# Appendix C. 4 : A ssessment of the applicability of existing epidemiology data to

inland waters



# ASSESSMENT OF THE APPLICABILITY OF EXISTING EPIDEMIOLOGY DATA TO INLAND WATERS

U

. S

. Environmental Protection Agency

Office of Water Health and Ecological Criteria Division

August 2010

## U.S. Environmental Protection Agency

August 2010 i Disclaimer

This document has not yet been r eviewed 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 docume nt 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 Eco logical Criteria Division Office of Science and Technology, Office of Water 1200 Pennsylvania Avenue, NW Mail Code 4304T Washington, DC 20460 Phone: 202

- 566

- 1101 Email: ravenscroft.john@epa.gov

Stephen Schaub (Alternate WAM) USEPA Headquarters Health and Eco logical Criteria Division Office of Water, Office of Science and Technology 1200 Pennsylvania Avenue

, NW Mail Code 43 04 T Washington

, DC 20460
P hone: 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 fo llowing individuals contributed to the development of the report:

Timothy Bartrand (lead) Clancy Environmental Consultants, Inc. Mark Gibson Clancy Environmental Consultants, Inc. Jeffrey Rosen Clancy Environmental Consultants, Inc. Jeffrey Soller Soller Environmental, LLC

## U.S. Environmental Protection Agency

August 2010 iii Table of Contents

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

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

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

................................ ................................ ................................ ................................ ..... 7 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 FFE CTS IN 

## I NLAND 

## S ETTINGS



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

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

- Epidemiological Studies of Inland Se ttings

................................ ................................ ...... 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. Coastal Sites

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

- Scale Indicator Variability

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

................................ ................................ ................................ ................................ ... 32 5. S URVIVAL OF 

## F ECAL 

## I NDICATOR 

## B ACTERIA IN 

## I NLAND AND 

## C OASTAL 

## S ETTINGS



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

................................ ...................... 34 5.2. Phenomena Contributing to Indicator Removal

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

................................ ................................ ................................ ................ 38 5.4. Comparison of Measured Decay Rates

................................ ................................ ..................... 41 5.5. Summary

................................ ................................ ................................ ................................ ... 45 6. I NDICATOR



## - P ATHOGEN 

## A SSOCIATION IN 

## I NLAND AND 

## C OASTAL 

## S ETTINGS



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

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

................................ ................................ ................................ ..... 48 6.2.1. Co

- occurrence and Correlation of Enteric Viruses and Fecal Indicators

...................... 48 6.2.2. Inactivation Rates of Enteric Viruses in Dif ferent Settings

................................ ........... 52 6.3. Bacterial Pathogens and Indicators

................................ ................................ ........................... 55 6.1. Summary

................................ ................................ ................................ ................................ ... 56 7. R EFERENCES



## ................................ ................................ ................................ ................................ ...... 58 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 TRA TEGY AND 

## R ESULTS



## ................................ .......................... B

- 38

## 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 Coli form Occurrence

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

................................ ...................... 26 Table 6. Reports in which Fecal Indicator Bacte ria Growth has been Observed or Inferred

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

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

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

................................ ........................ 54

List of Figures

Figure 1. Fecal Indicator and Pathogen Loading at Inland Sites

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

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

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

................................ ................................ .. 13 Figure 5. Summary of Reported E. coli De nsities in Various Water Types

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

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

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

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

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

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

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

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

................................ ............ 41 Figure 14. Spatial Trends in HAV and Fecal Indicator Bacteria in a Small Stream Located in an Area whose Land Use is Primarily Agriculture

................................ ................................ ............ 51 Figure 15. Inactivati on of Simian Rotavirus in Unpolluted Fresh Water (open squares), Polluted Fresh Water (filled squares), Low Salinity Estuary Water (open circles), Medium Salinity Estuary Water (open triangles), and High Salinity Estuary Water (crosses).

............................... 53 Figure 16. Survival Curves for Coxsackievirus B

- 1 and Poliovirus 1 in Membrane Diffusion Chambers in Fresh Water.

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

....................... 57

## U.S. Environmental Protection Agency

August 2010 v Acrony ms

AODC acridine orange (stain) direct count AWQC ambient water quality criteria BEACH Act Beaches Environmental Assessment and Coastal Health Act CC Coulter Counter CFU colony forming unit CHEERS Chicago Health, Environmental Exposure, and Recreation Stu dy CPSP Critical Path Science Plan CSO combined sewer overflow CWA Clean Water Act EEC European Economic Community EPA U.S. Environmental Protection Agency EU European Union FC fecal coliform
FIB fecal indicator bacteria GI gastrointestinal HAV hepatitis A virus HCGI highly credible GI illness HPC heterotrophic plate count MPN most probable number MST microbial source tracking NEEAR National Epidemiological and Environmental Assessment of Recreational

Water Study NOAEL no observed adverse effect level PC prospective cohort PCR polymerase chain reaction POTW publicly

- owned (sewage/wastewater) treatment works ppt parts per thousand (salinity) QMRA q uantitative 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

T his report evaluates whether the observed relationships between fecal indicator bacteria (FIB) densities and adverse health effects for Gre at Lakes 1 

## waters are applicable to inland waters. Results suggest that the epidemiological data and relationships developed for Great Lakes waters that are primarily impacted by publicly

- owned treatment work (POTW) effluent s can be applied to inland water s that are also primarily impacted by POTW effluents

. F or inland

waters that are predominantly impacted by fecal

s ources other than POTW effluent, the available science does not support the extension of the epidemiological relationships developed in the G reat 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 organ ism densities with fecal pollution sources and their health effects, as described in Exhibit 1. Performance was also assessed in terms of indicator occurrence (including variability), survival, and their association with pathogens. The FIB performance da ta were used in conjunction with the known differences in sources and hydrodynamics between inland and coastal settings to evaluate the validity of extending health effects relationships developed from Great Lakes epidemiology studies 2 

## to inland flowing or impounded waters.

Qualitative Comparison of Inland and Coastal Settings

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

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

1 

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

, Section 502 of the Federal Water Pollution Control Act (33 U.S.C. 1362) identifies “ coastal waters ” as the Great Lakes and marine coastal waters (including coas tal estuaries) that are designated under S ection 303(c) by a State for use for swimming, bathing, surfing, or similar water contact activities.

