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This is to certify that the
thesis entitled

Investigation of Bacterial Fecal Indicators and Coliphage Virus
in Sediment and Surface Water of Parks and Beaches along
the Grand River (MI) and Lake Michigan (MI)

presented by

Shikha Singh

has been accepted towards fulfillment
of the requirements for the

MS degree in Fisheries and Wildlife

 

 

\ICC it/H _,>‘ \6 g5;

Major Professor’s Signature

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Date

MSU is an affinnafive-action, equal-opportunity employer

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PLACE IN RETURN BOX to remove this checkout from your record.
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DAIEDUE

DAIEDUE

DAIEDUE

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6/07 p:/C|RC/DateDue.indd-p.1

 

Investigation of Bacterial Fecal Indicators and Coliphage Virus in Sediment and Surface
Water of Parks and Beaches along the Grand River (MI) and Lake Michigan (MI)

BY

Shikha Singh

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
MASTER OF SCIENCE
Department of Fisheries and Wildlife

2007

ABSTRACT

Investigation of Bacterial fecal indicators and Coliphage Virus in Sediment and Surface
Water of Parks and Beaches along the Grand River (MI) and Lake Michigan (MI)

By
Shikha Singh

According to a report by the Natural Resources Defence Council (2006) the
numbers of beach closing and advisory days have increased from 2003 where advisories
increased in the state of Michigan by 174 % due to elevated bacterial levels and are
associated with public health risks and economic vitality of the community. The
objective of this study was to examine fecal indicator species spatially and temporally
and to determine if a relationship exists between sediment and surface water quality.
Eight sites in the state of Michigan along the Grand River and Lake Michigan were
studied year round. Parks had significantly higher concentrations of fecal indicators
compared to the beaches (p<0.05) indicating a large dilution effect before reaching the
lake. Results were assessed for correlation between sediments and surface water for
fecal coliforms, Escherichia coli, Enterococci, Clostridium perfringens and coliphage.
The R2 values for the aforementioned ranged between 0.444 and 0.128. While sediment
quality was not directly related to the water column above it, it is a reservoir of fecal
contaminants downstream and was 2-3 log10 higher. In general, most indicators had
highest concentrations in surface water during the winter and spring seasons. For
rainfall, fecal coliform and E. coli had a positive relationship with surface water and
negative relationship in sediment indicating rainfall contributes to releases from

sediment.

ACKNOWLEDGMENTS

This is more of a thank you then an acknowledgement, so here goes. . . .First and foremost, I
would like to acknowledge my committee members, Dr. Jean Tsao and Dr. Mantha Phanikumar
for all their patience and support during this research and for their constant enthusiasm and
positivity. Thank you to NOAA for funding such a great project and to all the people in Ottawa
and Kent County for your support. Dr. Joan Rose, thank you for allowing me the opportunity of a
lifetime as that is what I feel my experience here in the department has been. I have learned so
much professionally and personally. It has been a long journey, between all the sampling,
partying, conferences, but somehow a thesis was born. Thank you so much for a wonderful start
to my career, and taking a chance on a random Canadian who “just walked into your office one
day”. Big shout out to everyone in the Jones-Bence lab, Taylor-Hayes lab, Scribner lab, Katerina,
Rina, the basement grad cube gang and everyone in between...its been fun, and I have the
pictures to prove it eh! ! I! Thanks A. J-M for the mid-day tea breaks and intemet searches, my
badminton crew (AA, SN, RV, W-NC, FK, SS, SM, JC, JH), Dr. Jones, thanks for everything,
thanks for keeping the Canadian spirit alive (Go Leafs Go); Dr. Dann and Dr. Hayes for your
time and support. I can’t forget the Rose Lab: Ai, Arun, Becca (thanks for the sampling
company, the topics that were discussed on route were so random ehl), Erin, Lauren, Lei Lei,
Lekha, Mark, Rachel, Sangeetha, Shiba, Stephanie, Tracie, Theng Theng and Yoshi. I can’t say
enough so I won’t even try. The girls. . .Gel, Theng Theng and Parama. . .you guys are family:
emotionally, academically, midnight tea breaks, 3am chats, laughter, tears, retail therapy, we did
it all and we did it in style eh! Thanks to Mom, Dad and Bidhi. . .for believing in the power of
education, honesty and humility, and encouraging me to succeed in life. Thanks is not enough,
your support means everything. Fudge, you are everything, and I owe you the most, I learned

patience, and unconditional love. Your spirit remains always, and you will never be forgotten.

iii

TABLE OF CONTENTS

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

LIST OF TABLES VI
LIST OF FIGURES VIII
HISTORICAL NOTES ON WATER CONTAMINATION 1
1.0 INTRODUCTION 2
1.1 BACTERIAL AND COLIPHAGE F ECAL INDICATORS 4
1.2 EXISTING WATER QUALITY ACTS 8
1.3 FECAL CONTAMINATION FROM POINT AND NON-POINT SOURCES 11
1.3.1 SOURCES OF POLLUTION .................................................................................................................. l3
Septic Tank Systems ............................................................................................................................. l 3
Combined Sewer Overflows (CSOs) and storm sewers ....................................................................... l4
Wastewater treatment plants ............................................................................................................... I 5
Animal Feeding Operations (AF 0) ..................................................................................................... l7
Grazing Animals .................................................................................................................................. l 8

Wild Animals ....................................................................................................................................... l9
Seaweed and Algae .............................................................................................................................. 20

I .3.2 SURVIVAL AND TRANSPORT OF FECAL MICRO-ORGANISMS ............................................................ 21
Rainfall ................................................................................................................................................ 22
Temperature ........................................................................................................................................ 25
Salinity ................................................................................................................................................. 27

1.4 PUBLIC HEALTH CONCERNS 28
1.5. WATER QUALITY IN GREAT LAKES BASIN AND MICHIGAN 30
1.6 SEDIMENTS AS SOURCES OF F ECAL INDICATORS & PATHOGENS 36
I. 6. I SEDIMENTS ASA RESERVOIR FOR FECAL INDICATOR BACTERIA ............................................................. 38
1.6.2 RE-SUSPENSION ................................................................................................................................. 40

l. 6.3 PROCESSING BACTERIA AND COLIPHAGE FROM SEDIMENT& SAND ...................................................... 42
1.7 OBJECTIVES OF THIS STUDY 44
1.8 REFERENCE PAGE 45
2.0 MATERIALS & METHODS 55
2.1 SITE DESCRIPTION 55
2.2 SAMPLE COLLECTION 57
2.2.1 SURFACE WATER .......................................................................................................................... 57
2.2.2 SEDIMENT .................................................................................................................................... 57
2.3 ENUMERATION OF WATER SAMPLES 58
2.4 ENUMERATION OF SEDIMENT SAMPLES 61
2.5 STATISTICAL ANALYSIS 62
3.0 RESULTS _ 66
3.1 SPATIAL ANALYSIS OF SURFACE WATER AND SEDIMENT 77

iv

 

 

 

 

 

 

 

 

 

 

 

 

 

3.1. I Surface water .............................................................................................................................. 77

3.1.2 Sediment ..................................................................................................................................... 80

3.2 TEMPORAL ANALYSIS OF SURFACE WATER AND SEDIMENT 88
3.2.1 SURFACE WATER .............................................................................................................................. 92
3.2.2 SEDIMENT ........................................................................................................................................ 96
3.3 RELATIONSHIP BETWEEN SURFACE WATER AND SEDIMENT 97
3-4 COMBINED SEWER OVERF LOW SAMPLES 103
3-5 SITE RANKINGS 106
3-6 INDICTOR VIOLATIONS 107
4.0 DISCUSSION 109
4.1 REFERENCES .................................................................................................... 129
5.0 SUMMARY 134
5.] CONCLUSIONS 136
5.2 MANAGEMENT RECOMMENDATIONS 137
APPENDIX A IMPORTANT JOURNAL ARTICLE FINDINGS 138
APPENDIX B LAND USE MAPS 139
APPENDIX C SITE PHOTOGRAPHS 144
APPENDIX D RAW DATA USED FOR ANALYSIS 149
APPENDIX E SEASONAL CHANGES OF PRECIPITATION COMPARED TO 1971 - 2000 ....... 155
CURRICULUM VITAE .............................................................................................. 160

LIST OF TABLES

Table 1-1. Classification of bacteria used in this study ......................................... 6
Table 1-2. Fresh water quality guidelines and standards (CFU/ 100) for areas of
recreational use ........................................................................ 10
Table 1-3. Summary of Great Lake published water and sediment literature. . . . . . .........31
Table 2-1. Location of study sites with corresponding GIS information ................... 55
Table 2-2. Types of analysis performed on both surface water and sediment .............. 58
Table 3-1. Site classifications and number of total samples taken at each site throughout
the course of the study ................................................................ 66
Table 3-2. Geometric means of fecal indicators in surface water reported as CFU or
PF U / 100 mL ........................................................................... 68
Table 3-3. Geometric means of fecal indicators in sediment reported as CF U or PFU/
100 g dw ................................................................................. 69
Table 3-4. Sediment classification and particle composition taken November/December
2005 ...................................................................................... 71
Table 3-5. Sediment classification and particle composition from samples taken
September 14th 2006 .................................................................... 71
Table 3-6. Pearson correlation coefficients for fecal indicator bacteria and coliphage in
surface water and sediment at river sites against water parameters ................ 74
Table 3-7. R2 values for Indicator species predicted by precipitation, pH, water
temperature, turbidity and flow ...................................................... 76
Table 3-8. Geometric mean of the physical water parameters per site over the course of
the four seasons .......................................................................... 89
Table 3-9. Geometric average of seasonal flow ................................................ 90
Table 3-10. Average monthly rainfall during the months of the study ..................... 90

Table 3-11. Mean concentration of fecal indicator species over time in water samples

and sediment samples ............................................................... 91

vi

Table 3-12. Regression values of water and sediment concentrations for each
indicator species broken down by seasons ..................................... 102

Table 3-13. Regression of each indicator species in relation to other fecal
indicator species surface water (values represent R2) .......................... 102

Table 3-14. Regression of each indicator species in relation to other fecal
indicator species in sediment (values represent R2). . . . . 102

Table 3-15. Concentration of fecal indicator bacteria and virus in surface water as CFU or
PFU/ 100 mL after February 16th cso ........................................... 104

Table 3-16.Concentration of fecal indicator bacteria and virus in sediment as CFU or
PFU/ 100 g dw February 16th CSOIO4

Table 3-17. Concentrations of fecal indicator bacteria and virus in surface water as CFU
or PFU /100 mL from July 18th cso .............................................. 105

Table 3-18. Concentration of fecal indicator bacteria and virus in sediment as CF U or
PFU/ 100 g dw from July 18th cso .............................................. 105

Table 3-19. Concentrations of fecal indicator bacteria and virus at Site B. Goodrich
overflow point in surface water. .‘ ................................................. 106

Table 3-20. Relative ranking of sites for highest to lowest amount of contamination in
surface water ......................................................................... 107

Table 3-21. Relative ranking of sites for highest to lowest amount of contamination in
sediment ............................................................................. 107

Table 3—22. Number of indicator violations in the upper, middle and lower reaches of the
Grand River and Lake Michigan study sites ..................................... 108

Table 4-1. A single day of C80 discharge and amount of sewage entering the Grand
River .............................................................................................................. 112

Table 4-2. State water quality exceedences at beaches along Lake Michigan at sites also
studied in this project ................................................................ 128

vii

LIST OF FIGURES

Figure l-l. Sources and pathways for fecal microbial transport .............................. 12
Figure 2-1. Map of study sites along the Grand River from Grand Rapids to Lake
Michigan ............................................................................... 56
Figure 3-1. Concentrations of fecal coliforms along the Grand River in a)surface water
and b) sediment ....................................................................... 83
Figure 3-2. Concentrations of E. coli along the Grand River in a) surface water and b)
Sediment .............................................................................. 84
Figure 3-3. Concentrations of Enterococci along the Grand River in a) surface water and
b) sediment ............................................................................ 85
Figure 3-4. Concentrations of C. perfringens along the Grand River in a) surface water
and b) sediment ....................................................................... 86
Figure 3-5. Concentrations of coliphage along the Grand River in a) surface water and b)
Sediment .............................................................................. 87
Figure 3-6. Seasonal trends of fecal coliforms in surface water ............................. 92
Figure 3-7. Seasonal trends of E. coli in surface water ....................................... 93
Figure 3-8. Seasonal trends of Enterococci in surface water .................................. 94
Figure 3-9. Seasonal trends of C. perfringens in surface water ................................ 95
Figure 3-10.Seasonal trends of coliphage in surface water .................................... 96

Figure 3-11.Seasonal trends in sediments for fecal coliforms, E. coli, Enterococci,

C. perfiingens and coliphage ........................................................ 97

Figure 3-12. Correlation graphs of indictor species in surface water and sediment for a)

fecal coliforms, b) E. coli, c) Enterococci, d) Clostridium and e)
coliphage .............................................................................. 99

viii

Historical notes on water contamination

Fecal contamination of water has been a source of concern for hundreds of year
and has led to spread of waterborne diseases, currently resulting in up to 5 million deaths
world wide (WHO, 1992). This includes diseases such as cholera and typhoid which
have long been associated with water contaminated with sewage and feces contamination.
The answers to the questions of how and where to dispose of fecal matter, has evolved
over time. Beginning in ancient Greek and Roman times chamber pots were used
(Mattelaer, 1999) to collect bodily refuse and were subsequently tossed out windows onto
busy streets (with a verbal warning. . .sometimes) along with development of sewers and
drainage where was entered into water sources such as streams and rivers. It was not
until the 18003 that the relationship between diseases (such as cholera) and contamination

of water was brought to light by Dr. John Snow, known as the father of epidemiology.

Between 1849 and 1854 Dr. Snow found 286 deaths among those that used water
from the river Thames with higher amount of sewage inputs in London compared to just
15 deaths from those who drew water from up river near Thames Ditton (Stewart-Tull,
2001) which at the time, was located in the suburbs. The epidemiological information
gleaned from this study has influenced our understanding about the protection of water
resources from fecal contamination. However, despite this information and knowledge
the contamination of fresh water resources in the United States with untreated and / or
improperly treated sewage (such as Combined Sewer Overflows and non-point source
pollution, which will be discussed later on) remains a significant challenge for

communities and public health. Better assessment of fecal contamination is needed in

order to address the overwhelming financial burden of upgrading our sewage
infrastructure to improve water quality and safeguard surface waters and particularly our

recreational waters.

1.0 Introduction

Environmental degradation and pollution of recreational and drinking water have
recently moved back to the forefront of public interest. In addition to water quality
concerns, the role of sediments as reservoirs of contamination in aquatic systems remains

a complex and important area of study.

When dealing with water quality, there are pollution and contamination issues.
Pollution is the introduction of substances into the environment that results in a negative
effect to ecosystems. This is the accumulation and adverse affects of contaminants or
pollutants and present hazards to human and animal health. Contamination is may be a
result of anthropogenic waste materials produced from the activities of humans, but can
also occur from natural processes such as blooms of hazardous algae, arsenic dissolution
from bedrock into ground water, smoke from natural sources presence of elevated

concentrations of substances in water, sediments or organisms.

Pollutants can impact the ecosystem and their inhabitants. Pollutants can
bioaccumulate in organisms or become biomagnified. Bioaccumulation is the net
accumulation of pollutants over time within an organism from both biotic and abiotic

factors (environmental). However, when dealing with food trophic levels, the

progressive accumulation of persistent toxicants by successive trophic levels is known as

biomagnification.

The higher the organism is on the food chain (top predator) the more magnified
the pollutant is, as it now contains the cumulative amount of pollutant of lower prey and
the prey of its prey. This is especially evident in issues of metal contamination such as
mercury where whales are at risk due to the large quantities of fish (each of which has
mercury) which has a magnified affect to the whale. This can be seen in the ratio of the

pollutant in tissue of predator compared to its prey.

It has been recognized by the US Environmental Protection Agency (EPA) that
nutrients (Phosphorous and Nitrogen), bulk organics (oil and grease), halogenated
hydrocarbons (or persistent organics, such as DDT and PCB’s), polycyclic aromatic
hydrocarbons, metals (mercury, lead, manganese, cadmium, zinc) and metalloids (arsenic
and selenium) are some of the major pollutants found in sediments (US EPA, 2005). For
these chemical pollutants, there are guidelines, standards and risk- levels set forth by
governmental agencies for water, sediment, and soils. However, there are no such
guidelines for dealing with microbial contaminants and pathogens found in sediment as
exist for surface water. . .neither in the “Clean Water Act” (US), “BEACH Act” (US) nor

in the Canadian Environmental Quality Guidelines (Environment Canada, 2005).

Microbial degradation of ambient waters is a known problem. According to the

2005 report by the Natural Resources Defense Council (NRC) in 2005, the numbers of

beach closing and advisory days increased by 9% in 2004 from 2003. Beach closings and

advisories increased in Michigan by 174 % in 2004 from 2003 due to elevated bacterial

levels (N RDC, 2005). This increase may be a result of increased number of beaches
monitored and increased amounts of rain during the sampling year. In the latest 2006
NRDC report, there was a 5% increase in ocean, bay and Great Lakes beach closings and
advisories in 2005 due to bacteria and of the 14,602 advisories and closures, 63% were
due to unknown sources (N RDC, 2006). While Michigan had a decrease in advisories
and closures in 2005 compared to 2004, the net amount was higher than 2002. One of the
Ottawa county beaches in Michigan at Lake Michigan [a site used in this study (Rosy
Mound Beach)] was found to have a 13% exceedance rate (N RDC, 2006). This has
potentially serious repercussions for the public who are exposed to this poor water
quality. Human health risks related to these beach closings are based on high levels of
fecal indicator microorganisms in the water. Indicators microorganisms are those
generally found in animal and human intestines and are discharged into the environment

through sewage, manure, wildlife fecal deposits and storm waters.

1.1 Bacterial and Coliphage Fecal Indicators
In order to assess water quality in terms of microbial pollution, fecal coliforms,
Escherichia coli, and Enterococci are the main indicator microorganisms used and to

some extent C lostridium spp. and bacteriophages (viruses that only infect bacteria).

Fecal Coliform bacteria belong to the family enterbacteriaceae as shown in Table 1-1.

Coliforms are aerobic and facultative anaerobic, non-spore forming, gram negative

bacteria able to ferment lactose at 35°C (Total coliform) and 445°C (fecal coliform).
Coliforms live in the digestive tract of warrn-blooded animals (humans, pets, farm
animals, and wildlife) (Gerba, 2000) and are excreted in the feces. In themselves, fecal
coliforms generally do not pose a danger to people or animals but they indicate the
possible presence of other fecal pathogens, disease-causing bacteria, such as those that
cause typhoid, dysentery and cholera. Escherichia coli are a specific type of coliform
bacteria that possess the enzyme B-glucuronidase and are capable of cleaving substrate 4-
methylum-belliferyl- B-D glucuronide (MUG). Their presence indicates specifically fecal
contamination, and the possibility of enteric pathogens. E. coli is a worldwide universal
indicator of fecal contamination of water. Some strains of E. coli are harmful, and do
cause sickness. One type of E .coli (0157) causes gastroenteritis (Levy et. al. 1998) and
hemolytic uremic syndrome and has been found in water at beaches and is associated
with illnesses in swimmers (Ihekweazu et. al., 2006, Bruneau, A et. al. 2004., Harrison

and Kinra, 2004, and Paunio et. al. 1999).

Table 1-1. Classification of bacteria used in this study

 

 

 

 

 

 

 

 

 

 

 

 

Kingdom Bacteria Bacteria Bacteria
Phylum (P) / Proteobacteria (P) F irmicutes (D) Firmicutes (D)
Division (D)

Class Gamma Bacilli Clostridia
Order Enterobacteriales Lactobacillales Clostridiales
Family Enterobacteriaceae Enterococcaceae Clostridiaceae
Genus Escherichia Enterococcus Clostridiaceae
Species coli avium perfringens

durans
faecalis
faecium
Shape Rod Cocci (sphereical) Rod
Growth condition Aerobic & Facultative Anaerobic
Facultative anaerobes anaerobes
Gram Stain - + +
Reaction (+/-)
Sporulate No No Yes

 

 

 

 

Enterococci are part of what is known as the fecal streptococci group; specifically

E. faecalis and E. faecium are found in humans (Gerba, 2000) but are not restricted to

humans. Enterococci are well suited as nosocomial pathogens because they readily

colonize skin and mucous membranes (Mallon, 2002) but are excreted in the feces of

animals and humans. These bacteria also tolerate temperatures from 10°C to 45°C,

survive in acid and alkaline conditions and are more resistant to environmental stress and

chlorination than coliform bacteria. They generally persist longer in the environment

(Maier et. al., 2000., Gleeson and Gray, 1997., Mellon, 2002).

One area of concern documented in literature involving water samples (such as

wastewater, river and agricultural runoff) was the occurrence of Enterococci that showed

antibiotic resistance. Rice et. al. (1995) found Enterococcusfaecalis, E. faecium, E.

gallinarum (collected within a 30—mile radius of Cincinnati, Ohio) demonstrating patterns

 

of antibiotic resistance to amino-glycosides. With agricultural drainage areas (smaller
bodies of water) flowing into larger bodies of water, this could lead to higher chances of
pollution containing potentially antibiotic resistant bacteria and other pathogens in rivers,
lakes and recreational areas. There is a fear that some of the antibiotic resistant bacteria

may be difficult to treat if a recreational user is exposed and becomes infected

Clostridium perfringens are spore forming bacteria which replicate under
anaerobic conditions. They are excreted in the feces, and can be an indication of old
pollution as the spores are able to persist in the environment. Some have suggested that
this makes them more suitable as an indicator for the presence of persistent pathogens of
a fecal origin (Payment and Franco, 1993) such as viruses and parasites. Due to the
ability of E. coli and Enterococci to re-grow in the environment under warmer
conditions, and C. perfi'ingens generally unable to do so (Davies et. al., 1995), it is
considered a pragmatic addition to other commonly used indicator species. Due to lower
decay rates, C. perfringens can persist in the environment significantly longer than
enteric pathogens (Cabelli, 1978) making them good indicators of fecal pollution

(Ashbolt, 2001), especially in warmer tropical waters.

