Deep Clean: The Deep Tunnel Project and Water Quality in Milwaukee
By
Sean Sullivan
An Undergraduate Thesis
Submitted in Partial Fulfillment for the Requirements of
Bachelor of Arts
In
Geography and Earth Science
Adviser:
Dr. Matthew Zorn
Carthage College
Kenosha, WI
April, 2012
Sean Sullivan
Geography Thesis
Carthage College
Table of Contents
Intro……………………………. ……………………………………………………………...Pg.3
Literature Review……………………………………………………………………………...Pg.4
Methodology…………………………………………………………………………………...Pg.9
Data Analysis…………………………………………………………………………………Pg.14
Conclusion……………………………………………………………………………………Pg.20
Appendix: First Hypothesis Graphs…………………………………………………………..Pg.20
Works Cited…………………………………………………………………………………..Pg.23
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Problem Statement:
The purpose of this paper is to either confirm or deny criticisms of the impact of the Deep
Tunnel Project on water quality in Milwaukee.
Hypothesis:
Hypothesis 1: There will be a statistically significant change in both dissolved oxygen and fecal
coliform levels in the six sites that are surveyed.
Hypothesis 2: Post-Deep Tunnel Project spikes in fecal coliform will coincide with periods of
heavy rainfall.
Abstract:
The Milwaukee Deep Tunnel Project was implemented in 1994 to take in overflow from
the Metro-Milwaukee sewer system after the current sewer system was deemed incapable of
holding water brought in by heavy rainfall events. The intention of the Deep Tunnel was to hold
this overflow until it could be properly treated and then released back into the Milwaukee
watershed. Critics of the Deep Tunnel Project claim that this project has been ineffective as
untreated sewage is still being released into Milwaukee’s major rivers and outer harbor. Data
dating back to 1979 has been collected to confirm or deny the veracity of these criticisms.
Looking specifically at dissolved oxygen and fecal coliform this project intends to test the
change in water quality in Milwaukee before and after the implementation of the Deep Tunnel
Project. A T-test and Spearman Correlation were employed to test water quality using data from
three sites in the major rivers and three in the outer harbor.
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Literature Review
The Milwaukee Deep Tunnel Project was designed to take on any overflow from the rest
of the Metro Milwaukee sewerage system. This is intended to keep the sewage system from
overflowing into Milwaukee’s major rivers, the outer harbor, and Lake Michigan. The
Milwaukee Deep Tunnel Project is one of many attempts to keep excess sewage out of the local
water supply. When studying the effects of the Deep Tunnel Project on water quality the first
thing that must be considered is the definition of “potable water”. This study will be analyzing
the presence of dissolved oxygen and fecal coliform bacteria. As such, knowing the ideal level of
each that is allowed in “potable water” is crucial to defining the parameters of this study. It is
also important to understand the effect that dissolved oxygen and fecal coliforms have on the
environment. Dissolved oxygen is mostly a byproduct of microorganisms breaking down organic
matter in the water (Environmental Protection Agency 2012). In contrast to fecal coliforms,
dissolved oxygen is not a pollutant and is an indicator that water is safe to drink. Dissolved
oxygen only becomes a problem when its levels get too low at which point the life forms will be
negatively affected and possibly die off. High levels of dissolved oxygen tend to be a problem
for populated places because high dissolved oxygen wears down water pipes faster. Dissolved
oxygen needs to remain at a specific level in order to keep the ecosystem in balance. If untreated
sewage brings dissolved oxygen levels down too low and life forms begin to die off which leaves
room for more pollution. As such if ideal levels of dissolved oxygen are seen in the data then it
could be inferred that the Deep Tunnel Project is having a positive impact on pollution levels.
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Fecal coliforms are not necessarily a pollutant but rather they are used as an indicator of
the presence of sewage contamination as they are commonly found in human or animal feces.
Health risks associated with fecal coliforms not only make drinking water potentially hazardous,
but also pose health risks associated with swimming (or other long term exposure) and
consumption of species that live in the water. The EPA does not set its standards for coliform
presence by level of coliforms in a sample. Instead a group of samples is taken and if more than
five percent of them contain coliforms the body is simply labeled as positive for coliforms (EPA
2012). If more than five percent of a monthly amount of forty samples test positive, then the
fecal coliform levels in that body of water are considered to be too high.
