Appendix C.4: Assessment of the applicability of existing epidemiology data to 

inland waters

ASSESSMENT OF THE APPLICABILITY OF EXISTING 

EPIDEMIOLOGY DATA TO INLAND WATERS

U.S. Environmental Protection Agency

Office of Water

Health and Ecological Criteria Division

August 2010
U.S. Environmental Protection Agency

August 2010 i

Disclaimer

This document has not yet been reviewed in accordance with U.S. Environmental Protection 

Agency (EPA) policy and approved for publication and distribution. Mention of commercial 

products, trade names, or services in this document or in the references and/or footnotes cited in 

this document does not convey, and should not be interpreted as conveying, official EPA 

approval, endorsement, or recommendation.
U.S. Environmental Protection Agency

August 2010 ii

Acknowledgements

Questions concerning this document or its application should be addressed to the EPA Work 

Assignment Manager (WAM) or the Alternate WAM:

John Ravenscroft (WAM)

USEPA Headquarters 

Health and Ecological Criteria Division 

Office of Science and Technology, Office of Water 

1200 Pennsylvania Avenue, NW

Mail Code 4304T 

Washington, DC 20460

Phone: 202-566-1101

Email: ravenscroft.john@epa.gov

Stephen Schaub (Alternate WAM)

USEPA Headquarters 

Health and Ecological Criteria Division 

Office of Water, Office of Science and Technology

1200 Pennsylvania Avenue, NW

Mail Code 4304 T

Washington, DC 20460

Phone: 202-566-1126

E-mail: schaub.stephen@epa.gov

This report was managed under EPA Contract EP-C-07-036 to Clancy Environmental 

Consultants, Inc., a Tetra Tech Company. 

The following individuals contributed to the development of the report:

Timothy Bartrand (lead) Clancy Environmental Consultants, Inc.

Mark Gibson Clancy Environmental Consultants, Inc.

Jeffrey Rosen Clancy Environmental Consultants, Inc.

Jeffrey Soller Soller Environmental, LLC
U.S. Environmental Protection Agency

August 2010 iii

Table of Contents

DISCLAIMER..................................................................................................................................................I

ACKNOWLEDGEMENTS ...............................................................................................................................II

LIST OF TABLES..........................................................................................................................................IV

LIST OF FIGURES ........................................................................................................................................IV

ACRONYMS...................................................................................................................................................V

EXECUTIVE SUMMARY................................................................................................................................ 1

1. INTRODUCTION.................................................................................................................................... 4

1.1. Purpose........................................................................................................................................ 4

1.2. Background................................................................................................................................. 4

1.3. Overview of Epidemiology and Recreational Water Quality Criteria ........................................ 5

1.3.1. Prospective Cohort Studies.............................................................................................. 6

1.3.2. Randomized Control Trials ............................................................................................. 6

1.4. Approach..................................................................................................................................... 7

2. QUALITATIVE COMPARISON OF INLAND AND COASTAL SETTINGS................................................. 8

2.1. Differences in Fecal Sources for Inland and Coastal Waters...................................................... 8

2.2. Pathogen and FIB Loading ......................................................................................................... 9

2.3. Biology and Mechanics of Resuspension ................................................................................. 11

3. FECAL INDICATOR BACTERIA SOURCES AND CORRELATION WITH HEALTH EFFECTS IN INLAND 

SETTINGS.................................................................................................................................................... 14

3.1. Epidemiology Studies of Inland Recreational Waters.............................................................. 14

3.2. Non-Epidemiological Studies of Inland Settings...................................................................... 18

3.3. Summary................................................................................................................................... 21

4. OCCURRENCE OF FECAL INDICATOR BACTERIA IN INLAND AND COASTAL SETTINGS ............... 22

4.1. Data Summary .......................................................................................................................... 22

4.2. Event-Scale Variability: Rainfall and Runoff........................................................................... 30

4.2.1. Inland Sites.................................................................................................................... 30

4.2.2. Coastal Sites .................................................................................................................. 31

4.2.3. Summary: Event-Scale Indicator Variability................................................................. 32

4.3. Summary................................................................................................................................... 32

5. SURVIVAL OF FECAL INDICATOR BACTERIA IN INLAND AND COASTAL SETTINGS...................... 34

5.1. General Description of Indicator Decay in Natural Waters...................................................... 34

5.2. Phenomena Contributing to Indicator Removal........................................................................ 36

5.3. Growth Observations................................................................................................................ 38

5.4. Comparison of Measured Decay Rates..................................................................................... 41

5.5. Summary................................................................................................................................... 45

6. INDICATOR-PATHOGEN ASSOCIATION IN INLAND AND COASTAL SETTINGS ............................... 46

6.1. Cryptosporidium and Fecal Indicators...................................................................................... 46

6.2. Viruses and Fecal Indicators..................................................................................................... 48

6.2.1. Co-occurrence and Correlation of Enteric Viruses and Fecal Indicators ...................... 48

6.2.2. Inactivation Rates of Enteric Viruses in Different Settings........................................... 52

6.3. Bacterial Pathogens and Indicators........................................................................................... 55

6.1. Summary................................................................................................................................... 56

7. REFERENCES...................................................................................................................................... 58

APPENDIX A SUMMARY OF STUDIES IDENTIFIED IN LITERATURE REVIEW.......................................A-1

APPENDIX B LITERATURE SEARCH STRATEGY AND RESULTS.......................................................... B-38
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August 2010 iv

List of Tables

Table 1. Summary of Completed Epidemiological Studies of Inland Waters............................. 15

Table 2. Studies of E. coli Occurrence ........................................................................................ 23

Table 3. Studies of Enterococci Occurrence................................................................................ 24

Table 4. Studies of Fecal Coliform Occurrence........................................................................... 25

Table 5. Studies of Fecal Streptococcus and Total Coliform ...................................................... 26

Table 6. Reports in which Fecal Indicator Bacteria Growth has been Observed or Inferred ...... 39

Table 7. Decay Rates for E. coli Reported in Studies Conducted with in situ Mesocosms ........ 42

Table 8. Decay Rates for Enterococci from Laboratory Mesocosm Studies............................... 44

Table 9. Summary of Enteric Virus Inactivation Rate Data ........................................................ 54

List of Figures

Figure 1. Fecal Indicator and Pathogen Loading at Inland Sites................................................... 9

Figure 2. Fecal Indicator and Pathogen Loading at Coastal Sites ............................................... 10

Figure 3. Resuspension Phenomena: Inland Waters.................................................................... 12

Figure 4. Resuspension Phenomena: Coastal Waters.................................................................. 13

Figure 5. Summary of Reported E. coli Densities in Various Water Types ............................... 27

Figure 6. Summary of Reported Enterococci Densities in Various Water Types. ...................... 27

Figure 7. Summary of Reported Fecal Coliform Densities in Various Water Types.................. 28

Figure 8. Summary of Reported Fecal Streptococcus Densities in Various Water Types.......... 28

Figure 9. Summary of Reported Total Coliform Densities in Various Water Types .................. 29

Figure 10. Survival Curves for E. coli from in situ Mesocosm Experiments in Coastal Fresh 

Waters. .......................................................................................................................................... 34

Figure 11. Survival Curves for E. coli in Seawater ..................................................................... 35

Figure 12. Survival Curves for E. coli in Freshwater, Stream Settings....................................... 35

Figure 13. Decay Rates of E. coli from in situ Mesocosm Studies. ............................................ 41

Figure 14. Spatial Trends in HAV and Fecal Indicator Bacteria in a Small Stream Located in an 

Area whose Land Use is Primarily Agriculture............................................................................ 51

Figure 15. Inactivation of Simian Rotavirus in Unpolluted Fresh Water (open squares), Polluted 

Fresh Water (filled squares), Low Salinity Estuary Water (open circles), Medium Salinity 

Estuary Water (open triangles), and High Salinity Estuary Water (crosses)................................ 53

Figure 16. Survival Curves for Coxsackievirus B-1 and Poliovirus 1 in Membrane Diffusion 

Chambers in Fresh Water.............................................................................................................. 54

Figure 17. Decay Rates for Salmonella for Various Settings and Temperatures. ....................... 57
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August 2010 v

Acronyms

AODC acridine orange (stain) direct count

AWQC ambient water quality criteria

BEACH Act Beaches Environmental Assessment and Coastal Health Act

CC Coulter Counter

CFU colony forming unit

CHEERS Chicago Health, Environmental Exposure, and Recreation Study

CPSP Critical Path Science Plan

CSO combined sewer overflow

CWA Clean Water Act

EEC European Economic Community

EPA U.S. Environmental Protection Agency

EU European Union

FC fecal coliform

FIB fecal indicator bacteria 

GI gastrointestinal

HAV hepatitis A virus

HCGI highly credible GI illness

HPC heterotrophic plate count

MPN most probable number

MST microbial source tracking

NEEAR National Epidemiological and Environmental Assessment of Recreational 

Water Study

NOAEL no observed adverse effect level

PC prospective cohort

PCR polymerase chain reaction

POTW publicly-owned (sewage/wastewater) treatment works

ppt parts per thousand (salinity)

QMRA quantitative microbial risk assessment

QPCR quantitative polymerase chain reaction

RCT randomized control trial

SCCWRP Southern California Coastal Water Research Project

SSO sanitary sewer overflow

TC total coliform

U.K. United Kingdom

U.S. United States

UV ultraviolet (light)

VBNC viable but not culturable

WERF Water Environment Research Foundation

WHO World Health Organization (United Nations)

WQS water quality standard(s)

WWTP wastewater treatment plant
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August 2010 1

Executive Summary

This report evaluates whether the observed 

relationships between fecal indicator bacteria 

(FIB) densities and adverse health effects for 

Great Lakes1 waters are applicable to inland 

waters. Results suggest that the 

epidemiological data and relationships 

developed for Great Lakes waters that are 

primarily impacted by publicly-owned 

treatment work (POTW) effluents can be 

applied to inland waters that are also primarily 

impacted by POTW effluents. For inland 

waters that are predominantly impacted by fecal 

sources other than POTW effluent, the available 

science does not support the extension of the 

epidemiological relationships developed in the 

Great Lakes. 

Methodology 

To prepare this report, the authors performed an 

extensive review of studies providing 

information on FIB performance in inland and 

coastal settings. In this report, FIB performance 

refers to the association of indicator organism 

densities with fecal pollution sources and their 

health effects, as described in Exhibit 1. 

Performance was also assessed in terms of 

indicator occurrence (including variability), 

survival, and their association with pathogens. The FIB performance data were used in 

conjunction with the known differences in sources and hydrodynamics between inland and 

coastal settings to evaluate the validity of extending health effects relationships developed from 

Great Lakes epidemiology studies2to inland flowing or impounded waters. 

Qualitative Comparison of Inland and Coastal Settings

Inland and coastal waters receive FIB from point sources, diffuse sources including non-point 

sources, direct deposition (e.g., gulls, cattle in a stream), and resuspension of FIB in sediments or 

 

1

As specified in the Beaches Environmental Assessment and Coastal Health (BEACH) Act of 2000, Section 502 of 

the Federal Water Pollution Control Act (33 U.S.C. 1362) identifies “coastal waters” as the Great Lakes and marine 

coastal waters (including coastal estuaries) that are designated under Section 303(c) by a State for use for 

swimming, bathing, surfing, or similar water contact activities.

2 Epidemiological data collected as part of EPA’s National Epidemiological and Environmental Assessment of 

Recreational (NEEAR) Water Study.

Exhibit 1. Relating Indicator Organism 

Densities to Health Effects

The features of an effective indicator (adapted 

from NRC, 2004) are

a demonstrated correlation with health risk; 

similar or greater survival time than the 

target pathogen(s);

similar or greater transport than the target 

pathogen(s);

presence in greater numbers than the 

target pathogen(s); and 

specificity to a fecal source or an 

identifiable source of origin.

Because humans and animals excrete different 

densities of fecal indicator organisms and 

pathogens, fecal indicator densities in waters 

impacted by different sources indicate different 

hazards. Thus, if inland and coastal waters 

have different primary fecal pollution sources, 

health effects will also differ.

This report focuses on differences in indicator 

performance in inland and coastal settings. It 

does not address the performance of indicators 

in each of the settings independently. To 

evaluate these differences, indicator 

occurrence, survival/growth, and association 

with pathogens is compared for inland and 

coastal waters.
U.S. Environmental Protection Agency

August 2010 2

overbanks (Exhibit 2). Loading 

and hydrodynamics of FIB in 

POTW-impacted inland and 

coastal waters are generally 

similar; POTW discharges in both 

settings are relatively steady and 

are not dependent on whether a 

recreational site is coastal or 

inland.

In contrast, significant differences 

exist in FIB loading between 

POTW-impacted coastal waters 

and non-POTW-impacted inland 

waters. Physical and biological 

characteristics that are different in 

these two types of settings and that 

influence indicator performance 

include shading, hydrodynamics, 

potential for deposition of particleassociated microorganisms, and 

microbial ecology. Differences 

potentially affecting the 

relationship between indicator 

density and health effects are the 

fecal source itself and the transport 

of pathogens and indicators in the 

receiving water—POTW effluent 

is loaded to receiving waters 

continuously, whereas 

contamination from other sources 

is primarily loaded to waters 

during precipitation events (rain, 

overflow, etc). 

Summary of Key Findings

1. Fecal pollution source (human or other animals) is the most important of the potential 

differences between the NEEAR study sites and inland waters.

o The pollution source directly influences the suite of pathogens and indicators in 

receiving waters and any health effects that could result from exposure to those 

waters.

2. The NEEAR epidemiology study findings may be extended to POTW-impacted inland 

waters on the basis of similar fecal pollution source (human) and FIB fate and transport. 

Exhibit 2. Illustration of Fecal Pollution Sources on 

Inland and Coastal Settings
U.S. Environmental Protection Agency

August 2010 3

o Indicator occurrence, survival, and association with pathogens are highly variable in 

both coastal and inland settings. For recreational waters where POTW inputs are the 

dominant impact, the expected health risks are not substantially different between 

coastal and inland settings.

o Extension of the NEEAR study results to POTW-impacted inland waters was also 

supported by the academic, government, and industry experts at a 2009 Water 

Environment Research Foundation workshop on inland waters research needs.

3. Sufficient data do not exist to extend the NEEAR epidemiology study findings to non-POTW 

impacted inland waters. 

o Because there are significant differences in hydrodynamics and fecal pollution 

sources between coastal POTW-impacted waters and non-POTW-impacted inland 

waters, it is reasonable to infer that indicator performance relationships will not be 

similar. POTW-impacted waters receive continuous loading whereas loads to waters 

impacted by other fecal sources are event-driven. 

o Non-POTW fecal pollution sources vary widely among inland waters and in their 

association of indicator densities with health effects.3 The hydraulics of inland waters 

can differ from coastal waters in phenomena such as particle settling and 

suspension/resuspension mechanics. These characteristics can also impact the 

number and diversity of FIB and pathogens that will be present in a waterbody at a 

given time and likely differ for POTW and non-POTW sources.

 

3 The association of indicator density with risk for different fecal pollution sources is evaluated in Soller, J.A., 

Schoen, M.E., Bartrand, T.A., Ravenscroft, J.E., and Ashbolt, N.J. 2010. Estimated human health risks from 

exposure to recreational waters impacted by human and non-human sources of faecal contamination. Water 

Research. doi:10:1016/j.watres.2010.07.064.
U.S. Environmental Protection Agency

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Introduction

Purpose

The primary purpose of this document is to help meet one of the elements (Project P-28) in the 

U.S. Environmental Protection Agency (EPA or the Agency) Critical Path Science Plan for 

Development of New or Revised Recreational Water Quality Criteria (CPSP or science plan) 

(USEPA, 2007a). The science plan is key component of EPA’s overall process to develop new 

or revised Section 304(a) Ambient Water Quality Criteria (AWQC) for recreational waters that 

will be used by States, Territories, and Tribes to develop their own water quality standards 

(WQS4). The CPSP was developed, in part, based on feedback from a large group of 

stakeholders and the detailed input and recommendations from the scientific community 

provided in the Experts Scientific Workshop on Critical Research and Science Needs for the 

Development of New or Revised Recreational Water Quality Criteria (USEPA, 2007b; see also 

Boehm et al., 2009).

The objective of CPSP Project P-28 is to evaluate applicability of EPA’s National 

Epidemiological and Environmental Assessment of Recreational Water Study (NEEAR) Great 

Lakes5epidemiological data to inland waters. This report evaluates whether the observed 

relationships between fecal indicator bacteria (FIB) densities and adverse health effects for Great 

Lakes waters are applicable to inland waters. To support this evaluation, the report also 

evaluates ―indicator performance‖ in inland and coastal settings, which includes the following: 

(1) the association of FIB densities with fecal pollution sources and their health effects, (2) an 

analysis of fate and behavior of FIB and select pathogens, and (3) an analysis of microbial 

ecology and persistence of FIB indicators and select pathogens. 

Background

Fecal matter from human and animal sources can be a major source of waterborne pathogens. 

Because it is not practical or feasible to monitor for all pathogens that may occur in ambient 

waters, water quality criteria, standards, or guidelines are typically specified as fecal indicator 

organism densities (NRC, 2004; Schwab, 2007; WHO, 2003). These fecal indicator 

organisms—which comprise a few groups of nonpathogenic fecal bacteria and, more recently, 

some viruses—have been used for decades to indicate the presence and magnitude of fecal 

material. This approach assumes that waterborne pathogens co-occur with the fecal material.

 

4 Under the Clean Water Act (CWA) Section 303(i)(1)(B), States, Territories, and Tribes are required to adopt new 

or revised WQS for those pathogens and pathogen indicators for which EPA’s new or revised criteria have been 

developed. Once approved by EPA, WQS are used for various CWA purposes and programs and are the effective

(enforceable) standards to protect waters for specified designated uses, such as ―primary contact recreation.‖ The 

latter typically encompasses recreational activities that could be expected to result in the ingestion of, or immersion 

in, a water body (such as swimming, water skiing, surfing, or any other recreational activity where ingestion of, or 

immersion in, the water is likely). 

5

As specified in the Beaches Environmental Assessment and Coastal Health (BEACH) Act of 2000, which revised the 

CWA, “coastal waters” are defined as the Great Lakes and marine coastal waters (including coastal estuaries) that 

are designated under CWA Section 303(c) by a State for use for swimming, bathing, surfing, or similar water 

contact activities.
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August 2010 5

―More specifically, fecal indicator bacteria provide an estimation of the amount of feces, and 

indirectly, the presence and quantity of fecal pathogens in the water‖ (NRC, 2004). Therefore, 

use of fecal indicator organisms in recreational waters is based on the presumption that their fate 

and behavior, ecology and persistence, and performance in all types of recreational waters, 

including marine, estuarine, and inland flowing and non-flowing waters, remains consistent. 

―Traditional‖ indicators include culturable total coliforms, fecal (thermotolerant) coliforms, E. 

coli (an important member of the coliform group), and enterococci.6 However, because the total 

coliform group has been shown to be a poor indicator of fecal contamination, they are no longer 

widely used in U.S. recreational waters. The attributes of an effective indicator (i.e., measures of 

indicator performance) are the following (adapted from NRC, 2004): 

a demonstrated correlation with health risk; 

similar or greater survival time than the target pathogen(s);

similar or greater transport than the target pathogen(s);

presence in greater numbers than the target pathogen(s); and 

specificity to a fecal source or an identifiable source of origin.

These indicator attributes are supported by the World Health Organization (WHO, 2003), which 

has a similar set of criteria describing effective indicators of fecal contamination. 

EPA used epidemiological studies of publicly-owned treatment work (POTW) effluent-impacted 

marine (USEPA, 1983) and freshwater (USEPA, 1984) recreational waters to develop the 1986 

AWQC for recreational water. Specifically, the results of those epidemiological studies provide 

quantitative relationships between culturable FIB density in recreational waters (E. coli and 

enterococci for freshwaters and enterococci for marine waters) and gastrointestinal (GI) illness 

levels for those individuals exposed to recreational waters (USEPA, 1986). The recommended 

criteria based on these studies are still in effect and are required for use by all coastal and Great 

Lake states (USEPA, 2004). 

EPA has conducted a significant amount of research since the BEACH Act was enacted in 

October 2000 and is finalizing research activities in accordance with the science plan to issue 

new or revised AWQC by 2012. 

Overview of Epidemiology and Recreational Water Quality Criteria

Since the 1950s, numerous epidemiological studies have been conducted throughout the world to 

evaluate the association between recreational water quality and adverse health outcomes, 

including GI symptoms; eye infections; skin irritations; ear, nose, and throat infections; and 

respiratory illness. Most of these studies are reviewed in one or more of the metaanalyses/systematic reviews of Prüss (1998), Wade et al. (2003), Zmirou et al. (2003). More 

recent epidemiology studies are reviewed in USEPA (2009) and WERF (2009). Both

 

6 The terms enterococci, Enterocooccus, fecal streptococci, fecal streptococcus, and intestinal enterococci are often 

used to refer to essentially the same environmental and fecal species of bacteria (see NRC, 2004 for further 

information). Thus, for convenience, this report uses the term enterococci unless otherwise noted.
U.S. Environmental Protection Agency

August 2010 6

prospective cohort (PC) and randomized control trial (RCT; also called prospective randomized 

exposure studies [Fleisher et al., 2010]) epidemiology studies have been conducted to describe 

and quantify relationships between illnesses among swimmers and recreational water quality. It 

is beyond the scope of this report to comprehensively describe, compare, and contrast these two 

major epidemiology study designs. However, a very brief overview of their use in various 

recreational water studies—including the development of U.S., WHO, and European Union (EU) 

recreational water quality criteria, guidelines, and standards, respectively—is provided below.

Prospective Cohort Studies

EPA’s current (1986) recreational water quality are based on the observed occurrence of GI 

illness associated with swimming in fresh or marine recreational waters receiving point sources 

of effluent from POTWs as determined through several PC studies conducted in the 1970s 

through the early 1980s. Over the past several years, EPA has conducted several PC studies at 

four POTW-impacted Great Lakes beaches and four marine recreational beaches (three POTWimpacted and one non-POTW-impacted) as part of the NEEAR Water Study. The results of the 

Great Lakes studies are published (Heaney et al., 2009; Wade et al., 2006, 2008) while the 

marine studies have not yet been finalized. 

To date, most U.S. and international epidemiology studies of recreational waters have used the 

PC study design at marine beaches (e.g., Fattal et al., 1983; Haile et al., 1999; Marino et al., 

1995). Further, there have been relatively few studies of inland (non-Great lakes) waters or of 

non-point source-impacted recreational sites. Calderon et al. (1991) used a PC study to follow 

the health status and swimming activities of volunteer participants at a small inland pond in 

Connecticut whose source was rainwater runoff from a forested watershed in Connecticut. 

Recently, Marion et al. (2010) conducted a PC study of recreational users of an inland lake 

(flood control reservoir) in Ohio with multiple point and non-point sources of fecal pollution. 

Several U.S. PC studies of predominantly non-point source-impacted beaches in southern 

California have been completed (Colford et al., 2007) or are nearing completion (SCCWRP, 

2008). 

Randomized Control Trials

The other major epidemiological design used in recreational sites is the RCT. This design has 

been used extensively in Europe and more recently in the United States to determine the 

association between microbial water quality and increased risk of adverse health effects in 

swimmers vs. non-swimmers in both marine and fresh recreational waters. The WHO 

Guidelines for Safe Recreational Water Environments (WHO, 2003) apply to both fresh and 

recreational waters and are based, in large part, on RCT studies conducted in the late 1980s and 

early 1990s at POTW-impacted marine recreational beaches in the U.K. (Fleisher et al., 1996; 

Kay et al., 1994). The EU adopted Directive 2006/7/EC of the European Parliament and of the 

Council of 15 February 2006 Concerning the Management of Bathing Water Quality and 

Repealing Directive 76/160/EEC (EP/CEU, 2006) is also based, in large part, on the same U.K. 

marine recreational water studies, and a more recent RCT study of POTW- and non-point 

source-impacted fresh recreational waters in Germany (Wiedenmann et al., 2006). Epibathe 

(2009a,b) describes the results of a series of RCT studies conducted at marine and fresh 
U.S. Environmental Protection Agency

August 2010 7

recreational waters in Europe in 2006 and 2007. Finally, the results of an RCT study of a nonPOTW-impacted marine beach in Miami, Florida have been recently published (Abdelzaher et 

al., 2010; Fleisher et al., 2010; Sinigalliano et al. 2010). 

Approach

To prepare this report, a detailed literature search and retrieval was performed in Fall 2008, the 

approach and summary of results of which are provided in Appendix B. Next, a series of 

analyses and summarizations of relevant studies (see Appendix A) were conducted to address 

indicator performance in inland and coastal settings7that are discussed in the five sections (2-6) 

that follow—each of which includes a summary. After completion of a draft report in early 

2009, the report was revised, expanded, and finalized in 2010. 

Following this background and introduction, Section 2 qualitatively compares and contrasts fecal 

indicator and pathogen loading and resuspension dynamics in inland and coastal sites. Section 3 

reviews fecal indicator sources and their association with health risk. Section 4 summarizes the 

occurrence of FIB in inland and coastal waters and evaluates whether they are different; it also 

compares and contrasts in FIB occurrence that is attributable to rainfall and runoff events (eventscale variability). Section 5 addresses survival of bacterial indicator organisms in inland and 

coastal settings, including a discussion of phenomena contributing to indicator removal, 

observations of indicator organism growth in the environment, and a comparison of measured 

decay rates. Lastly, Section 6 reviews indicator-pathogen associations in inland and coastal 

settings.

 

7 Categorized in this report as coastal freshwater, coastal marine water, estuarine, inland flowing water main stem, 

inland flowing water in a small reach, or inland non-flowing water.
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August 2010 8

Qualitative Comparison of Inland and Coastal Settings

Both inland and coastal recreational waters are highly diverse. Inland waters may be headwater 

streams or main stems, deep or shallow, shaded or unshaded, support different microbial 

populations and have different temperatures. Coastal waters are subject to different tides, waves, 

and currents and have different sediments. Despite being diverse, there are distinctive features of 

inland and coastal waters that result in differences in how indicator organisms and pathogens 

occur, are loaded, survive, and grow in their respective aquatic environments. This section 

qualitatively compares and contrasts fecal indicator and pathogen occurrence and dynamics in 

inland and coastal sites. (Sections 5 and 6 provide a review of quantitative data for assessing 

differences in the dynamics of indicators and pathogens in inland and coastal settings.)

The differences between inland and coastal sites with the greatest impacts on the performance of 

indicator organisms are (Dorevitch et al., 2010; WERF, 2009):

first and foremost, differences in source;

differences in hydrology (loading and dilution potential); and

differences in potential for indicator growth and resuspension.

A qualitative description of each of those features in inland and coastal waters is provided in the

following sections, along with hypotheses on how these differences might influence indicator 

performance.

Differences in Fecal Sources for Inland and Coastal Waters

As described in Section 3, epidemiological studies support the contention that association of 

illness with indicator level differs between sites that are human-impacted (POTW discharges and 

perhaps urban stormwater runoff) and sites that are impacted by non-human fecal pollution 

sources. Further, modeling studies indicate that different fecal pollution sources are associated 

with different suites of pathogens occurring at a given indicator level. Because pathogens, not 

indicators, are responsible for illnesses, the fecal pollution source is believed to be a more 

important determinant of the association of indicator level with health effects for a given site 

than whether the site is an inland site or a coastal site. This contention is supported by findings 

of an experts workshop on indicators in inland and coastal settings (Dorevitch et al., 2010; 

WERF, 2009).

Although source is believed to be the most important factor determining the association between 

indicator density and health effects at a given site, no data source allows systematic comparison 

and contrast of the sources typical of inland and coastal waters. Dorevitch et al. (2010) 

hypothesized that proportionally more inland waters than coastal waters are impacted by nonhuman sources of fecal pollution. However, the authors are not aware of a study that tests this 

hypothesis. Further, if it is true that fecal pollution source is a more important determinant of 

health effects than recreational site setting—as contended by participants in the recent Experts 

Scientific Workshop on Critical Research and Science Needs for the Development of 

Recreational Water Quality Criteria for Inland Waters (WERF, 2009)—then classifying sites by 

their fecal pollution source rather than by their setting may provide an improved opportunity for 
U.S. Environmental Protection Agency

August 2010 9

developing criteria for different recreational sites. The validity of characterizing inland waters 

with a dominant source type notwithstanding, the impact of fecal source on correlations of 

indicator organism density and health risk in inland waters is discussed in Section 3. 

Indicator performance in stormwater runoff from urbanized areas likely differs from that from 

rural areas characterized by lower impervious area proportion (WERF, 2009). Again, this 

observation relates more to the source of fecalpollution than to whether a setting is inland or 

coastal and as with distribution of fecal pollution sources among inland and coastal waters, it is 

unclear whether urban land use impacts proportionally more inland or coastal sites. Regardless 

of whether sites are inland or coastal, runoff from urbanized areas with a high proportion of 

impervious surfaces is flashier than that from rural areas. Additionally, impervious surfaces 

have less potential for retaining particles and bacteria and are expected to generate greater 

densities and higher loadings of suspended bacteria and suspended particle-associated bacteria 

than pervious areas. These physical and hydrological differences may result in different 

indicator loads from urbanized areas than from less densely developed areas, whether those areas 

are adjacent to coastal or inland waters.

