## 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 I NLAND 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

Step hen 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 Ba rtrand (lead) Clancy Environmental Consultants, Inc.
Mark Gibson Clancy Environmental Consultants, Inc. Jeffrey Rosen Clancy Environmental Consultants, Inc. Jeffrey Soller Soller Environmental, LLC

### U.S. Environmental Protection Agency

August 2010 iii Table of Contents

D ISCLAIMER

................................ ................................ ................................ ................................ .................. I A CKNOWLEDGEMENTS

................................ ................................ ................................ ............................... II L IST OF T ABLES

................................ ................................ ................................ ................................ .......... IV L IST OF F IGURES

................................ ................................ ................................ ................................ ........ IV A CRONYMS

................................ ................................ ................................ ................................ ................... V E XECUTIVE S UMMARY

................................ ................................ ................................ ................................ 1
1. I NTRODUCTION

................................ ................................ ................................ ................................ .... 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. Randomi zed Control Trials

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

................................ ................................ ................................ ................................ ..... 6
2. Q UALITATIVE C OMPARISON OF I NLAND AND C OASTAL S ETTINGS

................................ ................. 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. F ECAL I NDICATOR B ACTERIA S OURCES AND C ORRELATION WITH H EALTH E FFECTS IN I NLAND S ETTINGS

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

................................ .............................. 14
3.2. Non

- Epidemiological Studies of Inland Settings

................................ ................................ ...... 18
3.3. Summary

................................ ................................ ................................ ................................ ... 21
4. O CCURRENCE OF F ECAL I NDICATOR B ACTERIA IN I NLAND AND C OASTAL S ETTINGS

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

................................ ................................ ................................ .......................... 22
4.2. Event

- Scale Variability: Rainfall and Runoff

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

................................ ................................ ................................ .................... 30
4.2.2. Coast al Sites

................................ ................................ ................................ .................. 31
4.2.3. Summary: Event

- Scale Indicator Variability

................................ ................................ . 31
4.3. Summary

................................ ................................ ................................ ................................ ... 32
5. S URVIVAL OF F ECAL I NDICATOR B ACTERIA IN I NLAND AND C OASTAL S ETTINGS

...................... 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. I NDICATOR

- P ATHOGEN A SSOCIATION IN I NLAND AND C OASTAL S ETTINGS

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

................................ ................................ ...................... 44
6.2. Viruses and Fecal Indicators

................................ ................................ ................................ ..... 46
6.2.1. Co

- occur rence 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. R EFERENCES

................................ ................................ ................................ ................................ ...... 56
A PPENDIX A S UMMARY OF S TUDIES I DENTIFIED IN L ITERATURE R EVIEW

................................ ....... A

- 1
A PPENDIX B L ITERATURE S EARCH S TRATEGY AND R ESULTS

................................ .......................... B

- 36

### U.S. Environmental Protection Agency

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 Indica tor and Pathogen Loading at Inland Sites

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

................................ ............... 10 Figure 3. Resuspe nsion Phenomena: Inland Waters

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

................................ ................................ .. 13 Figure 5. Summary of Reported E. coli Dens ities in Various Water Types

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

...................... 27 Figure 7. Summar y 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 Fres h
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 Indic ator 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
Fre sh 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 f or 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

### U.S. Environmental Protection Agency

August 2010 v Acronyms

AODC acridine orange (stain) direct count AWQC ambient water quality crit eria
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 Wate r 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 mo st 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

### U.S. Environmental Protection Agency

August 2010 1 Executive Summary

This report evaluates whether the observed relationships between fecal indicator bacteria (FIB)
densities and adverse health effects for Great Lakes 1 waters are applicable to inland waters. Results suggest that the e pidemiological 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
descr ibed 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 hydrody namics between inland and coastal settings to evaluate the validity of extending health effects relationships developed from Great Lakes epidemiology studies 2 to inland flowing or impounded waters.

Qualitative Comparison of Inland and Coastal Settings

I nland 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 P OTW

- 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 Feder al 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 S ection 303(c) by a State for use for
swimming, bathing, surfing, or similar wa ter contact activities.

2 E pi demiological 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 ( a dapted
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 human s and animals excrete different densities of fecal indicator organisms and pathogens, fecal indicator densities in waters impacted by different sources indicate different

haza rds. 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 i ndicators in each of the settings independently. To evaluate these differences, indicator occurrence, survival/growth, and association with pathogens is compared for inland and

coastal waters.

### U.S. Environmental Protection Agency

August 2010 2 In contrast, significant differences exist in FIB loading betw een POTW

impacted coastal waters and non

POTW

- impacted inland waters. Physical and biological characteristics that are different in these two types of settings and that influence indicator performance include shading, hydrodynamics, potential for depositi on 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 wat er

— 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 anima ls) 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 exposur e 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

In land and Coastal Settings

### U.S. Environmental Protection Agency

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 perform ance relationships will not be similar. POTW

impacted waters receive continuous loading whereas loads to waters impacted by other fecal

sources are event

- driven.

o Non

- POTW fecal pollution sources vary widely among inland waters and in their association
of indicator densities with health effects. 3 The hydraulics of inland waters can differ from coastal waters in phenomena such as particle settling and suspension/resuspension mechanics. These characteristics can also impact the number and diversity of FI B 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 e valuated 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:10:1 016/j.watres.2010.07.064.

### U.S. Environmental Protection Agency

August 2010 4 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 revi sed 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 (WQS 4 ). The CPSP was developed, in part, based on feedback from a large gro up of stakeholders and the detailed input and recommendations from the scientific community provided in t he 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 Lakes 5 epidemiological 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 p erformance‖ 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

m icrobial ecology and persistence of FIB indicators and select pathogens.



### 1.2. Background

F ecal 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 feca l 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 bacteri a 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 beha vior, 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 develop ed. O nce approved by EPA, WQS are used for various CWA purposes and programs and are t he effective (enforceable) standards to protect waters for specified designated uses , such as ―primary contact recreation.‖ The
latter typically encompass es recreationa l 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 S ection 303(c) by a State for use for swimming, bathing, surfing, or similar water

contact activities.

### U.S. Environmental Protection Agency

August 2010 5 ―Traditional‖ indicators include culturable total coliforms, fecal (thermoto lerant) 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 f or 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 state s (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 Epidemiolog y 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 inf ections; 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 epidemi ology 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 a nd 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 feca l species of bacteria (see NRC, 2004 for further information). Thus, for convenience, this report uses the term enterococci unless otherwise noted.

### U.S. Environmental Protection Agency

August 2010 6 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 197 0s 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 P C 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 th e 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
Environment

s (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 a dopted 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 recreati onal 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 recrea tional 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 p repare 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 con ducted to address indicator performance in inland and coastal settings 7 that 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 fin alized in 2010.

7 Categorized in this report as coastal freshwater, coastal marine water, estuarine, inland flowing water m ain stem, inland flowing water in a small reach, or inland non

- flowing water.

### U.S. Environmental Protection Agency

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 a ssociation 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 compari son of measured decay rates. Lastly, Section 6 reviews indicator

- pathogen associations in inland and coastal settings.

### U.S. Environmental Protection Agency

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 compa res 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 setting s.)

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 p otential); 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 inf luence 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

- impac ted (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
occurri ng 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 whet her 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 fac tor 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 proportio nally 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 determinan t 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 notwithst anding, 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
charac terized 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 a s with distribution of fecal pollution sources among inland and coastal wate rs, 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 are as. 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 wate rs 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 wate rs 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

### U.S. Environmental Protection Agency

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]) effluen t, 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 s ewage 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 accid ental 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 i ndicators 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

- relate d 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 le sser 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 loadin g 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 f or 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 wate rs 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.

### U.S. Environmental Protection Agency

August 2010 11 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 particl e

- 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 M

echanics 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 impou nded 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. Th e 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 for esands. However, Olapade and colleagues showed that E. coli in the mats were seemingly not associated with exceedences of FIB

based beach closure criteria, despite the very high densities in the algal mats. Their mesocosm experiments demonstrated much hi gher 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., 19 99, 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, gro wth 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 per sistence 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 pe rsistence 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 particl es 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, F IB 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 dra w 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: Inl and Waters

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August 2010 13

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 setting s 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.

### U.S. Environmental Protection Agency

August 2010 14 3. Fecal Indicator Bacteria Sources and Correlation with Health Effects in Inla nd 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, epidemi ological studies of coastal waters with non

- human fecal impacts, and non

epidemiological studies such as QMRA and catchment modeling (non

- epidemiological). See Prüss (1998), USEPA (2009), Wade et al. (2003), WERF (2009), and Zmirou et al. (2003) for more comprehensive reviews of coastal and inland recreational water epidemiology studies. Notably, the WERF (2009) review and synthesis reported that all studies of water recreation and health effects identified higher rates of at least some self

- reported heal th 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
i ndicators 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 consti tute 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, thes e 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 F IB 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
huma n 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

### U.S. Environmental Protection Agency

August 2010 15 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 a reas (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 b y 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 res ulted in the relation:

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) comp ared 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 d id 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 enterococc i.

### U.S. Environmental Protection Agency

August 2010 16 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 a re 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 d epend 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, F

specific RNA bacteriophage, sulphite reducing clostridia, and
enteroviruses.

Variables signi ficantly 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 unlike ly).