2 

### E pi demiological data collected as part of EPA’s National Epidemiological and Environmental Assessment of
Recre ational (NEEAR) Water Study. Exhibit 1. Relating Indicator Organism Densities to Health Effects

The features of an effective indicator ( adapted
from NRC, 2004) are

a demonstrated correlation with health risk; similar or greater survival time th an 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 differ ent densities of fecal indicator organisms and pathogens, fecal indicator densities in waters impacted by different sources indicate different hazards. Thus, if inland and coastal waters have different primary fecal pollution sources,
health effects will also differ.

This report focuses on differences in indicator performance in inland and coastal settings. It does not address the performance of indicators in each of the settings independently. To evaluate these differences, indicator occurrence, surviv al/growth, and association with pathogens is compared for inland and
coastal waters.

## U.S. Environmental Protection Agency

August 2010 2 overbanks (Exhibit 2). Loading and hydrodynamics of FIB in POTW

- impacted inland and coastal waters are generally similar; POTW discharges in both settings are relatively steady and are not dependent on whether a recreational site is coasta l or inland.

In contrast, significant differences exist in FIB loading between POTW

- impacted coastal waters and non

- POTW

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

associated microorganisms, and microbial ecology. Differences potentially affecting the relationship between indicator density and health effects are the fecal sou rce itself and the transport of pathogens and indicators in the receiving water

— POTW effluent is loaded to receiving waters continuously, whereas contamination from other sources is primarily loaded to waters during precipitation events (rain, overflow, e tc).

Summary of K ey F indings

1. Fecal pollution source (human or other animals) is the most important of the potential differences between the NEEAR study sites and inland waters

.
o T he pollution source directly influences the suite of pathogens and indicat ors in receiving waters and any health effects that could result from exposure to those

waters.

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

- impacted inland waters on the basis of similar fecal pollution source (human) and FIB fate and tr ansport. Exhibit 2. Illustration of Fecal Pollution Sources on

Inland and Coastal Settings

## U.S. Environmental Protection Agency

August 2010 3 o Indicator occurrence, survival, and association with pathogens are highly variable in both coastal and inland settings. For recreational waters where POTW inputs are the dominant i m

pact
, 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 i nland w aters researc h needs

.

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

- POTW impacted inland waters.

o Because there are significant differences in hydrodynamics and fecal pollution sources between coastal POTW

- impacted waters and non

- POTW

- impacted inland waters, it is reasonable to infer that indicator performance relationships will not be similar. POTW

- impacted waters receive continuous loading whereas loads to waters impacted by other fecal sources are event

- driven.

o N on

- POTW feca l 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 mec hanics. These characteristics can also impact the number and diversity of FIB and pathogens that will be present in a waterbody at a given time and likely differ for POTW and non

- POTW sources

.

3 

### The association of indicator density with risk for different fecal pollution sources is evaluated in Soller, J.A., Schoen, M.E., Bartrand, T.A., Ravenscroft, J.E., and Ashbolt, N.J. 2010. Estimated human health risks from

ex posure to recreational waters impacted by human and non

- human sources of faecal contamination . Water Research. doi:10:1016/j.watres.2010.07.064.

## U.S. Environmental Protection Agency

August 2010 4 Introduction

Purpose

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

- 28) in the U.S. Environmental Protection Agency (EPA or the Agency) Critical Path Science Plan for Development of New or Revised Recreational Water Quality Criteria (CPSP or science plan) (USEPA, 2007a)

. The science plan is key component of EPA’s overall process to develop new or revised Section 304(a) Ambient Water Quality Criteria (AWQC) for recreational waters that will be used by States, Territories, and Tribes to develop their own water quality standards (WQS 4 

## ). The CPSP was developed, in part, based on feedback from a large group of stakeholders and the detailed input and recommendations from the scientific community provided in 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 Recreatio nal Water Study (NEEAR) Great Lakes 5 

## epidemiological data to inland waters. T his report evaluates whether the observed relationships between fecal indicator bacteria (FIB) densities and adverse health effects for Great Lakes waters are applicable to inlan d waters. To support this evaluation, the report also evaluates ―indicator performance‖ in inland and coastal settings, which includes the following: (1) the association of FIB densities with fecal pollution sources and their health effects, (2) an analys is of fate and behavior of FIB and select pathogens, and (3) an analysis of microbial ecology and persistence of FIB indicators and select pathogens.

Background

F ecal matter from human and animal sources can be a major source of waterborne pathogens.
B ecause 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). Thes e fecal indicator organisms

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

—have been used for decades to indicate the presence and magnitude of fecal material. This approach assumes that waterborne pathogens c o

- occur with the fecal material

.