The amount of dissolved oxygen in a body of water is measured in milligrams per liter.
According to the EPA’s website the ideal level of dissolved oxygen in the water varies
depending on water temperature. For example if the average temperature in Milwaukee’s outer
harbor is 10oC then the appropriate amount of dissolved oxygen is 11.27 milligrams per liter.
The ideal level of dissolved oxygen in a body of water varies inversely with the temperature of
the water. As water temperature decreases the ideal amount of dissolved oxygen increases. At
0oC the ideal level of dissolved oxygen increases to 14.6 milligrams per liter and at 45oC the
ideal level decreases to 5.95 mg/l. The EPA’s online guide to water quality monitoring and
assessment also notes that dissolved oxygen levels vary not only with water temperature, but
with the type of water body. In rivers and streams, which have stronger currents, dissolved
oxygen levels will stratify and vary horizontally. Inversely in larger bodies of water such as lakes
and harbors dissolved oxygen levels will vary vertically within the water column. (American
Public Health Association 1992)
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This study is partially inspired by recent criticisms of the Milwaukee Deep Tunnel
Project. The Deep Tunnel Project is intended to retain excess rain water during periods of heavy
rain; however a recent article published by the Milwaukee Journal Sentinel reports that between
1994 and 2011 the Deep Tunnel itself suffered an average of 2.5 overflows per year with one
overflow dumping about 170 million gallons of sewage into Milwaukee’s major rivers and outer
harbor. This criticism led to the suggestion that the Deep Tunnel is incapable of containing the
additional wastewater produced by heavy rain events. A second hypothesis aims to test the
validity of this accusation, but will require a definition to identify what constitutes a heavy
rainfall.
The National Meteorological Library and Archive (NMLA provides a glossary of terms
for the myriad of forms of precipitation. Interestingly enough the NMLA not only has a distinct
definition for light, moderate, and heavy rain but also has different definitions for rain and rain
showers. The NMLA defines rain showers as liquid precipitation from a convective cloud
whereas rain is distinguished as precipitation from layer clouds. Rain is further distinguished
from drizzle if its droplets are larger than 0.5 millimeters in diameter. Rainfall is classified as
slight, moderate, heavy, or violent. In this case “violent rain”, defined as “greater than 50
millimeters per hour”, seems closer to the “heavy rain” definition needed for this experiment.
The only foreseeable problem with this definition is that it comes from the Meteorological Office
(which is the United Kingdom’s equivalent of the National Weather Service); given that it is a
slightly different standard than that of the United States, the results of this experiment may not
properly align with the other US standards used in the experiment.
The Glossary of Meteorology provided by the American Meteorological Society (AMS)
presents a slightly different definition. The AMS also defines rain as droplets larger than 0.5
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millimeters, however they do not make any distinction between “rain” and “rain showers”. The
AMS only sets three rainfall classifications: light, moderate, and heavy. In this case “heavy” rain
is defined as either more than 0.3 inches per hour or more than 0.03 inches in six minutes. This
definition is arguably more suitable for the experiment as its definitions are set in imperial units
and will be easier to apply to any data acquired for an experiment conducted within the United
States.
Multiple studies have been conducted to assess water quality in Milwaukee. The EPA
defines water quality by a variety of parameters and they have standards of water quality for
different situations. For instance, the acceptable level of dissolved oxygen in drinking water is
lower than the acceptable level for recreational water (recreational water here meaning water
samples taken from beaches or boat launches). This article analyzes the presence of fecal
microbial communities within Milwaukee’s outer harbor. Analyzing 37 sewage samples the
researchers examined the presence of both fecal and human fecal contamination in the outer
harbor of Milwaukee (Christensen et.al 1997). Their research tested for a type of fecal bacteria
known as Lachro2 which was found to be the second most prevalent form of fecal bacteria found
in the outer harbor. The research also indicates that the presence of the bacteria increased after
heavy rain events and combined sewer overflows.