Pathogen and FIB Loading

Both inland and coastal waters receive FIB from point sources, diffuse sources including nonpoint sources, direct deposition (e.g., gulls, cattle in a stream), and resuspension of FIB in 

sediments or overbanks (NRC, 2004; WERF, 2009). These processes are illustrated for inland 

waters in Figure 1 and for coastal sites in Figure 2. In this context, loading refers to the 

contribution of net numbers of indicators and pathogens to the receiving water for each source. 

Figure 1. Fecal Indicator and Pathogen Loading at Inland Sites
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August 2010 10

Figure 2. Fecal Indicator and Pathogen Loading at Coastal Sites

In the United States, the most important point source of fecal pollution is POTW (also called 

wastewater treatment plant [WWTP]) effluent, which in most cases is disinfected prior to 

discharge. Human sources of fecal pollution include on-site wastewater treatment (―septic‖) 

systems, combined sewer overflow (CSO) and sanitary sewer overflow (SSO) discharges, urban 

stormwater, and leaking sewage conveyances. Livestock non-point sources include fecal 

pollution directly deposited into streams (unlikely for coastal waters), runoff from wastes 

deposited by pastured animals, runoff from fields with land-applied fecal wastes, and leakage or 

accidental discharges from stored wastes. Wildlife non-point fecal pollution may be directly

deposited into streams and coastal waters or deposited onto land surfaces and transported to 

receiving waters in overland flow.

Point and non-point sources of fecal indicators and pathogens load receiving waters in 

fundamentally different ways. In general, fecal loads from POTWs are continuous, whereas 

those from non-point sources occur due to rain events, snow melts, recession of tides, and other 

precipitation-related events (WERF, 2009). Indicator and pathogen loads from non-point 

sources are widely variable temporally and spatially and it is likely that within-event variations 

for pathogens differ from those of indicators. Although these differences likely impact indicator 

performance, it is difficult to generalize these impacts given the wide differences between 

recreational sites, between events, and even in conditions during events. 

POTW-related indicator and pathogen loads are also variable, but to a much lesser extent than 

those from non-point sources. Indicator organism densities in untreated sewage are related to 

human intestinal densities of FIB. While there are variations in production rates of indicator 

bacteria among individuals, the indicator loading of a POTW by a collection of individuals 

(population) is likely relatively constant. Treated POTW effluent is also characterized by 

relatively constant indicator densities, although variations in WWTP performance and raw water 

quality may be important for plants treating sewage from combined sewer systems (i.e., a type of 
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August 2010 11

sewer system that collects sanitary sewage and stormwater runoff in a single pipe system). The 

above considerations support a general finding that POTW-impacted inland and coastal waters 

are generally similar in terms of FIB loading because treated effluent discharges in both settings 

are relatively steady and not dependent on whether a site is coastal or inland. 

In contrast, significant differences in FIB loadings exist between POTW-impacted coastal waters 

and non-POTW-impacted inland waters. Physical and biological characteristics that are different 

in both types of settings and that influence indicator performance include shading, 

hydrodynamics, potential for deposition of particle-associated microorganisms, and microbial 

ecology. Differences potentially affecting the relationship between indicator density and health 

effects are the fecal source and the transport of pathogens and indicators in the receiving water. 

Biology and Mechanics of Resuspension

There are several potential sources of non- (extra-) enteric indicator organisms in recreational 

waters. Under the right conditions, E. coli and other enteric bacteria may bloom, as described by 

Ashbolt et al. (1997) for an impounded inland lake in Australia (see also Power et al., 2005). 

The conditions believed to contribute to the blooms of E. coli in that study were not exceptional 

and included the presence of sufficient organic carbon and surface temperatures above 18° C. 

The E. coli densities observed during the blooms however, were exceptional. The peak E. coli

density observed during blooms was 298,000 CFU/100 mL throughout the top layer of the lake 

and the E. coli density persisted above 5000 CFU/100 mL. Features of the water column may 

also promote the growth and persistence of FIB. Whitman and Nevers (2003) and Olapade et al. 

(2006) reported high densities and prolonged persistence of E. coli in algal mats of Cladophora

in Lake Michigan waters and on Lake Michigan foresands. However, Olapade and colleagues 

showed that E. coli in the mats were seemingly not associated with exceedences of FIB-based 

beach closure criteria, despite the very high densities in the algal mats. Their mesocosm 

experiments demonstrated much higher persistence of E. coli in the mats than in the water 

column.

The most commonly reported non-enteric source of FIB appears to be sediments and soils. 

Originally thought to occur mainly in tropical soils (e.g., Carillo et al., 1985; Fujioka et al., 1999, 

1999), indicator bacteria are now known to persist or grow in temperate soils (e.g., Ishii et al., 

2006a), and beach sands in temperate areas at freshwater (e.g., Whitman et al., 2003) or marine 

sites (e.g., Yamahara et al., 2009). As noted above, growth condition requirements for FIB are 

minimal and are often present in soils and sediments. Further, sediments may shelter indicators 

from predators or otherwise shelter the organisms and increase their persistence. The influence 

of sediments on the persistence and extra-enteric growth of indicators is described in Section 5. 

Although there are differences in inland and coastal sites that could result in differing survival 

and growth potential in the two settings, the authors identified no studies that systematically 

compared growth and persistence of FIB in inland and coastal soils and sediments. However, 

WERF (2009) suggest that smaller sediment sizes and greater area of wetted sediments per water 

volume for inland waters favor indicator growth and persistence in inland settings over growth 

and persistence in coastal settings. 
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Resuspension of indicators for inland sites is illustrated in Figure 3(a and b). In inland sites,

bottom shear may resuspend indicators in bottom sediments as well as particles with attached 

bacteria and indicators. Once in the water column, these suspended bacteria are mixed and 

advected downstream. Indicators may also wash into the water from soils during stream 

recession after storms, as depicted in Figure 3b. In both of these resuspension mechanisms the 

net indicator load contributed is dependent on the combination of the accumulation of indicator 

bacteria in the sediments/soils and the motive force imparted on the indicators. Because these 

two processes are variable, FIB density resulting from resuspension is also variable. 

Resuspension at coastal sites is depicted in Figure 4 (a and b). Resuspension may be the result of 

waves breaking on swash zone sands and receding (4a) or may result as tidal waters recede and 

draw indicator bacteria into the sediments (4b) (Boehm and Weisberg, 2005; Santoro and 

Boehm, 2007; Yamahara et al., 2007). As with inland waters, the net contribution of 

resuspension to indicator organism density at a coastal site depends upon accumulation of 

indicators in sands/sediments and the motive force for resuspending indicators. Resuspended 

loads are low when indicator reservoirs are depleted or the overlying water is quiescent. 

Figure 3. Resuspension Phenomena: Inland Waters
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Figure 4. Resuspension Phenomena: Coastal Waters

In summary, the mechanisms and conditions for indicator and pathogen growth, persistence, and 

resuspension differ between inland and coastal sites. Inland settings are generally believed to be 

characterized by smaller sediment sizes, greater ratio of wetted area to water column volume, 

and high bottom shear stresses. Coastal sites are subject to colonization of sands with indicator 

bacteria by shorebirds and other sources, sufficient conditions for promoting growth, and 

vigorous shear on sediments due to incoming and receding waves. It is not possible to state 

generally whether resuspension contributes a greater proportion of indicators at inland or coastal 

sites, only that the mechanisms producing resuspended sediments differ and may result in 

different indicator relationships with fresh fecal pollution in inland and coastal settings. 
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Fecal Indicator Bacteria Sources and Correlation with Health Effects in Inland Settings 

In this section, the sources of indicator organisms and their association with health risks are 

described. Studies used to connect inland and coastal sites to health effects include 

epidemiology studies of inland recreational waters, epidemiological studies of coastal waters 

with non-human fecal impacts, and non-epidemiological studies such as QMRA and catchment 

modeling (non-epidemiological). See Prüss (1998), USEPA (2009), Wade et al. (2003), WERF 

(2009), and Zmirou et al. (2003) for more comprehensive reviews of coastal and inland 

recreational water epidemiology studies. Notably, the WERF (2009) review and synthesis 

reported that all studies of water recreation and health effects identified higher rates of at least 

some self-reported health end points (usually GI illness) in relation to water exposure (usually 

swimmers vs. non-swimmers). 

Epidemiology Studies of Inland Recreational Waters

This section compares select epidemiological studies to explore differences in the association of 

indicators with health effects in inland and coastal waters and in coastal waters impacted by 

different fecal pollution sources. Although the intent of this report is not comparison of 

epidemiological study findings for coastal waters, those studies constitute the only information 

available for judging the impact of source on indicator-illness relationships. Because it has been 

suggested that source, not setting (inland vs. coastal) is the most important factor determining the 

association between indicator level and health effects, the coastal epidemiological studies for 

waters impacted by different sources are reviewed and reported.

Compared to marine waters, a relatively small number epidemiology studies have been 

conducted for inland recreational sites. Completed epidemiology studies for inland waters are 

summarized in Table 1. Although Wade et al. (2006, 2008) and Heaney et al. (2009) report and 

discuss the results of EPA’s Great Lakes epidemiology studies at inland freshwater recreational 

sites, these are defined as coastal waters under the CWA and are not summarized in this report 

(see USEPA, 2009 and WERF, 2009). It is important to note that the Great Lakes epidemiology 

studies reported the association of GI illness risk with increasing enterococci density as 

measured by quantitative polymerase chain reaction (QPCR; a molecular-based ―rapid‖ detection 

method), whereas all of the studies summarized in Table 1 used culture-based methods for 

detection of FIB. Although the Chicago Health, Environmental Exposure, and Recreation Study 

(CHEERS) PC epidemiology study (see http://www.cheerschicago.org/ for further information) 

is using QPCR and culture-based methods for FIB detection, its data and findings were not 

available for assessment in this report.

Collectively, these epidemiology studies indicate the following: 

1. E. coli, followed by enterococci, are predictive of GI illness rates in inland waters 

impacted by human fecal pollution.

2. When sites are impacted POTW effluent, data from freshwater inland and coastal sites 

may be pooled (i.e., indicator performance is the same for coastal and inland waters) 

when the sites are impacted by POTW effluent—even when other fecal sources also 

impact the study site (see Marion et al., 2010). In studies of freshwater inland and coastal 
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Table 1. Summary of Completed Epidemiological Studies of Inland Waters

Study Setting(s) and Sources Study Type Findings

Marion et al. 

(2010)

Impounded surface water (human-made flood control 

reservoir) in Ohio. Suspected fecal pollution sources 

included POTW discharges to lake tributaries, failing home 

septic systems, runoff from row crop agriculture, runoff from 

natural areas (wildlife).

PC E. coli density significantly associated with elevated odds of 

GI and highly credible GI (HCGI) illness. E. coli densities 

based on a single sample taken on study days.

Illness rates observed in this study similar to those observed 

by Dufour et al. (1984) in the studies used to develop EPA’s 

current (1986) freshwater criteria. Those studies included a 

large-scale study of an inland site (Keystone Beach).

Linear regression of observed incidence of excess HCGI with 

E. coli density resulted in the relation:

HCGI/1000 0.059 10.36log10 EC

where HCGI is the number of highly credible GI illnesses and 

EC is E. coli density as measured by membrane filtration, 

expressed in CFU/100 mL.

Epibathe 

(2009a,b)

Four recreational sites at two inland rivers in Hungary. No 

information provided regarding sources of fecal pollution, 

though all of the beaches complied with the EU mandatory 

bacteriological criteria for bathing waters and were therefore

considered as representative of compliant European 

beaches.

RCT Excess risk of gastroenteritis (GI illness) was 12% higher 

among bathers compared to non-bathers (baseline risk), but 

not statistically significant.

The risk of GI illness was markedly higher when bathers 

exposed to >200 enterococci (CFU/100 mL) compared with 

those exposed to less enterococci; however, there was a lack 

of strong evidence of any dose-response relationship 

between GI illness and enterococci levels.

The association was clearer for E. coli and GI illness, though 

the dose-response curve did not exhibit a consistent trend of 

increasing incidence of illness with increasing E. coli density. 

Results suggest that E. coli might be a more appropriate 

indicator for predicting risk of GI illness in fresh recreational 

bathing waters than enterococci.
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Study Setting(s) and Sources Study Type Findings

Wiedenmann 

et al. (2006)

Observations were collected at five inland sites in Germany, 

described below

Setting Suspected fecal pollution 

source(s)

Small inland lake, 

groundwater fed, rural 

setting

Waterfowl, bather 

shedding

Large inland lake, surface 

water fed, high bather 

density, near large 

urbanized area

Tertiary treated sewage, 

CSO discharges, 

agricultural runoff, bather 

shedding

Small inland lake, 

groundwater fed, rural 

setting

Waterfowl, bather 

shedding

Blind arm of a stream, 

urban environment

Urban runoff, CSO 

discharges, waterfowl

Groundwater lake in an 

urban environment

Overpopulation with 

waterfowl

RCT Based on analysis of no observed adverse effect levels 

(NOAELs) for pooled data from all the sites, recommended 

water quality guidelines are as follows:

Indicator Recommended water 

quality guideline

E. coli 100

Enterococcus 25

Somatic coliphage 10

Clostridium perfringens 10

NOAELs not dependent upon the choice of GI illness 

definition (three illness definitions were compared) but did 

depend upon the definition of exposure and the choice of 

indicator organism

Lee et al. 

(1997)

An inland concrete water channel bypassing a lock on a 

lowland river (Trent River) in the U.K. and used for whitewater recreation (canoeists and rafters). River received

treated sewage and during heavy rainfall, untreated sewage 

from stormwater overflows.

PC Water samples collected for culturable E. coli, enterococci, Fspecific RNA bacteriophage, sulphite reducing clostridia, and 

enteroviruses. 

Variables significantly associated with an increased risk of GI 

illness included swallowing water and levels of F-specific 

RNA bacteriophage. Notably, being a regular facility user 

was associated with a decreased risk of GI illness (though 

immunity was considered unlikely). 

Fewtrell et al. 

(1992)

Two inland recreational water sites used for white-water 

recreation: (A) an artificial concrete channel diverting water 

around a weir in a multiple POTW-impacted lowland river; (B) 

an upland impound that was considered to be pristine.

PC Site A had significantly higher counts of fecal coliforms and 

fecal streptococci (but not total staphylococci or 

enteroviruses) than site B.

Site A had significantly higher incidences of GI and upper 

respiratory symptoms than site B canoeists or non-exposed 

controls (spectators). 

Frequency in reporting of all symptom groups was 

significantly higher at 5 to 7 days for site A vs. site B 

canoeists and this excess persisted at one month for GI 

symptoms and skin symptoms. ―Like seawater bathers, freshwater canoeists can be made ill by sewage contamination.‖
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Study Setting(s) and Sources Study Type Findings

Calderon 

(1991)

Small inland pond formed behind impounded surface waters. 

Setting described as semi-rural. Primary fecal pollution 

sources believed to be runoff from undeveloped lands, 

swimmer loads. Investigations prior to the study indicated no 

point sources or human pollution sources contributing to the 

pond.

PC Swimmers had a significantly higher probability of GI illness 

than non-swimmers, but no association found between 

indicator density (enterococci, E. coli, Staphylococci, 

Pseudomonas aeruginosa) and incidence of GI illness 

among swimmers.

Ferley et al. 

1989

Ardeche river basin (south of France), samples collected at 5 

beaches (2 considered most polluted, 2 intermediate, 1 least) 

used for recreation. ―Urban domestic sewage, the main 

source of pollution, entered the river untreated at the time of 

the study...‖ 

RC 

(retrospective 

cohort)

Swimmers had significantly higher incidence of self-reported 

GI illness than non-swimmers. Fecal streptococci 

(enterococci) best correlated to GI illness. Swimmers also 

suffer skin, and ear, nose, throat (but not respiratory or eye) 

ailments much more frequently than non-swimmers, which 

was well correlated with the concentration of

fecal coliforms, Aeromonas, and Pseudomonas.

Seyfried et al. 

(1985a,b)

Ten lakes in Ontario, Canada. Papers do not state which or 

how many of the beaches were on Lake Ontario and how 

many were on inland lakes, but some may be assumed to be 

inland waters. In analyses setting (inland vs. coastal) is not 

included as a factor. Although possible sources of fecal 

pollution are not described, WERF (2009) notes some were 

likely impacted by WWTP effluent discharges. 

PC Swimmers had a significantly higher probability of GI illness 

than non-swimmers. Linear relationships between the logit of 

illness probability and logarithm of indicator density proposed 

for three indicator organisms:

total staphylococci, 

fecal coliforms, and

fecal streptococci

DuFour (1984) Keystone Lake, 15 miles from Tulsa, OK. Two beaches on 

Keystone Lake studied over two recreational use seasons. In 

the first study year a wastewater treatment plant discharged 

unchlorinated effluent to the lake. In the second study year 

the WWTP chlorinated effluent.

PC Data from both study years pooled with data from two Lake 

Erie beaches and log-linear relationships between HCGI and 

both E. coli and Enterococcus density derived. Note that 

regression analyses used averaged data, not data from 

individual study days.
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3. sites used for development of the 1986 AWQC indicator level-illness rate data were 

pooled. Those data have the same trend and are generally compatible with a more recent 

PC study of a human-impacted inland site by Marion et al. (2010).

4. For both inland and coastal settings indicator organism densities are not necessarily 

related to increased risk of GI illness (regardless of how GI illness is defined) when the 

fecal impact is known or suspected to be non-human. This contention is supported by 

findings of no illness-indicator relationship in studies of inland waters not impacted by 

human sources (Calderon et al., 1991) and coastal waters not impacted by human sources 

(Colford et al., 2007; Fleisher et al., 2010). Again, the key features in all of these 

epidemiology studies is a non-human fecal pollution source, not an inland or coastal 

setting.

These observations support the extension of criteria developed in epidemiology studies of 

POTW-impacted Great Lakes waters to POTW-impacted inland waters. They do not provide 

sufficient information to assess extension of indicator organism density-health risk relationships 

when fecal impacts are non-human. 

Note that in the studies by Wiedenmann et al. (2006) and Seyfried et al. (1985a,b), the authors 

assumed that observed illness rates and indicator densities for POTW- and non-POTW-impacted 

waters could be pooled. The findings of other epidemiological studies indicate this pooling 

should not be done without statistical analysis of the data. 

In epidemiological studies of non-POTW impacted-waters there is frequently no association 

observed between indicator density and health risk. This was true for an epidemiology study of 

an impounded inland water (pond) with no known human fecal pollution impacts (Calderon, 

1991). Similarly, no or limited association of indicator organisms with GI illness has also been 

observed for a bird-impacted coastal beach (Colford et al., 2007), and a subtropical coastal 

marine beach most likely impacted by dog and human non-point sources of fecal pollution 

(Abdelzaher et al., 2010; Fleisher et al., 2010; Sinigalliano et al., 2010). Results from a study by 

Haile et al. (1999) of stormwater impacts on illness rates at a coastal beach are difficult to 

interpret (WERF, 2009). Presuming fecal pollution source is the dominant feature determining 

the health effects observed for recreational sites, epidemiological studies conducted to date 

(1) do not support extending criteria derived for POTW-impacted waters to non-POTWimpacted waters and

(2) provide no information on the relationship between the level of traditional indicators and 

incidence of illness for sites not impacted by humans fecal pollution, despite a finding 

common to all studies that swimmers have higher incidences of illness than nonswimmers.

Non-Epidemiological Studies of Inland Settings 

The fecal pollution sources most likely to impact U.S. recreational sites include the following:

point-source human pollution from POTW effluent;
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diffuse human pollution from poorly treated sewage from on-site septic systems, small 

sewage treatment systems, CSOs, SSOs, sewage spills, and leaking sewage conveyance 

systems;

runoff from livestock operations;

runoff from areas impacted by companion animals; and

runoff from areas impacted by wildlife.

As described by recent QMRAs by Soller et al. (2010) and Schoen and Ashbolt (2010), human, 

cattle, swine, chicken and gull feces have different characteristic occurrences and abundances of 

indicator organisms and pathogens. Further, the pathogens occurring in animal feces frequently 

differ from those in human feces in their ability to initiate infection and subsequent illness in 

exposed humans. Because illnesses are ultimately caused by pathogens, not fecal indicator 

organisms, it is likely that the rates of illnesses arising from exposure to fecal pollution in 

recreational waters from different animal sources also differ. Further, because indicator densities 

differ among feces from different animals, it is likely that indicators levels will be associated 

with different illness incidences for different fecal pollution sources.

The hypothesis that a given indicator level is associated with different risks for different fecal 

pollution sources was tested by Soller et al. (2010) and Schoen and Ashbolt (2010). Those 

QMRA studies used reported indicator and pathogen densities from peer reviewed studies to 

develop characteristic ranges describing the occurrence and abundance of pathogens in treated 

sewage, untreated sewage, gull feces, cattle feces, swine feces, and chicken litter. Key pathogens 

assumed to occur in animal feces were the bacteria Salmonella, E. coli O157:H7, and 

Campylobacter; the protozoan pathogens Giardia and Cryptosporidium; and for human fecal 

pollution—norovirus (Soller et al., 2010). The studies determined that an indicator level of 35 

CFU of enterococci/100 mL (i.e., the current numeric criteria for marine recreational waters 

[USEPA, 1986]) is associated with roughly the same range of risks for indicator organisms 

originating from fresh human or cattle fecal pollution. However, Soller et al. (2010) determined 

that the risks associated with exposure to the same indicator levels but from fresh gull, chicken, 

or pig feces appears to be substantially lower than waters impacted by human fecal sources.

They also concluded that their QMRA results are consistent with the findings from epidemiology 

studies that show that illness risk associated with non-sewage-impacted beaches appears to 

depend on the source of contamination. 

Catchment scale modeling provides an alternative, non-epidemiological approach for relating 

fecal source and other site features with fecal indicator organisms with health risks. Till et al. 

(2008) conducted a large-scale sampling and modeling effort to (1) evaluate the ability of E. coli

to predict the presence of key pathogens and (2) determine an E. coli density at which actions 

should be taken. That study demonstrated that the degree of association between E. coli and the 

key pathogens differed among sites and, at individual sites, differed by season. Catchment types 

evaluated by Till and colleagues were those primarily impacted by birds, dairy or sheep 

operations, impacted by urban runoff, and undeveloped catchments. The authors reported that 

the bird catchments tended to be the most contaminated, followed by catchments with dairy 

impacts—despite the relatively infrequent observation of Campylobacter in the dairy 

catchments. The forested catchment was associated with the lowest level of contamination. In 

all cases, regression modeling demonstrated that catchment type was the most important factor 
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August 2010 20

governing the occurrence of the indicators and pathogens. Water quality features such as 

turbidity were also found to be predictive of levels of indicators and pathogens, but less 

important than catchment type.

Ferguson et al. (2009) developed a comprehensive a dataset describing the occurrence and 

abundance of E. coli, Cryptosporidium, and Giardia in all potential sources that could contribute 

to recreational waters. The authors noted that quantifying the ranges and variability of pathogens 

and indicators contributed by fecal pollution sources is a first step in construction a predictive 

model of microbial loads generated within and exported from catchments. This catchment 

modeling effort recognizes the importance of source in connecting indicator organism density to 

health risk. Additionally, it describes and demonstrates an approach that accounts for the 

contribution of multiple indicator and pathogens sources to a receiving water. In that regard, the 

authors found that contributions from multiple sources are likely for the vast majority of 

recreational sites.

Ferguson et al. (2009) noted that the virulence of pathogens in humans and their prevalence in 

the host animals are lower in wildlife than in domestic livestock animals, with the exception of 

wildlife living in close proximity to human fecal pollution. Despite this general observation, 

wildlife may still be an important source of zoonotic pathogens on a catchment-by-catchment 

basis. For example, beaver and muskrats are well known shedders of Giardia to the aquatic 

environment. 

Livestock is often kept for stocking purposes at much higher levels that can be maintained for 

native and feral species that do not receive supplemental feeding (Ferguson et al., 2009). 

Although there are established farm management practices for limiting pathogen prevalence 

(e.g., administration of probiotics), high stocking densities provide the potential for increased 

pathogen transmission between animals and as noted above, the prevalence of pathogens is often 

much higher in domestic species than in wildlife. Pathogens in livestock manures can persist for 

long periods in the environment, depending on the manure handling practices at a given 

operation. Fecal matter persistence is a special concern in cold-climate, where pathogens can 

persist throughout the winter to be released from land along with snow melt or during 

precipitation events. Land application requirements and best management practices may regulate 

the land application of manures on frozen or snow-covered ground.

Fecal indicator and pathogen sources in catchments that contain urban development are primarily 

of human origin, but fecal loads from companion animals (e.g., cats and dogs) may also be 

significant (Ferguson et al., 2009). Human sources include sewage effluent, septic leachate from 

on-site sewage disposal systems, stormwater, and direct deposition from human recreation 

activities in rivers and storages. These sources may be categorized as treated sewage (POTW 

effluent) and untreated (all other sources). Because treatment plants are designed to meet 

effluent limits, indicator and bacterial pathogens in treated human sewage is typically 

characterized by indicator organism densities much lower than those of primary sewage or other 

human sources (NRC, 2004).
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Summary 

This review supports the extension of criteria developed in epidemiology studies of POTWimpacted Great Lakes waters to POTW-impacted inland waters but does not provide sufficient 

information to assess extension of indicator organism density-health risk relationships when the 

fecal impacts are non-human. Both epidemiological and modeling studies indicate that fecal 

pollution source is the most important determinant of the relationship between indicator levels 

and health effects at a site. Because no epidemiological studies to date have demonstrated a 

relationship between illness and indicator level for sites impacted by non-human fecal pollution, 

the most promising avenue for exploring alternative criteria and risk levels for those sites is 

modeling studies. 

In conjunction with the findings of inland recreational water epidemiological studies, QMRA 

and catchment modeling studies demonstrate that indicators perform differently for sites with 

different fecal pollution sources. However, this finding cannot be applied in any direct way to 

assess whether water quality criteria for inland waters should differ from those developed for 

coastal waters. Although it has been suggested that inland waters are, in general, more 

associated with rural land use (Dorevitch et al., 2010; WERF, 2009), the authors know of no data 

source allowing this assertion to be tested. In most cases, it is likely that recreational sites are 

impacted by fecal pollution from multiple sources and the impact at a specific site is an 

aggregate of the impacts from all sources within the drainage to the site (Ferguson et al., 2009; 

Till et al., 2008). Recent QMRA studies have determined GI illness risks associated with 

exposure to fresh human or cattle feces in recreational waters may not be substantially different, 

whereas these risks appear to be substantially lower for recreational waters impacted by gull, 

chicken, and pig wastes.
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Occurrence of Fecal Indicator Bacteria in Inland and Coastal Settings

This section summarizes studies of the occurrence of FIB in inland and coastal waters and 

evaluates whether they are different. It also compares and contrasts FIB occurrence in both 

settings that is attributable to rainfall and runoff events (event-scale variability). 

Data Summary

A literature review (see also Appendix B) revealed a substantial number of studies that reported 

the occurrence of FIB in a wide variety of inland and coastal water bodies. These are 

summarized in Tables 2 through 5 for E. coli, enterococci, fecal coliform, and fecal 

streptococcus and total coliform, respectively. Tables 2 through 5 summarize key features of 

each of the studies, including the setting (which is categorized as coastal freshwater, coastal 

marine water, estuarine, inland flowing water main stem, inland flowing water in a small reach, 

or inland non-flowing water), the number of samples, the duration of the study, the geometric 

mean, minimum and maximum reported values, the microbiological method used, and brief 

explanatory notes for each study. 

To facilitate interpretation of the data presented in Tables 2 though 5, graphical summaries are 

provided in Figures 5 through 9 for E. coli, enterococci, fecal coliform, fecal Streptococcus, and 

total coliform, respectively. In Figures 5 through 7 and 9, the geometric mean values of FIB, and 

the minimum and maximum reported values for each study summarized in Tables 2 through 5

are presented (each study is shown as a vertical line) within the aforementioned water body 

categories. Each water body type is represented by a different symbol. Note that in Figure 8 for 

fecal Streptococcus, only the geometric mean values are illustrated. To develop these graphical 

summaries several simplifying assumptions were used. For example, minimum or maximum 

values that were reported below or above reportable limits were assumed to be present at those 

limits; thus, a value that was reported as <10 was assumed to be equal to 10, and >10,000 was 

assumed to be equal to 10,000. Furthermore, geometric mean values only are shown for studies 

that reported standard deviations but not minimum or maximum values. 