4 

### Under the Clean Water Act ( CWA ) Section 303(i)(1)(B), States , Territories, and Tribes are required to adopt new or revised WQS for those pathogens and pathogen indicators for which EPA’s new or revised criteria have been developed. O nce approved by EPA, WQS are used for various CWA purposes and programs and are t he effective (enforceable) standards to protect w aters for specified designated uses , such as ―primary contact recreation.‖ The latter typically encompass es recreational activities that could be expected to result in the ingestion of, or immersion in, a water body (such as swimming, water skiing, surfin g, 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 Gre at 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 ―More specifically, fecal indicator bacteria provide an estimation of the amount of feces, and indirectly, the presence and quantity of fecal pathogens in the water‖ (NRC, 2004). Therefore, use of fecal indicator organism s in recreational waters is based on the presumption that their fate and behavior, ecology and persistence, and performance in all types of recreational waters, including marine, estuarine, and inland flowing and non

- flowing waters, remains consistent

.
―Traditional‖ indicators include culturable total coliforms, fecal (thermotolerant) coliforms, E. coli (an important member of the coliform group), and enterococci. 6 

## However, because the total coliform group has been shown to be a poor indicator of fecal contamination, they are no longer widely used in U.S. recreational waters . The attributes of an effective indicator (i.e., measures of indicator performance) are the following (adapted from NRC, 2004):

a demonstrated correlation with health risk;
simi lar 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 indi cator 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

- im pacted 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 r ecreational waters ( E. coli and enterococci for freshwaters and enterococci for marine waters) and gastrointestinal (GI) illness levels for those individuals exposed to recreational waters (USEPA, 1986). The recommended criteria based on these studies are still in effect and are required for use by all coastal and Great Lake states (USEPA, 2004).

EPA has conducted a significant amount of research since the BEACH Act was enacted in October 2000 and is finalizing research activities in accordance with the science plan to issue new or revised AWQC by 2012.

Overview of Epidemiology and Recreational Water Quality Criteria

Since the 1950s, numerous epidemiological studies have been conducted throughout the world to evaluate the association between recreatio nal water quality and adverse health outcomes, including GI symptoms; eye infections; skin irritations; ear, nose, and throat infections; and respiratory illness. Most of these studies are reviewed in one or more of the meta

analyses/systematic reviews of Prüss (1998), Wade et al. (2003), Zmirou et al. (2003). More recent epidemiology studies are reviewed in USEPA (2009) and WERF (2009). Both

6 

### The terms enterococci, Enterocooccus

, fecal streptococci

, fecal streptococcus, and intestinal enterococci are often used to refer to essentially the same environmental and fecal species of bacteria (see NRC, 2004 for further information). Thus, for convenience, this report uses the term enterococci unless othe rwise noted.

## U.S. Environmental Protection Agency

August 2010 6 prospective cohort (PC) and randomized control trial (RCT; also called prospective randomized exposure studies [F leisher et al., 2010]) epidemiology studies have been conducted to describe and quantify relationships between illnesses among swimmers and recreational water quality. It is beyond the scope of this report to comprehensively describe, compare, and contras t these two major epidemiology study designs. However, a very brief overview of their use in various recreational water studies

— including the development of U.S., WHO, and European Union (EU) recreational water quality criteria, guidelines, and standards, respectively

— is provided below.

Prospective Cohort Studies

EPA ’s current (1986) recreational water quality are based on the observed occurrence of GI illness associated with swimming in fresh or marine recreational waters receiving point sources of effl uent from POTWs as determined through several PC studies conducted in the 1970s through the early 1980s. Over the past several years, EPA has conducted several PC studies at four POTW

- impacted Great Lakes beaches and four marine recreational beaches (thre e POTW

impacted and one non

- POTW

- impacted) as part of the NEEAR Water Study . The results of the Great Lakes studies are published ( Heaney et al., 2009; Wade et al., 2006, 2008) while the marine studies have not yet been finalized

.

To date, most U.S. and international epidemiology studies of recreational waters have used the PC study design at marine beaches (e.g., Fattal et al.

, 1983; Haile et al., 1999; Marino et al., 1995 ) . Further, there have been relatively few studies of inland (non

- Great lakes) waters or of

non

- point source

- impacted recreational sites. Calderon et al. (1991) used a PC study to follow the health status and swimming activities of volunteer participants at a small inland pond in Connecticut whose source was rainwater runoff from a forested watershed in Connecticut. Recently, Marion et al. (2010) conducted a PC study of recreational users of an inland lake ( flood control reservoir ) in Ohio with multiple point and non

- point sources of fecal pollution

. Several U.S. PC studies of pre dominantly non

- point source

- impacted beaches in southern California have been completed (Colford et al., 2007) or are nearing completion (SCCWRP, 2008).

Randomized Control Trials

The other major epidemiological design used in recreational sites is the RCT. This design has been used extensively in Europe and more recently in the United States to determine the association between microbial water quality and increased risk of adverse health effects in swimmers vs. non

- swimmers in both marine and fresh rec reational waters. The WHO Guidelines for Safe Recreational Water Environments (WHO, 2003) apply to both fresh and recreational waters and are based, in large part, on RCT studies conducted in the late 1980s and early 1990s at POTW

- impacted marine recreati onal beaches in the U.K. (Fleisher et al., 1996; Kay et al., 1994). The EU adopted Directive 2006/7/EC of the European Parliament and of the Council of 15 February 2006 Concerning the Management of Bathing Water Quality and Repealing Directive 76/160/EEC (EP/CEU, 2006) is also based, in large part, on the same U.K. marine recreational water studies

, and a more recent RCT study of POTW

- and non

- point

source

- impacted fresh recreational waters in Germany (Wiedenmann et al., 2006). Epibathe (2009a,b) describe s the results of a series of RCT studies conducted at marine and fresh

## U.S. Environmental Protection Agency

August 2010 7 recreational waters in Europe in 2006 and 2007. Finally, the results of an RCT stud y of a non

POTW

- impacted marine beach in Miami, Florida have been recently published ( Abdelzaher et

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

Approach

To prepare this report, a detailed literature search and retrieval was performed in Fall 2008, the approach and summary of results of which are provided in Appendix B. Next, a series of analyses and summarizations of relevant studies (see Appendix A) were conducted to address indicator performance in inland and coastal settings 7 

## that are discussed in the five sections (2

- 6) that follow

— each of which includes a summary. After completi on of a draft report in early 2009, the report was revised, expanded, and finalized in 2010.