This next article outlines a similar survey conducted in Milwaukee’s outer harbor by the
EPA. The EPA tested samples of the influent and effluent of a local wastewater treatment plant
monthly from August 1994 to July 2003. Samples were tested for a variety of viruses including
reoviruses, enteroviruses, and adenoviruses. According to their results viruses were found
frequently and in high concentration in the influent but were found to be less prevalent in
effluent samples (Sedmak et.al 2003). The effluent samples were also found to contain lower
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concentrations of viruses as well. This and the previous article would seem to contradict each
other but could be explained by the fact that they were testing for two different types of
contaminants and had different methodologies.
The considerably larger urban area of Chicago is also in the process of implementing a
large scale Deep Tunnel Project of its own. Chicago’s project, which currently runs underneath
109 miles of roadway and is still growing, also includes a reservoir which is intended to
sequester sewage overflows and hold them until the water is treated and suitable to be released
back into the water supply. Singapore has also been hard at work implementing a state of the art
version of the Deep Tunnel Project. Given the fact that Singapore is an entirely urbanized island
keeping their water supply clean is of the highest priority. As such the Singapore Deep Tunnel
Project utilizes new technologies to separate the sewage from the water as it is drawn into the
tunnel.
Another large urban area in the Great Lakes region that has been grappling with the
issues of sewage management is Toronto. The city of Toronto has a combined sewage overflow
(CSO) system, which is an older water treatment mechanism that simply releases untreated
sewage that the Toronto sewer system can no longer hold. This untreated sewage is mixed with
urban storm water and then released back into the municipal water supply. In the interest of
improving their ability to treat Toronto’s excess sewage the National Water Research Institute
took a mathematical approach to determining the best approach to cleaning the CSO effluent.
Using a method called computational fluid dynamics these researchers were able to construct
scale models which were used to determine that the CSO was an environmentally hazardous
method of sewage treatment that could only be improved by improving the effluent channels and
decreasing the amount of overall effluent (Cheng et. al. 2006).
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Another study examined the effectiveness of home sewage disposal systems in northeast
Ohio and the Cleveland area. This study, conducted by Mark A. Tumeo and Juliet Newland, does
not analyze the effectiveness of the entire Cleveland sewer system. However the article does
analyze the effectiveness of individual septic systems in the surrounding area. The effectiveness
of these systems was judged by whether or not there was observable effluent surfacing from the
treatment systems (Tumeo, Newland 2009). The survey found that 12.7 percent of onsite water
treatment systems were failing and causing sewage to rise up from underground rather than
dispersing the sewage safely into the soil underground. This article also highlighted the
importance of soil in removing waste from water. The article mentioned that part of the reason
for the failure of so many treatment systems was because most of the soils in northeastern Ohio
were not ideal for absorbing effluent from treatment systems.
Another article in the January 2012 edition of Civil Engineering discusses the city of
New York’s attempts to prevent combined sewage overflows. The local Department of
Environmental Protection worked with the state Department of Environmental Conservation to
implement a “greener” infrastructure which included having the sewage “enter the ground rather
than make its way into the city’s combined sewer system” (Landers 2012). The article notes that
pollutants enter New York’s water supply due to the face that a large majority of the surfaces in
the city are impervious to rainfall the causing a great deal of runoff. Part of this new green
infrastructure involves containing the first inch of that runoff before it reaches New York’s water
supply. The amount of runoff that is contained is expected to be expanded over the next two
decades. Although these changes to New York’s sewer system are expected to cost over two
billion dollars, experts project that these changes will also lower temperatures around the city
and reduce the urban heat island.
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Heavy rain fall tends to bring on more water than a sewage system can handle which
leads to overflows. To prevent this, retention ponds are created. These retention ponds are
intended to divert potential floodwaters into small enclosures where the water can be held until it
evaporates. Recently the University of Auckland conducted an experiment to determine whether
or not building artificial islands in these retention ponds to make them more efficient. The
hypothesis behind this experiment was that the islands would divert inlet flow into the pond and
would have the added benefit of filtering excess sediment out of the floodwaters. However the
results of the experiment proved the hypothesis to be incorrect as the islands did little to improve
the ponds performance and actually ended up short circuiting some of the ponds. The MMSD has
implemented many of these retention ponds as well as experimenting with “Green Streets” which
utilize plants to absorb and filter runoff from the roads and divert it into the ground.