Viruses are microscopic nano particles which infect cells of a living organism and
cannot replicate on their own. Bacteriophage are virus that infect bacteria, and
coliphages are bacteriophages that are specific to the host E. coli. Because coliphages
come from fecal material, their presence in water bodies indicates fecal contamination as

well as the survival and transport of potential human viral pathogens in that same source

(Noble et. al. 2003). Bacteriophage resemble enteric viruses in size, structure,
morphology and behaviour in water (Pepper, Gerba and Brusseau, 2006), therefore their
presence in the environment can indicate a possibility of human viruses if sewage is the
source of fecal contamination. Bacteriophages are also advantageous to use because they
are less likely to replicate in the environment. Raw sewage inputs found along the Rio
Grande River basin near the United States-Mexican border region, were best represented
by male specific and somatic coliphages detected in 52% (11/21) and 62% (24/39) of the
samples, respectively with somatic coliphages being greater by one order of magnitude
compared to male specific (Ryu et. al., 2005). It was suggested that these findings were a
result of surface water runoff and constant agitation of the water causing re-suspension of
already present microbes, input and continuous sewage loading and combined sewer

overflow events.

In order to gain a better understanding and the extent of fecal pollution, and to
minimize uncertainty and extent of contamination , the use of multiple indicator species
is suggested by Gerba and Rose (2003) such as C. perfringens and coliphage in addition

to standard indicators such as E. coli and Enterococci.

1.2 Existing Water Quality Acts

In 1914, the United States Public Health Service began using the total coliform
group as an indicator of contamination in drinking water (Maier et. al. , 2000). The public
health service oversaw “safe” water until USEPA was formed in 1970. Congress rewrote

and passed the “Safe Drinking Water Act” (SDWA) in 1974 to protect public health by

regulating all public drinking water supplies at a national level. The law was amended in
1986 and 1996 and requires treatment and finished water with a maximum contaminant

level goal of zero for parasites and viruses (EPA, 2006).

In 1972, the “Federal Water Pollution Control Act”, was amended to what is now
known as the “Clean Water Act”. Goals of the Clean Water Act are to have “fishable and
swimmable waters” and are geared towards contaminants (both microbial and chemical)
of navagatible surface waters and, maintaining the physical, chemical and biological
integrity of the aquatic system. The Act gives the government power in regulating point
source pollutant discharge in navigational waters (Environmental Protection Agency,
2005), wastewater management, and works to minimize non point source pollution. On
October 10th in the year 2000, an addition to the “Clean Water Act” was made under the
“Beaches Environmental Assessment and Coastal Health” Act, other wise known as the

“BEACH Act”.

The BEACH Act focuses on human safety and reducing human illness addressing
national coastal and Great Lake recreational waters (marine and fresh) via the
development of new water quality guidelines. Section 303 of the Federal Water Pollution
Control Act (3 3U.S.C. 1313) was amended by adding “Not later than 42 months after the
date of the enactment of this sub-section, each State having coastal recreation waters shall
adopt and submit to the Administrator water quality criteria and standards for the coastal
recreation waters of the State for those pathogens and pathogen indicators for which the

Administrator has published criteria under section 304(a)”. The guidelines/standards

referred to in the BEACH Act include microbial indicators Enterococci and E. coli
measured per 100 mL of water. Table 1-2 shows the EPA water quality criteria and
Michigan standards for Great Lakes recreational waters. Measures are for ambient fresh
water using geometric means for multiple samples or different days and a single sample
maximum for bathing beaches (Federal Register vol 69, 2004). Single sample maximum
suggested by US EPA for E. coli and Enterococci are 235 and 61 CFU/ 100mL
respectively. Michigan requires a maximum of 300 CFU/ 100 mL for E. coli for a single
sample and a geometric mean of 130 CFU/ 100 mL (at present, a Michigan standard does
not exist for Enterococci). Guidelines in both Clean Water and BEACH Acts suggest
when and how often to monitor and these are only for the water column. Currently no
standards or criteria exist for microbial contaminants in sediment or sand for recreational
waters. This is important as not all recreation takes place in the water and occurs on the

beach and at the sand/water interface where sediment and sand become agitated.

Table 1-2. Fresh water quality guidelines and standards (CFU/ 100 mL) for areas of
recreational use.

 

 

 

 

Geometric Mean” Single Sample
Maximum
US. EPA
Enterococci 33 61
E. coli 126 235
MDEQ
E. coli 130 300

 

8 based on five or more samples equally spaced over a 30-day time period
MDEQ: Michigan Department of Environmental Quality

10

 

1.3 Fecal Contamination from Point and Non-Point Sources

There are two types of pollution: Point and Non-point pollution. Point source
pollution can be traced to a specific source which directly inputs to a water body.
Examples of point source pollution include waste water treatment plant, factories and
combined sewer overflow pipes. Non-point source pollution comes from a variety of

more diffuse sources.

Pollution caused by non-point sources is usually a result of rainfall or snowmelt
runoff, which generally doesn’t have an end of the pipe discharge, are very diffuse, and
picks up and carry both natural and anthropogenic pollutants before depositing them into
lakes, rivers, wetlands, and coastal waters. Non-point source pollution also can have an
impact on underground sources of drinking water. Examples of non-point source
pollution include urban and rural storm water run-off containing oil and grease,
agricultural nutrients (also herbicides and pesticides), as well as fecal bacteria, viruses
and parasites from wild animals, pet waste, leaky septic tanks (bacteria and nutrients)
boats and manure from animal farming operations. Figure 1-1 shows how these sources
of pollution creates a pathway for interaction amongst surface water, sediment and
beaches and can has the potential to result in recreational human exposure to micro-

organisms.

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According to the National Water Quality Inventory (EPA,2000) prepared under section
305(b) of the Clean Water Act, the causes of water body impairments were siltation
(sediment), nutrients, bacteria, metals and oxygen-depleted substances. It also found that
non-point source pollution in the form of urban and agricultural runoff was the leading

source of impairment.

1.3.1 Sources of pollution

Septic Tank Systems

Onsite waste disposal systems known as septic tank are individual systems for
sewage storage and discharge. Septic systems are used to separate solids from liquid in
waste water, after which they are partially treated or piped to a leach field for disposal to
the soil. Septic systems from homes and businesses dispose of the liquid portion into the
ground through soil layers. The waste water contains bacteria, parasites and viruses. It
was found that 105 PFU/ 100 mL of F-male specific phage occurred in septic tanks
(Debartolomeis and Cabelli, 1991). Over 40% of homes in Michigan use septic tank
systems (Lusch, 1997), this is similar to other states with large coastlines such Florida

where 30% of Florida’s population use septic systems (Marrella, 1990).

In the lower reaches of the Myakka and Peace Rivers (southwest Florida), fecal
indicator organisms were found in areas with a high concentration of septic systems
(Lipp et. al. 2001). During wet periods (which coincided with El Nino weather effect in

end of l997-early 1998), the fecal pollution indicators became widespread (Lipp et. al.

13

2001). Both ground waters and surface waters in Wisconsin have been shown to be

impacted due to septic tanks particularly with fecal viruses (Borchardt, 2003).

Combined Sewer Overflows (CSOs) and storm sewers

According to the Environmental Protection Agency (2003), there are
approximately 772 communities in USA which use a Combined Sewer System (CSS)
which includes C803 and accidental SSOs (Sanitary Sewer Overflows). Most CSO
facilities are located in the northeast, northwest and Great Lakes regions of USA.
Combined sewer systems occur when a pipe carrying storm water is combined with a
pipe containing untreated sewage. This mixture is stored in a containment tank,
however during periods of heavy rainfall and snow melt, and when the capacity of the
tank is reached, the excess spillage is discharged without treatment into nearby streams,
rivers or other water bodies. In comparison, SSO’s are municipal waste, which do not
contain industrial waste. Causes for S80 are generally heavy rainfall and blockage of
pipes which can overflow into water bodies and/or in basements. Spillage from CSOs
can contain storm water run off, raw sewage, industrial waste and toxic chemicals. Due to
inputs of untreated sewage containing higher levels of total suspended solids and fecal
microorganisms into bodies of water, CSOs have the capacity to impact water and
sediment quality at the site of discharge as well as downstream. Greater risk may be
associated with recreational areas impacted by C80 spills. These contain human fecal
indicators and pathogens which can harm recreational users. Antibiotic resistance is also

a concern. When examining samples from inside the C80 containment tanks, it was

14

found that 2 of 12 E. coli isolates from the sewage had multiple resistance to ampicillin,

ciprofloxacin, gentamicin, and tetracycline (Edge and Hill, 2005).

Studies of intertidal mudflats in the Boston Harbour area (Savin Hill Cove) have
shown CSOs to impact sediment and water (Shiaris et. al., 1987). After repeated CSO
events over time, bacteria were found to form a reservoir in sediment. At high tide fecal
coliforms were present in sediments at two to four orders of magnitude higher than in the
overlying water column. Sediment contained between 200 — 60, 000 cfu/l 00mL slurry of

fecal coliform.

Wastewater treatment plants

While the United States has the Clean Water Act that has mandated secondary
treatment for all sewage treatment facilities, in Canada, no such act exists. A study
performed on the St. Lawrence River basin found high levels of indicator bacteria in
rivers which still received raw sewage discharge (Payment et. al., 2000). Geometric
means for fecal coliforms in some of the polluted waters were found to be: 15, 560
CFU/L (Laval Ste-Rose), 32, 948 CFU/1L (Lavaltrie) and 26, 355 CFU/L (St. Therese).
Geometric means for C. perfringens concentrations at the 3 sites were 957, 2676 and
1373 CFU/L respectively (Payment et. al., 2000). Sediments in addition to the water
column were impacted. This may be particularly important under cold climate
conditions. Cold temperatures can stabilize the bacteria and allow them to remain viable
for longer periods of time. At McMurdo Base (Antarctica), higher concentrations of

indicator species were reported in the sediment than in the water column at the sewage

15

outfall (Lisle et. al., 2004). The following averages were reported for the water column
(CFU/ 100mL) /sediment (CFU/g dw): fecal coliforms (21/1 .04x104), E. coli (15/65),

Enterococci (22/2.22x103), C. perfringens (4/7.78x102) and coliphage (0/0).

In order to control the amount of discharge of pollutants entering into surface
water, the National Pollutant Discharge Elimination System (N PDES) was created. This
permitting program was born out of the Clean Water Act amendments of 1972 in the
United States. Anyone or any organization proposing to discharge waste or wastewater
into surface water must obtain a NPDES permit from the state. In Michigan, applications
must be sent to Lansing a minimum of 180 days before the proposed use is needed. Each
permit is valid for only five years. Michigan developed a five year basin plan based on
each receiving water body (lake, river or stream). Every five years permits in each water
basin must be renewed during the same cycle. In order to process NPDES permits
efficiently, watersheds are staggered among five cycles with the Lower Grand River (part
of this study site) being in cycle and its permits being renewed by April 1St in the years
2006, 2011, 2016 etc... The upper Grand River (up river of the study site) is on cycle

three with next permits due to be renewed in the year 2008.

For wastewater treatment plants that discharge untreated or partially treated waste
into surface water (not including CSO events), there are strict compliance laws which
must be adhered to. Monthly fecal coliform bacteria must not be more than 200 CFU /

100 mL on a monthly basis and 400 CFU/ 100 mL during a 7 day average. Any

16

chlorination or ozonation to reduce bacteria concentrations must be done before water is

discharged as to minimize harm to fishes and other aquatic organisms (MDEQ, 2007).

Animal Feeding Operations (AFO)

Regulated large animal operations are knows as Concentrated Animal Feeding
Operations (CAF Os). These are facilities where animals have been, are, or will be
stabled or confined and fed or maintained for a total of at least 45 days in any 12-month
period, and the animal confinement areas do not sustain crops, vegetation, forage growth,
or post-harvest residues in the normal growing season (US EPA, 1993). In Michigan, a
CAF O is defined as an animal feeding operation housing 1000 or more animals.
Livestock excrete indicator bacteria and pathogenic bacteria such as Escherichia coli,
Salmonella spp., and Streptococcus spp., pathogenic protozoa such as Giardia lamblia

and Cryptosporidium parvum, and a number of animal specific viruses (Mawdsley et. al. ,

1995; Rice et. al., 1995).

These operations may sometimes use a lagoon system to store waste, while others
concentrate the waste and dry it out to spread onto fields (Williams et. al. , 1999).
Lagoons are generally open air pits filled with both urine and feces from animals.
However lagoons are susceptible to leakages, ruptures, weather effects and
mismanagement; also dried waste can enter water systems through surface runoff or
ground water filtration (Mallin, 2000., Edwards and Daniel, 1992). Manure from these

systems are generally applied to crops and soils both in a dry or liquid form.

17

These practices are another potential source of concern during rainy periods or
from runoff. In instances where CAFO disposal mechanisms are aging or not up to code,
microbial pollution can result in neighbouring drains, ditches, rivers, lakes and creeks. In
1995, 25 million gallons of liquid swine waste entered the New River (North Carolina)
after an 8 acre hog lagoon burst. After 14 days, fecal coliforms in the water column were
102-103 CFU/ 100 mL water and in the sediment where the plume stayed for 5 days,
fecal coliform concentrations were 2 104 CFU/ 100 mL slurry (Burkholder et. al., 1997).
According to NRDC (2006), during Hurricane Floyd, five manure lagoons burst while
approximately 47 of them were completely inundated and flooded with water leading to

contamination of well water and surface water nearby.

Grazing Animals

Large herds of ruminants or swine not only deposit large concentrations of fecal
microbes but their grazing can further expedite the travel of microbes from soil to ground
water (Celico et. al., 2004b). When an area is grazed, the soil is also vulnerable to
erosion during rainfall, leaving the runoff to sweep contaminated soil into nearby streams

and water sources.

In a study of two springs, it was found that 29% of the samples had violated the
Kentucky surface water rule (fecal coliform) before grazing occurred in the area,
however after grazing in nearby pastures, 80% of samples exceeded those the standards
(Howell, Coyne and Cornelius, 1995). These authors also observed that when rainfall

occurred, fecal bacteria moved from soil surfaces into well water and streams. It was

18

found that 5% of total cattle manure deposited by cattle contributed to stream pollution
(Gary, Johnson and Ponce, 1983). However, at least 150 grazing cattle were needed to
significantly increase the bacterial concentration of fecal coliforms and when 40 cattle or
less were grazing, concentrations went down to levels similar to no grazing as was shown

in the adjacent fields.

When comparing creeks with and without grazing impacts, a significance
difference was found in E. coli and Enterococci populations. Fisher and Endale (1999)
found on average 894 MPN/ 100 mL at the “Grazingland Creek” compared to 88
MPN/ 100 mL at the Wood Creek. Enterococci were found to be 174 MPN/ 100 mL and
10 MPN/100 mL respectively. The wooded creek had no domestic animals within 1km

of the site.

Wild Animals

Wildlife and animal fecal discharges cannot be discounted as a source of pollution
and potential pathogens. It was found that waterfowl accounted for 67% of the fecal
coliform loading to one of the coastal embayment studied (Weiskel et. al., 1996). In a
study using macroarray hybridization techniques for E. coli, 51% of urban lake water
samples were identified as coming from geese and or ducks (Yan et. al. , 2006). When
the presence of gulls on the beach was compared with concentrations of E. coli on
foreshore sand and water the following day, R values ranged from 0.352 to 0.483 with a

p<0.05 (Whitman and Nevers, 2003). However no correlation was found when

19

comparing same day samples with gull activity. Deer and other ruminants can harbour
pathogens such as E. coli 0157:H7 and shed the organism in their feces (Keene et. al.,
1997., Rice and Hanncock, 1995). In a study where deer were inoculated with 108 CFU
of E. coli 0157:H7, on average 4.3 logm E. coli 0157:H7 CFU/ 1g feces were shed one
day after inoculation, concentrations decreased substantially until day 17 (Fischer et. al.
2001). After day 17 E. coli 0157:H7 was found intermittently until 25 days post
inoculation however enrichment culture techniques had to be used. It was found that deer
and cattle which share the same pasture can have the same strain of E. coli 0157:H7

(Rice et. al. 1995).

Seaweed and Algae

Various studies have shown bacteria are able to accumulate and survive on
seaweed in marine environments. Anderson et. al. (1997) found Enterococci exceeding
the water quality levels in New Zealand by 2-4 magnitudes in decaying drifi seaweed in
recreational beaches. Shibata et. al. (2004) found the concentration of total coliforms and
C. perfiingens to be significantly higher in sand which was under seaweed than
uncovered sand. High concentrations of Enterococci were found in marsh seaweed with
a geometric mean of 2284 MPN / 100 g ranging from 18-450 000 MPN / 100g (Grant et.

al,2001)

Studies along Lake Michigan also show that green algae (Cladophora glomerata)

can contain high concentrations of E. coli. Whitman et. al. (2003) found mean

logrodensities to be 5.3 (E. coli) and 4.8 (Enterococci) g/ dw with 97% of the samples

20

containing these bacteria. Algal mats exposed to sunlight for 27 hours experienced lower
bacteria numbers with an exponential decline in E. coli, but only small populational
decrease occurred within the first 9 hours, even in mats only 1 mm thick. Those that
were 6 mm thick maintained a 4 loglo g/ dw density, when exposed to sunlight for 27
hours. This was also found to be the case for Enterococci. Mats 2-4 mm thick showed
Enterococci concentrations decrease by 2 loglo after 18 hours but remained constant
afterwards. Both bacteria were dried on mats and than refiigerated at 4°C for 6 months.

When the mats were re-hydrated, concentrations of bacteria increased 4 logm in 24 hours.

These results have suggested that seaweed or algae can offer protection from UV
rays and can sustain bacterial concentrations until they are re-suspended in surface water
(during periods of agitation or wave action) and/or washed onto beach sand where these
biomats can deposit bacteria or shelter bacteria already present. The algae study gives
rise to the possibility that bacteria, namely E. coli may not necessarily be the best
indicator in identifying sewage pollution in areas where seaweed and algae mats are
abundant. If these fecal indicators are indicative of pathogens, then by leaving algal mats
on the beach and along the swash zone (where the water meets the beach) an increased

risk to recreationalists may occur if they come into contact with the mats.

1.3.2 Survival and Transport of Fecal Micro-organisms

Once bacteria, parasites and viruses leave the source of fecal pollution, many
factors come into play that affects survival and transport (Gerba and Bitton, 1984).

Factors such as pH, salinity, nutrient abundance, solar insulation (cloud cover) and

21

temperature affect survival. Rainfall is a key factor in transport. Climate is the overall
average weather found in a specific region and weather is the day to day events.
According to Gerba and Bitton (1984) climate controls two of the most important factors
associated with transport and fate, mainly rainfall and temperature. Retention of bacteria
and viruses are also dependant on soil and sediment particle size and clay content (which
will be discussed in the sediment section). Factors discussed here will be rainfall,

temperature and salinity.

Rainfall

Rainfall can impact the transport of fecal micro-organisms and can impact both
recreation and drinking water. A first flush effect can occur after rainfall, where
sediments are mobilized in run-off carrying with them potential pathogens, nutrients and
debris (Lawler et. al., 2006). After heavy rainfall in Walkerton, Ontario between May 8-
12 in the year 2000, the likes of which occurs in Walkerton Ontario once every 60 to 100
years, a major E. coli 0157:H7 outbreak occurred (Auld et. al., 2004). This
demonstrated how rainfall can impact bacteria flow from nearby farms, eventually getting
into water supply systems. Even early studies such as Goyal et. al. (1977) found peaks of
total coliforms in both surface water and sediment samples taken from canals along
coastal Texas during the months of June and November 1975 and January 1976 of over 4

log 10 CFU/100 mL for surface water after periods of rainfall.

Many instances of non-point source pollution are facilitated through surface run-

off during and after periods of heavy rainfall. Storm events increase the concentrations

22

of fecal bacteria downstream, and reported in some studies to be approximately two loglo
higher than during dry weather conditions (Rechenburg, 2006). The authors also
concluded that there was a significant association when looking at intensity of rainfall.
High intensity rainfalls were observed to have higher levels of bacteria and parasite
concentrations compared to longer lasting moderate rainfall before an overflow occurred

(Rechenburg, 2006).

When examining both marine and freshwater creeks and outfall samples along the
coast of Oregon for Enterococci, 99 (22 fresh water and 77 marine samples) out of 3086
samples exceeded the 158 MPN/ 100 mL level. The mean freshwater exceedance was
510 MPN/ 100 mL with a maximum concentration of 2419 MPN/ 100 mL. At Mill Beach
(freshwater), the relationship between rainfall (3 day cumulative) and Enterococci was
found be R=0.70 (N eurnann et. al. , 2006). When analyzing the marine water samples,
researchers observed that 91% of the exceedances occurred when there was some rainfall
within five days preceeding the reported water exceedance. Most of those marine
exceedances (55/77) of marine water exceedances occurred when the amount of rainfall
was between 0.01-60.0mm (Neumann et. al., 2006). The 2 day cumulative rainfall

relationship for marine Enterococci levels also had an R value of 0.70.

A study performed along Lake Superior found that rainfall did not have a
significant correlation with E. coli. The R2 values ranged from 0.00005 to 0.23 in 2003

and in 2004 the range of R2 was 0.0032-0.03 (Sampson et. al., 2006). These

measurements were taken within 24 hours of a significant rainfall of at least 6 mm.