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 p ristine. 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, f

resh

- water canoeists can be made ill by sewage contamination.‖

### U.S. Environmental Protection Agency

August 2010 17 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, swimm er 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 dens ity (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) us ed 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 st reptococci (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, Ae romonas , 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 setti ng (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 illnes s 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 mi les 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 Da ta 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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August 2010 18 3. site s 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 coa stal 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 il lness

indicator relationship in studies of inland waters not impacted by human sources (Calderon et al., 1991) and coastal waters not impacted by human sources (Colford et al., 2007; Fleisher et al., 2010). Again, the key features in all of these epidemio logy studies is a non

- human fecal pollution source, not an inland or coastal setting.

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

impacted Great Lakes waters to POTW

- impacted inland waters. They do not p rovide 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 obse rved 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 studi es 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 p ollution 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 n o 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

- swimme rs.



### 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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August 2010 19 As de scribed 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
i llnesses 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) . Th ose 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 stud ies 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 sour ces. 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 modeli ng 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 abilit y 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 individu al 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 t o 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, regr ession 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 l ess 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 auth ors 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 mo deling 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 receivin g 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 ar e lower in wildlife than in domestic livestock animals, with the exception of wildlife living in

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August 2010 20 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 transmiss ion between animals and as noted above, the prevalence of pathogens is often much higher in domestic species than in wildlife. Pathogens in livestock manures can persist for long periods in the environment, depending on the manure handling practices at a given operation. Fecal matter persistence is a special concern in cold

climate, where pathogens can persist throughout the winter to be released from land along with snow melt or during precipitation events. Land application requirements and best managem ent 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., cat s 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 sou rces 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 o rganism densities much lower than those of primary sewage or other human sources (NRC, 2004).

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August 2010 21 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 non

human. Both epidemiological and modeling studies indicate that fecal pollution source is the most important determinant of the relationship between indicator levels and health effects at a site. Because no epidemiological studies to date have demonstrated a relationship between illness and indicator level for sites impacted by non

- human fecal pollution, the mo st 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 indic ators 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. Althou gh 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 s ites 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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August 2010 22 4. Occu rrence 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 settin gs 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 coas tal 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 (whic h 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 , enterococ ci, 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 stud y 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 gr aphical 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 eq ual 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 f or 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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August 2010 23 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 va lues are based on data collected at 3 beaches on the

Mediterranean Sea

Gersberg et al. (2006) Coastal marine waters 14 wet

weather, 6 dry weather 2 yrs 41 601,000 MPN Samples taken at discharge of highly impacted river

Mill et al. (2006) Es tuary 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 13 5 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 geometri c

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 da y s interval, 1

- 2

mos Baseflow
mean = 6200 High flow

mean = 140,000 Membrane

filtration Land use is primarily livestock grazing, mu ltiple 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 ty pes

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 hu man 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 filtrat ion 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 Membr ane

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 report ed 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. (2 008) 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 buildi ng 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

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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 ar e 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 QPC R 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 e t al. (2006) Coastal marine waters 14 wet

weather, 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 becaus e 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) Inla nd 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. (200 6) 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)

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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 66 1 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 i n 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 y r 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 (Pittsbur gh)

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 (urba n 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 fil tration 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 mai nly 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 filtrat ion 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.

P etersen 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
filt ration 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) I nland 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

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August 2010 26 Table 5 . Studies of Fecal Streptococcus and Total C oliform

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

filtra tion 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 flowi ng

- 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) In land 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 7 2000 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 e t 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

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August 2010 27 Figure 5 . Summary of Reported E. coli Densities in Various Water Types (data shown are minimum, geometric mean, and maximum values).

Figure 6 . Summary of Rep orted Enterococci Densities in Various Water Types (data shown are minimum, geometric mean, and maximum values).

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August 2010 28 Figure 7 . Summary of Reported Fecal Coliform Densities in Various Water Types (data shown are minimum, geometric m ean, and maximum values).

Figure 8 . Summary of Reported Fecal Streptococcus Densities in Various Water Types (data shown are geometric mean values).

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August 2010 29 Figure 9 . Summary of Reported Total Coliform Dens ities 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. Never theless, 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. T he 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 regi mes 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
thei r 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, agric ultural 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 (inl and or coastal) or predominant source of fecal contamination.

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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 sand s 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 variabl es (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 conc entration 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 ur banized 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 e t 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 watersh eds 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 sedimentati on. 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 wa terbody 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 b etter 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 thei r 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 f or an estuary along the North Carolina coast, indicator organism (fecal coliform and Enterococcus ) density was significantly different after storms with net precipitation of

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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 th an 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 (M PN) 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 subsequen t 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 Gran d 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 hou rs 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
th an 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 stan dards. 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 a ssumed 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 su ch 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 e vent, 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 st orms, 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 organ ism 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.

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August 2010 32 Events account for a large fraction of indicator organism loadings to sourc e 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 s oil 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 whe n 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 t he 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 d uring storms due to loading from stormwater runoff, near

shore sands, and due to increased wave action and mobilization of indicators from sediments. Although dilution would presumably cause event

- scale variability to be of less significance at coastal si tes 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 variet y 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 w aters 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 precipi tation 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 c onduct 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 a pproaches (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 out falls 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, insuf ficient data are currently available to assess whether pathogen

- to

- indicator ratios (see Section 6) change differently during rainfall for inland and coastal sites.

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August 2010 33

5. Survival of Fecal Indicator Bacteria in Inland and Coastal Settings

In this section, th e 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. Surviva l 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 l iterature 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 th e experiment) followed by apparent first

order decay.

Figure 10 . Survival Curves for E. coli from in situ Mesocosm Experiments in Coastal Fresh
Waters. Open triangles denote counts from experiments in dark bags, filled inver ted 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 F igure 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; fill ed 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 f rom 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 behavi or 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 f requent 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; Okab e 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 availabili ty, 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 pr edator 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 i nsolation 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 c ooler 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 a nd 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 pathoge ns (one feature of an effective indicator) in coastal and inland settings.

8 In this report, decay constants are reported as

where k is decay constant (in units of d - 1 unless noted otherwise), C is indicator or pathogen density at time t , and

C 0 is the initial indicator or pathogen density (at t = 0). In other reports, decay rate constants are reported as

.

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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) gr ow 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, includin g 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 vi able, 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 hav e 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 thi s 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 t o 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. Tw o 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 ar e 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 e vents 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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August 2010 37 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 Bifidobacteri um 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 Labo ratory 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 w ith
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 Trop ical 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 co liforms 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 ti me 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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August 2010 38 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 fec al 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 natur ally 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 sa linity

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 d ecay 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 s uspensions of E. coli
and Salmonella spp. In situ experiments in diffusion chambers; growth and decay monitored during all 4 seasons and with and without predators and competition E. coli and Salmonella spp. grew in filtered and
unfiltered water for about 2 days after inoculation Decay rate after the growth period was much higher in unfiltered water than in filtered water

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August 2010 39 5.4. Comparison of Measured Decay Rates

To assess potential differences in decay related to setting, observed decay rates from mesocosm stu dies 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 correspon d 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 obse rvation 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 condition s 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 e t 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, p S , is given by

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

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August 2 010 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

Rang e (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 cal culated based on reported T 90 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 densiti es 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

an d 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 ra te 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‰

R hodes 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;
fi ltering water reduced removal rates significantly and resulted in growth for experiments conducted in July

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August 2 010 41 Study Setting Indicator Temperature
or Month Average or

Median Decay Rate (d - 1 ) Decay Rate

Rang e (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 conduc ted 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 labora tory 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 Ag ainst expectations, measured decay rates for transparent mesocosm studies greater at 90 cm depth than 45 cm depth and greater on variably cloudy days than sunny days

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August 2010 42 ,

where k

S is a solar radiation decay constant (m 2 /MJ), S is th e net incident solar radiation (MJ/m 2 ), and n S 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
- 1 for fresh wate r and
0.113 to 1.74 d
- 1 for 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 an d 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 amoun ts 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 Marin e Water Ent k min = 9.36 Low light intensity, T = 20° C
k

max = 119.5 Medium light intensity, T = 20° C Bordalo et al., 2002 ‡ Fresh Water Ent k min = 0.561 Dark, ambient temperature (Bangkok)
k

max = 1.354 Natural sunlight, ambient temperature

M arine Water Ent k min = 1.742 Dark, ambient temperature (Bangkok)
k

max = 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 prese nt, 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 k min = 0.115 Dark, cold, with sewage addition
k

max = 0.187 Dark, warm, with sewage add ition

Ent * k

s = 0.310

n s = 2.58 Natural sunlight, sewage added

Sinton et al., 1999 Marine Water Ent k

max = 0.115 Dark, warm, with sewage addition

Ent * k

s,max = 0.27

n s = 9.47 Natural sunlight, sewage added

Sinton et al., 2002 Fresh Water Ent k min = 0.288 Dark, temperature unknown
k

max = 0.403 Dark, temperature unknown

Ent * k

s,min = 0.110

n s = 1.0 Cold, wastewater stabilization pond inoculums

k s,max = 0.276

n s = 1.3 Warm, wastewater stabilization pond

inoculums
† Ent: enterococci ‡ Decay data reported as T 90 * Decay constant determined as a function of incident UV dose, with survival fraction given by ; in that
expression, k

s is decay rate constant (units of m 2 /MJ), n s is a constant (unitless), and S is net radiation dose (MJ/m 2 )

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August 2010 43 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
whethe r 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,
de cay 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. T he 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 se ems 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., coast al marine, inland flowing stream, inland non

flowing waters); differences in microbial ecology in different settings; and fluid dynamics of different settings

— turbulent kinetic energy and differences in the potential for resuspension.