Presuming that it is reasonable to directly compare the reported occurrence of FIB across the 

various types of water bodies of interest, a qualitative inspection of the summarized study data 

presented in Tables 2 through 5 and Figures 5 through 9 indicates the following:

The occurrence of E. coli is not substantially different between the study results reported 

for coastal marine and estuarine waters compared to those reported for inland flowing 

(main stem and smaller reaches) and inland non-flowing waters.

Enterococci occurrence is slightly elevated in study results for coastal fresh and marine 

waters compared to those reported for estuarine, inland flowing (main stem and smaller 

reaches), and inland non-flowing waters.

The occurrence of fecal coliform is not substantially different between results reported 

for coastal marine and estuarine waters compared to those reported for inland flowing 

(main stem and smaller reaches) and inland non-flowing waters.
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Table 2. Studies of E. coli Occurrence

Indicator Study Setting # samples Study 

Duration

Geometric 

Mean

Min Max Methods Notes

E. coli Fattal. et al. (1987) Coastal marine waters 77 Summer 13 0 559 Not stated 

(reported as 

CFU)

Reported values are based on data collected at 3 beaches on the 

Mediterranean Sea

Gersberg et al. (2006) Coastal marine waters 14 wetweather, 6 

dry weather

2 yrs 41 601,000 MPN Samples taken at discharge of highly impacted river

Mill et al. (2006) Estuary NA 1 mo 0 1300 Membrane 

filtration

Estuary has known high FC concentration

Mill et al. (2006) Estuary NA 1 mo 0 200 Membrane 

filtration

Estuary has known high FC concentration

Buckwalter et al. (2006) Inland flowing- main stem 135 1 yr 123 <10 910 Membrane 

filtration

Upstream reach of the Monongahela River

Buckwalter et al. (2006) Inland flowing -small 24 1 yr 570 10 13,000 Membrane 

filtration

Tributary to the Monagahela River, presumed urban

Buckwalter et al. (2006) Inland flowing -small 24 1 yr 80 <10 30,000 Membrane 

filtration

Tributary to the Monongahela River, presumed urban

Byappanahalli et al. (2003(a)) Inland flowing -small 375 2 yrs 486 NA NA MPN, 

Membrane 

filtration

Mean is based on data from 7 upstream sites averaged; significant 

seasonal variation

Cinotto (2005) Inland flowing -small 10 One baseflow 

sample, all 

sites

195 50 1210 Membrane 

filtration

For baseflow samples only. Median reported (instead of geometric 

mean). High spatial variability in reach.

Cinotto (2005) Inland flowing -small 45 One baseflow 

sample, all 

sites

960 <1 11,000 Membrane 

filtration

For baseflow samples only. Median reported (instead of geometric 

mean). High spatial variability in reach.

Crowther et al. (2002) Inland flowing -small see duration 

note

Samples at 2-

3 days 

interval, 1-2 

mos

Baseflow 

mean = 6200

High flow 

mean = 

140,000

Membrane 

filtration

Land use is primarily livestock grazing, multiple types

Crowther et al. (2002) Inland flowing -small see duration 

note

Samples at 2-

3 days 

interval, 1-2 

mos

Baseflow 

mean = 3100

High flow 

mean = 

200,000

Membrane 

filtration

Land use is primarily livestock grazing, multiple types

Donnison et al. (2004) Inland flowing -small 52 2 years, 

fortnightly

Pastoral 

lands, 

summer 

median = 

1070

Upslope 

stream, newly 

planted, 

summer 

median = 68

Colilert 

(MPN)

Upslope catchment were believed relatively free of human impacts. Large 

seasonal variation observerd. EC concentration surprisingly high in 

unimpacted drainages

Giddings and Oblinger (2004) Inland flowing -small High flow and 

low flow 

samples 

collected

2 days 140 29,000 Membrane 

filtration

Land use is primarily forested and agriculture. Figure 5 shows minimal 

difference in concentrations observed in tributaries and main stem

Hyer et al. (2007) Inland flowing -small See max and 

min

2 yrs Low flow = 12 Storm flow = 

34

Membrane 

filtration

Data reported are chosen because stream order is low and only impacts 

are wildlife

Hyer et al. (2007) Inland flowing -small See max and 

min

2 yrs Low flow = 23 

(n=8)

Storm flow = 

176 (n=4)

Membrane 

filtration

Data reported are chosen because stream order is higher site is 

designated “recreational”

Petersen et al. (2005) Inland flowing -small 147 4 yrs 4664 <10 >10,000 IDEXX Numerous sites on Bayou samples. EC increased with stream mile.

Tiefenthaler et al. (2008) Inland flowing -small Different # 

samples at 

each site

Dry season 2.06 138.2 Colilert Reported values are for highest and lowest observed geometric mean 

among sites sampled

Vidon et al. (2008) Inland flowing -small See min and 

max

2.5 yrs Baseflow = 

682 – 3396 

(n=22)

High flow = 

2759 – 5759 

(n=13)

MPN Land use in drainages is mainly agricultural (row crops)

Whitman et al. (2008) Inland flowing -small ? ? 20.4 1412.5 Membrane 

filtration

Only data prior to building a pond reported. Pond (after construction) was 

a sink of EC during dry weather and a source during some wet weather

Hoyer et al. (2006) Inland nonflowing waters 3107 1 yr 70 0 7400 Membrane 

filtration

Data reported were chosen because they were for one entire year of 

sampling
U.S. Environmental Protection Agency

August 2010 24

Table 3. Studies of Enterococci Occurrence

Indicator Study Setting # samples Study 

Duration

Geometric 

Mean

Min Max Methods Notes

Enterococcus Haugland et al. (2005) Coastal fresh 47 2 mos 27 NA NA Membrane 

filtration

Reported data are composite for one of two beaches studied

Haugland et al. (2005) Coastal fresh 47 2 mos 143 NA NA QPCR Reported data are composite for one of two beaches studied

Wade et al. (2008) Coastal fresh 1359 2 summers 770 0.05 376,000 QPCR Data for all beaches used

Colford et al. (2007) Coastal marine waters 1897 6 days 29 ND 57,940 Chromogenic 

substrate

Samples were taken hourly. Beach was in southern CA

Colford et al. (2007) Coastal marine waters 790 6 days 65 ND 141,053 QPCR Samples were taken hourly. Beach was in southern CA

Fattal. et al. (1987) Coastal marine waters 77 Summer 20 0 450 Not stated 

(reported as 

CFU)

Reported values are based on data collected at 3 beaches on the 

Mediterranean Sea

Gersberg et al. (2006) Coastal marine waters 14 wetweather, 6 

dry weather

2 yrs 72 754,000 MPN Samples taken at discharge of highly impacted river

Lipp et al. (2001b) Estuary 12 1 yr 3 <1 60 Membrane 

filtration

Data reported were chosen because of 12 sites sampled, this had the 

highest conc.

Lipp et al. (2001b) Estuary 12 1 yr 79 19 395 Membrane 

filtration

Data reported were chosen because of 12 sites sampled, this had the 

highest conc.

Mill et al. (2006) Estuary NA 1 mo 1 68 Membrane 

filtration

Estuary has known high FC concentration

Mill et al. (2006) Estuary NA 1 mo 19 88 Membrane 

filtration

Estuary has known high FC concentration

Buckwalter et al. (2006) Inland flowing- main stem 135 1 yr 15 <10 320 Membrane 

filtration

Upstream reach of the Monongahela River

Buckwalter et al. (2006) Inland flowing- main stem 143 1 yr 30 <10 3,400 Membrane 

filtration

Downstream reach of the Monongahela River (Pittsburgh)

Chandramouli et al. (2007) Inland flowing- main stem 1165 NA 346 1 17,000 NA Mean appears to be arithmetic mean (not explicitly stated)

He et al. (2007) Inland flowing- main stem 171 2 yrs 108 10 270 MPN Heavily impacted waters (urban stormwater)

Buckwalter et al. (2006) Inland flowing -small 24 1 yr 305 <10 11,000 Membrane 

filtration

Tributary to the Monagahela River, presumed urban

Buckwalter et al. (2006) Inland flowing -small 24 1 yr 50 <10 9,600 Membrane 

filtration

Tributary to the Monongahela River, presumed urban

Buckwalter et al. (2006) Inland flowing -small 24 1 yr 2,200 70 180,000 Membrane 

filtration

Tributary to the Monongahela River, presumed urban

Cinotto (2005) Inland flowing -small 10 One baseflow 

sample, all 

sites

405 230 12,000 Membrane 

 filtration

For baseflow samples only. Median reported (instead of geometric 

 mean). High spatial variability in reach.

Cinotto (2005) Inland flowing -small 45 One baseflow 

sample, all 

sites

2800 <1 36,000 Membrane 

filtration

For baseflow samples only. Median reported (instead of geometric 

 mean). High spatial variability in reach.

Tiefenthaler et al. (2008) Inland flowing -small Different # 

samples at 

each site

Dry season 12.74 164.6 Enterolert Reported values are for highest and lowest observed geometric mean 

among sites sampled

He et al. (2007) Inland nonflowing waters 58 2 yrs 44,000 270 160,000 MPN Heavily impacted waters (urban stormwater)
U.S. Environmental Protection Agency

August 2010 25

Table 4. Studies of Fecal Coliform Occurrence

Indicator Study Setting # samples Study 

Duration

Geometric 

Mean

Min Max Methods Notes

Fecal

Coliform

Bordalo Coastal marine waters 184 3 weeks 4720 300 35,600 Membrane 

filtration

Urban beach

Bordalo (2003) Coastal marine waters 184 3 weeks 661 50 6625 Membrane

filtration

Urban beach

Colford et al. (2007) Coastal marine waters 1897 6 days 25 ND 48,000 Membrane 

filtration and 

chromogenic 

substrate

Samples were taken hourly. Beach was in southern CA

Crowther et al. (2001) Coastal marine waters 77 Uncertain 200 NA NA Membrane 

filtration

Samples taken in bathing waters. Data after sewer repairs reported

Crowther et al. (2001) Coastal marine waters 77 Uncertain 920 NA NA Membrane 

filtration

Samples taken in bathing waters. Data after sewer repairs reported

Fattal. et al. (1987) Coastal marine waters 77 Summer 46 1 650 Not stated 

(reported as 

CFU)

Reported values are based on data collected at 3 beaches on the 

Mediterranean Sea

Lipp et al. (2001b) Estuary 12 1 yr 4 4 320 Membrane 

filtration

Data reported were chosen because of 12 sites sampled, this had the 

highest conc.

Lipp et al. (2001b) Estuary 12 1 yr 174 64 424 Membrane 

filtration

Data reported were chosen because of 12 sites sampled, this had the 

highest conc.

Buckwalter et al. (2006) Inland flowing- main stem 135 1 yr 135 <10 690 Membrane 

filtration

Upstream reach of the Monongahela River

Buckwalter et al. (2006) Inland flowing- main stem 143 1 yr 360 <10 50,000 Membrane 

filtration

Downstream reach of the Monongahela River (Pittsburgh)

Buckwalter et al. (2006) Inland flowing- main stem 143 1 yr 260 <10 39,000 Membrane 

filtration

Downstream reach of the Monongahela River (Pittsburgh)

Chandramouli et al. (2007) Inland flowing- main stem 1165 NA 145 1 12,000 NA Mean appears to be arithmetic mean (not explicitly stated)

He et al. (2007) Inland flowing- main stem 171 2 yrs 360 20 1300 MPN Heavily impacted waters (urban stormwater)

Buckwalter et al. (2006) Inland flowing -small 24 1 yr 435 10 13,000 Membrane 

filtration

Tributary to the Monagahela River, presumed urban

Buckwalter et al. (2006) Inland flowing -small 24 1 yr 100 <10 34,000 Membrane 

filtration

Tributary to the Monongahela River, presumed urban

Buckwalter et al. (2006) Inland flowing -small 52 1 yr 17000 220 410,000 Membrane 

filtration

Tributary to the Monongahela River, presumed urban

Buckwalter et al. (2006) Inland flowing -small 52 1 yr 10500 70 510,000 Membrane 

filtration

Tributary to the Monongahela River, presumed urban

Edwards et al. (1997) Inland flowing -small Unknown 3 yrs, storm 

and base 

samples

310 NA 75,000 Membrane 

filtration

Uses are mainly pastoral and forested. One site (out of 5) reported here. 

Sites were similar. Seasonal variation observed.

Giddings and Oblinger (2004) Inland flowing -small High flow and 

low flow 

samples 

collected

2 days 92 27,000 Membrane 

filtration

Land use is primarily forested and agriculture. Figure 5 shows minimal 

difference in concentrations observed in tributaries and main stem

Obiri-Danso and Jones (1999) Inland flowing -small 24 2 yrs 1333 NA NA MPN and 

Membrane 

filtration

Sample sites were beaches on inland flowing waters. Data are for one of 

two sample years

Petersen at al. (2006) Inland flowing -small 625 5 yrs 1570 NA 200,000 Unknown Long-term trends may be found in paper. Data since 2000 reported here.

Petersen at al. (2006) Inland flowing -small 410 5 yrs 4623 NA 200,000 Unknown Long-term trends may be found in paper. Data since 2000 reported here.

Bragg and Clark (1992) Inland nonflowing waters 14 7 months 13 std dev = 42 Membrane 

filtration

Reservoir with recreational use and drinking water source

Bragg and Clark (1992) Inland nonflowing waters 18 7 months 2097 std dev = 

3145

Membrane 

filtration

Reservoir with recreational use and drinking water source

He et al. (2007) Inland nonflowing waters 58 2 yrs 62,000 70 160,000 MPN Heavily impacted waters (urban stormwater)

Francy et al. (2000) Inland waters, multiple 

watersheds

136 7 mos 280 <1 16,000 Membrane 

filtration

Data base is composite of results from NAWQA sites across the 

continental US
U.S. Environmental Protection Agency

August 2010 26

Table 5. Studies of Fecal Streptococcus and Total Coliform

Indicator Study Setting # samples Study 

Duration

Geometric 

Mean

Min Max Methods Notes

Fecal

Streptococcus

Crowther et al. (2001) Coastal marine waters 58 Uncertain 110 NA NA Membrane 

filtration

Samples taken in bathing waters. Data after sewer repairs reported

Crowther et al. (2001) Coastal marine waters 52 Uncertain 240 NA NA Membrane 

filtration

Samples taken in bathing waters. Data after sewer repairs reported

Crowther et al. (2002) Inland flowing -small see duration 

note

Samples at 2-

3 days

interval, 1-2 

mos

Baseflow 

mean = 1600

High flow 

mean = 

94,000

Membrane 

filtration

Land use is primarily livestock grazing, multiple types

Crowther et al. (2002) Inland flowing -small see duration 

note

Samples at 2-

3 days

interval, 1-2 

mos

Baseflow 

mean = 260

High flow 

mean = 

16,000

Membrane 

filtration

Land use is primarily livestock grazing, multiple types

Edwards et al. (1997) Inland flowing -small Unknown 3 yrs, storm 

and base 

samples

190 NA 61,000 Membrane 

filtration

Uses are mainly pastoral and forested. One site (out of 5) reported here. 

Sites were similar. Seasonal variation observed.

Obiri-Danso and Jones (1999) Inland flowing -small 24 2 yrs 182 NA NA MPN and 

Membrane 

filtration

Sample sites were beaches on inland flowing waters. Data are from one 

of two sample years.

Total 

Coliform

Bordalo (2003) Coastal marine waters 184 3 weeks 8790 150 72000 Membrane 

filtration

Urban beach

Bordalo (2003) Coastal marine waters 184 3 weeks 1141 100 9500 Membrane 

filtration

Urban beach

Colford et al. (2007) Coastal marine waters 1897 6 days 102 ND 45,000 Membrane 

filtration and 

chromogenic 

substrate

Samples were taken hourly. Beach was in southern CA

Crowther et al. (2001) Coastal marine waters 59 Uncertain 320 NA NA Membrane 

filtration

Samples taken in bathing waters. Data after sewer repairs reported

Crowther et al. (2001) Coastal marine waters 58 Uncertain 1500 NA NA Membrane 

filtration

Samples taken in bathing waters. Data after sewer repairs reported

Chandramouli et al. (2007) Inland flowing- main stem 1165 NA 1598 1 25,000 NA Mean appears to be arithmetic mean (not explicitly stated)

Bragg and Clark (1992) Inland nonflowing waters 14 7 months 146 std dev = 348 Membrane 

filtration

Reservoir with recreational use and drinking water source

Bragg and Clark (1992) Inland nonflowing waters 18 7 months 34,761 std dev = 

77,902

Membrane 

filtration

Reservoir with recreational use and drinking water source

Hoyer et al. (2006) Inland nonflowing waters 3107 1 yr 2070 0 23,800 Membrane 

filtration

Data reported were chosen because they were for one entire year of 

sampling

Francy et al. (2000) Inland waters, multiple 

watersheds

115 7 mos 1200 <1 190,000 Membrane 

filtration

Data base is composite of results from NAWQA sites across the 

continental US
U.S. Environmental Protection Agency

August 2010 27

Reported density per 100mL

10-1

100

101

102

103

104

105

106

107

Coastal marine

Estuary

Inland flowing main

Inland flowing small

Inland nonflowing

Figure 5. Summary of Reported E. coli Densities in Various Water Types (data 

shown are minimum, geometric mean, and maximum values).

Reported density per 100mL

10-1

100

101

102

103

104

105

106

107

Coastal fresh

Coastal marine

Estuary 

Inland flowing main

Inland flowing small

Inland nonflowing

Figure 6. Summary of Reported Enterococci Densities in Various Water Types 

(data shown are minimum, geometric mean, and maximum values).
U.S. Environmental Protection Agency

August 2010 28

Reported density per 100mL

10-1

100

101

102

103

104

105

106

107

Coastal marine

Estuary

Inland flowing main

Inland flowing small

Inland nonflowing 

Figure 7. Summary of Reported Fecal Coliform Densities in Various Water Types 

(data shown are minimum, geometric mean, and maximum values).

Reported density per 100mL

10-1

100

101

102

103

104

105

106

Coastal marine

Inland flowing small

Figure 8. Summary of Reported Fecal Streptococcus Densities in Various Water 

Types (data shown are geometric mean values).
U.S. Environmental Protection Agency

August 2010 29

Reported density per 100mL

10-1

100

101

102

103

104

105

106

Coastal marine

Inland flowing main

Inland nonflowing

Figure 9. Summary of Reported Total Coliform Densities in Various Water Types 

(data shown are minimum, geometric mean, and maximum values).

Total coliform occurrence is not substantially different between coastal marine waters 

compared to inland flowing main stem and inland non-flowing waters. However, the 

amount of data available for this comparison is less than that for E. coli, enterococci, or 

fecal coliforms.

Very limited data are available to compare the occurrence of fecal Streptococcus in 

coastal waters compared to those for inland waters. Nevertheless, based on the data that 

are available, the occurrence of fecal Streptococcus is not substantially different between 

coastal and inland waters.

These qualitative comparisons and observations must be caveated because of several overarching 

factors. First, the reviewed studies used a wide variety of culture- and molecular-based methods, 

techniques, and/or tools, such as membrane filtration, most probable number (MPN) methods, 

and chromogenic substrate methods. None of the studies explored ranges of qPCR 

determinations of indicator density, which is likely to vary within different ranges than those 

observed in studies employing culture methods (Lavender and Kinzelman, 2009). Many studies 

did not specify or fully articulate their detection methods. The extent to which the FIB 

occurrence results—especially for studies using different methods or measurement units (e.g., 

MPN, CFU, cell equivalents, etc.)—can be compared accurately is not clear. Second, the extent 

to which variations in the sampling regimes influence the reported FIB occurrence results is not 

known. For example, several studies reported that temporal and spatial variability was 

substantial (e.g., based on seasonal effects and/or rainfall) and other studies appear to have 

established their monitoring protocol based on a fixed schedule (e.g., monthly samples). Third, 

the studies were conducted in locations with diverse fecal pollution sources. For example, the 
U.S. Environmental Protection Agency

August 2010 30

dataset comprises sources as diverse as urban storm water impacted sites, agricultural lands used 

for livestock grazing, and a watershed believed to be relatively free of human impacts. Thus, 

there are insufficient data available to unambiguously determine whether FIB level trends, if they 

exist, are primarily due to water type (inland or coastal) or predominant source of fecal 

contamination. 

Event-Scale Variability: Rainfall and Runoff

Rainfall and runoff effects on FIB density include loading (e.g., wash-off of indicators with 

surface flow, washout of indicators from beach sands or river bank sediments, initiation of CSO 

or SSO events) and dilution (Gentry et al., 2006; Vidon et al., 2008). The complex relationship 

between hydrology and indicator organism density frequently results in poor correlation between 

hydrologic variables (e.g., stream flow and precipitation) and indicator organism density, but 

better correlation between hydrologic variables and indicator load. As noted by Petersen et al. 

(2005), ―bacterial pollution is characterized in terms of concentrations, but concentration data 

may be misleading if not related to the flows from each source as loads are additive, while 

concentrations are not.‖ 

Inland Sites

Traister and Anisfeld (2006) noted that stream E. coli density response to storms was not simply 

related to precipitation and that response varied greatly between storms. They also reported that 

changes in E. coli density may be related to land use, with more urbanized stream reaches 

showing a smaller response (change in density) for a given storm than less urbanized reaches. 

The response of stream indicator density to rainfall events varies significantly from storm-tostorm (Dorner et al., 2007) and within storms (Baxter-Potter and Gilliland 1988; Jamieson et al., 

2005). During the early part of storms, wash-off of indicators into streams is high whereas loads 

are lower later in storms because surface sources of microorganisms are depleted (Traister and 

Anisfeld 2006; Dorner et al., 2007). In studies of FIB density changes in streams during storms, 

Edwards et al. (1997), Haack et al. (2003), and Jamieson et al. (2005) all also observed higher 

densities associated with the rising limb of the hydrograph. Jamieson and colleagues speculated 

that indicator densities are higher during the rising limb because there is a greater availability of 

particle-associated bacteria to be resuspended. 

Rainfall influences on indicator organism densities in inland streams and coastal sites located 

near the outlet of streams have been observed in relatively undeveloped watersheds as well as in 

watersheds dominated by storm water or POTW discharges. In an agriculture- and woodlanddominated watershed in Jersey, U.K., FIB density (total coliforms, E. coli, and Streptococcus) 

was strongly influenced by rain events at coastal and inland sites, with enterococci density 

increasing by more than three orders of magnitude at the outlet of the stream following a storm 

(Wyer et al., 1995). Wyer and colleagues concluded that indicator organism loading from 

captive birds (swans and ducks) played an important role in elevation of FIB densities during 

storm events in that particular watershed. Notably, the authors also reported that a significant 

reduction in indicator density downstream of the bird sources could be attributed to 

sedimentation. These studies provide further evidence of the complex interactions between 

precipitation, loading, and geography that give rise to temporal changes in FIB density.
U.S. Environmental Protection Agency

August 2010 31

The importance of individual fecal sources in determining the indicator density in a waterbody 

may also vary significantly with rainfall. For example, using combined water quality data and 

microbial source tracking (MST) data, Shehane et al. (2005) observed that a coastal stream in 

Florida was predominantly impacted by animal sources during a period of drought while being 

predominantly impacted by human sources during periods of normal precipitation. The authors 

demonstrated that a composite index based on measurements of multiple FIB was a better 

indicator of water quality and provided a better correlation with rainfall than the occurrence of 

any individual indicator organism. This finding is consistent with the observation that there are 

typically multiple sources influencing the microbial water quality of a given water body and that 

their relative importance changes temporally (Ferguson et al., 2009; Till et al., 2008).

Thresholds at which rainfall and runoff produce large changes in FIB density have been shown 

to differ between rivers and within a given river based on the precipitation conditions prior to a 

rainfall event. Coulliette and Noble (2008) found that for an estuary along the North Carolina 

coast, indicator organism (fecal coliform and Enterococcus) density was significantly different 

after storms with net precipitation of ≥2.5 cm than when rainfall was <2.5 cm. This difference 

was observed at stations relatively near the coast (within 250 m) and for stations further offshore. 

Coastal Sites

The duration of the effect a rainfall event has on the microbial water quality of a coastal site is 

variable. For a marine beach in harbors receiving storm water runoff from urbanized areas, Hose 

(2005) reported that rainfall during the previous 24 hours accounted for 5 to 10× more variability 

in FIB density using a regression models than rainfall in other time periods (previous 48 hours, 

22 hours, etc.). Chigbu et al. (2005) observed that in an estuary on the Gulf of Mexico, the time 

required for fecal coliform density in the estuary to fall to a geometric mean of 14 fecal 

coliforms (MPN) per 100 mL ranged from 0.3 to 12.9 days. Similarly, Haramoto et al. (2006)

found that E. coli levels in marine coastal sites fell to pre-storm levels ―within a few days‖ of the 

rain event in Tokyo Bay. The lag between a rainfall event and a subsequent change in indicator 

organism density at a coastal site may vary significantly with the orientation of the site to storm 

water outfalls, river outlets, or other point or contained sources of indicator organisms. Haack et 

al. (2003) noted that on the Grand Traverse Bay, Lake Michigan (which is considered a coastal 

water under the BEACH Act of 2000 and within this report), there was a 48 to 72 hour lag 

between rainfall and elevated E. coli density at southern shoreline beaches, but no such lag was 

observed for western and eastern shoreline beaches.

The influence of rainfall events on beach water quality along the California coast has been 

observed to be much higher near storm drains, particularly those in urbanized areas, and to 

persist for more than 36 hours after a large storm (Noble et al., 2003). The authors reported that 

following a large storm with total precipitation between 2.7 and 7.8 cm, 87% of beaches in close 

proximity to urban runoff outlets failed to meet California numeric WQS (10,000 MPN or CFU 

per 100 mL total coliforms; 400 MPN or CFU per 100 mL fecal coliforms; or 104 MPN or CFU 

per 100 mL enterococci) based on single samples. The extent of California shoreline exceeding 

one or more of these criteria following the storm was 10× greater than during dry weather 

conditions. Among samples with FIB levels exceeding the WQS, the measured indicator density 

was generally far greater than the standards. In contrast, exceedences during dry weather 
U.S. Environmental Protection Agency

August 2010 32

conditions tend to be only slightly above the standards. This study indicates both the importance 

of rainfall events on FIB occurrence in coastal sites and the persistence of effects of rainfall on 

microbial water quality for a significant period following the event. In other words, dilution 

cannot be assumed to completely mitigate rainfall effects at coastal sites or to ensure rapid return 

of FIB density to pre-storm levels.

Rainfall and runoff generate indicator organism loads from sands and sediments on beaches in 

addition to from external sources such as storm drains and stream discharges. Whitman et al. 

(2006) observed E. coli response to a rainfall event for hydrologically-connected sand, pore 

water, and lake water. E. coli density in all three media increased in the early stage of the 

rainfall event, with sand E. coli density falling more sharply and rapidly than in pore and lake 

water following the event. This observation indicates the potential for high loading of indicator 

organisms originating from beach sands or stream sediments early in storms, and lower loadings 

after sediments and sands are depleted of FIB, late in rainfall events. This observation is 

consistent with the findings of Yamahara et al. (2007) who observed mobilization of enterococci 

during a rising tide or due to wave action, followed by reduced loading as sediment indicator 

bacteria were depleted.

Summary: Event-Scale Indicator Variability

Event-scale variability is the single greatest variability (including both temporal and spatial 

variabilities) of fecal indicator organism density for coastal and inland waters, which vary in 

terms of hydrodynamics. During events, FIB densities at inland and coastal sites may undergo 

orders-of-magnitude changes. Events account for a large fraction of indicator organism loadings 

to source waters for drinking water, inland lakes and reservoirs, and coastal sites. For inland 

settings, indicator densities correlate poorly with rainfall amounts due to dependence of indicator 

response on factors such as antecedent rainfall (which relates to soil capacity to retain storm 

water and the number of indicator organisms available for runoff into receiving waters) and the 

input of FIB from sources such as CSO discharges. In general, FIB density peaks during the 

rising limb of the storm hydrograph when loading to the stream is high and streams are turbulent, 

promoting resuspension of sediment-associated indicators. Indicator densities also generally 

decline faster than the hydrograph after indicators are (temporarily) depleted. The time required 

for the indicator density in a flowing or impounded inland water body to recede to pre-storm 

levels is highly variable among drainages and even within a particular drainage. Similar trends 

have been observed for coastal sites—indicator densities rise quickly during storms due to 

loading from stormwater runoff, near-shore sands, and due to increased wave action and 

mobilization of indicators from sediments. Although dilution would presumably cause eventscale variability to be of less significance at coastal sites vs. inland streams, poor mixing in the 

vicinity of stream outlets and stormwater outfalls appears to contribute to extreme changes in 

indicators densities associated with events.