Following this background and introduction, Section 2 qualitatively compares and contrasts fecal indicator and pathogen loading and resuspension dynamics in inl and and coastal sites. Section 3 reviews fecal indicator sources and their association with health risk. Section 4 summarizes the occurrence of FIB in inland and coastal waters and evaluates whether they are different; it also compares and contrasts in F IB occurrence that is a ttributable to r ainfall and r unoff e vent s (event

scale v ariability ). Section 5 addresses survival of bacterial indicator organisms in inland and coastal settings, including a discussion of phenomena contributing to indicator removal

, o bservations of indicator organism growth in the environment, and a co mparison of measured decay rates . Lastly, Section 6 reviews indicator

- pathogen association s in inland and coastal settings

.

7 

### Categorized in this report as coastal freshwater, coastal marine water, estuarine, inland flowing water main stem, inland flowing water in a small reach, or inland non

- flowing water.

## U.S. Environmental Protection Agency

August 2010 8

Qualitative Comparison of Inland and Coastal Settings

Bo th 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 t o 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 gro w in their respective aquatic environments. This section qualitatively compares and contrasts fecal indicator and pathogen occurrence and dynamics in inland and coastal sites. ( Sections 5 and 6 provide a review of quantitative data for assessing differen ces in the dynamics of indicators and pathogens in inland and coastal settings.)

The differences between inland and coastal sites with the greatest impacts on the performance of indicator organisms are (Dorevitch et al., 2010; WERF, 2009) :

first and fore most, differences in source; differences in hydrology (loading and dilution potential); and differences in potential for indicator growth and resuspension.

A qualitative description of each of those features in inland and coastal waters is provided in the following sections, along with hypotheses on how these differences might influence indicator performance

.
Differences in Fecal Sources for Inland and Coastal Water s

As described in Section 3, epidemiological studies support the contention that associati on of illness with indicator level differs between sites that are human

- impacted (POTW discharges and perhaps urban stormwater runoff) and sites that are impacted by non

- human fecal pollution sources. Further, modeling studies indicate that different feca l pollution sources are associated with different suites of pathogens occurring at a given indicator level. Because pathogens, not indicators

, are responsible for illnesses, the fecal pollution source is believed to be a more important determinant of the association of indicator level with health effects for a given site than whether the site is an inland site or a coastal site. This contention is supported by findings of an experts workshop on indicators in inland and coastal settings (Dorevitch et al., 2010; WERF, 2009)

.
Although source is believed to be the most important factor determining the association between indicator density and health effects at a given site, no data source allows systematic comparison and contrast of the sources typical of in land and coastal waters. Dorevitch et al

. (2010) hypothesized that proportionally more inland waters than coastal waters are impacted by non

human sources of fecal pollution. However, the authors are not aware of a study that tests this hypothesis. Furt her, if it is true that fecal pollution source is a more important determinant of health effects than recreational site setting

— as contended by participants in the recent Experts Scientific Workshop on Critical Research and Science Needs for the Developmen t of Recreational Water Quality Criteria for Inland Waters (WERF, 2009)

— then classifying sites by their fecal pollution source rather than by their setting may provide an improved opportunity for

## U.S. Environmental Protection Agency

August 2010 9 developing criteria for different recreational sites. The v alidity of characterizing inland waters with a dominant source type notwithstanding, the impact of fecal source on correlations of indicator organism density and health risk in inland waters is discussed in Section 3.

Indicator performance in stormwater runoff from urbanized areas likely differs from that from rural areas characterized by lower impervious area proportion (WERF, 2009) . Again, this observation relates more to the source of fecalpollution than to whether a setting is inland or coastal and a s with distribution of fecal pollution sources among inland and coastal waters, it is unclear whether urban land use impacts proportionally more inland or coastal sites. Regardless of whether sites are inland or coastal, runoff from urbanized areas with a high proportion of impervious surfaces is flashier than that from rural areas. Additionally, impervious surfaces have less potential for retaining particles and bacteria and are expected to generate greater densities and higher loadings of suspended bac teria 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 coas tal or inland waters.

Pathogen and FIB L oading

Both inland and coastal waters receive FIB from point sources, diffuse sources including non

point sources, direct deposition (e.g., gulls, cattle in a stream), and resuspension of FIB in sediments or overba nks (NRC, 2004; WERF, 2009). These processes are illustrated for inland waters in Figure 1 and for coastal sites in Figure 2 . In this context, loading refers to the contribution of net numbers of indicators and pathogens to the receiving water for each s ource.

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 fe cal pollution is POTW (also called wastewater treatment plant [WWTP]) effluent, which in most cases is disinfected prior to discharge. Human sources of fecal pollution include on

- site wastewater treatment (―septic‖) systems, combined sewer overflow (CSO) and sanitary sewer overflow (SSO) discharges, urban stormwater, and leaking sewage conveyances. Livestock non

- point sources include fecal pollution directly deposited into streams (unlikely for coastal waters), runoff from wastes deposited by pastured ani mals, runoff from fields with land

- applied fecal wastes, and leakage or accidental discharges from stored wastes. Wildlife non

- point fecal pollution may be directly deposited into streams and coastal waters or deposited onto land surfaces and transported to receiving waters in overland flow.

Point and non

- point sources of fecal indicators and pathogens load receiving waters in fundamentally different ways. In general, fecal loads from POTWs are continuous, whereas those from non

- point sources occur due t o rain events, snow melts, recession of tides, and other precipitation

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

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

- event variations for pathogen s differ from those of indicators. Although these differences likely impact indicator performance, it is difficult to generalize these impacts given the wide differences between recreational sites, between events, and even in conditions during events.