Similar to retention ponds are detention basins. These basins are trenches built on the
shores of rivers and lakes which are meant to either temporarily or permanently take on excess
water to prevent flooding and erosion. These basins function by detaining water for a period of
time which, although short, should provide enough time for any sediment or pollutants in the
water to settle. Ultimately the EPA points out that detention basins are generally not effective for
mitigating pollution unless they have a permanent pool which detains some of the water at all
times. The EPA also notes that detention basins can lower property value and become a nuisance
as they are often a breeding ground for mosquitoes. In general detention basins may reduce some
of the fecal coliform presence in a body of water however it will not be as effective as larger
pollutant removal methods such as the sewer system. Recently a study was conducted
(Takamatsu et. all.) on the effectiveness of detention basins on reducing pollutants in roadrunoff. Water that runs off of roads due to heavy rain and ice melting will often contain
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chemicals and other pollutants. After monitoring six runoff events the basin was found to have
mixed results with total dissolved solids only being reduced by 18% but lead and zinc being
reduced by at least 50%.
Methodology
This study is intended to verify two hypotheses. The first hypothesis is that there will be a
statistically significant difference between the mean amount of dissolved oxygen and fecal coliform
before and after the implementation of the deep tunnel project. The definition of “statistically significant”
will be set in later paragraphs of this methodology. The second hypothesis is that spikes in fecal coliform
will coincide with heavy rainfall events. This hypothesis is only intended to apply after the
implementation of the Deep Tunnel Project.
For the first hypothesis the independent variable is the Deep Tunnel Project and the dependent
variables will be dissolved oxygen and fecal coliforms. The first hypothesis suggests that there will be a
statistically significant change in the mean amount of dissolved oxygen and fecal coliform after the Deep
Tunnel Project is implemented. In this case the phrase “statistically significant” means that the result of
the T-test will be greater than 0.05. If the result is less than 0.05, then the hypothesis will be rejected. The
only material necessary for verifying this hypothesis will be data consisting of dissolved oxygen and fecal
coliform content at the specified testing sites. These testing sites are run by the University of Wisconsin in
Milwaukee and all of the necessary data has been compiled by them. Three testing sites have been
selected in the major rivers, one in the Kinnickinnic River, one in the Menominee River, and one in the
Milwaukee River. Three additional sites have been selected in Milwaukee’s outer harbor, which are
located on the north, center, and south sides of the harbor. Significant aspects of the data are: sample
depth (which is measured in meters and subdivided into S,M, and B levels); dissolved oxygen (which is
measured in milligrams per liter); and fecal coliform (which is measured in Most Probable Number
(MPN) per 100 milliliters).
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Figure 1 Map displaying the six cites used for this study.
Verifying the first hypothesis is simply a matter of conducting a t-test. By conducting a twosample difference of means test, I will be able to determine if the implementation of the Deep Tunnel
Project was successful from the stand point of keeping dissolved oxygen at an acceptable level and
lowering fecal coliform presence. In order to complete this test, I will need to determine the mean of
dissolved oxygen content before and after the implementation of the Deep Tunnel Project. Once the
standard error of the difference of means has been calculated, the result of the equation will confirm or
deny my hypothesis (McGraw et. all 2000). Results that are greater than 0.05 will confirm the hypothesis,
while results that are less than 0.05 show that the hypothesis is incorrect. The equation for this test is =
𝑋̅1 − 𝑋̅2 ÷ 𝜎𝑋̅1 − 𝑋̅2 . In this equation X1 represents the mean prior to the construction of the Deep
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Tunnel Project (DTP) and X2 represents the post-DTP mean. The equation will then be run again with
fecal coliform as the variable in order to verify the hypothesis for fecal coliform as well.
