Appendix B.6: Report on the Expert Scientific Workshop on Critical 

Research and Science Needs for the Development of Recreational Water 

Quality Criteria for Inland Waters, WERF, PATH4W09.
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
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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.............................................................................................. 5

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

1.4. Approach..................................................................................................................................... 6

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................................................................. 31

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

5. SURVIVAL OF FECAL INDICATOR BACTERIA IN INLAND AND COASTAL SETTINGS...................... 33

5.1. General Description of Indicator Decay in Natural Waters...................................................... 33

5.2. Phenomena Contributing to Indicator Removal........................................................................ 35

5.3. Growth Observations................................................................................................................ 36

5.4. Comparison of Measured Decay Rates..................................................................................... 39

5.5. Summary................................................................................................................................... 43

6. INDICATOR-PATHOGEN ASSOCIATION IN INLAND AND COASTAL SETTINGS ............................... 44

6.1. Cryptosporidium and Fecal Indicators...................................................................................... 44

6.2. Viruses and Fecal Indicators..................................................................................................... 46

6.2.1. Co-occurrence and Correlation of Enteric Viruses and Fecal Indicators ...................... 46

6.2.2. Inactivation Rates of Enteric Viruses in Different Settings........................................... 50

6.3. Bacterial Pathogens and Indicators........................................................................................... 53

6.1. Summary................................................................................................................................... 54

7. REFERENCES...................................................................................................................................... 56

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

APPENDIX B LITERATURE SEARCH STRATEGY AND RESULTS.......................................................... B-36
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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 ...... 37

Table 7. Decay Rates for E. coli Reported in Studies Conducted with in situ Mesocosms ........ 40

Table 8. Decay Rates for Enterococci from Laboratory Mesocosm Studies............................... 42

Table 9. Summary of Enteric Virus Inactivation Rate Data ........................................................ 52

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. .......................................................................................................................................... 33

Figure 11. Survival Curves for E. coli in Seawater ..................................................................... 34

Figure 12. Survival Curves for E. coli in Freshwater, Stream Settings....................................... 34

Figure 13. Decay Rates of E. coli from in situ Mesocosm Studies. ............................................ 39

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

Area whose Land Use is Primarily Agriculture............................................................................ 49

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)................................ 51

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

Chambers in Fresh Water.............................................................................................................. 52

Figure 17. Decay Rates for Salmonella for Various Settings and Temperatures. ....................... 55
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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 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.

 

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.
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August 2010 2

In contrast, significant differences 

exist in FIB loading between POTWimpacted coastal waters and nonPOTW-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 particle-associated 

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. 

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. 

Exhibit 2. Illustration of Fecal Pollution Sources on 

Inland and Coastal Settings
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August 2010 3

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. POTWimpacted 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.
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1. Introduction

1.1. 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. 

1.2. 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. ―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. 

 

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

―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. 

1.3. 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 meta-analyses/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 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.

1.3.1. Prospective Cohort Studies

 

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.
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August 2010 6

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 POTW-impacted 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). 

1.3.2. 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 recreational waters in 

Europe in 2006 and 2007. Finally, the results of an RCT study of a non-POTW-impacted marine beach in 

Miami, Florida have been recently published (Abdelzaher et al., 2010; Fleisher et al., 2010; Sinigalliano 

et al. 2010). 

1.4. 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. 

 

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 7

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 (event-scale 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.
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August 2010 8

2. 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.

2.1. 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 non-human 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 

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 
U.S. Environmental Protection Agency

August 2010 9

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.

2.2. Pathogen and FIB Loading

Both 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 

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 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. 
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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. 

2.3. 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 FIBbased 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. 

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 
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August 2010 12

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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3. 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 nonepidemiological 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). 

3.1. 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 white-water 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, fresh-water 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 illnessindicator 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 POTWimpacted 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-POTW-impacted 

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 non-swimmers.

3.2. 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;

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.
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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 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 
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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 coldclimate, 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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3.3. Summary 

This review supports the extension of criteria developed in epidemiology studies of POTW-impacted 

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 nonhuman. 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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4. 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). 

4.1. 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 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. 
U.S. Environmental Protection Agency

August 2010 30

4.2. 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.‖ 

4.2.1. 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-to-storm (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 woodland-dominated 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.

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 
U.S. Environmental Protection Agency

August 2010 31

≥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. 

4.2.2. 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 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.

4.2.3. 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. 
U.S. Environmental Protection Agency

August 2010 32

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, nearshore sands, and due to increased wave action and mobilization of indicators from sediments. Although 

dilution would presumably cause event-scale 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.

4.3. 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 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. 
U.S. Environmental Protection Agency

August 2010 33

5. 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. 

5.1. 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 firstorder 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 34

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).

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 
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August 2010 35

on observations in sediments with and without predators). Despite frequent non-first-order behavior, 

experimental studies of indicator survival typically report decay rates as first-order decay constants.8 

5.2. 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 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.

 

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 36

5.3. 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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5.4. 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 40

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‰

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
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Study Setting Indicator

Temperature 

or Month

Average or 

Median Decay 

Rate (d-1)

Decay Rate 

Range (d-1) Notes

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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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, ksis decay rate constant (units of m2/MJ), nsis a constant (unitless), and S is net radiation dose (MJ/m2)
U.S. Environmental Protection Agency

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5.5. 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 nonflowing 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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6. 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 short-lived 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.

6.1. 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 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).
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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 nonflowing 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 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 nonflowing, 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. 
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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.

6.2. 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.

6.2.1. 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.

6.2.1.1. 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 log-normal distributions. Although the distributions of the residuals 

associated with the fitted data were not assessed, a visual inspection of the fits indicates that the lognormal 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 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 co-occurrence 

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. 
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coli, fecal coliforms, enterococci, and coliphages) and viral pathogens (adenovirus, astrovirus, rotavirus, 

enterovirus) for freshwater or marine sites. 

6.2.1.2. 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. 

6.2.1.3. 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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6.2.1.4. 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 cooccurrence of fecal indicator organisms with other enteric viruses, some bacterial pathogens, and some 

pathogenic protozoa.

6.2.2. 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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6.3. 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 nonflowing, 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 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 non-flowing inland sources 
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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 non-pathogenic 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 nonflowing 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.

6.1. 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 non-flowing). 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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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 non-flowing 

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 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 

IndicatorsPathogens

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

Baums et 

al., 2007

F, 

M

C Trop WC, 

Sed

EC, 

Ent

BacterioidesShig B,

E,

No Samples collected from 

urbanized, tidally 

Technological approach evaluated has the 

potential to simultaneously detect multiple 
August 2010

A-2

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

F influenced river sites and 

a beach located 

downstream from flood 

control gates near Miami, 

FL

targets for coastal water

Bell et al., 

2007

F IF Temp WC Bacter-

ioides

B 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 WC FC, 

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 WC ECG 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 Bacter-

oides

Prevotella

E, A

Six 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 

contributing source was only one of the two 

tributary streams

Bordalo, 

2003

MC Temp WC TC,

FC

A Survey lasted 18 

consecutive 

No Two urban beaches in 

Portugal

Periodicity of fecal indicators in raw sewage, 

tidal status, and wind conditions influenced 
August 2010

A-3

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

summer days, 3 

times a day, a 

total of 184 

samples 

collected

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, 

Sed

Not 

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., 2005F IF, 

IN

Temp WC EC, 

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, 

Sed

FC,

Ent,

EC

A, D

Two 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

F O,F Sub WC, 

Sed

TC,

(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 WC EC,

Ent,

FC

A USGS survey 

from July 2001-

August 2005 

during dry and 

wet-weather 

periods; samples 

collected from 5 

sites on the 

No The Allegheny, 

Monongahela, and Ohio 

River Basins within 

Allegheny County and 

City of Pittsburgh, PA

Samples collected in the 3 rivers and tributaries 

frequently exceed established recreational 

standards and criteria for bacteria

FIB from tributaries most strongly correlated 

with streamflow, specific conductance, and 

turbidity
August 2010

A-4

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Three Rivers 

and from 8 sites 

on 4 tributaries

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, CTemp Sed, 

Soil

ECA 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, CTemp Sed,

soil 

ECA Monthly 

sampling between May

-

August 2003; 5 

samples were 

collected from 5 

different rocks 

in each of the 2 

beach sites

No Shoreline waters of lake 

Michigan (Ogden Dunes 

Beach, IN); Combination 

of urban and rural wastes, 

including sewage 

overflows, septic field 

leachate, and runoff from 

nearby urban areas and 

agricultural farms

EC associated with Cladophora (blue-green 

algae) may be a recurring source of indicator 

bacteria to the nearshore beach

Cabelli, 

1983

M, FC, 

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 

No Sampling 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
August 2010

A-5

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

the water; 

collected 2-3 

locations along 

each beach

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, 

Soil

TC, 

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)

G

1-year sampling 

at intake (lock) 

of a privately 

owned potable 

water supply on 

the Kentucky 

River; 

Water quality 

data augmented 

with flow and 

rainfall USGS 

data from 

several upstream 

sites at locks 

and gauging 

stations 

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

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 

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
August 2010

A-6

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

(Adv serotype 

40); inactivation 

results with 

sodium 

hypochlorite 

were compared 

at 0, 1, 2, 3, 24, 

and 48 hours

FC and Ent not resistant to chlorine with a 5-log 

reduction by the first hour

Chu et al., 

2007*

F, 

E, M

C 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, 

Sed

EC,

Ent,

FC,

FS 

(Ent)

A USGS sampling 

from September 

2002-August 

2003; a total of 

64 baseflow and 

15 stormflow 

sampling sites

No West Branch Brandywine 

Creek, Coatesville, PA; 

urban/ industrial land use 

serving as water supply, 

irrigation, and recreation 

uses

USGS assessment of effects of sediment particle 

size, climatic conditions, aquatic growth, environmental chemistry, 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 
August 2010

A-7

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

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, 

Noro-virus 

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 of bacteria in 

surface runoff

Cole et al., 

2000*

FU TempU FC, 

EC, 

Ent

CP,

somatic 

coliphage

male-

specific 

coliphage

A, F

Measured 

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
August 2010

A-8

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Colford et 

al., 2007

MC Sub WC Ent, 

FC, 

TC

Bacter-

oides, 

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, 

Sed

EC

Ent

Coliphage Salm

Typh-

imurium,

Salm 

derby

B, F

Microcosms 

maintained 

at10° C, 20° C, 

and 30°C and 

inoculated with 

prepared strains 

of indicators and 

pathogens; 

micro-organisms 

enumerated and 

decay rates 

determined for 

Days 0,1, 2, 7, 

14 and 28

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 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)

A 8 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
August 2010

A-9

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

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 TC

EC

A Baseflow 

sampling done 

monthly; 30 

individual storm 

events sampled 

during a 1-year 

period, during 

storm events, 

samples taken 

every 2 hours 

during 2 days

No Toenepi 

Stream/Catchment, 

Waikato Region, New 

Zealand: one of the most 

intensively dairy-farmed 

areas in the country, 

which is mostly flat with 

artificial drainage with 

100% pasture

EC peaks well ahead of flow during storms and 

concentrations increased with storm event size

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 WC EC

Ent

PA, 

Staphyl-

B, F

Microcosm 

experiments 

Yes NA, source of water used 

in experiments not 

Ent showed to be the most resistant organism 

and the most sensitive to solar irradiation
August 2010

A-10

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

ococcus 

aureus

conducted 

summers 2001-

2003

specified (studies 

conducted in Austria)

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, 

HAV

E Three water 

samples 

collected at each 

site between 

December-May 

1998 for range 

of streamflows; 

at least 1 sample 

from each site 

collected during 

or after a storm 

event

No Inland and coastal basin 

in OH, WA, IA, SC, WV 

Cuyahoga River Basin 

(OH) – urban and 

agricultural

Thornton Creek (WA) –

urban

Iowa River (IA) –

agricultural row crop and 

confined animal

Cow Castle Creek (SC) –

agricultural

Clear Fork (WA) –

mining/rural residential 

with septic systems

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

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, 

Sed

EC 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 

No Rural (hill

-country) 

streams in the 

Whatawhata district, 

Waikato, New Zealand

that were impacted by 

pastoral farming with 

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
August 2010

A-11

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

collected from 

each of 15 sites

grazing animals, 

indigenous forest, or pine 

forests 

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 WC EC,

FC,

Ent

H Epi

-micro study 

of recreational 

water exposure 

and health 

conducted 1979-

1982

No Keystone Lake, about 15 

miles from Tulsa, OK. 

Sampling sites located 

near sewage discharge 

and outfall; Lake Erie, 

PA with 2 sites, 1 near a 

sewage outfall

A good correlation was observed between 

swimming-associated GI symptoms and either 

EC or Ent densities in the water

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, F

FIB 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, 

Sed

TC, 

FC, FS 

(Ent)

Somatic 

phage

PA,

Salm 

A, F

Weekly and 

storm event 

sampling from 

October 1990-

February 1991

No 4 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
August 2010

A-12

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Elmir et al., 

2007

MC Sub WC, 

Soil 

Ent Staphyl-

ococcus 

aureus

A, C

Two sampling 

types, large and 

small pool: 1) 

large pool study: 

microbial 

shedding from 

bathers as 

group; 2) small 

pool study: 

microbial 

release from 

individuals + 

beach sand 

adhered to skin

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 

between bathing episodes

Evanson and 

Ambrose, 

2006

M, EC Sub WC, 

Sed

TC,

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 
August 2010

A-13

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

and finer grain size)

Ferguson et 

al., 1996

EC Temp WC, 

Sed

FC, FS 

(Ent)

CP, F-RNA 

phage

Aero-

monas spp,

EV

Crypto, 

Giardia, 

Salm

A, F

Water and 

sediment 

samples 

collected 10 

times between 

September 

1992-June 1993 

from 6 sites 

within the 

estuary

No Urban 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 and as popular 

venue; river receives 

inputs of urban runoff 

and during wet weather 

receive sewage 

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 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, F

51 samples total, 

28 from 11 

springs, and 23 

samples from 

five different 

locations of the 

Vilanos River

No Montefrío 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 

No

3-4 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 
August 2010

A-14

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

collected from 6 

NAWQA study 

units throughout 

the U.S. (e.g., 

Kanawa-New

River Basin in 

VA, WA, and 

NC)

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

Garcia-

Armisen and 

Servais, 

2007

F IF Temp WC EC, 

Ent

A 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 WC EC Bacteroide s (total) 

and 

bovine-

specific

A, F

From 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 WC EC,

Ent

EV,

HAV

A, F

From 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, 

Sed

FC,

EC 

ColiphageA Sampling at 5 

sites in 

Newfound 

Creek and 5 

No Newfound Creek 

Watershed, Western NC

USGS report

90% of the EC and FC samples exceeded 

corresponding EPA (1986) rec/ambient water 

quality criteria
August 2010

A-15

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

tributary sites 

during low flow 

conditions on May 28, 2003, 

and high flow 

on November 

19,2003

An additional 5 

sites sampled for 

FC and EC in 

streambed 

sediments (low 

flow) and 

coliphage

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

Sediments do not appear to be a substantial 

source of bacteria relative to WC concentrations

Gronewald 

et al., 2008

E IF Temp WC FCG Not specified No Used 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 

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
August 2010

A-16

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

quarterly basis

Hartel et al., 

2007

F, 

E, M

C, 

IF

Trop, 

Temp

WC EC,

Ent

D 20

-30 samples 

from Mayaguez 

Bay (Yaguez 

River) on 

February 2, 

2005; 

3 separate 

sampling 

periods in St. 

Simons, 

including a 

beach, storm 

drain, and inland 

creek

No Mayaguez Bay, western 

Puerto Rico is dominated 

by Mayaguez, a modestly 

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

Targeted FIB sampling and fluorometry (MST) 

identified two hot spots of human fecal 

contamination in the Yaguez River and on St. 

Simons Island

Haugland et 

al., 2005

FC Temp WC Ent A 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 

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 

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 
August 2010

A-17

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

taken from eight 

locations along 

the shoreline at 

each beach 

million visitors yearly lapse after a rain event, or channel flow rate all 

were factors that significant impacted FIB 

distribution in the shoreline water quality

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, F

Year-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, H

Sampling 

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, 

Temp WC EC, 

Ent

B, H

4 different 

locations of 

Yes Waters drawn from a 

small stagnant lake, a 

EC similar or more persistent than Ent in fresh 

water
August 2010 A-18

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

C water sampled

Experiments 

conducted in 

laboratory 

mesocosms

ditch, and a large river In salt water, Ent more persistent than EC

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/S

ub

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-19

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

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, I

NA 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

Jamieson et 

al., 2004b

F IF Temp WC ECC After initiation 

of in situ 

Yes Streams are described as 

―rural streams.‖ No 

Inactivation estimated for EC in bed sediment 

was an order of magnitude less than that 
August 2010

A-20

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

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

description is provided on 

land use in drainages.

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 presumed 

impacted by fecal 

pollution.

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

Because virus detection done by PCR, 

nonviable and damages viruses may have been 

included in estimates of virus 

concentration/presence
August 2010

A-21

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Jiang et al., 

2007

M, EC Sub WC TC, 

FC, 

Ent

F+ 

coliphage 

Adv,

EV

A, F

For 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 

Faulkner, 

2008

F IN Temp WC EC, 

TC

Turbidity Crypto, 

Giardia

A 193 samples 

taken at 17 

locations on an 

inland reservoir. 

Samples 

collected at 

No Drainages to sample sites 

varied. Most drainages 

impacted by agricultural 

runoff. Some sites located 

in a wildlife refuge. 

Several sites impacted by 

Occurrence of Crypto and Giardia 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
August 2010

A-22

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

frequency 

between 

monthly and 3 

months over a 

27-month study 

duration.

WWTP discharge or 

septic systems.

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, G

Hourly 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 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, 

A Surface water 

samples 

No Study conducted for 

shellfish harvesting 

Levels of CP in sediment up to 5 orders of 

magnitude greater than those observed in the 
August 2010

A-23

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

enteric 

viruses

collected at 12 

sites, monthly 

samples, study 

duration of 1 

year; sediment 

samples 

collected 

quarterly

waters whose drainage 

includes impacts from 

residential land use and in 

some cases high density 

of on-site disposal 

(septic) systems

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 FCA Water 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 

Szewzyk, 

2000

F IF Temp WC EC RotavirusG No sampling 

performed

No Study conceptual Fecal indicator (EC) concentrations assumed to 

be log-normally distributed

The ratio of fecal indicators and rotavirus 

concentration assumed to be constant over all 

samples

Mathes et 

al., 2007

F IF Temp WC EC Bacter-

oides, 

Ent 

marker, 

human 

urine 

D Water samples 

collected twice 

at each of 4 

sites. Samples 

collected in

October and 

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
August 2010

A-24

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

marker September

McCam-

bridge and 

McMeekin, 

1981

EC? WC EC SP, 

Entero-

bacter 

aero-genes

Salm, 

Klebsiella 

pneumo-

niae

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, MIF, CTemp WC EC SP Salm 

typhim-

rium

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

EntD 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, 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; the ambiguous effect of temperature and 

differences between results of this 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 
August 2010

A-25

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

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 

seawater

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 appeared to 

have a small shoulder and very long tail

Olyphant et 

al., 2003

F IF Temp WC EC A, G

Samples 

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 
August 2010

A-26

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

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, G

Samples 

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

Ent CP,host 16A 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 

(low-flow) 

months for 2 

years; sample 

collection 

frequency not 

provided

No Sample sites widely 

dispersed

Study intent was relating indicator occurrence to 

human ecosystem impacts

Levels of FC, EC, and TC found to 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, 

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
August 2010

A-27

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

monthly 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-

philus

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 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 WC EC FRNA-

specific 

bacter-

iophages

Astrovirus A, G

Monthly 

samples 

collected during 3-year study; 

sample times 

selected to include different 

hydrodynamic 

and weather 

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
August 2010

A-28

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

conditions

Roser and 

Ashbolt, 

2004

F IF Sub WC EC, 

Ent

CP

24-

ethylcopro

stanol, 

others not 

specified

Crypto, 

Campy, 

others not 

specified

A, G

Intensive 

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 Ent densities, 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

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

Bacter-

oides

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, N NA NA NA G, NA No NA Harmonization of risk approaches is encouraged 
August 2010

A-29

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

2004AI 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, G

Samples 

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

Shehane et 

al., 2002*

UU Trop WC FC, 

Ent

CP,

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, 

Ent

CP, 

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
August 2010

A-30

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Shellenbarg

er et al., 

2008

TI TI, 

IN

Sub WC FC, 

Ent, 

TC

Salm A, G

8 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, FSA 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

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, E

Monthly 

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
August 2010

A-31

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

Soller et al., 

2006

E WC Sub WC EC, 

Ent, 

FC, 

TC

G, H

26,625 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, G

Sampling of 

storm water 

discharges 

conducted for 3 

storms at 4 

drains and at 30-

minute intervals 

for up to 7 

samples

N All drainages primarily 

residential; one drainage 

included a major highway

Authors claimed that the proposed EC washoff 

model fit data well; the fit appears excellent for 

most storms but very poor for 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

Bateriodes 

thetaiota-

omicron

A 15 sites sampled 

weekly during 

dry season (no 

rain for 24 hr, 

flow < 20% 

above baseflow) 

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 
August 2010

A-32

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

over a 1-year 

period

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

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 

every 2 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., F IF, Temp WC EC B Growth Yes Not provided EC O157:H7 shown to grow in sterilized 
August 2010

A-33

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

2008 IN O157:H7 observed at 

approximately 5 

minute intervals 

for 70 hours

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 

(sample 

frequency not 

specified)

No Yukon River drainage is 

largely undeveloped but 

has many fecal inputs 

from poorly maintain 

septic systems; Illinois 

drainages primarily 

agricultural; while East 

coast drainage in a 

heavily developed area

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

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 Bacter-

oidales

EC 

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 

Yes 

(qua

litati

ve)

The study water drains an 

isolated area in a park and 

is relatively unimpacted 

by human and 

agricultural fecal 

contamination; 

population diversity of 

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 
August 2010

A-34

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

construction, 

samples 

collected at 

unknown 

frequency

Post-pond 

construction: 

samples 

collected 3 times 

per week for 1 

month and 

before and after 

1 rainfall event 

and before and 

after 1 snowmelt 

event

EC indicated human 

septic sources upslope in 

catchment

flow conditions but was frequently seen in 

flooding and snowmelt, though EC was plentiful 

in base flow conditions

Wiede-mann 

et al., 2006

F IN, 

IF

Temp WC EC, 

Ent

CP, 

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 

No Not provided (abstract 

only)

Abstract only

Coefficient of variation ranged from 0.7 for 
August 2010 A-35

Study

Water Type

Setting

Climate

Media

Indicator 

Organism(s)

Alternative 

IndicatorsPathogens

Study Type(s)

Frequency and 

Period of 

Observations

Decay Data?

Watershed Description Note(s)

minutes, hourly, 

and daily 

intervals

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

M C Sub Soil, 

Sed

Ent, 

EC

BacteroidesSalm A Sands, 

sediments, and 

waters collected 

from 55 

beaches; 

sampling at 1 

beach at 20 

minute intervals 

for 24 hours 

duration

No Impacted coastal beaches 

along the southern 

California coast; 

suspected fecal 

contamination sources 

were storm drains and 

agriculture sources; soils 

(sands) were also 

determined to be nonpoint sources

Mass balance of Ent based on water and soil 

samples during tidal period indicates that Ent 

persistent or growth is greatest in soils 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-36

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)

Fecal source tracking

MST (microbial source tracking)

(Microbial) water quality

Behavior (fate and behavior)
August 2010 A-37

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 

Temperature

Re(-)suspension

Re(-)growth

Light (duration, intensity)

Rainfall

Precipitation
August 2010 A-38

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*

Bacteroide* phage

Sanitary plastics grease

Fecal steroid* (sterols, stanols, stanones)

Caffeine

Detergent*
August 2010 A-39

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 peerreviewed 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. 

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.
Report on the Experts Scientific Workshop on

Critical Research and Science Needs

for the Development of Recreational

Water Quality Criteria for Inland Waters

Pathogens and Human Health
REPORT ON THE

EXPERT SCIENTIFIC WORKSHOP ON

CRITICAL RESEARCH AND SCIENCE NEEDS

FOR THE DEVELOPMENT OF RECREATIONAL 

WATER QUALITY CRITERIA FOR

INLAND WATERS

Dallas/Ft. Worth, Texas

February 18-20, 2009

PATH4W09
ii 

The Water Environment Research Foundation, a not-for-profit organization, funds and manages water quality 

research for its subscribers through a diverse public-private partnership between municipal utilities, corporations, 

academia, industry, and the federal government. WERF subscribers include municipal and regional water and 

wastewater utilities, industrial corporations, environmental engineering firms, and others that share a commitment to 

cost-effective water quality solutions. WERF is dedicated to advancing science and technology addressing water 

quality issues as they impact water resources, the atmosphere, the lands, and quality of life.

For more information, contact:

Water Environment Research Foundation

635 Slaters Lane, Suite 300

Alexandria, VA 22314-1177

Tel: (703) 684-2470

Fax: (703) 299-0742

www.werf.org

werf@werf.org

© Copyright 2009 by the Water Environment Research Foundation. All rights reserved. Permission to copy must be 

obtained from the Water Environment Research Foundation.

Library of Congress Catalog Card Number: 2009931452

Printed in the United States of America

 

Mention of trade names or commercial products does not constitute WERF endorsement or recommendation for use. 

Similarly, omission of products or trade names indicates nothing concerning WERF’s positions regarding product 

effectiveness or applicability.
WERF Inland Waters Workshop Report iii

This report was produced and published by the Water Environment Research Foundation to 

summarize the findings of 31 experts who devoted their time and energy to the Inland Water 

Workshop convened on February 18-20, 2009. 

WERF would like to thank the Environmental Protection Agency Office of Water for its

logistical, planning, and content support in organizing the workshop, especially Pat Harrigan and 

Shari Barash. Special thanks are owed to Clair Meehan, and her colleagues at Tetra Tech, Inc., 

for working with the meeting facility, preparing materials, and making everything look 

professional, and to the staff from Clancy Environmental and ICF International for their note 

taking and support skills. We are truly grateful to Jeff Soller for making sense of the initial drafts 

and putting together a well-organized and readable report. We extend our sincere appreciation to 

the topical group leaders for their patience, leadership, and hard work before, during, and 

following the workshop. And finally, we offer our immense gratitude to the workshop 

participants whose knowledge and teamwork led to a successful workshop and this report.

Report Preparation

Nick Ashbolt, U.S. EPA, Office of Research and Development

Samuel Dorevitch, University of Illinois Chicago, School of Public Health 

Christobel Ferguson, Ecowise Environmental, Australia 

Roger Fujioka, University of Hawaii, Water Resources Research Center

Rhonda Kranz, Water Environment Research Foundation 

Charles McGee, Orange County Sanitation District 

Jeffrey Soller, Soller Environmental 

Richard Whitman, USGS, Lake Michigan Ecological Research Station

Workshop Participants

Indicators and Pathogens Group: Biology, Ecology, and Methods 

Topical Group Lead: Roger Fujioka, University of Hawaii, Water Resources Research Center

Topical Group Lead: Richard Whitman, USGS, Lake Michigan Ecological Research Station 

Michael J. Casteel, San Francisco Public Utilities Commission

Kevin Oshima, U.S. EPA, Office of Research and Development 

John Ravenscroft, U.S. EPA, Office of Water

Jill Stewart, University of North Carolina Chapel Hill, School of Global Public Health

Gary Toranzos, University of Puerto Rico 

Health Risks Group: Epidemiology and Risk Assessment

Topical Group Lead: Samuel Dorevitch, University of Illinois Chicago, School of Public Health 

Alfred Dufour, U.S. EPA, Office of Research and Development 

Patrick Gurian, Drexel University, Department of Civil, Architectural, and Environmental 

Engineering 

David Kay, University of Wales, Centre for Research into Environment and Health 

ACKNOWLEDGMENTS
iv 

Mary E. Schoen, U.S. EPA, Office of Research and Development 

Jeffrey Soller, Soller Environmental 

Stefan Wuertz, University of California at Davis, Department of Civil & Environmental 

Engineering 

W ater M atr ix G r oup: H ydr ology, C hemistr y, G eology, and M odeling 

Topical Group Lead: Nick Ashbolt, U.S. EPA, Office of Research and Development 

Ali Boehm, Stanford University, Department of Civil & Environmental Engineering 

Donna Francy, USGS, Ohio Water Science Center

Helena Solo-Gabriel, University of Miami, Department of Civil Engineering

Marylynn Yates, University of California at Riverside, Department of Environmental Sciences 

I mplementation R ealities G r oup 

Topical Group Lead: Charles McGee, Orange County Sanitation District

Shari Barash, U.S. EPA, Office of Water

Denise Keehner, U.S. EPA, Office of Water 

Geeta Rijal, The Metropolitan Water Reclamation District of Greater Chicago

Mike Tate, Kansas Department of Health and Environment, Bureau of Water 

Peter Tennant, Ohio River Valley Water Sanitation Commission 

Dan Woltering, Water Environment Research Foundation 

Sources Group: Human v. Nonhuman and Point v. Nonpoint

Topical Group Lead: Christobel Ferguson, Ecowise Environmental, Australia 

Valerie (Jody) Harwood, University of South Florida, Department of Biology 

Rachel Noble, University of North Carolina Chapel Hill, Institute for Marine Sciences 

Norma Ruecker, University of Calgary, Provincial Laboratory for Public Health 

Marion Savill, Institute for Environmental Science and Research, New Zealand

Workshop Staff

Tim Bartrand, Clancy Environmental Consultants 

Mark Gibson, Clancy Environmental Consultants 

Tom Hargy, Clancy Environmental Consultants 

Pat Harrigan, U.S. EPA, Office of Water

Audrey Ichida, ICF International

Trisha Johnson, Clancy Environmental Consultants 

Lisa Koehler, Tetra Tech, Inc.

Randi McCuin, Clancy Environmental Consultants 

Clair Meehan, Tetra Tech, Inc.

Workshop Planning Team

Nick Ashbolt, U.S. EPA, Office of Research and Development 

Shari Barash, U.S. EPA, Office of Water

Barbara Biggs, Metro Wastewater Reclamation District of Denver

Michael J. Casteel, San Francisco Public Utilities Commission

Samuel Dorevitch, University of Illinois Chicago, School of Public Health 

Christobel Ferguson, Ecowise Environmental, Australia 
WERF Inland Waters Workshop Report v 

Roger Fujioka, University of Hawaii, Water Resources Research Center

Rhonda Kranz, Water Environment Research Foundation 

Charles McGee, Orange County Sanitation District

Geeta Rijal, Metropolitan Water Reclamation District of Greater Chicago 

Peter Tennant, Ohio River Valley Water Sanitation Commission 

Gary Toranzos, University of Puerto Rico 

Richard Whitman, USGS, Lake Michigan Ecological Research Station

WERF Pathogen and Human Health Issue Area Team

Shari Barash, U.S. EPA, Office of Water

Bart Bibler, Ferrate Treatment Technologies, LLC; Creech Engineers Inc.

Barbara Biggs, Metro Wastewater Reclamation District of Denver

Gail Boyd, Independent Consultant

Michael J. Casteel, San Francisco Public Utilities Commission 

William L. Cairns, Trojan Technologies, Inc. 

Christobel Ferguson, Ecowise Environmental, Australia 

Thomas C. Granato, Metropolitan Water Reclamation District of Greater Chicago

Paul W. Keohan, Boston Water and Sewer Commission 

Norman LeBlanc, Hampton Roads Sanitation District

Keith Linn, Northeast Ohio Regional Sewer District

Karen Pallansch, Alexandria Sanitation Authority 

Geeta Rijal, The Metropolitan Water Reclamation District of Greater Chicago 

Peter Tennant, Ohio River Valley Water Sanitation Commission 

Gary Toranzos, University of Puerto Rico 

Water Environment Research Foundation Staff

Director of Research: Daniel M. Woltering, Ph.D. 