POTW

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

- point sources. Indicator organism densities in untreated sewage are related to human intestinal densities of FIB. While there are variations in p roduction rates of indicator bacteria among individuals, the indicator loading of a POTW by a collection of individuals (population) is likely relatively constant. Treated POTW effluent is also characterized by relatively constant indicator densities, alt hough variations in WWTP performance and raw water quality may be important for plants treating sewage from combined sewer systems (i.e., a type of

## U.S. Environmental Protection Agency

August 2010 11 sewer system that collects sanitary sewage and stormwater runoff in a single pipe system ). The above consid erations support a general finding that POTW

- impacted inland and coastal waters are generally similar in terms of FIB loading because treated effluent discharges in both settings are relatively steady and not dependent on whether a site is coastal or inlan d.

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 pe rformance include shading, hydrodynamics, potential for deposition of particle

- associated microorganisms, and microbial ecology. Differences potentially affecting the relationship between indicator density and health effects are the fecal source and the t ransport of pathogens and indicators in the receiving water.

Biology and Mechanics of Resuspension

There are several potential sources of non

- (extra

- ) enteric indicator organisms in recreational waters. Under the right conditions, E. coli and other e nteric bacteria may bloom, as described by Ashbolt et al. (1997) for an impounded inland lake in Australia (see also Power et al., 2005). The conditions believed to contribute to the blooms of E. coli in that study were not exceptional and included the pr esence of sufficient organic carbon and surface temperatures above 18° C. The E. coli densities observed during the blooms however, were exceptional. The peak E. coli density observed during blooms was 298,000 CFU/100 mL throughout the top layer of the l ake and the E. coli density persisted above 5000 CFU/100 mL. Features of the water column may also promote the growth and persistence of FIB. Whitman and Nevers (2003) and Olapade et al. (2006) reported high densities and prolonged persistence of E. coli in algal mats of Cladophora in Lake Michigan waters and on Lake Michigan foresands. However, Olapade and colleagues showed that E. coli in the mats were seemingly not associated with exceedences of FIB

- based beach closure criteria, despite the very high densities in the algal mats. Their mesocosm experiments demonstrated much higher persistence of E. coli in the mats than in the water column.

The most commonly reported non

- enteric source of FIB appears to be sediments and soils. Originally thought to o ccur mainly in tropical soils (e.g., Carillo et al., 1985; Fujioka et al., 1999, 1999) , indicator bacteria are now known to persist or grow in temperate soils (e.g., Ishii et al., 2006a) , and beach sands in temperate areas at freshwater (e.g., Whitman et a l., 2003) or marine sites (e.g., Yamahara et al., 2009) . As noted above, growth condition requirements for FIB are minimal and are often present in soils and sediments. Further, sediments may shelter indicators from predators or otherwise shelter the org anisms and increase their persistence. The influence of sediments on the persistence and extra

- enteric growth of indicators is described in Section 5. Although there are differences in inland and coastal sites that could result in differing survival and growth potential in the two settings, the authors identified no studies that systematically compared growth and persistence of FIB in inland and coastal soils and sediments. However, WERF (2009) suggest that smaller sediment sizes and greater area of wett ed sediments per water volume for inland waters favor indicator growth and persistence in inland settings over growth and persistence in coastal settings.

## U.S. Environmental Protection Agency

August 2010 12 Resuspension of indicators for inland sites is illustrated in Figure 3 (a and b). In inland sites, bottom shear may resuspend indicators in bottom sediments as well as particles with attached bacteria and indicators. Once in the water column, these suspended bacteria are mixed and advected downstream. Indicators may also wash into the water from soil s during stream recession after storms, as depicted in Figure 3 b. 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 f orce imparted on the indicators. Because these two processes are variable, FIB density resulting from resuspension is also variable.

Resuspension at coastal sites is depicted in Figure 4 (a and b). Resuspension may be the result of waves breaking on sw ash zone sands and receding (4a) or may result as tidal waters recede and draw indicator bacteria into the sediments (4b) (Boehm and Weisberg, 2005; Santoro and Boehm, 2007; Yamahara et al., 2007) . As with inland waters, the net contribution of resuspensi on to indicator organism density at a coastal site depends upon accumulation of indicators in sands/sediments and the motive force for resuspending indicators. Resuspended loads are low when indicator reservoirs are depleted or the overlying water is quie scent.

Figure 3 . Resuspension Phenomena : Inland Waters

## U.S. Environmental Protection Agency

August 2010 13

Figure 4 . Resuspension Phenomena : Coastal Waters



## In summary, t he mechanisms and conditions for indicator and pathogen growth, persisten ce, and resuspension differ between inland and coastal sites. Inland settings are generally believed to be chara c terized by smaller sediment sizes, greater ratio of wetted area to water column volume, and high bottom shear stresses. Coastal sites are sub ject 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 resuspens ion 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 Fecal Indicator Bacteria Sources and Correlation with Health Effects in Inland Settings

In this section, the sources of indicator organisms and their association with health risk s are described. Studies used to connect inland and coastal sites to healt h effects include epidemiology studies of inland recreational waters , epidemiological studies of coastal waters with non

- human fecal impacts, and non

- epidemiological studies such as QMRA and catchment modeling (non

- epidemiological)

. See Pr ü ss (1998), USEP A (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 a nd health effects identified higher rates of at least some self

- reported health end points (usually GI illness) in relation to water exposure (usually swimmers vs. non

- swimmers).