Each of the above p henomena 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 sett ings.

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August 2010 44

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 me et 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 sett ings 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 or ganism 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 i n 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 populat ion); (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 repo rt 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 co rrelation 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 Massachuse tts (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 findi ngs, 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 Cryptospori dium
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 wash ed 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).

### U.S. Environmental Protection Agency

August 2010 45 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 o f 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 bot h 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 Giar

dia 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 concentrati on, 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 rain fall 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 t o 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 Cryptosporid ium partitions predominantly to particles in the size range 14.3 to 27.7 m while E. coli and enterococci partition predominantly to larger particles (> 63.3 m). With all other factors being equal, this indicates that removal of FIB from the water column by settling is greater than
that of Cryptosporidium (by a factor of 3 in the Brookes and colleagues study). One potential implication of this finding is that the fecal indicator

- Cryptosporidium ratio could differ between flowing and non

flowing waters (c oastal 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 st udy supports the conclusion that Cryptosporidium and Giardia loads are episodic and sporadic in all settings (inland flowing, inland non

flowing, and coastal). In contrast, indicator organisms have both increased sources and sources that are
more consiste nt. 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 stu dy, 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 influ ent 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.

### U.S. Environmental Protection Agency

August 2010 46 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 durin g 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 viru s [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 Vir uses 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 w ith suspended particles than that of fecal indicator organisms.

### U.S. Environmental Protection Agency

August 2010 47 As described below, these observations indicate significant differences between environmental behavior of enteric viruses and FIB, including seasonal variations, possible different trends i n 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 wat ers 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 lar ge 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
den sities 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 log

normal distribution seems reasonable. Enterovirus d ata 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

co rrelated 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 concentrat ion.

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 se ason 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 simi lar 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 obser vations 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 en terovirus. 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 temper ature 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 ent erovirus, 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 betw een indicators ( E.

### U.S. Environmental Protection Agency

August 2010 48 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 wit h 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 regi on 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 o f 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 Fer nández

- 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 s tation 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 d ifferent 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. col i 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 marin e 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

### U.S. Environmental Protection Agency

August 2010 49 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, t he 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 concent rations 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.

### U.S. Environmental Protection Agency

August 2010 50

6.2.1.4. Summary of Co

- occurrence and Correl ation 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 sou rces 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 indica tor organism density and HAV concentration do not appear valid

— particularly in the case of streams

— where spatial and temporal trends in the indicators and pathogen differ. These observations are consistent with observations on co

occurrence of fecal indic ator 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) i ndicate
rotavirus inactivation follows first

- order kinetics, with T 90 (the time to reduce the density by 90% [i.e., time for 1 log 10 removal]) of approximately 30 days in fresh water. In that study, the authors demonstrated that significantly higher UV do ses 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 (l ake water) but not the other (creek water). Decay rates (calculated assuming first

- order decay) for the lake and creek
water were 0.139 d
- 1 and 0.237 d
- 1 , respectively, for experiments performed at 20° C. The authors speculated that the difference in dec ay 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, sim ian 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 som e experiments conducted in fresh waters. Survival during the first two days was similar in all waters studied (T 99 ~2 to 3 days for all waters). After 3 days, decay rate reduced drastically in freshwater but not in estuarine water, though
within the sal inity 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 presum ably 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
dur ing 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.

### U.S. Environmental Protection Agency

August 2010 51 Figure 15 . Inactiv ation 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: Reprint ed, 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 sho ulders nor tails, as seen in Figure 16 from O’Brien and Newman (1977). Similarly rapid inactivation (T 90 < 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 hi gh 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 wat ers, 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

ent eric 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).

### U.S. Environmental Protection Agency

August 2010 52 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 . S ummary 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

Adenovi rus 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 2.36 a O’Brien a nd Newman, 1977

Poliovirus 1 Stream/inland 25 1.78 a 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.

### U.S. Environmental Protection Agency

August 2010 53 6.3. Bacterial Pathogens and Indicators

One factor that favors the association of FIB with bacterial pat hogens 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 bu t 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 differ ent 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 wi th 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 ve rsa, 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 pre valence 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 wate rs 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 (bot h 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

- occurre nce was observed of E. coli O157,
Salmonella , and Campylobacter . Among 406 samples analyzed for these pathogenic bacteria, only 3 samples were positive for both Salmonella and E. coli O157. A similar lack of co

- occurrence was observed for Salmonella and E. coli O157 with Campylobacter . Because inland flowing, inland non

flowing, and coastal waters are all subject to temporally

- variable pathogen loads from multiple, diverse sources, the above results offer no clear difference in anticipated FIB ability to predict bacterial pathogen occurrence and concentration in those settings.

Touron et al. (2007) had mixed success relating Salmonella spp. concentration to FIB (fecal coliform, E. coli , or enterococci) concentration. In their study of the Seine estuary in France, they found a strong
correlation between Salmonella and all three of these indicators at a station located in an upstream portion of the estuary. They also found a correlation between Salmonella and enterococci at the mouth of the estuary. Nota bly, 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 resear chers 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 wa ter (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.

Experi mental 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 i n waters collected from non

- flowing inland sources

### U.S. Environmental Protection Agency

August 2010 54 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 log 10 ) 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 non

flowing source (Vital et al., 2008). Although growth was observed under the same conditions for an
envi ronmental 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 esta blish 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 tho se 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 sedim ents, Craig et al. determined the decay rate to be

- 0.78 d
- 1 at 20° C. Maki and Hicks (2002) observed the decay rate of S. typhimurium varied between 0.226 and 0.511 d
- 1 in 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 differen t 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 wate rs 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 inl and 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, pathoge n 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

### U.S. Environmental Protection Agency

August 2010 55 fate and transport characteristics than indicator organisms. Beca use 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 follo wing 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 an d 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

.

### U.S. Environmental Protection Agency

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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) Environ mental 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 chai n 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 f ragilis ; 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 call ed fecal streptococci or FS) Pathogens

– Adv: adenovirus; AH: Aeromonas hydrophila ; Campy: Campylobacter; Crypto: Cryptosporidium ; EV: enteric virus; HAV: Hepatitis A Virus; HP: Helicobacter pylori ; PA: Pseudomonas aeruginosa ; PS: Plesiomonas shigelloides ; PV: Poliovirus; Salm: Salmonella ; Shig: Shigella ; VP: Vibrio parahaemolyticus Study Type

– A: observation/occurrence; B: laboratory microcosm study; C: in situ mesocosm study; D: MST (microbial source tracking) study; E: methods development or evaluation study; F: comparison of indicators; G: modeling study; H: epidemiological study; I: review paper; J: Other

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay Data?

Watershed Description Note(s) Ahn et al.,
2005 M C Sub WC TC, FC, Ent,
EC F+ coli

phage Adv,

EV A 17 stations in

the surfzone

– water samples collected 5 days during weekdays No Large urban watershed (Santa Ana River, CA) Stormwater runoff fr om 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

stu dies 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 hu mans FIB concentrations related to rainfall events

Baums et al., 2007 F,

M C Trop WC,
Sed EC,

Ent Bacter

ioides Shig 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 Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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,
G No 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 pur poses Models limited to describe bacterial life cycles and determine bacteria concentrations during

extreme events

Benhan et al., 2005 F IF Temp WC EC G No Primarily rural stream in VA; pasture is the main land use (49%);
residential and urban uses

acc ount 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 M C Temp WC Bacter

- oides
Prevotella E,
A Six 1 L water samples No Samples obt ained 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,

F C,
IF Tropic WC FC,
EC CP,

BF,
FRNA phage A No Unspeci fied 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 M C 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 influe nced

### August 2010 A

- 3

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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 E C Temp WC,
Sed Not

speci

- fied A,
G No 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

a l., 2005 F 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

p asture 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 M C Sub WC,
Sed FC,

Ent,
EC A,
D Two sampling

ev ents: 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

st orm 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) P S,

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 sit e, 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 Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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 N ot

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,

C Temp Sed,

Soil EC A Weekly samples
were taken from 14 sites along
coastal stream
from June

- November 1 999
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,

C Temp Sed,

soil EC A Monthly sampling
b etween 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,

F C,
IN Temp WC TC, FC, Ent,
EC Male

specific
coli

- phage,
CP A H,

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 a t 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 extramur al 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 Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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 HPC A Summer samplin g 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 an d 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 be haves 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* M C 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

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Watershed Description Note(s) (Adv serotype 40); i nactivation
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 nutrie nt 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

- al gae 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 an d
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,

e nvironmental 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

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Watershed Description Note(s) was sporadic Clark et al.,
2008 E,

M C 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

Measur ed 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 additi onal 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 F U U U None Crypto, EC O157, Salm, Campy,
Giardia

, Rota

- virus,
Noro

- vi rus 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 predic tions 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* F U Temp U FC, EC,
Ent CP,

somatic coliphage
mal e

- 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

gene rally 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 season al with higher levels in summer