23

While rainfall did not correlate well with E. coli in Lake Superior, there was one
occurrence of high E. coli concentrations on one of the samples taken after heavy rainfall.
After heavy rainfall (26.9 mm) on May 19"" 2003, the highest concentration of E. coli
was found (>2419.2 MPN / 100 mL) between May 20 through May 21) (Sampson et. al. ,
2006). However, this study did not take into account the possibility that over time, fecal
indicator bacteria may enter into Lake Superior from rivers and through surface water

runoff which may occur at time intervals greater than 24 hours after a significant rainfall.

Impact of rainfall was studied along the Milwaukee harbour along Lake
Michigan. After heavy rainfall (over 10 inches or 254 mm) water samples were
collected, cow specific Bacteriodes spp. were found in the harbour, but once the water
discharged into Lake Michigan, it was not found again. Parking lot run-off near beaches
were found to contain E. coli concentrations that ranged between 300 to 50, 000 CFU/
100 mL. After rain events, E. coli concentrations at two Lake Michigan beaches ranged
between 110 to 5400 CFU/ 100 mL with 7 out of 8 samples testing positive for Human

Bacteroides spp. (Bower et. al., 2005).

This is a world wide phenomenon and can affect large bodies of water. For
example, in Tokyo Bay (Japan), it was noted that after a rainfall of 84.5mm, total
coliforms increased from 13 to 240 CF U/mL and E. coli from 2 to 55 CFU/mL
(Haramoto et. al. 2006). Three days later, the concentrations decreased to 21 CFU/mL

(Total coliform) and 1.9 CFU/mL (fecal coliform).

24

Many studies have been performed examining the influence of rainfall on fecal
indicator bacteria concentrations in surface water, with a larger portion of studies on
marine and ocean waters. However gaps still exist in determining the extent of non-point
source inputs to rivers and lakes which potentially are increased due to heavy rainfall.
There is still need to examine water quality along longer reaches of rivers and creeks
before they enter into larger bodies of water like lakes and oceans, as opposed to limiting
sampling only near recreational beaches or harbours at the mouth of a river. As
technology develops, it would be beneficial to start using species specific markers such as
human sewage esp markers (Enterococci) and/or bird, cattle markers to determine
whether sewage or agricultural run-off is the primary source of fecal indicators and

pathogens during periods of intense rainfall.

Temperature

Temperature of water and seasonality can be related to fecal indicators in a
number ways. Warm temperatures may provide conditions for optimal re-growth for
some organisms, while cooler temperatures can stabilize environmental conditions for

others.

In southeast Carolina, Esham and Sizemore (1998) found fecal coliforms to be in
higher concentrations when temperatures were warmer (22-34°C) and when tides were
low. It is has already been established that indicators such as E. coli and fecal coliforms
may regrow in warm moist climates (Davies et. al. , 1995, Byappanahalli and Fujioka,

1998). Places like Hawaii use alternative indicators such as C. perfringens which would

25

not regrow along side traditional indicators to take into account bacterial regrowth in

tropical and sub tropical places.

However, increasing water temperatures can also be related to higher inactivation
rates. In some cases, part of this can be attributed to sunlight inactivation, as longer
summer days mean more exposure to sunlight and warmer temperatures. When modeling
the transport of fecal contamination in Lake Michigan, Liu et. al. (2006) found that
sunlight played an important role in E. coli, fecal coliforms, Enterococci inactivation with

k values of respectively. Sinton et. al. , (2002) found that Enterococci showed

significantly faster inactivation rates in summer (ks: 0.276 m2 MJ '1) than winter

(ks=0.110 m2 MJ") in rivers receiving wastewater. No significant differences were

observed for inactivation of fecal coliforms, E. coli and Coliphage. The inactivation rates

found for each indicator in summer and winter were as follows: fecal coliforms [summer

(ks: 0.086 m2 M1") and winter (k,=0.0.084 m2 M1")], E. coli [summer (k5= 0.078 m2
M1") and winter (k,=0.073 m2 M1")] and coliphage [summer (ks: 0.077 m2 M1") and

winter (ks=0.049 m2 MJ")]. Enteroccocci were found to have a higher inactivation rate

followed by fecal coliforms, E. coli and lastly coliphage (Sinton et. al. , 2002) .

Seasonal variation was found comparing bacterial exceedances in marine and
fresh water samples in Oregon. Ninety-nine samples were over the exceedance value of
158 MPN/ 100mL required for Oregon with an average of 559MPN / 100mL Enterococci

ranging from 160 - 43 52MPN/100mL. Neumann et. al. (2006) reported 60% of marine

26

sample exceedances occurred during winter compared to only 9% freshwater
exceedances during the same time period. With water temperatures in Oregon reaching

13°C in winter, full body contact and recreation occurs year round.

Bacteria have been shown to survive during colder temperatures. Escherichia
coli 0157:H7 has been shown to survive for prolonged periods in water, especially in
cold water, by transforming into a viable but non-culturable state (Wang and Doyle,
1998). In this state the pathogen cannot be isolated by traditional plating methods and

therefore may not be detected (Olsen et. al. , 2002).

In a study by Lipp et. al. (2001) seasonal variability was studied in southwest
Florida in low salinity estuaries. It was found that bacteria and viral indicators showed
significant seasonal changes over the course of one year and was related to rainfall,
temperature, salinity and river discharge. No significant differences were found in
sediment samples for C. perfiingens amongst the monthly concentrations. Enterococci
levels were found to be highest between December and February with a geometric range
between 77-112 CFU/ 100 mL. Lipp et. al. (2001) also found coliphage to be present in
higher concentrations in surface water from December to February. Coliphage peaked in
December with a monthly geometric mean of 293 PFU/100 mL.

Salinity

Esham and Sizemore (1998) found fecal coliforms to have an inverse relationship

with salinity concentrations. Coliphage was determined to be a poor survivor in warm

(25°C) saline water (Chung and Sobsey, 1993). Enterococci species may be more

27

halotolerent (Shehane et. al. , 2005) however salinity was found to negatively correlate
with Enterococci, fecal coliforms and coliphage in a Florida river system influenced by

coastal tides. Clostridium did not seem to be affected by salinity (Shehane et. al. , 2005).

Concentrations of indicator species are highly variable in time and space
(Shibata et. al., 2004) when examining recreational marine waters. Shibata et. al. (2004)
found the highest concentrations of indicator species to be during high tide and non-
detectable levels off—shore. This suggests that the real impact of pollution is along the

shoreline contributing to more recreational problems then previous recognized.

1.4 Public Health Concerns

Each state must have a set of guidelines and standards as mandated by the Clean
Water Act and BEACH Act in order for public recreational waters to be deemed safe.
Several indicators such as fecal coliforms, E. coli and Enterococci are monitored.
However, resulting beach advisories and closures as a result of monitoring programs are
often too late in capturing the pollution in real time and are generally 24 hours delayed.
Another issue in beach monitoring, is that generally only water samples are taken, and
not sediment and sand samples. Therefore, as of now, not all of the potential threats to

recreational safety are being monitored.

In order to minimize the risk of illness in beach goers, beach managers invest

millions of dollars in taking and processing water samples for fecal indicator organisms.

According to Schiff et. al. (2002), about $3 million is spent annually to determine the

28

public health risk potential in southern California. Ingestion of pathogenic micro-
organisms can occur through swallowing or drinking the water while recreating, through
the contamination of hands or possibly washing utensils in contaminated water, contact

with other materials such as algae, boats and beach toys.

Gastrointestinal illnesses and respiratory illnesses have been shown to occur in
Enterococci polluted water (Kay et. al., 1994). Eye, skin and respiratory symptoms were
other symptoms found to affect swimmers of microbially polluted beach water (Kueh,
C.S.W, 1995). It was found that swimmers had more episodes of diarrhoea and skin
rashes compared to non-swimmers in Mission Bay (California) and the number of
symptoms increased with higher exposure levels such as swallowing water (Colford et.
al., 2007). In the case of athletes, triathletes (those who swam, biked and ran) showed a
higher attack ratio of gastroenteritis one week post triathlon competition compared to
athletes who did not swim (only biked and ran) (Van Asperen et. al. 1998). According to
the authors, triathletes were twice as likely to show symptoms of gastroenteritis
compared to non swimmers in waters which had met the European and Dutch bathing

water standards with waters have less than 2000 CFU / 100 mL total coliform.

After reviewing many studies, it is evident that no one indicator can predict with
100% accuracy the exact water quality of a system and therefore prevent future water
born disease outbreaks from occurring. Based on a comprehensive meta analysis of
recreational water quality research, Wade et. al. (2003) support using indicators such as

E. coli and Enterococci over traditional indicators (fecal coliform) as the latter did not

29

show risk of illness if levels were increased. Their results suggested that Enterococci be
used as an indicator of fecal pollution in both marine and freshwater, while E. coli could
be used in freshwater. The authors also found that viral contamination indicators were
“strong predictors” of gastrointestinal illness for both fresh and marine water

environment (Wade et. al. 2003).

1.5. Water Quality in Great Lakes Basin and Michigan

The Great Lakes of North America are located along the border of Canada and the
United States and compose 1/5th of the world’s surface fresh water. These Lakes are an
important resource as they provide drinking water, recreational opportunities and drive
nearby economies. In total, the coastal line extends for 17,549 km, 5296 km of which is
along the State of Michigan. Due to the importance of the Great Lakes watershed,
numerous studies have been undertaken to determine the microbial water quality with a
focus on fecal pollution at beaches. Important papers highlighting Great Lakes research

are shown in Table 1-3.

30

Table 1-3. Summary of Great Lake published water and sediment literature.

 

 

Reference Microbe Year Water Sediment Water body
& water /season
type
Munawar General (1991) 2.5 xlOEL. Erie NA Great Lakes
et. al. 1994 Bacteria 1.6 x106 L. Huron

0.9 x106 L. Superior
0.75 x106 L. Ontario

 

 

 

Sampson E. coli 2003 10.3 -l92.3 MPN / 100 L. Superior
et. al.2006 & 2004 mL
Francy et. E. coli 17 to 190 CFU/100 mL 8 to >500 L. Erie
al., 2006 CFU/g dw
McLellan E .coli June — Offshore counts (IO-150m NA L. Michigan
and Sept. 2001 from shore)levels did not
Salmore, exceed 235 CFU/100 mL
2003 in more than 5%; beach

samples exceeded that
mark in 66% of samples

 

 

 

Murry et. E .coli 1997- 50% dry weather samples NA L. Michigan
al. 2001 I999 violated over 200 CFU
/ 100 mL
Alm et. al., E .coli 2005 NA Ambient sand L. Huron
2006 ranged from
67 CFU/g on
day 6 to 5
CFU/g on day
48.
Whitman E. coli Surface water- Sediment- L. Michigan
and 6.2x10'CFU/ 100 mL 7.2x103CFU/
Nevers, Pier- 1.2.2x10'CFU/ 100 100 cm3
2003 mL Foreshore
sand- 4.011103

CFU / 100 cm3

 

 

 

In 1991, a large scale study of the Great Lakes was undertaken with four great
Lakes and surrounding lakes being studied. Munawar et. al. (1994) reported of the great
lakes, highest bacterial abundance was found in Lake Erie and the lowest concentration in
the oligotrophic Georgian Bay and Lake Superior. In this study, the authors were looking
at total mean concentrations of bacteria and all were grouped together but were not
specified. The following are the mean numbers reported / mL x106MPN: 2.5 (Lake

Erie), 1.8 (Detroit River), 1.7 (Lake St. Claire), 1.6 (Lake Huron), 1.2 (St. Claire River),

31

0.8 (Georgian Bay), 0.9 (Lake Superior) and 0.75 (Lake Ontario). Lake Michigan was
not included in the study. Because Lake Erie is the shallowest of the lakes, it tends to
warm up faster and more often than the others which can influence bacterial
concentrations. Historically, of all the Great Lakes, Lake Erie has generally shown
higher amounts of pollution. Due to the shallowness of the lake, and chronic inputs from
agriculture and urban areas conditions have been ideal for microbial pollution and the
growth of algae . This study highlights that Lake Erie is still in need of consistent

monitoring, and strict adherence to laws regulating discharges and inputs.

In the state of Michigan, nine rivers which drained into various Great Lakes were
studied during July 2003 in the lower pennisula. Six of nine rivers had E. coli levels
above the US EPA guidelines of 235 CFU/ 100 mL (Jenkins et. al., 2005). The range of
E. coli for these six rivers were 235 (Raisin River) to 8500 (Rouge River, Dearbome)
CFU/ 100 mL. The Grand River site (upper reach of the Grand River watershed) had an
E. coli concentration of 900 CF U / 100 mL. Seven rivers tested above the US. EPA
guideline of 61 CFU/ 100 mL for Enterococci. Ranges for these seven rivers were 216
(Kalamazoo River) to 780 (Grand and Saginaw Rivers). Somatic coliphage (using C3000
E. coli as a host) ranged from 0.245 (Raison River) — 21.18 (Rouge River) PFU/ 100 mL.
Jenkins et. al. (2005) also determined that human fecal pollution was present in atleast
two of the rivers studied (Grand and Rouge River) using the esp Enterococci human
sewage marker. This study highlights the importance of inland rivers potentially

contributing to the degradation of the Great Lakes water quality, and that human sewage

32

has the potential to make its way into Lake Michigan and Lake Erie (Rouge River

empties into the Detroit River which connects Lake St. Clair to Lake Erie).

Sampson et. al. (2006) examined E. coli concentrations at 15 beaches in 2003 and
4 beaches in 2004 during beach season in Lake Superior, WI. Samples were collected
on a regular basis during the beach season. In 2003, the seasonal means at the 15 beaches
ranged from 10.3 MPN / 100 mL to 184 MPN/ 100 mL for E. coli and in 2004 ranged
between 118.7 to 192.3 MPN/ 100 mL. In some cases, E. coli concentrations were found
to be >2419.2 MPN/ 100 mL in Ashland county, WI and 816.4 MPN/ 100 mL in

Bayfield county, WI.,

In a recent study, two beaches along Lake Erie in Ohio were studied for fecal
contamination (Francy et. al., 2006). At the Edgewater location, E. coli were found to be
higher at sources near river mouths and outfalls away from the beach, and decreased
closer to the beach. Highest counts at the beach occurred within 1-3 feet of water and
decreased further out and when there were higher waves and rain (but not for all cases).
Investigation in Lake Erie found that pollution was along the shoreline and came from
near a pond drainage and boat launch. Researchers found physical evidence that run off
from the parking lot was impacting beach quality. Sediment values at bathing beaches
ranged from 8 to >500 CFU/g dw sediment at Lake shore beach. In the lake-water

samples, E. coli ranged from 17 to 190 CFU/100 mL during both studies.

McLellan and Salmore (2003) examined potential entry points of fecal pollution

into Lake Michigan. The study sites were a break wall—enclosed marina and a public

33

beach (South Shore Beach) on the western shore of Lake Michigan at the Milwaukee
metropolitan storm-water and C80 outfalls. In offshore samples (10—150m from shore)
E. coli did not exceed 235 CFU/ 100 ml in more than 5%. However, samples taken at the

beach exceeded that mark in 66% of the samples (McLellan and Salmore, 2003).

During the SSO/CSO events, human-specific markers were detected at sites in
nearshore Lake Michigan with >200 CFU/ 100 ml of E. coli. However, E. coli levels at
distances of more than 2 km from the harbor contained < 200 CF U/ 1 00 ml E. coli (Bower
et. al., 2005). However in a study performed by Murry et. al. (2001), no correlation of
fecal coliform abundance to C80 locations were found during the spring and summer of
1997, 1998, and 1999. Murray et. al. (2001) found that 50% of sites sampled during dry

weather periods violated acceptable water quality standards of 200 CFU /100 mL.

The abundance of E. coli was measured by Marasalek et. al. (1996) in the St.
Mary’s, St. Clair and the Detroit River. Marasalek et. al. (1996) described water quality
to be “excellent” in the St. Mary’s River in Sault St. Marie which did not have any CSO’s
(4-162 cfu/ 100 mL), but poor quality was found in the St. Clair River along a relatively
short Sarnia waterfront (5 CSOs) with an average of 62-5130 cfu/ 100 mL and 392-1929
cfu/ 100 mL in a long stretch of the Detroit River in Windsor (25 C805) (Marsalek et.
al. , 1996). In a study performed by Irvine et. al. (2005) in the Buffalo watershed area, on
a dry day fecal coliforms were found to be between 5450 cfu/ 100 mL but during rain
events, fecal coliform concentrations peaked l to 24 hours after rain events at

concentrations of approximately 1000 — 54000 cfu/100 mL. However, fecal coliform in

34

the Buffalo River did come from CSOs within the city boundary; higher concentrations

entered the river from the upper watershed region (upstream of the city).

When examining sand, sediment and water interactions at Lake Michigan, a range
of E. coli concentrations have been reported. Highest concentrations of E. coli were
found in the foreshore region of the beach with a geometric mean of 4.0x103 CFU / 100
cm3 (volume of “whole fresh sand”) followed by submerged sand at 7.2x103 CF U / 100
cm3 (Whitman and Nevers, 2003). Water sampled 45 cm below the surface (but above the
submerged sand) was 6.2x10'CFU/ 100 mL and 1.2.2x10'CFU/ 100 mL at the end of
Casino pier. This study highlights the importance of monitoring foreshore sand, sediment
and water. These results suggest that some of the foreshore sand may impact water
quality and monitoring should be on a beach ecosystem level as opposed to just surface

water.

A few studies (as previously mentioned) have examined fecal indicator bacteria
presence in sediment and sand (Byappanhalli et. al., 2003; Pettibone et. al., 1996;
Whitman and Nevers 2003; Whitman et. al. 2003). In an experiment performed on a
Lake Huron beach looking at wet weight sand, E. coli concentrations on ambient sand
went from being 67 CFU/g on day 6 to 5 CFU/g on day 48. However, initial
concentrations increased from 14 CF U/ g at time 0 and peaked to 7.1 x105. Bacteria
stayed at cultivable state for at least 48 days (Alm et. al., 2006). Studies indicate that
fecal indicator organisms can remain cultivatable for a prolonged period of time at

ambient beach sand temperature at the Great Lakes and can make their way to the sand-

35

water interface during periods of rainfall, high wave action, as well as re-suspension

during recreation as the previous studies have shown.

These instances of bacterial occurrences in the Great Lake basin could have
consequences to human health. At a Lake Erie beach during the summer of 1991 in
Ohio, 21 people acquired E. coli 0157:H7 infections (Keene et. al., 1994). All of the
patients reported swimming in the lake for extended periods of time. During some of the

outbreak days, Enterococci geometric means were reported to be >500 CF U / 100 mL.

Great Lake beaches remain an important source of potential recreational water
borne disease. It is imperative that more comprehensive monitoring programs get
established, on both American and Canadian beaches. In order to better protect the
public, current and up to date research needs to be carried out using indicators which
have found to be best suited to the Great Lakes environment. Also, technological
advances need to be made in order to develop faster testing methods to avoid the issue of
delayed beach closings and other potential sources and reservoirs of contamination must
be examined to gain a better picture of the extent of pollution in the Great Lakes and

where possible risks exist in a beach ecosystem.

1.6 Sediments as Sources of Fecal Indicators & Pathogens
Sediment is composed of loose particles such as sand, clay, silt, and other
substances that settle at the bottom of a water body. Sand is usually between 0.0625 mm

and 2 mm, silt is between 0.002-0.0625 mm while clay particles are generally classified

36

as smaller than 0.002 mm (USGS, 2005). Sand is usually shaped rather rounded or
angular and coarse, thereby creating relatively large spaces between each sand particle.
This promotes free drainage of water and entry of air into the substrate (Brady and Weil,
2004). Silt is characterized as having less space between particles than sand and is
mainly composed of the mineral quartz. It is smooth and silky, with a tendency to retain
more water (Celico et. al., 2004) and less water drains through it. Clay particles are
much smaller than sand and silt and therefore have smaller spaces between each particle.
Clay charge (negative) can also influence permeability. Clay behaves in a colloidal
manner and is difficult to separate out of water. Water moves in a very slow manner
through clay. The permeability (ability of a material to allow the passage of a liquid)
through sediment and soil are dependant on the ratio of clay, sand and silt with higher

amounts of clay correlating with less permeability.

Sediments come from eroding soil, decomposing matter and can be carried over
spatial distances by water. Soil is made up of various ratios of sand, silt and clay
constituents and soil columns have multiple layers. Usually the top layer is composed of
organic materials (each underlying organic layer being more compressed than that
above). Following the organic layer, come minerals, clays, oxides, carbonates ending
with salts. Because each layer is different, microbes travel differently through each layer.
It is important to note that soil varies greatly depending on region, climate and geological

aspects.

37

1.6.1 Sediments as a reservoir for fecal indicator bacteria

Sediments contain natural populations of microbes in their environment such as
Clostridium spp (Huang et. al., 2002). However, fecal indicator species originating from
auchtonous sources but have been found to survive and grow in sand, sediments and soils
near river banks such as Escherichia spp. (Burton et. al. 1987, Pang et. al., 2003) and

Enterococci (Whitman et. al. 2003, and Byappanahalli et. al. , 2003b).

Many sources of literature indicate that the majority of enteric bacteria in aquatic
systems are associated with sediments (Jamieson et. al. 2004). As mentioned previously,
these associations influenced their survival and transport characteristics. Sediments offer
a protective effect on microorganisms because they protect from solar irradiation (Bitton,
G., 1972) and salinity (Ghoul, M. et. al., 1990). Below, several studies, generally in
marine systems have reported on finding specific instances of fecal bacteria and

coliphage in sediment.