Program Director: Rhonda Kranz 

Report Production

Draft chapters for this report were prepared by the Inland Water Workshop participants during 

the course of the workshop. Topical group leaders revised and submitted the draft chapters to 

WERF. Based on these draft chapters, a draft report was compiled by Jeffrey Soller of Soller 

Environmental. The draft report was sent to the topical group leaders for review. Recommended 

revisions were addressed, and, subsequently, a revised report was sent to all workshop 

participants for review. Comments from the participants were incorporated by WERF into this 

final report. 
vi 

Acknowledgments..........................................................................................................................iii

List of Tables ................................................................................................................................. ix

List of Figures................................................................................................................................ ix

List of Acronyms ............................................................................................................................ x 

Executive Summary .................................................................................................................. ES-1

1.0 Introduction.................................................................................................................... 1-1

 1.1 Purpose ................................................................................................................. 1-1 

 1.2 Workshop Design................................................................................................. 1-1 

 1.3 Background .......................................................................................................... 1-3 

 1.4 Workshop Participants ......................................................................................... 1-4 

2.0 Setting the Stage.............................................................................................................. 2-1

2.1 Summary of Topic Areas ..................................................................................... 2-1 

 2.1.1 Indicators and Pathogens Group .............................................................. 2-1 

 2.1.2 Health Risks Group .................................................................................. 2-1 

 2.1.3 Water Matrix Group................................................................................. 2-2 

 2.1.4 Sources Group .......................................................................................... 2-2 

 2.1.5 Implementation Realities Group.............................................................. 2-3 

2.2 Perspectives for Framing Answers to Charge Questions ..................................... 2-3 

 2.2.1 Indicators and Pathogens Group .............................................................. 2-3 

 2.2.2 Health Risks Group .................................................................................. 2-4 

 2.2.3 Water Matrix Group............................................................................... 2-12 

 2.2.4 Sources Group ........................................................................................ 2-15 

 2.2.5 Implementation Realities Group............................................................ 2-17 

3.0 State of the Science......................................................................................................... 3-1

3.1 Indicators and Pathogens Group .......................................................................... 3-1 

 3.1.1 Water Quality Differences in Inland Compared to Coastal Waters......... 3-1 

 3.1.2 Use of AWQC Established for the Great Lakes in Inland Waters ........... 3-3 

3.2 Health Risks Group .............................................................................................. 3-4 

 3.2.1 Synthesis of Epidemiologic Literature..................................................... 3-4 

 3.2.2 Use of AWQC Established for the Great Lakes in Inland Waters ........... 3-7 

3.3 Water Matrix Group........................................................................................... 3-10 

 3.3.1 Use of AWQC Established for the Great Lakes in Inland Waters ......... 3-10 

 3.3.2 Issues Specific to Regression Models.................................................... 3-12 

 3.3.3 Issues Specific to Mechanistic Models.................................................. 3-12 

 3.3.4 Issues Specific to QMRA Models.......................................................... 3-13 

3.4 Sources Group .................................................................................................... 3-13 

 3.4.1 Differences in Sources Between Inland and Coastal Waters................. 3-13 

 3.4.2 Use of AWQC Established for the Great Lakes in Inland Waters ......... 3-18 

3.5 Implementation Realities Group........................................................................ 3-19 

TABLE OF CONTENTS
WERF Inland Waters Workshop Report vii

 3.5.1 Implementation Flexibilities in Current U.S. and International Approaches... 3-19 

 3.5.2 Realities and Flexibilities with Existing and Proposed Assessment

 Methodologies Used in Clean Water Programs..................................... 3-23 

4.0 Knowledge Gaps............................................................................................................. 4-1

4.1 Indicators and Pathogens Group .......................................................................... 4-1 

 4.1.1 Watershed Approach and Sanitary Survey to Characterize Sources and

 Locations of Pollution into that Watershed .......................................... 4-3 

 4.1.2 Sampling Strategy to Characterize Pollution for Inland Water Sites ...... 4-3 

 4.1.3 Evaluate and Optimize Molecular Methods .............................................4-4 

 4.1.4 Mechanistic Modeling Techniques.......................................................... 4-5 

4.2 Health Risks Group .............................................................................................. 4-6 

 4.2.1 Pollutant Sources as Modifiers of Risk .................................................... 4-6 

 4.2.2 Optimal QMRA Models and Methods for Inland Waters ....................... 4-6 

 4.2.3 The Use of Molecular Methods of Characterizing Microbial Water

Quality to Predict Health Risks................................................................ 4-7 

4.3 Water Matrix Group ............................................................................................. 4-8 

 4.3.1 Regression Models ................................................................................... 4-8 

 4.3.2 Understanding Factors Influencing Microbial Fate and Transport .......... 4-9 

 4.3.3 Mechanistic Models................................................................................. 4-9 

 4.3.4 Model Links to Health Outcomes .......................................................... 4-10 

4.4 Sources Group .................................................................................................... 4-11 

 4.4.1 Pathogenic Potential of Agricultural and Wildlife Feces ...................... 4-11

 4.4.2 Quantify Impact of On-site Sewage Treatment Systems on Microbial 

Water Quality......................................................................................... 4-12 

 4.4.3 Fate and Transport of Animal Pathogens in Relation to Indicators ....... 4-12 

 4.4.4 Epidemiology Studies in Inland Waters ................................................ 4-12 

 4.4.5 Characterization of Land Use and Sanitary Surveys............................. 4-13 

 4.4.6 Water Safety Plan Including BMPs....................................................... 4-13 

4.5 Implementation Realities Group........................................................................ 4-13 

 4.5.1 Sampling ................................................................................................ 4-13 

 4.5.2 Assessment............................................................................................. 4-14 

 4.5.3 Recreational Activities........................................................................... 4-14 

4.5.4 Proximity to Source ............................................................................... 4-15 

 4.5.5 Degree of POTW Influence ................................................................... 4-15 

 4.5.6 Potential Influence from Manure or Biosolids Spreading Activities..... 4-15 

 4.5.7 Greater Chance of Flowing Waters that are “Least Human Impacted” . 4-15 

 4.5.8 Implementation Issues that Might be Different for Inland Waters........ 4-15 

5.0 Research Priorities......................................................................................................... 5-1

5.1 Suggested Research Needs and Justifications...................................................... 5-1 

5.1.1 Indicators and Pathogens Group .............................................................. 5-1 

 5.1.2 Health Risks Group .................................................................................. 5-2 

 5.1.3 Water Matrix Group................................................................................. 5-6 

 5.1.4 Sources Group .......................................................................................... 5-7 

 5.1.5 Implementation Realities Group.............................................................. 5-8 

5.2 Consolidation of Research Priorities Across Groups......................................... 5-10 
viii 

5.3 Prioritized Research Recommendations............................................................ 5-11 

 5.3.1 Highest Priority Short-Term Research Activities.................................. 5-11 

 5.3.2 Highest Priority Longer-Term Research Activities............................... 5-13 

Appendix A ................................................................................................................................. A-1 

References ................................................................................................................................... R-1
WERF Inland Waters Workshop Report ix

3-1 Pathogen Hazards Arising from Animals...................................................................... 3-14 

3-2 Pathogen Sources and Hazards Typically Captured in Sanitary Surveys...................... 3-17 

5-1 Research Priorities for Fecal Contamination Sources Group .......................................... 5-8 

A-1 Understanding the Relationship Between Sources of Fecal Indicators and Pathogens.. A-2 

A-2 Retrospective Evaluation of Epidemiologic Studies....................................................... A-3 

A-3 Microbiological Method Development or Enhancement................................................ A-4 

A-4 Enhancements to or Recommendations for Future Epidemiologic Studies.................... A-5 

A-5 Model Development and/or Enhancement...................................................................... A-6 

A-6 Data Mining, Literature Reviews, and White Papers ..................................................... A-7 

A-7 Criteria Development/Implementation Options and Issues............................................ A-8 

3-1 Conceptual Model for Extending Health Risk Relationships to Inland Flowing Waters ... 3-5 

3-2 Schematic Diagram for Comparing Study Results........................................................ 3-10 

3-3 Sources Group Schematic for Applicability of Criteria to Inland Waters..................... 3-19 

4-1 Conceptual Inputs to a Lake or Stream............................................................................ 4-2 

LIST OF TABLES

LIST OF FIGURES
x 

ATP Adenosine Triphosphate 

AWQC Ambient Water Quality Criteria

BMP Best Management Practice

CAFO Confined Animal Feeding Operation 

CFU Colony-Forming Units

CI Confidence Interval

CSO Combined Sewer Overflow 

CWA Clean Water Act

DNA Deoxyribonucleic Acid

E. coli Escherichia coli 

FC Fecal Coliform

FIB Fecal Indicator Bacteria

FS Fecal Streptococci

GI Gastrointestinal 

GIS Geographic Information System 

GL Great Lakes

MPN Most Probable Number

MST Microbial Source Tracking

NEEAR National Epidemiological and Environmental Assessment of Recreational 

water study

NGO Nongovernmental Organization 

NOAEL No Observed Adverse Effects Level

NPDES Nonpoint Discharge Elimination System 

NPS Nonpoint Source 

PCR Polymerase Chain Reaction

PMA Propidium Monoazide 

POTW Publicly Owned Treatment Works 

pd Person-days

QMRA Quantitative Microbial Risk Assessment

Q-PCR Quantitative Polymerase Chain Reaction

SOP Standard Operating Procedure 

TMDL Total Maximum Daily Load

UAA Use Attainability Analysis

U.S. EPA United States Environmental Protection Agency 

LIST OF ACRONYMS
WERF Inland Waters Workshop Report xi

USGS United States Geological Survey

UV Ultraviolet

VBNC Viable but Not Culturable 

WERF Water Environment Research Foundation 

WHO World Health Organization

WQS Water Quality Standard 
xii 
WERF Inland Waters Workshop Report ES-1 

EXECUTIVE SUMMARY

On February 18-20, 2009, the Water Environment Research Foundation (WERF) with 

collaboration from the U.S. Environmental Protection Agency (U.S. EPA) held a workshop to 

consider the significance of differences between inland and coastal recreational waters within the 

context of national recreational water quality criteria for primary contact recreation users. The 

objectives were to determine if coastal research can be extrapolated to inland waters, and to 

identify and prioritize research needs for development of criteria applicable to inland waters.

Thirty-one invited experts from the academic, state and federal agency, utility, consultant, and 

nongovernmental organization communities participated in the Inland Waters Workshop. This

report summarizes the proceedings and findings from the Workshop. 

Background

It has been 20 years since water quality criteria to protect primary contact recreational 

users were last published. U.S. EPA is in the process of developing new or revised ambient water 

quality criteria (AWQC) for primary contact recreational waters. Under a Consent Decree, 

research for new criteria must be complete by December 15, 2010, and the criteria published in 

October 2012. Most research on recreational water quality and human health risk has focused on 

marine coastal and Great Lakes waters. U.S. EPA intends the new criteria to apply to all primary 

contact recreational waters, both coastal and inland. It is not clear, however, if criteria based 

solely on studies in the Great Lakes and marine coastal waters are appropriate for inland waters. 

The Inland Water Workshop was undertaken to address this and related questions.

The objectives of the Inland Water Workshop were to: 

♦ determine if or how marine coastal and Great Lakes recreational water research can be 

extrapolated to apply to inland waters 

♦ identify additional research that could aid in the development of water quality criteria 

applicable to inland waters in both the near and the longer term. 

Charge to the Participants

The workshop participants were asked to 1) assess the current state of knowledge about 

how inland waters are similar to or different from Great Lakes and marine coastal waters with 

respect to waterborne pathogens in recreational waters, 2) identify knowledge gaps and research 

needs for development of recreational water criteria for inland waters, and 3) identify research 

priorities for both the short and longer term. 

Short-term research was defined as new research that could be initiated and completed by 

WERF, U.S. EPA, or the broad scientific community by December 15, 2010. Short-term 

research would lead to better understanding of the appropriateness of applying new AWQC

based on studies in the Great Lakes and marine coastal areas to inland waters, particularly inland 

flowing waters. Longer-term research is that which could not be concluded by December 15, 

2010. Longer-term research is less constrained than short term and is research that would lead to

a more robust understanding of the health risks from recreating in inland waters.
ES-2 

The workshop was organized around five topical groups with a series of charge questions 

that experts in each topical group were asked to address. The topical groups were 

♦ indicators and pathogens: biology, ecology, and methods 

♦ health risks: epidemiology and risk assessment 

♦ water matrix: hydrology, chemistry, geology, and modeling 

♦ sources: human v. nonhuman and point v. nonpoint 

♦ implementation realities.

Each group addressed the following four questions along with a subset of questions specific to 

their expertise: 

1. What is the state of the science regarding differences that impact water quality in inland 

waters versus marine coastal or Great Lakes waters? What are the potential implications 

of any differences for the development of new or revised recreational water quality 

criteria? 

2. Are there scientific limitations for extrapolating AWQC based on marine coastal or Great 

Lakes waters to inland waters? If there are, what are they? Are these limitations 

substantially greater than those that currently exist in extrapolating data from a relatively 

small number of marine coastal water studies to all marine coastal waters?

3. Are there critical knowledge gaps that could be addressed by December 2010 by 

scientific research or by October 2012 by implementation approaches that may facilitate 

the development of national recreational water quality criteria for primary contact in 

inland waters? 

4. What critical knowledge gaps should be addressed in the longer term and how? 

Differences between Inland and Marine Coastal or Great Lakes Waters

Each group summarized knowledge and opinions about differences that affect water 

quality in inland waters as opposed to marine coastal or Great Lakes waters and the potential 

implications of those differences for the development of new or revised recreational water 

quality criteria. Salient points from each group are summarized below. 

The indicators and pathogens group identified sources of fecal indicator bacteria, as humans, 

animals, and the environment, and posited that factors affecting water quality in the Great Lakes 

fundamentally reflect the characteristic conditions of these large lakes. Inland flowing waters 

found throughout the United States are very diverse in terms of water flow, water volume, size, 

and morphology of stream beds, land use, and anthropogenic impacts as well as physical and 

biological composition of water quality. Inland lakes differ from coastal waters and the Great 

Lakes in terms of anthropogenic impacts, shoreline surface area, shoreline complexity, 

topography, land use, and other factors. With this mind, the group members concluded that no 

single set of characteristics can be applied to describe all inland waters. Because of such 

differences in inland water sites, the factors that control the fate, survival, transport, regrowth 

potential, and ecology of indicators and pathogens are not likely to be the same for all inland 

water sites and will likely differ from those factors found at the Great Lakes or marine coastal 

beaches. 
WERF Inland Waters Workshop Report ES-3 

The health risks group reviewed relevant epidemiologic studies of recreational water to identify 

differences between coastal and inland water settings. Based on their review, they indicated that 

the scientific literature does not provide a clear answer to the question of whether the 

epidemiologic results from the Great Lakes can be applied to inland flowing waters. In 

particular, only a handful of studies have been conducted in small lakes and even fewer in inland 

flowing waters, and none of the latter are readily comparable to studies conducted in coastal 

settings. Furthermore, it is not known whether and in what ways the predominant source of fecal 

contamination (human, livestock, wildlife, and environmental) influences the water 

quality/health risk relationship. 

It was the opinion of the health risks group that water quality criteria derived from Great Lakes 

studies would likely be protective of public health at inland waters. Given the unique aspects of 

inland waters identified in the workshop, the health risks group recognizes the significant

challenges in implementing the water quality monitoring methods used in Great Lakes recreation 

studies and interpreting the results of such testing in inland waters. Therefore, the group strongly 

recommended that an early effort be made to fill the knowledge gaps identified during this 

workshop by conducting multidisciplinary epidemiologic investigations in inland waters. 

The water matrix group was of the opinion that the only way to understand all the important 

factors that may affect the relationships between health effects and indicators/water quality is 

through modeling efforts. As no two watersheds are the same, there is a possibility that similar

beaches at one location may have a different relationship (between indicators and human health 

effects) as compared to beaches at another location due to significant differences in the sources, 

transport, and microbial fate. The water matrix group is of the opinion that the only way to 

effectively transfer the results from one watershed to another would be to evaluate similarities 

between watersheds with respect to potential sources and geographic distribution of those 

sources. Such efforts require a fundamental understanding of the fate and transport of indicators 

and pathogens, which is currently lacking in the literature and, therefore, limits the ability to 

apply modeling approaches to support regulatory purposes. This group also indicated that 

questions regarding differences between pathogens and indicators in terms of their regrowth and 

persistence in sediments/soils and associated waters need to be answered before epidemiologic 

data from Great Lakes and marine coastal areas can be applied with confidence to inland 

flowing waters.

The sources group characterized the differences between sources that impact Great Lakes and 

marine coastal waters as compared to inland waters in three categories: types of fecal 

contamination, scale issues, and inland environment issues. The types of fecal contamination are 

important because animal feces are prevalent sources in inland waters and are generally thought 

to present less of a risk to human health than human feces, but the extent of the reduced risk has 

not been quantified and varies depending on a number of factors such as the animal source, level 

of treatment, animal density, and climate. Scalar level differences between coastal and inland 

waters include: 1) proximity of sources of fecal contamination to receiving waters, 2) the 

quantity of fecal material (particularly livestock) that contains specific types of pathogens and 

the virulence of those pathogens, 3) the mechanisms of delivery of fecal contamination, 4) the 

land use types surrounding inland waters, and 5) the effect of manure and biosolids on inland 

waters. With respect to environmental issues, the sources group indicated that it is possible that 
ES-4 

indigenous fecal indicator bacteria sources are more important quantitatively in inland waters 

than in marine or Great Lakes environments. 

The implementation realities group focused on the effect of applying recreational water 

criteria developed for the Great Lakes and marine coastal beaches to inland waters in terms of 

implementation flexibilities currently available in the United States and in recreational water 

quality programs worldwide. The flexibilities most directly relate to the implementation 

challenges facing inland waters such as wet weather, high flow events, the increased potential for 

animal sources of fecal indicator bacteria in rural areas, and the increased influence on indicator 

concentrations by resuspension of sediment containing environmental strains of indicators. 

Because of the large number of inland river and stream miles, the impact of new criteria on the 

operations of state water quality programs and the implementation realities faced by municipal 

wastewater utilities and state and local health departments could be dramatic. The practicalities 

of implementing new criteria highlight the need for states (and territories) to have 

implementation flexibility of new criteria while ensuring that state water quality program 

resources remain focused on achieving the greatest public health benefits with the available 

resources.

Recommended Research Activities

Each group identified critical knowledge gaps that could be addressed in the short term to 

support development of the new national recreational water quality criteria for primary contact in 

inland waters. The groups also identified fundamental knowledge gaps that should be addressed 

in the longer term. Several common research needs and numerous overlapping ideas were 

identified across groups. The topical group leaders considered the relative importance and merit 

of all suggested research activities and developed a prioritized list. The following three shortterm and two longer-term research activities emerged as the highest priority research activities. 

Short-Term Research Activities 

Identify and quantify human pathogens in animal feces: The purpose of this activity would 

be to quantitatively characterize the human pathogenic potential of agricultural and wildlife 

feces. This research activity would be useful within the context of understanding epidemiologic 

studies with predominant sources of contamination that are nonhuman and for understanding the 

potential risks to human health for a broad range of waters impacted by nonhuman sources. 

Examine relationships between quantitative polymerase chain reaction (Q-PCR) and 

culture-based fecal indicator bacteria (FIB): Culture-based methods for FIB measure the 

fraction of culturable bacteria that are recovered by the method used. Q-PCR measures all 

fractions of FIB including the culturable fraction, the stressed fraction (which are not recovered 

by the culture method), the viable but non-culturable fraction, the killed or dead fraction, as well 

as the fraction of free nucleic acid.. This activity would lead to an improved understanding of the 

persistence of microbial nucleic acids and the relationship between cell-based and cellindependent targets. 

Optimize and anchor quantitative microbial risk assessment (QMRA) models to observed 

health effects data obtained from epidemiologic studies and develop QMRA tools for 

implementation of new AWQC: This research activity would provide an understanding of how 
WERF Inland Waters Workshop Report ES-5 

predictions from QMRA models relate to human health outcomes observed in epidemiologic

studies. Such anchoring of QMRA predictions can be accomplished retrospectively and 

prospectively and would enhance the scientific credibility for using these techniques to predict 

recreational waterborne illness. 

Longer-Term Research Activities 

Characterize fate and transport of animal pathogens in relation to indicators: Animal 

densities and fecal excretion rates have a significant impact on the amount of material available 

for mobilization to inland waters during rainfall or runoff events. However, little information is 

known about these factors and how they vary across the United States. This research activity 

would help to understand the factors affecting pathogen transport mechanisms to waterways 

during runoff events, to enable their incorporation into mechanistic models for predicting inland 

water quality. 

Conduct epidemiologic studies in inland waters: Presently, the scientific literature does not 

support direct comparisons of health risk as a function of recreational water quality in Great 

Lakes/coastal and inland waters. This activity would expand the base of available epidemiologic 

information and help to address the key knowledge gaps regarding sources, effects of hydrology, 

and indicator-pathogen relationships in inland waters within the context of health risks. 
ES-6 
WERF Inland Waters Workshop Report 1-1 

CHAPTER 1.0

INTRODUCTION

1.1 Purpose

From February 18 to 20, 2009, the Water Environment Research Foundation (WERF) 

convened an Expert Scientific Workshop on Critical Research and Science Needs

for the Development of Recreational Water Quality Criteria for Inland Waters to consider the 

significance of differences between inland and coastal recreational waters within the context of 

recreational water quality criteria development. The objectives of the workshop were to 

1) determine if or how marine coastal and Great Lakes recreational water research can be 

extrapolated to apply to inland waters, and 2) identify additional research that could aid in the 

development of water quality criteria applicable to inland waters in both the near and the longer 

term. 

The Inland Water Workshop was organized through WERF’s Pathogen and Human 

Health Research Program with logistical, planning, and content support provided by the U.S. 

Environmental Protection Agency’s Office of Water. A group of 31 scientific experts from 

academic, state and federal agency, utility, and consultant communities participated. The experts 

were asked to assess the current state of knowledge about how inland waters are similar to or 

different from Great Lakes and marine coastal waters with respect to waterborne pathogens in 

recreational waters and to identify knowledge gaps and research activities that could inform the 

development of new or revised ambient water quality criteria (AWQC) for primary contact 

recreational waters. This report summarizes the proceedings and findings from the workshop and 

is intended to provide the foundation for future research that will inform AWQC development. 

For purposes of the workshop, inland waters were defined as those waterbodies that are 

not coastal recreation waters as defined by the Clean Water Act (CWA). They are typically 

freshwater and include inland waterway systems, flowing waters (e.g., rivers and streams),

quiescent waters (e.g., reservoirs and lakes), and some limited saltwater waterbodies (that are not 

also coastal recreational waters). Thus, in this context, the term “inland waters” does not include 

marine coastal waters, estuaries, or the Great Lakes.

1.2 Workshop Design

The Inland Water Workshop was similar in format to the Society of Environmental 

Toxicology and Chemistry Pellston Workshops, in which technical experts in a particular subject 

area are invited to participate and evaluate current and prospective environmental issues. A 

Pellston-type workshop typically brings together up to 50 technical experts from academia, 

business, government, and public interest groups. Experts are semi-sequestered for up to a week 

to facilitate focused discussions. The experts participate in individual and collaborative writing 

of a draft summary report by the end of the workshop. Subject area leaders are then responsible 
1-2 

for consolidating, editing, producing, and distributing the final workshop proceedings. This same 

workshop format was used during the Expert Scientific Workshop on Critical Research and 

Science Needs for the Development of New or Revised Recreational Water Quality Criteria (U.S. 

EPA, 2007b). 

This workshop was organized around five topical areas with a series of charge questions 

that experts in each topical area group were asked to address. Expert input on these charge 

questions forms the basis of this workshop report. The topical areas comprised the following: 

♦ indicators and pathogens: biology, ecology, and methods 

♦ health risks: epidemiology and risk assessment 

♦ water matrix: hydrology, chemistry, geology, and modeling 

♦ sources: human v. nonhuman and point v. nonpoint 

♦ implementation realities.

Experts were asked to provide their individual knowledge and insights that would help 

define research and science needs for development of primary contact recreational water criteria 

for inland waters. The state of the science and the data currently available on marine coastal, 

Great Lakes, inland lakes, and inland flowing waters were of particular interest. Specifically, 

expert views were sought with regard to understanding the similarities and differences among 

these waterbodies and identifying research priorities for both the short and longer-term. 

Short-term research was defined as research that could be initiated and completed by 

WERF, U.S. EPA, or the wider scientific community by December 15, 2010. Short-term 

research would lead to better understanding of the appropriateness of applying new AWQC

based on studies in the Great Lakes and marine coastal areas to inland waters, particularly inland 

flowing waters. Longer-term research is research that could not be concluded by December 15, 

2010. Longer-term research is less constrained than short-term research and would lead to a 

more robust understanding of the health risks from recreating in inland waters. 

For each topic area, experts were provided a series of specific questions to facilitate 

discussions. The results of those discussions were then to be used in answering the following 

overarching questions: 

1. What is the state of the science regarding differences that affect water quality in inland 

waters versus marine coastal or Great Lakes waters? What are the potential implications 

of any differences for the development of new or revised recreational water quality 

criteria? 

2. Are there scientific limitations for extrapolating AWQC based on marine coastal or Great 

Lakes waters to inland waters? If there are, what are they? Are these limitations 

substantially greater than those that currently exist in extrapolating data from a relatively 

small number of marine coastal water studies to all marine coastal waters?

3. Are there critical knowledge gaps that could be addressed by December 2010 by 

scientific research or by October 2012 through implementation approaches that may 

facilitate the development of national recreational water quality criteria for primary 

contact in inland waters? 

4. What critical knowledge gaps should be addressed in the longer term and how?
WERF Inland Waters Workshop Report 1-3 

The responses to the above questions from each of the groups are summarized in the 

following chapters in this report. 

1.3 Background

U.S. EPA last published recommendations for water quality criteria to protect primary 

contact recreational uses of waters in 1986 (U.S. EPA, 1986). These criteria are CWA section 

304(a) criteria and, as such, U.S. EPA recommended applying them for all waters to protect 

people recreating in these waters from gastrointestinal illness. Among other provisions, the 

BEACH Act of 2000 (an amendment of the CWA), required U.S. EPA to develop new or revised 

AWQC for the protection of “swimming, bathing, surfing, or similar water contact activities” in 

all marine coastal and Great Lakes waters designated in state water quality standards for primary 

contact recreation1,2. State water quality standards are used in various CWA programs, including 

beach monitoring and notification programs, development of water quality based effluent limits 

for Nonpoint Discharge Elimination System (NPDES) permits, water body assessments to 

determine use attainment, and development of total maximum daily loads (TMDLs), where 

needed. 

Although the BEACH Act amendments do not directly apply to inland waters, CWA 

section 304(a)(2) requires U.S. EPA to periodically update CWA section 304(a) 

recommendations. Thus, it is U.S. EPA’s current perspective that the upcoming new or revised 

criteria (to be published by October 2012) should apply to all primary contact waters of the 

United States. Recognizing this, some stakeholders have raised concerns that inland waters, 

particularly flowing waters, may differ from coastal recreational waters in terms of the fate and 

behavior of indicators relative to pathogens, ecology of microbes, human health risks, hydrology 

and geology, sources of contamination, and exposure patterns. The thrust of these concerns is 

that new or revised recreational water quality criteria based solely on studies in the Great Lakes 

and coastal waters may not be appropriate for other types of waters. These stakeholder concerns 

reinforced the need to seek input through an expert workshop. 

Since the current AWQC were published, there have been substantial advances in the 

science surrounding waterborne microbiological contamination. In 2007, U.S. EPA held an 

expert workshop to obtain input on “critical path” research and science needs for developing 

scientifically defensible new or revised CWA Section 304(a) AWQC for recreational waters in 

the near term. The input from the 2007 workshop informed U.S. EPA’s Critical Path Science 

Plan, which identified the need for research specific to inland waters (U.S. EPA, 2007a). The 

 

1 In adopting new or revised water quality standards, states must adopt criteria that are scientifically defensible and 

protective of the use, but they have flexibility to do so by adopting U.S. EPA’s recommended criteria, adopting 

criteria to reflect site-specific conditions, or adopting other criteria that are scientifically defensible. In 

approximately 2015, states with coastal recreation waters will be required to adopt and submit to the administrator 

new or revised water quality standards for the coastal recreation waters of the state for all pathogens and pathogen 

indicators to which U.S. EPA's forthcoming new or revised water quality criteria are applicable.

2 Primary contact recreation is typically defined by states in their state water quality standards but is generally 

considered to mean water-related recreational activities in which there is a high degree of bodily contact with the 

water (e.g. where there is a high likelihood of incidental ingestion of water). Examples include, but are not limited 

to, swimming, certain kinds of kayaking, tubing, skin diving, surfing, water skiing, and water play by children. 
1-4 

Inland Water Workshop builds upon the 2007 workshop with a specific focus on the state of the 

science and research priorities with regard to inland waters.

Research is currently under way by U.S. EPA, WERF, and others to inform the 

development of the upcoming new or revised AWQC for recreational waters. Under a Consent 

Decree, research for the new or revised criteria must be complete by December 15, 2010. Within 

the broader objective of the workshop one particular output of interest to U.S. EPA was to 

understand whether the differential is greater, the same, or smaller in extrapolating from the 

Great Lakes and waters coastal to inland waters, as compared to the differential associated with 

extrapolating from a handful of coastal waters to all coastal waters. 

In identifying the scope and limits of the Inland Water Workshop, two issues arose: the 

relative degree of focus on 1) inland waters (generally) versus inland flowing waters 

(specifically); and 2) criteria for secondary contact recreational uses in addition to those for 

primary contact. Within the category of inland waters, flowing freshwaters are of particular 

importance to U.S. EPA in development of the new or revised criteria. Therefore, in addition to 

addressing the research needs for inland waters in general, specific input was requested from 

workshop participants regarding critical research that can be completed by the end of 2010 on 

flowing waters. Development of new criteria for secondary contact recreational waters is also an 

important issue for many stakeholders. Currently, the scientific and policy basis for criteria 

development for secondary contact is limited; therefore, secondary contact issues were not 

addressed directly in the workshop. It was suggested that the state of the science could be 

captured in the future. 

1.4 Workshop Participants

Indicators and Pathogens Group: Biology, Ecology, and Methods 

Topical Group Lead: Roger Fujioka, University of Hawaii, Water Resources Research Center

Topical Group Lead: Richard Whitman, USGS, Lake Michigan Ecological Research Station 

Michael J. Casteel, San Francisco Public Utilities Commission

Kevin Oshima, U.S. EPA, Office of Research and Development

John Ravenscroft, U.S. EPA, Office of Water 

Jill Stewart, University of North Carolina Chapel Hill, School of Global Public Health

Gary Toranzos, University of Puerto Rico 

Health Risks Group: Epidemiology and Risk Assessment

Topical Group Lead: Samuel Dorevitch, University of Illinois Chicago, School of Public Health 

Alfred Dufour, U.S. EPA, Office of Research and Development

Patrick Gurian, Drexel University, Department of Civil, Architectural, and Environmental 

Engineering 

David Kay, University of Wales, Centre for Research into Environment and Health 

Mary E. Schoen, U.S. EPA, Office of Research and Development

Jeffrey Soller, Soller Environmental 

Stefan Wuertz, University of California at Davis, Department of Civil & Environmental 

Engineering

Water Matrix Group: Hydrology, Chemistry, Geology, and Modeling 

Topical Group Lead: Nick Ashbolt, U.S. EPA, Office of Research and Development
WERF Inland Waters Workshop Report 1-5 

Ali Boehm, Stanford University, Department of Civil & Environmental Engineering 

Donna Francy, USGS, Ohio Water Science Center

Helena Solo-Gabriel, University of Miami, Department of Civil Engineering

Marylynn Yates, University of California at Riverside, Department of Environmental Sciences 

Implementation Realities Group 

Topical Group Lead: Charles McGee, Orange County Sanitation District

Shari Barash, U.S. EPA, Office of Water

Denise Keehner, U.S. EPA, Office of Water

Geeta Rijal, Metropolitan Water Reclamation District of Greater Chicago

Mike Tate, Kansas Department of Health and Environment, Bureau of Water 

Peter Tennant, Ohio River Valley Water Sanitation Commission 

Dan Woltering, Water Environment Research Foundation 

Sources Group: Human vs. Nonhuman and Point vs. Nonpoint

Topical Group Lead: Christobel Ferguson, Ecowise Environmental, Australia 

Valerie (Jody) Harwood, University of South Florida, Department of Biology 

Rachel Noble, University of North Carolina Chapel Hill, Institute for Marine Sciences 

Norma Ruecker, University of Calgary, Provincial Laboratory for Public Health 

Marion Savill, Institute for Environmental Science and Research, New Zealand
1-6 
WERF Inland Waters Workshop Report 2-1 

CHAPTER 2.0

SETTING THE STAGE

2.1 Summary of Topic Areas

Following are brief descriptions of each group’s primary focus during the workshop. 

2.1.1 Indicators and Pathogens Group 

This group focused on the persistence, ecology, and fate and behavior of indicators of 

fecal contamination and pathogens in inland waters as well as the performance and efficacy of 

analytical methods for indicators and pathogens in inland waters. This group also addressed

reports of significant and important differences between locations in terms of the densities and 

co-occurrence of indicators and pathogens. 

The indicators and pathogens group was asked to provide opinions and knowledge to 

1. Characterize and compare available information on inland waters and coastal recreational 

waters regarding fecal indicators and pathogens, including analytical methods. 

2. Determine if any differences between inland and coastal recreation waters could be 

considered significant in the context of recreational water quality criteria development.

3. Prioritize and provide input on protective public health actions and future research for 

inland recreational waters, especially with regard to national criteria development.