### August 2010 A

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Watershed Description Note(s)
Colford et al., 2007 M C 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

p er 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 M C Sub WC,
Sed EC

En t 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 a nd 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 M C 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 rai nfall 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, ra infall 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

co ncentrations

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Watershed Description Note(s) Crysup and Mott, 2001* F,

E IF Temp U 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 temperat ure; 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 stan dards 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.,
200 8 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
in tensively 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 l aboratory
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 concentrati ons 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

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Watershed Description Note(s)

ococcus

aureus conducted
summers 2001

- 2003 sp ecified (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,

E IF 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* E C 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 La uderdale,
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 co nditions 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 gene rally a more
stable indicator
Donisson et al., 2004 F IF Temp WC EC A 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 o f land use, with highest
bacterial counts in summer and autumn and lowest in winter and early spring

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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

wate r 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

- associ ated 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
recreation al 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 pa sture (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 betw een 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 1 991 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

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Watershed Description Note(s) Elmir et al.,
2007 M C 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
de signing 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 s ignificantly between bathing episodes

Evanson and Ambrose,
2006 M,

E C 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 ei ther 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 s amples 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 t hose 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
Differenc es between the two wetland sites may be due to sediment differences (organic content

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Watershed Description Note(s) and finer grain size) Ferguson et al., 1996 E C Temp WC,
Sed FC, FS

(Ent) CP,

F

- RNA phage Aero

-

monas spp, EV Crypto,
Giardia

, Salm A,

F Water and
sediment samples
coll ected 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 produc tion 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 incr eased 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 U U U U 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 p H, 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 tre atment; 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
i ndicators 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

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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, a lthough 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
W WTPs 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 pastur es 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 demonstrat es 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 prec ipitation, and turbidity Transport and occurrence of Bacteroides and EC primarily due to runoff

Gersberg et al., 2006 F,

M C 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 Coliphage A 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) re c/ambient water quality criteria

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Watershed Description Note(s) tributary sites during low flow
conditions on
M ay 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 an other tributary Sediments do not appear to be a substantial
source of bacteria relative to WC concentrations

Gronewald et al., 2008 E IF Temp WC FC G Not specified No Used FC data from shellfish harvesting
waters in the obtained for Newport River Estuar y, 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/c riteria Hall et al.,
2007* F IF Temp WC FC A 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 Cree k 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

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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 F C 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 dee p) 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

st andards 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 M C Sub WC TC,
F C,
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 Coast al 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

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Watershed Description Note(s) taken from eight locations along
the shoreline at
each beach million visitor s yearly lapse after a rai n event, or channel flow rate all were factors that significant impacted FIB distribution in the shoreline water quality

He et al.,
2007 F C Sub WC,
Sed TC,

FC, EC,
Ent A Samples taken from randomly
selected sites in
streams/ creeks (500 samples) No 1 0 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 wat er, 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 w ater temperature and to decrease with increasing water salinity

Heilman,
2000 F,

E C 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
stand ard 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 temperatur e 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 s ources 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 aft er 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,

M IF, 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

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Study Type(s)

Frequency and

Period of
Observations

D ecay Data?

Watershed Description Note(s)
C water sampled Experiments
conducted in
la boratory

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 t he 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 La kes 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 cons istently 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
recreatio nal 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 low

flow conditions
No statis tically 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 an d the Virginia instantaneous

water

- quality standard for EC frequently
exceeded Low EC concentrations in springs as well

### August 2010 A

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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 a nd 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
leac hate, 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., 2 005 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 o f 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 (gen eric) 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 s mall 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 EC C After initiation
of in situ Yes Streams are described as ―rural streams.‖ No I nactivation estimated for EC in bed sediment was an order of magnitude less than that

### August 2010 A

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay Data?

Watershed Description Note(s)

mesocosm experiments,

sa mples
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,

F IN,
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
Se diment 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 l aboratory 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

sa mpled in addition to the water column when assessing the health risks associated with waters

Jiang et al.,
2001 M C 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 dete ction done by PCR, nonviable and damages viruses may have been
included in estimates of virus concentration/presence

### August 2010 A

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Indicator Organism(s) Alternative Indicators

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Study Type(s)

Frequency and

Period of
Observations

D ecay Data?

Watershed Description Note(s) Jiang et al.,
2007 M,

E C 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 bacteri a (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 Ne wport 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* F U Temp WC EC D 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, raccoon s, 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 temporall y

- 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 org anism 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 Cry pto, 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 s ites 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 obtaine d during calving season; calving season coincides with the wettest period

### August 2010 A

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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 characteristi cs

Ki et al.,
2007 M,

E C,
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‖ pa ttern 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 NA A No microbiological analyses
conducted N o 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.
H igher 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,

M U 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 marin e water Lipp et al.,
2001a E,

M C Trop WC,
sed FC,

Ent CP,

coliphage Crypto,

Giardia

, A Surface water

samples No Study conducted for
she llfish harvesting Levels of CP in sediment up to 5 orders of magnitude greater than those observed in the

### August 2010 A

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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; sed iment 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
indicat ors 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 G iardia 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,

F C,
IF Trop WC FC A Water quality

measurements taken monthly
for a 2

- y ear 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 EC G 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 Rotavirus G No sampling performed No Study conceptual Fecal indicator (EC) concentrations assumed to be log

- normally distribute d
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

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Indicator Organism(s) Alternative Indicators

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Study Type(s)

Frequency and

Period of
Observations

D ecay Data?

Watershed Description Note(s)
marker September
McCam

- bridge a nd McMeekin,
1981 E C ? 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 bec ome more susceptible to predation

Menon et al., 2003 F,

M IF,
C Temp 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
Marin e 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

- ch aracterized by first

- ordered kinetics for EC Mortality rates of fecal bacteria (EC, Salmonlella typhimurium , S . faecium ) not significantly different
Molina et al., 2005* F IF Temp WC,
feces Ent D Monthly water
and feces samples No Farms where cows have
unrestricted access to

streams Abstract only Ent species observed in feces different from
those observed in streams Myers et al.,
1993 F IF Temp WC FC,
EC A, C,
G Unknown Yes Study area is in a
National Recreation Area
located in an urbanized
area and d ownstream of a large WWTP Summer decay rates for FC and EC generally greater than winter decay rates

Noble et al.,
2004 F,

M IF,
C Sub WC TC, EC,
Ent F+ specific

coliphage B Experiments performed in
seawater from 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

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Study

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay Data?

Watershed Description Note(s) characterized decay among sites Noble et al.,
2003 F,

M IF,
C Sub 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 runo ff 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 i ndicators 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) alon g 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, th ere was no seasonal variation in Campy occurrence

Okabe and Shimazu,
2007 F,

M IF,
C Temp WC TC,
FC BF B Experiments performed in
filtered and
unfiltered river
water and
filtered and
unfiltered

seawater Yes Drainages not described Decay rates of FC not s trongly 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 curv es 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 v ariation in EC observed; a plausible

### August 2010 A

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Study

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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 rainfall s Olyphant,
2005 F C 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 th e effects of other variables accounted for; and (3) rainfall had only one statistically significant partial correlation Paul et al.,
1995 F,

M,
G
W GW , C Trop WC,

GW Ent CP,host 16 A Two sampling episodes (March and August) conducted, with samples drawn
f rom 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 inj ection 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
indicato rs 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 s ites

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 dominate d 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

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Study

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Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay Data?

Watershed Description Note(s) monthly Relative abundance of indicators determined by regression (though non

- detect may not hav e been handled effectively)

Petersen et al., 2006 F IF Temp (in study) WC FC A 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 wat ers 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 streamflo w 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

- coliph age 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,

o r 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
variabilit y] Rex et al.,
2005* M,

F E,
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 cor relation found between any pathogen and any indicator for both the fresh
water and marine sites

Riou et al.,
2007 M,

E C,
TI Temp WC EC FRNA

- specific
bacter

- iophages Astrovirus A,
G Monthly samples collected during
3

- year study; sample times
selected to
i nclude 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 sign ificantly during rainfall events, while bacteriophage concentration generally did not

### August 2010 A

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Study

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Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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
multi ple 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, durin g 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 a nalyzed; 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* U U Trop WC EC,
Ent E Not specified No Not specified Abstract only Study proposes development of molec ular techniques for better estimate of population densities inclusive of damaged or nonculturable organisms.
Santoro and Boehm,
2007 M C Sub WC TC, Ent,
EC Bacter

-

oides
molecular
marker (HF marker) A Nightly sampling at multiple locations along a
9 km st retch 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

- specif ic) 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 a bundance 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

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Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay Data?