Sediments near off shore breakwaters were found to contain high counts of total
coliforms and Enterococci, as were instances of enteric viruses (Bitton, G., 1972).
Sediments also hold organic nutrients, which can support microbial growth. Compared to
water, sediments generally were found to have higher abundances of bacterial
populations (Burton et. al. 1987, Cavallo et. al., 1999) and lower die-off rates. It was
found in surface flow wetlands of Arizona, die-off rates of bacteria and coliphage were
greater in the water column than in the sediment (Karim, et. al., 2004). Die-off rates for

fecal coliforms were 0.256 logm / day (water) and 0.151 loglo / day (sediment). For

38

coliphage it was determined to be 0.397log10 / day (water) and 0.107logro / day
(sediment) (Karim, et. al., 2004). In general, the concentration of fecal coliform and
coliphage were similar when compared on a volume/wet weight basis in water and
sediment. When compared on a volume liquid : dry weight basis, the concentration of
fecal coliforms and coliphage were one to two orders of magnitude higher in sediment

(Karim, et. al., 2004).

In the Ionian Sea area of Italy, it was found that the highest heterotrophic (fecal
coliform, total coliform, fecal streptococci, sulphite-reducing Clostridia, Pseudomonas
aeruginosa and Staphylococcus aureus ) bacterial densities in water and sediment
samples were found in summer ( average: 2.7x105 CFU/mL for water and 5.9 x105
CFU/mL for sediment) while the lowest concentrations in fall (3.1x103 CFU/mL for
water and 3.8 x104 CFU/mL for sediment) (Cavallo et. al., 1999). This variance may
indicate re-growth occurring in the summer coupled with larger inputs from crowds that
come to beaches during summer. It was also shown that enteric bacteria were found to
have extended survival ability in freshwater sediment (Burton et. al. 1987) compared to
marine, indicating regrowth is an important issue in freshwater systems such as our study

area.

In southwest Florida fecal coliform bacteria ranged (geometrically) between 7 to
2337 CFU/ 100 g dw in sediment and were greater than the over laying surface water. In
the water column fecal coliform ranged (geometrically) from 4 CFU/ 100 mL in July to

157 CFU / 100 mL in December (Lipp et. al., 2001). For both sediment and surface

39

water samples, concentrations were observed to be highest during August and from
December through February. A five order of magnitude increase was found for C.
perfringens in sediment (184 to 36,834 CFU/ 100 g dw) and surface water. While the
greatest concentration of C. perfringens in surface water was found in March (36

CFU/ 100 mL), concentrations varied between months.

Fecal bacteria were found to be present in sediment areas of the New York Bight
apex disposal area (Babinchak et. al. 1977). In 1998, C. perfringens levels in sediment
were 556 spores/ g dw. Background concentrations in the same area were found to be 10-

20 spores /g dw (EPA, 1998).

These studies highlight the importance of sediment as a reservoir of potential
fecal indicator bacteria. Sediments were shown to protect the bacteria from UV light and
offer a somewhat stable environment. In instances where high concentrations of C.
perfringens were found, there is a potential of old pollution and harmful pathogens being
re-suspended into the water column when the sediment is re-suspended through

recreation or boating activity.

1.6.2 Re-suspension

In areas such as lakes, beaches or canals, pathogenic microbes which are
colonizing or concentrated in sediment, can be re-suspended into free flowing water.

Because the sediment reservoirs allow for enteric and pathogenic bacteria survival for up

40

to several months (Burton et. al. 1987), re-suspension is a possible source of risk. Re-
suspension occurs through sudden influx of water in shallow ponds, fish migration and
spawning disturbances, burrowing of small animals, nesting of sediment dwelling
species, earthquakes, tidal action, or seasonal flooding. Human induced re-suspension

can occur through dredging, boating and recreational activities.

Pettibone et. al. (1996) found fecal coliforms, heterotrophic plate counts and total
suspended solids increased immediately after the passage of a loaded boat along the
Buffalo River. In lake studies performed near the Texas-Oklahoma border (boating
marinas), E. coli in sediments were higher in number compared to those in lake water
(An et. al. 2002). Authors found a direct relationship between the amount of gasoline
sold which was related to recreational boating activity, and the re-suspension of E. coli
was found. This indicated that boating activity in the marinas likely re-suspended

sediments with attached E. coli.

In the Grand River Watershed (Ontario) a tracer study was performed to examine
the effects of re-suspension of bacteria from a fine grain sediment bed (grain size
0.11mm) to the water column using E. coli NAR (a strain of E. coli resistant to nalidixic
acid). Jarnieson et. al. (2005) recorded a first order inactivation constant of K=0.005/h in
the sediment. Tracer bacteria were not observed in the water column between 100 and
225 hours post seed. However, during the rising limb of a storm hydrograph at 225, 550,
and 600 h, the tracer bacteria was found in the water column, along with increased total

suspended solids. At 600 h E. coli was found to be 103 CFU/g in the sediment. The

41

authors concluded that the E. coli found was due to sediment mediated re-suspension.
This study is important as it highlights the risk of fecal indicator bacteria being
transported from its sediment reservoir into the water column. Once in the water column,

it may be transported downstream or potentially infect recreational users.

1.6.3 Processing bacteria and coliphage from sediment & sand

Sediment studies are limited partly due to the difficulties in collecting, sampling,
and analyzing sediments for indicator organisms. Currently, no standard method exists
for processing sediment samples. In order to process sediment samples, the sediment
must first be eluted and mixed, it has been suggested that one part sediment be added to
nine parts diluent or in some cases a 1:1 ratio of sediment to water has been used (Karim
et. al. 2004, Davies et. al. 1995, Gerba and McLeod. 1976). Diluents ranged from

sterilized river water, sterilized distilled water and Phosphate Buffer Water.

Two general ways to recover and quantify fecal indicators from sediment are
sonication and/or some sort of elution. In order to elute the bacteria, sediment and some
type of solvent (buffer, water, broth. ...) must be combined and shaken in such a way that
the fecal indicators detach from the sediment particles and get released into the solvent.
The solvent is than pipetted out. Literature surveys revealed that sonication (Craig, DL.
et a], 2002, Boenigk J, 2004, Furtado and Casper, 2000., Gough, H.L and DA. Stahl,
2003 Haglund et. al., 2003), hand mixing (Karim, MR. et. al., 2004), mechanical mixing
(Desmarais, TR., et. al. 2002), rolling (An et. al., 2002), density centrifugation (Furtado

and Casper, 2000), and vortexing (Byappanahalli et. al. 2003, Burton, G. et. al. 1987,

42

Cavallo, RA et. al. 1996, Lisle, JT et. al. 2004) were commonly used to elute the
sediment. Byappanahalli et. al. (2003) ran a comparison study using sonication, shaking,
and vortexing approaches. They found that the method which revealed optimum results
for eluting bacteria from sediment and soil samples involved vortexing the sample for 2
minutes. When comparing sediment to water in literature, sediment was usually
displayed as CFU or PFU/ 100 g dry weight ((Karim et. al., 2004) or wet weight (Lee et.

al., 2006) to the CFU or PFU/ 100 mL water;

43

1.7 Objectives of this Study

The Great Lake beaches remain at risk from C808 and other non-point source
pollution entering through river systems. However, only seasonal beach monitoring takes
place in Michigan and little emphasis is placed on the potential contribution of sand and
sediment on water quality. The role of sediment in fecal associated water pollution is an
on going problem which needs to be further investigated in Michigan watersheds. An
improved understanding of the relationship between fecal indicator species in sediments
and the potential impact to water quality will allow for improved decisions made on
performing beach closures and issuing beach advisories in order to protect public health.
The overall aim of this project is to examine the relationship between sediments and

water quality in an important river in Michigan. The specific goals of this study include:

1) Examine the spatial differences in fecal indicator concentrations along the
Grand River and Lake Michigan in both parks and beaches using traditional
and alternative indicators (fecal coliforms, E. coli, Enterococci, C.

perfringens and coliphage) in the water column and sediment.

2) Examine the impact of seasonal changes on the concentration

of fecal indicators.

3) Determine if a relationship exists between fecal indicators in surface water

and sediment.

44

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50

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54

2.0 Materials & Methods
2.1 Site description

The study sites (8 in total) were selected along the Grand River which flows from east
to west across mid Michigan, USA and ranged from Grand Rapids (Kent County) to
Grand Haven and F errysburg (Ottawa County). Six sites (three beach and three parks)
were studied in Ottawa County, Michigan and two sites (both parks) in Kent County,
Michigan (Table 2-1 and Figure 2-1). The three beach sites [North Shore Pier (NS),
Rosy Mound (RM), and North Beach Park (N BP)] were located along Lake Michigan —
north, south and at the entry point where the Grand River empties into Lake Michigan.
Parks studied were Riverside Park (RSP), Deer Creek Park (DC), Grand River Park
(GRP), Johnson Park (JP) and Sixth Street Park (SSP) - with Sixth Street Park located in

Grand Rapids and being the most easterly.

Table 2-1. Location of study sites with corresponding GIS information.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

City/Township Name MSU ID Latitude/Longitude Description
(AbbrevL site+sample date
Grand Haven North Shore NSmm/dd/yy N43 03.469 W86 15.324 B
Pier (NS)
Ferrysburg North Beach NBPmm/dd/yy N43 04.946 W86 15.265 B, Pi
Park (N BP)
Grand Haven Rosy Mound RMmm/dd/yy N43 01.164 W86 14.000 B
Natural Area
(RM)
Robinson Riverside Park RSPmm/dd/yy N43 01.728 W86 02.352 P, Pi, BL
Township (RSP)
Polkton Township Deer Creek DCmm/dd/yy N43 00.634 W85 56.199 P, Pi, BL
Park (DC)
Georgetown Grand River GRPmm/dd/yy N42 56.671 W85 51.262 P, Pi, BL
Township Park (GRP)
Grand Rapids Johnson Park lJPmm/dd/yy N42 58.330 W85 53.237 P, BL
(JP)
Grand Rapids Sixth Street SSPmm/dd/yy N42 58.603 W85 40.444 P, BL, F, D
Park (SSP)

 

Note: (B)Beach, (P) Park, (Pi) Picnic area, (BL) Boat launch, (F) Fishing area, (D) Dam few feet upstream,
(Abbrev) Abbreviations. Note MSU ID for sediment includes “sed” prior to date

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2.2 Sample Collection
2.2.1 Surface water

Samples were collected from April 2005 to August 2006. Sites were visited twice
a month during the spring/summer months (April -August) and monthly from September
to March. Two one-litre surface water samples were collected from the shore line.
Physical water parameter measurements taken during sample collection included water
temperature, ambient air temperature, pH, and turbidity. Qualitative weather
observations were recorded such as cloudiness, rain, snow fall, and whether or not the
lake or river had large waves or ice accumulation. Bottles were placed in a cooler with
ice, and transported back to the laboratory at Michigan State University where they were

placed at 4°C until processed. Samples were processed within 24 hours.

2. 2.2 Sediment

Sediment samples were collected by inverting a sterile Whirlpak bag, and scooping the
sediment along the submerged region up-to four inches deep where the water breaks with
the shore. Samples were taken from three points, one foot apart and than pooled into a
sterile Whirlpak bag. Samples were placed in a cooler with ice and transported back to
the lab where they were placed at 4°C until processed. All samples were processed

within 24 hours of collection.

57

2.3 Enumeration of water samples

Table 2-2 lists the various types of micro-organisms studied and the various types

of media used to quantify the bacteria and coliphage.

Table 2- 2. Types of analysis performed on both surface water and sediment

 

 

 

 

 

 

 

nalysis Media Incubation Volumes of water Reference
or sediment slurry
Assayed / plate or
tray
Fecal mFC 44.5'C 1-200 mL (water) EPA standard
Coliforms 0.5-50 mL (sediment) method 9222 D
E. coli Colilert 37°C 1-100 mL (water) Eckner (1998)
1-100 mL (sediment)
Enterococci Enterolert 41°C l-lOO mL (water) Eckner (1998)
1-100 mL (sediment)
C. perfringens mCP 45°C 1-200 mL (water) Bisson and Cabelli
0.5-50 mL (sediment) (1979)
Coliphage TSA 37°C 2 mL EPA standard
method 1601

 

 

 

 

 

 

Water samples were filtered through a 0.45 pm membrane filter (PALL Life Sciences
47 mm sterilized) according to EPA specifications. Selective agar media were used to
quantify fecal coliforms (mF C) and C. perfiingens (mCP). Fecal coliform agar were
prepared as follows: 5.2 g mF C agar (Difco267720, SanJose, CA), was added to 100mL
nano-pure water, boiled with agitation for 1 minute, and adjusted to a pH to7.4:t0.2. The
media was placed in a 55°C water bath until media was cooled to 55°C before adding 1.0
mL of 1% rosolic acid solution (0.01 g rosolic acid + 1.0 mL of 0.2M NaOH). The
selective agar used for C. perfringens was prepared as follows: 7.11 g mCP (Acumedia
7477A, Lansing, MI), was added to 100 mL nano-pure water, boiled until mixed,

adjusted to a pH of 7.6:t0.2, and autoclaved for 20 minutes. After autoclaving, the media

58

was cooled to 55°C water bath (until warm to touch) and the following additives were
subsequently added: 0.04 g D-cycloserine, 0.0025 g Polymyxin B sulphate, 0.2 mL 4.5%
ferric chloride solution, 2.0 mL of 0.5% Phenolphthalein diphospate solution and 0.006 g
Indoxy B-D glucoside. Afterwards, the media was pipetted into 47 mm Petri plates and
allowed to solidify. Water samples were filtered through membrane filters using vacuum
filtration. Filters were placed on each of the respective selective media, mFC plates were
incubated at 44.5 °C in a water bath and mCP plates were incubated in a 45°C incubator
in an anaerobic chamber. All plates were incubated for 24 hours. Blue colonies on the
mF C plates were counted as fecal coliforms, and yellow colonies which turned pink on

mCP media upon exposure to ammonium hydroxide gas were counted as C. perfringens.

In order to measure E .coli and Enterococci, 100 mL samples (diluted when
necessary) were assayed in a Quanti-Tray/2000 (WOT-2K) using the following IDEXX
(Westbrook, Maine) methods: Colilert (98-21375-00) and Enterolert (98-20705-00)
system. The powdered reagent (Colilert for E. coli & Enterolert for Enterococci) was
placed in a sterile container and than 100 mL of the sample were added. If samples
needed to be diluted, Phosphate Buffer Water was used as the diluent. The samples were
than mixed until the reagent was dissolved and than dispensed into the Quanti-Tray/2000.
Colilert samples were placed in a 36.5 °C incubator for 24 hours while the Enterolert
samples were placed in a 41°C incubator for 24 hours. After incubation, the Quanti-
Tray/2000 tray was placed in a dark room and exposed to a 365 nm long range ultra

violet light. All fluorescing wells were counted and enumerated by using a most

59

probable number chart which was provided with the IDEXX system and results are

quantified as most probable number (MPN) of E. coli and Enterococci.

Coliphage viruses were assayed according to an EPA method using a double agar
layer method (EPA 1602 section 11.3 double agar method). An overnight culture was
prepared the day before by adding 0.5mL of host bacteria (E. coli C3000 -ATCC 15597)
to 4.5 mL of TSB and incubating at 37 °C for 24 hours. A fast growth was prepared by
taking 1.0 mL of overnight culture and adding it to 45 mL of sterile TSB in a 50 mL
sterile centrifuge tube and incubating at 36£1 for 4 hours until culture was visibly turbid.
The fast growth host preparation was placed in 4°C to slow replication until use. Samples
were first filtered in 10 mL syringes (BD ref 309604) using an MILLEX®HA filter (0.45
pm) and MILLEX®GV filter (0.22 pm). In a test tube containing 2.5 mL of melted TSB
with 1.5% agar (kept at 49°C until used) 2 mL of sample and 0.3mL of host bacteria were
added. Sample, host and media were mixed by rolling the test tube between the palms
of the hands. The sample was than poured onto plates containing a bottom agar of
Tryptic Soy Agar (40 g TSA [Difco-236920] and IL of distilled water). The plates were
allowed to solidify, were inverted and incubated at 37 °C for 24 hours. Plaques in the

monolayer of the host bacteria were counted.

Bacterial colonies were counted and standardized to colony forming units (CFU)/
100 mL for surface water while coliphage was standardized to plaque forming units

(PFU) / 100 mL.

60

2.4 Enumeration of sediment samples

The following protocol was developed to enumerate sediment samples. Seventy-five
grams of wet sediment were placed in a sterile container and diluted by adding 675 mL of
Phosphate Buffered Water (PBW). The container was capped and sealed and mixture
was vortexed for 2 minutes (with a vigorous hand shake after one and two minutes). Any
dilutions were performed using PBW. Immediately, the resulting suspension was
collected without allowing anytime for settling and assayed using the same procedures
described above for the surface water samples [membrane filtration for fecal coliforms

and C. perfringens, Quanti-Tray 2000 for E. coli (Colilert) and Enterococci (Enterolert)].

In order to determine the amount of bacteria or virus per gram of sediment to allow
for comparison among the sites, dry weight was determined. To determine soil moisture
content, 10 g of wet sediment was placed in an aluminium foil boat and baked for a
minimum of 48 hours at 105°C (done in duplicate). Before measuring the dry weight,
sediment samples were cooled and placed in a desiccation chamber for one hour to cool
before being weighed again. The weight of the aluminium boat was subtracted from the
total dry weight. Dry sediment weight was divided by the total wet weight of sediment
used to obtain percent dry weight. The average of the two duplicate samples was

recorded.

The resulting colony forming units were multiplied by a factor of 10 (to take into

account original 10 fold dilution), divided by 75 g (to get colonies per g wet weight), than

divided by dry weight to wet weight ratio (per cent dry weight) to obtain colonies per

61

gram dry weight of sediment. Colonies were standardized to CFU/ 100 g dry weight

(dw) sediment. Coliphage was standardized likewise as PFU/ 100 g dw.

Soil nutrient, particle and organic matter analyses were performed on two samples
of sediment from each site (winter 2005 and summer 2006) at the Michigan State
University Soil and Plant Nutrient Laboratory. Sediment classification was performed
using a hydrometer method and Phosphorous by bray-p1 method (Brown et. al. , 1998).
Ammonium acetate extractable method was used to determine potassium, calcium and
magnesium. Organic matter was determined using the “loss un-ignition method” where

the organic matter was burned off and than subsequently weighed (Brown et. al., 1998).

2.5 Statistical analysis

Non-detects were assigned a value of 0, and a value of 1 was added to all data
points. This allowed non-dectects to be included in the analyses. Results were then logro
transformed. ANOVA and correlation analysis were performed using the program
MATLAB version 6.5 (N atick, MA). Statistical differences in means of indicator
bacteria and coliphage virus between sites were evaluated using Tukeys test from the
SPSS v. 12 (Chicago, IL). If the p value was greater than 0.05, than relationship was
deemed not significant, anything less than 0.05 was deemed significant. A box plot
containing 50 and 95% confidence intervals and means was generated and plotted

showing indicator concentrations along a spatial gradient.

62

Images in this thesis are presented in colour. Box plot graphs, land use images

and weather figures in the appendix best viewed in colour and are thus presented as such.

In order to examine seasonality amongst sediment and water samples, four time
periods were considered for analysis and were grouped as Spring (March 20-June 20),
Summer (June 21-August 22), Fall (August 23-December 20) and Winter (December 21-
March 19). An ANOVA was run to determine if differences existed among the different

indicators and Tukeys test was used to determine significance among seasonal groups.

Regression analysis between sediment and surface water, between indicator
species in surface water, indicators in sediment were evaluated using R2 values and p
values. When examining the effect of upstream sediment on water quality at the
immediate downstream site, only samples taken on the same day, and all sites were
sampled were included (n=11 for each site). Same day analysis were used to minimize
changes in sampling conditions such as rainfall, weekly water changes and any
significant changes in input loading which may occur. The uppermost sediment site was
compared to the water samples downstream. For example, SSP sediment was compared
to JP water; JP sediment was compared to GRP water etc. For the beaches, RSP
sediment was compared to each individual beach site. For abbreviation classifications,

please see Table 2-1.

Precipitation data for the duration of the study period was obtained from the

National Oceanic & Atmospheric Administration from the “local climatological data”

63

(Dept. of Commerce). The precipitation recorded the day before the sample was taken
data came from Grand Rapids, MI and Muskegon, MI rain gauges and than averaged.
Grand River discharge data was obtained from the USGS surface-water daily statistics
page from the Grand River at Grand Rapids, MI sites (U SGS 04119000) from April 13th,
2005 to August 28, 2006 (U SGS, 2006). Coordinates of the gauge are latitude 42°57’52”
and longitude 85°40’35”. The gage datum is 585.7 ft above sea level and covers a
drainage area of 4,900 miz. The average daily mean flow was measured and calculated
by USGS. Values used were from the same days that the samples were collected. Data
obtained was used to determine if flow of the river had any correlation to fecal indicator

bacteria and coliphage.

64

2.6 References

Bisson and Cabelli. 1979. Membrane Filter Enumberation Method for Clostridium
perfi'ingens. Appl. Environ. Microbial. 37(1): 55-66

Brown, J .R. 1998. Recommended Chemical Soil Test Procedures for the North Central
Region. North Central Regional Research PUblication No. 221. Revided January 1998.

Eaton, A.D., Clesceri, LS. and A.E. Greenberg. 1995. Standard methods for the
Examination of Water and Wastewater 19th Ed. American Public Health, Washington.

Eckner, K.F. 1998. Comparison of Membrane Filtration and Multiple-Tube Fermentation
by the Colilert and Enterolert Methods for Detection of Waterbome Coliform Bacteria,
Escherichia coli, and Enterococci Used in Drinking and Bathing Water Quality
Monitoring in Southern Sweden. Appl. Environ. Microbial. 64(8): 3079-3083

Michigan State University. 2005 & 2006. Soil and plant nutrient laboratory. Crops and
soils builiding, East lansing, MI.