Epidemiology Studies of Inland Recreation al Waters

This section compares select epidemiological studies to explore differences in the association of indicators with health effects in inland and coastal waters and in coastal waters impacted by different fecal pollution sources. Although the intent of this report is not comparis on of epidemiological study findings for coastal waters, those studies constitute the only information available for judging the impact of source on indicator

- illness relationships. Because it has been suggested that source, not setting (inland v s . coasta l) 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 n umber 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 G reat Lakes epidemiology studies at inland freshwater recreational sites, these are defined as coastal waters under the CWA and are not summarized in this report (see USEPA, 2009 and WERF, 2009). It is important to note that the Great Lakes epidemiology

st udies 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 furth er information) is using QPCR and culture

- based methods for FIB detection, its data and findings were not available for assessment in this report.

Collectively, these epidemiology studies indicate the following:

1. E. coli

, followed by enterococci, are pre dictive of GI illness rates in inland waters impacted by human fecal pollution. 2. When sites are impacted POTW effluent, data from freshwater inland and coastal sites may be pooled (i.e., indicator performance is the same for coastal and inland waters) when the sites are impacted by POTW effluent

— even when other fecal sources also impact the study site (see Marion et al., 2010)

. In studies of freshwater inland and coastal

## U.S. Environmental Protection Agency

August 2010 15 Table 1 . Summary of Completed Epidemiological Studies of Inl and 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 sys tems, runoff from row crop agriculture, runoff from natural areas (wildlife)

. PC E. coli density significantly associated with elevated odds of GI and highly credible GI (HCGI) illness. E. coli densities based on a single sample taken on study days.

Ill ness rates observed in this study similar to those observed by Dufour et al. (198 4 ) in the studies used to develop EPA’s current ( 1986 ) freshwater criteria. Those studies included a large

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

Linear regression of observed incidence of excess HCGI with E. coli density resulted in the relation:

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.
Ep ibathe (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 1 2% higher among bathers compared to non

- bathers (baseline risk)

, but not statistically significant.

The risk of GI illness was markedly high er when bathers exposed to >200 enterococci (CFU/100 mL) compared with those exposed to less enterococci; however, there was a lack of strong evidence of any dose

- response relationship between GI illness and enterococci levels.

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

- response curve did not exhibit a consistent trend of increasing incidence of illness with increasing E. coli density. Results suggest that E. coli might be a more appropriate indicator for predicting risk of GI illness in fresh recreational bathing waters than enterococci.

## 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

se tting 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 Waterfow l, 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 da ta from all the sites, recommended water quality guidelines are as follows :

Indicator Recommended water quality guideline

E. coli 100

Enterococcus 25 Somatic coliphage 10 Clostridium perfringens 10

NOAELs not dependent upon the choice of GI illness d efinition (three illness definitions were compared) but did depend upon the definition of exposure and the choice of indicator organism

Lee et al. (1997) An inland concrete water channel bypassing a lock on a

lowland river (Trent River) in the U

. K

. and us ed for white

water recreation (canoeists and rafters). River receive d treated sewage and during heavy rainfall, untreated sewage from stormwater overflows. PC Water samples collected for culturable E. coli , enterococci, F

specific RNA bacteriophage, sulph ite reducing clostridia, and enteroviruses.

Variables significantly associated with an increased risk of GI illness included swallowing water and levels of F

- specific RNA bacteriophage. Notably, being a regular facility user was associated with a decrea sed risk of GI illness (though immunity was considered unlikely).
Fewtrell et al. (1992) Two inland recreational water sites used for white

- water

recreation: (A) an artificial concrete channel diverting water around a weir in a multiple POTW

- impacted low land river; (B) an upland impound that was considered to be pristine. PC Site A had significantly higher counts of fecal coliforms and fecal streptococci (but not total staphylococci or enteroviruses) than site B.

Site A had significantly higher incidence s of GI and upper respiratory symptoms than site B canoeists or non

- exposed controls (spectators).

Frequency in reporting of all symptom groups was significantly higher at 5 to 7 days for site A vs. site B canoeists and this excess persisted at one month for GI symptoms and skin symptoms. ―Like seawater bathers, fresh

water canoeists can be made ill by sewage contamination.‖

## 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 pollutio n sources believed to be runoff from undeveloped lands, swimmer loads. Investigations prior to the study indicated no point sources or human pollution sources contributing to the pond. PC Swimmers had a significantly higher probability of GI illness than non

- swimmers, but no association found between indicator density (enterococci, E. coli

, Staphylococci

, Pseudomonas aeruginosa ) and incidence of GI illness among swimmers.

Ferley et al. 1989 Ardeche river basin (south of France), samples collected at 5

bea ches (2 considered most polluted, 2 intermediate, 1 least) used for recreation. ―Urban domestic sewage, the main source of pollution, entered the river untreated at the time of the study...‖ RC (retrospective cohort) Swimmers had significantly higher incid ence of self

- reported

GI illness than non

- swimmers. Fecal streptococci (enterococci) best correlated to GI illness. Swimmers also suffer skin, and ear, nose, throat (but not respiratory or eye) ailments much more frequently than non

- swimmers, which

was well correlated with the concentration of fecal coliforms, Aeromonas , and Pseudomonas

. Seyfried et al. (1985a,b) Ten lakes in Ontario, Canada. Papers do not state which or

how many of the beaches were on Lake Ontario and how many were on inland lakes, bu t some may be assumed to be inland waters. In analyses setting (inland vs. coastal) is not included as a factor. Although possible sources of fecal pollution are not described, WERF (2009) notes some were likely impacted by WWTP effluent discharges. PC Swimmers had a significantly higher probability of GI illness than non

- swimmers. Linear relationships between the logit of illness probability and logarithm of indicator density proposed for three indicator organisms: total staphylococci, fecal coliform s, and fecal streptococci
DuFour (1984) Keystone Lake, 15 miles from Tulsa, OK. Two beaches on

Keystone Lake studied over two recreational use seasons. In the first study year a wastewater treatment plant discharged unchlorinated effluent to the lake. In the second study year the WWTP chlorinated effluent. PC Data from both study years pooled with data from two Lake Erie beaches and log

- linear relationships between HCGI and both E. coli and Enterococcus density derived. Note that regression analyses us ed averaged data, not data from individual study days.