Watershed Description Note(s)
2004 A I to allow more effective utilization of risk study

resu lts Schets et al.,
2008 F,

E IF,
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 th e 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 proto zoan 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 ord er 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 condi tions In situ decay measurements indicated slightly higher decay rate than observed in laboratory experiments

Shehane et al., 2002* U U Trop WC FC,
Ent CP,

Somatic coliphage A Seven sites sampled twice each per sampling event during a 2

- year study; samp ling
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 documente d During dry seasonal, the majority of indicators of animal origin

Shehane et al., 2003* U U 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

w inter 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 indi cators of animal origin

### August 2010 A

- 30

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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 i mpacts 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 peri od of lower bird density; during this period the ponds studied not hydrologically connected to sloughs where high indicator organism concentrations observed Sherer et al.,
1992 F IF Temp WC,
sed FC, FS A Sediment and water samples
taken from two
sites a nd 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,

M C,
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 n onculturable (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 TC A 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

Re sults 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 Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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 de sign 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
Limitin g 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

stor ms 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
Sorens en 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
Ox bow lakes (presumed to be concentrators of fecal pollution) did not have elevated
concentrations of CP
Stewart et al., 2000* U U Temp WC EC FRNA coliphage D Unknown N Not provided Abstract only Multiple antibiotic resistance able to distinguish
human

- der ived 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 unimpaire d 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 Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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 estuar y 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 livestoc k 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 t he mouth of the estuary, Salm correlated
with Ent

Traister and Anisfeld,
2006 F IF Temp WC EC A Sampling
conducted at seasonal, storm

- related. and
diurnal time scales; sampling
conducted
between March
and November
at 11 sites in the drainage area No Dra inage 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 wit h temp for seasonal time scale data but inversely correlated with temp for storm

- scale samples

Tranter et al., 1996 F IF Temp WC FC A 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 e t al.,
2008 F IF Temp WC EC A 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 Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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 a vailable 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 HP F Yukon River (Alaska), 2 Illinois Rivers,
and 1 East

- coast river sampled for one year (sample freq uency 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. oft en 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 F C 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

R elatively low fluctuation observed in Ent concentration during the day when determined by QPCR
Waldron et al., 2002 F IF Temp WC FC O Sampling strategy not specified in
detail No Drainages for all sample sites described as heavily developed To allow com parison 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 B acteroidales 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 Somat ic
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 coliph age rarely occurred under base

### August 2010 A

- 34

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay 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 rai nfall event
and before and
after 1 snowmelt

event EC indicated human septic sources upsl ope 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 NO AELs for determining acceptable indicator concentration
is more robust than use of attributable risk

Wijesing

- he et al., 2005 F IF Temp WC EC D 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 FC A 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 o rder 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 basef low 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,

F C U 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 Indicators

Pathogens

Study Type(s)

Frequency and

Period of
Observations

D ecay Data?

Watershed Description Note(s) minutes, hourly, and daily
intervals samples taken seconds from each other to 2.2
f or samples taken daily Authors state that single samples cannot adequately characterize water quality
Yamahara et al., 2007 M C Sub Soil,
Sed Ent,

EC Bacte

roides Salm A Sands, sediments, and
waters collected
from 55 beaches; sampling at 1
beach at 20
min ute 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 non

point 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 sp ecific 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 literatu re 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)
Addition al 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 strateg ies (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) (Micro bial) 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* (fr eshwater)

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 soli ds 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 colifor m*

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 pla stics 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. G enthner
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 suitabil ity for use in the original draft report. There are many more papers in the peer

reviewed literature and this by no means represents all of them. Of the articles reviewed, 211 citations were included in the draft report.



### Supplemental Literature Search A ctivities

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. Na tional 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 Re sources 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 ref erence 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 W orkshop on Critical Resear ch and Science Needs
for the Development of Recreational

W ater Quality Criteria for Inland W aters P a t h og en s a n d H u m a n H ea l t h PATH4W09.qxd 6/24/09 4:16 PM Page 1 (2,1)

# R EPORT O N THE 

# E XPERT 

# S CIENTIFIC 

# W ORKSHOP ON 

# C RITICAL 

# R ESEARCH AND 

# S CIENCE 

# N EEDS

FOR THE 

# D EVELOPMENT OF 

# R ECREATI ONAL 

# W ATER 

# Q UALITY 

# C RITERIA FOR 

# I NLAND 

# W ATERS

Dallas/Ft. Worth, Texas

February 18

- 20, 2009 PATH4W09ii 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 addressin g water quality issues as they impact water resources, the atmosphere, the lands, and quality of life.

For more information, contact:
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© 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 : 20099314 52
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 not hing concerning WERF’s positions regardi ng 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 Februar y 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, a nd 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 tr uly 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 o ur immense gratitude to the workshop participants whose knowledge and teamwork led to a successful workshop and this rep o rt.



## Report Preparation Nick Ashbolt, U.S. EPA, Office of Research and Development
Samu el 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 Mc Gee, 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 Fuji oka, 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 De velopment 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 

## ACKNOWLEDGMENTSiv 

### 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, a nd 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 (J ody) 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 fo r 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, AustraliaWERF 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 Commissio n 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 Roa ds 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 Commis sion 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 CONTENTSWERF Inland Waters Workshop Report vii 

### 3.5.1 Implementatio n 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 Metho ds

............................................. 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 Grou p

............................................................................................. 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 Mat rix 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- 10viii 

### 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-1WERF 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 Understandi ng 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 5 ... 3-

3-2 Schematic D iagram for Comparing S tudy R esults

........................................................ 3- 10

3-3 Sources Group S chematic for A pplicability of C riteria to Inland W aters

..................... 3- 19

4-1 Conceptual Inputs to a Lake or Stream

............................................................................ 4- 2 

## LIST OF TABLES

LIST OF FIGURESx 

### 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 Escherich ia coli

FC Fecal Coliform

FIB Fecal Indicator Bacteria

FS Fecal Streptococci

GI Gastrointestinal

GIS Geographic Information System

GL Great Lakes

MPN Most Probable Numb er

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 Lo ad

UAA Use Attainability Analysis

U.S. EPA United States Environmental Protection Agency 

## LIST OF ACRONYMSWERF 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 Q uality StandardxiiWERF Inland Waters Workshop Report ES -1 

# E XECUTIVE 

# S UMMARY

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 p rioritiz e 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 L akes 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 studie s in the Great Lakes and marine coastal waters are appropriate for inland waters. The Inland Water Workshop was undertaken to address this and related question s.

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 P articipants
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 long er term.

Short- term research was defined as new research that could be initiated and c ompleted by WERF, U.S. EPA, or the broad scientific community by December 15, 2010. Short- term research would lead to better understand ing 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 no t 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 g reater 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 b y 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 b etween Inland and Marine Coastal or Great Lakes Waters

E ach 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 di fferences 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 enviro nment, and posited that factors affecting water quality in the Great Lakes fundamentally reflect the characteristic conditions of these large lakes. I nland flowing waters found throughout the United States are very diverse in terms of water flow, water vol ume, 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 fact ors 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
beache s.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 answe r 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 de rived 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 th at 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 relationship s between health effects and indicators/water quality is through modeling effo rts. As n o 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 resu lts from one watershed to another would be to evaluate similarities
between watershed s 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 i nland 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 a nimal 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 var ies depend ing on a number of factors such as the animal source, level of treatment, animal density, and climate. S calar 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 liv estock) 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 thatES -4 

### indigenous fecal indicator bacteria sources are more important quantitatively in inland waters
than in marine or G reat Lakes environments.

The implementation realities g roup 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 increase d 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. Se veral 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 prioritizedlist. 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
f raction 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 cell

independent 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 understand ing of howWERF Inland Waters Workshop Report ES -5 

### predictions from QMRA models relate to human health outcomes observed in epidemiolog ic
studies. Such anchor ing 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: A nimal
densities and fecal excretion rates have a significant impact on the amount of material available
for m obilization 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 mec hanisms 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 hydrol ogy, and indicator-pathogen relationships in inland waters within the context of health risks.ES -6WERF Inland Waters Workshop Report 1-1 

## CHAPTER 1.0



# I NTRODUCTION

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 ho w 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 am bient 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 purpose s of the workshop, i nland 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 waterbod ies (that are not also coastal recreational waters) . Thus, in this context

, the term “inland w aters ” do es not include marine coastal waters, estuaries, or the Great Lakes.



## 1 .2 Workshop Design

The Inland Water W orkshop 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 pro spective 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. T he experts participate in individual and collaborative writing of a draft summary report by the end of the workshop. Subject area leaders are then responsible1-2 

### 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 w orkshop was organized around five topic al 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 waterbod ies and identifying research priorit ies 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 understand ing 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- ter m 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 differe nces 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
sub stantially 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 r esearch or by October 2012 through implementation approaches that m ay 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 su ch, U.S. EPA recommended applying them for all waters to protect people recreating in these waters from gastrointestinal illness. Among other provisions, t he 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 recreation 1

, 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 perspe ctive 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 concern s 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.