United States Geological Survey. 2006. USGS Surface-Water Daily Statistics for
Michigan. Dept. of Interior. Website:
http://nwis.waterdata.usgs.gov/mi/nwis/dvstat/?format=sites selection links&search_site
_no=04l l9000&amp;referred module=sw Accessed November 20th, 2006.

65

3.0 Results

Eight sites along the Grand River were examined for fecal indicators fecal
coliforms, E. coli, Enterococci, C. perfringens and coliphage. Five sites were parks
located along the banks of the Grand River, one beach at the mouth of the Grand River
which emptied into Lake Michigan, and two beaches on either side of the river mouth
(directly along the coast of Lake Michigan). Reaches of the river were broken down into
3 groups: Upper (two eastern most site including SSP and JP), Middle (three parks
including GRP, DC and RSP), and Lower (the three beaches including NS, RM and

NBP). Site groupings are displayed below in Table 3-1.

Table 3-1. Site classifications and number of total samples taken at each site throughout
the course of the study.

 

 

 

 

 

 

 

 

 

 

 

 

 

# #
REACH SITE PARK OR WATER SEDIMENT
BEACH SAMPLES SAMPLES

Lower North Beach Park (N BP) Beach 21 21
Lower North Shore Pier (NS) Beach 20 19
Lower Rosy Mound (RM) Beach 19 19
Middle Grand River Park (GRP) Park 20 20
Middle Deer Creek Park (DC) Park 22 20
Middle Riverside Park (RSP) Park 19 19
Upper Sixth Street Park (SSP) Park 20 11
Upper Johnson Park (JP) Park 17 16

 

 

 

The overarching goal of this study was to determine the quality of surface water
in the Grand River and to determine the level of microbiological contamination in the
sediments of the same river. Sites were chosen based on areas where public recreation

takes place, and sampling was conducted during spring, summer, fall and winter.

66

A one way ANOVA was performed on each indicator in sediment and surface
water to determine if any significance existed amongst the samples. Significant
differences were found amongst the sites for all indicators in water samples (p < 0.05),
and four out of five indicators in sediment (coliphage in sediment p > 0.05). This
analysis indicated that there are differences within the indicator results worth exploring

and that further analysis can be undertaken. Results will be presented in this section.

At each site, for each fecal indicator, the geometric mean of the raw data was
determined for both surface water and sediment as shown in Table 3-2 (surface water)
and Table 3-3 (sediment). For surface water, SSP in the upper reach of the river had the
highest geometric average for fecal coliforms and Enterococci, and JP (also in the upper
portion of the river) had highest geometric for E. coli while GRP and DC (in the middle
reach of the river had the highest for C. perfiingens and coliphage respectively. Fecal
coliform geometric averages ranged from 11.30 CF U / 100 mL at the beaches to 185.19
CFU/ 100 mL at the parks. Geometric averages for E. coli ranged from 7.88 CFU/ 100
mL at the beaches to 68.03 CFU/ 100 mL at the parks. Enterococci geometric averages
ranged from 3.15 CF U / 100 mL at the beaches to 52.95 CFU / 100 mL at the parks.
Geometric averages for C. perfringens ranged from 2.13 CFU/ 100 mL at the beaches to
27.90 CFU/ 100 mL at the parks. Coliphage geometric averages ranged from 0.173 PFU

/ 100 mL at the beaches to 5.45 PFU/ 100 mL at the parks.

67

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69

For sediment, SSP had the highest geometric average for fecal coliforms and E.
coli, DC had the highest for Enterococci while GRP had highest for both C. perfiingens
and Coliphage. Fecal coliform geometric averages in sediment ranged from 1.84 CF U /
100 g dw at the beaches to 41681.94 CF U / 100 g dw at the parks. Geometric averages
for E. coli ranged from 1.30 CFU/ 100 g dw at the beaches to 14802.09 CFU/ 100 g dw
at the parks. Enterococci geometric averages ranged from 0.231CFU / 100 g dw at the
beaches to 34794 CF U / 100 g dw at the parks. Geometric averages for C. perfiingens
ranged from <0.15 CFU/ 100 g dw at the beaches to 21134 CFU / 100 g dw at the parks.
Coliphage geometric averages ranged from <15 PFU/ 100 g dw at the beaches to 0.697

PFU/ 100 mL at the parks.

Analysis was performed to classify the type of sediment found at each site during
late November and early December. Results are displayed in Table 3-4. For all sites, the
sediment type was Sand with the exception of GRP which was classified as Sandy Loam.
Sites DC and GRP had high levels of Phosphorous (33-40 ppm). At this level, soil can
support plant and vegetation growth. Highest organic content was also found at site
GRP. Sediment samples at the 3 beach sites were larger grained and easily separated in
the water column. Samples at RSP, DC, GRP were observed to be “sticky” and sediment
particles were hard to separate from the water. Sediment samples from September 14th
were analyzed and generally showed the same classification, however DC did shift to a
sandy-loam from sand and GRP was classified as sand rather than sandy-loam as before
(Table 3-5). Sites in the middle reaches showed increases in Phosphorous with DC and

GRP as the two sites with above optimum levels of Phosphorus for plant growth. All

70

sites collected in the fall showed increases in % organic matter except for RM and JP
which stayed the same. These results show the changing nature of spring and summer
conditions on the sediment classification. Table 3-8 shows the geometric physical
parameters of the water samples. Parameters are arranged by site and by season and
therefore displayed in section 3.2 where seasonality is explored. Date per sample are also

displayed in Appendix D.

Table 3-4. Sediment classification and particle composition taken November/December

2005
Site Phosphorous %
(ppm) pH Organic %Sand %Silt %Clay Classification

NBP (L) 2 8.3 0 97.6 0 2.4 Sand
NS (L) 2 8.5 0.1 97.6 o 2.4 Sand
RM (L) 2 7.7 0.1 97.6 o 2.4 Sand
RSP (M) 14 7.9 0.4 98.1 0.5 1.4 Sand
DC (M) 33 8.1 0.5 97.1 1 1.9 Sand
GRP (M) 40 7.9 2.4 72.6 13.7 13.7 Sandy Loam

JP (U) 24 8.2 0.2 95.6 0.5 3.9 Sand
SSP (U) 15 8.1 1 97.5 0.5 2.4 Sand

Reaches defined as (L )Lower, (M) Middle and (U) Upper.

Table 3-5. Sediment classification and particle composition from samples taken
September 14th, 2006.

Site Phosphorous %
(ppm) pH Organic %Sand %Silt %Clay Classification

NBP (L) 4 8.0 0.2 97.6 0 2.4 Sand

NS (L) 4 8.1 0.2 97.6 o 2.4 Sand

RM (L) 4 8.3 0.1 98.4 0 1.6 Sand
RSP (M) 10 7.9 1.7 88.4 8.9 2.7 Sand

DC (M) 44 7.9 1.5 82.4 6.2 11.4 Sandy Loam
GRP (M) 24 7.9 1.5 94.2 3.6 2.2 Sand

JP (U) 25 8.3 0.2 99.3 0 0.7 Sand
SSP (U) 15 8.6 1.5 96.8 1.8 1.4 Sand

Reaches defined as (L ) Lower, (M)Middle and (U) Upper.

71

In order to determine how the relationship of physical water parameters to fecal
indicator bacteria in surface water and sediment, pearson correlations were run and are
displayed in Table 3-6, all significant correlations occurred with a p<0.05. Fecal
coliform in surface water showed a positive correlation with the amount of precipitation
the day before sampling with R=0.369, however fecal coliform in sediment samples only
showed a significant positive correlation with water temperature (R=0.22). For E. coli,
water temperature showed a Significant negative relationship in surface water and a
positive relationship with E. coli in sediment. This suggests that E. coli may be growing
in sediment but dies off with warmer temperature in the water column. For rainfall, E.
coli had a positive relationship with rainfall (R=0.471) in the surface water but a
significant negative correlation with sediment (R=-0.22). This suggests that more rain
increases E. coli are in the water column from new inputs and less are in the sediment.
This may indicate loss of E. coli from the sediment to the water column during periods of

increased rainfall.

Enterococci in surface water Showed a significant positive relationship with
rainfall (R=0.351) and a very slight but significant negative correlation (-O. 199) with flow
indicating a possible dilution affect. Sediment samples were not found to significantly
correlate with any of the physical water parameters. Only rainfall showed a significant
relationship with C. perfringens in surface water (R=0.29) and in sediment a significant
negative correlation was found with turbidity in the water column. This may be an

indirect measure of loss form the sediments as turbidity increased that was not captured

72

during water sampling. Coliphage virus in surface water showed a significant positive
correlation with flow (R=0.122), but a significant negative correlation with pH
(R=—0.497) and water temperature (R=-0.43 3). However, no correlation was found for

coliphage virus in the sediment with any of the physical parameters.

73

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74

A regression / multiple regression was performed using factors (water temperature,
turbidity, pH, flow, and rainfall) to further examine relationships to the indiator.
Significance was determined using the pearson correlation test from Table 3-6. Basic
regression was used when only one factor was found to be significant according to Table
3-6. When more then one factor was found to be significant, a multiple regression was
run. Results from the ANOVA showed a p <0.05 for all indicator regression models
tested in surface water and in sediment for fecal coliform, E. coli, Enterococci, and
coliphage. No significance was found for models run for C. perfiingens in surface water
(p=0.07) and sediment (p=0.074). Models were not run on Enterococci and Coliphage in
sediment as none of the water parameters were found to show a significant correlation
with these indicators in the sediment substrate. Results for R2 were low for all indicator
species with the highest being R2 =O.252 for coliphage in surface water and R2 =0.119 for
E. coli in sediment. These results are displayed in Table 3-7. The values in Table 3-7
show water temperature and rainfall can explain 11.9% of the E. coli in the sediment
whereas temperature, pH and flow can explain 25% of the coliphage numbers in the

water column.

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7

3.1 Spatial Analysis of Surface water and sediment

A land use map was generated using Arc View 3.2 of Ottawa County and Grand
Rapids (Appendix A). The lower reach of the river (at the mouth of the river) contains
both high and low intensity residential area with sand dunes and evergreen or decidous
forests. The middle reach of the river is dominated by pastures and farms used for crops.
Small farms with cows were also visually observed near site DC. As the study area
transitions from middle reach to the upper reach, increased amounts of high intensity
urban residential areas are observed close to the Grand River, as well as an increase in
roads and transportation routes. Upper reach also contains some crop land but further

away from the river.

3.1.] Surface water

A spatial comparison found that there were significant differences between some
sites. Sites along the river were significantly different from beach sites (when p<0.05).
Beach sites were found to be statistically lower in contamination compared to the upper
and middle reaches of river sites. While sediments at beaches on average had higher
concentrations than surface water, differences were less than logw. However, sediments
at the park sites had generally 2-3 loglo higher concentrations of bacteria than in surface
water. Because coliphage only had 9 positive samples in sediment, a relationship could
not be adequately determined. Figures 3-1 to 3-5 (pages 82 to 86) are box plots
showing the mean concentrations of fecal indicators and 50th and 95th percentiles along
the Grand River and on Lake Michigan. All “a” graphs depict water samples, while

sediment is shown in the “b” graphs. The x-axis displays the reach of the river, broken

77

up into sites as was described in Table 3-1. The y-axis shows the concentration of each
indicator on a log scale as CF U/ 100 mL surface water or CFU/ 100 g dw sediment. In
general, sediment samples showed a higher degree of variability as opposed to surface

water samples.

Fecgl coliforms

Figure 3-1a shows fecal coliforms in surface water and sediment. No significant
differences were found among fecal coliform concentrations among the three beach sites
NBP, NS and RM. A significant difference was found between RSP & NBP and RSP &
RM. No significance was found between RSP and the beach site at the mouth of the
river. Sites east of RSP (DC, GRP, JP and SSP) all showed significantly higher amounts
of fecal coliforms than the three beach sites but no difference was noted amongst the
river sites. Upper and middle reaches of the river showed higher concentrations of fecal
indicators in both surface water and sediment. North Beach Park (N BP) was the only site
which had higher concentrations of fecal coliforms in surface water than sediment
samples on a 100 mL to 100 g dw basis. Figure 3-la does show some variability in the

water samples.

M

Figure 3-2a shows the concentration of E. coli in surface water. No significant
differences were observed among the three beach sites (NS, RM and NBP). A significant
difference was found between RSP and NBP. All sites east of RSP (upper and middle

reaches) had significantly higher concentrations of E. coli than the beaches, however no

78

significant differences between RSP, DC, GRP, JP and SSP (upper and middle reaches).
No significant differences were observed between park concentrations of E. coli. Middle

reach of the river showed increased levels of variability.

Enterococci

Figure 3-3a shows the concentration of Enterococci in surface water. No
significant differences were observed among beach sites, and none among the park sites.
All parks (upper and middle reaches) had significantly higher concentrations of
Enterococci than the beach NBP, however one park (RSP) was not statistically different

when compared to beach sites NS and RM.

C. perfringens

The concentration of C. perfringens in surface water is shown in Figure 3-4a. The
two farthest beaches NBP and RM did not show significant differences in concentrations
of C. perfringens amongst each other, however both beaches were found to have
significantly lower concentrations of C. perfringens than the beach located at the mouth
of the river into Lake Michigan (NS). The only park to have significantly higher
concentrations of C. perfringens than NS was GRP. No significance was found between
GRP and the other park sites and among park sites in general (upper and middle reaches).
The least amount of variability occurred in the water samples for C. perfringens

compared to all other indicators.

79

Coliphage

Site DC had significantly higher concentrations of coliphage than the two beaches
north and south of the Grand River mouth (NBP and RM). No other significant
differences were observed. However, only 54 samples of 164 samples tested positive for

coliphage. Coliphage concentrations are displayed in figure 3-5a.

3.1.2 Sediment
Fecal coliforms

Figure 3-1b shows the concentration of fecal coliforms in sediment samples. Out
of all the sites, NBP had the lowest concentration of fecal coliforms found in the
sediment and had significantly less fecal coliforms than all sites except NS. NS and RM
did not show significant differences from each other. All river sites (upper and middle
reaches) had significantly higher concentrations of fecal coliforms in sediment than the
beach sites. Sediment samples showed high levels of variability at all three reaches of the
river.
EJQII

Concentrations of E. coli in sediment samples are shown in figure 3-2b. Site NBP
was found to have significantly less concentrations of E. coli than all other sites in
sediment. No significant differences were observed between beaches NS and RM. All
sites in the upper and middle reaches of the study area (parks) had significantly higher
concentrations of E. coli compared to beach sediments (in lower reaches). No

significance was observed among sediments at the park sites. Variability was shown

80

along all reaches of the river in sediment, sediment samples had higher levels of

variability compared to E. coli in water samples.

Enterococci

Enterococci exhibited the similar trends in sediment as E. coli, however
Enterococci were found to have slightly higher concentrations in sediment compared to
E. coli in sediment (however this trend was reversed in surface water). Site NBP was
found to have significantly fewer concentrations of Enterococci as shown in figure 3-3b,
than all other sites in sediment. No significant differences were observed between beach
sites (NS and RM). All parks (upper and lower reaches) had significantly higher
concentrations of Enterococci compared to beach sediments in the lower reach of the
study area. No significant differences were observed among sediment samples among

the park sites.

C. perfringens

Figure 3-4b shows concentration of C. perfringens in sediment samples. There
was a clear difference in C. perfringens concentrations between parks and beaches. No
significant difference was observed among beaches (sites in the lower reaches), and no
significant differences were observed amongst the park sediments (among upper and
lower reaches of the study area). However, parks (upper and middle reaches) had
significantly higher concentrations of C. perfringens compared to the three beach sites
(lower reaches). Sediment samples had a larger range of variability compared to water

samples, especially in the middle reach of the river.

81

Coliphage

As shown in figure 3-5b, only a few samples tested positive for coliphage, 6
samples out of 148 tested positive for coliphage in the sediment. No significance was
observed among any of the sediment samples (p=0.709). However, the majority of the
positive samples (5 of 6) were found in the middle reaches of the river. Coliphage was
present in sediment at NS (June 19, 2005), RSP (June 21, 2005), DC (July 27, 2005),

GRP (September 28, 2005 & April 25, 2006) and JP (May 1, 2006).

82

 

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87

3.2 Temporal analysis of surface water and sediment
Four time periods were considered for analysis and were grouped as Spring
(March 20-June 20), Summer (June 21-August 22), Fall (August 23-December 20) and

Winter (December 21—March 19).

Precipitation was averaged from two gages (Muskegan and Grand Rapids airport),
both gages had high correlation with each other (R=O.85, p<0.05). A summary of the
averages for pH, water temperature, and precipitation is shown in Table 3-8. The pH of
the water was generally consistent ranging from 8.19 to 8.61. The two warmest seasons
were summer and fall. Flow was measured at one site using the USGS flow gauge
located near site SSP. Seasonal geometric average of flow is shown in Table 3-9 and the
monthly mean for rainfall is shown in Table 3-10. Highest seasonal flow was observed at
spring, while the lowest occurred in fall. Highest monthly rainfall occurred in July of
2005 in single month. However the highest period of rainfall occurred between a three

month period occurred between November 2005 and January 2006.

88

Table 3-8. Geometric mean of the physical water parameters per site over the course of

the four seasons

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Temperature (NTU)
m
NBP
Spring 8.61 5.15 3.84
Summer 8.55 15.20 2.96
Fall 8.50 20.72 3.32
Winter 8.56 1.55 2.26
RM
Spring 8.43 0.90 9.11
Summer 8.53 18.06 2.49
Fall 8.53 21.15 2.39
Winter 8.51 2.71 2.65
NS
Spring 8.53 3.34 6.21
Summer 8.55 13.86 6.60
Fall 8.52 20.50 4.98
Vlfinter 8.49 6.30 6.22
RSP
Spring 8.33 10.00 9.56
Summer 8.52 20.33 7.28
Fall 8.60 22.75 9.98
Winter 8.19 -0. 90 5.33
DC
Spring 8.24 6.24 15.34
Summer 8.31 20.45 10.92
Fall 8.22 19.35 6.32
Winter 8.27 1.14 17.69
GRP
Spring 8.22 4.62 9.00
Summer 8.49 20.16 6.57
Fall 8.41 20.07 5.96
Winter 8.24 2.30 7.61
JP
Spring 8.27 10.20 10.46
Summer 8.41 19.84 5.91
Fall 8.51 19.70 5.72
Winter 8.29 0.14 7.27
SSP
Spring 8.33 9.24 11.38
Summer 8.42 21.12 7.48
Fall 8.56 16.87 9.54
Winter 8.34 0.01 6.11

 

 

 

 

 

89

 

Table 3-9. Geometric average of seasonal flow

 

 

 

 

 

 

 

 

Season Flow
(cu ft/Q
Spring 5704.833
Summer 2971.293
Fall 1408.345
Winter 3868.762

 

Table 3-10. Average monthly rainfall during the months of the study

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Month Rainfall
(in.)
2005 April 0
2005 May 0.1
2005 June 0
2005 July 0.61
2005 August 0
2005 September 0
2005 October 0
2005 November 0.240
2005 December 0.035
2006 January 0.357
2006 February 0
2006 March 0
2006 April 0.149
2006 May 0.088
2006 June 0.025
2006 July 0.005
2006 August 0

 

Note: that n=37 for number of rainfall dates used

90

Seasonal means of indicator species in surface water and sediment are displayed

in Table 3-11. Higher colony or plaque counts occurred usually in the winter season for

water samples and in spring and summer for sediment samples.

Table 3-11. Mean concentration of fecal indicator species over time in water samples
and sediment samples

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Mean water # water Mean # sediment
CFUI100 sample sediment sample
mL CF UI1 00 9
W)
Fecal
coliform

Spring 36.47 54 615.46 47

Summer 66.02 62 2374.65 61

Fall 74.32 28 295.80 27

Winter 79.73 14 217.22 10

E. coli

SprinL 17.17 55 220.75 47

Summer 26.51 63 1152.13 63

Fall 64.54 28 277.91 27

Winter 55.48 14 71.40 10

Enterococci

SprinL 13.16 55 479.62 47

Summer 18.13 63 670.35 61

Fall 32.73 28 268.72 27

Winter 24.84 14 263.57 10

C.
perfringens

Spring 18.50 55 785.60 46

Summer 10.37 63 501.42 61

Fall 12.80 28 165.31 27

Winter 17.14 14 246.72 10

Coliphage

Spring 2.45 55 1.48 45

Summer 1.98 64 1.14 63

Fall 4.18 28 1.20 28

Winter 15.03 14 1.00 11

 

 

 

 

 

 

91

 

3.2.1 Surface water

Fecal coliforms

There were no significant differences in fecal coliform concentrations throughout
the year in surface water (p>0.05). A gradual increase in concentrations was observed
and peaked during the winter season. Figure 3-6 shows the concentration of fecal

coliforms over the four seasons.

 

 

 

Fecal coliforms in surface water (CFUI 100
mL) logscale

 

Spring Summer Fall Winter

Figure 3-6. Seasonal trends of fecal coliforms in surface water.
@301;

No significant differences were observed between spring and summer among E.
coli concentrations. Fall (mean 64.53 CFU/100) and winter (mean 55.48 CF U/ 100 mL)
showed significantly higher concentrations than spring (mean 17.17 CFU/ 100 mL). Fall

had significantly higher concentrations of E. coli than summer (mean 26. Winter was

92

only significantly higher than spring. Figure 3-7 shows the gradual increase of E. coli as

the year progresses.