Summary

Based on a literature review of FIB occurrence in a wide variety of inland and coastal water 

bodies, and presuming that it is reasonable to directly compare these results, a qualitative 

inspection of the summarized study data indicates that there do not appear to be substantial 
U.S. Environmental Protection Agency

August 2010 33

differences between inland and coastal waters for E. coli, fecal coliforms, fecal Streptococcus

(enterococci), or total coliforms. The hydrodynamics of inland and coastal sites are different and 

are associated with apparent differences in the responses of indicator organism densities to 

precipitation events. These differences have clear implications with respect to implementation of 

new or revised recreational water quality criteria. Knowledge of the period(s) during which 

rainfall influences FIB density most significantly can inform when to conduct monitoring and 

when beaches should be closed or when to issue beach advisories in the event of adverse 

microbial water quality. Such information could be used in conjunction with monitoring and 

(predictive) modeling approaches for risk management approaches (USEPA, 2007a). The direct 

implications of event-scale variability on differences of FIB occurrence in inland and coastal 

settings for the development of new or revised recreational water quality criteria are less 

certain—both types of settings exhibit extreme variability in indicator organism density 

following significant rainfall. Although coastal sites may respond to storms later and for 

prolonged durations compared to inland sites, FIB responses at locations near tributary or storm 

water outfalls may be similar to inland waters responses. Insufficient data are currently available 

to evaluate whether FIB densities are correlated differently with health risks at inland and coastal 

sites during rainfall events (see Section 3). Similarly, insufficient data are currently available to 

assess whether pathogen-to-indicator ratios (see Section 6) change differently during rainfall for 

inland and coastal sites. 
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August 2010 34

Survival of Fecal Indicator Bacteria in Inland and Coastal Settings

In this section, the survival (inactivation, removal, predation or growth) of indicator organisms in 

coastal and inland settings is compared and contrasted. General descriptions of indicator 

survival and conditions under which growth has been observed are provided. Survival data taken 

from in situ and laboratory experiments conducted in or with waters from different settings are 

then compared. 

General Description of Indicator Decay in Natural Waters

General features of E. coli decay in coastal fresh water (from Whitman et al., 2004) are 

illustrated in Figure 10, while Figures 11 and 12 cover estuarine (coastal) seawater and inland 

flowing waters, respectively. The survival curves chosen to illustrate decay in the three settings 

are representative of those found in the literature and were chosen because they are the result of 

experiments conducted in situ under comparable conditions. The curves for the three settings are 

similar, all displaying ―shoulder‖ behavior (i.e., slow removal/die-off or perhaps growth early in 

the experiment) followed by apparent first-order decay. 

Figure 10. Survival Curves for E. coli from in situ Mesocosm Experiments in 

Coastal Fresh Waters. Open triangles denote counts from experiments in dark bags, 

filled inverted triangles denote counts for experiments conducted in ambient lake water,

and open circles show counts for experiments conducted in transparent bags (SOURCE: 

Reprinted, with permission, from Whitman et al., 2004 © American Society for 

Microbiology).
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August 2010 35

Figure 11. Survival Curves for E. coli in Seawater. Symbols denote the month in 

which experiments were conducted—open circles: February; filled circles: March; open 

triangles: April; filled triangles: May; open squares: July; filled squares: November

(SOURCE: Reprinted, with permission, from Rhodes and Kator, 1988 © American 

Society for Microbiology).

Figure 12. Survival Curves for E. coli in Freshwater, Stream Settings. Open 

symbols denote results from experiments conducted in situ; filled symbols denote results 

from experiments conducted in natural waters in the laboratory (SOURCE: Reprinted, 

with permission, from McFeters and Stuart, 1972 © American Society for Microbiology).
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August 2010 36

Non-first-order behavior observed in the decay of E. coli has been attributed to the availability of 

substrate (Hijnen et al., 2007; in explanation of shoulders) and predation (e.g., Davies et al., 

1995; based on observations in sediments with and without predators). Despite frequent nonfirst-order behavior, experimental studies of indicator survival typically report decay rates as 

first-order decay constants.8 

Phenomena Contributing to Indicator Removal

The three primary factors demonstrated to influence the survival of FIB in all settings are solar 

radiation (e.g., Anderson et al., 2005; Bordalo et al., 2002; Harwood, 2004; He et al., 2007; 

Jeong et al., 2005; Lipp et al., 2001a; Šolić and Krstulović, 1992), temperature (e.g., Alkan et al., 

1995; Noble et al., 2004; Okabe and Shimazu, 2007; Rhodes and Kator, 1988; Šolić and 

Krstulović, 1992; Wait and Sobsey, 2001), and salinity (e.g., Anderson et al., 2005; Bordalo et 

al., 2002; Fujioka et al., 1980; Šolić and Krstulović, 1992). Other factors, such as nutrient 

availability, turbidity, organic matter, and pH, appear to play a smaller role in FIB survival 

within the range of values usually encountered in natural surface waters. In general, solar 

radiation greatly enhances die-off, higher temperature promotes faster decay (though some 

reports indicate this may not be universally true), and decay of FIB is faster in saline waters than 

fresh. The influence of temperature on survival is complex, partly due to predation on removal 

of indicator organisms and the dependence of predator density on temperature. 

These three primary factors (solar radiation, temperature, and salinity) may differ between inland 

and coastal sites. For example, tree shading of inland (riparian) sites may result in both lower 

average temperature and insolation in comparison with coastal sites, where shading is minimal. 

Temperatures of inland waters may be, on aggregate, systematically different from those of 

coastal waters. For example, during warm months small spring-fed streams are expected to be 

cooler than nearby lakes and coastal waters and smaller bodies of water are expected to 

experience greater temperature fluctuations than larger water bodies with higher thermal 

capacity. Temperature and insolation differences can exert direct influence on FIB growth and 

survival or produce a secondary influence on survival via changes in predator populations. An 

additional possible secondary effect of solar radiation and temperature is the differential survival 

of indicators and pathogens. If indicators and pathogens have different sensitivities to 

temperature change and solar radiation, differences in these factors may alter relative abundance 

 

8

In this report, decay constants are reported as

t

C C

k

0

ln

where k is decay constant (in units of d-1unless noted otherwise), C is indicator or pathogen density at time t, and 

C0 is the initial indicator or pathogen density (at t = 0). In other reports, decay rate constants are reported as

t

C C

K

10 0

log .
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August 2010 37

of the pathogens and indicators, resulting in a difference in the association of indicators with 

specific pathogens (one feature of an effective indicator) in coastal and inland settings.
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August 2010 38

Growth Observations

Several researchers (e.g., Carillo et al., 1985; Hardina and Fujioka, 1991) have demonstrated that 

fecal indicators (especially E. coli and fecal coliforms) grow in tropical climates under the right 

conditions and have greater persistence (if not growth) in sediments than in the water column. 

There is an increasing awareness that growth of FIB occurs in other climates and under a variety 

of conditions, including temperate conditions in the continental United States. Reports of growth 

in the water column for a variety of settings are summarized in Table 6. The studies reported in 

Table 6 were selected because (1) are from prominent, peer-reviewed journals; (2) the authors 

are well-established in their fields; (3) the methods for enumerating FIB are described; and (4), 

in each study, specific FIB are selectively cultured. It may be assumed that bacterial populations 

used in growth experiments were mixtures of viable, non-viable, and perhaps damaged cells. 

Because growth was observed in controlled settings, it can be assumed that viable cells are 

capable of growth under equivalent conditions in situ. In addition to the studies listed in Table 6, 

many studies have demonstrated growth of FIB in sediments and soils from a variety of settings. 

The general features that are the most important in fostering growth of indicator organisms in the 

water column are removal of predators and the presence of sediments in study waters. As can be 

seen in Table 6, growth has been observed in coastal and inland settings and in both large and 

small streams. Fewer studies have reported growth of enterococci than of E. coli and fecal 

coliforms; however, it is not certain whether this is because enterococci growth is less prevalent 

than that of the other indicators or whether fewer studies have been made of enterococci. 

There are relatively few features of inland and coastal sites that could distinguish these settings 

with respect to their ability to support FIB growth. For example, Davis et al. (1995) assessed the 

effect of dechlorination on FIB concentrations in WWTP effluent and found that, regardless of 

setting, the regrowth of FIB in dechlorinated WWTP effluent was minimal. Two potential 

differences between coastal and inland sites relate to growth of FIB in sediments. The sediments 

of coastal and inland sites may, on aggregate, be different and have a different potential for 

promoting growth. If persistence of FIB in coastal and inland settings were significantly 

different, this difference could influence the association of FIB with specific fecal pollution

events. A second potential result of differences in growth in coastal and inland settings is 

different loadings of the water column of FIB in sediments. Resuspension (or suspension in the 

case of microorganisms originating in sediments) of indicators and pathogens from sediments is 

highly variable. This is because the fluid dynamics of both inland and coastal settings are highly 

variable and, at present, are not well characterized. Coastal and inland resuspension may be 

driven by different features of the setting. In coastal settings, wave action and tidal fluctuations 

may dominate whereas bed scouring during rainfall events could be the dominant cause in inland 

flowing settings. In inland non-flowing settings one study implicated motor boat use in increases 

in indicator concentration in the water column, presumably through resuspension (An et al., 

2002).
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Table 6. Reports in which Fecal Indicator Bacteria Growth has been Observed or Inferred

Study Climate

Water 

Type Media Growth Conditions Growth Observations

Carillo et al., 

1985

Tropical Fresh Water column in a 

stream (in situ) via 

diffusion chambers

Water temperature between 21 to 

22 C for two sites at which in situ

studies conducted; nitrite + nitrate 

concentration were 0.43 and 0.53 

mg/L at the two sites, respectively; 

total phosphorous concentration 

3.48 and 3.04 g/L for the two 

sites at which in situ studies were 

conducted

E. coli density increased with time in in situ

experiments at all locations along a river 

reach; some study sites characterized as 

relatively unimpacted by sewage and others 

directly impacted by sewage

Bifidobacterium adolescentis (an alternative 

bacterial indicator organism evaluated by the 

study authors) did not increase over time for 

in situ growth experiments

Desmarais et al., 

2002

Tropical Estuarine Waters from a brackish 

creek mixed with sterile 

sediments

Laboratory experiments conducted 

with waters from a brackish creek

Within 30 hours of addition of small amounts of 

sterile soils to water samples, significant 

growth of E. coli and enterococci observed; 

no growth or decline of Clostridium 

perfringens observed under the same 

conditions

Gerba and 

McLeod, 1976

Tropical Estuarine Sediments and water 

column from areas 

known to be receiving 

domestic sewage 

pollution

Experiments performed with and 

without sterilization of the media, 

with and without sediments mixed 

with waters and with and without 

nutrients eluted from sediments

Growth and sustained high levels of E. coli

occurred in waters dosed with nutrients 

eluted from sediments; growth of 

approximately 5-logs realized within 3 days

Hardina and 

Fujioka, 1991

Tropical Fresh Water from a tropical 

stream with known 

impacts of human 

sewage; observations 

performed in situ and in 

laboratory experiments

Experiments performed in the field 

in a tropical stream with known 

sewage impacts and with a 

temperature range of 18 to 26 C; 

water from the stream allowed to 

diffuse to water in the test 

apparatus

Experiments performed in the 

laboratory with water drawn from a 

tropical stream and with incubation 

temperature in the range 23 to 

25 C

Under laboratory conditions, fecal coliforms 

concentration increased by more than 2-logs 

within two days and maintained high 

concentration through a third day 

E. coli observed to grow in both laboratory and 

field conditions during the first 24 hours of 

incubation; growth greater under field 

conditions

Enterococci did not experience growth under 

laboratory or filed conditions

Although growth observed in water, 

multiplication in streams deemed unlikely to 

be the cause of high levels of E. coli and 

enterococci in streams because the 

residence time in streams is low and 

because growth conditions are less than 

ideal due to suboptimal temperatures, 

nutrients and competition with other bacteria
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Study Climate

Water 

Type Media Growth Conditions Growth Observations

Isobe et al., 

2004

Temperate Fresh Water column in a river; 

samples drawn from a 

reach believed to be 

free of inputs of sewage 

and classified as 

―control sites‖ by the 

authors

In situ measurements made during 

one calendar year; the study area 

(Tokyo) has four seasons and 

water temperature ranged from 

below 10 C to above 25 C

Total coliforms, E. coli, and fecal streptococci 

(enterococci) detected at control sites 

irrespective of season

Coprostanol concentrations measured at control 

sites concurrent with FIB concentrations 

were below the detection limit, indicating that 

E. coli and fecal streptococci were naturally 

present in soils or feces of animal origin

Lee et al., 2006 Subtropical Marine Water from the water 

column with or without 

sediment present in the 

microcosm

Marine water overlaying 

approximately 10 g of autoclaved 

sediment and inoculated with E. 

coli or Enterococcus

Significant growth of both E. coli and 

enterococci occurred when microcosm 

waters were on top of a small quantity of 

sediments

Sediments may contribute organic content 

required for growth

Okabe and 

Shimazu, 2007

Temperate Fresh and 

low 

salinity 

waters

Unfiltered river water 

and unfiltered marine 

water diluted with 

unfiltered river water

Laboratory observations made of 

growth/decay of 6 fecal indicators; 

fresh and seawater samples mixed 

to achieve a desired salinity, 

inoculated with human, pig, and 

cow feces suspensions and 

maintained at target temperatures

Total coliform growth observed at T = 10 C and 

salinities of 0 ppt (k = 0.11 d-1) and 10 ppt (k 

= 0.07 d-1)

Net decay of total coliforms observed at 

salinities greater than 10 ppt

Net decay of fecal coliforms observed at all 

salinities and temperatures, though decay 

rate in fresh water at water temperature of 

10 C was very low (0.02 d-1)

Rhodes and 

Kator, 1988

Temperate Estuarine Filtered and unfiltered 

estuarine water 

inoculated with 

suspensions of E. coli

and Salmonella spp.

In situ experiments in diffusion 

chambers; growth and decay 

monitored during all 4 seasons and 

with and without predators and 

competition

E. coli and Salmonella spp. grew in filtered and 

unfiltered water for about 2 days after 

inoculation

Decay rate after the growth period was much 

higher in unfiltered water than in filtered 

water
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August 2010 41

Comparison of Measured Decay Rates

To assess potential differences in decay related to setting, observed decay rates from mesocosm 

studies are compared. Because in situ studies appear best suited to demonstrating differences 

related to setting, attempts were made to use mesocosm data where available. For E. coli, in situ 

mesocosm decay rate estimates were found for each setting (inland stream, inland river, coastal 

fresh, and coastal marine). Values for decay rate from those studies are reported in Table 7 and 

plotted in Figure 13. In Figure 13, the lines are the range of the decay rates in a particular study 

and the symbols correspond to the setting in which the study was conducted. Except for one 

study that reported extreme variability in decay rate (Beaudeau et al., 2001), decay rates appear 

to be comparable, regardless of setting or water type. This finding is counter to the observation 

that E. coli survival is greater in fresh waters than marine waters. 

No in situ mesocosm studies were found for enterococci, though numerous laboratory mesocosm 

studies were found (Table 8). Decay rates corresponding to different light conditions are 

reported, though comparison of these decay rates is not possible, since the light conditions 

(artificial versus natural light source, net UV radiation dose received, turbidity, etc.) varied 

widely between experiments. One series of studies (Sinton et al., 1994, 1999, 2002) introduced a 

different rate expression for microorganism decay based on the net dose of solar radiation 

received by the organism. In that model, the percent survival, pS, is given by

Figure 13. Decay Rates of E. coli from in situ Mesocosm Studies.
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August 2010 42

Table 7. Decay Rates for E. coli Reported in Studies Conducted with in situ Mesocosms

Study Setting Indicator

Temperature 

or Month

Average or 

Median Decay 

Rate (d-1)

Decay Rate 

Range (d-1) Notes

Beaudeau et 

al., 2001

Inland flowing, small 

and medium-sized 

streams

E. coli 11.9 5.86 0.221 to 

41.1

Decay rate for small streams varied more widely than 

that of medium sized streams

Studies conducted in temperate climate

Menon et al., 

2003

Inland flowing, large 

river

E. coli June 1.68 0.437 to 

1.87

Decay followed first-order kinetics

Studies conducted in a temperature climate

Menon et al., 

2003

Coastal marine site E. coli August 1.38 0.254 to 

1.507

Studies conducted in a temperate climate

Carillo et al., 

1985

Inland flowing, small 

stream

E. coli 21 Growth — Studies conducted in a tropical climate

Craig et al., 

2004

Coastal marine 

setting

E. coli February 

(Australia)

1.80 — Studies conducted in a subtropical climate

Reported decay rate calculated based on reported T90

and assuming first-order decay

Decay rates determined in laboratory microcosm 

studies comparable with those determined from in 

situ experiments

Decay rates in sediments significantly lower

Pérez-Rosas 

and Hazen, 

1988

Coastal marine 

setting

E. coli 19.8 to 26.2 0.446 -0.446 to 0 Studies conducted at two similar sites

Studies conducted in a tropical climate

Reported values calculated based on survival times 

reported and assuming decay follows first-order 

kinetics

E. coli densities determined via Coulter Counter (CC) 

and acridine orange (stain) direct count (AODC); 

results reported based on CC determination; growth 

inferred from AODC counts

V. cholerae more persistent than E. coli and growth of 

V. cholerae observed

Pérez-Rosas 

and Hazen, 

1989

Inland flowing setting, 

small stream

E. coli 22 0 (stability) — Studies conducted at two sites

Studies conducted in a tropical climate

E. coli densities determined via CC and AODC; results 

reported based on CC determination; decay at a low 

rate inferred from AODC counts

Rhodes and 

Kator, 1988

Inland flowing, 

tributary in estuary 

upstream waters

E. coli 25.1 (range 

6.7 to28.2)

0.65 -0.36 to 0.86 Studies were conducted in a temperate climate

Salinity corresponding to mean decay rate was 8.2‰
U.S. Environmental Protection Agency

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Study Setting Indicator

Temperature 

or Month

Average or 

Median Decay 

Rate (d-1)

Decay Rate 

Range (d-1) Notes

Rhodes and 

Kator, 1988

Coastal/estuarine, 

estuary mouth

E. coli 27.9 (range 

5.9 to 27.9)

0.51 -0.72 to 0.51 Studies conducted in a temperate climate

Salinity corresponding to mean decay rate 18.2‰

Experiments conducted with filtered and unfiltered 

water; filtering water reduced removal rates 

significantly and resulted in growth for experiments 

conducted in July

Wait and 

Sobsey, 2001

Coastal/marine E. coli 22 to 24 (full 

range 4 to 24)

0.58 0.58 to 2.56 Studies conducted in a temperate climate

Studies conducted at depths of 3 and 10 m; data 

reported are for 3 m depths; results at both depths 

similar

Results inconsistent with typical temperature trends—

the lowest decay rate observed at the highest 

temperature; this finding inconsistent with findings in 

laboratory microcosm studies

Whitman et 

al., 2004

Coastal, freshwater E. coli 0 (stability) 0 to 0.746 Studies conducted at a depth of 45 cm in dark and clear 

bags; no decay observed during 12 hours in the dark 

bags 

Studies conducted in a temperate climate

Against expectations, measured decay rates for 

transparent mesocosm studies greater at 90 cm 

depth than 45 cm depth and greater on variably 

cloudy days than sunny days
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August 2010 44

nS

pS100 1 1 exp kSS ,

where kS is a solar radiation decay constant (m2/MJ), S is the net incident solar radiation (MJ/m2), 

and nS is a constant. The data in Table 8 indicate that there is little difference in enterococci 

decay rates among settings. The decay rates observed in mesocosms kept dark are comparable 

(0.561 d-1for fresh water and 0.113 to 1.74 d-1for marine water). Comparisons between decay 

in different light conditions are difficult to assess because the radiation doses used in different 

studies are not known. The exception is the studies conducted by Sinton et al. (1994, 1999, 

2002) who used a different model than other researchers for decay rate. Comparing only decay 

rate constants determined by Sinton and colleagues shows that there was variation in the decay 

rates for experiments conducted in marine and freshwaters and results cannot be used to infer 

differences in decay rate for enterococci in different settings. However, as noted above, 

regardless of setting, light has a strong impact on decay rate and growth in the water column and 

can be observed when small amounts of sediment are included in the mesocosm.

Table 8. Decay Rates for Enterococci from Laboratory Mesocosm Studies

Study

Water 

Type

Media

Organism

†

Decay 

Constant or 

Range (min-1) Experimental Conditions

Alkan et al., 1995 Marine Water Ent kmin = 9.36 Low light intensity, T = 20° C

kmax = 119.5 Medium light intensity, T = 20° C

Bordalo et al., 2002‡Fresh Water Ent kmin = 0.561 Dark, ambient temperature (Bangkok)

kmax = 1.354 Natural sunlight, ambient temperature

Marine Water Ent kmin = 1.742 Dark, ambient temperature (Bangkok)

kmax = 2.678 Natural sunlight, ambient temperature

Davis et al., 2005 Fresh Water Ent k > 0.763 Dark, unknown temperature

Desmarais et al., 2002 Marine Water Ent Growth Sediment present, T = 28° C, dark

Decay No sediment present, T = 28° C, dark

Hartel et al., 2005 Marine Sed Ent Growth Dark, T = 25° C

Sinton et al., 1994 Marine Water Ent kmin = 0.115 Dark, cold, with sewage addition

kmax = 0.187 Dark, warm, with sewage addition

Ent*

ks = 0.310

ns = 2.58

Natural sunlight, sewage added

Sinton et al., 1999 Marine Water Ent kmax = 0.115 Dark, warm, with sewage addition

Ent*

ks,max = 0.27

ns = 9.47

Natural sunlight, sewage added

Sinton et al., 2002 Fresh Water Ent kmin = 0.288 Dark, temperature unknown

kmax = 0.403 Dark, temperature unknown

Ent*

ks,min = 0.110

ns = 1.0

Cold, wastewater stabilization pond 

inoculums

ks,max = 0.276

ns = 1.3

Warm, wastewater stabilization pond 

inoculums

†

 Ent: enterococci

‡

 Decay data reported as T90

* 

 Decay constant determined as a function of incident UV dose, with survival fraction given by

sS ns k 1 (1 e )

; in that 

expression, ks is decay rate constant (units of m2/MJ), ns is a constant (unitless), and S is net radiation dose (MJ/m2)
U.S. Environmental Protection Agency

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Summary 

Bacterial indicator organism survival is largely determined by the insolation, temperature, and 

salinity of the setting in which they live. These features vary from site-to-site and do not appear 

to be related to whether a site is coastal or inland. Possible connections between the site setting 

and the factors determining survival include differences in shading associated with inland and 

coastal sites, temperature differences typical of coastal and inland waters, growth potential in 

sediments typical of inland and coastal waters, and potential for resuspension by different 

mechanisms in coastal and inland waters.

To evaluate whether systematic differences in survival have been observed in coastal and inland 

settings, decay rate data from in situ and laboratory mesocosm studies were compared. In situ 

mesocosm decay rates for E. coli were surprisingly similar, even between fresh and marine 

waters. Fewer data were available to evaluate differences in enterococci decay. The assembled 

decay rates for enterococci indicate solar radiation has a strong effect on decay rate and that 

decay/growth is radically different in mesocosms with a small mass of sediment compared to 

mesocosms with only water. Neither of these findings seems to indicate specific differences 

between inland and coastal waters.

Several features were not considered in this discussion of survival, but are potentially important, 

and include the following:

removal via settling in different settings (e.g., coastal marine, inland flowing stream, 

inland non-flowing waters);

differences in microbial ecology in different settings; and

fluid dynamics of different settings—turbulent kinetic energy and differences in the 

potential for resuspension.

Each of the above phenomena is complex and the studies reviewed in preparation of this report 

did not provide a means for assessing them. It is likely that additional research is required before 

their impact on indicator survival can be estimated for coastal and inland settings.
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Indicator-Pathogen Association in Inland and Coastal Settings

As noted previously, effective indicators should be specific to the target organism yet retain

broad applicability (NRC, 2004). In this section, the ability of indicator organisms to meet these 

two related criteria in coastal marine waters, coastal fresh waters, inland flowing waters, and 

inland non-flowing waters are compared and contrasted. 

Studies assessing correlations or relationships between indicators for inland and coastal settings 

were compared in an attempt to discern differences in the association of indicators with 

pathogens in those settings. In general, few statistically significant correlations were reported 

between any of the traditional indicators and any pathogenic organism for site-specific studies—

though more highly fecal polluted waters do have a higher incidence of both pathogens and 

indicators. Temporal and spatial trends in indicator density and pathogen concentration are 

frequently contrary. Different trends in pathogens and indicators may arise because (1) their 

primary sources may be different; (2) pathogen loadings may be episodic (e.g., related to shortlived activities or conditions in a watershed or to an outbreak of a disease in a human or animal 

population); (3) their environmental fate and transport are different (e.g., differences in 

attachment to settleable particles or differences in optimal temperature or sunlight inactivation 

rate); or (4) other factors. In the following section, studies that report the relationship (or lack 

thereof) between pathogens and indicator organisms are reviewed and compared, as are the 

characteristics of inland and coastal waters. See Appendix A for further information.

Cryptosporidium and Fecal Indicators

A lack of correlation between Cryptosporidium concentration and fecal indicator organism 

density or turbidity has been observed in numerous studies, including those of surface waters in 

central Arizona (Ryu and Abbaszadegan, 2008), surface waters in central Massachusetts (Rees et 

al., 2005), WWTP effluent in southern France (Lemarchand and Lebaron, 2003), southern 

Florida estuarine waters (Lipp et al., 2001a), and canals and lakes used for recreation in the 

Netherlands (Schets et al., 2008). In contrast to these findings, LeChevallier et al. (1991) found 

a significant correlation between fecal coliform density and Cryptosporidium concentration 

based on a review of a database of occurrence of Cryptosporidium and fecal coliforms in water 

samples collected from 66 source waters for drinking water located throughout the United States. 

LeChevallier and colleagues reported a general tendency of waters with high fecal indicator

densities to also have higher concentrations of Cryptosporidium. However, they did not report 

that E. coli or other fecal indicators are predictive of Cryptosporidium concentrations in source 

waters. 

At specific sites, temporal variations in Cryptosporidium concentration may differ from those of 

fecal indicator organisms on the seasonal time scale (e.g., Lipp et al., 2001a; Ryu and 

Abbaszadegan, 2008), during the course of rainfall events (e.g., Rees et al., 2005; Roser and 

Ashbolt, 2004), and even at the daily time scale (e.g., Lemarchand and Lebaron, 2003). These 

reported variations in Cryptosporidium concentration and differences between Cryptosporidium

and fecal indicator organism temporal variations arise from different loadings of 

Cryptosporidium and indicator organisms in source waters. Rees et al. (2005) found that small 

rainfall events washed oocysts retained in near-stream sediment into streams, elevating stream 
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August 2010 47

concentration. The authors asserted that production of oocysts by wildlife is seasonal and that 

seasonal variations in production may differ from variations in indicator organisms. Other 

studies have confirmed seasonal variation in Cryptosporidium oocysts loading of surface waters 

for wildlife (e.g., Atwill et al., 2004) and domestic animal sources (Atwill et al., 2003), and have 

suggested variation in Cryptosporidium concentration related to human outbreaks of 

cryptosporidiosis (Lemarchand and Lebaron, 2003).

Schets et al. (2008) reported differences in the nature of Cryptosporidium and FIB sources. In 

that study, the authors found that at two similar sites (canals) ―the levels of fecal indicators in the 

canal with houseboats (Prinsengracht) and the canal without houseboats (Herengracht) were 

almost equal and did not suggest that houseboats contributed to the fecal contamination of canals 

to a larger extent than other sources did. However, Cryptosporidium and especially Giardia

numbers were much higher in the Prinsengracht canal than in the Herengracht canal, suggesting 

that wastewater from the houseboats may have been a source of those parasites.‖ This finding is 

significant both in what it says about the ability of fecal indicators to predict risk related to a 

specific pathogen and because Cryptosporidium is particularly infectious (Okhuysen et al., 2002; 

WHO, 2006). 

Ryu and Abbaszadegan (2008) observed no seasonal variation in Cryptosporidium and Giardia

concentration in a large database of inland flowing waters—despite marked seasonal variation in 

total coliforms and fecal coliforms, E. coli, and other microorganisms. Based on all data 

collected, the authors found that Giardia correlated significantly with the presence of fecal 

coliforms, whereas Cryptosporidium did not. In a study of flowing inland waters, Roser and 

Ashbolt (2004) observed increases in E. coli and enterococci densities, but not Cryptosporidium

concentration, during rain events in watersheds that were not suspected to be impacted by human 

fecal pollution. This finding reflects differences in both sources and hydrologic dependence of 

the indicators and pathogens in that inland setting. In this regard, Rees et al. (2005) reported that 

the occurrence of Cryptosporidium and Giardia in tributaries of small watersheds is not easily 

explained by the presence or absence of traditional indicator organisms or source-specific 

organisms. They observed that small rainfall events can wash oocysts in the near-stream 

sediments into streams, elevating stream concentration (spatial variability). The authors asserted

that production of oocysts by wildlife may be seasonal and may occur with a different 

seasonality compared to indicators. 

A potential difference in indicator organism and Cryptosporidium behavior in flowing versus

non-flowing waters may be related to the settling of oocysts and FIB associated with particles. 