S ince 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, s tates 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 r ecommended criteria, adopting
criteria to reflect site

- specific conditions, or adopting other criteria that are scientifically defensible. In approximately 2015, s tates with coastal recreation waters will be required to adopt and submit to the a dministrato r new or revised water quality standards for the coastal recreation waters of the s tate 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 typical ly defined by states in their state water quality standards but is generally
considered to mean w ater

- 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: t he relative degree of focus on 1) inland waters (generally) versus inland flow ing 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
flo wing 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 an d 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 Engineeri ng

Water Matrix Group: Hydrology, Chemistry, Geology, and Modeling Topical Group Lead: Nick Ashbolt, U.S. EPA, Office of Research and DevelopmentWERF Inland Waters Workshop Report 1-5 

### Ali Boehm, Stanford University, Dep ar t ment of Civil & Environmental Engineering Donna Francy, USGS, Ohio Wa ter 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, Ora nge 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 Zealand1-6WERF Inland Waters Workshop Report 2-1 

## CHAPTER 2.0



# S ETTING THE 

# S TAGE

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 address ed

re ports 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 o f 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 u nderlying 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 water s. A review of the literature indicates that few epidemiologic studies into the health risks of recreational use of inla nd waters have been performed. The literature also indicates that several r isk assessmentstudies 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 heal th risks of recreation in th e setting of inland

waters. 2. C haracterize 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 m icrobial risk assessment [QMRA]).
3. E valuate the relevance of studies conducted in marine or Great Lakes coastal waters to the development of recreational water qua lity criteria for inland waters.2-2 

### 4. D efine 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 w ater matrix group was to identify the physicochemical and hydrological parameters that might differ whe n 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 est imates 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 adv isories

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

o Identifying any outstanding issues in adapting c ur rent 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 a lmost all watersheds and, therefore, are potential sources of pathogen contamination in both co astal 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.

L ittle quantitative data exist on the relative contribution of pathogens from human s as compared to various animal hosts. Comparison of these two sources is also complicated because animal contributions are typically spread a cross 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 e ffectiveness of these toolsWERF 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. D etermine whether there are significant differences in source loads to inland waters as compared to coastal recreation waters

. 2. A ssess the research that may be required to define any such differences.
3. Di scuss 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 permit ting 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 co liforms, 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 us ing these fecal indicator bacteria (FIB),
the U. S. EPA has made two implicit assumptions

. The first is that waterborne pathogens co

occur 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 th ose 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,

se diments ) (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, m ore 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 . I f 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 i mplementation r ealities g roup

.


### 2.2.2 Health Risks Group

The healt h 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 t he 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 W aters

France : A prospective cohort study was conducted on the Ardeche river basi n 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 variationWERF 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 answer ed questions about illness and bathing behavior during the 7 days prior to the interview day. The study population was recruited
fr om people vacationing at locations along the river. A total of 5,737 participants provided data
on their health status and da ys 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 n o water measurements were made.

A water quality/ health risk relationship was observed between f e cal streptococci (FS) density
and the rate of gastrointestinal (GI) illness

. A similar relationship was not observed for total or
fecal coliforms and GI illnes s, although densities of fecal coliforms, and not FS, were associated with skin symptoms.

Whitewater Channels, UK : A prospective cohort study enrolled whitewater canoeist s 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 lat er 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 w ere higher among those exposed to the pristine water than among the unexposed group. Those who canoed in the wastewater

- impacted coursewere 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 t wo 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). Densiti es of fecal indicator bacteria were generally high but variable among the sites. The geome tric 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 follow

up information, rates of i llness 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 stu dy (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 the2-6 

### whitewater course. The study did not include a group of unexposed participants. All follow -up was by written , s elf

- 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 predict ed 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 W aters Keystone Lake, Oklahoma : E pidemiol ogic 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 a t which the swimming took place are not described in detail in the publication but are known to be nonflowing inl and 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 cru de 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 f reshwater 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 t he 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 exi t 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 gastroe nteritis 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 range d 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 attributab le 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

contam ination.

Coastal F reshwater (Great Lakes)

U.S. EPA F reshwater 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 includ ed 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). W ithin 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 teste d 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 nonswim me rs 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 qu ality

. In the Keystone Lake study, symptoms for enteric diseases tended to be higher in swimmers than nonswim mers

. In 1979, there was one other group of symptoms (fever, headaches lasting greater than 3 hours, and backache) that showed significant differen ces 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, th ese 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 pros pective 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 ill ness were two - to three fold 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 S tudy, 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 treatme nt plants . Be achgoers were asked for information on demographics, swimming and other beach activities, and numerous non- water

related risk factors for GI illness. F ollowing 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 enter ococci 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 

### M arine Coastal W aters
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 Orle ans, 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 limi ted 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 . Nonswim mers who attended the same beach were the control population for the study. Water samples were collected at three locations and a ssayed 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 wa s d eemed “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 i n 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 th at 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 nonswim mers 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 ind icator of illness than E. coli . Further, stormwater runoff appeared to be less harmful than sewage sources

. Th ese 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 statistic ally 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 a2- 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 wa ter, 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 . O ne week following the exposure period, study participants were medically exa mined 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 recreati onal water.

In addition, the water quality of the bathing area was sampled at 30- minute in tervals 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 wate r 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 dep th 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 sewa ge 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 a vailable for only 3,887. (McBride et al., 1998) . Beaches were categorized as “minimal impact ” (Rabbit Island and Wenderho lm), “ rural” (with animal impact: Oho pe, Spencerville) and “oxidation pond ” (human impacted: Oma nu, Paraparumu, and Raglan). Indicator densities were low at all sites; the 75 th 

### percentile of
enterococci measures was 13 CFU/100 mL. Absolute risks were not present ed by source (i.e., human vs. animal). For nonswim mers, there was an illness rate of about 2 5 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 swimme rs 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 i llness 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 beachWERF 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 o ccurred 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 b eaches that were polluted by submarine sewage o utfall s, 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 so mewhat 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 animal

impacted 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 d ays 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 drain s. I n 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
d id no t 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 al l 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 d rains. 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 enteric2- 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 R eview A rticles : This prospective cohort study of swimmers and nonswim mers was conducted at beaches in Mission Bay, California (Colford et al., 2007). Human sources of fecal pollutio n 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 path ogenic viruses and coliphages. Rapid molecular methods (i.e., Q- PCR ) were used to measure enteroc occi , Bacteroide s
, adenovirus 40 and 41,
and norovirus. Geometric means (per 100 mL) of water quality measures were 29 enterococc i (chromogenic method), 65 Enterococcus spp. (Q- PCR ), and 25 fecal coliforms

. Higher rates of some symptoms were noted among sw immers 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 w ith 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 mari ne waters. One possible explanation for th is 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 giv en 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

. Prü ss (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, Zm irou et al. (2003) conducted a meta -analysis and also concluded that indicat or organi sms 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 betwee n 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 environment al 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 depen dent 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 stan dard 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. Regressio n models have not been used for other CWA purposes (303d listing, NPDES permitting, and so forth).

The U.S. E PA created Virtual Beach (Frick et al., 2008), a software program designed to help beach m anagers 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. G eological S urvey (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 co ntamination 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 concentrat ions (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.

Me chanistic 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 parameter s 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 develo ping 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 ch ange 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
concentratio n 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 do se

response 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 t he 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 ma nagement 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 ep idemiologic 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 r ecreational water users and our2- 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 repert oire 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 path ogen

related characteristics of certain fecal sources are known or can be inferred, e.g.

, human sewage has a high probability of containing pathogenic human viruses, whe reas 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 affe ct 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 assess ed 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 waterbod y. 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 r anges 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. Furt hermore, 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 abilit y to parse the probable sources that impact a given waterbody, these allocations represent a rough estimate

. It is generally assumed that waterbo d ies in urban watersheds receive some level of human contamination, whe reas 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 differentWERF Inland Waters Workshop Report 2- 17 

### combinations of pathogens, the relative proportion of source loading and the quantity of fecal loading contr ibute 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 epidemiolog ic 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 poul try . 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 failur e. 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,

m icrobial 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 e ffectiveness of these tools and reduce the reliability of their outputs

. Water quality criteri a developed for all waters will need to include a better understanding than we currently have of the effect of fecal source s 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 base d 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 A WQC 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 criter ia 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
condu cted 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, mean ing 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 muni cipal 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

- basedmethod, 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, s tate , and t erritorial laboratories performing analytical work for other program areas such as the Safe Drinking Water
Act or assessment of disinfection eff icacy

, traditional culture methods would still be required

. S imply 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 cu lture 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 da ta. Any assessment method must be proven to be robust enough to provideWERF 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 t hese 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- 20WERF Inland Waters Workshop Report 3-1 

## CHAPTER 3 .0



# S TATE OF THE 

# S CIENCE

3.1 Indicators and Pathogens Group
The indicators and pathogens group believe that sufficient microbial and he alth 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 enterococ ci 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 q uestion 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 (L iu 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 nu trients. These decaying mats have been reported to support the growth3-2 

### 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 Uni ted 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 biologica l 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 beca use 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
inla nd 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. S ediments 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 g reater 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,

o rganic composition, and microbial load than marine coastal and Great Lakes water (Olyphant et al., 2003).WERF Inland Waters Workshop Report 3-3 

### Th e sources and the types of pollutants in most inland waters are not known, but often
contain measurab le concentrations of FIB from probable sources such as w 

### ild 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 FI B. 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 (Hardi na 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 locatio ns, 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 a nd physiological capabilities to multiply under environmental conditions (Fujioka and Byappanahalli, 2001; Byappanahalli and Fujioka, 2004).