The second hypothesis aims to determine if heavy rainfall events coincide with spikes in fecal
coliform now that the Deep Tunnel Project has been implemented. In the case of this hypothesis, the
dependent variable is heavy rainfall and the independent variables are measures of dissolved oxygen and
fecal coliform. The data necessary for this experiment will come from two sources. The University of
Wisconsin in Milwaukee will be providing the dissolved oxygen and fecal coliform data. Data on heavy
rainfall events will be provided by a chart obtained from the National Oceanic and Atmospheric
Association (NOAA). The same six testing sites will be used for obtaining dissolved oxygen and fecal
coliform data.
This hypothesis will be tested by examining the spikes in fecal coliform that occur post-DTP
construction. The dates at which fecal coliform was the highest will be cross checked with data from the
NOAA to determine if the date of the fecal coliform spike occurred within two weeks after a month in
which the rainfall total is higher than average. The date can occur up to two weeks after these months of
heavy rainfall, because a rain can build up within the sewer system and would need to be purged after two
weeks of consistent rainfall. If the fecal coliform spikes do indeed coincide with months of higher than
average rainfall then it could be theorized that the heavy rainfall was the cause of the spike. The results of
this test will be recorded in an Excel chart.
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Figure 2A table summarizing the total monthly precipitation in Milwaukee for every month from 1983 to 2012. Image
provided by the NOAA
Figure 3A chart indicating the monthly average of precipiation. Data provided by the NOAA.
The data will be analyzed in Microsoft Excel for the sake of making charts and graphs that are
more legible. The data is subdivided into S, M, and B sample depths. S level samples are taken near the
surface at a depth of one meter or less; M level samples are taken at a depth between five and six meters;
and B level samples are taken near the bottom of the water body in question which is a depth greater than
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six meters. The data will be separated into six sheets based on sample depth and the material being tested
(DO or FC). All tests in this study will be run once at each sample depth to ensure that the hypotheses are
thoroughly verified.
Data Analysis
Within the data there were a great deal of records with null values which means that there
was no data recorded for that sample at that date. No reason was given for why these values were
missing and there is no estimate given for what these values may be. The null values are
represented in the spreadsheets as -99.9, -999, or -9999999 which made graphing the data a
difficult task. This problem was fixed by replacing the null values with zeroes. The null values
were present in every data set; however the majority of the null values seemed to be concentrated
in the B and M level fecal coliform data. Because there was such a high concentration of null
values on these sheets the graphs that they produced were unreliable and resembled the graph in
figure 1.1. Because there were plenty of other sheets with available data the B and M level fecal
coliform sheets were omitted from the final analysis. Each sheet had over one thousand records
of data which would have rendered the graphs illegible if the data were not compressed. The data
for each sheet was subtotaled and now displays the annual average of dissolved oxygen or fecal
coliform for the time period being surveyed.
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Figure 4.1 All B and M level FC graphs looked like this due to a large amount of null values and gaps in the data.
The first site surveyed was OH-5, which is located at the northern end of Milwaukee’s
outer harbor. Fecal coliform at this site was relatively low with the exception of a spike in 1986,
which brought the FC levels in OH-3 to 2532 MPN/100ml. The mean of all FC averages preDTP was much lower at 325.8 MPN/100ml while the average post-DTP was 8.4 MPN/100ml.
The T-test result for FC in OH-3 was 0.04, which indicates that the hypothesis was incorrect.
Dissolved oxygen in OH-3 has fluctuated a great deal since 1979. It reached a low point of 7.7
mg/L in 1997, after which, it steadily rose back up above 10 mg/L. At the B level the pre-DTP
mean was 10.3 mg/L and the post-DTP mean was 10.2 mg/L. The T-test result for the B level
was 0.35, which indicates that the hypothesis was correct. The pre-DTP mean at the M level was
similar to that of the B level, however the post-DTP mean was lower at 9.9 mg/L. The mean for
the S level was almost exactly the same as well as closely matching the pre and post-DTP means
for the M level. The T-test result for the M level was 0.06 and the S level result was 0.08
indicating that in both instances the hypothesis was incorrect.