2.1.2 Health Risks Group 

The underlying reason for developing recreational water quality criteria for inland waters 

is to improve public health protection from waterborne illness. The health risks group focused on 

the body of health-related literature directly pertinent to inland waters. A review of the literature 

indicates that few epidemiologic studies into the health risks of recreational use of inland waters 

have been performed. The literature also indicates that several risk assessment studies have been 

conducted to model recreational risks in inland environments, yet the body of information 

supporting risk assessment assumptions in the context of inland waters is limited. 

The health risks group was asked to provide opinions and knowledge to 

1. Summarize what is known about the health risks of recreation in the setting of inland 

waters.

2. Characterize the uncertainty in estimates of risk derived from studies designed to measure 

risk (i.e., epidemiologic studies) and the assumptions of models designed to model risk 

(i.e., quantitative microbial risk assessment [QMRA]).

3. Evaluate the relevance of studies conducted in marine or Great Lakes coastal waters to 

the development of recreational water quality criteria for inland waters.
2-2 

4. Define key data gaps that may preclude developing science-based recreational water 

quality criteria for inland waters, and outline studies to address those gaps. 

2.1.3 Water Matrix Group 

The overall focus of the water matrix group was to identify the physicochemical and 

hydrological parameters that might differ when modeling the fate and transport of pathogens 

and/or indicators in inland waters as compared to in marine coastal or Great Lakes waters. 

The water matrix group was asked to provide opinions and knowledge to 

1. Describe the various modeling approaches used to assess pathogen and/or indicator fate 

and transport in aquatic media. 

2. List the key parameters used in modeling pathogen and/or indicator fate and transport by 

classes of water of interest (flowing, inland lakes, coastal and Great Lakes). 

3. Describe key differences in hydrologically driven parameters used to model inland water 

pathogens and/or indicators as compared with coastal and Great Lakes waters. 

4. Identify potential issues in interpreting indicator concentration estimates from models 

versus direct estimates used in epidemiologic studies – i.e. are there potential impacts on 

our understanding and interpretation of epidemiologic derived health outcomes? 

5. Describe research projects that could address inland waters with respect to:

o Identifying or developing models to provide indicator concentrations that may be 

used in estimating TMDLs and public health advisories 

o Determining the most sensitive model parameters, research that would reduce data 

uncertainty 

o Identifying any outstanding issues in adapting current models to their use for inland 

waters and in setting appropriate AWQC. 

2.1.4 Sources Group

Humans and animals are sources of fecal material that exist in almost all watersheds and, 

therefore, are potential sources of pathogen contamination in both coastal and inland recreational 

waters. Consideration of the host origin of indicators of pathogens and specific pathogens 

(concentration, prevalence, and frequency) and the extent of their variability are important 

factors in assessing the relative risks of pathogens to surface waters.

Little quantitative data exist on the relative contribution of pathogens from humans as

compared to various animal hosts. Comparison of these two sources is also complicated because 

animal contributions are typically spread across wide areas of a watershed occurring as diffuse 

inputs (i.e., nonpoint sources) whereas human inputs are usually discharged as point sources of 

pollution. Variations in sewage treatment efficacy, efficiency of microbial transport to 

waterways, and environmental regrowth of FIB further complicate comparison of these sources 

of contamination. Also, the effectiveness of various control measures and best management 

practices for mitigating pathogen loads from diffuse and point sources are not well defined. 

A variety of tools are becoming available to assess pathogen risks to waterways including 

QMRA and mathematical modeling. However, a lack of solid quantitative data on the source 

loads, and particularly a description of their variability, can limit the effectiveness of these tools 
WERF Inland Waters Workshop Report 2-3 

and reduce the reliability of their outputs. Similarly, AWQC developed for these waters must be 

based on sound data to ensure that they are achievable for both coastal and inland waters. 

The sources group was asked to provide opinions and knowledge to 

1. Determine whether there are significant differences in source loads to inland waters as 

compared to coastal recreation waters. 

2. Assess the research that may be required to define any such differences.

3. Discuss the potential for existing tools such as sanitary surveys and TMDLs to assist in 

the evaluation of pathogen risks to inland waters. 

2.1.5 Implementation Realities Group 

The task of the implementation realities workgroup was to document concerns and 

practical implications from the points of view of the regulated community and the regulatory 

authorities associated with applying recreational criteria to inland waters. The group worked 

under the assumption that the criteria for inland waters were to be based on existing marine

coastal and/or Great Lake studies from which relationships between pathogens/indicators of 

pathogens and health effects had been established. Workgroup members also operated under the 

assumption that new or revised AWQC need to be implemented for NPDES permitting and for 

monitoring and assessment programs required for CWA §303(d) and §305(b) purposes, and in 

the development of TMDLs for inland waters. 

The implementation realities group was asked to

1. Participate in other workgroups with the intention of capturing informational gaps related 

to 

♦ the science upon which any recommended criteria are developed 

♦ the applicability of the criteria to tropical as well as temperate climates

♦ the robustness, accuracy, reproducibility, timeliness, and cost effectiveness of the 

assessment tools 

♦ the ease with which assessment tools can be transferred from research laboratories 

into monitoring laboratories and programs.

2. Describe research or implementation strategies that might mitigate the informational gaps 

and implementation concerns in the above areas. 

2.2 Perspectives for Framing Answers to Charge Questions

2.2.1 Indicators and Pathogens Group 

Indicators of fecal contamination historically have been chosen from a few groups of 

nonpathogenic fecal bacteria (e.g., fecal coliforms, Escherichia coli, enterococci) and have been 

used for decades by public health officials and regulatory agencies to indicate the presence and 

magnitude of fecal material in recreational waters. In using these fecal indicator bacteria (FIB), 

the U.S. EPA has made two implicit assumptions. The first is that waterborne pathogens cooccur with the fecal material and that there are no significant environmental (i.e., non-enteric) 

sources of these microorganisms. The second assumption is that indicator fate and behavior, 

ecology and persistence, and performance in all types of recreational waters, including marine, 
2-4 

estuarine, and inland flowing and nonflowing waters, remain consistent and are similar to those 

of pathogens of fecal origin. Both of these assumptions were evaluated during a recent workshop 

focused on tropical water quality and reported to be invalid for tropical regions such as Hawaii, 

Guam, Puerto Rico, and South Florida (Fujioka and Byappanahalli, 2003). Studies conducted in 

these regions have shown that FIB are able to multiply in environmental sites (soil, plants, 

sediments) (Rivera et al., 1988; Byappanahalli and Fujioka, 1998; Solo-Gabriele et al., 2000; 

Byappanahalli and Fujioka, 2004). Initially, only data from these tropical regions studies 

indicated that fecal coliforms, E. coli, and enterococci bacteria are able to multiply in the 

environment (soil, sediment, plants) and, enter inland waters at concentrations exceeding 

recreational water quality standards. However, more recently, growth and persistence of 

environmental sources of FIB also have been reported in temperate areas such as within the 

Great Lakes region (Byappanahalli et al., 2006; Ishii et al., 2006a; Whitman et al., 2006) and 

along the California Coast (Yamahara et al., 2009). 

The acknowledged problem associated with unreliability of recreational water quality 

standards based on concentrations of E. coli and enterococci was one of the questions targeted 

during the recent 2007 U.S. EPA Expert Workshop (U.S. EPA, 2007b). One identified central 

issue in criteria development is whether it is scientifically valid to extrapolate developing and 

existing data sets, such as the epidemiology studies conducted in Great Lakes freshwater 

environments, to flowing (e.g., streams, rivers) and quiescent (e.g., ponds, lakes, reservoirs) 

inland freshwater environments. The specific questions of concern are related to similarities and 

differences between coastal and inland freshwaters. If these questions cannot be answered, given 

current data and understanding of phenomena in coastal and inland waters, additional studies 

should be recommended to establish any significant differences.

The methods used to enumerate bacteria and pathogens in environmental waters are 

intricately linked to criteria development. When methods to be used in the development of new 

or revised criteria in the near term are recommended, consideration should be given to resources, 

training, and capabilities of state public health and environmental laboratories to incorporate 

these new methods. Consideration should also be given to the methods currently being evaluated 

by U.S. EPA in their epidemiologic studies to correlate water quality measurements to measured 

human health effects. In addition, consideration should be given to other promising methods 

reported in the literature, however, they should be sufficiently verified or used by several 

laboratories to meet the criteria for use by the implementation realities group. 

2.2.2 Health Risks Group 

The health risks groups conducted a review of epidemiologic studies related to inland 

waters. This review, and the knowledge of group members about completed and ongoing studies, 

formed the basis for answering the charge questions. Following is a brief summary of the studies 

that were discussed and considered by this group. Studies of surfing, generally a coastal, rather 

than an inland water activity, were not reviewed. 

Inland Flowing Waters

France: A prospective cohort study was conducted on the Ardeche river basin in France at eight

vacation camps in the vicinity of five beaches (Ferley et al., 1989; Zmirou et al., 1990). The main 

microbial source was reported to be urban domestic sewage discharged to the river, untreated at 

the time of study. The microbiological concentrations exhibited considerable spatial variation 
WERF Inland Waters Workshop Report 2-5 

among the study locations. The study population was tourists who stayed at least 3 days at the 

holiday camps during July and August. Study participants answered questions about illness and 

bathing behavior during the 7 days prior to the interview day. The study population was recruited 

from people vacationing at locations along the river. A total of 5,737 participants provided data 

on their health status and days of exposure to recreational waters. Among 2,978 bathers, 18,945 

person-days (pds) of observation were recorded and among 750 non-bathers, 9,011 pds were 

recorded. Water quality was measured only twice per week, and exposures occurred on days for 

which no water measurements were made.

A water quality/health risk relationship was observed between fecal streptococci (FS) density 

and the rate of gastrointestinal (GI) illness. A similar relationship was not observed for total or 

fecal coliforms and GI illness, although densities of fecal coliforms, and not FS, were associated 

with skin symptoms.

Whitewater Channels, UK: A prospective cohort study enrolled whitewater canoeists at two 

slalom courses in the UK, one fed by pristine water from an upland impoundment and one on a 

lowland river receiving biologically treated, but not disinfected, wastewater effluent (Fewtrell et 

al., 1992). A third group of individuals, comprising spectators without water contact, was also 

enrolled. Study participants were interviewed before, immediately after, then 5-7 days following 

water recreation by telephone and, finally, 28 days later by a mailed questionnaire. Water quality 

was measured at the two slalom courses. A total of 516 participants provided telephone followup information. Rates of respiratory symptoms were higher among those exposed to the pristine 

water than among the unexposed group. Those who canoed in the wastewater-impacted course 

were more likely than those in the pristine course to develop GI, respiratory, skin, and flusymptoms. Reported symptom attack rates in the exposed group approached 40%. Water quality 

studies showed comparable levels of FS in the water at the two sites, but enterovirus levels were 

high in the wastewater effluent-dominated water whereas they were below detectable limits in 

the pristine water. This suggests that compared to pathogen measurements, FS densities may be 

poor predictors of health events in similar inland waters settings.

UK Canals and Estuarine River: A prospective cohort study of marathon canoeists was 

conducted at 4 sites: two freshwater canals with little flow, and two sites on an estuarine river 

(Fewtrell et al., 1994). Participants were enrolled at canoe marathons (one at each of the two 

canals) and rowing regattas (one of two sites on the estuarine river). Unexposed individuals 

(spectators) were also enrolled at the sites, and the data acquisition tools employed were similar 

to those employed in Fewtrell et al. (1992). Densities of fecal indicator bacteria were generally 

high but variable among the sites. The geometric means of fecal coliform ranged from 62-4,613 

CFU/100 across the four sites. For FS, the range was 13-528 CFU/100mL. Staphylococci and 

Pseudomonas aeruginosa also measured. Of the 1,086 participants who provided 1-week followup information, rates of illness were not associated with measures of water quality after adjusting 

for potential confounders. However, self-reported water ingestion did increase the likelihood of 

developing GI and skin symptoms. 

UK Whitewater Channel: This prospective cohort study (Lee et al., 1997) was conducted at the 

same site as the previously summarized study by Fewtrell et al. (1992), which is fed by a large 

effluent-impacted lowland river that also receives untreated sewage in storm overflows. A total 

of 473 canoeists and rafters provided health follow-up information 1 week after using the 
2-6 

whitewater course. The study did not include a group of unexposed participants. All follow-up 

was by written, self-administered questionnaire forms. Water quality was evaluated by testing for 

E. coli, clostridia, enterococci, and F+ coliphages. Among the study participants, GI and other 

symptoms were very common (although symptom rates were not summarized, on some trial 

dates more than 20% of subjects developed vomiting and/or diarrhea). The median of the daily 

water quality measures was 769 CFU/100 mL E. coli and 102 CFU/100 mL enterococci. In 

multivariate regression models, only three factors independently predicted rates of GI illness: F+

coliphage densities, self-reported water ingestion, and frequency of use of the whitewater course 

(more frequent use was associated with less frequent health symptoms). 

Inland Nonflowing Waters

Keystone Lake, Oklahoma: Epidemiologic research was conducted at this lake by Dufour and 

colleagues (U.S. EPA, 1984) This inland lake research was part of a larger study also conducted 

at Lake Erie and is described below under “Great Lakes.” 

The Netherlands: Participants in run-bike-run competitions or triathlons (swim-bike-run) in the 

Netherlands were recruited into this prospective cohort study (van Asperen et al., 1998). The 

sites at which the swimming took place are not described in detail in the publication but are 

known to be nonflowing inland waters, some of which were impacted by domestic treated 

sewage effluent (Personal communication, D. Kay). The response rate for individuals who 

received the questionnaire was 62%. Of the 773 run-bike-runners, GI illness rates were about

1% or 2% (depending on the specific definition of GI illness) whereas for the 827 triathletes, 

incidence rates were in the range of 2% to 5%, with overall crude relative risks of 2.0-2.7. Water 

analyses showed a geometric mean of 204 CFU/100 mL E. coli and 16 CFU/100 mL FS. Across 

the seven triathlons, a statistically significant trend was noted for higher rates of illness with 

increasing densities of E. coli and FS. The authors suggested a threshold above which attack 

rates of GI illness increased. For E. coli this was estimated to be 335 CFU/100 mL and 220 

thermotolerant coliforms. Rates of illness were not stratified by site or the type of presumed 

source(s) of fecal contamination. 

German Inland Lakes: Randomized controlled trials using the questionnaires developed by Kay 

et al. (1994) were conducted at five public freshwater bathing sites in Germany (Wiedenmann et 

al., 2006). Three of the sites were urban lakes, one was a rural lake, and one was the blind arm of 

a stream. Sources of fecal contamination potentially impacting the waterbodies included treated 

and untreated municipal sewage, agricultural runoff, and contamination from waterfowl. 

A total of 2,196 participants over 4 years of age were recruited from the local population and 

underwent an initial interview 2 or 3 days before the exposure. On the day of exposure, study 

participants were randomized into equal groups of bathers and non-bathers. Bathers were 

exposed for 10 minutes in designated areas and had to immerse their head at least three times. 

Following their exit from the water, bathers were asked to report whether they had accidentally 

swallowed water. During the exposure period, water samples for microbiological analysis were 

collected at 20-minute intervals and analyzed for fecal indicator organisms. One week following 

the exposure, volunteers were medically examined and interviewed again. Three weeks later, 

study participants completed a written questionnaire. 
WERF Inland Waters Workshop Report 2-7 

Water quality/health risk relationships were observed for the three different definitions of 

gastroenteritis and four fecal indicator organisms including E. coli, enterococci, Clostridium

perfringens, and somatic coliphages. Relative risks for bathing in waters with levels above “no 

observed adverse effect levels” (NOAELs) compared with non-bathing ranged from 1.8 (95% 

confidence interval [CI], 1.2 to 2.6) to 4.6 (95% CI, 2.1 to 10.1), depending on the definition of 

gastroenteritis that was used. Additionally, swallowing water as compared to not swallowing 

water resulted in significantly higher attributable risks above NOAELs. Moreover, swallowing 

water below NOAELs did not result in any significant effect compared with nonbathing, whereas

swallowing water above NOAELs always produced a significant effect. Based on the results of 

this study, the authors concluded that the NOAELs for water quality should be as follows: 100 E. 

coli, 25 enterococci, 10 somatic coliphages, or 10 C. perfringens per 100 mL. Data were not 

analyzed for differences in health outcomes from exposure to animal versus human fecal 

contamination. 

Coastal Freshwater (Great Lakes)

U.S. EPA Freshwater Epidemiologic Studies, 1970s-1980s: Dufour conducted a series of 

epidemiologic studies (U.S. EPA, 1984) to determine whether a model developed for U.S. EPA 

marine studies (U.S. EPA, 1983) to predict health effects based on marine water quality could 

also apply to freshwater. This study also included identifying a water quality indicator that best 

describes the relationship between health effects and freshwater quality. The studies were 

conducted at two U.S. locations, Lake Erie in Erie, Pennsylvania (29,976 participants) and 

Keystone Lake in Tulsa, Oklahoma (16,363 participants). Within each location, beaches of 

varying water quality were selected for recruiting study participants and measuring water quality. 

The Lake Erie studies were conducted in 1979, 1980, and 1982 on beaches considered to have 

good or excellent microbial water quality. One site was located approximately three-quarters of a 

mile northwest of a sewage outfall for the City of Erie, PA. The Keystone Lake studies were 

conducted in the summers of 1979 and 1980, and the beaches demonstrated variable water 

quality for bacteria. The two beach sites at Keystone Lake were located 3 and 5 miles from an 

outfall for a wastewater treatment facility. In 1979, the treatment plant released an average of 

120,000 gallons of unchlorinated sewage per day into the lake. In 1980, this practice was 

discontinued, and sewage passed through a settling lagoon, an aeration basin, and was 

chlorinated before being released into the lake.

Water samples were tested for E. coli and enterococci. Fecal coliforms were also monitored for 2 

years during the Keystone Lake studies and in 2 years of the Lake Erie studies. A regression 

analysis determined whether there was a direct relationship between swimming-associated GI

illness and microbial water quality. A correlation analysis determined which water quality 

indicator showed the strongest relationship to swimming-related illness. 

In the Lake Erie studies, symptom rates for swimmers were generally higher than nonswimmers 

in all categories; however, most symptoms were not statistically significant. Statistically 

significant differences between swimmers and nonswimmers were found in symptoms related to 

enteric diseases and tended to occur at the beach with poorer water quality. In the Keystone Lake 

study, symptoms for enteric diseases tended to be higher in swimmers than nonswimmers. In 

1979, there was one other group of symptoms (fever, headaches lasting greater than 3 hours, and 

backache) that showed significant differences between swimmers and nonswimmers. In 1980, 
2-8 

statistical differences between swimmers and nonswimmers were found at one or both sampling 

locations with symptoms for GI, respiratory, and other illnesses. Unlike the U.S. EPA study of 

marine water sites, these freshwater studies found both E. coli and enterococci to be predictors of 

health events attributable to water recreation.

Lake Ontario and Other Ontario Beaches: Seyfried et al. (1985a; 1985b) conducted a prospective 

cohort study at 10 beaches in Ontario, Canada. The papers do not specifically state which or how 

many of the beaches were on Lake Ontario and how many were on inland lakes. Sources of 

possible fecal contamination were not specified, but a doctoral dissertation by Nancy Lightfoot 

mentioned wastewater effluents from Toronto reaching some of these locations via the Humber 

River. A total of 3,967 swimmers and 2,105 nonswimmers provided follow-up health 

information. Geometric mean densities of FC and FS were 75.9 and 42.8 MPN/100mL, 

respectively (densities of these and other microbes in sediment were ~10 fold higher). Rates of 

incident illness among nonswimmers were below 4/100 for all age groups other than those under 

5 years (rate 6.1/100); rates of illness were two- to threefold higher for swimmers. Among 

swimmers, illness rates were similar regardless of head immersion status. Staphylococci 

densities in water samples were more strongly related to health risks than other microbes, 

suggesting that bathers themselves may have been sources of pathogens. 

U.S. EPA NEEAR Study, Lake Michigan and Lake Erie: Wade et al. (2006; 2008) conducted a 

prospective cohort study at four Great Lakes beaches as part of the National Epidemiological and 

Environmental Assessment of Recreational water (NEEAR) study. The research was conducted 

at Lake Michigan beaches in Indiana and Michigan, and on Lake Erie in Ohio. The beaches were 

variably impacted by effluent from wastewater treatment plants. Beachgoers were asked for 

information on demographics, swimming and other beach activities, and numerous non-waterrelated risk factors for GI illness. Following a 10- to 12-day period, a telephone interview was 

conducted to gather information about health symptoms experienced since the beach visit, as 

well as other water-related activities, contact with animals, and consumption of high-risk foods. 

Water samples were also collected three times a day on each study day and analyzed for 

Bacteroides spp. and enterococci. The water samples were analyzed using Q-PCR, a method 

that, unlike culture-based approaches, can produce results the same day that the water is 

sampled. Respiratory and GI illness and ear, eye, and skin rash symptoms were evaluated. 

Swimmers at both beaches had a higher incidence of GI illness compared to nonswimmers. A 

statistically significant relationship was observed between increased rate of GI illness and 

enterococci at the Lake Michigan beach, whereas a positive trend for enterococci at the Lake 

Erie beach was noted. The association between enterococci and increased risk of GI illness was 

significant when results for the two beaches were combined. In terms of Bacteroides, a positive 

trend was observed at the Lake Erie beach, but no trend was observed at the Lake Michigan 

beach. Archived filters from the NEEAR study freshwater sites will be re-analyzed by the U.S. 

EPA as part of the Critical Path Science Plan using a revised Bacteroides Q-PCR method. This 

will inform the selection of a rapid water testing method for health protection purposes. In 

addition, the association between enterococci and GI illness strengthened with increasing 

exposure. Another finding is that children may be more susceptible to GI illness than adults for a 

given increase in enterococci measures. Compared to the culture-based measures of quality, the 

Q-PCR measures of enterococci were stronger predictors of GI illness. 
WERF Inland Waters Workshop Report 2-9 

Marine Coastal Waters

U.S. EPA Marine Studies: In the late 1970s, Cabelli et al. (U.S. EPA, 1983) began 

epidemiologic studies in the following four locations: Coney Island and Rockaway beaches in 

New York City; Lake Pontchartrain in New Orleans, Louisiana; and Boston Harbor in Boston, 

Massachusetts. The studies consisted of two interviews, one at the beach where individuals were 

recruited and a second phone interview 7 to 10 days later. Beach interviews occurred only on 

weekends and were limited to individuals who had swum on one or two weekend days. Midweek 

swimmers were excluded from the study. These initial beach interviews occurred on days with 

minimal tidal effects and during time periods of peak beach usage (from 11 am to 5 pm). A total 

of 26,676 participants were interviewed. Swimmers were defined as individuals whose upper 

bodies were exposed to water. Nonswimmers who attended the same beach were the control 

population for the study. Water samples were collected at three locations and assayed for E. coli

and enterococci. Results were analyzed using regression analysis.

In the New York study, two beaches were sampled. The Coney Island beach was considered 

“barely acceptable” in terms of pollution levels, whereas the Rockaways beach was deemed 

“relatively unpolluted.” The author found statistically significant differences in the rate of GI 

symptoms in swimmers compared to nonswimmers at the Coney Island, but not Rockaways 

beach. The author also found a higher rate of respiratory symptoms in swimmers at Rockaways 

beach. The symptom rate for GI illness for swimmers at Coney Island was 10 out of 1,000 

swimmers compared to 2 out of 1,000 swimmers for Rockaways beach. The author determined 

that measurable health effects could occur on beaches that met existing recreational guidelines 

and that enterococci densities provided the best correlation with health effects.

The Lake Pontchartrain study was conducted in a brackish area with limited tidal activity. The 

authors found statistically different rates of illness for swimmers versus nonswimmers for 

symptoms of vomiting, diarrhea, stomachache, earache, and skin irritations. In general, the GI 

symptom rates were higher in children than adults. The authors also found that enterococci were

a better indicator of illness than E. coli. Further, stormwater runoff appeared to be less harmful 

than sewage sources. These results suggest that the source of fecal indicator bacteria may modify 

the relationship between densities of those bacteria and health effects attributable to water 

recreation.

The Boston Harbor study took place on two beaches in 1978 and attempted to confirm the 

observation that significant health effects can be observed when there are low indicator densities. 

The author did not find statistically different illness in GI symptoms between swimmers and 

nonswimmers at that site. Overall, however, this series of marine studies found that there was an 

increased risk in GI illness from swimming in waters in increasingly polluted seawater. 

Enterococci also appeared to be a better indicator for illness associated with swimming in 

seawater than E. coli or other indicators. 

UK Randomized Controlled Trials Studies: In the UK, Kay et al. conducted randomized trials at 

four different locations during the summers of 1989 through 1992 (Kay et al., 1994; Fleisher et 

al., 1996). The study population consisted of 1,216 adults that were recruited from populations 

near the study locations. Study recruits participated in an extensive interview and medical 

examination no more than 2 days prior to the day of exposure. Researchers gathered data on a 
2-10 

number of potential confounding factors (e.g., age, sex, general health, illness in previous three 

weeks, medications taken, water contact activities). 

Study participants were randomized as either bathers (548 participants) or non-bathers (668 

participants) who were unaware of their status until they arrived at the study location beach. 

Bathers entered into a defined area in the water, remained in the water for at least 10 minutes, 

and completely immersed their heads in the water at least three times. Non-bathers remained on 

the beach in a designated area. One week following the exposure period, study participants were 

medically examined and interviewed extensively again for data on their health, diet, water 

contact activity, and other potential risk factors. Lastly, study participants were mailed a 

questionnaire to fill out with any other symptoms of illness and exposure to recreational water.

In addition, the water quality of the bathing area was sampled at 30-minute intervals during the 

exposure period at various designated locations (sampled every 20 m at surf, 1 m deep, 1.3 to 

1.4 m deep, and 30 cm below the surface). These water samples were analyzed via standard 

methods for the following indicators: total and fecal coliforms, FS, and P. aeruginosa. Total 

staphylococci were also counted at three of the study sites. The sampling results were assigned to 

each individual bather within 15 minutes of exposure and within a maximum of 10 m of the 

place of exposure. 

The results indicated that of the indicators measured only FS demonstrated a statistically 

significant increase in rates of gastroenteritis with increasing microbe density. Bathers exposed 

to more than 32 FS/100 mL demonstrated a significant relationship with the risk of 

gastroenteritis and this relationship was independent of non-water-related predictors of 

gastroenteritis.

Based on their results, the authors concluded that, although none of the other microbiological 

indicators illustrated a significant relationship between measured concentrations and occurrence 

of gastroenteritis in the marine waters studied, the relationship between FS concentration 

measured at chest depth and gastroenteritis is robust. The authors suggested that whatever causes 

gastroenteritis might co-partition in seawater with FS. The authors’ findings also suggest that 

coliforms seem to have little value as indicators of gastroenteritis risk from sewage pollution of 

marine coastal waters and that FS concentrations are a better microbiological indicator.

New Zealand: This prospective cohort study enrolled a total of 5,533 participants (bathers and 

non-bathers), though usable follow-up information was available for only 3,887.(McBride et al., 

1998). Beaches were categorized as “minimal impact” (Rabbit Island and Wenderholm), “rural” 

(with animal impact: Ohope, Spencerville) and “oxidation pond” (human impacted: Omanu, 

Paraparumu, and Raglan). Indicator densities were low at all sites; the 75th percentile of

enterococci measures was 13 CFU/100 mL. Absolute risks were not presented by source (i.e., 

human vs. animal). For nonswimmers, there was an illness rate of about 25 per 1,000. Relative 

risks of respiratory illness were higher among swimmers, particularly among those who swam 

more than 30 minutes. GI illness rates among swimmers were, in general, not associated with 

measures of water quality. Bathers with head immersion (“swimmers”) had higher rates of 

respiratory symptoms than those who had water contact but no head immersion (“paddlers”). The 

authors concluded that rates of illness at the human- and animal-impacted beaches were similar 

to one another and higher than the minimal-impact beaches. The crude rates of illness by beach 
WERF Inland Waters Workshop Report 2-11

suggest higher rates of illness at the animal-impacted beaches. However, after adjustment for 

participant age and other variables, the relationships between enterococci concentration and rates 

of respiratory symptoms were similar for the human and animal impacted beaches. Relative to 

unexposed beachgoers, the risk of respiratory symptoms when exposure occurred at the highest 

quartile of enterococci density (greater than 12 CFU/100 mL) were 3.17 (1.81-5.55) and 2.97 

(1.33-6.60) at the human- and animal-impacted beaches, respectively. The authors state that 

similar observations were noted for other health endpoints. The very low indicator densities 

across all study beaches limit the degree to which these findings can be generalized to other 

settings. 

Hong Kong: This prospective cohort study was conducted at beaches that were polluted by 

submarine sewage outfalls, livestock waste (mainly pig), and urban runoff in differing amounts 

(Cheung et al., 1990). Two animal impacted sites, six human waste and storm water-impacted 

beaches, and one beach impacted by both a sewage outfall and a pig source were studied. 

Densities of nine indicators and pathogens were evaluated at each beach. The two animal 

impacted beaches were quite different from one another, with geometric mean FS densities of 43 

and 286/100 mL, while densities at the human-impacted beaches were typically between 40 and 

140 CFU/100 mL. A total of 18,741 eligible participants provided telephone follow-up 

information (77% swimmers, 23% nonswimmer). Unlike the U.S. and UK studies, E. coli and 

fecal coliform densities were better correlated with GI and total illness rates than were 

enterococci densities.

The two animal impacted sites appear to have somewhat lower rates of GI illness attributable to 

swimming (0/1,000 and 2.8/1,000 at the beaches with lower and higher FS densities, 

respectively), compared to an overall swimming-attributable GI illness rate of 3.2/1,000. The 

focus of this research was not the water quality/health risk relationship as a function of pollutant 

source; statistical testing was not performed to determine if the illness rates at the animalimpacted beaches were different than at the other beaches. 

Santa Monica, California: This prospective cohort study conducted at three beaches in Santa 

Monica, CA, evaluated proximity to urban runoff outfalls as a predictor of illness among 

swimmers (Haile et al., 1999). Interviews were conducted 9-14 days after exposure, and a total 

of 10,459 people provided follow-up information that could be linked to measures of water 

quality. Of interest was the impact of distance from storm drain on health outcomes. Location of 

recreation was categorized as 0, 1-50, 51-400, and 400+ yards from storm drains. In this study, 

stormwater included dry weather (relatively constant) runoff into storm drains (likely due to 

lawn watering and nuisance flow sources). Except in the immediate vicinity of the outfall, there 

did not appear to be a difference in rates of symptoms as a function of distance from the storm 

drains. Among study participants who swam at the storm drains locations, fever, chills, ear 

discharge, cough and phlegm, and a complex of respiratory symptoms were all significantly 

more frequent than among those who swam > 400 yards from the drains. Rates of nausea and 

diarrhea were significantly lower at 1-50 meters from the drains compared to > 400 yards; 

otherwise GI symptoms were not related to distance from the drains. Because a nonswimming 

reference groups was not part of the study design, rates of illness among those far from the storm 

drains are difficult to put into a broader context. On days with high total coliform counts, an 

interesting relationship was observed with higher rates of GI symptoms with decreasing ratios of 

fecal to total coliforms. About 10% of swimmers were in waters that tested positive for enteric 
2-12 

viruses. Although point estimates of relative risk suggested a relationship of various symptoms 

with detection of enteric viruses, none of these associations reached statistical significance. 

Given the presence of human enteric viruses, the sources must have included a human pathogen 

source, perhaps leaking sanitary sewers. Thus, the relevant pathogen sources for this study site 

are likely a mix of human, urban non-sanitary surface water drainage, and potentially avian 

sources.

Mission Bay, California

Meta-Analyses and Review Articles

: This prospective cohort study of swimmers and nonswimmers was 

conducted at beaches in Mission Bay, California (Colford et al., 2007). Human sources of fecal 

pollution were thought to account for < 10% of the total; birds were thought to be the 

predominant source of fecal pollution overall. A total of 8,751 study participants provided 

telephone follow-up information (71% of the total). Water quality measures were made for a 

variety of fecal indicator bacteria and pathogenic viruses and coliphages. Rapid molecular 

methods (i.e., Q-PCR) were used to measure enterococci, Bacteroides, adenovirus 40 and 41, 

and norovirus. Geometric means (per 100 mL) of water quality measures were 29 enterococci 

(chromogenic method), 65 Enterococcus spp. (Q-PCR), and 25 fecal coliforms. Higher rates of 

some symptoms were noted among swimmers than nonswimmers (diarrhea: adjusted odds ratio 

of 1.4; skin rash: 2.3). There is a suggestion that among swimmers, swallowing water further 

increased risk of illness. Levels of enterococci, fecal coliforms, and total coliforms were not 

associated with health outcomes. Male-specific coliphage measures were associated with fever

and symptoms of GI illness. These associations reached statistical significance despite the fact 

that gastrointestinal illness only occurred in relation to eight positive male-specific coliphage 

tests. The absence of a quantitative relationship between measures of water quality (other than 

coliphage) and health risk observed in this publication appears to be in contrast to the findings of 

other epidemiologic studies set in marine waters. One possible explanation for this is a different 

water quality/health risk association for avian, as opposed to human sources, of fecal 

contamination. Another possible explanation is that subtle increases in health risk could not be 

detected given the relatively low densities of indicator bacteria observed in this study. 