A significant consequence resulting from growth and presence of environ mental 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 t he 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 hav e 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 be3-4 

### 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 dire ct 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 w ill have similar risk for water borne diseases as has been measured for POTW

- impacted
coastal water s. However, whether the same criteria and water quality standards established for
coastal Great L akes 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 wa ter sit e. 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 concentrati ons 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 Grea t Lakes cannot be reasonably applied . Under these conditions, epidemiologic studies should be conducted at inl and water sites, and alternative criteria may be required for pre dicting waterborne diseases for these inland water
site s. 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 pa thogens 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

pa ddling 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 w aters 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 identifyWERF 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 relati onships 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
difference s 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 Hydro

logy

, dilution Flow



### Evaluation by Water Type

U.S. P rospective Cohort Studies : Studies by Cabelli (1983) and Dufour (1984) employed the same study design and were the basis for the U .S. EP A 1986 water quality criteria. The Cabelli studies were conducted at marine locations, and the Dufour study sites w ere 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

wa s steep er in marine water compared to freshwater. In other words, a given increase in

enterococc us density would be expected to result in greater health risk s 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 effec ts 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 beach es (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 additional3-6 

### light on potential differences bet ween health risks of swimming at POTW

- impacted beaches in marine and freshwater settings.

European Randomized Controlled T rials

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, an d 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 suscep tibility 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 wate r 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 impa cted 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 stu dies 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 no t 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 setting s 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 S ource P ollution : Studies conducted in Hong Kong (Cheung et al., 1990) and New Zealand (McBride et a l., 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 underprotec ted by applying criteria developed from human studies to settings with substantial impacts from agricultural animals.

Stormwater and U rban Runoff: Potential d ifferences 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 wastewat er (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 hu man 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, t he Mission Bay study (Colford et al., 2007) and NEEAR studies (Wade et al., 2006; 2008) had similar st udy 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 a t 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

approx imately 1,000 environmental isolates of Enterococcus spp. suggested that avian sources of
fecal contamination may have domina ted at the Mission Bay b each . 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 d ifferences 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 ). Howev er, 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 epidemiolo gic literature was reviewed in detail . This review included what is known about the health effects of recreation in inland, coastal

, and Great Lakes settings . E vidence was3-8 

### also considered to support the hypotheses that the predominant source of fecal conta mination 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

.

Apply ing 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 water s 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 st udies 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 conduct ed 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, b ounded 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) loca tions to locations with flowing water. D ata to address this evidence gap c ould 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 comp are 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 o f 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 wate rs, 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 perspectiv e 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 r elative 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 enterococc i. 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 resul ts 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 f or 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 freshwat er studies had not been published at the time of writing). The E uropean 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 contained3- 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 tha t a policy imperative exists for immediate
action. Th e group support ed 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 de rived from
Great Lak es 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 metho ds 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 D iagram for C omparing S tudy R esults

.



## 3 .3 Water Matrix Group

3.3.1 Use of AWQC Established for the Great Lakes in Inland Wat ers

T he w ater matrix group recognized that the implicit assumption of a n 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
th e sources relative to the water body, a function of the transport characteristics at the point (s) of deposition to the waterbod y and within the waterbod y, the differential survival rates and potential for regrowth under differing environmental conditions, the dilution capacity and mixing characteristics of the receiving waterbod y, and the chemistry of the receiving water body. All ofWERF 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 effo rts. As n o two watersheds are the same, there is a possibility that, for example, a
marine coastal beach at one locat ion 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 watershe d. The only way to
effec tively transfer the results from one watershed to another is to evaluate each watershed with respect to potential sources, local physicochemical conditions, and geographic d istribution 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 in creased 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 thi s 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 re sult 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 persistence3- 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 mode ling techniques are not needed for inland waters than those currently being used in the Great Lakes and marine coastal waters

. However, the matrix group believe s that key differences in the approach to modeling would be: 1) the types of independent variables u sed 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 L akes or within d ifferent marine
coastal waters.



### 3.3.2 Issues Specific to Regression Models Independent variables u sed 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 th e 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 fun ctions 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.

Differe nces 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 s izes 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 g reater 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 i nland 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
defecati on 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

**♦** t ype of animal

**♦** l evel of fecal waste treatment3- 14 

### ♦ p roximity of waste to waterways, including direct deposition

**♦** p at hogenicity and host specificity

**♦** pathogen i nfecti vity

**♦** pathogen prevalence in herds and shedding intensity/concentrations

**♦** animal density and variations in density across geographic areas, including migration of wildlife species

**♦** r elationship between pathogens and indicators

**♦** c limate (d rought, 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 compar ed 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 faul ty 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/o r states.

Table 3 - 1

. Pathogen Hazards Arising f rom Animals

. Pathogen Animal*
Salmonella spp. Birds and mammals Campylobacter spp. Birds and mammals Yersinia enterocolitica Pigs Pathogenic E. coli Cattle, other ruminants, po ultry, 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 m onocytogenes 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 N ew Z ealan d, 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 f ecal 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 assume d that urban runoff has less variability in terms of animal

sources , this assumption cannot be supported w ith a high degree of certainty.

Scale

Some of t he significant differences between coastal waters and inland waters can be best

su mmarized 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 o f 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 fec al contamination to receiving waters : In inland waters, wildlife and livestock are in direct proximity to receiving waters . A nimal s in concentrated or confined animal feeding operations (CAFOs, including waste lagoons) can at times be in direct contact wit h 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, a nimal 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, of ten 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 ar e 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 h ost specificity, pathogenicity, and density of pathogens stemming from specif ic 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 the3- 16 

### environment into which the pathog ens 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 no t culturable (VBNC) state

. This state has been well described for several enteric pathogens, including Salmonella enteri ca
, E. coli, and Campylob acter jejuni (Rollins and Colwell, 1986)

. The VBNC state represents a response to survival stress by not being cultur able
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 p recipitation 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 w ind 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 ap proaches 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 s ingle, 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 character ization, 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 agricultu ral drainage is also important. This includes irrigation return flows and seepage, which may contain s alts that include nutrients (fertilizers), agrochemicals (including herbicides and pesticides), and runoff or effluent from animal husbandry locationsWERF Inland Waters Workshop Report 3- 17 

### such as feedlots, pig farms , dairies, or chicken farms, which also contribute to fecal
contamination. Inc reases 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 stormw ater 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 to gether constitute major data gaps in our current knowledge.

Table 3 -2

. Pathogen S ources and H azards T ypically C aptured in Sanitary Surveys

.
Sources Information needed
POTWs Discharge volume and quality Combined s ewer o verflows 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 faci lities 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 & a battoirs 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 waste s are important sources of nutrients for agricultural activities. Hence, rainfall/runoff ev ents 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

, th e 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 wat ers than in marine or G reat 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

env ironmental systems and pathogens/parasites, even within a common geographic setting (Wilkes et al., 2009). H ence, it will be difficult to apply a single set of AWQC for all inland3- 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 f or 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 s ources 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 Figu re 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 be cause no study has been conducted specifically to evaluate CSO s’ 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 de scriptions 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 p revalence, 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 G roup S chematic f or A pplicability of C riteria to I nland W aters

.



### POTW Inland POTW GL and Coastal

CSO Inland CSO GL and Coastal

NPS Inland NPS GL and Coastal ??Knowledge Gaps/DifferencesHuman Influence ?

**≈**

**∝**



## 3.5 Implementation Realit ies 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 countri es 3



### 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 qual ity 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 Stat es are incorporated into water quality standards regulations and, therefore, se rve 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
devel opment. 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 Re gulations

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 h ealth 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 cl osings 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 adva ntage of this flexibility. The group did pointout 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 wa ter 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 UAA 4

4 A UAA is a structured scientific evaluation of the feasibility of attaining a designated use based on s ix 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 theWERF 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 recr eation 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 pub lic. 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 influen ce 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 influenc e 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/10 0 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 l east3- 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” events 5



### ♦ 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 inc urring “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 Zeal and 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 mi crobiological 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 assess ment 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 monit oring 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

.

The re 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 bath ing 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 be en 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 bas is for this approach w as a lack of epidemiologic information for freshwater sites in New Zealand, a lack of credible information to develop ris k 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 app ropriate

. 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 o n 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 wastewa ter discharges, including FIB. Those permit limits are set to protect designated uses based on compliance with the waterquality criteria. The use assessment (303d)/TMDL program assesses the attainment/nonattainment of designated uses by comparing observe d 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 b e 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 wastew ater 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 tr eatment 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 tre atment, 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 an alytical 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 mic robes. 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 analys t.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) cou ld 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 th e 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

- sp ecific 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 

## C HAPTER 4.0



# K NOWLEDGE 

# G APS

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 ev ents. 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 s ources 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 genera l, 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 bacteria

laden 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 taken4-2 

### 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 stream s 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 no n-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
la kes 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 evenWERF 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 T hat 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 c haracterizing 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. Implementat ion 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 terr estrial 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 challenge s 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 be en 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 p recise, 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
distrib ution 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. Coast al lakes often stratify, but this rarely occurs with the swash through surf zones where swimmers tend to4-4 

### 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 impor tant 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 reco mmendations 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 previo usly determined that bacterial
indicators are inadequate or unre liable surrogates for all sewage -borne pathogens, especially the more resistant pathogenic human enteric viruses or parasitic protozoa. Moreover, d ecades 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. Theoret ically, each sample comprises the following five fractions of that microbial population: 1) viable and
culturable fraction rec overed 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 bi ochemical and nucleic acid -based amplification methods. Examples of such methods include the q uantitative (real

- time) polymera se 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 usi ng adenosine triphosphate (ATP)- based detection (Bushon et al., 2009). Standard culture and ot her 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 male

specific ( 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 t hat 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 techn ical 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 improvin g 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 interac tions (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, e specially wildlife (shorebirds, aquatic mammals) and non-enteric sources (persistence and growth) are not easily incorporated into mechanistic modeling. Thus, effective numerical modeling should be a4-6 

### 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.

Th e 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 trackingmethods 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
differ ent 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 M odels and Methods for I nland 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 pr edictive value of QMRA is required , and
additional data are need ed 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 be enWERF Inland Waters Workshop Report 4-7 

### conducted to sites where epidemiologic dat a 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 i n source type or source load. Furthermore, by modifying t he

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 qu antifying 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 M ethods of Characterizing Microbial Water Quality to
P redict Health R isks Two broad categories of knowledge gaps exist regarding Q-PCR: interpreting andapplying 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 c omparing 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 microbia l 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 samp les 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 concen tration 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 b e 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 a4-8 

### 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
wi ll 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 ong oing 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 resul ts 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 T 99 

### (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 T 99 

### 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, sal inity, 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 gr oup 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 abili ty 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.