The next site surveyed was OH-3 located in the center of the outer harbor at a point
where Milwaukee’s three major rivers converge and empty out into the harbor. Fecal Coliform at
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this site has spiked several times in the 31 year period that was surveyed. Although FC has gone
as low as 15 MPN/100ml in 2006, its largest spike occurred in 2000 when FC sky-rocketed to
3531.07 MPM/100ml from an average of 1270.07 MPN/100ml the previous year. Although the
mean of fecal coliform dropped from 1078.49 to 921.27 MPN/100ml after the Deep Tunnel
Project was implemented, the result of the T-test was 0.4 indicating that the hypothesis was
incorrect and the difference of means was not statistically significant. In terms of dissolved
oxygen, OH-3 was one of the locations at which the level slowly rose. At the B level, the mean
amount of DO rose from 9.2 to 9.8 mg/l, which yielded a T-test result of 0.00005, indicating that
the hypothesis was correct. At the M level the mean DO level rose from 9.1 to 9.57 mg/l. This
resulted in the T-test giving a 0.002, which proved the hypothesis to be incorrect (although it was
by a smaller margin). Dissolved Oxygen at the S level of OH-3 rose the most (almost reaching
11 mg/l), while the mean shifted from 8.8 to 9.4 mg/l. The T-test result for the S level was
0.0002, which shows that the hypothesis was incorrect for DO at all three depth levels in OH-3.
OH-10 was the final outer harbor site selected for analysis. This site was located at the
southern end of the harbor, which was also on the edge of a marina. Results on the south end of
the harbor were similar to the north end. At the B level, the mean for dissolved oxygen shifted
down from 9.5 to 9.2 and yielded a T-test result of 0.19. At the M level the mean DO shift was
even more miniscule, as the mean lowered from 9.9 to 9.7 mg/l and produced a T-test result of
0.15. Finally, at the S level, the DO mean shifted from 10.04 to 9.7 mg/l with a T-test result of
0.14. Needless to say, the hypothesis was correct for dissolved oxygen at every level of OH-10.
Fecal coliform in OH-10 decreased significantly after the Deep Tunnel Project with the mean
dropping from 513.05 to 101.95 MPN/100ml. The T-test result was 0.002, proving that the
hypothesis was incorrect.
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RI-14 was located at the mouth of the Kinnickinnic River and proved to be the second
strongest refutation of the first hypothesis. The data for the Kinnickinnic River was also strange
in that it was the only site which had a great deal of data missing. Rather than starting at 1979 the
RI-14 data started at 1980. Data at the M level started even later at 1981. Furthermore all data
between 1993 and 2009 was missing. At all levels, DO increased from 4mg/l to 5 mg/l over the
thirty years covered. Due to the large amount of data missing from the M level no T-test could be
conducted, however the B and S level T-tests results were 0.0000001 and 0.0000000000001
respectively. Fecal coliform in the Kinnickinnic River was surprisingly high. This site had a preDTP mean of 23754.65 MPN/100ml which decreased to 12996.7 MPN/100ml after the Deep
Tunnel Project was initiated. The T-test result for the Kinnickinnic River was 0.03 which
indicates that the hypothesis was incorrect at this site.
RI-6 was the Menomonee River site (located just within the boundary of the MMSD
service area and north of the other two major rivers). The B level mean of dissolved oxygen
started at 8.4 mg/l and rose only .3 mg/l after the Deep Tunnel Project began. The B level T-test
result was 0.09 indicating that the hypothesis was correct at this level. The M level at the
Menomonee River was similar to the Kinnickinnic River in that both sites had a great deal of
missing data. Records at this level started in 1975 and then immediately skipped to 1981. All
available data at this level ends at 1999. The mean at this level barely changed at all (increasing
from 8.853 to 8.859 mg/l and yielding a T-test result of 0.49) indicating another correct
hypothesis. At the S, level there was still a data gap between 1975 and 1981; however the
available data now ended in 2010 instead of 1999. The mean amount of DO at this level started
at 8.6 mg/l and rose 0.3 mg/l after the implementation of the Deep Tunnel Project. The
hypothesis was confirmed at this level by a T-test result of 0.12. Fecal coliform in RI-6
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decreased from 8229.76 to 5225.76 MPN/100ml after the start of the Deep Tunnel Project.
Running the T-test on fecal coliform at the RI-6 site yielded a result of 0.15 confirming that the
hypothesis was correct.