Brookes et al. (2005) determined that Cryptosporidium partitions predominantly to particles in 

the size range 14.3 to 27.7 m while E. coli and enterococci partition predominantly to larger 

particles (> 63.3 m). With all other factors being equal, this indicates that removal of FIB from 

the water column by settling is greater than that of Cryptosporidium (by a factor of 3 in the 

Brookes and colleagues study). One potential implication of this finding is that the fecal 

indicator-Cryptosporidium ratio could differ between flowing and non-flowing waters (coastal 

and inland non-flowing).

A lack of correlation between Cryptosporidium and Giardia concentration and indicator 

concentration was also observed in an estuary (Lipp et al., 2001a). These researchers found that 
U.S. Environmental Protection Agency

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over a 12-month period of water quality sampling at multiple sites, the concentrations of fecal 

indicators (fecal coliforms, enterococci, C. perfringens, and coliphage) were not correlated with 

the occurrence of Cryptosporidium or Giardia. As with inland flowing and non-flowing waters, 

this study supports the conclusion that Cryptosporidium and Giardia loads are episodic and 

sporadic in all settings (inland flowing, inland non-flowing, and coastal). In contrast, indicator

organisms have both increased sources and sources that are more consistent. Thus, fecal 

indicators are more consistently present than pathogens. Variability in Cryptosporidium loading 

was also demonstrated by Lemarchand and Lebaron (2003) in their analyses of WWTP influent 

and effluent and surface water samples. In that study, the authors did not find a significant 

correlation between Cryptosporidium and fecal coliforms or fecal streptococci (enterococci) in 

WWTP influent. However, they did report a significant correlation between Cryptosporidium

and fecal coliform (but not fecal streptococci) in WWTP effluent and between Cryptosporidium

concentration and both fecal coliform and fecal streptococci concentration for surface waters. 

They also reported higher Cryptosporidium concentrations in plant effluent than in plant influent 

on several occasions, which was attributed to high temporal variability in Cryptosporidium

concentration, and concluded that Cryptosporidium loads depend on the level of 

Cryptosporidium infection in communities whereas indicator loads do not. 

Other sporadic or episodic loadings of Cryptosporidium may arise from nearby livestock 

operations or wildlife contributions. For example, Keeley and Faulkner (2008) found that in an 

inland flowing water, the highest Cryptosporidium concentrations occurred during calving 

season. Calving season coincided with the wettest time of year in the study area. Perhaps 

because the role of calves in Cryptosporidium loading or different fate and survival 

characteristics was not evaluated, they did not observe a correlation between concentration of 

fecal indicators and Cryptosporidium.

Viruses and Fecal Indicators

The literature review included studies of the co-occurrence of various human enteric viruses 

(adenovirus, enterovirus, Norovirus, rotavirus, and hepatitis A virus [HAV]) and fecal indicator 

organisms. It also included studies that reported decay rates of these viruses in some 

environmental waters. The results of these reviews are provided in the sections that follow.

Co-occurrence and Correlation of Enteric Viruses and Fecal Indicators

General features of enteric viruses in aquatic environments are 

higher occurrence at low temperatures versus high temperatures (Fong and Lipp, 2005b; 

Griffin et al., 2003);

frequent low concentrations or non-detections (Jiang et al., 2007; Wyer et al., 1995);

association of virus occurrence with disease outbreaks (Skraber et al., 2004) whereas 

fecal indicator organism sources are relatively constant; and

different associations between viral, bacterial, and protozoan pathogens with suspended 

particles than that of fecal indicator organisms. 
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As described below, these observations indicate significant differences between 

environmental behavior of enteric viruses and FIB, including seasonal variations, possible 

different trends in inactivation with temperature, and differences in the net loadings from all 

sources for specific receiving waters.

Enterovirus

A study of enteroviruses, fecal coliforms, and fecal Streptococcus concentrations by Wyer et al. 

(1995) in marine coastal waters produced mixed results in attempts to correlate enterovirus with 

fecal indicator organisms. This led the authors to conclude that fecal indicator organisms had 

―low predictive capability‖ for enterovirus in marine coastal waters. In that study, a large data 

base (n = 40,449 for fecal coliforms, n = 33,459 for fecal streptococci, and n = 3015 for 

enterovirus samples) was used to attempt to establish a parametric relationship between the 

indicator organisms and enteroviruses. The indicator organism densities were assumed to fit lognormal distributions. Although the distributions of the residuals associated with the fitted data

were not assessed, a visual inspection of the fits indicates that the log-normal distribution seems 

reasonable. Enterovirus data fit poorly with a log-normal distribution because the data contained 

many zero observations. An adequate fit for enteroviruses was obtained when zero values were 

omitted and the data were log-transformed. When the transformed enterovirus data were 

correlated with indicator organism data, positive, significant correlations were found. However,

the correlations were weak, indicating that even for this relatively large data set, indicator 

bacteria are relatively poor predictors of enterovirus concentration. 

When enteric virus concentration and indicator organism density data for individual sites (rather 

than aggregated data) are assessed, there appears to be less correlation between FIB and enteric 

virus concentrations. For example, Jiang et al. (2007) found in a coastal/estuary setting in 

California that detection of human enteroviruses depends on a (seasonal) distribution pattern that 

is opposite of FIB (total coliform, fecal coliform, enterococci), with enteroviruses more prevalent 

during the dry season and FIB more prevalent during the wet season. The observed temporal 

variations in viruses were attributed to temporal trends in viral shedding or ―heightened 

anthropogenic activities‖ (e.g., primary contact recreation) during summer months. 

A similar lack of correlation between FIB (in this case, fecal coliforms) and enterovirus was 

noted in a study of river waters by Skraber et al. (2004). In that study, trends in enterovirus and 

fecal coliform concentrations were found to be the opposite. Fecal coliforms were more 

abundant at lower temperatures while enterovirus concentrations were characterized by frequent 

non-detect values and lower concentrations at low temperature (around 7° C) and more frequent 

detection at higher temperatures. These observations either indicate that the loadings of 

enterovirus are different than those of the indicator bacteria or that the fate of the indicator 

bacteria (e.g., die-off or removal via predation) has a much different temperature dependence 

than does that of enterovirus. Fong et al. (2005a) likewise found a lack of correlation between 

FIB (fecal coliforms and total coliforms) and enteric viruses (human enteroviruses and human 

adenoviruses) in a tidally-influenced river in Georgia. In contrast to the study by Skraber et al. 

(2004), Fong et al. (2005a) detected all viruses at a higher frequency in December when the river 

temperature was low. The authors speculated that more frequent occurrence of enterovirus may 
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be a result of improved persistence at low temperature or higher loading, though the authors saw 

no increase in viral loads associated with rainfall. 

In an early study of both fresh and marine waters by Vaughn et al., (1979), a similar lack of cooccurrence was observed between fecal coliforms and enterovirus, with enterovirus occurring at 

sites with low fecal coliform concentration, and not occurring at sites with high fecal coliform 

concentration. In a comparison of marine and freshwater sites, Rex et al. (2005) found no 

significant correlation between indicators (E. coli, fecal coliforms, enterococci, and coliphages) 

and viral pathogens (adenovirus, astrovirus, rotavirus, enterovirus) for freshwater or marine sites. 

Hepatitis A Virus (HAV)

Conflicting results regarding the correlation of HAV with fecal indicator organisms were 

obtained in studies of an inland flowing water (Fernandez-Molina et al., 2004) and coastal 

marine waters (Gersberg et al., 2006). Fernández-Moilna et al. (2004) collected samples from 

springs and a stream located in a region whose land use is primarily agricultural. The springs 

were perceived (and confirmed) to be relatively free of fecal pollution, while a small WWTP 

discharged into the stream. Among stream samples, no correlation was observed between the 

concentration of several fecal indicator organisms (total coliforms, fecal coliforms, enterococci,

and sulfite-reducing Clostridia) and HAV. In addition, spatial trends in HAV concentration and 

concentration of the indicators were drastically different. A plot from Fernández-Molina et al.

(2004) showing the trend in HAV and indicator organisms with river station is presented in 

Figure 14. The designations on the x-axis refer to stream locations, with A being the furthest 

upstream sample location, B corresponding to a station immediately downstream of a WWTP,

and E being the furthest downstream station. The trends in all of the FIB are the same and are 

different from HAV. The authors suggested the lack of correlation between indicator organisms 

and HAV is a result of different environmental fates of the microorganisms and spatial and 

temporal differences in the net loadings of the microorganisms.

In contrast to the above findings for an inland water, Gersberg et al. (2006) found a significant 

correlation between E. coli and enterococci and both HAV and enteroviruses in a marine coastal 

setting. In that study, samples were drawn from a wider, more diverse study area in which 

human fecal pollution was more prevalent than that of Fernández-Molina et al. (2004). Gersberg 

and colleagues collected and analyzed both dry weather and wet weather samples, finding wide 

variation in concentrations of all microorganisms in all samples, and among samples collected 

during wet weather events. 

Adenovirus

In a study of coastal marine waters by Jiang et al. (2001), exceedance of indicator standards did 

not correlate with presence of adenovirus. In fact, high viral concentrations (2300 and 924

genomes/L; as determined by nested PCR) were observed at two locations (river mouths) where 

indicator organism density did not exceed FIB criteria. Similar observations were made by 

Xagoraraki et al. (2007) in a study of fresh coastal waters in which adenovirus densities were 

observed to vary significantly—spatially and temporally. Although co-occurrence of adenovirus 
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Figure 14. Spatial Trends in HAV and Fecal Indicator Bacteria in a Small Stream 

Located in an Area whose Land Use is Primarily Agriculture. Heterotrophic plate 

count bacteria [HPC]; total coliform (TC); fecal coliform (FC); fecal streptococci (FS); 

sulfite- reducing clostridia (SRC); human adenovirus (HAV) (SOURCE: Reprinted, with 

permission, from Fernandez-Molina et al., 2004 © Kluwer Academic Publishers). 

with FIB was not assessed in that study, the heterogeneity of adenovirus presence/absence and 

the trends in adenovirus concentration appear to differ from those typical of FIB. Xagoraraki 

and colleagues observed generally low adenovirus concentrations or non-detection, with minimal 

difference in adenovirus concentration between morning and afternoon samples. This lack of 

diurnal variation is a difference from trends of FIB and was attributed to the suspected source of 

the viruses (municipal WWTP effluent). Different seasonal trends in adenovirus concentration 

were observed at the two study sites, with adenovirus concentration highest in the early summer 

at one site and in late summer at the other site. 

In a study of an urban river, trends in adenovirus detection and concentration were opposite to 

those of FIB and coliphages (Choi and Jiang, 2005a). Indicator organism concentrations tended 

to be higher during early winter months (the onset of the rainy season) and could be described by 

a log-normal distribution. Adenovirus presence and concentrations were greatest in March, May,

and December and adenovirus were not log-normally distributed. In that study, adenovirus 

density was determined by QPCR. In one of the rivers studied by Choi and Jiang (2005a), 

adenovirus concentration was highest at the river mouth whereas on another river the 

concentration was highest at the furthest upstream station studied. The authors described

adenovirus occurrence as ―sporadic‖ and did not note seasonality in its occurrence.
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Summary of Co-occurrence and Correlation of Enteric Viruses with Fecal Indicator 

Bacteria

Fecal indicator bacteria are relatively poor predictors of enteric virus occurrence for both inland 

and coastal waters. In both settings, loadings and occurrence of enteric viruses have different 

sources and seasonal trends than the bacterial indicators. These seasonal trends may be related to 

relative differences in survival of FIB and enteric viruses or may be related to seasonal loading 

differences. For example, a large database of FIB and HAV co-occurrence indicates a general 

relationship between the indicators and pathogen; that is, higher indicator concentrations indicate 

fecally polluted waters that are more likely to contain HAV. However, on a site-by-site basis,

relationships between indicator organism density and HAV concentration do not appear valid—

particularly in the case of streams—where spatial and temporal trends in the indicators and 

pathogen differ. These observations are consistent with observations on co-occurrence of fecal 

indicator organisms with other enteric viruses, some bacterial pathogens, and some pathogenic 

protozoa.

Inactivation Rates of Enteric Viruses in Different Settings

Studies of infectious rotavirus decay in seawater and fresh water by Caballero et al., (2004)

indicate rotavirus inactivation follows first-order kinetics, with T90 (the time to reduce the 

density by 90% [i.e., time for 1 log10 removal]) of approximately 30 days in fresh water. In that 

study, the authors demonstrated that significantly higher UV doses were required to achieve 1 

log reduction in rotavirus concentration in seawater than in freshwater. In a study of rotavirus 

survival in freshwaters from two different sources, Pancorbo et al. (1987) observed shoulder 

behavior for one of the waters (lake water) but not the other (creek water). Decay rates 

(calculated assuming first-order decay) for the lake and creek water were 0.139 d-1and 0.237 d-1, 

respectively, for experiments performed at 20° C. The authors speculated that the difference in 

decay rate between the creek and lake waters may be the result of differences in water quality, 

especially pH and chloride concentration. 

Dependence of inactivation rate on water type/quality was also observed by Hurst and Gerba 

(1980). In that study, simian rotavirus inactivation was observed in polluted and unpolluted 

fresh water and in estuary water at three salinities. Their survival curves, shown below in Figure 

15, did not exhibit shoulders in that study, though tailing behavior was observed for some 

experiments conducted in fresh waters. Survival during the first two days was similar in all 

waters studied (T99 ~2 to 3 days for all waters). After 3 days, decay rate reduced drastically in 

freshwater but not in estuarine water, though within the salinity range studied salinity did not 

appear to influence inactivation. Ward et al. (1986) found only minor differences in inactivation

rate of simian rotavirus in waters from four sources of drinking water ranging from very polluted 

(Ohio River) to presumably unpolluted (groundwater source). In a study of simian rotavirus 

survival in marine water and sediments by Rao et al. (1984), rotavirus was observed to survive 

significantly longer in sediments than in water alone at 25° C. Based on inactivation during the 

first 3 days of experiments, the decay constant for marine water alone was 1.16 d-1 while the 

decay constant for sediments was 0.462 d-1. Rotavirus inactivation rate data are summarized in

Figure 15.
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Figure 15. Inactivation of Simian Rotavirus in Unpolluted Fresh Water (open 

squares), Polluted Fresh Water (filled squares), Low Salinity Estuary Water (open 

circles), Medium Salinity Estuary Water (open triangles), and High Salinity Estuary 

Water (crosses) (SOURCE: Reprinted, with permission, from Hurst and Gerba, 1980 © 

American Society for Microbiology).

Survival curves for poliovirus 1 and coxsackievirus B-1 for in situ (membrane diffusion 

chamber) studies done in flowing river water at 23 to 25° C exhibited neither shoulders nor tails, 

as seen in Figure 16 from O’Brien and Newman (1977). Similarly rapid inactivation (T90 < 24 

hr) with no shoulder or tail was observed for poliovirus type 1 at 24° C in seawater from 3

locations with different levels of pollution (Fujioka et al., 1980). At 6° C and in sterilized 

seawater, Fujioka and colleagues observed that poliovirus concentration was essentially stable, 

indicating that both temperature and predation by microorganisms play roles in removal of 

poliovirus at relatively high temperature. In a comparison of poliovirus 1 and rotavirus (SA11),

survival in estuarine water, estuarine sediments, and two types of suspended solids, Rao et al. 

(1984) noted much longer survival of both enteric viruses in sediments or when attached to 

suspended particles compared to survival in water alone. Enhanced survival of indicators in 

sediments and when attached to particles has been observed for FIB in all relevant settings 

(inland flowing waters, inland non-flowing waters, coastal fresh waters, and coastal marine 

waters).

In summary, enteric viruses generally decay according to first-order kinetics, exhibiting fewer 

tendencies toward shoulders or tails in survival curves than FIB. Inspection of the inactivation 

rates reported for the enteric viruses in various studies, and summarized in Table 9, reveals 

variability in decay rate estimated among studies, but does not indicate differences in decay rate 

that may be attributed to the setting (inland vs. coastal). 
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Figure 16. Survival Curves for Coxsackievirus B-1 and Poliovirus 1 in Membrane 

Diffusion Chambers in Fresh Water (SOURCE: Reprinted, with permission, from 

O’Brien and Newman, 1977 © American Society for Microbiology).

Table 9. Summary of Enteric Virus Inactivation Rate Data

Virus Setting

Temperature 

(°C)

Decay 

Rate (d-1) Reference

Rotavirus

Lake/Inland 20 0.139 Pancorbo et al., 1987

Stream/Inland 20 0.237 Pancorbo et al., 1987

Marine/Coastal 25 1.16 Rao et al., 1984

Adenovirus 40 Tap water 23 0.0709 Enriquez et al., 1995

Marine/coastal 15 0.0592 Enriquez et al., 1995

Adenovirus 41 Tap water 23 0.0608 Enriquez et al., 1995

Marine/coastal 15 0.0582 Enriquez et al., 1995

Coxsackievirus B-1 Stream/Inland 25 2.36a O’Brien and Newman, 1977

Poliovirus 1

Stream/inland 25 1.78a O’Brien and Newman, 1977

Stream/inland 20 0.442 Pancorbo et al., 1987

Lake/inland 20 0.087 Pancorbo et al., 1987

Estuarine/coastal 25 2.04 Rao et al., 1984

Marine/coastal 20 1.28 Wait and Sobsey, 2001

Marine/coastal 15 0.256 Enriquez et al., 1995

a Calculated based on survival time data provided in original study and assuming first-order decay.
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Bacterial Pathogens and Indicators

One factor that favors the association of FIB with bacterial pathogens is that, compared to enteric 

viruses or protozoa, they are biologically similar. Factors that work against an association are 

temporal and spatial differences in their loadings to surface waters, differences in their abilities 

to assume a viable but nonculturable (VBNC) state, differences in sensitivity to salinity, and 

existence of nonhuman hosts of organisms pathogenic to humans. All of these 

behaviors/features are exhibited by both pathogens and indicators, but to different extents and at 

different rates. Similarly with viruses and protozoa, processes that could give rise to differences 

in the ability of indicators to predict bacterial pathogen concentrations in different settings are 

different substrate and nutrient requirements, association with particles of different sizes 

(differential settling, especially in non-flowing waters), predation, and different susceptibility to 

UV radiation.

As for viruses and protozoa, the presence of bacterial pathogens appears to be episodic and 

sporadic in all settings. In a study of five rivers of varying size, Voytek et al. (2005) observed 

that FIB were of limited use in detection of Helicobacter spp. or H. pylori. Fecal indicator 

bacteria were frequently present when H. pylori was detected, but not vice versa, and only weak 

correlations between Helicobacter spp. and E. coli and fecal coliforms were observed. 

Correlation of Helicobacter spp. concentration with enterococci concentration was poor. This 

lack of correlation is somewhat surprising given the prevalence of H. pylori infection in human 

populations worldwide, which would be expected to make H. pylori concentration in surface 

waters less variable. The tendency for H. pylori concentration to vary significantly does not 

appear to be different for waters from inland and coastal settings. This is because, as 

demonstrated for viruses and protozoa, coastal waters are also subject to wide variation in 

occurrence of pathogens and in pathogen loadings that are different from those of FIB. 

Variability (both spatial and temporal) in bacterial pathogen occurrence was also reported in a 

study of three bacterial pathogens by Walters et al. (2007) in inland flowing waters in a 

watershed with widespread livestock operations. In that study, very little co-occurrence was 

observed of E. coli O157, Salmonella, and Campylobacter. Among 406 samples analyzed for 

these pathogenic bacteria, only 3 samples were positive for both Salmonella and E. coli O157. A 

similar lack of co-occurrence was observed for Salmonella and E. coli O157 with 

Campylobacter. Because inland flowing, inland non-flowing, and coastal waters are all subject 

to temporally-variable pathogen loads from multiple, diverse sources, the above results offer no 

clear difference in anticipated FIB ability to predict bacterial pathogen occurrence and 

concentration in those settings.

Touron et al. (2007) had mixed success relating Salmonella spp. concentration to FIB (fecal 

coliform, E. coli, or enterococci) concentration. In their study of the Seine estuary in France, 

they found a strong correlation between Salmonella and all three of these indicators at a station 

located in an upstream portion of the estuary. They also found a correlation between Salmonella

and enterococci at the mouth of the estuary. Notably, Salmonella was not correlated with any 

indicator organisms in an urban reach of the river. In contrast, Lemarchand and Lebaron (2003) 

observed no correlation between Salmonella and any fecal indicator in an inland flowing water 

setting. Other researchers have previously reported a tendency for waters with very high 
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August 2010 56

concentration of fecal coliforms (> 2000 CFU/100 mL) to contain Salmonella (e.g., Goyal et al.,

1977). In that study, sediments were found to be more abundant in Salmonella than in the water 

(though the ratio of Salmonella concentration to fecal coliform concentration was not constant), 

indicating that the sediments may have been a source of Salmonella during rainfall periods of 

increased turbulence at the sediment-water interface.

Experimental survival studies of bacterial pathogens in waters from different settings indicate 

that bacterial pathogens have survival characteristics more similar to those of FIB than do enteric 

viruses or protozoa. In a study on the survival of E. coli O157 in waters collected from nonflowing inland sources by Wang and Doyle (1998), water quality and temperature both 

influenced survival, the longest survival was observed at a temperature of 8° C in all waters (91 

days to achieve a decrease between 1.5 and 1.6 log10) and the shortest survival was at 25° C (the 

highest temperature evaluated). Not surprisingly, the influence of temperature on E. coli O157 

was similar to that of FIB, with improved survival at temperature around 10° C. Similar to nonpathogenic E. coli, E. coli O157:H7 has been shown to grow in sterilized fresh water from a 

small flowing inland stream, an inland flowing river, and an inland non-flowing source (Vital et 

al., 2008). Although growth was observed under the same conditions for an environmental E. 

coli isolate and an E. coli lab strain, growth curves for the three E. coli strains were different, 

with the E. coli O157 growth curve bearing greater similarity to that of the environmental isolate. 

While Craig et al. (2003) could not establish direct correlations between decay rates in overlying 

water (marine water from a coastal site) of Salmonella spp. and indicators, they observed that 

decay of Salmonella most resembled that of E. coli—the indicator with the highest decay rate 

among those studied. As with all FIB, the authors also noted greater survival of S. typhimurium

and S. derby in sediments than in the overlying water and greater inactivation rate at 30° C than 

at 20° C. For S. typhimurium in marine waters in the absence of sediments, Craig et al. 

determined the decay rate to be -0.78 d-1at 20° C. Maki and Hicks (2002) observed the decay 

rate of S. typhimurium varied between 0.226 and 0.511 d-1in laboratory experiments conducted 

with natural, fresh coastal water (Lake Superior) at a temperature of 20° C. The range of decay 

rates reported were drawn from experiments with different duration and indicate that Salmonella

survival data do not necessarily fit first-order rate curves. Figure 17 shows decay rates from 

several different studies (Maki and Hicks, 2002; McCambridge and McMeekin, 1981; Rhodes 

and Kator, 1988; Sinton et al., 2007; Wait and Sobsey, 2001) of waters from different settings. 

Note that a negative decay rate indicates growth. Despite their correspondence to waters from 

various settings, the decay rates are relatively consistent and have the same general trend with 

temperature. Collectively, these data from laboratory survival studies do not indicate a 

difference in Salmonella decay that is related to setting inland versus coastal water.

1.1. Summary

Consistent co-occurrence or correlation between the waterborne pathogens evaluated in this 

report and FIB were not found—regardless of the setting (coastal, inland flowing, or inland nonflowing). In many cases, pathogen occurrence seems to be driven by events such as rainfall,

epidemics, or large releases from wildlife or livestock, and these events seem to have different
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August 2010 57

fate and transport characteristics than indicator organisms. Because coastal and inland sites are 

both subject to pathogen loads from these and other types of events, the lack of correlation noted 

between pathogens and (predominantly bacterial) indicators does not distinguish these site types 

from each other.

The following factors have the potential for causing different indicator-pathogen behavior in 

different aquatic settings:

different removal rates of indicators and pathogens via settling in flowing and nonflowing settings;

different removal rates of indicators and pathogens via UV inactivation (assuming the 

incident UV radiation is different in coastal and inland settings due to shading or other

features); and

different sources or loading rates associated with different settings.

Based on the information obtained for this report, it is not possible at present to assess the 

significance of these potential differences.

 

Figure 17. Decay Rates for Salmonella for Various Settings and Temperatures.
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August 2010 58

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August 2010 A-1

Appendix A

Summary of Studies Identified in Literature Review

Table A-1. Study Classification and Data Summary (Inland Waters)

Key:

*

Abstract only

Miscellanous acronyms – CAFO: concentrated animal feeding operations; CFU: colony forming units; CSO: combined sewer overflow; EMAP: (EPA) Environmental Monitoring and 

Assessment Program; FIB: fecal indicator bacteria; NA: not applicable; NAWQA: USGS’s National Water Quality Assessment Program; NOAELs: no observable adverse effect 

levels; PFU: plaque forming units; QPCR: quantitative polymerase chain reaction; TMDL: total maximum daily load; WWTP: waste water treatment plant

Water Type – F: fresh; E: estuarine; M: marine; U: Unknown (not specified)

Setting – IF: inland flowing; IN: inland non-flowing; C: coastal; GW: groundwater; TI: Tidal influence; U: unknown (not specified)

Climate – temp: temperate; sub: subtropical; trop: tropical; U: unknown (not specified)

Media – WC: water column; sed: sediments; soil: soils; GW: groundwater; U: unknown (not specified)

Alternate Indicators – BF: Bacteroides fragilis; CP: Clostridium perfringens; HPC: heterotrophic plate count; SP: Streptococcus faecium

Indicator Organisms – FIB: fecal indicator bacteria (not specified); TC: total coliforms; FC: fecal coliforms; EC: Escherichia coli; Ent: enterococci (also called fecal streptococci or FS)

Pathogens – Adv: adenovirus; AH: Aeromonas hydrophila; Campy: Campylobacter; Crypto: Cryptosporidium; EV: enteric virus; HAV: Hepatitis A Virus; HP: Helicobacter pylori; PA: 

Pseudomonas aeruginosa; PS: Plesiomonas shigelloides; PV: Poliovirus; Salm: Salmonella; Shig: Shigella; VP: Vibrio parahaemolyticus

Study Type – A: observation/occurrence; B: laboratory microcosm study; C: in situ mesocosm study; D: MST (microbial source tracking) study; E: methods development or 

evaluation study; F: comparison of indicators; G: modeling study; H: epidemiological study; I: review paper; J: Other

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Ahn et al., 

2005

M C Sub WC TC, 

FC, 

Ent, 

EC

F+ coliphageAdv, 

EV

A 17 stations in the 

surfzone –

water samples 

collected 5 

days during 

weekdays

No Large urban watershed 

(Santa Ana River, CA)

Stormwater runoff from the Santa Ana River 

negatively impacted coastal water quality 

(surf zone and offshore)

Bacteria and viruses in the offshore 

stormwater plumes associated with small 

particles 

Alkan et 

al., 1995

M C Temp WC EC, 

Ent

B, 

F

Yes Water used in mesocosm 

studies taken from 

Seaton Point, England, 

North Sea coast

Higher rates of die-off resulted from high 

levels of light intensity and mixing with low 

levels of turbidity and sewage content of the 

water

Survival capabilities of EC and Ent on 

exposure to light not significantly different

Anderson

et al., 1999

F IF Temp WC, 

Soil, 

Sed

FC, 

Ent, 

EC

A Samples 

collected every 

2 weeks in 

several 

streams

No Select Kansas streams Variable FC levels from 50 to 700 CFU

Higher concentrations of FIB in streams 

impacted by humans

FIB concentrations related to rainfall events
August 2010

A-2

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Baums et 

al., 2007

F, MC Trop WC, SedEC, EntBacterioidesShig B,

E, F

No Samples collected from urbanized, tidally 

influenced river sites

and a beach located 

downstream from flood 

control gates near 

Miami, FL

Technological approach evaluated has the 

potential to simultaneously detect multiple 

targets for coastal water

Bell et al., 

2007

F IF Temp WC BacterioidesB No Not specified, inland 

stream

Abstract only

Occurrence of Bacteroides in function of 

aggregate size, concentration, and 

temperature

Temperature reduced considerably presence 

of Bacteroides in unfiltered stream water

Complete removal of Bacteroides occurred in 

7 days at 25° C

Benhan et 

al., 2006

F IF Temp WCFC, 

TC, Ent, EC

I, GNo Streams in VA, MO, and 

KS

Mill Creek (VA) – small 

watershed with pasture 

(70%)

Shoal Creek (MO) –

medium watershed 

with pasture and forest

Kansas River – large 

watershed,

predominantly 

agricultural

Bacterial modeling using hydrological models

for TMDL purposes

Models limited to describe bacterial life cycles 

and determine bacteria concentrations 

during extreme events

Benhan et 

al., 2005

F IF Temp WCECG No Primarily rural stream in 

VA; pasture is the main 

land use (49%); residential and urban 

uses account for 9%

Model results suggest up to 100% reduction 

in cattle manure and wildlife direct deposits 

and non-point fecal source loading to the 

stream

Bernhard

and Field,

2000

MC Temp WC Bacteroides

Prevotella

E, ASix 1 L water 

samples

No Samples obtained from 

Tillamook Bay, OR, 

which is frequently 

contaminated with fecal 

pollution

Specific PCR primers that discriminate human 

and ruminant sources of fecal 

contamination

Bonilla et 

al., 1999

M, FC, 

IF

Tropic WC FC,

EC

CP,

BF,

FRNA

phage

A No Unspecified beach and 

inland stream in Hawaii

Abstract only

FC and EC elevated at all up-stream sites did 

not indicate sources

FRNA low and also did not indicate source; 

however, CP clearly indicated that the 
August 2010

A-3

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

contributing source was only one of the two 

tributary streams

Bordalo, 

2003

MC Temp WCTC,

FC

ASurvey lasted 18 

consecutive 

summer days, 3 times a day, 

a total of 184 

samples

collected

No Two urban beaches in 

Portugal

Periodicity of fecal indicators in raw sewage, 

tidal status, and wind conditions influenced 

water quality

Microbial water quality decreased in morning 

regardless of tide conditions, but improved 

during high tide and afternoon (NW) winds

Bowen and 

Oliver, 

2008

EC Temp WC, SedNot 

speci-

fied

A, GNo North Carolina watershed 

(Neuse River Estuary) 

with known public 

health problems related 

to municipal and 

agricultural wastewater 

discharge, storm runoff

Abstract only (of proposed integrated water 

quality research and modeling) Impact of extreme climatic storm events is 

enormous

Brookes et 

al., 2005

F IF, 

IN

Temp WCEC,

Ent

CP,

aerobic 

spores, 

somatic 

coliphage

particle 

size,

turbidity

Crypto,

Giardia

A Sampling during 

a large runoff 

event following 

intense rainfall

No South Australia, reservoir 

and inland stream, mixed land use, 

including pasture and 

vegetation

CP and Ent most highly correlated with 

Crypto

Crypto associated with small sized particles All of the indicators except CP associated 

with large particle size

Brownell et 

al., 2007

MC Sub WC, SedFC,

Ent,

EC

A, DTwo sampling 

events: one 

within 48 hours

of heavy 

rainfall and 

one after a dry 

period (6 days 

of no precipita-

tion)

No Siesta Key Beach on 

west coast of Florida 

with an adjacent 

(parallel) stormwater 

conveyance system 

High indicator bacteria levels attributable to a 

storm water system that acted as a 

reservoir and conduit, flushing high levels of 

indicator bacteria to the beach during the 

rain event

No evidence of human fecal contamination 

found by MST methods

Buckley et 

al., 1998

FO,F Sub WC, SedTC,

(Ent),

(EC)

PS, AH A total of 240 

samples were 

analyzed for 

TC, and 306 

for individual 

bacterial 

species

No Stream in a subtropical 

rainforest reserve but 

with significant tourism 

in Queensland, 

Australia

TC concentrations in sediment not correlated 

with sampling site, rainfall, streamflow, or 

visitor number

TC in sediment 1000× higher than in the WC

First report of PS in natural surface water in 

Australia

Buckwalter

et al., 2006

F IF Temp WCEC,

Ent,

A USGS survey 

from July 

NoThe Allegheny, 

Monongahela, and 

Samples collected in the 3 rivers and 

tributaries frequently exceed established 
August 2010

A-4

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

FC 2001-August 

2005 during 

dry and wet-

weather 

periods; samples 

collected from 

5 sites on the 

Three Rivers 

and from 8 

sites on 4

tributaries

Ohio River Basins 

within Allegheny 

County and City of 

Pittsburgh, PA

recreational standards and criteria for 

bacteria

FIB from tributaries most strongly correlated 

with streamflow, specific conductance, and 

turbidity

Burkholder

et al., 2007

F IF, 

IN, 

GW

1° 

Temp (All U.S.)