Regr ession 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 t he role of sediments in impacting both the survival and transport of pathogens versus indicators. These know ledge 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 turbid ity, 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 TMDL s 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 recognize d that developing compliance strategies based upon a mechanistic modeling approach may be pre mature because information and fundamental knowledge in fate and transport processes are still lacking.

Because of the advantages of a mechanistic approach, the w ater matrix group
recommended that research efforts focus on establishing the fundamental understanding and garnering the knowledge needed for establishing mechanistic models , specifically:

**♦** q uantifying the loads associated with different sources, especially nonpoint sources

**♦** e valuating microbial transport mechanisms from their p oint of deposition to and within
the water body4- 10 

### ♦ evaluating fate of microbes including an evaluation of physical- chemical factors that
influence their det ectable 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 i n 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 gap s in understanding how:

**♦** regression models may be used to predict health outcomes (instead of indicator concentrations)

**♦** QMRA predictions relate to epidemiol ogy 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 risk s.

Regression Models and H ealth O utcomes
More work needs to be undertaken to evaluate the ab ility 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 H ealth O utcomes 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 e pidemiologic 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 stu dies 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 s ources (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

. Alternative ly, 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 isWERF Inland Waters Workshop Report 4- 11 

### considerable potential to further exploit QMRA models in this capaci ty. In particular, future
research should focus on

**♦** t he most important dif ferences in exposure scenarios

**♦** better understanding how different types of waterbodies should be managed

**♦** d evelop ment of site

- speci fic/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 pathoge ns ).

Mechanistic Models and H ealth O utcomes To understand contributions from specific nearby sources, e pidemiolog ic 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
hu man health effects directly . Both data mining of existing source/load information and gapfilling research may be necessary to develop models retrospectively.

During epidemiolog ic 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 managemen t 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. Z oonotic 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.
T here 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

a s 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 particular4- 12 

### importance for determining the suitability of using indicato r 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 on site 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). Compoun ding 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 f ai ling 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 sys tems also requires further research. A recent study (C harles 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 a nimal densities and fecal excretion rates have a sign ificant effe ct 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, t he 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 the se various environments affects the potential risk associated with their subsequent

trans port into inland waters. Transport of pathogens to waterways is highly variable due to differences in rainfall/snowmelt, overland flow, drainage ditch es (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 exi sts for inland waters with NPS or CSO as the primary source of contamination. (Refer to S ections 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 chara cterize 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 suf ficient 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 r equires 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 w ater 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 pro actively managing them . In this context, t he watershed is seen as the first barrier in the application of a “multi -barrier” approach to the control and minimization of
risks to drinkin g 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 i dentifyin g 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, i t has yet to be
demonstrated that BMPs can effective ly 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 samp le 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 stream4- 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 b asic 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 environmenta l strains of FIB could lead to exceedances of standards – potentially without an associated health risk. Th is 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, a ctivities suc h 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.

I nland 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 . Further more , a failure to accou nt 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 o f 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 f eed 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 be tween pathogens and
indicators could be diff erent 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 o n 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”

Wat ers 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 conta mination 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 microbi al 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 mai ntain 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- 16WERF Inland Waters Workshop Report 5-1 

## CHAPTER 5. 0



# R ESEARCH 

# P RIORITIES

5.1 Sugg ested 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 ident ified 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 perspectiv e, 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

sour ce 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 Q

PCR 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 m ay 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
ris k 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 the se 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, experi mental 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 r esearch that would address them are summarized below.WERF Inland Waters Workshop Report 5-3 

### Short

- Term Research Needs Optimiz e 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 tim e 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.

1 A: 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.
Su ch 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.

Incorpora te 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 condu cted, 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 pathog ens (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.

Optimiz e 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 wat er 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.

I dentif ying 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 persisten ce 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 m eta -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 link age 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 wel l 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 (H aile 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 sour ces (Wiedenmann et al., 2006) . POTW

- impacted flowingWERF Inland Waters Workshop Report 5-5 

### water s 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 quantita tive , 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 modificati on by source. One approach that could evaluate such effect modification would involve a meta- an a lysis of the epidemiologic studies conducted to date. Unlike the previously conducted meta

an a lyses

, such a meta

- an alysis would be stratified by source (i.e., t reated 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 obtain ed 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 River s are anticipated and should be included in the proposed

meta

- an a lysis . 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 fo r 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

crit eria 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 : h ow much uncertainty is there in using the results of epidemiologic
studies conducted in G reat Lakes and coastal settings to establish criteria for inland flowing waters? S pecifically, the use of the NEEAR study design and methods at a flowing and a nonflowing inland water site would redu ce 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 anticipate s the persistence of questions regarding applying results of a study at one inland site to other s. Members of the group went so far as to say that th e variability of risks across inland flowing waters settings is likely substantially greater than the variability of risk between inland flowing

waters and G reat Lakes coastal settings

. For these reasons, this group recommend s targeted epidemiologic studie s be conducted at the first available opportunity that would5-6 

### 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 criteri on. 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 r everse QMRA for its applicability in the development of site- specific criteria.

Apply data mining activities t o identify data gaps that limit application of models and identify long er -term research goals.

Longer- Term Research Needs

Use m odeling 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

m easurement 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 th eir applicability, limits , and future research needs.

Focus on developing the fundamental understanding and knowledge needed for establishing

mec hanistic models.

Because of the advantages in being able to extrapolate to a range of site situations with th e 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 feca l 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 pr ovided 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

on site sewage treatment systems on microbial water quality Identify and quantify human pathogens in various types of onsite sy stems, especially during wet weather and including disinfection efficacy of systems and their rate of failure

. Risk with these systems and

par ticularly the cumulative effect is unknown

Long er term Fate and transport of animal pathogens in relation to indi cators Identify fate and transport of importan t pathogens identified in short

- term priority #1

. Not adequately characterized; Apply to model development

Long er term Epidemiologic studies in inland waters Include agricultural, NPS runoff, measure pathogens identified in short

term priority #1

. No such study has been conducted in U.S. inland
waters Long er 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 Long er 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 wat er 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, r elationships between indicators, relationships of indicators to human health risk ).

This recommendation is similar to the meta -analysis suggestion from the h ealth r isks

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 fl owing 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 l onger 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. Unde r 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 adjustin g 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. T here is a need for scientifically defensible criteria that are protective of seco ndary

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 sh ould 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., ho lding 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 t ranslation 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 imp act 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 re suspended 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 d ata on pathogens/infectivity and exposure information for input t o site

- specific QMRA
models.

The use of a QMRA model to derive a site- specific or categorical water qua lity 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 QMR A 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 Consolidatio n 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 b e 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 activitie s 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 paper s, 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 int erconnected 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 perspec tive 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 W ater 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 an d 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, t he extent to which it occ urs 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 relationship s 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 indicato r organisms as guidance for NPS

- impacted inland waters

.

The implementation realities group indicated that there are many miles of inland water
beach es 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– heal th 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 cu rrent 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 vario us 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 establi shed. 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 t o 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

**♦** valida tion 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-s pecific targets, be they generalWERF 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 anchor ing of the predictions
from QMRA with epidemiologic observations will enhance the scientific credibility for us ing
these techniques to predict recreational waterborne illness . Similar sentiments were echoed by all five group s albeit in slightly different terms.

As indicated previously by the health risks group, optimizing and anchoring QMRA models and model inputs ca n 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 pred ictions 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 a dequately 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
extende d 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 a nimal 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 the se5- 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 ditch es (tile dr ains), 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 eve nts 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 inla nd 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:

**♦** Epidemiolog ic studies in inland waters should separately include agricultural, NPS runoff,
and POTW sources.

**♦** Epidemiolog ic studies in inland waters should include source characteriza tion and microbial source apportionment.

**♦** E pidemiologic studies in inland waters should include standardized molecular methods to identify pathogens and their sources.

**♦** Epidemiolog ic studies in inland waters should be designed in parallel with QMRA and
shoul d clearly account for the p athogenic potential of a gricultural 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
NEEA R study design and methods at flowing and nonflow ing inland water site s would reduce that uncertainty . The major components of that uncertain ty 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 AResearch 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 microbialwater 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 P athogens.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-1Table A-3. Microbiological Method Development or Enhancement.

Re search 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:CTable 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 ATable 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-termResearch 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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