The final site at which the first hypothesis was tested was the RI-11 site on the
Milwaukee River. Dissolved oxygen increased from 4.4 to 7.1 mg/l at the B level; from 4.5 to
6.9 mg/l at the M level; and from 4.3 to 7.2 mg/l at the S level. The average amount of fecal
coliform decreased from 34785.8 to 6146.5 MPN/100ml. T-test results for this site proved to be
the most thorough rejections of the first hypothesis in the entire study. The three DO T-tests gave
results with as many as 24 decimal places and as few as 19. This is in addition to the 0.001 result
from the FC test which indicated that the first hypothesis was incorrect every single time it was
tested in RI-11. A chart of all T-test results is shown in the figure below.
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Figure 5 Map detailing the results of hypothesis 1. Green dots indicate that the null hypothesis was confirmed while red xes
indicate that the null hypothesis was rejected.
Table 1 The results of all T-Tests conducted in this study are shown here.
Testing the second hypothesis required less testing as there were never more than four
spikes that occurred in a single site after the Deep Tunnel Project began. In the outer harbor there
were a total of seven spikes: two in OH-5; four in OH-3; and one in OH-10. The two OH-5
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spikes did little to raise the average amount of fecal coliform which barely exceeded the postDTP mean. The four OH-3 spikes were considerably larger and raised the average by almost
2000 MPN/100ml. The sole spike that took place in OH-10 occurred on October 24th, 2001. On
that date fecal coliform at the south end of the outer harbor rose to 4600 MPN/100ml. During
October of 2001, the total amount of rainfall was 4.29, inches which is 1.64 inches above the
average monthly rainfall as indicated by the rainfall chart below. The spreadsheet that
accompanies the rainfall chart will confirm that all fecal coliform spikes that occurred in the
outer harbor after the Deep Tunnel Project began, coincide with months in which rainfall was
higher than average.
Data for the major rivers reveals that a total of eight spikes occurred after the
implementation of the Deep Tunnel Project. Three spikes occurred on the Kinnickinnic River
(RI-14); three occurred on the Menomonee River (RI-6); and one occurred on the Milwaukee
River (RI-11). The three spikes that occurred on the Kinnickinnic River brought their respective
annual averages up to 30,000 MPN/100ml in 1999; over 60,000 MPN/100ml in 2001; and about
15,000 MPN/100ml in 2010. The chart below indicates that all three of these spikes occurred
within two weeks of a month of high rainfall. The first two spikes that occurred on the
Menomonee River happened in June of 1996 and May of 2000. These two spikes verified the
hypothesis, however the third spike (occurring in July of 2002) happened during a dryer than
average month. The single spike that occurred on the Milwaukee River took place on the same
date. These two spikes are the only two examples that do not verify the second hypothesis. This
could possibly be explained by an extended period of rain rather than a short period of heavy rain
(however that is impossible to deduce with the data that is available).
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Figure 6 Map indicating the results of hypothesis 2. The null hypothesis was confirmed in 4 of the 6 sites.
Table 2 All observations on the second hypothesis are shown here
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Conclusion
The T-test was run 24 times and proved the first hypothesis to be correct twelve times.
The first hypothesis was also proven to be incorrect eleven times which makes it difficult to say
whether or not the first hypothesis was correct overall. The hypothesis was proven to be correct
on the north and south ends of the outer harbor, but not in the center. The first hypothesis was
also proven correct in the Menomonee River, but not the Kinnickinnic River or the Milwaukee
River. The second hypothesis was shown to be correct (with one exception which could be
explained by limitations in available data).
Appendix: First Hypothesis Graphs
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Sean Sullivan
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Geography Thesis
Carthage College
Sean Sullivan
Geography Thesis
Carthage College
Works Cited
1. Sedmak, Gerald, David Bina, and Jeffrey MacDonald. "Assessment Of An Enterovirus
Sewage Surveillance System By Comparison Of Clinical Isolates With Sewage Isolates
From Milwaukee, Wisconsin, Collected August 1994 To December 2002." Applied &
Environmental Microbiology 69.12 (2003): 7181-7187. Academic Search Premier. Web.
