
9.4584
59950800
11.61
12.1905
146187720
19.37
6-Oct
9.3874
50727600
9.78
59
17Sep
18Sep
19Sep
20Sep
21Sep
22Sep
23Sep
24Sep
25Sep
26Sep
27Sep
28Sep
29Sep
30Sep
12.2569
123936750
18.77
7-Oct
9.2681
69174000
13.21
12.1901
138348000
20.8
8-Oct
9.3892
138348000
18.04
12.0269
92232000
13.775
9.2638
129124800
18.30
11.8442
64562400
13.908
9.1717
32281200
16.11
12.3085
73785600
16.54
9.0210
69174000
14.90
12.0951
78397200
19.04
8.8763
112984200
13.91
12.0321
119901600
16.67
8.8469
80703000
12.48
12.1459
78397200
22.86
8.5022
0
14.20
11.9454
112984200
14.305
8.4891
0
9.59
11.8981
83008800
18.035
8.1597
0
10.08
11.5865
18446400
14.905
8.0509
46116000
8.48
11.2165
13834800
10.913
7.6287
55339200
11.07
10.8747
55339200
10.407
7.5701
55339200
14.04
10.5280
32281200
7.387
7.5749
0
11.35
1-Oct
10.1010
50727600
10.472
7.5289
83008800
11.81
2-Oct
9.9420
43810200
6.874
7.6461
92232000
13.91
3-Oct
9.4350
46116000
7.4205
8.1158
64562400
19.47
4-Oct
9.3139
59950800
14.93
8.2619
101455200
19.17
5-Oct
9.4547
64562400
15.675
8.2166
80703000
15.54
6-Oct
9.4148
69174000
18.43
8.1207
115290000
17.31
7-Oct
9.5697
69174000
18.1
8.1159
145265400
16.75
8-Oct
9.6705
84853440
18.23
8.2164
85314600
17.05
9-Oct
10Oct
11Oct
12Oct
13Oct
14Oct
9.6213
110678400
16.075
8.6526
48421800
20.44
9.7241
106066800
19.96
8.7411
41504400
24.00
10.1346
115290000
17.91
8.5284
27669600
15.11
9.9548
55339200
14.735
8.4185
55339200
14.28
10.0318
53033400
14.4345
8.2148
110678400
16.55
9.7997
77936040
12.841
9-Oct
10Oct
11Oct
12Oct
13Oct
14Oct
15Oct
16Oct
17Oct
18Oct
19Oct
20Oct
21Oct
22Oct
23Oct
24Oct
25Oct
26Oct
27Oct
28Oct
29Oct
30Oct
31Oct
1Nov
2Nov
3Nov
7.8641
0
12.38
60
15Oct
16Oct
17Oct
18Oct
19Oct
20Oct
21Oct
22Oct
23Oct
24Oct
25Oct
26Oct
27Oct
28Oct
29Oct
30Oct
31Oct
1Nov
2Nov
3Nov
4Nov
5Nov
6Nov
7Nov
8Nov
9Nov
10Nov
11Nov
9.5596
115290000
13.2055
9.4836
101455200
14.77
9.2866
59950800
9.8055
9.2652
66868200
13.4375
9.3032
62256600
18.43
9.5356
71479800
21.87
9.3300
106066800
18.035
9.2920
101455200
14.375
9.2815
87620400
14.008
9.3862
96843600
14.9695
9.1512
108372600
13.815
8.7952
9223200
5.4505
8.6630
32281200
7.8815
8.4012
29975400
9.939
8.2604
29975400
9.9065
8.2984
55339200
15.0355
8.1644
110678400
18.4
8.1237
62256600
9.94
8.2452
83008800
17.935
8.3992
64562400
20.325
8.3992
124513200
17.9
8.2092
73785600
5.8825
7.8686
36892800
1.456
7.5126
0
2.751
7.1207
0
0.855
6.8805
0
3.3175
6.8304
0
7.148
6.7727
27669600
15.705
4Nov
5Nov
6Nov
7Nov
8Nov
9Nov
10Nov
11Nov
12Nov
13Nov
14Nov
15Nov
16Nov
17Nov
18Nov
19Nov
20Nov
21Nov
22Nov
23Nov
24Nov
25Nov
26Nov
27Nov
28Nov
29Nov
30Nov
1Dec
7.6811
0
7.15
7.5266
0
8.19
7.3304
0
7.22
7.3548
0
14.61
7.2117
0
12.28
7.0080
0
7.55
6.9645
0
8.48
6.8489
0
12.55
6.6244
0
10.18
6.3276
0
4.36
6.0742
0
3.59
6.0374
0
6.45
6.1139
27669600
11.11
6.3985
87620400
12.31
6.4300
0
16.37
6.3833
0
12.28
6.4863
0
12.55
6.2854
0
11.45
6.1864
0
8.15
6.1280
0
8.15
5.9904
0
11.08
5.6641
0
4.25
5.3446
0
0.19
5.2333
0
8.72
5.2274
0
7.49
4.9405
0
2.95
4.8921
0
4.89
4.7741
0
3.16
61
12Nov
13Nov
14Nov
15Nov
16Nov
17Nov
18Nov
19Nov
20Nov
21Nov
22Nov
23Nov
24Nov
25Nov
26Nov
27Nov
28Nov
29Nov
30Nov
1Dec
2Dec
3Dec
4Dec
5Dec
6Dec
7Dec
8Dec
9Dec
6.8284
103761000
12.739
6.5644
46116000
3.283
6.2602
0
2.75
6.1064
18446400
6.652
6.0876
9223200
11.1735
6.1454
39198600
10.3475
6.1454
73785600
13.715
6.3065
46116000
10.775
6.3563
80703000
14.5375
6.4608
78397200
13.141
6.5646
46116000
14.905
6.3065
59950800
9.248
5.9358
0
-0.5465
5.5168
0
1.518
5.5168
13834800
5.3835
5.3146
53033400
8.077
4.9567
0
-0.209
4.6613
94537800
2.05
4.4939
0
10.773
4.4139
0
4.776
4.3147
0
4.5155
4.1419
0
3.053
4.0241
0
3.7875
3.8090
0
1.122
3.5900
0
-0.577
3.5975
0
2.6865
3.5900
0
4.8545
3.8090
0
11.145
2Dec
3Dec
4Dec
5Dec
6Dec
7Dec
8Dec
9Dec
10Dec
11Dec
12Dec
13Dec
14Dec
15Dec
16Dec
4.5823
0
3.42
4.5225
0
3.65
4.3791
0
3.58
4.2991
0
7.12
4.3508
0
4.12
4.4575
0
10.65
4.3735
0
6.29
4.3791
0
2.52
4.2610
0
8.25
4.1573
0
3.92
4.0029
0
0.66
3.8427
0
4.23
3.5288
0
-0.91
3.2101
0
-4.35
3.0188
0
-1.25
62
10Dec
11Dec
12Dec
13Dec
14Dec
3.6674
0
4.278
3.3739
0
-3.644
3.1546
0
-4.4455
2.9420
0
-2.4455
2.7139
0
-4.4735