Three major reviews have been conducted to evaluate the health risks of water recreation and to 

summarize indicator-pathogen relationships. Prüss (1998) concluded that sufficient basis existed 

for setting health-based guidelines for recreational water based on indicator bacteria, specifically 

enterococci for marine waters, and both enterococci and E. coli for fresh waters. Several years 

later, Zmirou et al. (2003) conducted a meta-analysis and also concluded that indicator 

organisms are associated with health risks. In addition, they concluded that risks were associated 

with lower concentrations of enterococci in marine waters compared to freshwaters. A second 

meta-analysis published that year also confirmed the association between indicator organisms 

and health risks (Wade et al., 2003). This study concluded that enterococci are the most 

appropriate indicator for marine waters whereas E. coli was the most appropriate indicator for 

freshwater. These review articles and meta-analyses did not seek to define indicator-pathogen 

relationships by source type (human, treated; human, disinfected; agricultural animal; urban 

runoff; wildlife). 

2.2.3 Water Matrix Group 

The ambient water quality criteria being developed for the Great Lakes are being 

evaluated for their applicability to inland waters. Inland waters include quiescent (i.e., 
WERF Inland Waters Workshop Report 2-13

nonflowing) and flowing waters, including lakes, streams, and rivers. Various modeling 

approaches were discussed by the group. 

Two classes of models – regression and mechanistic – are used to predict or forecast 

concentrations of indicator organisms and pathogens in environmental waters (Boehm et al., 

2008; Francy et al., 2006; Palmer et al., 2008). Models that estimate indicator or pathogen 

concentrations at points of recreational activity can also be used to provide source concentrations 

for use in quantitative microbial risk assessments (QMRA) (Roser et al., 2006; Roser et al., 

2007). 

Regression Models 

Regression models use a training data set consisting of the target microorganism 

concentration as the dependent variable and environmental factors (such as turbidity, rainfall, 

and so forth) as the independent variables (e.g., Nevers and Whitman, 2005; Hou et al., 2006). A 

multiple linear regression, partial-least squares regression or other empirical, statistical technique 

of relating dependent and independent variables is used to create an empirical relationship 

between the independent variables that predict the dependent variable. Regression models can be 

used at beaches where the sources of fecal contamination are unknown and of nonpoint origins; 

this is a common situation at many beaches.

Regression models are validated by evaluating responses during an independent year. The 

percentages of correct responses and model specificities and sensitivities are compared to those 

associated with the current method to assess recreational water quality (the previous day’s 

bacterial indicator concentrations determined using standard culture methods). In many cases, 

models perform better than the current sampling of indicators. 

Regression models have been used by beach managers to aid in public notification of 

beach water quality (issuance of closures and/or advisories). The regression models have been 

embraced by beach managers in the Great Lakes region. Regression models are used to issue 

beach advisories and closings at three locations, all within the Great Lakes – SwimCast in Lake 

County, Illinois, Project SAFE in northwest Indiana, and the Ohio Nowcast. Less work has been 

undertaken on the testing and implementation of models for public notification at marine beaches 

in the United States. Such work has been motivated by successful programs in Australia and 

Scotland. Regression models have not been used for other CWA purposes (303d listing, NPDES 

permitting, and so forth). 

The U.S. EPA created Virtual Beach (Frick et al., 2008), a software program designed to 

help beach managers develop multiple-linear regression models for local beaches. Virtual Beach 

has been tested at a handful of beaches; additional testing and refinement of this tool is under 

way. 

A guidance document that includes the steps to developing predictive models using 

regression techniques is available online from the U.S. Geological Survey (USGS) (Francy and 

Darner, 2006). Considerable information on this topic is also available in the Airlie Workshop 

report (U.S. EPA, 2007b). 
2-14 

Regression models are not generally used to assess fate and transport in aquatic media; 

however, they may provide insights into potential sources of fecal contamination at beaches. In 

some instances, because of the error associated with the prediction, regression models are not 

used to predict bacterial indicator values. Rather, they are used to predict the probability that the 

applicable single-sample bathing-water standard is exceeded, similar to a weather forecast. 

Models have generally been trained with a single FIB sample for each day, but also could 

be trained and validated against more intensive datasets to assess if FIB concentrations (Francy 

et al., 2006; Boehm et al., 2008) over the course of a day could be predicted, potentially 

providing a more accurate assessment for beach notifications. Regression models in use in the 

Great Lakes are beach specific, although research has shown that larger-scale models can be 

used at multiple beaches proximate in location with similar attributes and sources. 

Mechanistic Models 

Mechanistic models refer to a broad class of models that may include simple box models 

where gross assumptions about mixing, residence time, sources, and sinks are made, to complex 

models that start with the equations of motion and continuity and use numerical methods to 

estimate pathogen concentrations (Roser et al., 2007a). There are watershed models that predict 

the runoff magnitude and quality from watersheds (Dorner et al., 2007; Ferguson et al., 2007a). 

There are stream, river, lake, and coastal models that predict concentrations of microbes once 

they have entered a waterbody (e.g., HSFP, SWAT, ROMS, and SUNTANS). Models can be 

created for any system where an inventory or mass balance can be made on the target of interest. 

Mechanistic models are currently not used in the regulatory arena with the possible 

exception of TMDL implementation. The general view of the matrix group was that mechanistic 

models are currently not able to estimate bacterial indicator levels with the accuracy needed for 

current criteria at the present time. However, in the future, when the fundamental processes 

governing microbial fate and transport are better known, mechanistic models could be more 

widely applied for this purpose. 

The types of parameters required for a mechanistic model depends on the type of model 

one wishes to create. These will include parameters describing dispersion, advection, die-off 

rates, deposition rates, adsorption rates, settling rates, partitioning coefficients, transport, growth 

rates, grazing rates, pathogen concentrations, and so on. For watershed models, information on 

the soil type, land use, fecal scat presence, permeability of soils and sediments, slope of land, 

moisture content of soils, etc. are needed. Key to developing a mechanistic model is a conceptual 

model of the various processes affecting fate and transport of the target microbe. It is also 

important to quantify or accurately estimate boundary conditions. 

Mechanistic models are useful for determining how a change in land use, best 

management practice, or presence of particular sources might change pathogen or indicator 

concentrations in a system. Mechanistic models can be used to test specific hypotheses or to test 

the general understanding of a dynamic system. This is why they have been used in TMDLs. 

However, in general, model output is very difficult to fit to measurements in the field and 

agreement is generally poor, particularly for pathogens. The output from mechanistic models 

could be coupled for use in regression models. For example, current direction values from a 

mechanistic model are used in some models as part of Project SAFE.
WERF Inland Waters Workshop Report 2-15

The matrix group indicated that mechanistic modeling is important as a means for testing 

our understanding of the fate and transport of indicators/pathogens and revealing knowledge 

gaps. Once the fate and transport processes of indicator and pathogenic microbes are better 

known, these models may be calibrated sufficiently for issuing beach closures and water quality 

advisories. 

Quantitative Microbial Risk Assessment 

Quantitative microbial risk assessment (QMRA) is a health-risk modeling approach that 

translates microbial exposures into infection or illness risk estimates. Alternatively QMRA can 

be used to take a benchmark level of infection/illness and work backwards to provide safe target 

concentrations at points of exposure or further upstream to advise best management practices. 

The dose received by individuals is derived from estimates of the exposure volume and 

concentration of selected pathogen(s) (or indicator). The volume of water ingested can be 

estimated for different activities (e.g., swimmer v. drinking v. kayaking). Once a dose is 

determined, then a risk of infection or illness can be derived by applying published doseresponse models for specific pathogens, which are derived from either human feeding trials or 

outbreak investigations (Haas et al., 1999). 

Estimations of key model parameters are generally described as probability density 

functions (PDFs) (i.e., distributions to account for the stochastic nature of the parameter) to help 

account for inherent variability as well as various sampling, analytical, and modeling 

uncertainties. The characterized risk is best described with variability and uncertainty separated 

where possible. This characterized risk can then be compared to “tolerable risk” or a site 

benchmark for the recreational water (e.g., eight GI illnesses per 1,000 bathers). Regression or 

mechanistic models can be linked to a QMRA model by providing relevant concentrations in the 

exposed media. These predicted concentrations can then be used in conjunction with volume 

ingested, (e.g., Dufour et al., 2006) to estimate a dose. 

An initial screening-level risk assessment for a site may start by only using point 

estimates to describe model parameters (e.g., Ashbolt et al., 1997). Then, to reduce uncertainties 

in the risk estimate, more complexity is built into a QMRA model using PDFs to better represent 

a specific site, in what is called a static model. A more complex approach known as dynamic 

QMRA takes into account immunity and secondary infections to the broader community (Soller 

et al., 2003; Eisenberg et al., 2004; Soller and Eisenberg, 2008). 

QMRA can be useful for a number of purposes. First, it can be used to estimate 

hypothetical risks under different scenarios of pathogen/indicator sources and recreational 

activities and exposure routes, which is particularly useful to compare various management 

approaches. Second, QMRA can be used to work backward to look at the acceptable 

concentrations of specific pathogens for a particular “acceptable risk” benchmark, generally or 

for a specific site. Ideally QMRA should be anchored to recreational epidemiologic studies to 

ground the absolute risk estimates with observable data. 

2.2.4 Sources Group

The source of fecal contamination and associated indicator organisms in environmental 

waters has potentially far-reaching implications for the health of recreational water users and our
2-16 

ability to establish rational and protective criteria for water quality. The suite of human 

infectious pathogens that can potentially be introduced into water is somewhat constrained by 

host species or group, and this repertoire determines the type and severity of diseases that the 

pathogens may cause in humans. 

The frequency of host infection and the shedding rate of pathogens increase the 

likelihood that humans will be infected by waterborne transmission. Some of the pathogenrelated characteristics of certain fecal sources are known or can be inferred, e.g., human sewage 

has a high probability of containing pathogenic human viruses, whereas fecal waste from animals 

is less likely to carry such human infectious viruses. Conversely, some of the risks posed by 

pathogens stemming from various potential fecal sources that could affect a recreational 

waterbody are characterized by little or no data, making an accurate assessment of the risk of 

human illness nearly impossible. For example, we know very little about the frequency of 

various pathogens in wild animal feces, the probability that their pathogens would reach the 

water, and particularly the extent to which animal-associated genotypes of known zoonotic 

pathogens such as Cryptosporidium spp. can infect humans. 

Human health risk posed by exposure to recreational waters is routinely assessed by 

measuring FIB concentrations. FIB are used as surrogates for waterborne pathogens because of 

the difficulty and expense posed by measuring the gamut of possible pathogens that could be 

present in a given waterbody. The dominant FIB used to assess recreational/ambient water 

quality in the United States is fecal coliforms, E. coli (a member of the fecal coliform group) and 

enterococci. Each of these FIB groups is present at fairly high, but frequently differing, 

concentrations in the feces of humans and most animals. Our knowledge of the quantitative 

relationship between FIB and the pathogens whose presence they are intended to predict ranges 

from acceptable in well-studied sources like human sewage influent (raw or unprocessed 

sewage) to incomplete for important domestic and agricultural animals like dogs, cats, cattle, 

pigs, and poultry, to nearly nonexistent for most wild animals. Furthermore, the relationship 

between the persistence, decay rates, and potential for growth of FIB under environmental 

conditions compared to pathogens from various host types that may be present in fecal sources is 

largely unexplored and represents a major gap in knowledge that hinders efforts to accurately 

characterize human health risks posed by recreational water use. 

Human and animal sources of fecal material exist in most watersheds and are, therefore, 

potential sources of FIB and pathogens in coastal, Great Lakes, and inland recreational waters. 

Knowledge of the relative contribution to fecal loading by various sources is an initial step to 

estimating human health risk and can be estimated using the tools of the emerging field known as 

microbial source tracking (MST) and land use surveys. Although emerging methodologies and 

technologies are improving the ability to parse the probable sources that impact a given 

waterbody, these allocations represent a rough estimate. It is generally assumed that waterbodies 

in urban watersheds receive some level of human contamination, whereas domestic animals and 

some wild animals such as birds may also contribute. Stormwater contains a heterogeneous array 

of sources carried from the watershed. Conversely, fecal sources from rural watersheds may be 

dominated by wild animals and birds or by livestock if there is agricultural activity. The mass of 

fecal material produced by livestock each year in the United States is estimated to be 

substantially greater than that produced by the human population and the contribution from 

wildlife animals is not known. Because each of these sources is expected to contribute different 
WERF Inland Waters Workshop Report 2-17

combinations of pathogens, the relative proportion of source loading and the quantity of fecal 

loading contribute to the aggregate health risk experienced by recreational water users.

The water quality of inland waters throughout the United States is influenced by some 

factors that differ from the urban coastal waters or Great Lakes beaches at which epidemiologic

investigations were conducted by the U.S. EPA. One example is the effect of tropical climate on 

regrowth of FIB in the environment (Fujioka and Byappanahalli, 2003). In general, rural inland 

waters are more likely to be affected by substantial wild animal populations (other than birds) 

and by livestock such as cattle, pigs, or poultry. Although POTW outfalls or combined sewer 

overflows (CSOs) represent discrete point sources for urban environments, animal waste can be 

added to rural inland water in a diffuse manner, (i.e., nonpoint sources [NPS]) and can be spread 

across wide areas of a watershed. Wastewater treatment in many suburban or rural inland 

watersheds is often accomplished by individual onsite wastewater treatment systems (single 

family) or package plants, which have high variability in treatment efficacy and rate of failure. 

Although these wastewater treatment systems are not often treating large numbers of people, 

after extreme rainfall events runoff can be a major concern and difficult to mitigate. Also, 

microbial transport in streams and rivers is a predominantly one-way, flow-driven phenomenon 

that moves contaminants to downstream locations rather than the wave and current-driven 

activity characteristic of coastal and Great Lakes waters. This has implications for recreational 

water users because downstream water quality is affected by the cumulative risk from 

microorganisms that are resistant to environmental inactivation.

A variety of tools are being developed to estimate pathogen risks for recreational water 

users including QMRA and a range of mathematical modeling approaches. (See previous 

section.) However, a lack of reliable, quantitative data on source loads and fecal 

source/FIB/pathogen relationships limits the potential effectiveness of these tools and reduce the 

reliability of their outputs. Water quality criteria developed for all waters will need to include a 

better understanding than we currently have of the effect of fecal sources on the 

indicator/pathogen/risk relationship to ensure that they are appropriate for both coastal and 

inland waters.

2.2.5 Implementation Realities Group 

When U.S. EPA issues new or revised water quality criteria for primary contact 

recreational uses of waters in 2012, there is an expectation that states will incorporate these 

criteria into their water quality standards and that these criteria will, once adopted, serve as 

regulatory standards for a variety of CWA purposes. That is, these criteria will be used by Great 

Lakes and coastal states (and territories) as the basis for beach advisory and closing decisions, as 

water quality based effluent limitations in NPDES permits and used as the basis for listing waters 

as impaired as well as serve as the target or goal for TMDLs. Because of the great importance 

that EPA’s water quality criteria play in the implementation of many CWA programs, U.S. EPA 

and the states need to understand, preferably well in advance of adoption, implementation issues 

that will likely arise from new or revised criteria and how to address them. This will be 

particularly important if U.S. EPA recommends innovative AWQC or criteria that are very 

different from the current ones. When states understand the science underlying newly 

recommended criteria, view the newly recommended criteria as benefiting public health, and are 

ready to address major implementation issues, it is thought that states (and territories) will 

readily adopt the newly recommended criteria into their water quality standards. 
2-18 

For purposes of the Inland Water Workshop, it was assumed that the U.S. EPA will issue 

new recreational water quality criteria in 2012 for all freshwaters (including inland flowing 

freshwaters) based primarily on indicators of pathogens to illness relationships. It was assumed 

that these indicator-to-illness relationships will have been established in epidemiology studies 

conducted at marine coastal beaches and in the Great Lakes, and that Q-PCR may be 

recommended as the preferred analytical method at least for beach monitoring and notification 

purposes. The implementation realities group explored for inland waters, particularly flowing 

freshwaters, the likely implementation issues that may arise, the possible flexibilities that may 

exist within existing regulations to address these issues, and the science or research that would 

facilitate addressing these issues both in the near term (over the ensuing 18 months) and the 

longer term. 

Many miles of inland rivers and streams are designated for primary contact recreational 

use in the United States. The state of Kansas, for example, has more than 34,000 miles of 

flowing waters, meaning that this one state alone more beach miles than those for the Great 

Lakes and coastal areas of the United States combined. Thus, the impact of new criteria on the 

operations of state water quality programs and the implementation realities faced by municipal 

wastewater utilities and state and local health departments could be dramatic. 

One major issue for state and regulatory programs that are already strained is that many 

of their inland waters are currently listed as impaired for bacteria, and it is unknown whether 

assessment against a new criteria would result in an increase or decrease in the number of waters 

listed as impaired. In some areas, there is already a realization that meeting existing criteria may 

not be attainable. In these circumstances, it is highly likely that site-specific risk assessments 

would be in order so that scientifically defensible alternative criteria could be applied or use 

attainability analysis (UAA) might be undertaken to determine what uses (and associated 

criteria) are the highest attainable uses/criteria. 

If the recreational water criteria move away from traditional culture methodologies, 

utility, state, and territorial laboratories would be significantly impacted as well. In most, if not 

all, of these laboratories, personnel would have a learning curve related to implementation of 

molecular methodologies, some laboratories could have significant infrastructure-related changes 

that would be necessary and most would have to purchase equipment such as biological cabinets, 

freezers, centrifuges, micro-pipets, and thermocyclers. Prior to switching to any molecular-based 

method, research must be completed that will develop translation factors between molecularbased and culture methods. Without an understanding of this relationship, the connection to 

decades of existing culture-based data would be lost. Finally, utility, state, and territorial 

laboratories performing analytical work for other program areas such as the Safe Drinking Water 

Act or assessment of disinfection efficacy, traditional culture methods would still be required. 

Simply supplanting existing culture-based laboratory with a molecular-based laboratory may not 

always be an option. Because molecular-based methodologies would be in addition to the 

traditional culture methodologies, operating budgets would be significantly affected. 

Another major consideration is that prior to implementation of any new assessment 

approach, standardization and approval of methods by U.S. EPA is required for reporting 

compliance data. Any assessment method must be proven to be robust enough to provide 
WERF Inland Waters Workshop Report 2-19 

reproducible results in laboratories across the country and be applicable in a wide range of water 

matrices. Culture methods approved by U.S. EPA historically have been shown to meet these 

requirements through round-robin trials, proficiency demonstrations through state or national 

certification programs, and optimization of methods to account for differences in water matrices. 

Ultimately, implementation of new criteria may highlight the need for states to have 

flexibility in the implementation of new criteria while ensuring state water quality program 

resources continue to be focused on achieving the greatest public health benefits for the 

resources available. It will be important to provide the analytical community sufficient lead time 

to acquire funding, laboratory space, and equipment if molecular methods are required. In the 

case of government-run laboratories, legislative appropriation may be forthcoming. Thus, some 

thought should be given as to implementation expectations if the buildup of analytical capacity 

lags behind the criteria.
2-20 
WERF Inland Waters Workshop Report 3-1 

CHAPTER 3.0

STATE OF THE SCIENCE

3.1 Indicators and Pathogens Group

The indicators and pathogens group believe that sufficient microbial and health effects 

data have been collected from the Great Lakes. However, it is believed that insufficient data have 

been collected from inland waters throughout the United States. The basic question is whether 

the data and standards using FIB such as E. coli and enterococci collected in the Great Lakes

can be directly applied to inland flowing waters without conducting additional studies at inland 

water sites. 

3.1.1 Water Quality Differences in Inland Compared to Coastal Waters 

The first step to address the question posed above is to characterize and compare the 

factors that affect inland and Great Lakes water quality. If the same factors affect both the Great 

Lakes and inland waters, then it might be justified to directly apply water quality standards 

established for Great Lakes to inland waters. However, if different factors affect water quality of 

inland waters as compared to the Great Lakes, they should be considered different than the Great 

Lakes; therefore, separate epidemiologic studies should be conducted to develop recreational 

water quality standards appropriate for inland waters. Inland waters include all noncoastal rivers, 

lakes, and wetlands. 

The Great Lakes are the largest lakes in the United States and are sometimes called 

inland seas because their vast area, deep offshore waters, and large volumes of waters are 

comparable to those of marine coastal areas. Like many marine beaches in temperate areas in the 

United States, the recreational beaches in the Great Lakes are located along the shorelines and 

used for swimming only during the warmer months. Land-based discharges into the Great Lakes 

from streams and storm drain sites occur but can be identified and their impacts on nearby 

coastal water quality have been reported (Byappanahalli et al., 2003a; Nevers and Whitman, 

2005; Whitman et al., 1999). The fate of microbial pollutants that enter the Great Lakes is 

controlled by factors dictated by Great Lakes conditions (Liu et al., 2006; Nevers and Whitman, 

2008). In this regard, land-based pollutants entering the Great Lakes are initially diluted with 

coastal waters and transported to deeper offshore sites where the heavier pollutants settle. the 

Great Lakes are exposed to full sunlight, the microbial solar inactivating may occur (Whitman 

and Nevers, 2004). The Great Lakes have been reported to be contaminated by fecal bacteria by 

nontraditional sources such as birds, algae, and sand (Fogarty et al., 2003; Haack et al., 2003; 

Whitman and Nevers, 2003; Whitman et al., 2003). The open sandy beach areas of Lake 

Michigan become highly populated with birds (e.g., gulls), which defecate onto the sand as well 

as in coastal waters (Whitman and Nevers, 2003). Summer conditions greatly stimulate the 

growth of algal populations (Cladophora spp.) located on the bottom of the Great Lakes. The 

excess algal growth detaches and accumulates as massive mats in coastal areas of the lake, where 

they decay and release nutrients. These decaying mats have been reported to support the growth 
3-2 

of fecal bacteria (E. coli, enterococcus), which then enter coastal waters (Byappanahalli et al., 

2003b; Whitman et al., 2003). More recently, Cladophora has been shown to be a potential 

source of human enteric pathogens, such as Campylobacter and Salmonella, in Lake Michigan 

(Ishii et al., 2006b). Streams also carry appreciable quantities of contaminated algal mats 

containing Salmonella and FIB (Whitman, personal communication). 

In contrast to the fairly stable conditions of the Great Lakes, which are located in one 

climatic region of the United States, inland waters are found in every U.S. state and territory, 

including tropical islands such as Hawaii, Guam, and Puerto Rico. Due to the great diversity in 

the physical, chemical, and biological composition of inland waters, their varied locations under 

different climatic conditions, and great variation in physical makeup, it is not possible to 

adequately describe them by one set of characteristics. Because of this diversity, the water 

quality data obtained from the Great Lakes cannot be expected to be applicable to all inland 

water sites. 

Inland flowing waters are defined as waterways that drain excess water (rainwater runoff, 

storm drains, groundwater, POTW effluents, and septic systems) from the many watersheds that 

make up the entire United States. Such factors as morphology, water volume, and rate of flow, 

which characterize each inland water site, are determined by climatic conditions, geography, and 

the drainage area for the watershed. The climatic region generally determines the biological 

composition of inland waters, and it is well known that the biological composition of natural 

waters plays an active role in the fate of FIB and sewage-borne pathogens. Inland flowing waters 

range from trickling creeks to very large rivers with a wide variation between these extremes. 

The width, depth, and volumes of water flowing in these waters vary considerably and often 

dictate the sites where recreational activities occur. A distinct characteristic of inland flowing 

waters is that they collect a wide range of pollutants (physical particles, chemicals, organic 

compounds, biological organisms), which are present in the surrounding watershed and are 

washed off the land by rain. The sites for land-based contamination of inland flowing waters are 

many because waterborne pollutants enter inland waters from both banks and from multiple sites 

and sources as this water flows downstream (Byappanahalli et al., 2003a). Moreover, because the 

volumes of water in many inland water sites are relatively small and land-based pollutants are 

often close to these sites, the concentrations of pollutants per volume of water can quickly 

increase to levels that exceed water quality standards. 

There are also other attributes of inland waters that differ from those of the Great Lakes. 

For example, the banks of most inland waters offer preferential growth for trees, which shade 

inland waters and protect fecal indicators and pathogens from the inactivating effects of sunlight. 

Another attribute of inland water sites is their limited depth, which allows for soil-based particles 

to settle as sediment. Sediments in inland waters can act as suitable habitats for the persistence 

and growth of E. coli and enterococci and represent sources of other contaminants including 

chemicals; sediments are easily resuspended and can release bound pollutants into the water 

phase. These sediments have a greater impact in redistributing fecal indicators and pathogens in 

inland waters compared to waters in the Great Lakes. These factors help to explain why the 

quality of inland waters is often characterized by higher concentrations of turbidity, nutrients, 

organic composition, and microbial load than marine coastal and Great Lakes water (Olyphant et 

al., 2003). 
WERF Inland Waters Workshop Report 3-3 

The sources and the types of pollutants in most inland waters are not known, but often 

contain measurable concentrations of FIB from probable sources such as wild animals, farmed 

animals, POTWs, septic systems, and storm drains. In addition, nonfecal rather than fecal 

sources of E. coli and enterococci have been reported to enter inland waters because soil and 

plant ecosystems near inland water sites provide conditions (moisture, nutrients, temperature) 

that allow for the multiplication and colonization of FIB. For example, in Hawaii, the non-fecal 

sources of E. coli and enterococci (soil) have been implicated as the major source of FIB in 

streams that routinely exceed current recreational water quality standards (Hardina and Fujioka, 

1991; Luther and Fujioka, 2004). Environmental sources of E. coli and enterococci have been 

reported in other tropical locations such as Guam (Fujioka et al., 1999), Puerto Rico (Rivera et 

al., 1988), south Florida (Desmarais et al., 2002), other geographical and climatic locations, such 

as Australia (Mackay and Ridley, 1988), and more recently in temperate areas such as the Great 

Lakes (Whitman et al., 2003; Byappanahalli et al., 2006; Ishii et al., 2006a). The results of these 

studies point out two flaws in the current application and interpretation of recreational water 

quality standards: 

 

♦ The assumption that fecal bacteria cannot grow in the environment is not valid. 

♦ The microbial ecology should be considered in predicting the fate of E. coli and enterococci 

because these two fecal bacterial groups are known to have genetic and physiological 

capabilities to multiply under environmental conditions (Fujioka and Byappanahalli, 2001; 

Byappanahalli and Fujioka, 2004). 

A significant consequence resulting from growth and presence of environmental sources 

of E. coli and enterococci in inland waters is that they falsely indicate recent fecal contamination. 

In summary, inland waters found throughout the United States are very diverse in terms 

of water flow, water volume, size, and morphology, as well as physical and biological 

composition of water quality. As indicated above, no set of characteristics can be applied to 

describe all inland waters. Due to such differences in inland water sites, the indicators and 

pathogens group concluded that the factors that control the fate, survival, transport, growth and 

regrowth potential, and ecology of indicators and pathogens will not be the same for all inland 

water sites and will differ from those factors found at the Great Lakes. From this perspective, the 

indicators and pathogens group inferred that the available state of science indicates that criteria 

developed for coastal Great Lakes cannot be directly and broadly applied to all inland waters. 

3.1.2 Use of AWQC Established for the Great Lakes in Inland Waters

As summarized previously (Section 2.2.2), recreational water quality standards have been 

developed based on epidemiologic studies, which provide data to predict and prevent health 

effects to swimmers. In this regard, epidemiologic studies have been completed for marine 

coastal and Great Lakes beaches under conditions of sewage contamination by POTWs but for 

limited cases of nonpoint sources of contamination. Few epidemiologic studies have been 

completed for inland waters, where the prevailing conditions are for nonpoint source 

contamination. As a result, epidemiologic data are limited to predict health effects for people 

using inland waters for primary contact recreation. The indicators and pathogens group 

concluded that the available information indicates that insufficient evidence exists to support the 

direct extrapolation of water quality standards and criteria developed for Great Lakes to inland 

waters. The group believed that it is reasonable to conclude that epidemiologic studies should be 
3-4 

completed for inland waters under conditions of nonpoint sources of contamination, as well as 

under conditions of point source contamination with POTW effluents, to determine reliable 

health-related criteria for inland waters.

Even in the absence of direct data, there was a general consensus in the indicators and 

pathogens group that it is reasonable to expect that swimmers using POTW-impacted inland 

waters will have similar risk for waterborne diseases as has been measured for POTW-impacted 

coastal waters. However, whether the same criteria and water quality standards established for 

coastal Great Lakes can be directly extrapolated to the broad category of inland waters will 

depend on the ambient concentrations of E. coli and enterococci at that inland water site. If the 

ambient concentrations of E. coli and enterococci at the inland water site are low (well below 

current water quality standards) and increase due to effluent discharges from POTW, the same 

current criteria and standards based on concentrations of E. coli and enterococci established for 

the Great Lakes can be reasonably applied to this inland water site. For these inland waters, no 

additional epidemiologic studies will be required. 

However, if the ambient concentrations of E. coli and enterococci at the inland water site 

are elevated (often exceeding current water quality standards) due to general nonpoint sources, 

animal feces, or environmental sources of FIB, the current criteria and standards based on 

concentrations of E. coli and enterococci at the coastal Great Lakes cannot be reasonably 

applied. Under these conditions, epidemiologic studies should be conducted at inland water sites, 

and alternative criteria may be required for predicting waterborne diseases for these inland water 

sites. Under these conditions, water quality standards different from those for Great Lakes will 

need to be established. This conclusion is supported by previous epidemiologic studies (Calderon 

et al., 1991; Colford et al., 2007) demonstrating that the predominant source of FIB was animal 

rather than POTW-based and a lack of correlation between increases in enterococcal counts and 

gastrointestinal disease rates. 

In summary, the general consensus of the indicators and pathogens group is that it may 

not be appropriate to extrapolate health risks from POTW-impacted waters to waters with 

elevated concentrations of FIB impacted primarily from nonpoint sources such as animal feces, 

general urban discharges, and environmental sources until further research confirms comparable 

health risks. 

3.2 Health Risks Group

3.2.1 Synthesis of Epidemiologic Literature 

A review of the epidemiologic literature indicated that all studies of water recreation and 

health effects identified higher rates of at least some health end points in relation to water 

exposure, and many identify elevated rates of illness in relation to some measure of water 

quality. Exposure factors are also important with self-reported water-ingestion (and in the case of 

paddling activities, capsizing) increasing the risk of illness. If water quality criteria were to be 

developed to be protective under a worst-case scenario, they would be protective in lower-risk 

settings. However, some of the most heavily polluted flowing waters that were studied were used 

for canoeing and rowing, (Fewtrell et al., 1992; Fewtrell et al., 1994; Lee et al., 1997) rather than 

swimming. Thus, attempting to develop criteria using data from several of the studies of inland 

waters would likely not be sufficiently protective for primary contact recreation. To identify 
WERF Inland Waters Workshop Report 3-5 

major differences about which assumptions would be necessary to apply marine-derived criteria 

to inland flowing waters for primary contact recreation, the health risks group employed a model 

of the assumptions involved (Figure 3-1). The conceptual model illustrates ways that differences 

across settings could limit the ability to apply Great Lakes or marine-derived water quality/health 

risk relationships to criteria development in inland (flowing) waters. 

In addition to these differences, sources of fecal pollutants can vary within and across 

these categories of water settings. To evaluate the differences in health risks attributable to 

differences in setting (i.e., water type, hydrology, flow regime), contrasts were sought among 

studies that employed similar methods across settings. Several pairs of studies were identified to 

create such contrasts. Those contrasts are summarized below.

Figure 3-1. Conceptual Model for Extending Health Risk Relationships to Inland Flowing Waters. 

Marine 

waters

Great 

Lakes

Inland, 

quiescent

Inland, 

flowing

Water 

matrix

Hydrology, 

dilution

Flow

Evaluation by Water Type 

U.S. Prospective Cohort Studies: Studies by Cabelli (1983) and Dufour (1984) employed the 

same study design and were the basis for the U.S. EPA 1986 water quality criteria. The Cabelli 

studies were conducted at marine locations, and the Dufour study sites were at Great Lakes and 

an inland lake. This pair of studies identified two important differences between water 

quality/health risk associations that varied by type of water. In marine waters, presence of 

enterococci was a predictor of health risks, whereas in freshwater, enterococci or E. coli

predicted health risks. Second, the slope of the enterococcus density–health risk regression line 

was steeper in marine water compared to freshwater. In other words, a given increase in 

enterococcus density would be expected to result in greater health risks in marine water in 

comparison with freshwater. 