## U.S. Environmental Protection Agency

August 2010 18 3. sites used for development of the 1986 AWQC indicator level

- illness rate data were pooled. Those data have the same trend and are generally compatible with a more recent PC study of a human

- impacted inland site by Marion et al. (2010). 4. For both inland and coastal settings indicator organism densities are not necessarily related to increased risk of GI illness (regardless of how GI illness is defined) when the fecal impact is known or suspected to be non

- human. This contention is supported by findings of no illness

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

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

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

- impacted Grea t Lakes waters to POTW

- impacted inland waters. They do not provide sufficient information to assess extension of indicator organism density

- health risk relationships when fecal impacts are non

- human.

Note that in the studies by Wiedenmann et al. (2006) and Seyfried et al. (1985a,b) , the authors assumed that observed illness rates and indicator densities for POTW

- and non

- POTW

- impacted waters could be pooled. The findings of other epidemiological studies indicate this pooling should not be done without statistical analysis of the data.

In epidemiological studies of non

- POTW impacted

- waters there is frequently no association observed between indicator density and health risk. This was true for an epidemiology study of an impounded inland water (pond) with no known human fecal pollution impacts (Calderon, 1991) . Similarly, no or limited association of indicator organisms with GI illness has also been observed for a bird

- impacted coastal beach (Colford et al., 2007) , and a subtropical coastal marine bea ch 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 beac h are difficult to interpret (WERF, 2009). Presuming fecal pollution source is the dominant feature determining the health effects observed for recreational sites, epidemiological studies conducted to date

(1) do not support extending criteria derived for P OTW

- impacted waters to non

- POTW

impacted waters and (2) provide no information on the relationship between the level of traditional indicators and incidence of illness for sites not impacted by humans fecal pollution, despite a finding common to all studies th at swimmers have higher incidences of illness than non

swimmers.

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 effl uent;

## U.S. Environmental Protection Agency

August 2010 19 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 companio n animals; and runoff from areas impacted by wildlife.

As described by recent QMRAs by Soller et al. (2010) and Schoen and Ashbolt (2010) , human, cattle, swine, chicken and gull feces have different characteristic occurrences and abundances of indicator o rganisms 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, no t fecal indicator organisms, it is likely that the rates of illnesses arising from exposure to fecal pollution in recreational waters from different animal sources also differ. Further, because indicator densities differ among feces from different animals , it is likely that indicators levels will be associated with different illness incidences for different fecal pollution sources.

The hypothesis that a given indicator level is associated with different risks for different fecal pollution sources was test ed by Soller et al. (2010) and Schoen and Ashbolt (2010) . Those QMRA studies used reported indicator and pathogen densities from peer reviewed studies to develop characteristic ranges describing the occurrence and abundance of pathogens in treated

sewage, untreated sewage, gull feces, cattle feces, swine feces, and chicken litter. Key pathogens assumed to occur in animal feces were the bacteria Salmonella

, E. coli O157:H7, and Campylobacter ; the protozoan pathogens Giardia and Cryptosporidium ; and for hum an fecal pollution

—

norovirus (Soller et al., 2010) . The studies determined that an indicator level of 35 CFU of enterococci/100 mL (i.e., the current numeric criteria for marine recreational waters [USEPA, 1986]) is associated with roughly the same range of risks for indicator organisms originating from fresh human or cattle fecal pollution. However, Soller et al. (2010) determined that the risks associated with exposure to the same indicator levels but from fresh gull, chicken, or pig feces appears to be substantially lower than waters impacted by human fecal sources. They also concluded that their QMRA results are consistent with the findings from epidemiology studies that show that illness risk associated with non

- sewage

- impacted beaches appears to dep end on the source of contamination.

Catchment scale modeling provides an alternative , non

- epidemiological approach for relating fecal source and other site features wi th fecal indicator organisms with health risks. Till et al. (2008) conducted a large

- scale sampling and modeling effort to (1) evaluate the ability of E. coli to predict the presence of key pathogens and (2) determine an E. coli density at which actions should be taken. That study demonstrated that the degree of association between E. col i and the key pathogens differed among sites and, at individual sites, differed by season. Catchment types evaluated by Till and colleagues were those primarily impacted by birds, dairy or sheep operations

, i mpacted by urban runoff, and undeveloped catchm ents. The authors reported that

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

— despite the relatively infrequent observation of Campylobacter in the dairy catchments. The forested catchment was associate d with the lowest level of contamination. In all cases, regression modeling demonstrated that catchment type was the most important factor

## U.S. Environmental Protection Agency

August 2010 20 governing the occurrence of the indicators and pathogens. Water quality features such as turbidity were also found to be predictive of levels of indicators and pathogens, but less important than catchment type.

Ferguson et al. (2009) developed a comprehensive a dataset describing the occurrence and abundance of E. coli

, Cryptosporidium , and Giardia in all potential so urces that could contribute to recreational waters. The authors noted that quantifying the ranges and variability of pathogens and indicators contributed by fecal pollution sources is a first step in construction a predictive model of microbial loads gene rated within and exported from catchments. This catchment modeling effort recognizes the importance of source in connecting indicator organism density to health risk. Additionally, it describes and demonstrates an approach that accounts for the contribut ion of multiple indicator and pathogens sources to a receiving water. In that regard, the authors found that contributions from multiple sources are likely for the vast majority of recreational sites.