WC, Sed, Soil,

GW

Not 

spec-

ified

Not 

specified

Not

specified I No NA CAFO workshop proceedings and recommendations 

Accepted livestock waste management practices do not adequately or effectively 

protect water resources from contamination 

with excessive nutrients, microbial 

pathogens Impacts on surface water sources and wildlife 

have been documented in many agricultural 

areas in the U.S.

Byappana-

halli et al., 

2003

F IF, CTempSed, SoilECA Weekly samples 

were taken 

from 14 sites 

along coastal 

stream from 

June-

November 

1999 and from 

February-

November 

200, for a total 

of 710 

samples

No Dunes Creek watershed 

(primarily 

nondeveloped

Aquatic or wetland 

habitat; remaining land 

use 

Residential and 

agricultural) in northern 

IN, drains into Lake 

Michigan at a major 

recreational beach

EC in dunes Creek and beach water 

significantly correlated

Chronic loading of EC throughout the stream

Significant correlations between EC in stream 

water and sediment, submerged sediment 

and margin, and margin and 1 m from 

shore

EC is ubiquitous and persistent in the basin

EC in riparian sediments increased bacteria in 

the creek

Enlargement of the stream, increase 

drainage, and wetland loss may account for 

high EC levels

Byappana-

hallii et al., 

2007

F IN, CTempSed,

soil 

ECA Monthly 

sampling 

between May-

August 2003; 5

samples were 

collected from 

5 different 

rocks in each 

No Shoreline waters of lake 

Michigan (Ogden 

Dunes Beach, IN); 

Combination of urban 

and rural wastes, 

including sewage 

overflows, septic field 

leachate, and runoff 

EC associated with Cladophora (blue-green 

algae) may be a recurring source of 

indicator bacteria to the nearshore beach
August 2010

A-5

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

of the 2 beach

sites

from nearby urban 

areas and agricultural 

farms

Cabelli, 

1983

M,

F

C, 

IN

Temp WC TC, 

FC, Ent, EC

Male 

specific 

coli-

phage, CP

AH,

Acineto-

bacter sp, 

PA,

VP 

I,

J,

A, H

Epi/microbial 

data collected 

1972-1979; 

samples 

collected 

below the 

surface of the 

water during 

the time when 

people were in 

the water; collected 2

-3 

locations along 

each beach

NoSampling sites included 

beaches at New York 

City, NY; Lake 

Pontchartrain, New 

Orleans, LA; and 

Boston Harbor, MA

Assessment of the relationship between 

microbiological indicators of water quality 

and illness that may have resulted from 

swimming

Data resulted from EPA internal and 

extramural epi-micro projects

Epi studies used to establish 1986 EPA 

health effects criteria for marine 

recreational waters

Large number of pathogenic bacteria and 

viruses in municipal sewage

Campbell

et al., 

1999*

F C, 

IF

Temp WC TC, 

FC, EC

HPCA Summer 

sampling in 

1997; a total of 

26 sites were 

resampled

No Random selection 

(EMAP protocol) of 146 

streams located 

throughout Oregon

Abstract only

17% of streams exceeded the then current 

Oregon standard for water-contact 

recreation

FIB levels differed significantly among the 8 Oregon ecoregions

Chambers

et al., 

2005, 2008

F IF, 

IN

Temp WC, SoilTC, 

EC

A WC and soil 

samples 

collected from 

lakes, river, 

and puddles at 

intersections of 

major 

boardwalks

and along the 

main road

No Rural Alaska: Yup’ik 

village on the Yukon-

Kiskokwim Delta south 

of Bethel in a tundra 

ecosystem

Study conducted to determine main pathways 

(vehicles, shoes, and surface flow) of 

microbial water contamination In early summer, many ponds and puddles in 

and around town tested positive for TC and EC

EC also detected on tested shoes, dog paws,

and tires of all terrain vehicles returning 

from nearby dump 

Chamdra-

mouli et al., 2007

F IF Temp WC TC, 

FC, 

FS (Ent)

AC 

(atypical 

total 

coliforms)

G1-year sampling

at intake (lock) 

of a privately 

owned potable 

water supply 

on the 

Kentucky 

River; 

Water quality 

data 

No Kentucky River system: 

essentially a series of 

small lakes separated 

by locks, which

behaves differently 

under high and low 

flow conditions as well 

as seasonally

Objective was to predict peak indicator 

bacteria concentration in surface water from 

44 related physical, chemical, and bacterial 

data

Model provided slightly superior prediction of 

actual microbial concentrations when 

compared to multiple linear regression 

models
August 2010

A-6

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

augmented 

with flow and 

rainfall USGS 

data from

several 

upstream sites 

at locks and 

gauging 

stations 

Choi and 

Jiang, 

2005b*

MC Sub Ent, 

FC

F-specific 

coliphage

Adv40 A, 

F, B

100 mL of 

sewage mixed 

with 900 mL of 

marine water 

seeded with 1 

mL of 10

7

PFU/mL Adv40 (Adv 

serotype 40); inactivation 

results with 

sodium 

hypochlorite 

were 

compared at 0, 

1, 2, 3, 24, and 

48 hours

Yes Southern CA beaches

(not specified)

Abstract only Preliminary results showed that the 

inactivation of AD40 (66%) occurred mostly 

during the first hour, where most of the 

available chlorine is sequestered by 

particles and organisms present

F-specific phage showed to have high 

resistance to inactivation by chlorine

FC and Ent not resistant to chlorine with a 5-

log reduction by the first hour

Chu et al., 

2007*

F, E, MC Sub WC FIB

(not 

spec-

ified)

B Not specified No Fresh and brackish water 

obtained from Newport 

Bay Watershed, CA

Abstract only

No FIB growth in microcosms; FIB survival or 

growth appeared to be better in freshwater 

added with nutrient from bird feces and 

macro-algae in the dark (lab experiment)

Differences in bacteria species and 

community composition between fresh and 

marine microcosm

Total bacterial and viral direct counts 

increased in microcosms seeded with bird 

feces and macro-algae

Salinity, nutrients, and competition with 

indigenous microbial community contributed 

to the growth or death of FIB in WC

Cinotto, 

2005

F IF Temp WC, SedEC,

Ent,

FC,

A USGS sampling 

from

September

No West Branch Brandywine 

Creek, Coatesville, PA; 

urban/ industrial land 

USGS assessment of effects of sediment 

particle size, climatic conditions, aquatic 

growth, environmental chemistry, 
August 2010

A-7

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

FS 

(Ent)

2002-August 

2003; a total of 

64 baseflow 

and 15 

stormflow 

sampling sites

use serving as water 

supply, irrigation, and 

recreation uses

impervious surfaces, sediment, and soil 

filtration and dams on FIB

EC and Ent appeared to be related to specific 

particle size

Climate conditions affected FIB; e.g., drought 

of 2002 had lower overall bacteria 

concentrations than wet year of 2003 

Symbiotic relationship between bacteria and 

aquatic growth likely responsible for 

increased bacteria observed within a sampled impoundment area

Nutrients increased during both base-flow and 

stormflow that could had contributed to 

accelerate aquatic growth Impervious surfaces found to increase 

bacteria concentrations along the creek

Turbidity shown to indicate higher 

concentration of bacteria but the 

relationship was sporadic 

Clark et al., 

2008

E, MC 1° 

Temp,

(Sub)

WC FIB (not 

speci-

fied) I Not specified No Not specified, though 

Table 1 of Clark, 2008 

summarizes hydrogen 

peroxide 

measurements in 

various surface marine 

waters reviewed in 

article 

Review of hydrogen peroxide production and 

affect on FIB in marine recreational waters

Measured peak hydrogen peroxide 

concentration in surface coastal seawaters 

are too low to directly cause FIB mortality 

based on lab studies, but likely contribute to 

oxidative stress and diurnal cycling

Peroxide levels in the surf zone may be 

increased by additional peroxide production 

mechanisms such as deposition, 

sediments, and stressed marine biota, 

which may further enhance impacts on FIB 

in marine bathing waters

Coffey et 

al., 2007

FUUU None Crypto,

EC O157,

Salm, 

Campy, 

Giardia,

Rota-

virus, Norovirus 

G No Not specified, 

―agricultural 

watersheds‖

Evaluation of 13 quantitative simulations 

(microbial risk assessment models) for 

modeling bacterial pollutants in agricultural 

watersheds 

No one model suits all modeling criteria or 

needs

Pathogen predictions have proved variable 

and no model was capable of accounting 

for all geological and hydrological factors in 

addition to modeling the physical transport 
August 2010

A-8

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

of bacteria in surface runoff

Cole et al., 

2000*

FU TempU FC, 

EC, Ent

CP,

somatic 

coliphage

male-

specific 

coliphage

A, FMeasured 

quarterly for 3 

years and 

during storm 

events for 8 

months

No 2 unspecified watersheds 

impacted by animal 

agriculture, urban 

development, and rural 

residence

Abstract only

Geometric mean of FC, EC, and somatic 

phage generally higher at sites impacted by 

animal and human inputs (e.g., CAFOs) 

than at rural residential and background 

stations

Differences in indicator levels with land use 

most often statistically significant for 

somatic phages

FC levels dropped at CAFO after application 

of best management practices for animal 

wastes

Levels of all FIB increased during rainfall 

events at all sites

FIB correlated with total suspended solids,

but correlation differed for base and storm 

flows

Ent and somatic phages were most seasonal

with higher levels in summer

Colford et 

al., 2007

MC Sub WCEnt, 

FC, 

TC

Bacteroides,

coliphage

Adv Noro

-

virus

H Varied

depending on 

the specific 

indicator; participants 

recruited each 

sampling day; 

microbial water

quality 

sampled at 

multiple sites 

per beach and

multiple time 

periods per 

day

No Mission Bay, Southern 

CA: water quality 

standards had been 

exceeded ~20% of the 

time; recent MST 

studies suggested that

human fecal material 

constitutes a minor 

proportion of fecal 

inputs to the Bay

Traditional FIB used to monitor these 

beaches not associated with adverse health 

risks

Epidemiological results suggest a need for 

alternative indicators of water quality where 

non-point sources are dominant fecal 

contributors

Craig et al., 

2003

MC Sub WC, SedECEntColiphage Salm

Typh-

imurium,

Salm 

derby

B, FMicrocosms 

maintained 

at10° C, 20° C, 

and 30°C and 

inoculated with 

prepared 

strains of indicators and 

Yes NA; WC and sed 

samples taken from 

recreational coastal 

sites in Adelaide,

Australia

Decay rate of Salm spp. greater than either Ent or coliphage in WC and Sed Decay rate of EC similar to Salm spp in WC, 

although greater in Sed

Increased temperatures resulted in an 

increased decay rate for all organisms in 

the WC but to a lesser extent in Sed

Decay rates for both Salm greater in WC than 
August 2010

A-9

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

pathogens; 

micro-

organisms

enumerated 

and decay 

rates 

determined for 

Days 0,1, 2, 7, 

14 and 28

in Sed, which suggests that Sed may be 

acting as a reservoir for pathogens

Crowther et 

al., 2001

MC Temp WC TC, 

FC, 

FS

(Ent)

A8 designated 

bathing waters

No Fylde Coast, UK: 

economy in the study 

area dependent on 

tourism; there had 

been a recent major 

investment in the 

sewerage infrastructure

(new WWTP)

Before the WWTP, higher bacterial 

concentrations strongly associated with 

rainfall

TC and FC originated from the sewage 

sources but not FS (Ent) that may have 

been more strongly affected by diffuse 

catchment sources and did not decrease 

after WWTP

After the WWTP, catchment sources 

appeared to be of greater significance; 

however, rainfall remained as a significant, 

though less important predictor of FIB 

concentrations

After the WWTP, tide height at time of 

sampling, together with variables including 

sunshine and the proportion of onshore 

winds became of greater significance to FIB 

concentrations

Crysup and 

Mott, 2001*

F, EIF TempU FC, EC,

Ent

October 1999-

September 

2000; 8 

stations

sampled 

monthly and 

during significant 

rainfall (>0.9 

inches) 

No Oso Creek/Bay 

Watershed, TX: 

characterized by a 

wide range of salinity

and temperature; Oso 

Creek receives 

uncontrolled 

agricultural and urban 

runoff

Abstract only

Bacterial densities exceeded 1986 EPA rec 

water standards in 19% (FC), 20% (EC), 

39% (Ent) of dry weather samples at the 

mouth of Oso Creek

During rainfall, all bacterial standards

exceeded most frequently in the freshwater 

stations and for up to 72 hours

Ent persisted both in both saline and 

freshwater environments

Lowest bacterial counts recorded during 

drought conditions and warmer air 

temperatures

Davies-

Colley et 

al., 2008

F IF Temp WC TCECABaseflow 

sampling done 

monthly; 30 

No Toenepi 

Stream/Catchment, 

Waikato Region, New 

EC peaks well ahead of flow during storms

and concentrations increased with storm 

event size
August 2010

A-10

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

individual 

storm events

sampled 

during a 1-year

period, during 

storm events,

samples taken 

every 2 hours 

during 2 days

Zealand:one of the 

most intensively dairy-

farmed areas in the 

country, which is 

mostly flat with artificial 

drainage with 100% 

pasture

Because EC correlated well with turbidity, it

was used as surrogate for EC 

concentrations during storm events

Davis et 

al., 1995

F C, 

IF

Temp WC FC, 

FS/

Ent

A,

B

Sampling from March-May, 

1992;8

sampling 

surveys 

conducted: samples taken 

during low and 

high flow 

periods from 

stormwater 

inflow; a 48-

hour laboratory 

static 

effluent/stream 

mixture also 

assessed

No Coastal stream, above 

tidal influence, and 3 

nearby WWTP 

effluents at Galveston 

Bay (Houston), TX, 

which is a heavily 

urban environment

Study assessed the effect of dechlorination 

on FIB concentrations above and below 

WWTPs Improvement in bacterial water quality found, 

principally due to municipality efforts to 

correct illicit connections and other 

sewerage system problems

Regrowth of dechlorinated WWTP effluent 

bacteria was minimal

Ent found to be a better indicator of microbial 

water quality in stream for public health 

purposes

Deller et 

al., 2006

F NA Temp WCEC

Ent

PA, 

Staphyl-

ococcus 

aureus

B,

F

Microcosm 

experiments 

conducted 

summers 

2001-2003

Yes NA, source of water used 

in experiments not 

specified (studies 

conducted in Austria)

Ent showed to be the most resistant organism

and the most sensitive to solar irradiation

Results showed a significant correlation 

between radiation intensity and reduction 

rates

Best elimination of organisms occurs on the 

water surface with deeper water having less 

UV

High turbidity substantially reduces UV-B 

transmittance in water causing decreased 

elimination efficiency

Denis-Mize

et al., 2004

F, EIF Temp WC EC EV,

PV 

Reo-

viruses, 

Rota-

virus, 

E Three water 

samples 

collected at 

each site 

between 

December-

No Inland and coastal basin 

in OH, WA, IA, SC, WV 

Cuyahoga River Basin 

(OH)– urban and 

agricultural

Thornton Creek (WA) –

All sites showed evidence of fecal 

contamination and were positive for EC

All 5 sampling sites positive for viruses by 

both molecular and cell culture-based virus 

assays; overall, 87% of unseeded samples 

contained culturable viruses
August 2010

A-11

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

HAV May 1998 for 

range of 

streamflows; at 

least 1 sample 

from each site

collected 

during or after 

a storm event

urban

Iowa River (IA) –

agricultural row crop 

and confined animal

Cow Castle Creek (SC) –

agricultural

Clear Fork (WA) –

mining/rural residential 

with septic systems

After excluding potentially false-positive 

results, PCR assays identified reovirus in 

30% of the samples, rotavirus in 20%, and 

HAV in 17% of samples

Desmarais

et al., 

2000*

EC Sub WC, SedEC CP A, 

B, F

Field samples 

collected along 

the length of 

the river, at

both high and 

low tide, in 150 M increments 

North Fork of the New 

River Fort Lauderdale, 

FL

Abstract only Results along the river indicate that large 

numbers of EC are associated with low 

levels of conductivity and chloride and 

elevated levels of phosphate

CP found to increase with the overall tidal 

stage of the river and with wet conditions

Results from soil experiment indicate that EC

is capable of multiplying by two orders of 

magnitude when subjected to wetting and 

drying cycles and have a significant impact 

on the concentration in the water column

Authors concluded that CP is generally a 

more stable indicator

Donisson

et al., 2004

F IF Temp WC ECA Samples

collected every 

2 weeks for 2

years with a

total of 52

samples 

collected from 

each of 15 

sites

No Rural (hill-country) 

streams in the 

Whatawhata district, 

Waikato, New Zealand 

that were impacted by 

pastoral farming with 

grazing animals, 

indigenous forest, or 

pine forests

EC detected in virtually all samples and

highest in streams flowing through grazed 

pasture

There was a noticeable seasonal pattern in all 

streams regardless of land use, with 

highest bacterial counts in summer and 

autumn and lowest in winter and early 

spring

No obvious correlation between EC and 

rainfall or streamflow

28% of pastoral samples, 25% of indigenous 

forest samples, 14% of 7-year pine forest 

samples, and 5% in new pines stream 

samples (after planting) had EC 

concentrations associated with a high level 

of risk for contact recreation; the highest EC 

usually occurred in summer

Dufour, 

1984

F IN Temp WCEC,

FC,

Ent

HEpi-micro study

of recreational 

water 

No Keystone Lake, about 15 

miles from Tulsa, OK. 

Sampling sites located 

A good correlation was observed between 

swimming-associated GI symptoms and 

either EC or Ent densities in the water
August 2010

A-12

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

exposure and 

health 

conducted 

1979-1982

near sewage discharge

and outfall; Lake Erie, 

PA with 2 sites, 1 near 

a sewage outfall

FC showed little or no correlation to GI illness 

rates in swimmers

In general, high GI illness rates associated 

with high densities of FIB

Freshwater studies to form basis for 1986 

EPA recreational water criteria (see also 

Cabelli, 1983)

Edwards et 

al., 1997

F IF Temp WC FC, 

FS

(Ent)

A, FFIB measured for 

up to 3 years 

(September 

1991-April 

1994) at 5

sites; flow data 

collected from 

2 of 5 sites

No Two NW Arkansas 

streams: land use primarily pasture (57

-

90%; beef production 

and poultry CAFOs) 

and forest (6-40%)

For on the two sites with flow data, flow rate 

generally increased when FC and FS (Ent) 

also increased during all seasons

Ratios of FC and FS did not appear to reliably 

differentiate between animal and human 

sources of fecal pollution

Highest concentrations of FC and FS 

observed during the summer 

Ellis and 

Yu, 1995

F IF Temp WC, SedTC, 

FC, 

FS

(Ent)

Somatic 

phage

PA,

Salm 

A, FWeekly and 

storm event 

sampling from

October 1990-

February 1991

No4 CSO outfalls, the 

serving trunk sewer, 

and a downstream site 

on the main stream 

within the Pymmes 

Brook (urban) 

catchment in North

London, UK

CSOs serve as effective generator of bacteria 

and pathogens to urban receiving water In-stream Sed from sewer source function as 

reservoirs for high bacterial concentrations

over extended periods following wet 

weather conditions

FC and FS (Ent) demonstrated a clear ability 

to multiply and survive in Sed downstream 

of CSO outfalls with phages surviving 

longer than FC as distance from the CSO 

increases

Extended bacterial inoculation from 

contaminated sediment with FC and FS 

(Ent) equilibria indicate that a biotic balance 

is achieved between reproduction and 

predation rates

Elmir et al., 

2007

MC Sub WC, 

Soil 

Ent Staphyl-

ococcus 

aureus

A, CTwo sampling 

types, large 

and small pool: 

1) large pool 

study: 

microbial 

shedding from 

bathers as 

group; 2) small 

pool study: 

microbial 

release from 

Volunteer studies 

conducted at a marine 

beach in Miami-Dade 

County, FL using off-

shore water and on-

beach sand

Demonstrated that bathers shed significant 

concentrations of Ent and S. aureus into the 

WC; thus human microbial bathing load 

should be considered as a non-point source 

when designing recreational water quality 

models 

S. aureus concentrations at least one order of 

magnitude greater than Ent

Ent contribution from sand adhered to skin 

was small (5%) relative to the amount shed 

directly from the skin 

Ent and S. aureus decreased significantly 
August 2010

A-13

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

individuals + 

beach sand 

adhered to 

skin

between bathing episodes

Evanson

and 

Ambrose, 

2006

M, ECSub WC, SedTC,

EC, Ent

A Two month study 

at two sites in 

coastal 

wetlands: one 

site with 

presence of 

birds and the 

other (urban) 

located on the 

main channel 

of the wetland

No Santa Ana River 

Wetlands, Southern 

California:restored 

wetland designated 

open space and 

recreational by Orange 

County, CA; although 

limited public access is 

allowed, urban impacts 

are felt through 

landscape and 

agricultural irrigation 

runoff

Examined temporal trends of water and 

sediment-associated FIB after rain events 

along with spatial sediment characteristics 

and made comparisons to FIB levels

observed in adjacent surf zone waters. 