The NEEAR studies (Wade et al., 2006; 2008) described an association between Q-PCR 

measures of enterococci and health effects in swimmers, but the Mission Bay study did not 

(Colford et al., 2007). The NEEAR study beaches are different than those studied in Mission Bay 

in ways that go beyond water type (Great Lakes v. marine). Pollutant sources were also different, 

with POTW impacts at the Great Lakes beaches but not at the Mission Bay marine beaches, 

which had primarily avian and limited human impacts. Furthermore, Q-PCR enterococci 

measures were somewhat higher at the Great Lakes beaches (median 76.4 cell equivalents/100 

mL) than at Mission Bay (geometric mean 65 CE/100mL). The consensus of the health risks 

group was that the disparate findings of these studies are unlikely to be attributable to the 

difference in water type (marine v. fresh), but rather to the greater extent of fecal pollution 

overall, the majority of which was from human sources in the Great Lakes. The results of the 

Santa Monica Bay study (Haile et al., 1999) are less readily comparable to the Great Lakes 

studies due to differences in study design such as the absence of Q-PCR measures of enterococci. 

The anticipated publication of findings of the NEEAR marine studies will likely shed additional 
3-6 

light on potential differences between health risks of swimming at POTW-impacted beaches in 

marine and freshwater settings. 

European Randomized Controlled Trials

Evaluation by Flowing v. Nonflowing 

: The Kay (1994) and Wiedenmann (2006) studies both 

demonstrated elevated health risks associated with microbial measures of water quality above a 

certain level. The UK marine studies (Kay et al., 1994) had substantial POTW impacts, and the 

freshwater studies in Germany (Wiedenmann et al., 2006) were conducted at sites with varying 

impacts, including POTW, CSO, urban and agricultural runoff, and waterfowl. Swimming (at 

least three head immersions) in the UK marine waters with enterococcus densities above 32 

CFU/100 mL was associated with an attributable risk for GI illness of 19.5%. Swimming (same 

definition) in the German freshwaters water with densities of enterococci greater than 24 

CFU/100 mL was associated with an attributable risk GI illness of 4.5%. The higher attributable 

risk in the UK studies has been explained by the higher baseline rate of illness (in the 

nonswimming group) and susceptibility to infection in the UK studies. It is also possible that the 

higher attributable risk in the UK studies is due to the source of the fecal contamination (thought 

to be predominantly human in the UK and mixed in Germany). Thus, an evaluation of water type 

(marine v. freshwater) as a modifier of the water quality/health risk relationship is not possible 

from this pair of studies. 

U.S. v. European Cohort Studies: Two cohort studies were conducted on freshwater impacted by 

human fecal pollution, one in the United States (Dufour, 1984) and one in France (Ferley et al., 

1989; Zmirou et al., 1990). The U.S. study was conducted at one of the Great Lakes and an 

inland lake site, and the French study (Ferley et al., 1989; Zmirou et al., 1990) was conducted on 

a river. Both found increasing health risk with increasing densities of enterococci. Direct 

comparisons of the water quality/health risk regression lines contained in the two studies is 

limited by the fact that the French study modeled rates of illness among swimmers (per 1,000 

person-days), and the U.S. study modeled rates of illness attributable to swimming (compared to 

nonswimmers) per 1,000 persons. The anticipated publication of randomized controlled trials on 

European rivers may allow the evaluation of effect modification of the water quality/health risk 

association in freshwater as a function of water flow.

European Prospective Cohort Studies: The health risks of canoeing on waters with substantial 

flow, namely, at an inland whitewater slalom course, have been evaluated in two studies 

(Fewtrell et al., 1992; Lee et al., 1997). The health risks of participating in a rowing regatta or

canoe marathon on canals, a river, and an estuarine river and have also been reported by Fewtrell 

et al. (1994). These studies did not enroll swimmers, and the relative risks of swimming and 

rowing/canoeing in the same waters are not known. This precludes direct comparisons of these 

studies to the other epidemiologic studies. Both ingesting water or capsizing were found to be 

risk factors for illness. Therefore, differences in water ingestion rates in marine, Great Lakes, 

inland nonflowing and flowing waters would be expected to result in differences in health risks 

for a given measure of water quality. Data are lacking about such exposures, but the health risks 

group suspected that jumping into waves or body surfing in marine settings might result in 

greater ingestion rates than swimming in inland lakes or rivers where wave height is small. Such 

exposures would not be expected in the randomized controlled trials (in which study participants 

simply immersed their heads three times) but would be expected the prospective cohort studies 

of swimming.
WERF Inland Waters Workshop Report 3-7 

Evaluation by Pollution Source 

Agricultural Animal v. Human Source Pollution: Studies conducted in Hong Kong (Cheung et 

al., 1990) and New Zealand (McBride et al., 1998) provide very limited information and, taken 

together, inconclusive findings about the modification of the risk attributed to a given change in 

water quality by fecal source. There is no convincing evidence that public health would be 

underprotected by applying criteria developed from human studies to settings with substantial 

impacts from agricultural animals. 

Stormwater and Urban Runoff: Potential differences in the water quality/health risk relationship 

for urban runoff, storm water overflows, combined sewer overflows, and wastewater have not 

been directly evaluated in a single epidemiologic study. The U.S. EPA marine study conducted 

at Lake Pontchartrain in the late 1970s suggested lesser health impacts for stormwater runoff 

than for wastewater (U.S. EPA, 1983). Although the health effects of swimming near urban 

runoff were studied in Santa Monica, California (Haile et al., 1999), this study differed 

substantially from other prospective cohort studies. The absence of a nonswimming control 

group precludes comparing results from Santa Monica to the NEEAR or Mission Bay studies. 

Based on the finding of human enteric viruses in water samples, there was apparently a source of

human fecal contamination. Urban runoff without POTWs is also the subject of a study at 

Doheny Beach, California, and an ongoing randomized controlled trial in South Florida. These 

and other planned studies may shed light in the near future on the question of whether the water 

quality/health risk relationship is different for diffuse urban sources of fecal pollution compared 

to POTW sources. 

Mission Bay v. NEEAR Great Lakes

3.2.2 Use of AWQC Established for the Great Lakes in Inland Waters 

: As noted above under the comparison of health risks for 

marine and freshwater, the Mission Bay study (Colford et al., 2007) and NEEAR studies (Wade 

et al., 2006; 2008) had similar study designs and found different associations between water 

quality measured as Enterococcus Q-PCR cell equivalents. The Q-PCR enterococci measures

were found to predict risk at Great Lakes sites but not at Mission Bay. Two of the factors that 

differentiate the Mission Bay and NEEAR study sites are water matrix (marine v. fresh) and 

sources (avian plus limited human v. POTW). Source tracking based on ribotyping of 

approximately 1,000 environmental isolates of Enterococcus spp. suggested that avian sources of 

fecal contamination may have dominated at the Mission Bay beach. This conclusion was 

supported by the detection of another source identifier, the human Bacteroides marker, by PCR 

in only 9% of receiving waters tested (S. Wuertz, personal communication). The consensus of 

the health risks group is that the observed differences in the water quality/health risk association 

were most likely due to difference in source (human v. avian), rather than the difference between 

water types (marine v. freshwater). However, this is speculation, and targeted research that 

specifically addresses the question of source effects v. water type effects is needed. 

The purpose of this section is to summarize the health risks group’s perspective regarding 

the application of water quality criteria that are derived based on studies of recreation in marine 

coastal or Great Lakes waters to inland waters. As summarized in the preceding sections, the 

available epidemiologic literature was reviewed in detail. This review included what is known 

about the health effects of recreation in inland, coastal, and Great Lakes settings. Evidence was 
3-8 

also considered to support the hypotheses that the predominant source of fecal contamination is 

an important determinant of health risks characterized by epidemiologic studies. Finally, the 

relative scientific merit of applying the epidemiologic results from the Great Lakes to inland 

water settings was considered. 

Applying water quality criteria derived from research conducted in marine coastal or 

Great Lakes settings to inland waters would be based on the assumption that the water 

quality/health risk associations derived from epidemiologic studies conducted on Great Lakes or 

marine waters would be no less protective in inland flowing waters. For this assumption to be 

valid, the sources of fecal contamination and the indicator–pathogen relationships should be 

similar in (flowing) inland waters and the settings in which the epidemiologic studies were 

conducted. The health risks group suspected that sources of fecal contamination and the types 

and densities of pathogenic microbes vary widely within flowing waters and could be very 

different than those in the most epidemiologic studies conducted to date. Specifically, river 

systems that drain agricultural and rural areas may be contaminated by fecal pollution of animal, 

rather than human, origin. This supposition is consistent with the point of view presented by the 

indicators and pathogens group described previously. In addition to differences in pathogen 

sources, inland flowing waters may be characterized by different microbial transport, survival, 

regrowth, and fate characteristics than those observed in Great Lakes and marine settings. Thus, 

in the opinion of the health risks group, applying existing epidemiologic results to inland flowing 

waters requires consideration of both these areas of uncertainty: flowing v. non-flowing waters 

and differences in predominant sources of fecal contamination. 

The scientific literature does not definitively answer what the health implications would 

be of applying criteria derived from epidemiologic studies of Great Lakes swimming to inland 

flowing waters. Given this, a range of perspectives can be taken, bounded by the following 

options in the short-term:

♦ Position 1: Applying the results from the Great Lakes studies to inland flowing waters is 

not supported by the scientific literature because directly comparable studies have not 

been conducted. It is unknown whether such application is underprotective of public 

health.

♦ Position 2: Applying the results from the Great Lakes studies to inland flowing waters is 

a reasonable step based on supporting information in the literature and approaches taken 

worldwide and is unlikely to result in the underprotection of public health. 

Position 1 can be justified based on the following arguments: 

1. There is simply a lack of direct evidence that would support applying epidemiologic

results from nonflowing (freshwater) locations to locations with flowing water. Data to 

address this evidence gap could be generated by an epidemiologic study modeled after 

the NEEAR study, conducted at inland flowing water locations. In addition to the lack of 

existing studies that directly compare health risks in Great Lakes/coastal and inland 

flowing waters, epidemiologic studies are limited in their characterization of sources of 

the indicator organisms or microbes that were measured. Additional research should seek 

to fill this knowledge gap regarding source effects. 
WERF Inland Waters Workshop Report 3-9 

2. It appears that differences exist between marine water and freshwater. First, E. coli is a 

predictor of health risks in fresh but not marine waters. Second, using culture-based 

methods, a given increase in enterococcus density is associated with a larger increase in 

health risk in marine, compared to freshwater. If substantial differences in indicator–

pathogen relationships were to be found between Great Lakes and inland flowing waters, 

the public health implications of applying of Great Lakes/coastal-derived criteria to 

inland flowing waters would be uncertain. 

Although the World Health Organization (WHO) used health risk information derived 

from marine studies to establish water quality recommendations for other types of waters, 

it did not apply the same numeric criteria to all waters. Instead, the WHO approach also 

considers differences in pollutant sources and local conditions that could be identified in 

sanitary investigations (WHO, 2003). Therefore, although the WHO applied information 

from coastal marine and quiescent waters to all inland waters, it did not provide a 

precedent for one-size-fits-all criteria, as WHO recognized the impacts of local factors on 

the interpretation of indicator measurements. 

Position 2 can be justified through a weight-of-evidence perspective based on the following 

points (graphically illustrated in Figure 3-2): 

1. Randomized controlled trials conducted at marine and freshwater sites in Europe indicate 

that the relative risk in marine waters is approximately twice that of freshwaters for a 

given density of intestinal enterococci. The prospective cohort studies conducted in the 

United States that were used to support the 1986 ambient water quality criteria indicated 

that the relative risk in marine waters in the U.S. is also approximately twice that of 

freshwaters for a given level of enterococci. The fact that the risk ratio for marine water 

recreation to either Great Lakes or inland waters is similar (approximately 2:1) suggests 

similar risk in both Great Lakes and inland waters. 

2. The results of an epidemiologic study conducted in inland flowing waters in France 

(Ferley et al., 1989; Zmirou et al., 1990) appear similar to the results reported in the 

United States for nonflowing freshwaters (Dufour, 1984) when the reported results are 

converted into approximately similar format (Dufour unpublished data). The primary 

similarity is that both exhibited increases in swimming-associated health effects with 

increasing levels of fecal contamination. 

3. The sources of fecal contamination for the studies summarized above (#1 and #2) were 

mixed and, though typically not well characterized, included POTW effluent of varying 

quality, combined sewer overflows, untreated human contamination (from bathers), 

agricultural sources, waterfowl, and various combinations of these sources. 

4. The WHO faced a similar data gap when developing water quality policy and 

recommended water quality criteria for all waters based the results of epidemiologic

studies conducted only in marine waters (as the freshwater studies had not been published 

at the time of writing). The European Union has recommended numeric criteria for all 

member states based on studies conducted in settings that do not include all water types 

regulated. They recommended water quality criteria for all freshwaters based on the 

results of epidemiologic studies conducted in five quiescent waters sites in Germany (one 

of which was described as a blind arm of a stream in an urban environment that contained 
3-10 

probable sources of fecal contamination that included CSOs, urban runoff after a heavy 

rain, waterfowl, and bathers). The extent to which these policy decisions have ensured a 

precautionary approach to public health protection is open to scientific debate. 

The health risks group acknowledged that a policy imperative exists for immediate 

action. The group supported the objective of establishing water quality criteria that are applicable 

to inland waters. It is the opinion of the health risks group that water quality criteria derived from 

Great Lakes studies would likely be protective of public health at inland waters. Given the 

unique aspects of inland waters identified in the workshop, the health risks group recognizes the 

significant challenges in implementing the water quality monitoring methods used in Great 

Lakes recreation studies, and interpreting the results of such testing, in inland waters. Therefore, 

the group strongly recommends that an early effort be made to fill the clear knowledge gaps that 

have been identified in this workshop, by conducting multidisciplinary epidemiologic 

investigations in inland waters. 

Figure 3- 2. Schematic Diagram for Comparing Study Results. 

3.3 Water Matrix Group

3.3.1 Use of AWQC Established for the Great Lakes in Inland Waters

The water matrix group recognized that the implicit assumption of an acceptably constant 

relationship for various types of waters between human health and indicator levels may not be 

valid. Logically, the relationship between human health and indicators should be different and a 

function of the following: microbe sources (human, animal, or environmental), the distribution of 

the sources relative to the waterbody, a function of the transport characteristics at the point(s) of 

deposition to the waterbody and within the waterbody, the differential survival rates and 

potential for regrowth under differing environmental conditions, the dilution capacity and mixing 

characteristics of the receiving waterbody, and the chemistry of the receiving waterbody. All of 
WERF Inland Waters Workshop Report 3-11

these factors may affect the relative distribution of indicators as measured via traditional culture 

methods (and potentially Q-PCR) and infectious pathogens, which ultimately cause disease. 

The matrix group was of the opinion that the only way to tease out all of the important 

factors that affect the relationship between health effects and indicators/water quality is through 

modeling efforts. As no two watersheds are the same, there is a possibility that, for example, a 

marine coastal beach at one location may have a different relationship between indicators and 

human health effects compared to a marine coastal beach at another location due to differences 

in the sources, transport, and fate differing significantly in each watershed. The only way to 

effectively transfer the results from one watershed to another is to evaluate each watershed with 

respect to potential sources, local physicochemical conditions, and geographic distribution of 

FIB/pathogen sources. Such efforts require a fundamental understanding of the fate and transport 

of health-related microbes, which is currently lacking in the literature and limits the ability to 

apply mechanistic modeling approaches to support regulatory purposes. 

One distinct difference between inland waters and coastal/Great Lakes waters is the ratio 

of sediment to water. The ratio of sediment to water can be expressed in hydrologic terms as the 

hydraulic perimeter (cross-sectional area of flow divided by the length of the cross-section in 

contact with the channel banks). Inland waters, because they are more confined, have a lower 

water volume to surface area (lower hydraulic perimeter) relative to coastal or Great Lakes 

recreational waters. Because of this difference, the matrix group suspects that inland waters may 

be more susceptible to processes associated with their sediment boundary. These processes can 

include, for example, resuspension events especially during increased flow conditions because of 

limitations with respect to dilution. Resuspension may be further increased by the greater 

accumulation of very fine/colloidal organic matter associated with indicators and pathogens in 

riverine systems and by increased turbulence due to the increased velocities.

Other effects may include the uptake or sorption of microbial contaminants and 

subsequent release under changing hydrologic or chemical conditions. Moreover, riverine 

sediments may also influence the persistence and potential regrowth of fecal indicator bacteria 

(Davies et al., 1995) because the sediment boundary which is subjected to wetting and drying, is 

the zone whereby regrowth is suspected to occur (Solo-Gabriele et al., 2000; Desmarais et al., 

2002; Wheeler Alm et al., 2003; Yamahara et al., 2009). The differences between coastal and 

inland waters can be even more exaggerated when considering this smaller wet/dry zone because 

the ratio of the wet/dry zone to water volume is considerably different in each system. To 

complicate matters, the regrowth of indicator bacteria is likely to be independent or decoupled 

from pathogen levels and thus could result in different relationships between indicator bacteria 

and pathogen levels between inland and coastal systems. 

More research is needed to evaluate environmental sources of indicators, especially their 

behavior in channel sediment, and to evaluate whether or not the pathogens are affected by the 

same processes that affect indicator microbes. The research community has generally reached 

consensus that indicator bacteria can persist and potentially regrow in sediments (Davies et al., 

1995; Whitman et al., 2003; Byappanahalli and Fujioka, 2004). A question that remains to be 

answered is whether pathogens can also persist and possibly regrow (especially bacterial 

pathogens) in the environment. These questions regarding differential regrowth and persistence 
3-12 

need to be answered before epidemiologic data from coastal areas are widely applied to inland 

flowing waters.

Although there are differences in the fate and transport of microorganisms in coastal, 

Great Lakes, and inland waters, the matrix group did not believe that these differences have a 

major influence on the understanding and interpretation of the health risk information from the 

epidemiologic studies. 

Because models are usually site specific, different modeling techniques are not needed 

for inland waters than those currently being used in the Great Lakes and marine coastal waters. 

However, the matrix group believes that key differences in the approach to modeling would be: 

1) the types of independent variables used in a regression model, and 2) the values assigned to 

parameters in mechanistic models (different die-off rates, inputs from resuspension, and so 

forth). Overall, most members of the group agreed that the differences in parameters used in 

models for inland waters and Great Lakes are not expected to be any more different than 

parameter differences between different sites within the Great Lakes or within different marine 

coastal waters.

3.3.2 Issues Specific to Regression Models 

Independent variables used in regression models in the Great Lakes include, but are not 

limited to wave height, turbidity, antecedent rainfall, wind direction and velocity, water 

temperature, sunlight intensity (ultraviolet or photosynthetically active radiation), lake level, 

day-of-the-year, chlorophyll or color, current direction, and foreshore water level. At ocean 

beaches, these same variables can be used with the addition of tide level and tide range as two 

important independent variables. In inland flowing waters, turbidity has been shown to be a 

dominant independent variable (Francy et al., 2002; Francy and Darner, 2006; Francy et al., 

2006). Similarly, wind direction and intensity were shown to be dominant independent variables 

in an inland reservoir in Ohio (Francy et al., 2006). Regression modeling of an urban estuarine 

river system indicated that rainfall in the previous 72 hours and sewage overflow volumes were 

significant independent variables predicting FIB and pathogen concentrations in the water 

column (Ferguson et al., 1996). These studies are limited in scope; more work needs to be done 

to identify the independent variables that can be used to predict recreational water quality in a 

variety of inland waters.

3.3.3 Issues Specific to Mechanistic Models 

The types of parameters needed to develop a mechanistic model depend on the 

complexity and source functions to be included within the model. These include parameters 

describing dispersion, advection, die-off rates, deposition rates, adsorption rates, settling rates, 

partitioning coefficients, transport, growth rates, grazing rates, types of sources, source loadings, 

timing of source inputs, and so on. For watershed models, information on the soil type, land use, 

fecal presence, manure management, permeability of soils and sediments, slope of land, moisture 

content of soils is likely to be needed. 

Differences in mechanistic models for coastal and inland flowing waters could include 

the following: 
WERF Inland Waters Workshop Report 3-13

♦ Rivers/streams are modeled as one- or two-dimensional systems whereas lakes and oceans 

are generally modeled as three-dimensional systems because their hydraulics are more 

complex.

♦ Boundary conditions may be different between inland/flowing waters. (Some group members 

thought that this might be important and others were not as sure.) 

♦ Lakes and oceans are wind-driven systems whereas rivers/streams are flow-driven systems. 

♦ There is a greater potential for dilution of contaminants in lakes and oceans than in inland 

flowing waters.

♦ Indicators and pathogens preferentially attach to finer particles and/or particles with higher 

organic matter content. Because particle sizes in inland flowing waters may be finer than in 

coastal waters, the potential for attachment, deposition, and resuspension in the water column 

is likely to be different in flowing waters than in coastal waters. 

♦ Turbidity is likely to be higher and of greater importance in inland flowing waters than in 

coastal waters.

♦ Sunlight-mediated inactivation of indicators and pathogens may vary due to shading near 

flowing waters and increased turbidity, which may quench reactive oxygen species. 

♦ Higher organic content of inland waters may increase the potential for growth of FIB and 

pathogens in sediments compared to marine or Great Lakes environments. 

3.3.4 Issues Specific to QMRA Models 

QMRA may be useful for understanding site-specific differences in risk for inland waters 

and for comparing between inland waters and coastal/Great Lake studies. However, the matrix 

group acknowledged that there are inherent uncertainties in risk parameterizations (e.g., 

pathogen concentrations, ingestion rates, dose-response curves). In addition, the concentration of 

pathogens (and the indicator:pathogen ratio) as they move from source to receiving waters are 

highly uncertain. It is considered a high priority to anchor the results of QMRA to epidemiology 

studies to lend credence to their use. Even if QMRA cannot be anchored to an epidemiology 

study, QMRA techniques can provide useful insight into relative risk differences between 

different hazardous events or worst-case scenarios (e.g., heavy rainfall, CSO discharge, direct 

defecation of domestic animals into water). 

3.4 Sources Group

3.4.1 Differences in Sources between Inland and Coastal Waters 

In considering the differences between sources that impact Great Lakes and marine 

coastal waters compared to inland waters, the sources group identified three categories of salient 

factors: types of fecal contamination, scale, and inland environments. Each of those factors is 

described below.

Types of Fecal Contamination 

Animal feces are generally thought to present less of a risk to human health than human 

feces, but the extent of the reduced risk has not been quantified and will vary dependent on a 

number of factors. These factors include 

♦ type of animal

♦ level of fecal waste treatment
3-14 

♦ proximity of waste to waterways, including direct deposition

♦ pathogenicity and host specificity 

♦ pathogen infectivity 

♦ pathogen prevalence in herds and shedding intensity/concentrations 

♦ animal density and variations in density across geographic areas, including migration of 

wildlife species

♦ relationship between pathogens and indicators 

♦ climate (drought, feed quality, and other climate-related variables can alter the shedding 

intensity and pathogen prevalence within animal populations) 

♦ pathogen survival and potential for regrowth in soil, manure, and water compared to FIB. 

Pathogen and FIB prevalence and concentrations in feces of various animal hosts, in 

particular, are known to be highly variable (Ferguson et al., 2009) and represent one of the 

greatest uncertainties in existing mechanistic models predicting water quality in inland rivers 

(Ferguson et al., 2007a). Some microorganisms in animal feces have the potential to cause 

zoonotic disease. The animal species that are the predominant hosts are highlighted in Table 3-1. 

The prevalence of onsite waste water treatment systems (septic tanks, aerated water 

treatment systems, lagoons, and package plants) is much higher for inland watersheds than in 

coastal environments. Hence, the contribution of nonpoint source human sewage effluents could 

be much greater in inland waterways. Compounding this higher rate of occurrence is the higher 

propensity for onsite systems to fail and to be linked to faulty infrastructure thus contributing to 

the load of “diffuse” fecal pollution (Charles et al., 2003). Another difficulty with 

onsite/decentralized systems is that there is very great variability in how they function. In this 

instance, “function” includes all aspects of the design, location, efficacy, maintenance, and 

suitability to soil type. This variability in performance and “function” is difficult to predict 

because the management and standards for “function” are geographically highly variable since 

on-site systems are usually regulated at a decentralized government level by individual counties 

and/or states.

Table 3- 1. Pathogen Hazards Arising from Animals. 

Pathogen Animal*

Salmonella spp. Birds and mammals

Campylobacter spp. Birds and mammals

Yersinia enterocolitica Pigs

Pathogenic E. coli Cattle, other ruminants, poultry, waterfowl

Mycobacterium bovis Cattle

Mycobacterium avium Birds

Cryptosporidium parvum Placental mammals, rodents

Giardia lamblia/intestinalis Placental mammals including beavers

Toxoplasma gondii Most mammals

Hepatitis E virus Pigs

Listeria monocytogenes Pigs, cattle

Microsporidia Most mammals

Legionella spp. Birds

Leptospira spp. Dogs, rodents, other mammals

Enteroviruses Pigs, cattle

*Known variants that are more or less infectious for humans but their distribution across these hosts is unknown.
WERF Inland Waters Workshop Report 3-15

Another major difference in inland systems is the variation in quality and quantity of 

urban runoff as compared to agricultural/rural/wildlife runoff. Urban runoff is typically derived 

from land areas with much higher population densities and with much greater impervious surface 

areas. Whereas agricultural/rural/wildlife runoff will arise from areas with much lower 

population densities and less hard, impervious surface areas but probably large amounts of fecal 

material. For example, in New Zealand, dairy cattle (9.7 million animals) produced 194,000 tons 

of fecal waste per day whereas the 4 million humans produced 800 tons of fecal waste per day 

(Savill, personal communication, 2009); hence, agricultural runoff represents a significant source 

of fecal contamination in this setting. 

Although it is known that there is considerable variability of pathogens and indicators in 

urban runoff, little is known about the relationships between pathogens and FIB within urban 

runoff and even less information is available on the variability and quality of runoff from 

agricultural/rural/wildlife dominated watersheds. Runoff from agricultural/rural/wildlife 

dominated areas is also composed of complex mixtures of particles, solids, pathogens, and 

indicators. Although it could be assumed that urban runoff has less variability in terms of animal 

sources, this assumption cannot be supported with a high degree of certainty. 

Scale

Some of the significant differences between coastal waters and inland waters can be best 

summarized at the scalar level. These are quantitative differences in 1) proximity of sources of 

fecal contamination to receiving waters, 2) the quantity of fecal material (particularly livestock) 

that contains specific types of pathogens and the virulence of those pathogens, 

3) the mechanisms of delivery of fecal contamination, 4) the land use types surrounding inland 

waters, and 5) the impact of manure and biosolids on inland waters. Each one of these issues is 

discussed below. 

Proximity of sources of fecal contamination to receiving waters: In inland waters, wildlife and 

livestock are in direct proximity to receiving waters. Animals in concentrated or confined animal 

feeding operations (CAFOs, including waste lagoons) can at times be in direct contact with 

receiving waters, both flowing and quiescent. Direct access for fecal contributions from wildlife 

and livestock has a significant impact on water quality (Wood, 2007). In these cases, animal 

feces are contributed in raw form to receiving waters, thereby constituting high density of 

“fresh” sources of FIB and potentially zoonotic pathogens. In many areas, the proximity of 

livestock to waterways is controlled, often with the use of fences. However, wildlife has access 

to waterways and this access can generally not be controlled. Limited data are available to 

estimate the numbers and types of livestock and some wildlife affecting inland waters (Ferguson 

et al., 2009), but these data are currently not being used to estimate inputs of fecal contamination 

and are generally not being used for active management purposes. 

Animal pathogens and their virulence: The host specificity, pathogenicity, and density of 

pathogens stemming from specific animals, particularly livestock, are not well understood. Some 

previous research has demonstrated that specific genotypes of Cryptosporidium have been 

tracked to specific watersheds, indicating a dominant host specificity in specific geographical 

areas (Jiang et al., 2005; Ruecker et al., 2007; Yang et al., 2008). There is also information that 

suggests that virulence of pathogens carried by animals can be highly variable and the 
3-16 

environment into which the pathogens are excreted can control genetic diversity of the pathogens 

(Kemp et al., 2005). 

The ability of zoonotic pathogens to reside on the landscape cannot be ignored for inland waters. 

This dynamic could be substantially different in inland waters than in coastal areas, because of 

the prevalence of livestock and wildlife populations. Zoonotic pathogens have the ability to enter 

a viable but not culturable (VBNC) state. This state has been well described for several enteric 

pathogens, including Salmonella enterica, E. coli, and Campylobacter jejuni (Rollins and 

Colwell, 1986). The VBNC state represents a response to survival stress by not being culturable 

on artificial laboratory media but being capable of retaining virulence. Therefore, in this form, 

survival can prove to be an important potential public health threat. The VBNC state in 

Campylobacter was first reported by Rollins and Colwell (1986), who examined the ability of C.

jejuni strain HC, isolated from human campylobacteriosis patients, to survive in sterile stream 

water.

Mechanisms of delivery: For inland waters, there are significant differences in the mechanisms 

of delivery of fecal contamination. Mechanisms of delivery are highly watershed specific and 

depend upon impervious surface coverage, intensity, and duration of precipitation patterns, 

upstream flow, and the episodic versus chronic nature of events. There is a broad understanding 

that storm events are highly variable. Stormwater runoff into inland streams and rivers can cause 

dramatic increases in the rates of flow given the large volume of runoff and low baseline flows. 

The precipitation amount, as well as the duration and intensity of storms, are all important 

factors. Improved characterization of land use contiguous to inland waters will assist in 

understanding the rates of infiltration and soil conditions. It is generally hypothesized that coastal 

waters are strongly influenced by urban landscapes and that inland waters are likely be more 

closely linked to rural, low-density residential, and agricultural land uses. Where wind can play 

an important role in resuspension in coastal and lake systems, it is likely that in smaller streams 

and rivers that this effect is diminished. However, resuspension of stream bed sediments in 

inland waters during rainfall/runoff events is known to be a significant source of FIB (Jamieson 

et al., 2005).

Land use and geography of surrounding inland waters: Geography and land use characteristics 

are important tools for predicting and assessing water quality. In coastal and Great Lakes areas, 

land use has been well characterized. However, for many smaller watersheds and for inland 

lakes, streams, rivers, and creeks, the characterization of land use could be improved to assist in 

water quality management. Sanitary survey approaches could be conducted for all waters, 

contributing further to the knowledge of sources of specific types of fecal contamination to 

receiving waters (Table 3-2). 

A land use mapping system for inland waters would be highly desirable, and creating a single, 

centralized repository for this type of information would likely improve the ability of water 

quality managers to protect public health. In addition to land use characterization, a major 

difference between inland flowing waters compared to coastal waters is the defined and 

immediate impact of upstream land uses and runoff stemming from upstream. For agricultural 

land uses, it is likely that agricultural drainage is also important. This includes irrigation return 

flows and seepage, which may contain salts that include nutrients (fertilizers), agrochemicals 

(including herbicides and pesticides), and runoff or effluent from animal husbandry locations 
WERF Inland Waters Workshop Report 3-17

such as feedlots, pig farms, dairies, or chicken farms, which also contribute to fecal 

contamination. Increases in impervious surfaces in urban areas that impact inland waters increase 

delivery to surface waters. In inland waters, the lack of dilution that would otherwise take place 

in the Great Lakes and coastal waters can lead to increased impacts of stormwater runoff and 

point source inputs. Finally, it is likely that land use is an important component of predictive 

models of pathogen risks if pathogens stemming from livestock operations and wildlife can be 

more adequately characterized. These two issues together constitute major data gaps in our 

current knowledge. 

Table 3-2. Pathogen Sources and Hazards Typically Captured in Sanitary Surveys. 

Sources Information needed

POTWs Discharge volume and quality

Combined sewer overflows Discharge volume, quality, and frequency

Onsite septic systems GPS location, type, function, proximity to waterways

Sewer assets, e.g., pumping stations GPS location, type, function

Stormwater drains GPS location, type, function

Animal production facilities Type, location, manure handling, effluent discharge, proximity to 

waterways

Animal presence Type, density, proximity to streams

Soil type/ vegetation/land use Type

Spills Nature, location, type, proximity to waterway

Waste/rubbish/dumping sites Nature, location, type, proximity to waterway

Biosolids Nature, location, type, proximity to waterway

Recreational access/activity Frequency of use, density, location

Sale yards & abattoirs Type, density, frequency of use, effluent disposal

CAFOs Type, density, effluent disposal system

Wildlife Type, density, proximity to streams

The impact of manure and biosolids on inland waters

Inland Environment

: Inland waters are frequently used as a 

source of irrigation for adjacent horticultural and agricultural activities which are also frequently 

associated with the widespread use of animal manure and biosolids as fertilizers. Manure slurries 

and land application of human and animal wastes are important sources of nutrients for 

agricultural activities. Hence, rainfall/runoff events in watersheds that support these types of 

activities have significant potential to contaminate inland waterways and represent a potential

public health risk. Current regulations for biosolids application include pathogen reduction 

schemes. However, the impact of biosolids on inland receiving waters, especially for specific 

viral and protozoan pathogens, is not well understood. 