   

A 4 1, ..1m 7 , 'V _-7 —7—v———— —
a i
o 3.5— - 1 , .
2 .
\ 31 ‘
D

b

3 g l
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s 2 ‘
g 1.57 i
3

.. ._ i
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._ i
3 0.54 ‘
O

“i o

 

 

 

Spring Summer Fall Winter

Figure 3-7. Seasonal trends of E. coli in surface water.

Enterococci
No significant differences were observed among seasons for Enterococci
concentrations in surface water (p>0.05). Figure 3-8 illustrates how Enterococci

concentrations peaked during both the summer and winter months.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3

E 4

a wee--__-_-e—~______ .
D

‘3' 3——77 44A*v*—*——————e
L

%0254— ______2___1__2_2-2___._22
33

e3 2., 4 i, 7_71.n, (A ’*—i——
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w

C

I 1-__,T__ - “A ~
3 l.

g 0.5—»— _ ———. —
é o . , legs
m Spring Summer Fall Winter

Figure 3-8: Seasonal trends of Enterococci in surface water.
C. perfiingens
Significance was found among the means of the different seasons
(p<0.05). Spring was found to have significantly higher concentrations of C.
perfringens in surface water compared to summer, but not fall and winter.
Concentrations gradually decrease from spring to summer than fall before slightly

increasing in winter. Peaks in both spring and winter are shown in Figure 3-9.

94

A

 

(a)
01
l
l
l
l
i
l
i
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l
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2.5 - 1 , 1 , 7 7.77717. #7 W 77,117 A777~~

 

 

 

 

C. perfringens in surface water(CFUl 100 mL)
logscale
N
i
i
i
i
l
l
l
i
i
i
l
i
l
i
l
i
l
i
i
i
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1

Spring Summer Fall Winter

Figure 3-9: Seasonal trends of C. perfiingens in surface water.

Coliphage

Significance was found among surface water in surface water for coliphage
(p<0.05). Winter showed significantly higher concentrations of coliphage compared to
all seasons. Concentrations peaked in winter and steadily decreased until late summer.

Figure 3-10 shows the seasonal trend of coliphage over the year.

95

 

 

0 “ ‘r fir J. r

Spring Summer Fall Winter

Coliphage in surface water (PFU I 100 mL)
logscale

 

 

 

Figure 3-10: Seasonal trends of Coliphage in surface water.

3.2.2 Sediment

No significance was found amongst seasons in any of the indicator species in
sediment samples (p>0.09). General trends for fecal coliform, E. coli and Enterooccci
include a gradual increase in indicator species, peaking in fall. However, a decline is
observed in winter. Spring was the peak season for C. perfringens in sediment, while

winter was the peak season for coliphage. Seasonal trends are displayed in figure 3-11.

96

 

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01

 

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ALLA 12;; .

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—* 01 N 01 03 U" A
i 1 r i i 1 Arm

EM?

 

a
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1
1
.i
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.05 _ FCsed EC sed .EN sed

 

 

 

 

Fecal indicators in sediment (CFU or PFU l 100
g dw) logscale

 

 

Figure. 3-11: Seasonal trends in fecal indicators in sediment in fecal coliforms, E. coli,
Enterococci, C. perfringens and coliphage.

3.3 Relationship between surface water and sediment

A regression analysis was performed on surface water and corresponding
sediment samples for fecal coliforms, E. coli, Enterococci, C. perfiingens and Coliphage
virus. The R2 values were 0.444 (fecal coliform), 0.391 (E. coli), 0.331 (Enterococci),
0.441 (Clostridium) and 0.128 (Coliphage). Correlation graphs for each indicator species
are displayed in Figure 3-12. The strongest correlation was found for C. perfringens and
fecal coliforms when examining sediment and water. Regression analyses was also
performed on river sediment and river water samples for each indicator according to
seasonality. The highest R2 value between water and sediment was 0.625 for
C. perfringens which occurred in summer followed by R2=0.38 for fecal coliform in

winter (p<0.05). These results are shown in Table 3-12.

97

In order to test the significance of upstream sediment on downstream surface
water, sediment for each indicator species from the immediate upstream site was
regressed with the water sample of the site immediately downstream. Sediment from
SSP was matched with surface water from JP, JP sediment was matched with GRP
surface water etc... For all indicators, R2 <O.21. When RSP sediment was compared to
beach water quality, the highest correlation occurred with NS, compared to RM and NBP.
For RSP sediment analyzed with NS surface water, the R2 for fecal coliform and E. coli
was found to be 0.706 and 0.675 with a p <0.002. For Enterococci, C. perfiingens and
coliphage, no significance was found (p>0.05) between RSP sediment and NS surface
water. No correlation was found between RSP sediment and the beaches to the right and

left of the river mouth (NS) and p>0.10.

98

 

6.00-

 

R2=O.444

 

 

 

 

 

-§ 5.00—
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in
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0.00 1.00 2.00 3.00 4.00 5.00 6.00
Fecal Coliform in sediernnt (Ioascalel
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b)

Figure 3-12. Correlation graphs of indictor species in surface water and sediment for a)

E.coll In sediment (logscale)

fecal coliforms, b) E. coli, 0) Enterococci, d) Clostridium and e) coliphage

99

 

 

 

 

 

 

 

 

 

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Enterococci in sediment (logscale)
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Clostridium in sediment (logscale)

Figure 3-12 cont’d.

100

 

 

 

 

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Coliphage In sediment (logscale)

Figure 3-12 cont’d

101

Table 3-12. Regression values between water and sediment concentrations for each
indicator species broken down by seasons.

 

 

 

 

 

 

Fecal E. coli Enterococci C. Coliphage
coliforms perfringens
Sprig .352(13)* .228(13) .036(13) .062(13) .056(12)
Summer .310(30)* .25 5(32)* .O28(30) .625(30)* .008(3 1)
Fall .066 (24) .056(25) .016 (25) .136 (26) .147(26)*
Winter .380(13)* .000(12) .005(13) .053(13) N.A

 

Note: Values in brackets represent number of samples, * represents p value <0.05

Regression analysis was performed on each indicator in relationship to the other
four indicators in surface water. Similar analysis was also performed on indicators in
sediment. Highest regression in water was found between fecal coliforms and E. coli
(R2=O.647) followed by Enterococci and E. coli (R2=0.617). The same trend was found
in sediment: fecal coliforms and E. coli (R2=O.597) followed by Enterococci and E. coli
(R2=0.551). Results are shown in Table 3-13 for R2 in water and in Table 3-13 for
sediment.

Table 3-13. Regression of each indicator species in relation to other fecal indicator
species surface water (values represent R2).

 

 

 

 

 

 

 

Fecal coliforms E. coli Enterococci C. perfringens Coliphage
Fecal coliforms x 0.647 0.488 0.385 0.083
E. coli 0.647 x 0.617 0.282 0.165
Enterococci 0.488 0.617 x 0.243 0. l 78
C. perfringens 0.385 0.282 0.243 x 0.044
Colipflrge 0.083 0.165 0.178 0.044 X

 

Table 3-14. Regression of each indicator species in relation to other fecal indicator
3 ecies in sediment (values represent R2).

 

 

 

 

 

 

 

Fecal coliforms E. coli Enterococci C. perfringens Coliphage
Fecal coliforms x 0.597 0.502 0.391 0.034
E. coli 0.597 x 0.551 0.400 0.039
Enterococci 0.502 0.55] x 0.448 0.022
C. perfringens 0.391 0.400 0.448 x 0.009
Coliphage 0.034 0.039 0.022 0.009 x

 

 

102

' .LL

 

 

 

 

3-4 Combined Sewer Overflow samples

Two CSO samples were examined for fecal indicators. The first event occurred
on February 16‘“, 2006. Total combined CSO discharge was 1.457 million gallons and
occurred between 2:40pm and 7:48pm. Discharge occurred due to rain and snowmelt,
with a total precipitation amount of 1.67 inches occurring between 11:45am and 7:02pm.
The duration of the overflow sampled (Site A) was 5 hours and 8 minutes where 1.443

million gallons of raw sewage was discharged into a creek leading to the Grand River.

A CSO discharge pipe is located at the intersection of Ionia and Stevens (Grand
Rapids) where it leaves the waste water treatment plant and at this point the sample is on
route to being released into the environment (at this point the pipe is underground in the
city). This point is called Site A (Ionia & Stevens). Low concentrations of fecal
indicators were found at this point. Site B is the point where the C80 effluent (mixture
of dilute raw sewage and storm water) is emptied into the Grand River, the pipe can be
seen from the banks of the Grand River. However at the actual discharge into the Grand
River [Site B - Goodrich outfall (located on bank of Grand River)] high levels of the fecal
indicators were found. Site B is 1.2 miles downstream from SSP (the eastern most site
for the study). Site C (Freeman Drive) was approximately 1 mile downstream from site
B and 3 miles upstream from study site JP. Table 3-15 shows the concentration of
indicators found in the surface water and Table 3-16 shows concentrations in sediment.
No sediment sample was obtained from the sewer sample at site A. Similar trends were
found in sediment as was found for surface water. The outfall showed higher

concentrations of fecal coliforms, E. coli and Enterococci. However, C. perfringens was

103

found in higher concentrations downstream at site C compared to site B. Water samples
had bacterial concentrations ranging between <1 to 5.75x104 CFU/ 100 mL and coliphage
ranged between <6.7 to 326.67 PFU/ 100 mL. Sediment samples had bacterial
concentrations ranging between 184 to 5.69x105 CFU/ 100 mL. Coliphage was not

detected in the sediment samples.

Table 3-15. Concentration of fecal indicator bacteria and virus in surface water as CFU
or PFU/ 100 mL after February 16‘“, cso.

 

Site Fecal coliforms E. coli Enterococci C. perfringens Coliphage Turbidity

 

 

 

 

(ntu)
A 3 <1 6.8 <1 <6] 44
B 5,75x104 22950 4970 1600 326.67 24
C 1975 1335 1040 666.67 <67 17

 

Table 3—16. Concentration of fecal indicator bacteria and virus in sediment as CF U or
PFU/ 100 g dw after February 16th cso

 

 

 

 

 

 

Site Fecal coliforms E. coli Enterococci C. perfriggens Coliphage_
A No sample No sample N0 sample No sample No sample
B 5.70x105 1.39 x105 36308.05 2.21 x105 <14.33
C 3.51 x105 184.36 737.46 4.71 x105 <23.89

 

The second CSO overflow occurred between July 17thth and July 18‘h 2006. Total
combined volume of the C80 for the city of Grand Rapids that day was 25.331 million
gallons starting at 10:31pm until 7:49am July 18‘“. Total precipitation amount was 2.91
inches of rain, rainfall started 10:12pm July 17th and ended 2:10am July 18‘“. The
duration of the overflow where samples were collected (Site A) was 2 hours and 17
minutes starting at 10:42pm July 17‘“, 1.52 million gallons of raw sewage was
discharged. The results of discharge at Site A are displayed in Table 3-17 (surface water)

and Table 3-18 (sediment). No sediment sample was obtained from the sewer sample at

104

 

site A. Similar trends were found in sediment as was found for surface water. Water
samples had bacterial concentrations ranging between 583.33 to 4.55 x105 CFU/ 100 mL
and coliphage ranged between 300 to 2160 PFU/ 100 mL. Sediment samples had
bacterial concentrations ranging between 2490793 to 828473658 CFU/ 100 mL.

Coliphage ranged between <10 to 16.23 PFU/ 100 mL in sediment samples.

Table 3-17. Concentration of fecal indicator bacteria and virus in surface water as CFU
or PFU/ 100 mL from the July 18‘h cso.

 

Site Fecal coliforms E. coli Enterococci C. perfringens Coliphage Turbidity

 

 

(am)
A 2.72 x105 33200 10140 5950 2160 35
B 4.55 x105 12210 17220 583.33 300 330
c 3.30 x105 24235 28680 822.73 460 31

 

 

 

Table 3-18. Concentration of fecal indicator bacteria and virus in sediment as CFU or
PFU/ 100 g dw from July 18‘h cso.

 

 

 

 

Site Fecal coliforms E. coli Enterococci C. perfiingens Coliphage
A No sample No sample N0 sample No sample No sample
B 8.29 x106 2.49 x105 2.14 x106 3.11 x11? <10
c 3.09 x10’ 7.88 x105 1.51x x105 6.87 x105 16.23

 

 

 

Two surface water samples were taken at the Goodrich outfall (Site B) on non-
CSO discharge days. These results are shown in Table 3-19. There is a 100 to 1000 fold
decrease in fecal indicator bacteria from the first CSO discharge and a sample taken 39

days later.

105

 

Table 3-19. Concentrations of fecal indicator bacteria and virus at Site B (Goodrich
overflow point in surface water).

 

 

 

 

 

 

Date Fecal E. Enterococci C. Coliphage Turbidity
coliforms coli Jerfringens (ntu)
2I1 6I2006 57500 22950 4970 1600 326.67 24
3/28/2006 122.7 52 15 76.2 <10 15.8
5/08/2006 19.45 76.1 <10 4.6
7“ 8/2006 4. 55 x105 12210 17220 583.33 300 330

 

Note that CSO events occurred on 2/16/2006 and 7/18/2006 and middle two days were
when no rainfall occurred previously.

3.5 Site Rankings

The geometric average of all fecal indicators at each site was determined, and on that
basis, each site was ranked in terms of which site had the highest levels of fecal indicator
relative to each other. Each site was given a rank between one and eight. The rankings
were summed up and the site with the lowest rank (being 1) classified as the most
contaminated site. This was performed for both surface water (Table 3-20) and sediment
(Table 3-21). For surface water the SSP site was found to be the most contaminated in
surface water, while GRP had the highest level of fecal indicator bacteria in the sediment.
The beaches and RSP maintained the same rankings and were consistently the least

contaminated for both surface water and sediment.

106

 

Table 3-20. Relative ranking of sites for highest to lowest amount of contamination in
surface water.

 

 

 

 

 

 

 

 

 

 

Site Fecal E. coli Enterococci C. Coliphage Summed Overall
coliforms perfringens Score Rank
NBP(L) 8 7 8 8 7 38 7
NS(L) 6 8 6 6 6 30 5
RM(L) 7 8 7 7 8 37 6
RSP(M) 5 5 5 3 4 22 4
DC(M) 4 3 3 5 1 16 3
GRP(M 2 4 2 1 2 l 1 l
JP(U) 3 1 4 2 5 15 2
SSP(U) 1 2 1 4 3 1 1 1

 

 

 

 

 

 

 

 

Note: L (Lower reach), M (Middle reach), and U (Upper reach) Site with highest
geometric mean given a value of one and site with lowest amount given an eight. Site
given a 1 indicates it is the most contaminated.

Table 3-21. Relative ranking of sites for highest to lowest amount of contamination in

 

 

 

 

 

 

 

 

 

 

sediment.
Site Fecal E. coli Enterococci C. Coliphage Summed Overall
coliforms perfringens Score Rank
NBIflJ) 8 8 8 8 7 39 7
NS(L) 7 6 7 6 4 30 5
RMQ 6 7 6 7 7 33 6
RSP(M) 5 5 3 4 5 23 4
DC(M) 3 2 1 5 3 14 2
GRP(M) 4 4 2 1 1 12 1
J P(U) 2 3 5 3 2 l 5 3
SSP(U) 1 1 4 2 7 15 3

 

 

 

 

 

 

 

 

Note: L (Lower reach), M (Middle reach), and U (Upper reach) Site with highest
concentration of indicators given a value of one and site with lowest amount given an
eight. Site given a 1 indicates it is the most contaminated.

3-6 Indictor Violations

Throughout the study, single samples which exceeded various criteria and

standards were noted. Most violations occurred in the upper and middle reaches of the

107

 

 

 

study sites and occurred in the Grand River. Results are displayed in Table 3-22.
Because Michigan currently does not have a standard for C. perfiingens, results were
compared to Hawaii’s freshwater criteria of 50 CFU/ 100 mL. For E. coli and

Enterococci criteria and standards, see Table 1-2.

There were more US EPA violations when using the Enterococci than E. coli, 38
versus 13 with only 12 if using the C. perfringens. The middle reaches of the river were
violation 27 times versus 19 in the upper reaches if considering the EPA criteria. The
higher contamination risk is also reflected in the rankings. See the above table (Table 3-

20 and 3-21).

Table 3-22. Number of indicator violations in the upper, middle and lower reaches of the
Grand River and Lake Michigan study sites

 

 

 

 

E. coli Enterococci C. perfringens
US EPA 13/157 38/157 NA
Criteria [5 upper, 6 middle [14 upper,2l middle,
and 2 lower] and 3 lower]
Michigan 7/157 NA NA
standard [2 upper, 4 middle
and 1 lower]
Hawaii fresh NA NA 12/158
water criteria [6 upper, 6 middle
and 0 lower]

 

 

 

 

 

Note: NA means not applicable. N=157 samples collected. For EPA and Michigan
standards see Table 1-2).

108

4.0 Discussion

Surface water quality has always been a concem for both recreational users and
beach managers in the state of Michigan due to the long coastline along the Great Lakes.
Traditionally, only surface water has been measured for fecal indicator organisms such as
fecal coliforms and E. coli which are used in Michigan for measuring safety. Studies
undertaken by EPA however, evaluated a number of indicators and found that
Enterococci had a higher correlation with swimming associated gastroenteritis rates at
marine and fresh water bathing beaches. Enterococci had a correlation coefficient with
regards to recreational sickness of 0.75 followed by E. coli (0.52) and Klebsiella (0.32),
Einterobacter / Citrobacter (0.26), total coliform (0.19), C. perfringens (0.19), P.
aeruginosa (0.19), and fecal coliforms (-0.0l) (EPA, 1986). Many states including

Michigan, are not requiring the monitoring of recreational water for Enterococci.

This study examined the Grand River and beaches along Lake Michigan
influenced by the Grand River watershed using routine and alternative indicators. In
addition to E. coli and fecal coliforms (which may show evidence of re-growth under
warmer conditions) and Enterococci coliphage and C. perfiingens were also used as a
measure of water quality. By using a variety of indicators species, on multiple occasions
in this study, Enterococci were found in higher concentrations than E. coli in surface
water. This represents a potential health risk to people who use the Grand River as a
place for water recreation. Based on the results of this study, a broad spectrum of
indicators should be used in Michigan, and water quality should not just be limited to

traditional indicators such as fecal coliforms and E. coli.

109

Using multiple types of indicators, several studies have shown how surface run-
off, human sewage, animal waste and grazing pastures impact surface water quality
(Jiang et. al., 2001; Mallin, 2000; Burkholder et. al., 1997; Fischer and Endale, 1999;
Gary et. al., 1983). Limited research has also shown that sediment is a source of fecal
indicator bacteria and once bound to the sediment particles, can become re-suspended
into the water column through sediment disturbance by wave action and rain events (An
et. al., 2002; Whitman and Nevers, 2003; Davies et. al., 1995; Shiaris et. al., 1987;
Pettibone et. al. , 1996). However, not much is known about the role that sediment plays
in water quality degradation. One of the goals of this study was characterization of the
Grand River in Michigan in regards to microbial pollution in sediments as the source of
problems in the water column. This study suggests that sediments should be more

routinely examined to better characterize pollution loading to surface waters

It is not surprising that as this study examined the spatial differences in fecal
indicator concentrations along the Grand River and Lake Michigan in both parks and
beaches using traditional and alternative indicators (fecal coliforms, E. coli, Enterococci,
C. perfringens and Coliphage), the River showed higher concentrations of fecal indicator
species, specifically in the sediment samples than beach sites in Lake Michigan.

The upper reach of the river is near the city of Grand Rapids, MI which has a population
of 197,800 according to the US Census of 2000. Grand Rapids also has 77,960 total
occupied housing units that are connected to the requiring sewage disposal system.

During periods of high rain, wastewater treatment plants may not be able to handle the

110

increased volume of water, thereby resulting in numerous CSO events. During this study,
Grand Rapids experienced 42 CSO events (24 of which either directly or indirectly
discharged into the Grand River), and 31 S80 events as shown in (Table 4-1). For
seasonal breakdown of fecal indicator species in water and sediment samples over
seasons see Table 3-11). Volumes of raw diluted sewage were discharged, specifically
on July 17th, 2006 where over 23 million gallons of raw sewage were discharged directly
into the Grand River over a 9 hour and 28 minute time period and 2.91 inches of

precipitation.

Samples from CSO events discharging into the Grand River included both
partially treated sewage and diluted raw sewage. These inputs contained high
concentrations of fecal bacterial indicators (2.3x104 to 4.55x105 CFU/100 mL).
Coliphage were seen as good indicators of the recent impact as numbers were low
generally in the river, but in the discharges to the river, they ranged between 327-460
PFU/ 100 mL.. It was difficult to sample and thus compare CSO events relative to one
another as the total volume of discharge were different, and the amount of rainfall
triggering the CS0 was also different. Often these CSOs occurred in the Grand River
and were reported and there was not sufficient time to sample. However, the sampling in
this study showed that very little difference was found throughout the river and this was
consistent over time. It is likely that the Grand River and beaches are similar to the
national data showing that within the US, beach closures associated with CS0 and S80
are prevalent. In 2003, out of 3214 closures, 272 closures were specifically due to CSO

and S80 events.