In first two rain events, TC/EC/Ent in wetland 

water and sediment peaked either on the 

same day or within several days later; the 

third rain event resulted in higher wetlands 

sediment TC levels only

TC in adjacent coastal waters consistently 

peaked on the same day as the rain event 

and deceased quickly

TC/EC ratios of surf zone samples less than 

10, indicating an increased probability of 

human fecal contamination

Wetland TC/EC ratio were 60 and 14 for the 

two sites and do not necessarily indicate 

human fecal contamination but suggest 

sediment-associated FIB may be distinct 

from those found in the WC samples Increases in sediment-associated FIB may be 

due to in situ population growth and/or 

increased survival due to changes in 

environmental parameters (salinity, 

moisture, and nutrient input) resulting from 

the rain events

Differences between the two wetland sites 

may be due to sediment differences 

(organic content and finer grain size)

Ferguson

et al., 1996

ECTemp WC, SedFC, 

FS

(Ent)

CP, F-RNA 

phage

Aero-

monas

spp,

EV

Crypto, 

Giardia, 

Salm

A, FWater and 

sediment 

samples 

collected 10 

times between 

September

1992-June 

1993 from 6 

sites within the 

NoUrban estuary in Sidney, 

Australia; tidal regions 

of the Georges River 

which is an important 

recreational and 

economic resource 

within the Sydney 

region, used for the 

production of shellfish 

Water quality affected by rainfall and sewage 

overflows with significant increase in fecal 

bacteria and pathogens In sediment, only FC increased by rainfall but 

sewage overflow resulted in increased FC, 

FS, CP, and Aeromonas

Salmonella occurrence appeared to coincide 

with rain events

Enteric virus did not correlate with wet 
August 2010

A-14

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

estuary and as popular venue; 

river receives inputs of 

urban runoff and during 

wet weather receive 

sewage 

weather

CP identified as the most useful indicator of 

fecal pollution

CP only indicator correlated to Giardia and 

Aeromonas

Ferguson

et al., 2003

UUUU NA EV, 

EC-

O157:H7 

Crypto, 

Giardia I NA No NA

Reviews the fate and transport of pathogens 

in watersheds supplying drinking water

Key processes determining the fate and 

transport of pathogens within watersheds 

are discussed in the context of changing 

agricultural practices, climate, and scale 

factors

Main factors for inactivation of viral and 

protozoan pathogens include water/osmotic 

potential, temperature, sunlight and pH, 

inorganic (ammonia) and organic nutrients

Transport processes for controlling pathogen 

movement include adsorption/desorption 

effects, hydrological movement, and 

mechanical and biological movement

Fernandez-

Molina et 

al., 2004

F IF Temp WC,

GW

TC, 

FC, FS 

(Ent)

CP,

HPC

HAV A, F51 samples total, 

28 from 11 springs, and 

23 samples 

from five 

different 

locations of the 

Vilanos River

NoMontefrío munipality 

(Granada, Spain)

which is rural with 

some agriculture; 

springs are used as 

drinking water with no 

treatment; Vilanos 

River receives WWTP 

discharges

No HAV detected in any spring water, but 

69.6% of the river water samples positive

No relationship between HAV and the FIB Conductivity and chemical oxygen demand 

correlated with all microbial water quality

indicators

Ammonia and phosphate correlated best with 

FC and FS

Francy et 

al., 2000

F IF, 

GW

Temp WC, 

GW

TC, 

EC

CP

Coliphage

A A total of 136 

stream water 

and 143 

groundwater 

samples 

collected from 

6 NAWQA 

study units 

throughout the 

U.S. (e.g., 

Kanawa-New 

River Basin in 

VA, WA, and 

No3-4 stream sites located 

within 6 NAWQA study 

units and from a variety 

of existing wells from 4 

of the study units

TC found in 99%, EC in 97%, and CP in 73% 

of the stream water samples

TC found in 20%, EC in less than 1%, and CP

in none of the GW samples

Coliphage samples became contaminated 

and not analyzed as part of study

Land use had the most significant effect on 

FIB in stream water

Presence of septic system near collection 

sites and well depth related to TCC in GW, 

although these relationships were not 

significantly different
August 2010

A-15

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

NC)

Garcia-

Armisen

and 

Servais, 

2007

F IF Temp WC EC, EntA For non-point 

sources, 

samples 

collected in 

rural areas 

upstream from 

WWTPs; 

Samples also 

collected at 

raw and 

treated effluent

of 9 WWTPs

No France: Seine river 

watershed 

characterized

by a high population 

density, intense 

industrial activity, and 

intensive agriculture, 

though some parts 

include forested, 

cultivated, and grazed 

areas (small streams)

Small streams flowing through pastures 

systematically more contaminated than 

those flowing through forest or cultivated 

areas

Results show that the land use of the 

watershed has a significant impact on the 

quantity of FIB brought to rivers by surface 

runoff and soil leaching

Study demonstrates the predominant 

importance of the point sources over the 

non-point sources of FIB

Gentry et 

al., 2007

F IF Temp WCEC Bacteroid

es (total) 

and 

bovine-

specific

A, FFrom April 2003-

February 

2004, a total of

84 individual

grab (WC) 

samples 

collected at 7

locations along

the main 

channel of 

Stock Creek

No Stock Creek Watershed

near Knoxville, TN: mixed watershed with 

human, cattle, and 

wildlife fecal inputs

Strong correlation between total fecal load, 

bovine fecal load, EC load rate, 7-day

antecedent precipitation, and turbidity

Transport and occurrence of Bacteroides and EC primarily due to runoff 

Gersberg

et al., 2006

F, MC Sub WCEC,

Ent

EV,

HAV

A, FFrom 2003 to 

2005, 20 

samples 

collected from 2 surfzone 

sites during 

wet and dry 

weather 

conditions

No Tijuana River and 

Imperial Beach, San 

Diego, CA

HAV and EV detected in 79% and 93% of the 

wet-weather samples, respectively

Concentration of HAV and enterovirus below 

detection for all dry weather samples 

collected at Imperial Beach

Regression analyses showed a significant 

correlation between the densities of both 

Ent and EC and HAV and EV levels

Giddings

and 

Oblinger, 

2004

F IF Temp WC, SedFC,

EC 

ColiphageA Sampling at 5

sites in 

Newfound 

Creek and 5

tributary sites 

during low flow 

conditions on 

May 28, 2003, 

and high flow 

on November 

No Newfound Creek 

Watershed, Western 

NC

USGS report

90% of the EC and FC samples exceeded 

corresponding EPA (1986) rec/ambient 

water quality criteria

During the high-flow sampling, all tributaries 

contained high densities of EC

Coliphage results indicated that non-human 

sources of bacteria present in one tributary,

and during high flow, human sources of FIB 

present in another tributary
August 2010

A-16

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

19,2003

An additional 5 

sites sampled 

for FC and EC 

in streambed 

sediments (low 

flow) and 

coliphage

Sediments do not appear to be a substantial 

source of bacteria relative to WC 

concentrations

Gronewald

et al., 2008

E IF Temp WCFCG Not specified NoUsed FC data from 

shellfish harvesting 

waters in the obtained 

for Newport River 

Estuary, NC

FIB concentration metrics, including MPN and 

CFU, are not direct measures of the true in 

situ concentration distribution of FIB, as a 

result, model and sample-based 

assessments can provide different results

In response to this problem, an innovative 

assessment based on Bayesian analysis 

was evaluated; results indicated that areas 

determined to be compliant according to the 

sampling may actually have an 

unacceptably high probability of being in 

violation of concentration-based water 

quality standards/criteria

Hall et al., 

2007*

F IF Temp WC FCA Sampling from 

2002-2006 on 

4 creeks within 

the Watauga 

River 

watershed; 14 

stations 

sampled on 

Sinking river, 9 

stations on 

Cash Hollow 

Creek, and 12 

stations on 

Buffalo Creek; stations 

sampled on a 

month or 

quarterly basis

Watauga River 

watershed,

NE Tennessee: agricultural input is a 

major source of 

pollution to for Sinking 

and Boones Creek; urban runoff is a major 

source of pollution to 

the Cash Hollow Creek

Abstract only

Sampling results from Buffalo Creek indicated 

that FC concentrations were high at 

stations adjacent to agricultural land

Regression analysis indicated that chemical 

water quality parameters do not provide 

additional information regarding sources of 

fecal contamination

Hartel et 

al., 2007

F, 

E, M

C, 

IF

Trop, 

Temp

WCEC,

Ent

D 20-30 samples 

from 

Mayaguez Bay (Yaguez River)

No Mayaguez Bay, western 

Puerto Rico is 

dominated by 

Mayaguez, a modestly 

Targeted FIB sampling and fluorometry (MST) 

identified two hot spots of human fecal 

contamination in the Yaguez River and on 

St. Simons Island
August 2010

A-17

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

on February 2, 

2005; 

3 separate 

sampling 

periods in St. 

Simons, 

including a 

beach, storm 

drain, and 

inland creek

sized city and had a 

history of fecal

contamination 

problems; St. Simons 

Village on the southern 

end of St. Simons

Island, one of the State 

of Georgia’s (U.S.) 

barrier islands

Haugland

et al., 2005

FC Temp WC EntA Sampling on 

weekends and 

holidays from 

May-August,

2003; 3 sampling visits 

daily (8 AM, 11 

AM, and 3 PM)

in waist-level 

(1m deep) and 

shin-level 

water (0.3m 

deep) 

No West Beach at the 

Indiana Dunes National 

Lakeshore in Porter,IN

on Lake Michigan and 

Huntingon Beach in 

Bay

Village, Ohio on Lake 

Erie; selected, in part, 

as both generally 

meeting the state

or local water quality 

standards while having 

potential for

contamination by a 

human source of fecal 

pollution 

Samples collected and analyzed by QPCR 

and culture-based methods

Regression analysis showed a positive 

correlation between both methods

He et al., 

2008

MC Sub WC TC, 

FC, 

Ent

A,

F, G

Dry and wet 

weather 

sampling

Dry event refers 

to 7 days after 

a rainstorm 

and wet event 

refers to 

sampling 

within 0-5 days 

after a 

rainstorm

Wet sampling –

daily samples 

taken from 

eight locations 

along the 

No Coastal watersheds in 

San Diego County in 

southern California

Beaches receive direct 

discharges from 

stormdrains, creeks or 

rivers, or indirectly 

through lagoons

Urbanized land uses 

upstream and year-

round recreational uses 

for approximately 1-2 

million visitors yearly

Study investigated temporal and spatial 

variations in FIB concentrations in two San 

Diego beaches

Large temporal and spatial variations in FIB 

concentrations along the two beaches

Rainstorm-induced runoff from the 

watersheds impacted significantly water 

quality of the beaches adjacent to lagoons 

during the first 1-2 days after a rain event

Geomorphology of the beach shoreline, 

distance from the outlet channel, wind 

strength, wind direction, tide height, wave 

height, rainfall, time lapse after a rain event, 

or channel flow rate all were factors that 

significant impacted FIB distribution in the 

shoreline water quality
August 2010

A-18

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

shoreline at 

each beach 

He et al., 

2007

FC Sub WC, 

Sed

TC, 

FC, 

EC, 

Ent

A Samples taken 

from randomly 

selected sites 

in streams/ 

creeks (500 

samples) 

No 10 watersheds within the 

San Diego region in 

Southern California

Land use dominated by 

undeveloped vacant 

lands and 

park/recreational areas 

(75%) and residential 

and agricultural land 

uses comprising 10% 

and 7%

FIB levels varied significantly in flowing water, 

ponded water

Associated sediment FIB concentrations in 

ponded water in waterways significantly 

higher than in flowing water

Sediment under ponded water had a high FIB 

concentration

FIB concentrations in ponded water tended to 

increase with increasing water temperature 

and to decrease with increasing water 

salinity

Heilman, 

2000

F, EC Trop WC FC, 

EC, 

Ent

A, FYear-long 

sampling 

study; four 

sites sampled 

weekly in 

August 1998 

through June 

1999

No Shallow bay in gulf coast 

with frequent bacterial 

standard exceedances.

Abstract only Sometimes high counts of fecal and Ent Site with the highest counts had extensive 

shorebird usage near the outfall of a 

wastewater treatment plant

Low bacterial counts found during drought 

conditions and warmer air temperature

Significant negative correlations found 

between salinity and all fecal FIB

At the two sites with highest salinity, Ent 

exceeded EPA water criteria more 

frequently than fecal coliform but at 

freshwater sites both fecal coliform and EC

exceed EPA criteria more frequently than 

Ent

Hendry et 

al., 1982

F IN Temp WC FC, 

FS

A, HSampling

occurred 

during two 5-

day periods in 

late May-early 

June, July 

1976

No Shallow eutrophic lake in 

a region known fecal 

impacts from 

agriculture, wildlife, 

septic systems

Main sources of FIB were cattle watering 

sites, farms, public beaches, some flooded 

septic tanks, and a bird sanctuary Impairment of water quality localized to 

shoreline locations near the suspected 

source of the input of bacteria

FIB concentration increased after rainfall –

about 10× increase – however this effect 

lasted only 2 or 3 days

FIB levels low and did not exceeded 

Canadian levels

Hijnen et 

al., 2007

F, MIF, 

IN, C

Temp WC EC, 

Ent

B, H4 different 

locations of 

water sampled

Yes Waters drawn from a 

small stagnant lake, a 

ditch, and a large river

EC similar or more persistent than Ent in 

fresh water

In salt water, Ent more persistent than EC
August 2010 A-19

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Experiments 

conducted in 

laboratory 

mesocosms

Decay rate increased with temperature

Hood et al., 

2003*

F, 

M

M, 

?

Sub WC, 

sed

FC, 

Ent

Coliphage A Experiments 

conducted in 

laboratory 

mesocosms in 

waters 

sampled from 

multiple 

sources

No Water sources not fully 

described. Sources are 

fresh and brackish

Abstract only

Ent and fecal persisted longer in sediments 

than in the WC

Ent and fecal persisted longer in the fresh 

water than in brackish and saline waters

coliphage not detected beyond three days

Hoyer et 

al., 2006

F IN Trop/

Sub

WC EC A 79 lakes 

sampled once 

during a 9 

month study

30 lakes 

sampled 

intensively

No Lakes sampled located in 

numerous drainages 

presumed to be 

heterogeneous

Septic tank sources 

confirmed for some 

lakes

Spatial variations in lakes studied less than 

temporal variations in EC density.

Open-water samples (taken away from litteral 

zone) had consistently fewer EC than 

littoral samples

Hyer et al., 

2007

F IF Temp WC EC A During 2005 and 

2006, 20 

streams and 

springs

sampled in 

Shenandoah 

National Park

Most sampling 

occurred 

during low flow 

conditions 

during the 

warm months; 

high outdoor 

recreational 

and bacterial 

survivorship

Few event 

sampling

No Recreational use for 14 

streams out of the 20, 

and 6 in control basins 

where minimal 

recreational activities 

occurred (very pristine)

Relatively low EC concentrations during lowflow conditions

No statistically significant increase in EC

density observed in the recreational 

streams relative to the control streams

Results showed that recreational activities 

had no significant effect on EC density

After rain, EC density increased by nearly a 

factor of 10 and the Virginia instantaneous 

water-quality standard for EC frequently 

exceeded

Low EC concentrations in springs as well
August 2010

A-20

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Ishii et al., 

2006b

F IN Temp

Cladophora attached to submerged rocks

EC 

(STEC), 

Salm

Shig,

Campy

A Samples 

collected from 

Lake side and 

Ditch side; 

samples were 

collected from 

submerged 

rocks below 

the waterline

Samples 

collected in 

July and Sept 

2004 and 

monthly 

between July 

and October 

2005

No Combination of rural and 

urban waste, including 

combined sewage 

overflows, septic field 

leachate, urban runoff, 

sludge or runoff from 

manure farm fields, 

sedimentation, and 

nutrients

Study to assess the presence of pathogens in

green algae Cladophora

Shigella and STEC detected in 100% and 

25% in algal samples near Burns Ditch in 

2004, but not in 2005

40 to 80% of Salmonella measured in the 

ditch- and lakeside samples

Campylobacter detected in 60-100% of lake 

and ditchside samples

Results show that Cladophora is a likely 

secondary habitat for pathogenic bacteria in 

Lake Michigan

Iwamoto et 

al., 2005

F IN Temp WC FC Shigella 

sonnei

H Samples 

collected on 2 

occasions; FC 

enumerated 

for both 

samples and 

Shigella 

sonnei

enumerated 

for only one

No Watershed is in a large 

park, presumably 

separated from urban 

fecal pollution sources

The likely source of Shigella sonnei for this 

outbreak was an infected swimmer

Shigella sonnei was detected despite no 

apparent sewage contamination

Routine monitoring would not have prevented 

the outbreak

Jamieson, 

et al., 

2004a

F IF NA Soil, 

sed, 

WC

NA 

(gen-

eric)

NA 

(generic)

G, INA No NA This is a general modeling paper not specific 

to an indicator or pathogen

Deviation of removal processes from first

order decay is likely

There is a significant data/knowledge gap 

related to overland transport of 

microorganisms at the small watershed 

scale

Current models for settling of particle

associated bacteria (PAB) are empirical; 

efforts should be made to develop

phenomenological models
August 2010

A-21

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Jamieson 

et al., 

2004b

F IF Temp WC ECC After initiation of 

in situ 

mesocosm 

experiments, 

samples 

collected at 15 

min, 1 hr, 2 hr, 

4 hr, 8 hr, 20 

hr and daily 

time intervals 

for a duration 

of 20-24 days, 

with sample 

collection 

higher during 

storms

Yes Streams are described as 

―rural streams.‖ No 

description is provided 

on land use in 

drainages.

Inactivation estimated for EC in bed sediment 

was an order of magnitude less than that 

estimated for the water column

Concentration of re-suspended did not appear 

to correlate with total suspended solids 

(TSS)

The authors assert that inactivation (removal) 

in sediments does not follow first-order 

kinetics

Jeong et 

al., 2005

E, FIN, 

SW

Sub WC, 

sed

FC, 

EC, 

Ent

A, 

B, G

During a 6-month 

study duration, 

samples 

collected 5 

times per 

month for dry 

weather and at 

unknown 

frequency after 

rain events > 

0.25 cm

Sediment 

samples 

collected daily 

for at least 

three days 

after rainfall 

events > 0.25 

cm

Yes Stormwater drains from a 

densely urbanized area. Sediment 

samples drawn near 

the stormwater outfall.

Settling of particle-associated bacteria (PAB) 

observed in the laboratory and inferred from 

filed measurements. The propensity for FIB 

to attach to particles varied with particle 

size and FIB type (FC, TC, Ent)

The non-settling fraction of FC, EC, and Ent 

varied from 65 to 85%

The authors suggest sediments should be 

sampled in addition to the water column 

when assessing the health risks associated 

with waters

Jiang et al., 

2001

MC Sub WC TC, 

FC, 

Ent

Coliphage F-specific 

coliphage

Adv A, 

E, F

Study duration of 

1 month, 

sampling at 12 

sites, sampling

conducted 

once at each 

site.

No Multiple watersheds 

drained to study 

waters. Watershed 

descriptions not 

provided in the report, 

but based on location 

of the study sites, all 

drainages are 

This study was primarily concerned with 

methods development

For the limited number of samples in the 

study, adenovirus detection not correlated 

with level of fecal indicator bacteria (TC, 

FC, Ent).

Limited data indicate that urban runoff is the 

source of adenovirus in the study waters
August 2010

A-22

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

presumed impacted by 

fecal pollution.

Because virus detection done by PCR, 

nonviable and damages viruses may have 

been included in estimates of virus 

concentration/presence

Jiang et al., 

2007

M, EC Sub WC TC, 

FC, 

Ent

F+ 

coliphage 

Adv,

EV

A, FFor a study 

duration of 1 

year, sampling 

conducted at 

15 locations, 

with a biweekly 

frequency 

during summer 

and a monthly 

frequency 

during other 

months.

No Estuary in a major 

urbanized area with 

known impairment

Detection of human enteroviruses depends 

on a distribution pattern that is opposite of 

fecal indicator bacteria (TC, FC, Ent); the 

temporal variations in viruses may be the 

result of temporal trends in viral shedding or 

―heightened anthropogenic activities‖ during 

summer months

FIB (TC, FC, Ent) displayed a strong 

seasonal pattern (high during winter 

storms) in Newport Bay, CA; gross mass 

balance considerations indicate the high 

FIB loads during storms are not from 

sewage plants, but from non-point sources 

and agricultural point sources

F+ coliphage displayed temporal and spatial 

variations similar to those of FIB

Jones and 

Bryant, 

2002*

FU Temp WC ECD All samples 

taken in a 

single month 

Samples drawn 

from an 

unknown 

number of 

sites in two watersheds

No Not specified Abstract only

Isolates indicated contamination by people, 

cattle, pets, birds, horses, raccoons, and 

pigeons

Kay et al., 

2007

F All All Soil, 

feces

FIB 

(cons-

idered 

as a 

group)

Crypto,

EC

O157:H7 

and 

others

G, 

I, J

NA No Though no specific 

watershed was studied, 

work pertains to 

agriculture (livestock) 

dominated drainages

Insufficient temporally- and spatially-resolved 

data are available to calibrate proposed 

models for indicator organism and 

pathogen flux from agricultural sites

Small watershed features (buffer strips, other 

best management practices) can exert 

large influences on indicator organism and 

pathogen fluxes

A data gap related to contribution of 

sediments to indicator organism fluxes is 

the influence of sediment characteristics 

(grain size, mineralogy, etc) on indicator 

fate

Keeley and F IN Temp WC EC, Turbidity Crypto, A 193 samples No Drainages to sample Occurrence of Crypto and Giardia
August 2010

A-23

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Faulkner, 

2008

TC Giardia taken at 17 

locations on an 

inland 

reservoir. 

Samples 

collected at 

frequency 

between 

monthly and 3 

months over a 

27-month 

study duration.

sites varied. Most 

drainages impacted by 

agricultural runoff. 

Some sites located in a 

wildlife refuge. Several 

sites impacted by 

WWTP discharge or 

septic systems.

widespread; this finding is consistent with 

high proportion of rangeland in study area

The highest Crypto concentrations obtained 

during calving season; calving season 

coincides with the wettest period

Correlation not found between concentration 

of fecal indicators and Crypto; authors 

speculate lack of correlation is a results of 

different fate (settling) and survival 

characteristics

Ki et al., 

2007

M, EC, 

TI

Sub WC TC, 

FC, 

Ent

A, GHourly sampling 

conducted for 

at least 2 

weeks (only 

data taken in 

the 2-week 

period 

analyzed) at 

multiple sites

Samples 

collected at 

ankle- and 

waist-depth

Yes Coastal waters and 

waters in a tidally-

influenced marsh near 

a large urban area with 

known fecal impacts

Autocorrelation and cross correlation of 

indicator organism concentrations in time 

series (hourly time step) indicate diurnal 

pattern of occurrence in the surface zone 

and ―semi-diurnal‖ pattern in a tidally-

influenced marsh

Decay rate constant values predicted in 

modeling consistent with those from the 

literature for sites/waters with similar 

characteristics

Lee and 

Bang, 2000

F IF Temp WC NA NA NAA No 

microbiological 

analyses 

conducted

No Urban drainages Study primarily concerned with variation of 

physical and chemical parameters during 

storm events

Lemar-

chand and 

Lebaron, 

2003

F IF Temp WC FC, 

FS 

Crypto, 

Salm

A Sampling 

strategy not 

described

No Upstream drainages of 

the study water are 

mixed forested and 

animal husbandry land 

uses; 21 WWTP 

outfalls located in the 

study watershed 

Daily loads of FC and FS much less variable 

than daily load for Salm and Crypto

In analyses of WWTP influent and effluent 

and surface water samples, did not find a 

significant correlation between Crypto and 

FC or FS in WWTP influent, but did find a 

significant correlation between Crypto and

FC (but not FS) in wastewater plant effluent 

and between Crypto and both FS and FC 

concentration for surface waters. 

Higher Crypto concentration in WWTP 

effluent than influent on several occasions, 

which was attributed to high temporal 

variability in Crypto concentration; noted 
August 2010

A-24

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

that Crypto loads depend on level of Crypto 

infection in communities whereas indicator 

loads do not

Lévesque 

and 

Gauvin, 

2007

F, MU Temp WC FC, 

EC, Ent

H NA No Study is general and 

nature and not related 

to a specific watershed

Authors suggested Canadian water quality 

standards of 100 CFU EC/100 mL for fresh 

water and 35 CFU Ent/100 mL for marine 

water

Lipp et al., 

2001a

E, MC Trop WC, 

sed

FC, 

Ent

CP,

coliphage

Crypto, 

Giardia, 

enteric 

viruses

A Surface water 

samples 

collected at 12 

sites, monthly 

samples, study 

duration of 1 

year; sediment 

samples 

collected 

quarterly

No Study conducted for 

shellfish harvesting 

waters whose drainage 

includes impacts from 

residential land use 

and in some cases 

high density of on-site 

disposal (septic) 

systems

Levels of CP in sediment up to 5 orders of 

magnitude greater than those observed in 

the water column; sediment and water 

column concentrations of Ent generally 

within an order of magnitude

Bacterial and viral indicator concentrations 

negatively correlated with temperature

FC negatively correlated with salinity

Seasonal variation of bacterial and viral 

indicators significant; high concentrations in 

both the water column and sediments 

observed in August and the study period 

was December-February

The concentrations of fecal indicators (FC, 

Ent, CP, and coliphages) not correlated 

with the occurrence of Crypto or Giardia

Authors suggested that perhaps Crypto and 

Giardia occurrence is episodic, whereas 

indicators have more sources and have 

sources that are more consistent

Lipp et al., 

2001b

E, FC, 

IF

Trop WC FCAWater quality 

measurements

taken monthly 

for a 2-year 

period 

No Drainages above sample 

locations either 

primarily agricultural or 

mixed agricultural-

urban

Extreme El Niño winter months are 

characterized by greater fecal pollution 

resulting from greater precipitation

Lopez et 

al., 2008

F IF Temp WC ECG Sampling 

performed by 

the USGS 

from 1997-

2002; sample 

collection 

frequency not 

provided

No Study drainage land use 

was a mix of 

agricultural (poultry 

farming), forested, 

urban, and aquatic

EC concentration found to be related to 

drainage urban land use extent

Future work will allow prediction of temporal 

variations in water quality

López-Pila 

and 

F IF Temp WC EC RotavirusG No sampling 

performed

No Study conceptual Fecal indicator (EC) concentrations assumed 

to be log-normally distributed
August 2010 A-25

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Szewzyk,

2000

The ratio of fecal indicators and rotavirus 

concentration assumed to be constant over 

all samples

Mathes et 

al., 2007

F IF Temp WC EC Bacteroides, 

Ent 

marker, 

human 

urine 

marker

D Water samples 

collected twice 

at each of 4 

sites. Samples 

collected in 

October and 

September

No Study drainages primarily 

covered with forest, but 

characterized by 

frequent high levels of 

fecal indicator bacteria

Intent of study was evaluating indicators in 

their ability to determine source of fecal 

pollution

McCambridge and 

McMeekin,

1981

E C ? WC EC SP, 

Enterobacter 

aerogenes

Salm, 

Klebsiella 

pneumoniae

B All experiments 

conducted with 

fresh estuary 

water; no 

information 

provided on 

season or 

frequency for 

which water 

was collected

Yes Experiments conducted 

in natural and 

autoclaved estuary 

water from an estuary 

with unknown water 

quality

Decay of EC (and alternative indicators and 

pathogens) is a result of the interaction of 

solar radiation effects and predation; one 

possibility is that solar radiation causes EC 

to become more susceptible to predation

Menon et 

al., 2003

F, 

M

IF, 

C

Temp WC EC SP Salm 

typhimrium

B Experiments 

performed 

over a 1-month

period; sample 

collection 

frequency not 

provided

Yes Freshwater samples 

collected downstream 

of a large urban area

Marine samples collected 

from a pier in a large 

urban area

Grazing by protozooplankton was the 

dominant process in mortality of both types 

of fecal bacteria and for autochthonous 

bacteria

Portion of decay attributable to processes 

other than grazing was well-characterized 

by first-ordered kinetics for EC

Mortality rates of fecal bacteria (EC, 

Salmonlella typhimurium, S. faecium) not 

significantly different

Molina et 

al., 2005*

F IF Temp WC, 

feces

Ent D Monthly water 

and feces 

samples

No Farms where cows have 

unrestricted access to 

streams

Abstract only

Ent species observed in feces different from 

those observed in streams

Myers et 

al., 1993

F IF Temp WC FC, 

EC

A, 

C, 

G

Unknown Yes Study area is in a 

National Recreation 

Area located in an 

urbanized area and 

downstream of a large 

WWTP

Summer decay rates for FC and EC generally 

greater than winter decay rates

Noble et 

al., 2004

F, 

M

IF, 

C

Sub WC TC, 

EC, 

Ent

F+ 

specific 

coliphage

B Experiments 

performed in 

seawater from 

Yes For experiments, marine 

and fresh waters 

spiked with WWTP 

All indicators degraded faster at 20° C than at 

14° C; the ambiguous effect of temperature 

and differences between results of this 
August 2010

A-26

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

a bay near a 

bathing beach 

or freshwater 

from a creek 

flowing 

through a state 

park

effluent, raw sewage, 

or urban runoff

study and those in other studies is 

acknowledged

Inoculants did not influence decay rates

Overall decay rate highest for EC and lowest 

for Ent for all experiments

EC growth observed at low solar radiation, 

low temperature conditions

Decay rates of indicators similar in fresh and 

saline waters

Decay rate results at variance with rates 

reported in the literature and indicate 

significant temporal and spatial differences 

may characterized decay among sites

Noble et 

al., 2003

F, MIF, CSub WC TC, 

EC, 

Ent

F+ 

specific 

coliphage

B Experiments 

performed in 

seawater from 

a bay near a 

bathing beach 

or freshwater 

from a creek 

flowing 

through a state 

park

Yes For experiments, marine 

and fresh waters 

spiked with WWTP 

effluent, raw sewage, 

or urban runoff

All indicators degraded faster at 20°C than at 

14°C.

Inoculants did not influence decay rates

Overall decay rate highest for EC and lowest 

for Ent for all experiments

EC growth observed at low solar radiation, 

low temperature conditions

Decay rates of indicators similar in fresh and 

saline waters

Decay rate results at variance with other rates 

reported in the literature and indicate 

significant temporal and spatial differences 

may characterized decay among sites

Obiri-

Danso and 

Jones,

1999

F IF Temp WC, 

sed

FC

(all 

EC), 

FS 

Salm, 

Campy

A Bimonthly 

samples 

collected from 

tributaries, 

main stem and 

WWTP outfall 

for 24 months

No River reach sample 

locations downstream 

of a WWTP outfall; 

land use mainly 

agricultural (extensive 

sheep and cattle 

grazing) along the river 

reach studied

In the water column, indicators did not show 

seasonal variations, Campy more plentiful 

in winter months, possibly due to less die-

off and high wash-off of Campy from 

grazing lands during relatively rainy periods

In sediments, there was no seasonal variation 

in Campy occurrence

Okabe and 

Shimazu,

2007

F, MIF, CTemp WC TC, 

FC

BFB Experiments 

performed in 

filtered and 

unfiltered river 

water and 

filtered and 

unfiltered 

Yes Drainages not described Decay rates of FC not strongly influenced by 

salinity; increasing salinity greatly increased 

TC decay rates; 

At temperature ≥ 10°C, TC and FC decay 

rates in unfiltered river water very low or 

negative (growth); B. fragilis decay greater 

at all water temperatures and growth curves 
August 2010

A-27

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

seawater appeared to have a small shoulder and very 

long tail

Olyphant et 

al., 2003

F IF Temp WC EC A, GSamples 

collected once 

per week for 3 

years and via 

auto-sampler 

during 10 

storms during 

that period

No One drainages above 

sample sites recreation 

areas with sparse 

residential land use; a

second drainage has 

mixed residential, 

agricultural and 

undeveloped land use

During one rain event, EC discharge from a 

small wetland fell sharply after at the 

hydrograph peak. Potential causes are 

association of EC with settleable particles 

or die-off

The signature of a CSO discharge clearly 

visible in the trend in EC concentration for a 

large storm known to cause a CSO; pre-

CSO concentrations of EC elevated; post-

CSO concentration increased by more than 1-log

Seasonal variation in EC observed; a

plausible explanation for increased warm-

temperature EC concentration is higher soil 

temperature promoting ―population 

explosion‖ of EC in soils with subsequent 

transport of EC to receiving waters during 

relatively small rainfalls

Olyphant,

2005

FC Temp WC EC A, GSamples

collected at 

8AM and 1PM, 

Mon-Fri, early 

July-early 

September

No Studies conducted at four 

beaches, two in a large 

urbanized area and two 

in state parks, though 

with known impacts In an attempt to eliminate spurious 

correlations from analyses, authors 

conducted partial correlations and 

determined that (1) wave height tended to 

be the dominant storm-related parameter 

(for predicting EC concentration); that (2) 

turbidity turned out not to be significant 

when the effects of other variables 

accounted for; and (3) rainfall had only one 

statistically significant partial correlation

Paul et al.,

1995

F, 

M, GW

GW

, C

Trop WC, 

GW

EntCP,host 

16

A Two sampling 

episodes 

(March and 

August) 

conducted, 

with samples 

drawn from 

observation 

wells and 

marine waters

No Aquifer and coastal 

waters are impacted by 

septic systems from 

residential land-use, 

including tourist sites.