It is possible that indigenous or “naturalized” FIB sources are more important 

quantitatively in inland waters than in marine or Great Lakes environments. This possibility 

could be related to higher organic matter, higher sediment-to-water ratio, greater shade, and 

different redox potential environments in inland waters that would perhaps favor growth. 

A recent study that investigated seasonal effects among indicator and pathogen bacteria 

and parasites in an agricultural watershed confirmed an earlier conclusion by Yates (2007), that 

no single indicator bacteria or simple hydrological index is entirely suitable (or predictive) for all 

environmental systems and pathogens/parasites, even within a common geographic setting 

(Wilkes et al., 2009). Hence, it will be difficult to apply a single set of AWQC for all inland 
3-18 

waters and it is likely that predictive modeling techniques using land use data, combined with 

data from locally conducted sanitary surveys, will be required to conduct suitable UAAs for the 

wide variety of inland waters in the United States.

3.4.2 Use of AWQC Established for the Great Lakes in Inland Waters 

In the context of source loadings (Figure 3-3) describes the sources group’s evaluation of 

the extent to which the members believe it is reasonable to extrapolate existing data from the 

U.S. EPA’s epidemiologic studies in Great Lakes and Marine Coastal waters to inland waters.

The size of the knowledge gaps about these systems is represented by the arrow on the left side 

of the Figure 3-3. Our understanding of POTW-impacted Great Lakes and coastal waters is much 

greater; hence, the knowledge gap about how these data can be extrapolated to inland waters is 

smaller than for waters affected by NPS runoff. The green arrow on the right of Figure 3-3 

indicates that the extent of human activities and human fecal impacts decreases from POTW 

compared to environments with CSO- and NPS-impacted runoff. 

The designation of POTW does not include sewage treatment systems that have the 

potential for storm overflow (CSOs). If treatment and/or dilution factors are substantially 

different, then the relationship between POTW-impacted inland water and POTW-impacted 

Great Lakes/coastal water may not hold true. 

For CSOs, there is a significant data gap because no study has been conducted 

specifically to evaluate CSOs’ effects on inland waters. Thus, our understanding of CSO impact 

on Great Lakes and coastal waters is less than adequate because of the variability of inputs and 

the lack of adequate source descriptions for some of the studies. 

The effects of NPS runoff on inland waters are dominated by animal and livestock inputs. 

There is reason to expect that these inputs have a differential impact on human health risk 

because of the presence of zoonotic pathogens, possibly constituting a lower human health risk 

than that associated with human waste from POTWs. However, there are data gaps in this area 

that need to be addressed to determine if this is indeed the case.

In conclusion, lack of data about the prevalence, concentration, and ecology of pathogens 

and the relationship to fecal indicator bacteria in NPS runoff, particularly from livestock and 

wildlife make it difficult to extrapolate from Great Lakes and coastal epidemiology studies to 

inland regions because the sources are different. The knowledge gaps are so profound and the 

inherent variability in NPS-impacted systems is so great that we do not know if water quality 

criteria based on Great Lakes/coastal studies can be extrapolated to inland waters. These criteria 

could be either over- or under-protective of human health, depending on the circumstances. 
WERF Inland Waters Workshop Report 3-19

Figure 3-3. Sources Group Schematic for Applicability of Criteria to Inland Waters. 

POTW

Inland

POTW

GL and Coastal

CSO

Inland

CSO

GL and 

Coastal

NPS

Inland

NPS

GL and 

Coastal

??

Knowledge Gaps/Differences

Human Influence

?

≈

∝

3.5 Implementation Realities Group

When applying the state-of-the-science concept to implementation realities for inland 

waters, this group focused on implementation flexibilities currently available in the United States 

and in recreational water quality programs in other countries3

3.5.1 Implementation Flexibilities in Current U.S. and International Approaches 

. The flexibilities discussed in this 

section are those that are most directly related to the implementation challenges facing inland 

waters. These challenges include wet weather and high flow events, the increased potential for 

animal sources of fecal indicator bacteria in rural areas, and the increased influence on indicator 

concentration by resuspension of sediment containing environmental strains of indicators. This 

section also discusses current use of QMRA for development of recreational water quality 

criteria as well as some realities and possible flexibilities in existing and proposed assessment 

methodologies. 

One important challenge in considering the “flexibilities” used in beach programs outside 

the United States for applicability to CWA programs in the United States is that water quality 

criteria are used for multiple regulatory purposes far beyond beach advisory programs. Water 

 

3 More information on the elements of the WHO and European Union approaches to criteria development can be 

found in the March 2007 Expert Scientific Report on the Development of New or Revised Recreational Criteria

(U.S. EPA, 2007b).
3-20 

quality criteria in the United States are incorporated into water quality standards regulations and, 

therefore, serve as the foundation for water quality-based effluent limitations in discharge 

permits, the basis for determining whether a waterbody is impaired, and the target for TMDL 

development. International beach assessment programs discussed in this section, on the other 

hand, are only used for beach advisory and classification of the beaches themselves. It is 

important to note that each of these international applications pertains only to beaches or 

“bathing waters” and there are no apparent international corollaries to the U.S. method of 

evaluating all waters against bacteria standard regardless of its use as a bathing water. 

U.S. 1986 Bacteria Criteria/U.S. Water Quality Standards Regulations 

U.S. EPA’s 1986 Bacteria Criteria include recommended numeric limits for indicator 

bacteria that are aimed at protection of primary contact recreation designated uses. For 

freshwaters, U.S. EPA recommends either E. coli or enterococci. There are two components to 

the criteria, a geometric mean, and a single-sample maximum. The geometric mean is the value 

most directly related to health, based on the manner in which the epidemiology studies were 

completed. The single-sample maximum values are most useful in beach advisory programs, 

where there is a need to interpret single grab sample results on a daily basis for purposes of 

making decisions about whether to issue advisories or close a beach on a given day. The U.S. 

EPA has recommended that public health officials interpret single-sample results at beaches 

differently for purposes of making advisory or closing decisions, depending upon beach usage. 

Simply stated, at heavily used beaches, numeric single-sample standards for triggering advisories 

or closings could be lower than at less frequently used beaches. The reality, though, is that at 

least some states apply the one standard regardless of beach usage due to the public demand that 

all those recreating should be protected equally.

Another implementation flexibility in the criteria is a path or “off-ramp” to allow use of 

alternative criteria values if a sanitary survey is performed to demonstrate that the water is not 

impacted by human sources of fecal contamination and where an epidemiologic study indicates 

those nonhuman sources pose no increased risk to human health. This is referred to by many as 

the “wildlife exclusion.” In reality, few states have the resources to perform sanitary surveys and 

gather the epidemiologic data necessary to take advantage of this flexibility. The group did point 

out that, although not discussed in the criteria as an alternative, there is the potential for a wellconducted QMRA to be substituted for a site-specific epidemiologic study. 

The regulation pertaining to water quality standards ((WQSs) at 40 CFR 131 also 

provides some implementation flexibility where primary contact recreational uses are not 

attainable. Specifically, states can develop subcategories of their recreational uses to address 

wildlife or nonhuman–source impacted waters. A UAA4

 

4 A UAA is a structured scientific evaluation of the feasibility of attaining a designated use based on six factors 

that are specified in the regulations.

 could be developed to support a 

“wildlife-impacted use” or a “nonhuman–impacted use.” This does mean, however, that states 

have to develop scientifically defensible narrative or numeric criteria that are still protective of 

the new use subcategory. Revising state WQSs to reflect the highest attainable uses through 

utilizing recreational use subcategories is an approach that can also provide some flexibility for 

inland waters impacted by wet weather or high flows. For example, both Indiana and California 

WQS regulations include recreational use subcategories that allow temporary suspension of the 
WERF Inland Waters Workshop Report 3-21

primary contact designated uses for certain waterbodies. These temporary use subcategories 

(e.g., CSO-impacted use) would be associated with either an alternative criteria or a suspension 

of the criteria for the temporary time period established in the state’s WQS. Prior to U.S. EPA 

approval of such WQS revisions, states must allow for public participation in the process. 

Ultimately, the inclusion of revised designated use subcategories (even for temporary periods) 

may provide more transparency to the public than an exclusion embedded in the criteria itself. In 

reality, however, because of the many miles of stream banks where primary recreation could 

occur, some states find this implementation flexibility challenging particularly for inland waters. 

Communicating use suspensions or exemption of particular locations along the waterbody is 

difficult for the regulators and confusing to the public. One committee member suggested an 

alternative use suspension plan based on the situation rather than location would be a better 

approach. An example of this approach would be to suspend primary contact recreation in the 

case where physical safety is a greater risk than pathogen exposure. 

World Health Organization Guidelines for Safe Recreational Water Environments 

The WHO developed a beach classification system that incorporates use of a sanitary 

survey to demonstrate susceptibility of fecal influence and microbiological water quality 

assessment over a range of enterococci values. Their approach is used to classify beaches from 

“very good” to “poor.” This framework is used in the beach advisory/public notification and 

annual beach classifications but not for regulatory programs such as permitting of discharges. 

The WHO framework includes some aspects that may be seen as providing some 

implementation flexibility. The sanitary investigation included in the framework tries to express 

“susceptibility of fecal influence” by considering:

♦ the human source (sewage outfalls, CSO, and stormwater discharges) and its proximity to the 

recreation area 

♦ the degree of treatment, population, and flow characteristics of any river feeding into the 

beach

♦ bather density and degree of dilution of the source. 

Flexibility can be realized because the framework uses combinations of susceptibility of 

fecal influence and indicator concentration ranges to assign classifications. For example, when 

susceptibility of fecal influence is low due to low bather density, secondary treatment of sewage 

discharges and long/effective outfalls, the beach can still obtain the highest classification even 

when the indicator concentrations are at intermediate concentrations (41-200 

enterococci/100 mL).

European Union’s (EU) Directive Concerning the Management of Bathing Water Quality 

(Directive 2006/7/EC) 

The EU’s directive provides for monitoring and classification of bathing water quality, 

the management of bathing water quality, and the provision of information to the public on 

bathing water quality. Bathing waters are classified across three classifications from “excellent” 

to “sufficient” using either intestinal enterococci or E. coli concentrations. If water quality does 

not meet any of these classifications, the bathing water is classified as “poor.” The EU 

classification scheme is intended only for public notification and advisory purposes. However, 

the directive provides timelines for member states to ensure that all bathing waters are at least 
3-22 

“sufficient” and they encourage member states to take management actions to increase the 

number of waters classified as “excellent” or “good.” 

Flexibility can be realized in that the directive allows for identification of “short-term 

pollution” events5

♦ sufficient management measures being taken, including surveillance, early warning systems 

and monitoring, with a view to preventing bathers’ exposure by means of a warning or 

bathing prohibition 

 and discounting of samples (for classification purposes) with thorough bathing 

water profiles (see EU Annex III) and sampling to confirm the end of a “short-term pollution” 

event. Achieving a classification of sufficient, good, or excellent, while incurring “short-term 

pollution” events is conditioned on 

♦ adequate management measures being taken to prevent, reduce, or eliminate the causes of 

pollution. 

The directive allows up to 15% of the total samples to be disregarded for classification 

purposes due to short-term pollution during the last assessment period. This “discounting” is 

allowed even under the “excellent” water quality classification. This flexibility recognizes the 

issues associated with achieving water quality during high-flow, wet weather events.

Guidelines for Recreational Water Quality – New Zealand 

This framework uses both beach grading and guideline values (e.g., indicator 

concentration). Beach grades provide the basic means to assess suitability for recreation over 

time, using a combination of knowledge of beach catchment characteristics and microbiological 

information gathered over previous years. Single-sample results of indicator concentrations are 

compared against guideline values to help beach managers determine when management 

intervention is required. The guidelines use a catchment assessment checklist, a microbiological 

assessment category, and a sanitary inspection category to determine a classification from “very 

good” to “poor.” 

Monitoring requirements are based on usage, available information, and the resources 

available to the monitoring authority. E. coli is the preferred indicator organism for freshwaters. 

These guidelines specify that enterococci should not be used as the microbial indicator because 

some enterococci can multiply from natural sources such decaying leafy material. 

Flexibility in this system is realized in that the guidelines allow for the grading to 

incorporate management practices that are shown to be protective of recreational usage. One 

acceptable practice is prohibiting exposure during wet weather events. 

There is a requirement in these regulations that the public be informed if two consecutive 

samples exceed the action level for marine waters and one sample exceeds the action level for 

freshwater.

 

5 Short-term pollution means microbiological contamination...that has clearly identifiable causes, is not normally 

expected to affect bathing water quality for more than approximately 72 hours after the bathing water quality is first 

affected, and for which the competent authority has established procedures to predict and deal with as set out in 

Annex II [of the Directive].
WERF Inland Waters Workshop Report 3-23

QMRA in Criteria Development

One instance in which QMRA has been used specifically for the purpose of criteria 

development is the case of the freshwater guidelines in New Zealand. It was indicated above that 

the New Zealand guidelines follow the general format outlined by the WHO. However, the risk 

cut-offs in fresh recreational waters were set at lower values (0.1%, 1%, and 5%) and are based 

on Campylobacter infection. The basis for this approach was a lack of epidemiologic information 

for freshwater sites in New Zealand, a lack of credible information to develop risk figures for 

other waterborne illnesses, and the fact that campylobacterosis is deemed a public health priority

in New Zealand. Thus, a different approach than that used for marine recreational waters and one 

that was based directly on QMRA was deemed appropriate. Specifically, a comprehensive 

monitoring program indicated a moderate correlation between E. coli and Campylobacter. That 

correlation was used to make an assessment of a critical value for E. coli, corresponding to 

Campylobacter infection based on an individual infection risk from recreational activities.

3.5.2 Realities and Flexibilities with Existing and Proposed Assessment 

 Methodologies used in Clean Water Programs 

Several programs authorized by the CWA utilize microbiological criteria to make 

programmatic and regulatory decisions. The WQS program specifies pathogen criteria and their 

implementation for various waterbody uses. The National Pollutant Discharge Elimination 

System (NPDES) program sets permit limits for pollutants in wastewater discharges, including 

FIB. Those permit limits are set to protect designated uses based on compliance with the water 

quality criteria. The use assessment (303d)/TMDL program assesses the attainment/nonattainment of designated uses by comparing observed ambient water quality to criteria. In 

addition to these CWA programs, the BEACH Act has monitoring requirements and a desire for 

rapid detection for issuing beach advisories/closures. The needs for each of these specific 

programs are 

♦ WQS: Criteria must be science-based, protective of health and the environment, and have the 

ability to be implemented by state WQS programs. 

♦ NPDES: Criteria must translate to a permit limitation that will protect the designated use of 

the receiving water. Because many wastewater treatment facilities disinfect wastewater to 

comply with permit limits, the indicator analysis must be able to determine disinfection 

effectiveness. Both regulators and the regulated have concerns that molecular methods may 

not be able to ascertain treatment and disinfection effectiveness if genetic material is 

conserved through treatment processes. Although the use of molecular methods offers the 

chance for improving the detection of indicator microbes and readily identifying suboptimal 

wastewater treatment, it is generally feared that these there is methods may be ineffective for 

measuring permit compliance. 

♦ 303d/TMDL: Criteria are compared to ambient waterbody concentrations. Ambient networks 

typically generate thousands of samples each year, so analytical methods must be able to 

produce high-volume results at a reasonable cost. TMDL assessment is retrospective, so 

rapid methods are not imperative. 

Assessment and compliance in these programs are currently based on culture methods for 

the target microbes. Some programs and laboratories allow analytical methods for indicator 

bacteria such as Colilert® and Enterolert®. These methods are simple and inexpensive, allow 

high-volume processing of samples, and require little technical expertise of the analyst.
3-24 

Flexibility could be achieved if U.S. EPA and state regulators allowed indicator/method 

combinations selected as the basis of the criterion to be translated to existing culture indicator 

methods. In this scenario, programs not requiring rapid (molecular-based) results, cases where 

there is matrix interference with the molecular chemistries (high incidence of false negatives), or 

where molecular methods are measuring DNA or RNA fragments of nonviable microorganisms 

(high incidence of false positives) could be permitted to utilize culture-based methods. This 

flexibility may be particularly important for the NPDES and TMDL programs unless molecular 

methods can be demonstrated not to be measuring genetic fragments of nonviable 

microorganisms.

Florida has successfully introduced some flexibility into its regulatory programs with its 

data interpretation and data sufficiency approaches. States that have revised standards to select 

different duration and frequency components of their criteria (e.g., change in the averaging 

period) can then change their assessment methodology to include that flexibility. Florida has also 

used the approach of establishing nutrient levels that are clearly associated with impairment or 

non-impairment of state waters and doing site-specific assessments for all waters in-between. 

This approach provides an expedited way to get worst waters on the impaired waters list as well 

as a way to “clear” waters. This narrows the universe of locations where site-by-site assessments 

are required.
WERF Inland Waters Workshop Report 4-1 

CHAPTER 4.0

KNOWLEDGE GAPS

4.1 Indicators and Pathogens Group

Environmental contributions and interactions of indicator bacteria within inland lakes and 

streams and respective watersheds are highly variable and complex. Unlike coastal waterbodies 

whose biogeochemistry tends to be dominated by the characteristics of the waterbody itself, 

smaller lakes and streams are intimately associated with riparian and watershed factors such as 

soils, runoff characteristics, shoreline processes, and meteorological events. Recent studies have 

demonstrated that much of the indicator bacteria loading derives from latent sources within 

watersheds and along shores (Haile et al., 1999; Fujioka and Byappanahalli, 2001; Desmarais et 

al., 2002; Byappanahalli et al., 2003a; Whitman et al., 2006). Therefore, as the ratio of shoreline 

to water volume increases, the relative contributions from nonhuman sources or persistent 

reservoirs may be more important. It is therefore important to understand the overall indicator 

contributions (budget) of these bacteria within these inland settings before an accurate 

assessment of human source based risk can be assigned. 

The potential inputs into a stream or lake are illustrated conceptually in Figure 4-1. In this 

diagram, major inputs are outside the box: sewage point sources might be POTWs, CSOs, and/or 

SSOs while nonpoint sources might be chiefly from septic fields or outdoor waste facilities. 

Animal point sources include CAFOs and poor ranching practices. Nonpoint animal input could 

include unregulated domestic and nondomestic inputs that enter the watershed through surface 

and subsurface mechanisms. Infiltration consists of any groundwater input (exclusive of sewage) 

that introduces pathogens into surface waters; this may be through any groundwater discharges 

including springs and seepage. Runoff inputs might be in the form of streams, ditches, or drains 

that contribute fecal or nonfecal indicators. Runoff can occur in urban, rural, or natural settings 

and the contributions closely reflect riparian characteristics. Salient biological and physical 

mechanisms that influence populations of pathogens and indicators are depicted within the 

diagram’s box. In general, it is known that bacteria populations can become inactive and enter 

dormancy due to environmental stresses but later resuscitate or recolonize (Roszak et al., 1984; 

Rollins and Colwell, 1986; Desmarais et al., 2002; Byappanahalli and Fujioka, 2004). We 

understand now that in both streams and lakes, dynamic exchanges take place between bacterialaden sediments and overlying water; this phenomenon is largely dependent on the hydrology 

and sediment characteristic of the aquatic system. Finally, autochthonous input from direct 

defecation of birds and mammals complicates the overall microbiological budget and adds to the 

complexity of assessing risk. 

Of these various sources and interactions, contributions from point sources are perhaps 

the best studied. This is in part because most epidemiologic and pathogen studies have taken 
4-2 

place in areas downstream of POTW and CSOs. Less is known about nonpoint sewage risks to 

bathers, but there is reason to believe that many of the assumptions underlying pathogenicity of 

point sources probably apply, to some extent, to nonpoint human waste. Nonetheless, fate and 

transport of nonpoint sewage sources are far more complex and harder to estimate hydrologically 

due to physical complexity and relative inputs of individual contributions. 

Of the remaining inputs, point source animal inputs have been extensively studied. 

Nonpoint animal input from wildlife or domestic animals is poorly understood. Furthermore, 

little is known about the risk to bathers from other sources, including nonfecal, nonanthropogenic runoff and seepage, or wildlife. 

Figure 4-1. Conceptual Inputs to a Lake or Stream*. 

*Modified from: Whitman, R.L., M.B. Nevers, and M.N. Byappanahalli. 2006. Examination of the watershed-wide distribution of 

Escherichia coli along southern Lake Michigan: An integrated approach. Applied and Environmental Microbiology 72:7301-7310.

Although the contribution from sewage and regulated animal sources can be reasonably 

characterized, other sources are highly dependent on idiosyncrasies of the watershed, land use, 

and waterbody itself. The interaction between a stream and its valley is highly complex. Thus, 

comparisons between coastal waters and that of streams are very difficult. Unfortunately, unless 

the stream is effluent dominated, epidemiologic studies should be conducted on individual 

streams or at least on groups of streams with similar potential sources of contaminants and basin 

characteristics. In a non-effluent dominated stream, use of indicators themselves may be in 

question since the mechanisms governing their presence and persistence (e.g., inactivation, 

growth, resuspension, storage, seasonality) are highly variable and poorly understood. Inland 

lakes also tend to be closely tied to its basin and source waters, unlike coastal areas of the Great 

Lakes or oceans that are more a product of source geological, chemical, and physical 

limnology/oceanography. In short, smaller bodies of water are more allochthonous based, 

whereas large freshwater and marine waterbodies settings tend to be influenced more by 

autochthonous (internal) factors. Where either coastal or inland bodies are waste effluent 

dominated (an allochthonous factor), risk estimation differences are much diminished even 
WERF Inland Waters Workshop Report 4-3 

though hydrodynamics, riparian interactions and basin characteristics remain influential in both 

settings.

4.1.1 Watershed Approach and Sanitary Survey to Characterize Sources and 

 Locations of Pollution into That Watershed 

Recreational water quality of inland waters is intimately related to land use and 

hydrological factors within watersheds. A watershed approach, including microbial source 

characterization is recommended for managing inland recreational waters. The most widespread 

and perhaps least understood source of enteric microorganisms is stormwater runoff, in part 

because of the diffuse nature of nonpoint source pollution that is often carried by stormwater. It 

is critical that short-term research focus on characterizing microbial loading in terms of timing 

and sources at the watershed scale. 

Sanitary surveys should be standardized to allow a thorough assessment of source 

characterizations and facilitate data comparison across sites of interest. Implementation of water 

safety plans also offers a unique opportunity to consider how watershed-level processes 

contribute to health risks. Standardization of such watershed approaches would allow 

relationships between water quality and watershed attributes (e.g., land use, infrastructure, 

development, soil types, hydrological flow paths) to be described and, for some relationships, 

predicted. Modeling tools, including temporal geographic information systems (GIS) and 

advanced geostatistical tools for spatio-temporal modeling and mapping, could elucidate 

relationships among watershed attributes, weather events, and microbial loading. Overall, it is 

expected that watershed approaches would lead to increased understanding of the 

interrelationship between aquatic and terrestrial ecosystems in direct support of water resource 

management.

4.1.2 Appropriate Sampling Strategy to Characterize Pollution for Inland 

 Water Sites 

Adequate representative sampling of streams for risk-based criteria pose particular 

challenges not present in coastal waters. Although temporal and spatial variables exist in the 

Great Lakes and marine waters, longitudinal, vertical, and temporal variation along a stream 

reach is complex and not necessarily comparable to standing waters. It has been clearly 

demonstrated that concentrations of indicators (and presumably pathogens) vary with water 

depth in lakes, that large variation within and among locations exist, and that distributions are 

dependent on such hydrometeorological factors as wave height, current direction, beach 

orientation, and responses of near- and far- field loading sources (Whitman and Nevers, 2004). 

Physical factors in streams are of singular importance for precise, reliable sampling of streams. 

Sampling in coastal waters often takes place where most visitors are potentially exposed but 

equivalent representative or germane locations for sampling in flowing waters has not been well 

defined. There is an exponential change of suspended solids and probably indicator species 

moving from the margin to the center of a stream due to sediment loading capacity as driven by 

changes in velocity and frictional bottom drag. The relationship holds equally for vertical 

distribution of sediments with velocities decreasing rapidly as the bottom boundary is 

approached. Because many microbes are associated with particulates, it follows that microbial 

distribution and relative indicator to pathogen ratios might change as well. Coastal lakes often 

stratify, but this rarely occurs with the swash through surf zones where swimmers tend to 
4-4 

congregate. Rivers also stratify either thermally or chemically, thereby complicating vertical and 

longitudinal distributions. Probably the most conspicuous changes in stream variation and trends 

occur along reaches of streams. Upper reaches often have lower contaminant loading and, if 

nonpoint in nature, tend to increase with stream distance. The impact of point sources often 

decreases with distance as streams tend to self-reclaim and accrue cleaner water. Temporal 

changes in response to rainfall, as well as diurnal changes in temperature, sunlight, and loading 

variation, are also important. For these reasons, the load of the stream is sometimes as important 

as absolute concentrations of the contaminants. Therefore, velocity and discharge of the stream 

are important components of stream monitoring. 

Hence, there is a need to identify factors that most strongly influence sampling variation 

and to make recommendations for standardization of monitoring streams for indicators and 

pathogens. Different flowing waters would need to be studied to determine the consistency of 

these pathogen characteristics between and within locations. 

4.1.3 Evaluate and Optimize Molecular Methods 

The typical monitoring strategy employed by agencies across the United States is to 

monitor one kind of fecal bacteria indicator (E. coli or enterococci) to evaluate the potential 

presence of fecal-borne pathogens. However, it was previously determined that bacterial 

indicators are inadequate or unreliable surrogates for all sewage-borne pathogens, especially the 

more resistant pathogenic human enteric viruses or parasitic protozoa. Moreover, decades of 

work in this area have led to a consensus amongst environmental and public health 

microbiologists that no single microbial indicator of fecal contamination (or for that matter, any 

method used by itself) can reliably indicate the presence of all the various classes of waterborne 

pathogens, especially in different recreational water exposure scenarios and contexts (Yates, 

2007). 

The fundamental differences between cultural and Q-PCR methods are the fractions of 

the total population of microorganisms being measured in a given sample. Theoretically, each 

sample comprises the following five fractions of that microbial population: 1) viable and 

culturable fraction recovered by that culture method, 2) viable and culturable fraction, to include 

stressed bacteria, which cannot be recovered by that culture method, 3) viable and non-culturable 

fraction, which cannot be cultured by laboratory means but may be infectious in vivo, 4) killed or 

dead fraction of intact cells, and 5) extracellular, free nucleic acid fraction, which can be detected 

by Q-PCR method. The culture method used detects only the fraction that will grow on the 

medium used. In contrast, Q-PCR can detect all five fractions of the microbial population. The 

proportions of these five fractions will likely differ from one sample to another depending on the 

many and variable environmental stresses placed on that sample. In addition, Q-PCR may 

measure multiple nucleic acid sites per cell. These differences can be expected to complicate the 

degree of correlation between these analytical tools. Despite these theoretical differences, 

comparative controls have been reported to correlate culture based method with Q-PCR data. If 

the correlation is significant, it may allow for a mechanism to link culture numbers to a Q-PCR 

value. Such analysis, their results, and the degree to which observations from one beach can be 

applied to another should proceed with caution. Given the various sources of the indicator and 

the potential differences of environmental parameters on the inactivation or degradation of 

targets detected by culture v. Q-PCR, it is reasonable to expect site-specific and temporal 

variation in the linkage between the various analytical tools.
WERF Inland Waters Workshop Report 4-5 

Methods for detection and enumeration of microbial indicators of fecal contamination 

now include biochemical and nucleic acid-based amplification methods. Examples of such 

methods include the quantitative (real-time) polymerase chain reaction (Q-PCR) procedures 

(e.g., U.S. EPA Draft Methods 1606 and 1607 for the detection and enumeration of enterococci 

in water and wastewater using TaqMan® and Scorpion TM probes) for enterococci in water, and 

rapid (2-3 hours) detection of E. coli and enterococci in recreational water using adenosine 

triphosphate (ATP)-based detection (Bushon et al., 2009). Standard culture and other analytical 

methods can be used in conjunction with and in modified ways for specific applications; for 

example, there is now a rapid (4-6 hours or less) procedure that employs a combination of malespecific (F+) coliphage culture, latex agglutination, and typing. This procedure has been 

demonstrated as a simple and rapid method to detect and source track fecal contamination in 

recreational waters (Love and Sobsey, 2007). 

The current Q-PCR methods for enterococci have not yet been shown to be applicable to 

a wide variety of waters due to detection limits, matrix interference, and inability to distinguish 

among enterococci species. Further optimization of these techniques is needed. In addition, it is 

important that there is a clearer understanding of the relationship of this metric to pathogens and 

culturable indicators. In conclusion, given the pace at which new methods are being developed, 

studies are needed to interpret and compare culture and molecular data. 

4.1.4 Mechanistic Modeling Techniques 

Probably the most promising rapid method for monitoring inland lakes and streams is 

mechanistic modeling, but much research remains to be done before its use can be routinely 

incorporated into management practices. Traditional regression models have proven to be more 

challenging than originally envisioned because of the limitations of historical statistical 

techniques, a lack of understanding of explanatory variables, and inadequate sampling and 

validation techniques. Current efforts by U.S. EPA to develop an expert system such as Virtual 

Beach are unlikely to be universally satisfactory as a complete operational tool because of the 

experimental nature of the approach and the lack of robustness, flexibility, and technical 

understanding necessary to develop an operational model that can be widely applicable. 

Nevertheless, these types of systems work well as preliminary exploratory tools and as a 

foundation for more definitive modeling that might be useful as an adjunct to sanitary surveys. 

Modern modeling tools such as neural networks, recursive partitioning, partial regression, 

path analysis, Bayesian networks, wavelet analysis, forecasting, and integration of numeric and 

empiric modeling show great promise in improving modeling to a state that can be adequately 

applied to beach management. Some progress in numeric modeling has been made, but these 

models tend to break down because of the complexity of mechanisms governing beaches 

especially when biological variables are considered. Traditionally, mechanistic approaches are 

two-dimensional although there is a trend toward three-dimensional approaches. Models have 

focused on mostly physical factors such as currents, thermal layering, and fluid dynamics. 

Biological interactions (inactivation, regrowth, biological storage, differential growth and death, 

resuspension, seasonal and temporal variation) greatly challenge these models especially within 

the turbulent zones where swimming often occurs. Likewise, nonpoint sources, especially 

wildlife (shorebirds, aquatic mammals) and non-enteric sources (persistence and growth) are not 

easily incorporated into mechanistic modeling. Thus, effective numerical modeling should be a 
4-6 

longer-term research goal for future beach monitoring. Hybridization of mechanistic and 

empirical approaches that seeks to develop better predictive and exploratory models should also 

be a high priority for water quality management and regulations. 

4.2 Health Risks Group

4.2.1 Pollutant Sources as Modifiers of Risk 

There was unanimous agreement among health risk group members that little is known 

about the degree to which sources modify the risk of adverse health events for a given change in 

microbial water quality. Specifically, fecal material from humans, various agricultural animals, 

birds, other wildlife, and domestic animals may present different indicator-response relationships 

in terms of risk to humans. This consideration is based on the knowledge that some pathogens, 

particularly viruses, tend to be host-specific. Although bacterial and protozoan pathogens can be 

zoonotic, much remains to be elucidated regarding the risks to humans from various 

microorganisms that may potentially be transmitted via a wide range of avian and nonhuman 

mammalian hosts. 

The epidemiologic studies described previously addressed sources as effect modifiers in a 

very limited way. Many of the studies did not separately characterize the sources of pollution; 

others provide brief mentions of what was thought to be the dominant source of fecal pathogens. 

Systematic sanitary surveys were generally not performed, and microbial source tracking 

methods have only recently been employed and were limited to one genetic marker for humanspecific Bacteroides. 

The relative contribution of humans, agricultural animals, domestic animals, birds, and 

other wildlife as sources of fecal pollution likely varies substantially across the range of inland 

waters settings. The lack of information about whether and in what ways such sources present 

different levels of risk to humans is considered the most critical knowledge gap. A related 

knowledge gap, perhaps more from an implementation and risk modeling standpoint, is the 

relative contribution of these diverse sources to the overall indicator and pathogen loads in a 

given body of water. 

4.2.2 Optimal QMRA Models and Methods for Inland Waters 

In the United States, there are thousands of inland water sites with unique hydrologic 

features and diverse sources of fecal pollutants. QMRA has been identified as a potential tool for 

predicting risk for sites where an epidemiologic study has not evaluated the human health 

protection provided by current or desired measures of water quality. Before using QMRA for 

operational and policy purposes, confidence in the predictive value of QMRA is required, and 

additional data are needed to fill knowledge gaps in the QMRA process. To be considered 

thoroughly credible, QMRA models should be able to predict rates of illness for a given setting 

consistent with those observed in epidemiologic studies. It is not known to what degree QMRA 

approaches would arrive at modeled health risk estimates that are comparable to the risks 

observed in epidemiologic studies of water recreation. 