111

Table 4-1. Average monthly CSO sewage discharge directly entering the Grand
River, [no intermediary creek or river]. (MDEQ, 2006).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Month of Discharge Average amount of sewage
(in million gallons)
May 2005 0.027
June 2005 0.431
July 2005 0
August 2005 0.013
September 2005 0.021
October 2005 0
November 2005 0.031
December 2005 0
January 2006 0.001
February 2006 0.014
March 2006 0.006
April 2006 0
May 2006 0.157
June 2006 0.0625
July 2006 11.92
August2006 0. 1 19

 

One of the single CSO samples tested showed lower concentrations of bacteria
than expected at one of the sewer/manhole. This may have been due to large volumes of
water from rain being diverted through the sewer system from impervious surface runoff
at that location at that time etc. However samples at the outfall showed much higher
concentrations indicating that water quality was compromised at discharge sites. While
CSO events may contribute to water impairment, Murray et. al.. (2001) found that there
was no correlation between CSO sites and water quality impairment when looking at
fecal coliform and fecal streptococci bacteria. They cited that data depicted “a strong
influence of upstream water and rural runoff “on water quality of the Rouge River located

in south-eastem Michigan. This study of the Grand River, found that while CSOs

112

contribute to short term peaks of water quality impairments, over time those numbers
decrease as shown in Table 3-18. However, these events are also depositing sediment
and debris which settles to the bottom with microbes attached, and are seeding the
sediments. Even though CSO events do not occur on a day to day basis, it still represents

a chronic problem that influences water quality at the beach.

According to the city of Grand Rapids waste water treatment fact sheet (2007),
Grand Rapids waste water collection system covers a geographical area of approximately
201.6 square miles, and of that, 5.37 miles is a combined sewer system. Compared to the
late 1960’s, where 12.6 billion gallons of overflow was produced, in 2006, the total of
CS0 water released was 0.0323 billion gallons. Long term water quality and sediment
monitoring are not available, and improvements in water quality can not be demonstrated.
While the overall volume has decreased, there remains an impact from untreated sewage
entering Michigan natural water bodies. In the state of Michigan in 2006, 19.8 billion
gallons of combined sewage was released by 31 communities, of which Grand Rapids
was responsible for 50.276 million gallons (0.25%) which ended up in the Grand River.
The average concentration of E. coli found in the two CSO samples (February 16 and
July18th, 2006) discharging in the river in this study was 17,580 CF U/ 100 mL. If Grand
Rapids was responsible for 50.276 million gallons, the number of E. coli entering the
Grand River would be approximately 3.33x10l3 CFU / year from CSOs.
The city of Grand Rapids is however, required to eliminate combined sewer overflows by
December 315‘, 2019, until then, CSOs will be an important input of microbial pollution

to the Grand River.

113

There are other sources of fecal inputs to the river. In the upper and middle
reaches of the Grand River many farms and pastures dominate the landscape. Many
farms use manure as a fertilizer for vegetable crops. If manure is not dried long enough,
some fecal indicators and pathogens may remain viable and attach onto manure particles.
In the event of heavy precipitation, the water can wash surface soil and manure into the
Grand River and creeks which feed into the Grand River. However, this study did not
demonstrate any differences in water or sediment quality along the 77.3 km (48 mile)

stretch of the river related to land use.

The second objective of this study was to examine the impact of seasonal changes
on the concentration of fecal indicators. Not all indicators showed seasonal differences in
water (only fecal coliforms and Enterococci did with slightly lower numbers in water)
and no indicators showed seasonal differences in sediment. Thus the numbers in
sediment seemed to reach an equilibrium. Many seasonal studies of recreational waters
are done in warmer areas where recreation occurs year round. Shibata et. al.. (2004)
looked at seasonal differences of fecal indicators (Enterococci, E. coli, fecal coliform,
total coliform and C. perfiingens) between wet and dry seasons in Florida. Only total
coliforms showed a seasonal difference, the other indicators did not show significant
difference between wet and dry season, even though the physical parameters (rainfall,

temperature, salinity and pH) differed greatly.

In mid-Michigan, the most obvious climatic change by season is temperature. In

this study the following was observed with regards to seasonality and water / sediment

114

quality. It was reported by National Climatic Data Center (2006b) that between
September and November 2005, and between December 2005 to February 2006 the
conditions in Michigan was more wet (by 15-30%) in both of these time periods
compared to the 1971 -2000 average (shown in Appendix E). Soil moisture is important
in influencing pathogen survival, with survival being more likely under moist conditions
(Crane and Moore, 1986. and Entry et. al. ., 2000). When E. coli was placed in dry soil
for 14 days and then moistened, re-growth was shown (Chandler and Craven, 1980).
Considering that the climate during the study period was wetter than average, a potential
for E. coli re-growth may be possible after periods of desiccation even in the soils that
may have run off into the Grand river. Sediment moisture was found to facilitate
pathogen survival (Byappanahalli et. al., 2003) with higher concentrations of E. coli
being found with higher moisture. Fecal coliforms, Enterococci and E. coli showed a
trend of peaking in winter with the lowest temperatures and the lowest concentrations
occurring in spring (during thawing) before starting to increase in summer and fall. The
highest volumes of CSOs were in the summer then spring followed by fall and finally
winter. These lower concentrations in spring may indicate a washing effect due to the

extra volume coming in during the spring melt.

In Michigan, some forms of recreation do occur in the fall and winter, and
include boating and fishing, both of which can result in direct contact with water. While
most CSO events occurred in the summer and spring, winter temperatures stabilized the
system and the fecal indicators over winter easily. Due to the constant freeze-thaw cycle,

while fresh snowfall and rain may make an immediate impact to the water system,

115

melting snow can take time to reach the mouth of the river from various elevated areas in

the water shed.

The only indicator which showed a dramatic change with temperature was the
coliphage virus. A much greater die-off was observed in the summer and fall months.
Higher concentrations of coliphage occurred when water temperatures ranged between
-O.9°C and 63°C. However, coliphage were rarely found to survive in sediment samples.
This indicates that coliphage viruses are very sensitive to temperature changes, and
would be a good indicator used for determining whether or not recent contamination has

taken place in the Grand River.

Currently, some farms in Michigan apply manure on top of snow during the
winter. However, it is not known if this was the case in the Grand River watershed. One
reason for increased indicators in the water column may be due to winter application of
manure onto fields during the winter months. Because Michigan winters are variable,
manure applied on top of snow may enter the water collunn during periods of snow melt
as there is constant freeze and thaw weather events occurring in Michigan and other
states and provinces in the mid-west USA and in Canada. Currently no law prevents
winter manure applications for smaller animal operations. In the Michigan Department
of Agriculture does mention that winter manure application should be avoided, but if
“necessary” solid waste can only be applied to slopes 6% or less and liquid manure

applied to slopes 3% or less. Stronger language is needed to minimize this potential

116

source of pathogens and / or clear guidelines as to what constitutes “necessary” needs to

be established.

Due to a possible dilution affect and length of transportation time, numbers of
coliphage virus may have been too low to be used as a consistent indicator of pollution at
the beaches of Lake Michigan. In a survey of literature by John and Rose (2005), it was
observed that coliphage viruses had a higher inactivation rate when temperatures
increased, especially between 1 1-3 0°C where inactivation rates ranged between 0.03-2.5
log/day compared to 0-0.l log/day at temperatures between 0-10°C. This trend is
reflected in this study, as higher concentration of coliphage occurred during cooler
periods. The advantage of using coliphage in the Grand River is that it is less likely to
re-grow in the environment compared to indicators such as E. coli and Enterococci. Thus
it is recommended that coliphage be used in the river, but further studies would be needed

to demonstrate this indicator usefulness at the beaches in the lake.

Trends for C. perfiingens were different in surface water compared to fecal
coliform, E. coli, Enterococci and coliphage. A peak concentration was found in spring
related to flow or rain. As mentioned previously, C. perfringens does not re-grow in the
enviromnent, which is why it is used as an indicator in warmer climates. Because it is a
spore forming bacteria, it can represent older pollution. Our results found that
C. perfringens significantly decreased from spring to summer, and stayed similar

between summer and fall as flows and CSOs increased.

117

 

Sediment

Concentrations in sediments of the Grand River appear to be stable throughout
the year due to the protective aspects of the sediment; however the sediments which were
sand in nature at the beach sites had very low concentrations of bacteria which could
have been influenced by wave action suspending bacteria to water column than being
exposed to ultraviolet radiation from sunlight. Surface water was much less turbid at the
beaches compared to the park surface water, therefore less particles to deflect and absorb
ultraviolet rays in the shallow water - sand interface. Enhanced water clarity increases
light transmittance (Mcisaac, 1996) through surface water and this can be seen to occur
when there are zebra mussels. Lake Michigan has an abundance of zebra mussels,

including areas at the beach study sites.

In this study, sediments were found to be a reservoir and source for the fecal
bacteria throughout the year. Fecal coliforms and E. coli were less tightly bound to
sediments where as Enterococci and C. perfringens were more tightly bound to sediment
particles. This was highlighted when analyzing rainfall, it was observed that gram
negative bacteria, which have lipids in their cell walls had a higher negative correlation
between values in sediment and rainfall. It was found by Jamison et. al. ., (2005) that E.
coli re-suspension was limited to the rising limb of the storm hydrograph and only a finite
amount of E. coli was available for re-suspension during rain events._Concentrations in
the sediment bed were replenished afterwards, possibly due to fresh inputs from surface
runoff (Jamison et. al. ., 2005). Gerba and Bitton (1984) stated that rainfall “mobilizes

previously retained bacteria and viruses” and promotes transportation to water bodies.

118

Physical sediment properties were characterized and revealed that the river
samples had higher concentrations of Phosphorus (10-44 ppm) compared to beaches (2-4
ppm). In a study that looked at surface water and ground water from a natural areas, it
was found that when phosphorus was added, there was an increase in microbial grth
(Miettinen et. al. ., 1997). However, the addition of other nutrients such as nitrogen,
Potassium, Magnesium and Calcium did not significantly affect microbial growth. In
another study Carrillo et. al.. (1985) found that both fecal coliforms and E. coli were
found to be positively correlated (R= 0.668and 0.469) with phosphate concentrations in
the Mameyes River (Puerto Rico). Rivers studied in the UK were found to have the
highest soluble reactive phosphorus during low-flow conditions, with concentrations
diluted as the flow increases (J arvie et. al. ., 2006). The Grand River has many winding
turns with sections of high flow and sections of slower moving water. The highest
concentration of phosphorus found in sediment in this study occurred in the middle reach
of the study site where the river slows compared to the upper and lower reaches.
Unfortunately in this river, there is only one river gauge, better monitoring of flow will

be important to modeling water quality in this system.

This river also has the middle third dominated by lands used for agriculture and
housing projects which dump sewage into the river. This may be another reason that
microbial concentrations such as E. coli as well as phosphorous are high in the middle
reach. In a study which looked at sediments and seawater, it was found that E. coli

survived longer in the sediment which was attributed to having higher organic and

119

nutrient content then the surface water (Gerba and McLeod, 1976). High nutrient content
(phosphorus) and organic content in the sediment in parks (Table 3-4 and Table 3-5)
allow for good growing conditions and accumulation for bacteria. When sediment is

disturbed or re-suspended it can affect downstream water quality.

Electrostatic and hydrophobic forces are generally recognized as important in
bacterial adhesion (Salerno, Logan and Velegol, 2004, McNamara, Lemke and Leif,
1997)). Because the bacteria have a charge associated with them (+ or -), the charge may
also influence sediment to water interactions. Soil properties such as particle size, cation-
exchange capacity, and clay content (Gerba and Bitton, 1984) can also influence retention
of fecal indicator bacteria to sediment particles. The higher the clay content, the more
negative the charge on of the sediment particles. Even though many studies have been
done examining the physical characteristics of bacteria, “mechanisms governing the
adhesion of bacterial cells onto sediment grains are not fully understood” (Redman et.
al.., 2004). Rheinheimer (1985) concluded that most aquatic bacteria are gram-negative
while soil bacteria were predominantly gram-positive. Our results found that the gram
negative bacteria (E. coli) had higher concentrations in the water column and is most
likely to be re-suspended from sediments to the water column during rainfall events.
Also, gram positive bacteria concentrations are slightly higher in sediment samples in the

middle and upper reaches of the Grand River.

McNamara et. al.. (1997) found that 44% of hydrophobic bacteria and 17% of

hydrophilic bacteria were gram-positive bacteria (Enterococci and Clostridium). A

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difference in enzymatic activity was observed between the two types of bacteria
(McNamara et. al. ., 1997). However, studies have shown that when bacterial cells and
sediment granules with high quartz content both had negative charges, a rate of bacterial
deposition was observed (Redman et. al. ., 2006). This phenomenon may be due to the
secondary energy medium encountered by the bacteria as it approaches the quartz
particle. Hahn and Melia (2004) describe that the cell which is unable to overcome the
repulsion after the initial attraction may be bound to the particle. In the case of
coliphage, it was only found in 6 (upper and middle reaches of the river) of 148 sediment
samples and 54 of 161 surface water samples. Based on the results, it seems the coliphage
does not survive very long in sediment or encounters obstacles which prevent it from

reaching the sediment substrate

Sediment is a source of fecal pollution in the Grand River. Sediment cleanup
methods currently employed include dredging, capping and doing nothing. Dredging
requires removing the contaminated sediment to an offshore site for further remediation
or landfill. The main drawback is the initial re-suspension when the sediment is removed
(Thorma et. al., 1993). Grimes (1975) found fecal coliform concentrations to
significantly increase in the vicinity of dredging. When a small lake in Sweden was
dredged, bacterial concentrations were found within the top 50m of sediment and at the
same concentration as before dredging (Cronberg, Gelin and Larsson, 1975). However, it

was found that the water quality improved after 2km from the dredge site (Grimes, 1980).

121

Capping involves covering contaminated sediment with layers of additional
substrate materials such as gravel, rocks, and or synthetic materials. Generally capping
methods are used when contamination of sediments consists of nutrients such as
phosphorus and metals (Berge et. al., 2004; Kim et. al., 2007; Eek et. al., 2007). The
materials used can rocks, clean sediment, calcite (limestone), sand and gypsum granules
(O’Conner , 1984; Berg et. al., 2004; Park et. Al., 2007) depending on what the major
contamination in the sediment is. It was suggested that the capping layer be one meter
deep J (O’Conner, 1984) to prevent benthic organisms from burrowing and disturbing the
capping material. Clean sand was used to cover sediment with heavy concentrations of
sewage sludge in Hiroshima Bay and dredging was used remediate nutrients in Osaka
Bay (Kuroda and F ujita, 1982). Hiroshima Bay had decreased nutrients while Osaka Bay
remained unchanged (O’Conner, 1984). When sand material was compared with
cohesive silty material, both when exposed to severe storms, kept contamination from
the water, but the silt cap was severely eroded (O’Conner, 1984). The idea is to prevent
the contaminated sediment from being re-suspended into the water column by layering it
with other materials. This method can only be used if the source of pollution has been
determined and prevented from reoccurring, if the bottom of the water body or river can
support the additional amount of substrate. Initial issues with capping could involve re-
suspension of contaminants when placing the first substrate layer over the sediment bed.
Capping is not always 100% affective. Future issues regarding sediment capping could
arise if there are changes to the hydrology of the system, or there is redirected water flow
/ discharge to the capped area there is the potential for the added substrate to be disrupted

or washed thereby re-suspending the contaminants.

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The final alternatives are do nothing and simply monitor to see if the
contaminants will degrade or get diluted out. At this point, both dredging and capping
would not be an ideal solution as they are expensive and the deposition of microbial fecal
pollution is ongoing. Fresh sediment would be easily re-contaminated. For the Grand
River, efforts should be directed at minimizing inputs of pollution to the river and

minimizing contamination from C803 and agricultural run-off.

Beach sand can be dealt with using proper grooming techniques or sand
remediation. Grooming can occur using a mechanical groomer or hand raking the sand.
It was found that by using a mechanical grooming machine, E. coli counts were
significantly higher then that of hand raking and doing nothing (Kinzelman et. al., 2003).
Depth of sand grooming and sand moisture were found to be important (Kinzelman et.
al. ., 2004). Concentrations of E. coli in unleveled and deeper groomed sand was lower in
visibly moist sand but not in dry sand. However, grooming techniques were found to
reduce the number of poor water quality advisories due to dry weather effects by 30%
(Kinzelman et. al. , 2004). Grooming is a type of tilling method which can aerate and
remoisten sand. This process can provide bacteria with protection from heat desiccation
and UV (Kinzelman et. al., 2003). By raking the sand before recreation occurs and long
enough for the surface of the sand to be exposed to UV, pathogens can be eliminated.
Grooming methods should be designed to minimize standing water on beaches. Sand
remediation can occur by removing contaminated sand and replacing with clean sand.
Contaminated sand can be trucked to a landfill site or moved to a treatment facility. This
method can prove quite costly and may only be an expensive temporary solution. Sand

remediation is generally used for beaches with chronic sand contamination problems or

123

when large scale contamination occurs such as sewage and oil spills. All parks and
beaches in this study had birds and waterfowl within the vicinity. Beaches along Lake
Michigan have many gulls and subsequently gull feces in sand, beach sand grooming and

maintenance should be carefully examined and tested before proceeding.

Indicators such as E. coli and Enterococci, (particularly Enterococci) have proven
to be highly correlated with recreational illness compared to other indicators. This study
suggests that 10 to 80% of fecal bacteria are coming from the sediments. It has been
suggested that 1 g of sediment containing 104 MPN/ 100 g Enterococci is a similar
exposure “as ingesting 100 mL of water at the health limit” (Lee et. al.., 2006).
Sediments in the Grand River have high enough concentrations to pose risks to
recreational users who use the river for full bathing recreational activities. This study
supports only secondary uses of the Grand River. During high flow events with large
sediment loads emerging from the river swimming should be restricted and signs posted

indicating reasons for restricted full bathing.

Economic concerns for Grand River and Lake Michigan parks and Beaches

Optimal recreational opportunities are often based on factors such as aesthetics

(cloudiness, visibility, day length), physical climatic conditions (wind, air quality, ultra

violet radiation) and thermal climatic conditions (de Fereitas, 2003). For beach

recreational opportunities, such as Grand Haven, MI along Lake Michigan, communities

124

rely on the summer season for water recreation to bolster the economy. In summer,
daylight is longer, allowing for prolonged amounts of recreation to take place, warmer
water temperatures allow for increased amounts of time spent swimming, water and jet
skiing. In order for the full economic potential of recreational beaches and parks to be
realized, one must factor in water quality. Fecal coliform, E. coli, Enterococci, coliphage
and C lostridia can be used to address water safety and contamination. Yet the state of

Michigan uses only one indicator, E. coli.

In the event of beach closures due to high fecal bacteria indicators, there can be
severe economic repercussions to the community, and result in negative attitudes towards
beach managers for not “fixing” the problem. When social norm curves were generated
measuring acceptability with beach closures due to bacterial contamination, the threshold
of acceptability was exceeded after 7 days of closures (Smyth, Watzin and Manning,
2007). But not closing the beach may have severe health implications and the current
indicator system is not adequate to address this trade-off. Some beaches also are host to
multiple large scale sporting events, such as boating competitions and triathlons. In a
study performed by Van Asperen et. al. (1998), they found that among endurance
athletes, triathletes (those who biked, swam and ran) were twice as likely to develop
symptoms of gastroenteritis the week following exposure from fresh waters which met
European bathing standards compared to the non-swimming athletes (who ran, biked, and
than ran again). Thus also indicating that current water quality standards used are not
adequate to protect public health. Closures of beaches result in cancellation of large scale

events which economically benefit the community; it can also impact local businesses.

125

Businesses such as hotels, government revenue, cottage rentals, restaurants and small
business involved in selling or renting recreational equipment can lose large amounts of
money. Thus there is a tendency to protect the economic safety of the community as

compared to the public health safety.

Economic impact of swim closures were examined by Rabinovici et. al. (2004)
using existing water quality and visitor data from Lake Michigan taken from 1998 to
2001. The authors found that based on information from Indiana Dunes National
Lakeshore system, beach closures can cause an average economic loss of up to $35 000
per day (ranging between $1274 -$3 7,030) for those who want to swim. The authors feel
that an efficient standard would be set when the fecal indicator bacteria concentrations
where the gains from closing the swim area exceed the recreation value lost such as 423
E. coli cfu/100 mL and perhaps never. Dwight et. al., (2005) estimated gastrointestinal
illness (GI) burden for two beaches in southern California. The estimated that the
economic burden is approximately $36.58 per gastrointestinal illness, $76.76 per acute
respiratory disease, ear ailment was $37.86, and eye irritation $27.31. Values were
adjusted to 2001 dollar value. These two beaches were estimated to generate
approximately 36,778 GI plus 38,000 other illnesses per year. Based on the number of
expected illness, the public health burden was estimated to be $3.3 million per year for
these two beaches (Dwight et. al., 2005) but are likely to be conservative as number of
GI’s were derived from a risk model. Other studies found the cost per illness to range
between $218 to $2198 US according to 2001 dollars and adjusted for inflation (Scott et.

al., 2000; Frflhwirth et. al., 2001, Fleisher et. al. 1998).

126

Generally, closures are implemented 24 hours after a high fecal indicator bacteria
reading. The 24 hour lag is due to time needed in collecting, processing and to analyze
the samples. Tests such as IDEXX’s colilert and enterolert require at minimum 18 hours
of incubation before a reading can be taken. This is in essence a retrospective assessment
of the water quality. It in reality is telling beach managers today what they should have
been doing yesterday. Because there is a delay of usually 24 hours between sample taken
and closure of beaches, the actual fecal indicator levels may not be harmful, thereby
resulting in a needless closure, and loss of economic income. This type of unnecessary
closure occurred on 14 out of 118 days that were monitored (Rabinovichi et. al.. 2004).
This means roughly $490 000 was unnecessarily lost if you multiplied the average loss by
the 14 days when unnecessary closures were issued. This value could be higher,

considering days not included in the study were not factored in.

In 2005, two beaches in this study were found to exceed the 300 CFU/ 100 mL
Michigan standards for E. coli in a single sample surface water (Table 4-2). This shows
that beaches are susceptible to water impairments, and factors such as wind, rain and

river water quality may be factors worth investigating.