10 Dec. 2012.
2. Manache, Gemma, Charles S. Melching, and Richard Lanyon. "Calibration Of A
Continuous Simulation Fecal Coliform Model Based On Historical Data Analysis."
Journal Of Environmental Engineering 133.7 (2007): 681-691. Academic Search
Premier. Web. 10 Dec. 2012.
3. Trimbath, Karen. "Chicago's Deep Tunnel Project Reaches Milestone." Civil Engineering
(08857024) 76.5 (2006): 36-37. Academic Search Premier. Web. 10 Dec. 2012.\
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Sean Sullivan
Geography Thesis
Carthage College
4. Wung Hee, Moh. "Deep Tunnel Sewerage System. (Cover Story)." Innovation 8.1
(2008): 22-24. Academic Search Premier. Web. 10 Dec. 2012.
5. Takamatsu, Masatsugu, Michael Barrett, and Randall J. Charbeneau. "Hydraulic Model
For Sedimentation In Storm-Water Detention Basins." Journal Of Environmental
Engineering 136.5 (2010): 527-534. Academic Search Premier. Web. 10 Dec. 2012.
6. Sandra L. McLellan, et al. "Lachnospiraceae And Bacteroidales Alternative Fecal
Indicators Reveal Chronic Human Sewage Contamination In An Urban Harbor." Applied
& Environmental Microbiology 77.19 (2011): 6972-6981. Academic Search Premier.
Web. 10 Dec. 2012.
7. Lon Couillard, et al. "Nine-Year Study Of The Occurrence Of Culturable Viruses In
Source Water For Two Drinking Water Treatment Plants And The Influent And Effluent
Of A Wastewater Treatment Plant In Milwaukee.." Applied & Environmental
Microbiology 71.2 (2005): 1042-1050. Academic Search Premier. Web. 10 Dec. 2012.
8. Bonjoch, X., C. García-Aljaro, and A. R. Blanch. "Persistence And Diversity Of Faecal
Coliform And Enterococci Populations In Faecally Polluted Waters." Journal Of Applied
Microbiology 111.1 (2011): 209-215. Academic Search Premier. Web. 10 Dec. 2012.
9. Khan, S., B. W. Melville, and A. Y. Shamseldin. "Retrofitting A Stormwater Retention
Pond Using A Deflector Island." Water Science & Technology 63.12 (2011): 2867-2872.
Academic Search Premier. Web. 10 Dec. 2012.
10. Christensen, Erik R., and Wasunthara Phoomiphakdeephan. "Water Quality In
Milwaukee, Wisconsin, Versus Intake Crib Location." Journal Of Environmental
Engineering 123.5 (1997): 492. Academic Search Premier. Web. 10 Dec. 2012.
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Sean Sullivan
Geography Thesis
Carthage College
11. "5.2 Dissolved Oxygen and Biochemical Oxygen Demand." Home. N.p., n.d. Web. 28
Nov. 2012. <http://water.epa.gov/type/rsl/monitoring/vms52.cfm>.
12. "5.11 Fecal Bacteria." Home. N.p., n.d. Web. 28 Nov. 2012.
<http://water.epa.gov/type/rsl/monitoring/vms511.cfm>.
13. McGraw, J.R., J.C., & C.R. Monroe An Introduction to Statistical Problem Solving in
Geography 2nd ed., McGraw-Hill, 2000
14. Bommanna G. Krishnappan, et al. "Case Study: Refinement Of Hydraulic Operation Of A
Complex CSO Storage/Treatment Facility By Numerical And Physical Modeling." Journal Of
Hydraulic Engineering 132.2 (2006): 131-139. Academic Search Premier. Web. 6 Apr. 2013.
15. Tumeo, Mark A., and Juliet Newland. 2009. "Survey of the Home Sewage Disposal Systems in
Northeast Ohio. (Cover story)." Journal Of Environmental Health 72, no. 2: 17-22. Academic
Search Premier, EBSCOhost (accessed May 4, 2013).
16. Landers, Jay. 2012. "New York City Looks To 'Green' Infrastructure To Reduce Combined Sewer
Overflows." Civil Engineering (08857024) 82, no. 1: 26. MasterFILE Premier, EBSCOhost
(accessed May 5, 2013).
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