There is greater uncertainty in the predictive accuracy of QMRA when nonhuman fecal 

sources and combinations of sources are of concern. Once credibility through grounding is 

established, QMRA can extend knowledge from sites where an epidemiologic study had been 
WERF Inland Waters Workshop Report 4-7 

conducted to sites where epidemiologic data do not (and likely will not) exist. The potential 

benefit of QMRA is its flexibility in prediction of human health risk from a variety of pathogens 

and sources. The predicted human health risks can then be compared to a given benchmark of 

protection for alternative water quality criteria to evaluate human health protection. This process 

can be repeated for changes in source type or source load. Furthermore, by modifying the 

process, it is possible to make predictions based on direct measurements of pathogens, pathogen 

predictions from models, or pathogen source attribution. As our understanding of the sources, 

fate, and transport of pathogens and indicators improves, QMRA can be updated to reflect these 

advances in knowledge. 

Current QMRA models and methods often use health risk information obtained from 

research that employed culture-based methods of quantifying waterborne microbes. The 

increasing use of Q-PCR methods to estimate microbe densities in water samples (in health 

research studies and, potentially, in regulatory contexts) will require updates of QMRA models 

so they can accommodate Q-PCR-derived inputs. 

4.2.3 The Use of Molecular Methods of Characterizing Microbial Water Quality to 

Predict Health Risks

Two broad categories of knowledge gaps exist regarding Q-PCR: interpreting and 

applying the results of the tests to meet research and regulatory needs. The reproducibility of QPCR methods is perhaps the most urgent knowledge gap. The absence of SOPs validated by 

different laboratories precludes comparing Q-PCR measures of water quality that have been 

made in different laboratories. Consequently, the estimates of health risk as a function of water 

quality derived from these studies may depend on the specific personnel and the techniques and 

primers they utilized to conduct the Q-PCR analyses. It is important to establish a mechanism 

that will administer these interlaboratory comparisons given the logistical difficulties associated 

with obtaining, processing, and analyzing identical samples by multiple laboratories. From an 

implementation perspective, methods must be standardized, simplified, and shown to be 

sensitive, precise, and accurate across a range of physical and chemical measures of water 

quality. 

Identification and quantification of human sources by Q-PCR is another critical research 

gap. Such data will be extremely valuable for QMRA. Currently, there are Q-PCR assays that 

produce quantitative data in the form of gene copies per unit volume, but this is not the same as 

quantitative microbial source tracking. Most genetic assays for animal host-specific bacteria are 

not perfect. This means that no assay will, on one hand, detect all individual stool samples from a 

particular host species and, on the other hand, discriminate against stool samples from all other 

relevant animal hosts. In addition, the number of gene copies of any targeted genetic marker 

based on specific bacteria in individual stool samples will be variable. It is, therefore, desirable 

to have a way of estimating the true concentration of the genetic markers in source and receiving 

waters to help guide the interpretation of environmental monitoring studies. A probabilistic 

model is needed to remove false information from Q-PCR results and fill the data gap how QPCR results may be used in the context of QMRA. 

A related basic question is what should be measured to estimate health risk. Enterococcus

has emerged as one of the best characterized indicator measures by Q-PCR with respect to health 

effects in POTW-impacted waters and at least one non-POTW impacted site. This is a 
4-8 

knowledge gap. Other than Enterococcus and Bacteroides (more appropriately termed 

Bacteroidales unless the marker is limited to the genus Bacteroides), little is known about any QPCR measurements of other microbes or their association health effects. Some initial research 

suggests that Bacteroides offers advantages of greater specificity and greater diversity in target. 

This data gap may be on its way to being narrowed as archived filters from the NEEAR study 

will be analyzed using Q-PCR for other microbes, and these measurements will be evaluated as 

predictors of the health events observed in the cohort. It is essential to include measurements of 

all promising alternative indicators and source identifiers in ongoing and planned epidemiology 

studies. This is especially true for genetic markers where there already exists a broad database 

for concentrations in receiving waters and both host specificity and sensitivity. 

Another challenge to interpreting Q-PCR results is that DNA from viable organisms and 

free DNA (nonviable organisms) is detected together. Pretreatment with propidium monoazide 

(PMA) may allow the differentiation of DNA from intact cells, as opposed to extracellular DNA or 

DNA in dead cells without a functioning membrane. Standardized sensitive and specific methods 

for PMA-Q-PCR that produce the same results across laboratories will be needed as well. A related 

missing piece of information is the persistence in the environment of many of the DNA-based

targets for which molecular detection methods have been developed. Unpublished work indicates 

the T99 (2-log reduction) for the Q-PCR signal for host-specific Bacteroidales in seawater in a 

controlled study was 177 h. When the sample was pretreated with PMA, the T99 was only 28 hours. 

Similar findings were observed for freshwater samples (Bae and Wuertz, 2009a, 2009b). 

Persistence of microbial DNA in surface waters is a research area that U.S. EPA is concerned 

about and an important data gap to be filled in the short-term. Potential influences on DNA 

persistence that should be investigated include: natural sunlight, salinity, predation, and 

temperature. PMA-Q-PCR holds the potential to improve estimated health risks in research studies.

4.3 Water Matrix Group

4.3.1 Regression Models 

The matrix group recommended that regression modeling approaches should lead the way 

in establishing recreational water advisories and closures, with routine measures of microbes 

serving to calibrate and validate the modeling approaches. Currently the strategy is the reverse of 

this, with sample measurements driving compliance. The matrix group is in agreement that 

regression models can be readily developed for beach compliance at many types of sites and that 

efforts should focus on expanding the use of regression models for compliance. The main 

advantage of a model-driven compliance approach is the ability to “nowcast” and even forecast 

beach water-quality conditions, a current process which is not only hindered by the time delay 

between sample collection and analysis, but also sampling limitations in the current strategy. The 

potential ability of models to forecast beach closures would represent a significant improvement in 

public health protection as there would be no time delay between bather exposure and notification. 

Regression model knowledge gaps include: 

♦ the need to be applied to a broader range of settings, including all types of inland waters

♦ the need to be incorporated into current and future epidemiologic studies so as to provide a 

direct link between model output and human health risk. 
WERF Inland Waters Workshop Report 4-9 

4.3.2 Understanding Factors Influencing Microbial Fate and Transport 

There are numerous gaps in our understanding of the factors that influence the fate and 

transport of microorganisms in water. Some of the critical knowledge gaps that exist in those 

factors are specific to inland waters, such as the role of sediments in impacting both the survival 

and transport of pathogens versus indicators. These knowledge gaps include the need to better 

understand: 

♦ The role of organic-rich sediments as a reservoir and potential environment for regrowth of 

fecal indicator organisms as compared to pathogens in flowing waters or lakes. For example, 

sediment characteristics (e.g., particle size, organic content) can influence 

persistence/regrowth. 

♦ The role of particle size in harboring and transporting indicators and pathogens. Sediment 

particle/colloid sizes within inland flowing waters may be different from those in coastal 

waters. Particle size may influence the potential for microbe attachment, deposition, and 

resuspension in the water column as well as result in differential transport of indicators 

versus pathogens. 

♦ The greater potential for dilution of contaminants in lakes and oceans than in inland flowing 

waters and the effects of dilution with respect to the differential impacts on indicator versus 

pathogen concentrations. 

♦ The role of sunlight-mediated inactivation of indicators and pathogens, as greater shading 

near flowing waters and the high organic content would preferentially reduce sunlight effects 

in inland versus coastal waters. 

♦ The role of turbidity, as it is likely to be greater and have more effect on inactivation rates 

and transport behavior in inland flowing waters than in coastal waters. 

4.3.3 Mechanistic Models 

Mechanistic models have the desirable attribute that they provide the basis with which to 

evaluate remedial measures. In the case of TMDLs, this could be a significant factor. With this 

basic understanding incorporated into the mechanistic modeling approach, key sources and 

barriers to pathogens can be identified, which could support management strategies to remediate 

systems and consequently better enable TMDLs to address pathogen issues rather than just 

indicators. 

 

The matrix group had mixed views concerning the use of mechanistic models for issuing 

beach closures and advisories. In general, it was recognized that developing compliance 

strategies based upon a mechanistic modeling approach may be premature because information 

and fundamental knowledge in fate and transport processes are still lacking. 

Because of the advantages of a mechanistic approach, the water matrix group 

recommended that research efforts focus on establishing the fundamental understanding and 

garnering the knowledge needed for establishing mechanistic models, specifically: 

♦ quantifying the loads associated with different sources, especially nonpoint sources

♦ evaluating microbial transport mechanisms from their point of deposition to and within 

the waterbody 
4-10 

♦ evaluating fate of microbes including an evaluation of physical-chemical factors that

influence their detectable levels and viability in the environment. 

For situations where information is lacking, uncertainty should be quantified, and the use 

of stochastic approaches should be considered. For example, inactivation rates may be sensitive 

to small changes in the water matrix (presence of suspended solids) and the biology of the 

organism itself. For this reason, assigning a point estimate for a variable used in a mechanistic 

model is not appropriate in most settings; rather, a stochastic representation of the variable may 

be more appropriate.

4.3.4 Model Links to Health Outcomes 

Interdisciplinary approaches are needed to understand how models, broadly speaking, can 

aid in the prediction of health outcomes and management strategies. There are currently major

knowledge gaps in understanding how: 

♦ regression models may be used to predict health outcomes (instead of indicator 

concentrations) 

♦ QMRA predictions relate to epidemiology study health observations 

♦ mechanistic predictions of indicator and pathogen concentrations from specific sources (such 

as POTW, waterfowl input) can aid in the interpretation of epidemiology study results and 

can support QMRA to estimate health risks. 

Regression Models and Health Outcomes

More work needs to be undertaken to evaluate the ability of regression models to predict 

the rate of swimming-associated illness. This could augment the use of indicator organisms to 

assess health risk (a measure with uncertainty and variability on its own) and, instead, provide a 

direct link between model output and human health risk.

QMRA Models and Health Outcomes

There is a strong need to understand how predictions from QMRA models relate to actual 

human health outcomes measured during epidemiology studies. We need to anchor the 

predictions of QMRA in epidemiologic observations to lend credence to the use of the technique 

to predict recreational waterborne illness. QMRA models require inputs of pathogen 

concentrations, and often these are difficult to measure at the point of exposure. Therefore, 

QMRA studies should be linked to mechanistic fate and transport models of pathogen or 

surrogates from specific sources. There is a knowledge gap on the relationship between 

pathogens and surrogates, as well as their differential fate and transport for identified sources 

(e.g., POTW, bird feces). There is also a knowledge gap regarding the best way of representing 

the variability and uncertainty in QMRA model parameters. A Bayesian approach can be used to 

take advantage of the knowledge of the system and enable parameters to be described 

stochastically. Alternatively, there are also traditional regression and maximum likelihood

approximation that have been used successfully in the past. Either way, the required precision 

needs to be on the same order of magnitude as for epidemiologic studies. 

QMRA is a powerful tool for exploring relative risks under different exposure scenarios 

(for example, storm event v. nonstorm event, kayaking v. swimming, enterococci from bird feces 

v. POTW). However, there has only been a limited range of studies to date, and there is 
WERF Inland Waters Workshop Report 4-11

considerable potential to further exploit QMRA models in this capacity. In particular, future 

research should focus on 

♦ the most important differences in exposure scenarios

♦ better understanding how different types of waterbodies should be managed 

♦ development of site-specific/source-specific criteria 

♦ for the latter, development of QMRA models to identify which type(s) of sources/conditions 

may really represent different risks (due to different types/fate of pathogens).

Mechanistic Models and Health Outcomes

To understand contributions from specific nearby sources, epidemiologic studies should 

include, at a minimum, an in-depth evaluation of microbe sources and measurement of physicalchemical-hydrologic parameters that influence the fate and transport of microbes from specific 

sources. Efforts should also focus on going back in time, to prior epidemiologic studies, to build 

models after-the-fact, and the results from such retrospective models should be compared to 

human health effects directly. Both data mining of existing source/load information and gapfilling research may be necessary to develop models retrospectively.

During epidemiologic studies, we strongly recommend a holistic approach that accounts 

for many source, fate, and transport environmental factors, rather than just focusing on 

measurements of bacterial indicators at recreation sites.

4.4 Sources Group

The sources group was of the opinion that there are two points that need to be addressed 

in the short-term: 1) obtain knowledge on the pathogenic potential of agricultural and wildlife 

feces, and 2) quantify impact of on-site sewage treatment systems on microbial water quality. 

Moreover, four areas were identified as knowledge gaps for inland waters that need to be 

addressed over the longer term: 1) fate and transport of animal pathogens in relation to 

indicators; 2) epidemiologic studies in inland waters; 3) characterization of land use and sanitary 

surveys; 4) water safety plans including best management practices (BMPs). Brief summaries of 

each of these knowledge gaps are provided below. 

4.4.1 Pathogenic Potential of Agricultural and Wildlife Feces 

As described in Section 3.2.1, pollutant sources are a significant modifier of risk to 

human health, and there is a fundamental knowledge gap regarding the level of risk associated 

with agricultural and wildlife feces. Zoonotic transmission of pathogens from animal sources to 

humans via the contamination of drinking or recreational waterbodies can pose a serious risk to 

human health. The extent to which this occurs is dependent upon the prevalence of human 

infectious strains in various animal species (domestic, agricultural, and wildlife) and the extent to 

which they interact with the environment and the opportunity for human exposure to infection. 

There is, therefore, a need to know which animal hosts carry human infectious strains of what 

pathogens and what the prevalence and excretion rates may be across diverse geographic regions 

as well as how this may be influenced by seasonal and climatic effects. 

Furthermore, there is limited knowledge of the relationships between pathogen 

concentrations and FIB or coliphage concentrations in the animal hosts. This is of particular 
4-12 

importance for determining the suitability of using indicator organisms as guidance for NPSimpacted inland waters. Pathogens of specific concern were outlined previously in Table 3- 1. 

4.4.2 Quantify Impact of Onsite Sewage Treatment Systems on Microbial 

Water Quality 

A greater number of onsite sewage treatment systems, including package plants are 

associated with many inland waters compared to urban coastal areas due to the lack of 

centralized sewage treatment facilities because of relatively low population densities. The quality 

of effluent from these systems is known to be poor and highly variable (Charles et al., 2005). 

Compounding this problem is the fact that although these systems serve a smaller fraction of the 

population, the diffuse pollution load from these systems can be as significant as the load from 

centralized point source facilities (POTWs) (Charles et al., 2003). The poor efficacy of onsite 

systems has been attributed to system failures, poor or no disinfection capability, faulty 

infrastructure, inadequate maintenance, or poor design. There is a need to understand 

disinfection efficiency, potential, and frequency of failing systems to estimate the contributions 

of pathogens that may originate from these types of systems. 

One of the factors contributing to the high uncertainty in predicting pathogen loads from 

onsite systems is related to the sporadic nature of human infections in each household. However, 

the disinfection efficacy of various onsite treatment systems also requires further research. A 

recent study (Charles et al., 2008) showed that virus disinfection rates achieved in an onsite sand 

mound system were greater than for traditional septic systems and aerated water treatment 

systems. However, the virus disinfection rates were variable depending on which virus was 

examined, indicating that environmental fate and transport studies need to examine a range of 

index pathogens. 

4.4.3 Fate and Transport of Animal Pathogens in Relation to Indicators 

Although animal densities and fecal excretion rates have a significant effect on the 

amount of material available for mobilization to inland waters during rainfall and runoff events, 

little information is known about these factors and how they vary across the United States. 

Similarly, the survival time of pathogens and indicators in different animal fecal matrices, soil, 

sediments, and aquatic environments is also not well understood. Yet the ability for pathogens to 

survive in these various environments affects the potential risk associated with their subsequent 

transport into inland waters. Transport of pathogens to waterways is highly variable due to 

differences in rainfall/snowmelt, overland flow, drainage ditches (tile drains), slope, soil type, 

particle size, pH, impervious surface area, land use, and riparian areas (including vegetative 

type). Although several studies have examined some of the factors affecting pathogen transport 

mechanisms to waterways during runoff events (Mawdsley et al., 1996; Trask et al., 2004; 

Davies et al., 2005; Atwill et al., 2006; Ferguson et al., 2007b), further research is needed to 

elucidate them in sufficient detail to enable their incorporation into mechanistic models that will 

predict inland water quality. 

4.4.4 Epidemiology Studies in Inland Waters 

Limited epidemiologic information exists for inland waters with NPS or CSO as the 

primary source of contamination. (Refer to Sections 2.2.2 and 3.2.1.) 
WERF Inland Waters Workshop Report 4-13

4.4.5 Characterization of Land Use and Sanitary Surveys 

Few studies have attempted to characterize the quality of inland waters by examining the 

relationship between land use and fecal inputs (Ferguson et al., 2007a; Kay et al., 2008; 

Stapleton et al., 2008). The reason for this is probably a lack of sufficient data. The types of data 

required to establish this relationship include animal types and stocking numbers, farming 

practices, and presence and function of BMPs. This information needs to be linked to land use 

activities within a GIS framework and requires detailed knowledge of local watershed practices, 

this type of information is best collected using sanitary surveys. Comparison of information 

across watersheds and correlations with land use types would be possible if these sanitary 

surveys were performed in a standardized way and if the information was stored electronically 

enabling it to be easily accessed and subsequently utilized in statistical analyses, QMRA,

and modeling. 

4.4.6 Water Safety Plan Including BMPs 

The development of water safety plans is recommended by the WHO (2004) and the 

Australian Drinking Water Guidelines (NH&MRC and NRMMC, 2004) as a means of 

identifying hazards and proactively managing them. In this context, the watershed is seen as the 

first barrier in the application of a “multi-barrier” approach to the control and minimization of 

risks to drinking water quality in a water supply system. To produce a water safety plan, it is 

essential to have knowledge of how the watershed is hydrologically linked, where the hazards 

arise, and where the critical control points are. This approach includes identifying possible 

sources and probability of contamination of a water supply and how to mitigate these effects. For 

example, by reducing direct access of livestock to water, an immediate reduction of microbial 

contamination is achieved. The application of this approach to the protection of water quality in 

inland waterbodies, which in many instances are both recreational and drinking water supplies is 

thus entirely consistent with WHO guidelines (WHO, 2004). However, it has yet to be 

demonstrated that BMPs can effectively reduce microbial loading of inland waters (Wood, 

2007). Further research is required to establish which BMPs are most effective at reducing 

microbial loadings before their implementation can be prioritized

4.5 Implementation Realities Group

4.5.1 Sampling 

Although the areas of concern on the Great Lakes and marine coastal waters are clearly 

defined – i.e., designated bathing beaches – such is rarely the case on inland flowing waters. The 

entire segment of the inland receiving water must be considered and, as a result, sites that require 

sampling may be hundreds of miles apart. These distances could have a significant impact on 

holding time for a bacteria sample and turnaround time for results. Standard methods require that 

transport time after a sample is collected to be no longer than 6 hours. After arrival at the 

laboratory, sample processing must begin within 2 hours. Studies investigating the impact of 

longer holding times on samples are needed. 

Another concern regarding sampling is what constitutes an appropriate sample for a 

flowing stream. Incorporation of stream bed dynamics on flow, mixing, and settling add 

complexity to inland waters relative to marine and Great Lakes beaches. These issues have not 

yet been addressed. A step toward resolution of this reality could begin with the USGS stream 
4-14 

classification system leading to stream characterization studies performed by trained personnel 

from the state (or territory). Development of appropriate sampling regimens for each stream type 

would then need to follow. 

4.5.2 Assessment 

Inland water flow and contamination dynamics are significantly influenced by wet 

weather/high flow events resulting in resuspension of sediment, and this sediment has a 

significant impact on the makeup and concentrations of microbial contaminants. Very basic 

research is lacking on methods for recovery of microorganisms from sediment, and there is even 

less of an understanding of the role sediment-associated FIB play in relation to health risks. 

Resuspension of environmental strains of FIB could lead to exceedances of standards – 

potentially without an associated health risk. This resuspension phenomenon in inland flowing 

waters especially could ultimately lead to more waters on the impaired list requiring resources 

directed at TMDL development in waters that might not be high priority for recreational users. 

Because agricultural land use is more predominant on inland watersheds, inland waters as 

a group may be affected more by loadings of FIB from nonhuman sources such as animal feces, 

and regrowth of FIB in the environment. Current knowledge of the potential for human 

pathogens to be emitted from nonhuman sources is inadequately characterized at this time.

One characteristic of inland flowing waters is that they are more “flashy” than waters at 

marine beaches and in the Great Lakes. Short-term hydrological spikes are common, and these 

often relate to short-term indicator spikes. The importance of these spikes to the recreating 

public’s health risk is virtually unknown but still could be important with respect to waterbody 

impairment listings.

4.5.3 Recreational Activities 

The types of recreational activities and density of recreational users on inland waters may 

differ from those at marine coastal beaches or in the Great Lakes. The realities associated with 

these different uses include the route and duration of exposure. For example, swimming may be 

less practical on inland waters because many of these waters are too shallow for whole body 

immersion. However, activities such as water and jet skiing, canoeing and kayaking, and water 

play by children may be much more common on inland waters. These activities, which are 

included in many state definitions of primary contact recreation, are likely to present different 

exposure scenarios than swimming, all of which add up to an unknown impact on health risks. 

Inland flowing waters are subject to periods when physical safety considerations (e.g., 

elevated flow) preclude or discourage recreational use. These periods often coincide with the 

greatest elevation in FIB levels. Failure to take into account or exclude these periods of physical 

safety on the diminished recreational use result in substantial overestimation of exposure to 

waterborne pathogens. Furthermore, a failure to account for the potentially extreme variation in 

pathogen levels under such conditions could also result in significant mischaracterization of 

health risk. 
WERF Inland Waters Workshop Report 4-15

4.5.4 Proximity to Source 

Typically, coastal recreation areas (e.g., beaches) have predominant sources of pathogens 

or indicators of pathogens located well upstream on watershed tributaries or otherwise far from 

shore (POTW outfalls). Conversely, recreational areas on inland waters can often be located in 

the immediate vicinity of the sources (e.g., animal feed lots, CSOs, or presence of animals in the 

water). Consequently, it should be noted in assessing risk in inland waters as opposed to marine 

coastal and Great Lakes studies that the survivability/signal loss between pathogens and 

indicators could be different based on distances from the source. These differences are not at all 

well defined. 

4.5.5 Degree of POTW Influence 

A reality in some cases, particularly in the arid west, is that the flow in inland water 

streams can be dominated by treated wastewater effluent. In other cases, these streams may be 

influenced by combined sewer overflows. These waters have a lower assimilative capacity of 

pathogen loading compared to Great Lake and marine beaches due to the lack of dilution and 

mixing factors. In other situations, it is possible for disinfected POTW effluent to dilute the 

indicator/pathogen concentration from upstream sources of a flowing stream. 

4.5.6 Potential Influence from Manure or Biosolids Spreading Activities 

Similar to POTW and CSO influence on inland waters, the potential for inland waters to 

be impacted by any uncontrolled runoff from manure piles, biosolids-spreading activities, or 

direct deposit of fecal material from wildlife in the water is much greater than in coastal waters. 

As described above, lower assimilative capacity, and greater mileage of potential recreational 

access, and proximity to the source are again likely to have an influence on exposure potential. 

4.5.7 Greater Chance of Flowing Waters That Are “Least Human Impacted” 

Waters in areas relatively unpopulated by humans, such as headwater streams and 

waterbodies in nature preserves, are more likely to be located inland than on the coast. Thus, 

there is a greater potential for the number of inland waters to have microbial contamination 

dominated by animal rather than anthropogenic sources. As a result, the risk from human 

pathogens would be lower and exposure/illness assumptions would be different if water quality 

were assessed using indicator organism densities based on microbial criteria generated at beaches 

impacted by human sources. In these situations, even though the relationships between health 

risk and water quality are not understood, the stream might still be classified as impaired. 

4.5.8 Implementation Issues That Might Be Different for Inland Waters 

Due to the widespread distribution of inland waters throughout the country, there is a 

greater possibility many of those waters are impacted by nonhuman sources – domestic animals, 

livestock, and wildlife. A reality is that it is critically important to understand the significance of 

the risk of nonhuman pathogens to the recreating public. Flexibility could be realized if 

nonhuman pathogens present more or less health risk, and criteria could be modified accordingly 

to maintain an equivalent risk level while adjusting the indicator value. This group suggests that 

QMRA could be worked in reverse to adjust numeric criteria if sufficient data existed to quantify 

nonhuman impacts. 
4-16 
WERF Inland Waters Workshop Report 5-1 

CHAPTER 5.0 

RESEARCH PRIORITIES

5.1 Suggested Research Needs and Justifications

Each of the groups was asked to address these two points: 

♦ whether there are critical knowledge gaps that could be addressed in the short term that may 

facilitate the development of national recreational water quality criteria for primary contact in 

inland waters

♦ which critical knowledge gaps should be addressed in the longer term and how. 

The following sections summarize their responses. 

5.1.1 Indicators and Pathogens Group 

The indicators and pathogens group identified research needs (italicized) and provided 

justification for those priorities (indented) as described below. 

Short-Term Research Needs

Examine relationships between Q-PCR and culture-based FIB and develop a database of results 

to date of other reliable potential new monitoring methods. 

The massive amount of data on and understanding of culturable FIB within beaches makes it 

imperative that we calibrate these two databases. Much historical effort will be lost 

otherwise, and, from a management perspective, the transition from a culture to a molecular 

based criterion will be more difficult.

Longer-Term Research Needs

Conduct studies on watershed assessment information to be used as input for site-specific water 

quality criteria.

Sanitary surveys that are watershed based and incorporate wildlife and environmental 

loadings are important to the understanding of stream and lake recreational water quality and 

criteria development. At present, those tools do not exist and are restricted to traditional 

approaches that only focus on human sources. A new paradigm needs to be developed that 

measures all major sources of indicators and pathogens in that water sample if we are to 

properly protect recreational usage of streams and inland waters. Development of good 

source tracking tools and better regression and numerical modeling approaches are critical to 

this undertaking. 

Investigate the potential for speciation of enterococci to identify fecal-specific strains (preferably 

human) from environmental strains, and then apply results to future epidemiologic studies. 
5-2 

Research to develop a robust method for speciation of enterococci with a view to identify 

fecal-specific strains from environmental strains is critical if we are to adequately apply QPCR techniques to recreational water quality. Enterococci species greatly differ in respect to 

their ecology, biology, origin, and potential relationship to human pathogens. Thus, by 

accepting “total enterococci,” both living and dead, as the indicator of fecal contamination 

we may repeat the erroneous use of past criteria based on total coliforms. Research studies to 

resolve this issue are imperative.

Conduct epidemiologic studies that take into account urban runoff and nonpoint sources of fecal 

contamination. Include the use of culture-based and molecular-based analytical methods. 

Include sensitive populations (particularly children). 

To date, most epidemiologic studies have been conducted at beaches contaminated by human 

point source effluents from nearby POTWs. However, many or most beaches in the United 

States (including popular ones) are influenced by predominately nonpoint sources of FIB 

including feces from human, domestic animals, wildlife as well as from nonfecal sources 

related to growth of FIB in the environment. Studies should be conducted to take into 

account rural, urban runoff and nonpoint sources to determine 1) if there are differences in 

risk from these contributions and 2) whether the same or different ambient water quality 

criteria should be applied to a variety of streams and inland waters. 

Conduct epidemiologic studies incorporating the measurement of pathogens of interest along 

with indicators to determine the correlations of these organisms and to better understand their 

associations with diseases at downstream recreational locations. 

The relationship of fecal indicators and pathogens is likely dependent on the sources of 

indicators. More information is needed on the correlation of indicators to pathogens in a 

variety of settings of inland waters. How these ratios change with changing landscapes, 

hydrometeorological conditions, land use practices, and with time is very important for the 

protection of the recreating public. These studies should be coupled with landscape studies, 

exploratory modeling, experimental manipulations such as hydrological simulations, 

limnological surveys, and source tracking. 

5.1.2 Health Risks Group

 The health risks group developed a prioritized list of research that could be completed 

in the short term and longer term using the following questions: 

1. How critical is the knowledge gap? 

2. How well can the data gap be addressed in the relevant time frames using targeted 

research studies? 

3. Could the research be effectively conducted with limited funding? 

 Using this approach, the health risk group identified four short-term research needs, and 

one research need to be identified in a 2- to 5-year time frame. The specific knowledge gaps and 

the research that would address them are summarized below. 
WERF Inland Waters Workshop Report 5-3 

Short-Term Research Needs

Optimize and anchor QMRA models to epidemiologic studies. 

Optimizing and anchoring QMRA models and model inputs can be accomplished by 

utilizing information about health risks obtained from epidemiologic studies. This can be 

done in two ways, based on the time frame of data collection: 1) retrospectively for prior 

epidemiologic studies, and 2) prospectively with all ongoing and future epidemiologic

studies. The basic concept is that QMRA models and methods can be evaluated based on 

their ability to accurately predict health risks obtained from epidemiologic studies. 

Existing models, methods, and inputs can be “tuned” to bring their predictions in close 

alignment with the risks observed in epidemiologic studies. Models and methods 

obtained from such an optimization process – those that reliably predict health risks for 

diverse conditions (marine/fresh, flowing/nonflowing, human/agricultural/urban 

runoff/etc. sources, flowing/quiescent) would be of greatest value for meeting public 

health and regulatory needs. 

1A: Retrospective QMRA research. There is a need to anchor QMRA to previously 

conducted epidemiologic studies. At relatively little cost, data from such epidemiologic 

studies could be mined, and exposures and sources reconstructed to the degree possible. 

Such information could be used in QMRA models, which could be adjusted as needed so 

that modeled risks are equivalent (within an acceptable range of uncertainty) to the risks 

observed in the epidemiologic studies. 

1B: Prospective QMRA research. QMRA should be considered in the design of future 

epidemiologic studies. Epidemiologists, hydrologists, microbiologists, molecular 

biologists, exposure measurement researchers, and risk assessment experts should 

collaborate in the development of study protocols. Methods to measure exposures, 

characterize and apportion sources, and identify pathogens responsible for disease should 

be developed, validated, optimized, and standardized. Future epidemiologic studies 

should incorporate such methods. As described above, QMRA should then be anchored 

to each future epidemiologic study, so that models and methods may be evaluated by 

their ability to predict the health risks observed in the epidemiologic studies. Such 

anchoring of QMRA approaches would enhance confidence in their findings and 

scientific credibility when extended to different settings. 

Incorporate source characterization methods into ongoing epidemiologic studies. 

Previous epidemiologic studies generally were not designed to derive source-specific 

water quality/health risk relationships. Incorporation of source characterization methods 

into ongoing epidemiologic studies is a research need that, if it is to be met, must be 

addressed immediately. Some of the epidemiologic studies for collecting data during the 

2009 water recreation season will apparently evaluate sources of pollutants, but every 

effort should be made to ensure that all such studies utilize the best available source 

characterization methods. At the most basic level, a sanitary survey should be conducted, 

ideally utilizing a standardized approach (such as that developed by the U.S. EPA for use 

at Great Lakes beaches). A more sophisticated (and perhaps more informative) approach 

could include the use of molecular methods to identify and quantify pathogens (Q-PCR, 
5-4 

genotyping, speciation, sequencing) and the entire suite of molecular options available 

for microbial source tracking. Measuring fluxes of microbial pollution has been 

completed in Quantitative Microbial Source Apportionment studies world-wide and this 

would offer the best empirical policy evidence base of sources if implemented in parallel 

with epidemiologic site investigations (Stapleton et al., 2008). Utilizing these approaches, 

sources of microbial pollutants could be apportioned to humans, agricultural animals, 

domestic animals, birds, and other wildlife. Results of such studies will advance our 

ability to identify possible differences in risk attributable to differences in sources. 

Optimize and standardize Q-PCR methods and enhance their interpretation. 

Research to compare protocols across laboratories (in a “round robin” or “ring trial” type 

procedure) is essential to standardize the methods of health research studies that employ 

Q-PCR methods. Such standardization would be required for implementation purposes as 

well. Optimizing specific elements of the protocols could lead to improved precision, 

accuracy, and sensitivity. These improvements could, in turn, yield more precise, 

accurate, and sensitive estimates of the health risks of water recreation in inland (and 

other) waters. These improvements, as well as the development of conditional probability 

approaches to analysis of MST data, would benefit QMRA approaches. 

Identifying molecular markers that are robust predictors of human and various animal 

sources using Q-PCR is another critical research need. Improving our understanding of 

the persistence of microbial nucleic acids, and the relationship between cell-based and 

cell-independent targets is important. Characterizing the persistence of DNA-specific 

targets, be they general indicators, source identifiers, or pathogens, must be studied in a 

variety of environmental settings and by considering the fate of molecular target 

sequence both inside and outside the bacterial cell.

Conduct meta-analysis of epidemiologic studies by source. 