Aquifer is subject to 

treated WWTP effluent

Fecal pollution from septic drainfields, WWTP 

effluent injection and other sources 

apparent sources of aquifer contamination.

Observation of fecal indicators in coastal 

waters is not necessarily associated with 

discharge to marine waters from the 

aquifer; other possibilities are runoff or 

mobilization of indicators that have grown in 

waters or sediments

Pennington 

et al., 2001

F IF Temp WC FC, 

EC, 

TC

A Sampling 

conducted only 

during summer 

No Sample sites widely 

dispersed

Study intent was relating indicator occurrence 

to human ecosystem impacts

Levels of FC, EC, and TC found to 
August 2010

A-28

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

(low-flow) 

months for 2

years; sample 

collection 

frequency not 

provided

correspond to level of ecosystem human 

impact as measured by physico-chemical 

properties of waters and by direct 

observation of ecosystem in the vicinity of 

sample sites

Petersen et 

al., 2005

F IF Temp WC TC, 

EC, 

FC

A WWTP effluent 

(36 plants, 2 

samples per 

plant), 

stormwater 

outfalls (52 

pipes, each 

sampled 

once), and in-

stream 

samples, 

monthly

No Large impacted 

watershed with multiple 

WWTPs, agricultural 

use in upper reaches 

and urban land use in 

lower researches

Range of TC, FC, and EC shown in figure for 

WWTP effluent and stormwater outfalls

In-stream geometric mean of EC and FC 

shown for locations on main stem and a 

tributary

Dry weather water quality dominated by 

stormwater and WWTP effluent (though 

authors claimed EC concentration in 

WWTP effluent typically 5 CFU or less)

Event water quality dominated by non-point 

sources

Relative abundance of indicators determined 

by regression (though non-detect may not 

have been handled effectively)

Petersen et 

al., 2006

F IF Temp 

(in 

study)

WC FCA Data taken from 

multiple 

sources to 

create an 

approximately 

30-year period 

of record; 

samples drawn 

at different 

intervals for 

different 

collecting 

agencies

No Both study waters are 

located in an urban 

area and both are 

known to be highly 

impacted by fecal 

pollution

Very high number of exceedances (>90%) 

observed (based on FC concentration) for 

all sample sites on both study waters

Correlation of FC with rainfall and streamflow 

confounded on one study water by flood-

control retention and releases in a reservoir 

in the drainage

FC correlation with days since last rain and 

rainfall amount was poor for both study 

waters

Rees et al.,

2005

F IF Temp WC TC, 

FC

CP, 

F+ and F-

coliphage 

Sorbitol-

ferment.

Bifido-

bacteria, 

Rhodo-

coccus 

copro-

Crypto, 

Giardia

6 locations, 3-

year study 

duration, 

monthly, 

storm-based 

and 

continuous 

sampling

No Drainages for sample 

locations wildlife-

dominated, agriculture-

(cow pasture) 

dominated, or 

residential/commercial 

mixed-use

The occurrence of Crypto and Giardia in 

tributaries of small watersheds is not easily 

explained by [other parameters]...presence 

or absence of standard indicator organisms 

or source-specific organisms

Small rainfall events can wash Crypto oocysts 

in the near stream area into streams, 

elevating stream concentration (spatial 

variability); production of oocysts by wildlife 

may be seasonal and may occur with a 
August 2010

A-29

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

philus different seasonality than changes in 

indicators [temporal variability] 

Rex et al.,

2005*

M, FE, 

IF

Temp WC EC, Ent, 

FC

m-phage, 

s-phage

Adv, EV, 

rotavirus, 

astrovirus

A Dry and wet 

weather 

samples 

collected at 

one freshwater 

and one 

marine water 

site. 

No Insufficient detail

provided

Abstract only

No significant correlation found between any 

pathogen and any indicator for both the 

fresh water and marine sites

Riou et al.,

2007

M, EC, 

TI

Temp WCEC FRNA-

specific 

bacter-

iophages

Astrovirus A, GMonthly samples 

collected 

during 3-year 

study; sample 

times selected 

to include 

different 

hydrodynamic 

and weather 

conditions

No The coastal area studied 

has a low population 

density but receives 

flow from a large river 

with significant 

upstream human and 

animal fecal impacts 

EC concentration in coastal tributaries varied 

significantly during rainfall events, while 

bacteriophage concentration generally did 

not

Roser and 

Ashbolt,

2004

F IF Sub WC EC, 

Ent

CP

24-

ethylcopr

ostanol, 

others not 

specified

Crypto, 

Campy, 

others not 

specified

A, GIntensive 

sampling 

conducted at 

multiple sites 

for 2-6 rainfall 

events

No Sample sites had one of 

three drainage types:

fully-protected; light 

grazing and peri-urban; 

and dairy urban with 

known faulty onsite 

septic systems

Increases in EC and Entdensities, but not 

Crypto concentration, during rain events in 

watersheds not suspected to be impacted 

by human fecal pollution

High variability for all indicators and 

pathogens observed, even when only 

samples taken during base flow conditions 

are compared

Loading should be considered when 

assessing risk—reservoirs and drinking 

water storage are loaded with indicators 

and pathogens during precipitation events

Ryu and 

Abbasza-

degan,

2008

F IF Sub WC EC, 

TC, 

FC

Male 

specific 

coliphage

somatic 

coliphage

Crypto, 

Giardia

A 192 water 

samples from 

5 sites 

analyzed; monthly 

collection over 5-year study 

period

No Sample sites correspond 

to three drainages: one 

primarily range land, 

one primarily 

recreational lands, and 

one mixed use with 

significant residential 

land use

No seasonal variation observed in Crypto and 

Giardia concentration, despite marked 

seasonal variation in TC and FC; TC and 

FC both relatively high during monsoon and 

summer seasons

For the entire data set, Giardia concentrations 

correlated with FC, but Crypto 

concentration did not correlate with FC or 

other indicator organism concentrations

Giardia concentration varied significantly 

spatially; Crypto concentration did not
August 2010

A-30

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Santo 

Domingo,

2008*

UU Trop WC EC, 

Ent

E Not specified No Not specified Abstract only

Study proposes development of molecular 

techniques for better estimate of population 

densities inclusive of damaged or 

nonculturable organisms.

Santoro 

and 

Boehm,

2007

MC Sub WC TC, Ent, 

EC

Bacteroides

molecular 

marker 

(HF 

marker)

A Nightly sampling 

at multiple 

locations along 

a 9 km stretch 

of beach for 1 

month in each 

of 2 summers; sampling 

schedule 

intended to 

expose 

variation due 

to tides 

No Study area in a highly

urbanized region with 

known human and non-

human pollution 

(particularly seabirds) 

sources

Occurrence of HF (human-specific) marker 

not correlated with fecal indicator (TC, Ent, 

EC) concentration for individual samples, 

but correlated when data considered by 

year

Authors considered their estimate of the 

frequency of exceedance conservative, 

since samples taken at night

Ent abundance significantly greater in low tide 

samples for the two sites with the most 

exceedances during the study

Schaub,

2004

NANA NA NA G, INA No NA Harmonization of risk approaches is 

encouraged to allow more effective 

utilization of risk study results

Schets et 

al., 2008

F, EIF, 

IN

Temp WC FC, Ent, 

FS, 

EC

F-specific 

bacterio-

phage, 

somatic 

coliphage

Campy, 

EC O157, 

Crypto, 

Giardia, 

Rota-

virus, EV, 

reovirus, 

noro-

virus, 

astro-

virus, 

HAV, 

HEV

A, GSamples 

collected 

during 1 

calendar year, 

frequency not 

specified

No Sample sites canals with 

known fecal impacts 

and inland lakes with 

recreational use

Levels of fecal indicators in the canal with 

houseboats and the canal without 

houseboats almost equal and did not 

suggest that houseboats contributed to the 

fecal contamination of canals to a larger 

extent than other sources did; Crypto and 

especially Giardia numbers much higher 

canal with houseboats than in the other 

canal, suggesting that wastewater from the 

houseboats may have been a source of 

those protozoan pathogens

Indicator counts more closely associated with 

rainfall in canals than in recreational lakes

Servais et 

al., 2007

F IF Temp WC FC, Ent, 

EC

A Between 1-6 

sampling 

campaigns 

conducted on 

a large river 

and numerous 

tributaries of 

varying order

Yes Drainage is ―highly 

anthropogenically 

impacted‖ from 

industrial, WWTP and 

intensive agriculture 

sources

No major difference in mortality associated 

with small vs. large rivers

Mortality of EC dominated by grazing when 

observed under laboratory conditions

In situ decay measurements indicated slightly 

higher decay rate than observed in 

laboratory experiments
August 2010

A-31

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Shehane et 

al., 2002*

UU Trop WC FC, EntCP, Somatic 

coliphage

A Seven sites 

sampled twice 

each per 

sampling event 

during a 2-year 

study; sampling 

conducted 

during spring, 

summer,and 

winter

No Not fully described; known sources of fecal 

pollution in the 

drainage septic 

systems and leaking 

sewer systems

Abstract only

Impacts of poorly maintained septic systems 

and leaking sewer systems documented

During dry seasonal, the majority of indicators 

of animal origin

Shehane et 

al., 2003*

UU Trop WC FC, EntCP, 

Somatic 

coliphage

A Seven sites 

sampled twice

each per 

sampling event 

during a 2-year 

study; sampling 

conducted 

during spring, 

summer and 

winter

No Not fully described; known sources of fecal 

pollution in the 

drainage septic 

systems and leaking 

sewer systems

Abstract only Impacts of poorly maintained septic systems 

and leaking sewer systems documented

During dry seasonal, the majority of indicators 

of animal origin

Shellenbar

ger et al.,

2008

TI TI, 

IN

Sub WC FC, Ent, 

TC

Salm A, G8 sampling 

events 

conducted: 4 

events weekly 

during the 

summer and 4 

events weekly 

during the 

winter

No Drainage is in an 

National Wildlife 

Refuge with suspected 

impacts from waterfowl 

and storm water 

conveyances

Tidally-influenced ponds can act as either 

sources or sinks of indictor organisms, 

depending on loading rate from all sources 

and hydraulics/hydrology

Lower occurrence of indicators occurred 

during the period of lower bird density; during this period the ponds studied not 

hydrologically connected to sloughs where 

high indicator organism concentrations 

observed

Sherer et 

al., 1992

F IF Temp WC, 

sed

FC, 

FS

A Sediment and 

water samples 

taken from two 

sites and 

experiments 

conducted in 

the laboratory

Yes Land use adjacent to 

streams studied is 

primarily rangeland and 

is expected impacted 

by animal fecal 

pollution

FC and FS decay much slower in the 

presence of sediments than in water alone

Decay of both FC and FS in water with 

sediment is characterized by a pronounced 

shoulder followed by apparent first-order 

decay; the shoulder may correspond to the 

time period during which nutrient supplies 

have not been exhausted

FC die-off in a sandy loam significantly less 

than in a clay loam (fine sed); FS die in the 

two sediments not significantly different
August 2010

A-32

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

The authors believed first-order decay 

kinetics are sufficient to describe the decay 

of FC and FS incubated in the presence of 

sediment

Signoretto 

et al., 2004

F, MC, 

IN

Sub WC Ent A, EMonthly samples 

taken over 1 

year from a 

marine site 

and a large 

lake

No Drainage for the lake 

studied has a relatively 

low year-round 

residential population 

and as many as 25× 

the resident population 

during summer months

Viable but nonculturable (VBNC) bacteria are 

present in many samples with no culturable 

bacteria

Plankton is much more plentiful in both 

marine and fresh waters during summer 

months

When plankton are plentiful, the majority of Ent present in samples is associated with 

plankton; when plankton are not plentiful, 

the majority of Ent are free swimming

Association of Ent with plankton appears 

enhance survival of Ent

Smith et 

al., 2008

F IF Temp WC, 

Sed

TCA 106 observations (2 streams) 

taken weekly 

over a single

year

No Streams described as 

polluted and are in the 

vicinity of Charlotte, NC

Raw data given for coliforms in water column, 

in sediments, river stage, temperature, and 

rainfall

Results demonstrate the contribution of 

sediment bacteria to water column 

community

Results show that pre-storm sediment 

bacteria concentration can be a predictor of 

post-storm water quality violations

Soller et 

al., 2006

E WC Sub WC EC, 

Ent, 

FC, 

TC

G, H26,625 samples 

analyzed for 

TC, EC, Ent,

and FC at 35 

sites; details of 

sampling 

design not 

provided

N Study conducted 

downstream of large 

urbanized area in 

waters known to be 

impacted by human 

fecal pollution

Though dry season FC frequently exceed 

water quality objectives, exceedances 

sporadic and geographically-limited

Recreational use intensity varied between 

sites and not present or prohibited at some 

sites exceeding WQ standards frequently

Exceedances of WQ standards occurred at 

sites with recreational use during times of 

the year when recreational activity was 

relatively low

Limiting controllable pollution is not predicted 

to have a significant impact on overall water 

quality or risk of illness due to recreational 

activity

Soonthorn-

nonda et 

al., 2008

F IF Temp WC FC, 

EC

A, GSampling of 

storm water 

discharges 

N All drainages primarily 

residential; one 

drainage included a 

Authors claimed that the proposed EC 

washoff model fit data well; the fit appears 

excellent for most storms but very poor for 
August 2010

A-33

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

conducted for 

3 storms at 4 

drains and at 

30-minute 

intervals for up 

to 7 samples

major highway one storm in two drainages

Washoff model validity is suggested for 

portions of rainfall/washoff events near the 

hydrograph peak.

A transport coefficient of 6.12 cm

-1

is 

suggested for wash-off of EC from mixed 

residential land use drainages

Sorensen 

et al., 1989

F IF Temp WC FC, 

TC

CP,

FSi A Sampling mostly conducted on 

a single 

occasion on 

each of two 

streams at 

numerous 

locations

N Upland streams, not 

expected to be 

impacted by human 

sewage but with 

livestock/non-point 

sources

CP concentrations lower than those of fecal 

indicators, but a better indicator of fecal 

pollution, since non-point livestock 

associated indicators suspected to be 

entering the stream; indicators increased 

with distance downstream from WWTP 

discharge whereas CP decreased

Oxbow lakes (presumed to be concentrators 

of fecal pollution) did not have elevated 

concentrations of CP

Stewart et 

al., 2000*

UU Temp WC EC FRNA 

coliphage

D UnknownN Not provided Abstract only

Multiple antibiotic resistance able to 

distinguish human-derived EC

Tiefentha-

ler et al., 

2008

F IF Sub WC EC, 

Ent, 

TC

Bateriode

s 

thetaiota-

omicron

A 15 sites sampled 

weekly during 

dry season (no 

rain for 24 hr, 

flow < 20% 

above 

baseflow) over 

a 1-year period

N All drainages selected 

based on status as 

unimpaired and low 

level of developments 

and impacts

Concentrations of all three indicators under 

baseflow conditions higher during summer 

months

Correlation of TC with temp is stronger than 

those of EC and Ent

Based on absence of alternative human fecal 

indicator, sources of EC, Ent, and TC 

believed to be non-human

Low stream flow may contribute to high 

indicator levels (no dilution?)

Touron et 

al., 2007

E TI Temp WC FC, 

Ent, 

EC

CP Crypto,

Giardia, 

Salm

A 45 samples 

collected at 

each of 8 

sample sites in 

an estuary 

over a 9-year 

period; between 4

-7 

samples 

collected from 6 locations on 

tributaries

No Upper reaches of the 

study waters in a large urbanized area; the 

study water (estuarine 

portions of the Seine) 

end at the Bay of 

Seine; intensive 

farming with livestock 

prevalent in middle 

reaches

Upstream activities impair estuary water 

quality and pose recreational use risk

Relationship between indicator concentration 

and Salm concentration varied from site-to-

site; in an urbanized area there was no 

relationship

At the mouth of the estuary, Salm correlated 

with Ent
August 2010

A-34

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Traister 

and 

Anisfeld,

2006

F IF Temp WC ECA Sampling 

conducted at 

seasonal, 

storm-related.

and diurnal 

time scales; sampling 

conducted 

between 

March and 

November at 

11 sites in the 

drainage area

No Drainage for sample 

locations mainly 

forested; ag land use 

accounted for about 

10% of drainage for all 

study sites

EC positively correlated with drainage 

residential land cover and negatively 

correlated with forest cover

Greater diurnal fluctuations observed at less 

shaded, slower flowing sites

Storm events have a strong effect on EC 

concentration though storm influences vary 

between storms

The relation between EC concentration and 

temperature differed according to the time 

scale of sampling: EC correlated with temp 

for seasonal time scale data but inversely 

correlated with temp for storm-scale 

samples

Tranter et 

al., 1996

F IF Temp WC FCA Weekly sampling

for a 1-year

period

No Upland catchment, 

agricultural land use

FC concentrations highly variable at all sites; 

summer concentrations general higher, 

possibly due to slurry application

Ag activities degraded water quality, though 

the degree of development of the drainage 

seemed to play a role in the degree to 

which ag impacts observed in the streams

Vidon et 

al., 2008

F IF Temp WC ECA Samples 

collected for 2

years either 

bimonthly, 

monthly, or 

every2 weeks

No Watershed for two study 

streams mixed 

agricultural (60%), low 

density residential 

(10%) and forested, 

herbaceous, roads and 

open water

For all flow conditions, EC concentration 

correlated best with 7-day antecedent 

discharge (better than precipitation or 

same-day discharge)

For base flow conditions, EC concentration is 

not correlated to 7-day discharge but is 

correlated with turbidity and current day 

discharge

Vital et al.,

2008

F IF, 

IN

Temp WCEC

O157:H7

B Growth observed 

at 

approximately 

5 minute 

intervals for 70 

hours

Yes Not providedEC O157:H7 shown to grow in sterilized 

freshwater under low carbon conditions, 

with the yield associated with available 

carbon

Growth rate positively correlated with 

temperature (max specific growth rate 

around 30° C)

Voytek et 

al., 2005

F IF Temp WC FC, 

EC, 

Ent

HPF Yukon River 

(Alaska), 2

Illinois Rivers,

and 1 East-

coast river 

sampled for 

one year 

No Yukon River drainage is 

largely undeveloped 

but has many fecal 

inputs from poorly 

maintain septic 

systems; Illinois 

drainages primarily 

HP and Helicobacter spp. often found 

concurrently with indicator bacteria, but the 

presence of indicator bacteria not predictive 

of the presence of HP

Indicator organism concentrations lowest in 

the undeveloped watershed
August 2010

A-35

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

(sample 

frequency not 

specified)

agricultural; while East 

coast drainage in a 

heavily developed area

Wade et 

al., 2008

FC Temp WC Ent Samples 

collected at 8

AM, 11 AM 

and 3 PM; a total of 1,359 

samples 

collected

No All sample sites were 

Great Lakes beaches 

near large metropolitan 

areas

Ent as determined by QPCR correlated better 

with rec-related exposure and illness than 

Ent as determined by culture techniques

Relatively low fluctuation observed in Ent 

concentration during the day when 

determined by QPCR

Waldron et 

al., 2002

F IF Temp WC FCO Sampling 

strategy not 

specified in 

detail

No Drainages for all sample 

sites described as 

heavily developed

To allow comparison between drainages, FC

loads were expressed as yield (load per 

drainage area) 

The highest FC loads associated with an 

industrial drainage near a highway; the 

lowest yield was associated with a low-

density residential area

Reservoirs attenuate peaks in FC loads

Walters et 

al., 2007

F IF Temp WC BacteroidalesEC 

O157:H7 

Salm, 

Campy

F Weekly 

sampling: May 

23-July 17;

Fortnightly sampling

:

May-October, 

2003 and 2004

No Expected to be highly-

impacted by 

agricultural fecal 

pollution

Ruminant specific Bacteroidales predicted EC

O157:H7 occurrence

Detection of ruminant-specific Bacteroiodales 

increased odds of detecting Salm

Detection of human-specific Bacteroidales 

increased odds of detecting Campylobacter

spp.

Whitman et 

al., 2008

F IN Temp WC EC Somatic 

and 

FRNA 

coliphage

A Pre-pond 

construction:

samples 

collected twice 

monthly for 8 

months; during 

pond 

construction,

samples 

collected at 

unknown 

frequency

Post-pond 

construction:

samples 

collected 3

times per week 

for 1 month 

Yes 

(qu

alita

tive)

The study water drains 

an isolated area in a 

park and is relatively

unimpacted by human 

and agricultural fecal 

contamination; population diversity of EC indicated human 

septic sources upslope 

in catchment

Solar radiation reduction in EC estimated at 

26% (74% attributable to non-solar factors)

EC removal became more predictable with 

pond age

Pond was less effective at reducing EC during 

the winter months than during summer

months

FRNA coliphage rarely occurred under base 

flow conditions but was frequently seen in 

flooding and snowmelt, though EC was 

plentiful in base flow conditions
August 2010

A-36

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

and before and 

after 1 rainfall 

event and 

before and 

after 1

snowmelt 

event

Wiede-

mann et 

al., 2006

F IN, 

IF

Temp WC EC, EntCP, 

somatic 

coliphage

Aerom-

onads, 

Pseudo-

monas 

aerug-

inosa

H Samples taken at 

20-minute 

intervals 

during bathing 

episodes

No Four lake sites and one 

river site studied; 

suspected sources of 

fecal contamination 

were sewage (treated 

and untreated), 

agricultural runoff and 

waterfowl.

Authors stated that the use of NOAELs for 

determining acceptable indicator 

concentration is more robust than use of 

attributable risk

Wijesing-

he et al.,

2005

F IF Temp WC ECD Fecal samples 

from 8 hosts in 

the watershed

No Watershed impacted by 

urban and agricultural 

sources

Apparent variability in EC diversity among 

host species

Wilson et 

al., 2005

F IF Temp WC FCA Sampling at 5 

minute 

intervals for 1 

hour under low 

flow conditions 

in the stream; weekly 

sampling 

conducted 

July-February

No One site in unimpacted 

headwaters (high order 

stream?); other sites 

are near urban areas

and presumed 

impacted

Low variability observed between samples 

collected at 5-minute intervals

High variability observed month to month for 

low flow (baseflow) conditions

Suspected sources for FC during baseflow 

conditions were leaky sewers/septic 

systems, wildlife, and FC in sediments

Although overall levels of FC at the 

unimpacted site were less than at impacted 

sites, the range in the observed FC was the 

same as for impacted sites

Wymer et 

al., 2005

M, 

F, E

C Temp, 

sub

WC Ent, 

EC

A Sampling at 1 

hour, daily,

and longer 

intervals

No All study beaches located 

near large metropolitan 

regions

Ent and EC concentrations poor predictors of 

concentrations on the next day for all 

settings

High spatial and temporal variability

Wymer et 

al., 2007

*

M, FCU WC Ent, 

EC

A Sampling at 1 

minute, 10 

minutes, 

hourly, and 

daily intervals

No Not provided (abstract 

only)

Abstract only

Coefficient of variation ranged from 0.7 for 

samples taken seconds from each other to 

2.2 for samples taken daily

Authors state that single samples cannot 

adequately characterize water quality

Yamahara 

et al., 2007

MCSub Soil, 

Sed

Ent, 

EC

Bacte-

roides

SalmA Sands, 

sediments,

and waters 

No Impacted coastal 

beaches along the southern California 

Mass balance of Ent based on water and soil 

samples during tidal period indicates that 

Ent persistent or growth is greatest in soils 
August 2010 A-37

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

Indicators

Pathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

collected from 

55 beaches; 

sampling at 1 

beach at 20 

minute

intervals for 24 

hours duration

coast; suspected fecal 

contamination sources 

were storm drains and 

agriculture sources; 

soils (sands) were also 

determined to be nonpoint sources

and that Ent are readily transported into the 

water column

Ent are ubiquitous in sands of the beaches 

studied

High spatial variability in Ent concentration 

noted at all beaches

EC observed in sands much less often than 

Ent
August 2010 A-38

Appendix B

Literature Search Strategy and Results

The literature search strategy consisted of a number of combined approaches conducted in Fall 

2008. Search terms and a synopsis of information needed were given to a professional librarian 

to search the online DIALOG databases. To supplement the DIALOG searches, individual 

authors used free search engines on the internet (e.g., PubMed) to find articles pertaining to 

specific information needed. It is important to note that the titles of literature cited in specific 

reports, books, review articles, and conference proceedings were also evaluated for relevance 

and constituted an important component of the overall literature search.

Initial Literature Search Strategy Conducted by Professional Librarian

Selection of DIALOG data base files used for this search:

Biosis

NTIS

Enviroline

Embase

WasteInfo

Biological & Agricultural Index

Pascal

MedLine

Waternet

FEDRIP

Engineering Village and ISI Web of Science

Descriptions of these databases are available at http://library.dialog.com/bluesheets/.

Retrieve: Titles and year, 1985-present (2002-present is more crucial)

Additional information: Interested in international and domestic journals and government reports

Language: English only

Primary search terms in order of importance to be searched as noted below:

1. Fecal indicator*

2. Fecal contamination

3. Fecal pollution

Search strategies (SETS) used for this search:

SEARCH SET 1

Primary search term [bolded terms are of increased importance] AND

Applicability

Fate

Transport (fate and transport)

TMDL (total maximum daily load)
August 2010 A-39

Fecal source tracking

MST (microbial source tracking)

(Microbial) water quality

Behavior (fate and behavior)

Microbial ecology

Primary contact

Secondary contact

Persistence (microbial ecology and persistence)

o (Fecal) pathogen

Performance

o Compliance

o Monitoring (compliance monitoring)

Source

o Indigenous

o Environmental*

o Non-fecal (nonfecal, non fecal)

o Extra(-)enteric

o Nonhuman (non human, non-human)

o Zoon* (zoonotic, zoonoses)

Inland (water*)

o Flowing

o Lake

o Pond

o Stream

o Reservoir

o Creek

o River

o Lentic

o Lotic

o Tributary

Water column

Recreational water

Ambient water

Fresh water* (freshwater)

Coastal

Marine water*

Beach

SEARCH SET 2

Primary search term* AND

Decay (rate)

Inactivation

pH

Hydrology

Alkalinity 
August 2010 A-40

Temperature

Re(-)suspension

Re(-)growth

Light (duration, intensity)

Rainfall

Precipitation

Storm

Salinity

Runoff

Suspended solids

Turbidity

Nutrients

Organics

Organic foams

Biological community in water column

Water depth

Stratification

Depth

Mixing (wind, waves, etc.)

Regrowth

Presence of aquatic plants – epiphytic bacterial communities on plants

Biofilms

Predation

SEARCH SET 3

Primary search terms AND

Fecal pathogen*

(Environmental) fecal coliform*

(Environmental) Escherichia coli

(Environmental E. coli

(Environmental) enterococc* (enterococcus, enterococci)

Fecal streptococc*

Intestinal enterococc*

(Environmantal) fecal coliform*

Total coliform*

Alternate (alternative) fecal indicator*

Clostridium perfringens

sulfite-reducing Clostridia

Bifidobacterium

Rhodococcus coprophilus

Bacteroid*

Human enteric virus*

Somatic coliphage*

F-specific coliphage*
August 2010 A-41

Bacteroide* phage

Sanitary plastics grease

Fecal steroid* (sterols, stanols, stanones)

Caffeine

Detergent*

Partial list of authors of interest:

R. Fujioka 

M. Byappanahalli

S. Ishii

K. Isobe

J.B. Rose

H. Solo-Gabriele

G.A. Toranzos

J. Tiedje

T.C. Hazen

R.L. Calderon

M.J. Sadowsky

F. Genthner

E. Akazawa

C. Gerba

M. Sobsey

T. Slifko

M. Yates

C. Moe

J.A. Jay

R.L. Whitman

Summary of Literature Search Results

This process resulted in a total order of 292 citations of which a total of 152 (52%) were obtained 

and reviewed for their suitability for use in the original draft report. There are many more papers 

in the peer-reviewed literature and this by no means represents all of them. Of the articles 

reviewed, 211 citations were included in the draft report.

Supplemental Literature Search Activities

In addition to the literature search conducted by the professional librarian, specific reports were 

obtained and the titles of the references cited in the reports were reviewed for relevance.

NRC. 2004. Indicators for Waterborne Pathogens. National Academies Press. 

Washington, DC. 

USEPA, 2007b. Report of the Experts Scientific Workshop on Critical Research Needs 

for the Development of New or Revised Recreational Water Quality Criteria. EPA 823-

R-07-006. 
August 2010 A-42

References cited by the Natural Resources Defense Council reviewers of the EPA Critical 

Path Science Plan. 

Lastly, Clancy Environmental Consultants, Inc., Soller Environmental, LLC, and EPA’s Health 

and Ecological Criteria Division all maintain extensive literature bibliographies and reference 

lists from previously completed projects. All of those in-house resources were also sources of 

literature used in this report.