127

Table 4-2. State water quality exceedences at beaches along Lake Michigan at sites also
studied in this project (MDEQ, 2006).

 

Park Date E. coli (CFU/ 100 mL)

 

Grand Haven State Park 7/18/2005 311.66

(state designation for our
study site “North Shore”

 

 

 

 

 

Rosy Mound Recreational 6/21/2005 371.25
Area

Rosy Mound Recreational 7/18/2005 708.31
Area

 

and this highlights the need for further study into sediment role in the river and it’s
impact at the beach with regards to microbial pollution. Sediments are a reservoir of
microbial pollution and must be taken into account when examining water quality.
Currently, no standard method exists for analyzing fecal indicator bacteria in sediments
as exists for other pollutants. Further monitoring of sediments for fecal indicator bacteria
is imperative, without this data appropriate standards/ guidelines could not be established
in setting safety levels for monitoring. By combining sediment and surface water data,
predictive models can be established to help better predict water quality and reduce the
amount of unnecessary beach closures while at the same time, improving the

understanding the dynamics of the river watershed system.

128

 

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133

5.0 Summary

Hot spots have been identified along the Grand River near CSOs and sewage
discharge points as sites containing high concentrations of fecal indicators. These sites
predominate in the upper reaches of the river and at Deer Creek. It is likely that
sediments are a source of microbial pollution and can impact water quality given
optimum climatic conditions (for example E. coli). Sediment contamination should be
considered when making water quality decisions as re-suspension of sediment can be due

to heavy precipitation, runoff or river discharge causing suspension of those microbes.

When examining both surface water and sediment, higher concentrations were
found in the upper and middle reaches of the river compared to the lower reach indicating
a large dilution affect occurring in the river system. While the Grand River is likely
contributing to Lake Michigan beach quality, the concentration is diluted. Other sources
such as bird feces and tourist garbage must be also taken into account when identifying

sources of pollution.

In general, most indicators had highest concentrations in surface water during the
winter and spring seasons. However, fecal indicator bacteria in sediment showed no
statistical significance when analyzed for seasonality. Generally, declines in fecal
indicator concentrations were observed sediment during the winter season. This shows
that some species are able to survive the freeze thaw cycles found during Michigan
winter seasons and/or there are additional inputs to the river during the fall / winter

seasons.

134

Results were assessed for correlation between sediments and surface water for
fecal coliforms, E. coli, Enterococci, C. perfringens and coliphage. The R2 values for the
aforementioned ranged between 0.444 and 0.331 for the bacterial indicators. While
sediment quality was not directly related to the water column above it, it is a reservoir of
fecal contaminants downstream. For E. coli, both rainfall and water temperature showed
a significant relationship in both surface water and sediment. For rainfall, E. coli had a
positive relationship with rainfall and a negative correlation with sediment. This may
indicate loss of E. coli from the sediment to the water column during periods of increased

rainfall.

When making decisions regarding issuing beach closures and advisories, the
concentration of Enterococci spp. should be considered if it is shown to violate EPA
criteria more than E. coli. Because E. coli and Enterococci can re-grow in the
environment under warmer conditions, alternative microbial indicator species should be
tested for. One such indicator is the spore forming C. perfringens; it requires anaerobic
growth conditions and will persist in the environment. It is a good indication of past
pollution levels. Another indicator, coliphage, is very sensitive, and does not persist long
in the environment, therefore making it a good indicator of fresh pollution. Both C.
perfringens and coliphage virus do not to grow in the environment, and would prevent

over estimating extent of pollution.

135

5.1 Conclusions

1.

Upper and middle reaches of the study sites has significantly higher
concentrations of fecal indicator species

There are no seasonal differences in surface water for fecal coliforms and
Enterococci, but exist for E. coli, C. perfiingens and coliphage

No seasonal differences exist in sediment samples for any of the indicator species

On a per gram dry weight to mL volume, sediments have 2-3 logm higher
oncentrations of indicator species than surface water

Sediment samples are not related to surface water directly above

Riverside Park sediments correlated with North Shore surface water
concentrations for fecal coliforms and E. coli

136

5.2 Management Recommendations

1.

10.

11.

12.

13.

Implement a no body contact with surface water for atleast 24 hours after 1 inch
of rain or CSO event

Mandatory testing for Enterococci for beaches and bathing sites

. Build prediction models for different seasons

Separate raw sewage from surface water (CSO separation)

. Development criteria and standards for fecal indicators in sediment and beach

sand
Future work on examining re-suspension of indicator species

Mandate farms have vegetative cover on land before applying manure spreads on
farm land to minimize surface run-off into rivers and lakes

Store manure for atleast 6 months before spreading onto land.

Prohibit liquid or dry manure from being placed on snow or on snow covered
ground. Must be injected directly into ground during that time period.

Post advisories on beaches which have closed due to fecal indicator bacteria
exceedances posting date and by how much it exceeded state laws

Post signs for good beach etiquette (do not throw garbage on the beach,
encouraging defecation and urination in public beach waters, do not feed gulls)

Increase testing around parks and beaches with farms and combined animal
farming operations

Farms and CAFO’S be required to have an emergency plan in case of sewage spill
or discharge

137

Appendix A Important Journal article findings

Reference

Weiskel et. al. ,
1996

Burkholder et.
al,l997

Esham and
Sizemore 1998

J iang et. al.

2001

Farag et. al.,
200 l

Shiaris et. al. ,
1987

Ahn et. al.,
2005

Munawar et.
al. 2001

McLellan and
Salmore, 2003

Marsalek et.
al. , 1996

Irvine et. al.
(2005)

Microbe
& water

type
FC

(fresh)

FC
(fresh)

FC

(saline)

Coliphage

(fresh)

EC
(fresh)

FC
(saline)

FC
(saline)

FC, EC
(fresh)

EC
(fresh)

EC
(fresh)

FC
(fresh)

Year/season

1986-86

1995

Jan —Dec 1992

Feb-Mar 1999

Summers of
96&97

June 5, 1985
(sed)
Oct.15&17,
1984 (water)
Feb. 18-Mar 3,
2004

1991

June-
September
2001 .

May, June,
July September
2000

Finding

Low of 0491th9 FC/day in Aug. to
217x109 FC/ day in Dec. from
waterfowl

102-103 cfu/ 100 mL water
2 10“ cfu/ 100 mL slurry
sediment
cfu inc. 22-34°C
FC inverse r/w salinity

5.3 to 3332 PFU/litre of
freshwater

Cascade + for elk, deer, human,
avian, canine, rodent, and
human coliforms;
Gamett - pres
sediments 2 to 4 orders > water
column; Sediment 200 — 60, 000
cfu/ lOOmL slurry

concentrations exceeding CA
ocean bathing water standards
by up to 500% ; pollution
limited to <5 km from river
outlet
highest bacterial abundance in
Lake Erie; lowest concentration
Georgian Bay and Lake
Superior.

Offshore counts (10—150m from
shore) levels did not exceed 235
CFU/ 100 ml in more than 5%;
beach samples exceeded that
mark in 66% of the samples
St. Mary’s River 4-162 cfu /100
mL,

St. Clair River 62-5130 cfu / 100
mL
Detroit River 392-1929 cfu/ 100
mL
5-450 cfu/ 100 mL during rain;
concentrations peaked 1 to 24
hours after rain events at
concentrations of approx. 1000 —
54000 cfu/ 100

138

Water body

Buzzards Bay
(MA)

New River (NC)

Creeks (58
Carolina)

Creeks and rivers
beween malibou
and Mexican
border (CA)
Cascade Creek
Gamett Creek

Savin Hill Cove
(MA)

Santa Ana River
(CA)

Great Lakes Basin

Lake Michigan
(W1)

Great Lakes Basin
(Windser, Sarnia)

Buffalo River

Appendix B Land use maps

1992 Land use map of mouth of the Grand River

c
10
.9
.1:
.2
E
111
x
10
_l

 

B Open Water

[3 Low Intensity Residential -

DHighlntensity Residential 1'79““
l‘ ' III A ' "T r A 1' 2.80m

I: Quarries/Strip MinestGravel Pits

- TransitionalLand(Agricultural/Clearcut)

Deciduous Forest
Evergreen Forest
Mixed Forest

Pasture/Hay
l3 Crops (Corn. Soybean. Vegetables...)
- RecreationalGIass (Golf course. Parks, Airport grasses. Industrial)
[3 Woody W etlands
- Emergent Herbaceous W etlands

 

139

1992 Land use of the middle reach of Grand River study site

 

- Open Water
13 Low lntensity Residential l l
High Intenslty Resrdenlial
Com merelal/lndustrIaI/i ransportation 1 .79I'I‘II
Quamesistrip Minest’r‘ravel Pits
E Transitional Land (AgriculturaliClearcut‘l 2-88km
E Deciduous Forest
- Evergreen Forest
- Mixed Forest
a Pasture/Hay
Crops (C orn, Soybean, Vegetables ..)
E Recreatlonol Grass [Golf course, Parks, Airport grasses, Industrial)

Woody Wetlands
E m ergent H erbaceous Wetlands

 

140

1992 Land use of the upper reaches of Grand River study sites

-'.

l.-

 

“ Open Water |__—|
Low lnlensrty Resrdentral .

E ngh lnlensrtyResldenlial 1'79““

[:l Commercrai/lnduslrial/Transportation 2.88km

[:] Quarries/Strip MrnestGravel Pits

[j Transrtlonal Land (AgriculturallCIearcul)

C] Deciduous Forest

- Evergreen Forest

- Mixed Forest

m Pasture/Hay

E Crops (Corn, Soybean.Vegetahles

n Recreatlonal Grass (Golf course. Parks, Airport grasses, Industrial)

[3 Woody Wetlands

- Emergent Herbaceous Wetlands

141

Lake Michigan

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142

Notes for Land use mag) classification
Developed open space — includes areas with a mix of constructed and vegetation (such as
front lawn) and impervious surfaces account for less then 20 of total cover

Low intensity development- Impervious surfaces are between 20-49% of the total cover
and area is mainly single family housing units

Medium intensity development- Impervious surfaces are between 50-79% of the total
cover and area is mainly single family housing units

High intensity development- Impervious surfaces are between 80-100% of the total cover
and area includes single family housing units, apartment complexes and commercial and
industrial buildings

Barren land- mainly sand dunes, strip mines, gravel pits and earthen material
accumulations. Vegetation accounts for less then 15% of total cover.

Pasture/Hay- Areas of grasses, legumes or grass-legumes planted for ruminants or hay
crops. Pasture vegetation accounts for more then 20% of cover.

Cultivated crops- Areas used for annual crop production such as corn, soybeans,

vegetables, tobacco. Crop vegetation is greater then 20% of the total vegetation and land
is being actively tilled.

143

Appendix C Site Photographs

 

Rosy Mound Beach-6/25/2006

 

North Beach Park-8/28/2006

 

“ w,

North Bach Park-2/20/2006
Ice build up along shoreline preventing access to water.

 

North Shore Beach-2/20/2006

145

7 ”MNGE'R -
LAUNCH AREA‘
SHALLOW’ “CATER-
No SWIMMING: '

'° N0 merc

 

Riverside Park-5/21/2006
Flooding of the boat launch area

 

Riverside Park-8/28/2006

146

 

      

“:‘ K .

Johnson l’ark — 12/14/2006

147

 

Sixth Street Park — 11/16/2005

 

Sixth Street Park — 12/14/2005

148

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154

Appendix E Seasonal changes of precipitation compared to 1971 - 2000

J” 0 .'. Jun to Aug 2005 Precipitation
Percent of 1971-2000 Normal

National Clinall: Data Cantor. NOAA
This map I: based on preliminary report;
3 Slal'ion values may diller lrorn linal
quality conliolled data.

 

Mon! 0! Normal ’
I07. 95% ms
and 25% m 59" m I“ to 119mm “5% I” 175% and
has 105%
O C O O O o o O O O O .

u $3

. ' g 0 °- / Sop to Nov 2005 Praclpnallon

O
“a Percent of 1971-2000 Normal
~ 0

Mallond Clinatlc Data Oanhr. no“
. this map la based on preliminary moon;
'. Stallon values may diner lrom llnal

 

3 quality conliollod Gala.
MamolNoi-mal :‘
10% 99% 1m
and 25% m 59% 70% 05% lo llS‘blMflS‘blMlTSfis and
loan 105%
O O O o o . - o o o O O

155

. . ct ° . 3 ,/ Dec 2005 to Feb 2006 Precipitation
Percent of 1971-2000 Normal

W cum am. no“
'0 This map is based on preliminary report:
Station value: may enter irom llnal
quality coniiolhd data.

 

PaleontolNomIl A
was was man
and an m m m an to iisximusmmrm and
HI 105* m
. . . C O 0 a O O . . .

 

 

 

 

 

Mar to May 2006 Precipitation
Percent at 1971-2000 Normal
0
‘o 0!. F. .... ‘ o e
. I
v e ' 1 Q -,
. . .1» . ..-
Nationd cm on: cum-r. non . . .
This map is based on preliminary report: . . .
suiion values may duller lrom linal ‘ \‘d 0 ..0 -
. quality controlled data. ” . 0
\ O
Worm ‘.
m 95% i“
and 8% m 55% m 05% to 115%IMIIS%160$175% and
Ieaa 105%
O 0 e o o . - o o e O 0

156

Jun to Aug 2006 Precipitation
Percent of 1971-2000 Normal

 

Mallard Clinlllc D‘a Oanhr, NOAA
This map is based on preliminary reports.
Station values may diner from linai
quality controlled data.

 

PercentolNermal

10% 95% 1m
and 25% m 55% 70% 55% lo ilSfiiMl‘SfiHMi‘lsx and
lea: 105%

O O o a a . - o e a O O

157

January-December 2005 Statewide Ranks

National Climatic Data ComarlNESDlS/NOM

 

January-December 2006 Statewide Ranks

National Climatic Data Center/NESDISINOAA

   

Temperature

1 = Coldest
112 = Warmest

El
5%; El
35 El
if D
Em

iii I
an

158

National (Contiguous U.S.) Temperature

Degrees F
OI
A
'0

or
N
0

50.0 -

1895 - 2006

 

56.0 -

 

I I I I I I I I I I I I l I I I l I I I I I I

llllllllllllll|lllllll‘

 

 

 

1900 1920 1940 1960 1980 2000

Year
National Climatic Data Center/ NESDIS I NOAA

159

 

a—a Yearly Values
— Filtered Values
— Long-Term Mean

 

 

 

Shikha Singh

Education

 

Graduate Studies (MSc. candidate) January 2005— May 2007
Dept. of Fisheries and Wildlife (College of Agriculture and Natural Resources)
Michigan State University, East Lansing, MI.
Resgirch Focus:
Surface water and sediment quality in parks and beaches along the Grand River in Michigan.
0 Sites are located between Grand Rapids, MI to Grand Haven and F errysburg MI
0 Organisms studied: Fecal coliforms, Escherichia coli, Enterococci sp.,
Clostridium perfringens and Coliphage virus
0 Defended April 3“,, 2007

 

Relevant Courses:

Human dimension research in Fisheries and Wildlife Management, Conservation Biology
(advanced topics), Environmental Engineering Project, Outreach in Fisheries and Wildlife
Resource Management, Quantitative Methods Ecology & Evolution, Historical Roots of
Epidemiological Thought, Investigation of Wildlife Disease Outbreaks (seminar), Shaping Future
Water Policy: The Role of Science (seminar), Introduction to ArcView 3.2 and GIS

Relevant Experiences:

 

Teaching Assistant for FW 414 Aquatic Ecosystem Management Fall 2006
Course Grader for F W 414 Aquatic Ecosystem Management Fall 2005
Department of Chemical & Biochemical Engineering Fall Term 2004

University of Western Ontario, London, ON
Courses Taken:
Biochemical Engineering II, Chemical Engineering Thermodynamics Il (audit)

Field Course August & September 2003
Ecosystem Survey in South & Central Siberia (Russia)

University of Western Ontario, London, ON. & Queens University, Kingston, ON.

Relevant experiences:

Visited and studied tundra, taiga, dessert and steppe ecosystems where we observed vegetation
growth, local animals, and effects of pollution on the environment. Major areas travelled were
Krasnoyarsk, Stolby National Park, Shira (Khakassia), Shushenskoye, Kyzyl, Abakan, Sayano
mountain region, Yenesi River Paper topic: Impact of Russian Dams on the Environment

Bachelor of Science June 2003

Dept. of Biology (Faculty of Science)
University of Western Ontario, London, ON

160

 

Research & Work Experience

 

Research Assistant, Michigan State University September 2004 - December 2006

o Membrane Filtration and IDEXX analysis of water and sediment samples

0 DNA extraction of bacteria, measurement of DNA concentration (NanoDrop
Spectrophotometer), PCR amplification, Gel electrophoresis

0 Media preparation and bacteria grth

0 Side Projects: PRD-l and Rhodamine Tracer Study in Grand River (Grand Rapids,

Michgian), Microbial characterization in beach sands of North Beach Park, Water quality
of Lake Billings (Manton, MI) & Sediment analysis in St. Claire River (Sault Ste. Marie,

Michigan)

Research Assistant, University of Western Ontario May 2003 — July 2004

o The purpose was to optimize grth conditions for Halobacterium salinarium in order to
extract Bacterio Rhodopsin (purple membrane), a protein produced in various bacteria

0 Lab organization, safety and maintenance also part of duties

Undergraduate Researcher, University of Western Ontario 1999 - 2002

0 Worked during the summer months between school terms

0 Involved independent and unsupervised work on an assigned project involving Vibrio
fisheri and Escherichia coli,

0 Main focus was to immobilize bacteria onto a gel and place in a light sensing chamber to
monitor parameters

0 Resulted in two conference proceeding publicfiations

 

Conference Oral presentations

 

0 South Bass Island ground water outbreak
Michigan Environmentafilealth Association. 2007 Annual Education Conference
Invited speaker
March 30‘“, 2007

o Microbial and Pathogenic pollution in parks and beaches along the Grand River
Michigan chapter of American Water Works Association - Sept. 13, 2006

0 Microbial pollution in Beaches and Parks along the Grand River — from Grand Rapids,

M1 to Lake Michigan
Fisheries and Wildlife Graduate Student Symposium- March 17“, 2006

161

 

Lectures Given

 

Ground water contamination at South Bass Island
Monroe county public officials (May 18“) 2007
Invited keynote speaker

Chemical and Microbial Contamination in Aquatic Ecosystems
(4‘h year Aquatic Ecosystem Management) 2006

Public Education-Water quality Lecture Chemical and Microbial Contamination in
Aquatic Ecosystems

230 Grade 8 students-Ionia Middle School (October 315‘) 2006
Spoke about water quality issues, contamination and economic impact

Water and sediment quality along the Grand River, from Grand Rapids to L. Michigan

(Graduate Student Seminar) 2005
0 Impact of Russian Dams on the Environment

(4th year Political Biology) 2004
0 Ivan Turgenev: A study of his themes and how they portray 19th century Russia

(3rd year Russian History) 2003
Publications

 

Knopf, G.K, Bassi, A.S., Singh, S., F iorilli, M., and Jauda, L. 2000. “Optoelectronic
biosensor for remote monitoring of toxins”, OptoMechatronic Systems, Proc. Soc. Photo
- Opt. Instrum. Eng., vol. 4190, pp. 9 - 19.

Knopf, G.K., Bassi, A.S., Singh, S., Macleod, R. 1999. Biosensor for the remote
monitoring of airborne toxins. SPIE The international Society for Optical Engineering,

Symposium on Environmental Monitoring and Remediation Technologies 11 (19-22
September), Boston, MA, pp. 185-193.

McNinch, R, Singh, S. and J .B. Rose. 2007. UNESCO (United Nations Educational
Scientific and Cultural Organization) encyclopaedia article: recreational waters

Proposals

 

S. Singh and J .B. Rose. 2007. Microbial Water Quality Assessment for Muskegon
county. Muskegon County Waste Water Treatment Project (accepted)

162

Poster

 

0 S Singh, T. Shibata, T-T. Fong. 2007. Septic tank Impairment of Water Quality at Silver
Lake Sand Dunes Recreational Area, Michigan. National Beaches Conference, October

3”, Traverse City, MI.

0 S Singh, M Phani Kumar & J B Rose. “Comparing bacterial indicators in surface water
and sediment at Lake Michigan beaches and parks along the Grand River, MI”.
American Society of Microbiologists national conference, Toronto, Canada. May 21-25,

2007

0 S Singh and J.B. Rose. “Presence of fecal indicator bacteria in sediment and surface
water along the Grand River and beaches of Lake Michigan”. Ottawa County public

meeting August 19, 2006

0 S Singh, L Liu, M Phani Kumar & J B Rose. “C80 and occurrence of faecal indicators in
sediment and water along the Grand River and at the beaches of Lake Michigan”.
International Water Association/World Health Organization: 13“ International
symposia on Health-Related Water Microbiology. Swansea, Wales, UK. September 3- l 0,

2005

Volunteer Experience

 

Graduate Students Organization
Seminar Committee

Liason Officer
Graduate Women in Science (Mu Sigma Upsilon)

Executive of Communications
UWO Russian Students’ Union

Lets Talk Science
President - UWO Cause for Paws
President - UWO Humane Society Club

Executive of Fundraising - UWO Humane Society Club

May 2006 - December 2007

September 2005 - May 2006

September 2003 - June 2004

September 1999 — August 2003
September 2002 - May 2003
September 2001 — May 2002

September 2000 — May 2001

 

Memberships

0 American Society of Microbiologists (2005-2007)

0 Graduate Women in Science (National Chapter)~Sigma Delta Epsilon (2005/06)

0 Graduate Women in Science (Michigan State University)-Mu Sigma Upsilon (2005/06)

Executive Member-Liaison to the National Chapter

163

 

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