A number of meta-analyses of epidemiologic studies of indicator organisms and 

recreational health risks are available. These studies have focused on establishing a 

robust linkage between indicator organisms and health outcomes, identifying the most 

appropriate indicator organisms, and comparing associations found in marine water with 

those found in freshwater. As indicated previously, epidemiologic studies have been 

conducted in settings with a range of sources. For example, studies conducted in New 

Zealand (McBride et al., 1998) and Hong Kong (Cheung et al., 1990) included humanimpacted and agricultural animal-impacted marine sites. U.S. EPA studies during the 

later 1970s and early 1980s (USEPA, 1983, 1984) included sites heavily impacted by 

human wastewater as well as sites without such impacts. The Mission Bay study (Colford 

et al., 2007) includes a marine site without significant point sources, whereas the Santa 

Monica Bay study (Haile et al., 1999) includes a stormwater/runoff-impacted site. Studies 

conducted in the UK were heavily impacted by wastewater (Kay et al., 1994; Lee et al., 

1997) or contained different sites with and without such impacts. Studies of both 

quiescent and (slightly) flowing freshwater in Germany had POTW sources, urban 

runoff, and/or agricultural sources (Wiedenmann et al., 2006). POTW-impacted flowing 
WERF Inland Waters Workshop Report 5-5 

waters were studied in France (Ferley et al., 1989) and human-impacted quiescent waters

were studied in the Netherlands (van Asperen et al., 1998). 

Large studies, designed to develop quantitative, source-specific relationships between 

microbial measures of water quality and health risk, have not been reported. The studies 

noted above that did enroll participants at sites with different types of sources, likely 

lacked the statistical power needed to evaluate such effect modification by source. One 

approach that could evaluate such effect modification would involve a meta-analysis of 

the epidemiologic studies conducted to date. Unlike the previously conducted metaanalyses, such a meta-analysis would be stratified by source (i.e., treated but 

undisinfected POTW discharge, disinfected POTW discharge, agricultural animals, urban 

runoff, birds, and other wildlife). Such stratification would be based on information 

contained in the published studies, as well as that which could be obtained by 

communicating with those individuals who conducted the original research. In the near 

term, published results of NEEAR study marine beaches and randomized controlled trials 

on the Danube and Tisza Rivers are anticipated and should be included in the proposed 

meta-analysis. Data sharing on the part of the U.S. EPA and the European investigators 

would help in the retrospective characterization of sources in these studies. Further 

differentiating sources by water type (flowing, quiescent, coastal, marine) would be 

beneficial and might suggest the relative importance of water type versus source as 

modifiers of health risks. The health risks group recognized that the amount of 

information that would allow accurate categorization of sources may be limited for many 

of the studies, particularly those published decades ago. Given the relatively small 

number of published studies and the large number of source-water type combinations, 

such source-site interactions are not expected to reach statistical significance, but 

nevertheless should be attempted. 

Longer-Term Research Needs

Conduct further epidemiologic research to identify how much uncertainty exists in using the 

results of epidemiologic studies conducted in Great Lakes and coastal settings to establish 

criteria for inland flowing waters. 

The group was unanimous in agreeing that additional epidemiologic studies were the 

single highest longer-term priority research need. Such studies are needed to answer the 

question at hand: how much uncertainty is there in using the results of epidemiologic 

studies conducted in Great Lakes and coastal settings to establish criteria for inland 

flowing waters? Specifically, the use of the NEEAR study design and methods at a 

flowing and a nonflowing inland water site would reduce that uncertainty. Nevertheless,

substantial uncertainty would remain about applying findings of such studies to all inland 

waters sites. The major component of that uncertainty is thought to be variability of 

sources across inland water sites. For this reason, although an epidemiologic study on an 

inland water would narrow the data gap, this group anticipates the persistence of 

questions regarding applying results of a study at one inland site to others. Members of 

the group went so far as to say that the variability of risks across inland flowing waters

settings is likely substantially greater than the variability of risk between inland flowing 

waters and Great Lakes coastal settings. For these reasons, this group recommends 

targeted epidemiologic studies be conducted at the first available opportunity that would 
5-6 

evaluate risks of inland flowing and quiescent waters at several sites, each with a single 

predominant source type of fecal pollution (birds, other wildlife, POTW effluent, 

agricultural drainage, and urban runoff). By establishing whether or how the water 

quality/health risk relationship (change in health risk expected for a given change in 

microbial water quality) is modified by source type, it would be possible to assess the 

level of public health protection afforded by a single regulatory standard or criterion. 

Additionally, such studies would shed light on the question of whether criteria could be 

more rationally applied following a relatively basic sanitary survey.

5.1.3 Water Matrix Group 

The water matrix group grouped their research priorities into shorter and longer time 

frames and provided justification for those priorities as described below. 

Short-Term Research Needs

Apply model-driven nowcasting and/or forecasting in current epidemiologic studies to determine 

a relationship of model variables to health outcome. (Note: This is currently being undertaken 

for the Avalon study.) 

Further develop and test regression models in inland waters (at rivers with different 

morphologies from those in Ohio, Georgia, and Kansas). 

Focus on prior epidemiologic studies to build models after the fact and compare the results from 

such retrospective models to the observed human health effects. 

Include an in-depth evaluation of target microbe/pathogen sources and environmental conditions 

in epidemiologic studies to evaluate the sources and parameters needed for coupling health 

outcomes with model output. 

Evaluate reverse QMRA for its applicability in the development of site-specific criteria.

Apply data mining activities to identify data gaps that limit application of models and identify 

longer-term research goals. 

Longer-Term Research Needs

Use modeling approaches to characterize source impacts as an integral part of the design of all 

recreational water epidemiology studies. 

1. Design and implement epidemiology studies specifically to incorporate models and to 

understand the link with health outcome(s). 

2. Integrate modeling components (e.g., QMRA, regression models, and mechanistic 

models) to all future epidemiology studies so as to better describe source contributions 

and aid in result extrapolation. 

3. To evaluate the sources and parameters needed for coupling to measured health 

outcomes, develop methods to include in-depth evaluation of microbe sources and 

measurement of physical-chemical-hydrologic parameters that impact the fate and 

transport of microbes (rainfall, UV light, wind, etc.) for future epidemiology studies. 
WERF Inland Waters Workshop Report 5-7 

Further develop and test regression models in all types of inland waters, to clarify their 

applicability, limits, and future research needs. 

Focus on developing the fundamental understanding and knowledge needed for establishing 

mechanistic models. 

Because of the advantages in being able to extrapolate to a range of site situations with the 

model-driven mechanistic approach, the following research efforts should be considered: 

♦ evaluating the microbial loads associated with different sources, especially nonpoint sources 

♦ identifying and quantifying the factors affecting the transport of key microbes from their 

point of land deposition to the waterbody and within the waterbody 

♦ identifying and quantifying the factors affecting the fate of microbes, including an evaluation 

of physical-chemical factors that influence their detectable levels and viability/infectivity in 

the environment 

♦ addressing differences between flowing and nonflowing waters in terms of the fate and 

transport of pathogens and indicators associated with colloidal/particulate matter

♦ evaluating the effect of sunlight and organic matter on the fate of pathogens and indicators in 

flowing water

♦ evaluating data gaps identified during data mining and design research programs to fill those 

gaps

♦ assessing the role of sediments as a reservoir and potential environment for regrowth of fecal 

indicator organisms and pathogens in flowing waters as opposed to lakes. For example, 

sediment characteristics (e.g., particle size, organic content) that may influence 

persistence/regrowth. 

5.1.4 Sources Group

The fecal contamination sources group provided a table to summarize their research 

priorities. Their research priority table (Table 5-1) identifies whether the research is intended for 

the short or longer term, provides a title for the research topic, summarizes the scope of the 

research, and provides a justification and approximate time frame for the research. 
5-8 

Table 5-1. Research Priorities for Fecal Contamination Sources Group. 

Priority Title Scope Justification

Short term Pathogenic potential of 

agricultural and wildlife 

feces

Identify and quantify human pathogens 

in animal feces. 

Not adequately characterized

Short term Quantify impact of 

onsite sewage 

treatment systems on 

microbial water quality

Identify and quantify human pathogens 

in various types of onsite systems, 

especially during wet weather and 

including disinfection efficacy of 

systems and their rate of failure.

Risk with these systems and 

particularly the cumulative 

effect is unknown

Longer term Fate and transport of 

animal pathogens in 

relation to indicators

Identify fate and transport of important 

pathogens identified in short-term 

priority #1.

Not adequately characterized;

Apply to model development

Longer term Epidemiologic studies 

in inland waters

Include agricultural, NPS runoff, 

measure pathogens identified in shortterm priority #1. 

No such study has been 

conducted in U.S. inland 

waters

Longer term Characterization of 

land-use and sanitary 

surveys 

Define consistent template and 

quantify important inputs. 

Enables accurate identification 

and quantification of hazards 

and enables prediction of 

inland water quality via 

incorporation of this information 

into QMRA and numerical 

models

Longer term Water safety plans 

including effectiveness 

of BMPs

Determine recreational component of 

water safety plans involving U.S. EPA, 

utilities, scientists, and community 

collaboration. 

Undertake research to quantify 

effectiveness of various BMPs and 

their applicability to various watershed 

scenarios.

Garner stakeholder buy-in for 

source water protection that 

enables multiple water uses, 

with pollution reduction, and 

enhanced public perception

5.1.5 Implementation Realities Group 

The implementation realities group identified a number of research topics and issues 

related to the implementation of new or revised water quality criteria that could be addressed in 

the short (next 18 months) and longer term. Those research topics and implementation issues are 

summarized below. 

Short-Term Research Needs

Perform analyses of all existing inland water epidemiologic data (domestic and international) 

including multiple sub-analyses (e.g., flowing versus quiescent, source type, relationships 

between indicators, relationships of indicators to human health risk).

This recommendation is similar to the meta-analysis suggestion from the health risks 

group. However, the implementation realities group also highlighted the fact that E. coli

is a top priority for states and utilities.

Develop more science to understand regrowth and/or resuspension of enterococci in sediment of 

inland flowing waters.
WERF Inland Waters Workshop Report 5-9 

Research the effects of prolonged holding times on microbiological analytical results. 

Develop early communication on aspects and/or options of implementation guidance and 

national-level expectations in terms of adoption for inland waters. 

Use longer averaging periods for assessment purposes to deemphasize short-term excursions. 

This approach for implementation would not be of value, however, if the goal of the 

criteria is to identify acute conditions with an immediate health impact. Under those 

criteria, short-term excursions would be more important. 

Consider modification or use suspensions during defined high-flow conditions; 

Consider developing site-specific criteria based on QMRA or other methods. 

QMRA may hold the key to adjusting criteria while maintaining an equivalent level 

of risk. 

Designate a new use (or uses) based on physical waterbody characteristics and/or the types of 

activities that a waterbody is used for (shallow water use or secondary contact use).

Related to this need is the situation in which the highest attainable use of inland waters is 

not primary contact. In such cases, secondary contact recreation should be the designated 

use. There is a need for scientifically defensible criteria that are protective of secondary 

contact uses. Guidance is needed to assist states and others in developing scientifically 

sound criteria that are protective of secondary contact uses. 

Develop a guidance document to facilitate criteria adoption by states.

The guidance document should be as comprehensive as possible and include issues such 

as the following: 

♦ approved standard methods for new indicators (where new methods are to be used in 

permitting, wastewater methods must be available) including logistical considerations 

(e.g., holding time, capabilities of small discharges)

♦ sampling and analytical training

♦ lab certification for new methods. 

Longer-Term Research Needs

Develop data to quantify risk in waters impacted by nonhuman sources. 

Develop a flowing water sample design based on stream characteristics. 

Develop a translation between current criteria and any new criteria. 

Standardize methods including an evaluation of method robustness and a certification program 

for regulated laboratories. 
5-10 

Conduct studies evaluating the impact of sediment-borne resuspension events especially during 

high flow periods. 

Under these types of conditions it is thought that release of environmental strains of FIB 

could dominate and be associated with low health risk. If this is the case, results could 

lead to criteria modification. Use of this modification depends heavily on whether studies 

indicate resuspended sediment does not correlate to increased pathogen density. 

Conduct studies to determine appropriate indicators for each CWA purpose and a method to 

bridge current assessment criteria and methodologies to new ones. 

Develop data on pathogens/infectivity and exposure information for input to site-specific QMRA 

models. 

The use of a QMRA model to derive a site-specific or categorical water quality criterion 

could be based on the premise that risk is primarily related to the site specific source and 

recreational use. However, application of this paradigm to water quality assessment may 

also be valuable in terms of evaluating impairment.

Use QMRA for estimating health risks and developing appropriate and detailed exposure 

pathways for inland waters. 

The concept of watershed approaches including sanitary surveys, water activity use 

frequency, and water safety plans were discussed to be factored into a framework of 

QMRA model for waterbody-specific uses. Given the inherent variables in the QMRA 

that are subject to site differences, there is a need for exposure research (ingestion) 

related to inland flowing waters during recreational activities. The variables listed by this 

group as those that need to be considered are: exposure (body contact, ingestion, 

aerosolization), use (recreation in water v. recreation on the water, accessibility), and 

Source (human v. animal, bather load proportion in marine and Great Lakes beaches v. 

flowing waters).

5.2 Consolidation of Research Priorities across Groups

Review of the information provided by each of the Inland Water Workshop topical 

groups reveals that there were several common and overlapping themes among the research 

needs identified by the groups. Therefore, it appears reasonable to categorize the identified 

research needs into the following themes: 

♦ understanding the relationship between sources of fecal indicators and pathogens 

♦ retrospective evaluation of epidemiologic studies 

♦ microbiological method development or enhancement 

♦ enhancements to or recommendations for future epidemiologic studies 

♦ model development, enhancement, or both. 
WERF Inland Waters Workshop Report 5-11

The research activities that were recommended by the workshop participants are 

summarized by these themes in the Appendix as a series of tables (Tables A-1 through A-5). In 

those tables, research activities that are shaded grey are anticipated to require sufficient time 

such that the results are unlikely to be available to be incorporated into the current AWQC 

revision efforts (research must be complete by December 2010 to be included in the 2012 

revision to the AWQC). The group from which the idea was championed is identified in the 

table, although the descriptions combine related ideas from other groups. 

There were also a number of recommendations that could be fulfilled in a very short 

period of time by data mining exercises, literature reviews, or white papers. Because those 

activities are not specific research activities per se, they are included in a separate table 

(Table A-6). There were also a number of recommendations that relate to criteria development 

and/or implementation options and issues. Similar to the data mining exercises, literature 

reviews, and white papers, these criteria development or implementation-related activities are not 

specific research activities, per se. These criteria development and implementation options and 

issues are summarized in Table A-7. 

Obvious linkages among the recommended activities, options, or issues within and across 

tables are identified in the rightmost two columns of Tables A-1 through A-7. Other, more subtle 

dependencies and linkages clearly exist between research activities. The linkages demonstrate 

the multifaceted and interconnected nature of the science that may be needed in the short and 

longer term to address the questions at hand. 

5.3 Prioritized Research Recommendations

Topical group leaders from each of the workshop groups considered the relative 

importance and relevance of the research activities suggested by the participants. During a series 

of deliberations and discussions, they were asked to identify the highest priority short- and 

longer-term research activities that could be used to support the technical basis for new or 

revised AWQC. (Refer to Tables A-1 through A-7 columns entitled “IWW Topical Area 

Priority.”) Throughout these deliberations, it became clear that the options and issues that are 

presented in Table A-7 formed an important foundation and perspective from which the research 

needs were considered with respect to relative priority. From these deliberations, three short-term 

and two longer-term research activities emerged as the consensus opinion highest priority 

research activities from the Inland Water Workshop. A brief description of those activities is 

provided below. 

5.3.1 Highest-Priority Short-Term Research Activities 

Identify and quantify human pathogens in animal feces 

The primary purpose of this activity would be to quantitatively characterize the human 

pathogenic potential of agricultural and wildlife feces (zoonosis). This research activity would 

not only be useful within the context of understanding epidemiologic studies with predominant 

sources of contamination that are nonhuman, but also for understanding the potential risks to 

human health for a broad range of waters impacted by nonhuman sources. The data resulting 

from this activity could be used as input to QMRA models in the near term to aid in the 

derivation of appropriate AWQC and in the longer term within an implementation context for the 

derivation of site or waterbody-type specific AWQC.
5-12 

The sources group indicated that although zoonotic transmission of pathogens from 

animal sources to humans occurs, the extent to which it occurs is dependent upon the prevalence 

of human infectious strains of pathogens in animal species and the opportunity for exposure. 

Moreover, they indicated that there is a need to understand which animal hosts have human 

infectious strains of organisms and what the prevalence and excretion rates may be across 

diverse temporal and spatial bounds. Given that there is limited knowledge about the 

relationships between pathogen concentrations and FIB or other fecal indicators, such as 

coliphage, in each of these hosts, this type of research is of particular importance for determining 

the suitability of using indicator organisms as guidance for NPS-impacted inland waters. 

The implementation realities group indicated that there are many miles of inland water 

beaches that are likely to have a greater potential to have microbial contamination dominated by 

animal rather than anthropogenic sources. As a result, the associated health risks at these sites 

may or may not be accurately predicted by using the indicator–health relationships that were 

generated at beaches that were impacted by human sources. In these situations, health risk and 

water quality is not well characterized, and research is needed to better understand the health 

impacts associated with nonhuman fecal contamination. 

Examine relationships between Q-PCR and culture-based FIB 

Culture-based methods for FIB measure the fraction of culturable bacteria recovered by 

the method used. Q-PCR measures all fractions of FIB to include the culturable fraction, the 

stressed fraction not recovered by the culture method, the viable but non-culturable fraction, the 

killed or dead fraction, as well as the fraction of free nucleic acid. An improved understanding is 

needed of the persistence of microbial nucleic acids and the relationship between cell-based and 

cell-independent targets. Developing a better understanding of this relationship will require 

several avenues of research. 

Specifically related to Q-PCR, research is needed to optimize and standardize methods 

for current indicators and to enhance their interpretation. Research that would compare protocols 

across laboratories (in a “round robin” or “ring trial” type procedure) is essential to standardize 

the methods and demonstrate the robustness of the assay in various matrices. Optimizing specific 

elements of the protocols could lead to improved precision, accuracy, and sensitivity. Once the 

methods have been proven, they must then be used in epidemiologic studies where a relationship 

to health effects can be established. These improvements could, in turn, produce more precise, 

accurate, and sensitive estimates of the health risks of water recreation in inland (and other) 

waters and would benefit QMRA approaches. The development of conditional probability 

approaches to analysis of MST data would also benefit QMRA. Q-PCR work that is needed 

includes 

♦ persistence of DNA and cell-based targets

♦ optimization and standardization of Q-PCR in support of other objectives 

♦ design of additional animal-specific Q-PCR assays 

♦ validation of existing assays.

Another important and related area of needed research is methods development and 

validation for alternative indicators and pathogens for use in future U.S. EPA epidemiologic or 

QMRA studies. Characterizing the persistence of DNA-specific targets, be they general 
WERF Inland Waters Workshop Report 5-13

indicators, source identifiers, or pathogens, must be studied in a variety of environmental settings 

and should take into account the fate of molecular target sequence both inside and outside the 

bacterial cell. For example, the identification of molecular markers that are robust predictors of 

human and various animal sources using Q-PCR is critical. The role of the indicators and 

pathogen component in these studies is to identify and develop necessary methods for 

monitoring purposes. Potential (longer-term) promising research areas include, but are not 

limited to, fecal and nonfecal source-specific indicators, bacteriophage, ATP, viability-based 

molecular assays, and field-deployable automated systems.

Optimize and anchor QMRA models to observed health effects data obtained from 

epidemiologic studies and develop QMRA tools for implementation of new AWQC 

There is a significant need to understand how predictions from QMRA models relate to 

human health outcomes observed during epidemiology studies. This anchoring of the predictions 

from QMRA with epidemiologic observations will enhance the scientific credibility for using 

these techniques to predict recreational waterborne illness. Similar sentiments were echoed by all 

five groups albeit in slightly different terms. 

As indicated previously by the health risks group, optimizing and anchoring QMRA 

models and model inputs can be accomplished in two ways: 1) retrospectively for prior 

epidemiologic studies, and 2) prospectively with ongoing and future epidemiologic studies. 

QMRA models and methods can be evaluated based on their ability to accurately predict health 

risks observed during epidemiologic studies. Existing QMRA models, methods, and inputs can 

be “tuned” to bring their predictions in close alignment with the risks observed in epidemiologic 

studies. Models and methods obtained from such an optimization process would be of greatest 

value for meeting public health and regulatory needs. 

All groups believed QMRA should be considered in the design of future epidemiologic 

studies because it is important to understand the animal fecal sources to use as explanatory 

variables in both the epidemiologic and QMRA analyses and to adequately interpret the results. 

Methods to characterize and apportion sources and identify pathogens responsible for disease 

should be developed, validated, optimized, and standardized. As described above, QMRA should 

then be anchored to each future epidemiologic study, so that models and methods may be 

extended to settings for which epidemiologic data do not exist. 

The use of QMRA for both criteria development and implementation should be 

developed and articulated. One particularly promising potential application of QMRA is its use 

in “reverse” to develop site-specific criteria based on a defined health target. Default models and 

parameter values are needed for a wide range of waterbody types and fecal contamination 

sources.

5.3.2 Highest-Priority Longer-Term Research Activities 

Characterize fate and transport of animal pathogens in relation to indicators

Although animal densities and fecal excretion rates have a significant impact on the 

amount of material available for mobilization to inland waters during rainfall/runoff events, little 

information is known about these factors and how they vary across the United States. Similarly, 

the survival time of pathogens and indicators in different animal fecal matrices, soil, sediments 

and aquatic environments is not well understood. The ability for pathogens to survive in these
5-14 

various environments affects the potential risk associated with their subsequent transport into 

inland waters. Transport of pathogens to waterways is highly variable due to differences in 

rainfall/snowmelt, overland flow, drainage ditches (tile drains), slope, soil type, particle size, pH, 

impervious surface area, land use, and riparian areas (including vegetative type). Although 

several studies have examined some of the factors affecting pathogen transport mechanisms to 

waterways during runoff events further research is needed to elucidate them in sufficient detail to 

enable their incorporation into mechanistic models for predicting inland water quality. 

Conduct epidemiology studies in inland waters 

The scientific literature does not support direct comparisons of health risk as a function of 

recreational water quality in Great Lakes/coastal and inland waters. Given this information, there 

were diverse opinions among the workshop participants regarding the use of existing 

epidemiologic data for inland waters. Knowledge gaps regarding sources, effects of hydrology, 

and indicator–pathogen relationships in the context of health risks should also be addressed in 

future studies of health risk in or on recreational waters. 

The health risks group suggested that every effort should be made to fill the clear evidence 

gaps related to health risks associated with inland flowing waters with further epidemiologic

investigations. In fact, conducting future epidemiologic studies in inland waters was suggested in 

one way or another by all of the workshop groups. Moreover, enhancing future epidemiology 

studies to address the potential salient differences between inland and coastal waters and among 

inland waters was a unifying theme among the workshop groups. For example, suggestions from 

the various workshop groups included the following: 

♦ Epidemiologic studies in inland waters should separately include agricultural, NPS runoff, 

and POTW sources. 

♦ Epidemiologic studies in inland waters should include source characterization and microbial 

source apportionment. 

♦ Epidemiologic studies in inland waters should include standardized molecular methods to 

identify pathogens and their sources. 

♦ Epidemiologic studies in inland waters should be designed in parallel with QMRA and 

should clearly account for the pathogenic potential of agricultural and wildlife feces.

Epidemiologic studies are needed to answer directly the question at hand; that is, how 

much uncertainty is there in using the results of epidemiologic studies conducted in Great Lakes 

and coastal settings to establish criteria for inland flowing waters? Specifically, the use of the 

NEEAR study design and methods at flowing and nonflowing inland water sites would reduce 

that uncertainty. The major components of that uncertainty are thought to be variability of 

sources and variability of indicator–pathogen relationships across inland water sites. For this 

reason, although an epidemiologic study on an inland water would narrow the data gap, 

persistence of questions regarding applying results of a study at one inland site to others should 

be expected. Therefore, targeted epidemiologic studies should be conducted at the first available 

opportunity that would evaluate risks at inland flowing waters and quiescent waters at sites 

selected for the predominance of a single source type of fecal pollution. Such research should 

follow the NEEAR study design and be conducted at several sites, each dominated by fecal 

pollution predominantly from key sources. 
WERF Inland Waters Workshop Report A-1 

APPENDIX A 
Research Activity

IWW Subject 

Area Priority

Primary 

Group Timeframe

Linkage 

Within 

Category

Linkage to Other 

Category

Evaluate the pathogenic potential of agricultural and wildlife feces - 

Identify and quantify human pathogens in animal feces - Beyond the 

context of epidemiology studies 1 Sources 1-2 years

Develop data to quantify risk in waters impacted by non-human 

sources 1 Implementation < 2 years A

Future 

Epidemiology A-4:B

Quantify impact of on-site sewage treatment systems on microbial 

water quality - Identify and quantify human pathogens in smaller onsite systems, esp. wet weather 2 Sources 1-2 years

Develop tools so that future epidemiological studies can be 

accompanied by sanitary surveys and source characterizations to link 

risk and sources 3 Matrix < 2 years A

Retrospective 

Epidemiology A-2

Future 

Epidemiology A-4:C

Conduct sand/sediment sampling projects 4 Indicators < 2 years B

Develop studies to understand regrowth of FIB in sediment of inland 

flowing waters 2 Implementation > 2 years B

Characterize growth and regrowth of indicators and pathogens 1 Indicators > 2 years B

Understand fate and transport of animal pathogens in relation to 

indicators - Identify important fate and transport characteristics of 

important pathogens 1 Sources 2-5 years

Future 

Epidemiology A-4:A

Note: Under "Linkage Within Category", rows with entries in this column have linkages to other research activities in this table. Activities are grouped by letters A, B, 

 Under "Linkage to Other Category", rows with entries in this column have linkages to research activities in other tables, as identified. For example,

 "Future epidemiology A-4, B" refers to the research activities in group B of Table 4, "Enhancements to or Recommendations for Future Epidemiologic Studies"

Table A-1. Understanding the Relationship Between Sources of Fecal Indicators and Pathogens.
Table A-2. Retrospective Evaluation of Epidemiologic Studies. 

Research Activity

IWW Subject 

Area Priority

Primary 

Group Timeframe

Linkage 

Within 

Category

Linkage to Other 

Category

Optimize and anchor QMRA models and model inputs by using 

health effects data obtained from epidemiologic studies (include 

source risk attribution if possible) 1 Health 1-2 years A

Models A-5

Criteria Development 

A-7

Build "after-the-fact" regression models and compare results to 

observed human health effects directly 2 Matrix < 2 years

Perform analysis of all existing inland water epidemiology data 

internationally including multiple sub-analyses (e.g. flowing versus 

quiescent, source type, relationships between indicators, 

relationships of indicators to human health risk, etc.) - E. coli (via 

culture methods) is a top priority to states and utilities 3 Implementation 1-2 years B

Understand health risks in previous research relative to source:

- Classification of prior epi studies by source

- Stratified analyses of health risk by source 3 Health 1-2 years A,B Sources A-1
Table A-3. Microbiological Method Development or Enhancement.

Research Activity

IWW Subject 

Area Priority

Primary 

Group Timeframe

Linkage 

Within 

Category

Linkage to Other 

Category

Examine relationships between qPCR and culture-based FIB and develop a 

database of results to date 1 Indicators Short-term

Conduct QPCR Work including the following: 

- Persistence of DNA and cell-based targets 

- ID and quantification of human and animal sources 

- How qPCR is used in the context of QMRA and epi studies

- Optimization and standardization of qPCR in support of other objectives

- Design of additional animal-specific qPCR assays; validation of existing 

assays; conditional probability approaches to analysis of MST data for 

QMRA 1 Health 1-2 years

Conduct methods development and validation for current and alternative 

indicators and pathogens for use in future EPA epi or QMRA studies. The 

role of the indicators and pathogen component in these studies will be to 

identify and develop any necessary methods in support of these projects 

as well as for monitoring purposes. Include evaluation of:

- Fecal- and non fecal source-specific indicators 

- Bacteriophage

- ATP

- Viability-based molecular assays

- Field deployable automated systems 1 Indicators 1-2 years

Future 

Epidemiology A-4:C
Table A-4. Enhancements to or Recommendations for Future Epidemiologic Studies.

Research Activity

IWW Subject 

Area Priority

Primary 

Group Timeframe

Linkage 

Within 

Category

Linkage to Other 

Category

Apply regression model-based nowcasting/forecasting in current 

epidemiology studies to determine a relationship of model variables 

to health outcomes 1 matrix 1-2 years A

Conduct epidemiology studies in inland waters - Should include 

agricultural NPS runoff, and measure pathogens identified as high 

priority 1 Sources 5 years B Microbial Methods A-3

Conduct epidemiology studies in inland waters - Should include 

agricultural, NPS runoff, and POTW sources (all seperately) and 

include source tracking 1 Health 5 years B Microbial Methods A-3

Incorporate source characterization methods into ongoing 

epidemiologic studies (microbial source apportionment) - Should 

include using molecular methods to identify pathogens and their 

sources 1 Health >2 years C Microbial Methods A-3

Evaluate the pathogenic potential of agricultural and wildlife feces - 

Identify and quantify human pathogens in animal feces - in every 

epidemiology study 1 Sources 1-2 years C

Covered in other 

projects; Follow up to 

Microbial Methods A-3

Design future epidemiology studies in parallel with QMRA 1 Health >2 years C

Include modeling approaches as an integral components in the 

design of epidemiologic studies 2 matrix >2 years A
Table A-5. Model Development and/or Enhancement.

Research Activity

IWW Subject 

Area Priority

Primary 

Group Timeframe

Linkage 

Within 

Category

Linkage to Other 

Category

Further develop and test regression models in inland waters (at 

rivers with different morphologies from those in Ohio, Georgia, and 

Kansas) 1 Matrix Short-term A

Develop standardized protocol to use QMRA (in reverse) for the 

development of site-specific criteria 2 Matrix Short-term B

Retrospective 

Epidemiology A-2

Develop standardized QMRA procedures and define the default data 

that are needed (e.g., land use, source type) 2 Implementation Short-term B

 

7:B

Retrospective 

Epidemiology A-2

Further develop and test regression models in all types of inland 

waters 1 Matrix > 2 years A Data Mining A-6

Develop the fundamental understanding and knowledge needed for 

establishing mechanistic models 1 Matrix Longer-term
Research Activity

IWW Subject 

Area Priority

Primary 

Group Timeframe

Linkage 

Within 

Category

Linkage to Other 

Category

Conduct data mining to identify data gaps that limit application of 

models, and identify long term research goals Matrix Short-term

Prepare a consensus/position paper describing the detailed development 

of tool box approach and related implementation guidance Indicators Short-term Criteria Development A-7:B

Prepare a consensus/position paper describing the attributes of a robust 

indicator method for use in new or revised criteria Indicators Short-term

Note: These activities were not prioritized, rather the topic group leaders decided that these activities should be undertaken as part of the related research project.

Table A-6. Data Mining, Literature Reviews, and White Papers.
Research Activity

IWW Subject 

Area Priority

Primary 

Group Timeframe

Linkage 

Within 

Category

Linkage to Other 

Category

Prepare early communication products and outreach on aspects/options of 

implementation guidance and national-level expectations in terms of adoption for 

inland waters Implementation Short-term A

Develop provisions in the criteria that allow for use of tools (e.g. QMRA, other 

modeling approaches) to develop site-specific or categorical criteria or to support a 

designated use Implementation Short-term B Data Mining A-6

Prepare a guidance document that includes:

- Approved standard methods for new indicators (where new methods are to be used 

in permitting, wastewater methods must be available) including logistical 

considerations (e.g., holding time, capabilities of small discharges)

- Sampling and Analysis Training

- Lab Certification for new methods

- QMRA Training Implementation Short-term A

Consider watershed approaches, including microbial source characterization

- Standardized sanitary surveys

- Water safety plans as a potential component of new or revised criteria

- Advanced modeling approaches Indicators ?? B

Develop a standardized format for sanitary surveys - Define consistent template and 

quantify important inputs Sources 1-2 years B

EPA working on 

template for sanitary 

survery

Develop QMRA software package for use by non-QMRA professionals during 

implementation and for site specific criteria purposes Health Short-term B

Models A-5

Retrospective 

Epidemiology A-2

Develop plan to include "Water safety plan" including BMPs - Determine recreational 

component of water safety plan which includes agency, scientists, community 

collaboration Sources 3-5 years B

EPA working on 

template for sanitary 

survery

Note: Topic group leaders decided that these would not be treated as "research needs" but rather as context from which the research that is selected will need to be conducted.

Table A-7. Criteria Development/Implementation Options and Issues.
WERF Inland Waters Workshop Report R-1 

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