Ferguson et al. (2009) noted that the virulence of pa thogens in humans and their prevalence in the host animals are lower in wildlife than in domestic livestock animals, with the exception of wildlife living in close proximity to human fecal pollution. Despite this general observation, wildlife may still be an important source of zoonotic pathogens on a catchment

- by

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

Livestock is often kept for stocking purposes at much higher levels that can b e 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 den sities provide the potential for increased pathogen transmission between animals and as noted above, the prevalence of pathogens is often much higher in domestic species than in wildlife. Pathogens in livestock manures can persist for long periods in the environment, depending on the manure handling practices at a given operation. Fecal matter persistence is a special concern in cold

- climate, where pathogens can persist throughout the winter to be released from land along with snow melt or during precipit ation events. Land application requirements and best management practices may regulate the land application of manures on frozen or snow

- covered ground.

Fecal indicator and pathogen sources in catchments that contain urban development are primarily of hu man origin, but fecal loads from companion animals (e.g., cats and dogs) may also be significant (Ferguson et al., 2009). Human sources include sewage effluent, septic leachate from

on

- site sewage disposal systems, stormwater, and direct deposition from h uman recreation activities in rivers and storages. These sources may be categorized as treated sewage (POTW effluent) and untreated (all other sources). Because treatment plants are designed to meet effluent limits, indicator and bacterial pathogens in t reated human sewage is typically characterized by indicator organism densities much lower than those of primary sewage or other human sources (NRC, 2004).

## U.S. Environmental Protection Agency

August 2010 21 Summary

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

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

- human fecal pollution, the most promising avenue for exploring alternative criteria and risk levels for those sites is modeling studies.

In conjunction with the findings of inland recreational water epidemiological studie s, QMRA and catchment modeling studies demonstrate that indicators perform differently for sites with different fecal pollution sources. However, this finding cannot be applied in any direct way to assess whether water quality criteria for inland waters s hould differ from those developed for coastal waters. Although it has been suggested that inland waters are, in general, more associated with rural land use (Dorevitch et al., 2010; WERF, 2009) , the authors know of no data source allowing this assertion t o be tested. In most cases, it is likely that recreational sites are impacted by fecal pollution from multiple sources and the impact at a specific site is an aggregate of the impacts from all sources within the drainage to the site ( Ferguson et al., 2009 ; Till et al., 2008) . Recent QMRA studies have determined GI illness risks associated with exposure to fresh human or cattle feces in recreational waters may not be substantially different, whereas these risks appear to be substantially lower for recreati onal waters impacted by gull, chicken, and pig wastes.

## U.S. Environmental Protection Agency

August 2010 22

Occurrence of Fecal Indicator Bacteria in Inland and Coastal Settings

This section summarizes studies of the occurrence of FIB in inland and coastal waters and evaluates whether they are different. It also compares and contrasts FIB occurrence in both settings that is a ttributable to r ainfall and r unoff e vent s (event

- scale v ariability ).

Data Summary

A literature review (see also Appendix B) revealed a substantial number of studies that report ed the occurrence of FIB in a wide variety of inland and coastal water bodies. These are summarized in Tables 2 through 5 for E. coli , enterococc i , fecal coliform, and fecal streptococcus and total colifor m, respectively. Tables 2 through 5 summarize key features of each of the studies, including the setting ( which is categorized as coastal freshwater, coastal marine water, estuarine, inland flowing water main stem, inland flowing water in a small reach, or inland non

- flowing water), the number of samples , the duration of the study, the geometric mean, minimum and maximum reported values, the microbiological method used, and brief explanatory notes for each study

.
To facilitate interpretation of the data presented in Tables 2 though 5

, graphical summari es are provided in Figures 5 through 9 for E. coli , enterococc i , 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 st udy summarized in Tables 2 through 5 are presented (each study is shown as a vertical line) with in the aforementioned water body categories. Each water body type is represented by a different symbol. Note that in Figure 8 for fecal S treptococcus , only th e geometric mean values are illustrated. To develop these graphical summaries several simplifying assumptions were used. For example, minimum or maximum values that were reported below or above reportable limits were assumed to be present at those limits ; thus, a value that was reported as <10 was assumed to be equal to 10, and >10,000 was assumed to be equal to 10,000. Furthermore, geometric mean values only are shown for studies that reported standard deviations but not minimum or maximum values.

Pre suming t hat 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 th e 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.
E nterococci occurrence is slightly elevated in study results for coastal fresh and marine waters compared to those reported for estuarine, inland flowing (main stem and smaller reaches), and inland non

- flowing waters.
The occurrence of fecal coliform is not substantially different between results reported for coastal marine and estuarine waters compared to those reported for inland flowing (main stem and smaller reaches) and inland non

- flowing waters.

## U.S. Environmental Protection Agency

August 2010 23 Table 2

. Studies of E. coli Oc currence

Indicator Study Setting # samples Study Duration Geometric

Mean Min Max Methods Notes

E. coli Fattal. et al. (1987) Coastal marine waters 77 Summer 13 0 559 Not stated (reported as CFU) Reported values are base d 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) Estuary NA 1 mo 0 1300 Membra ne filtration Estuary has known high FC concentration

Mill et al. (2006) Estuary NA 1 mo 0 200 Membrane filtration Estuary has known high FC concentration

Buckwalter et al. (2006) Inland flowing

- main stem 135 1 yr 123 <10 910 Memb rane 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 s ites averaged; significant

seasonal variation

Cinotto (2005) Inland flowing

- small 10 One baseflow sample, all sites 195 50 1210 Membrane filtration For baseflow samples only. Median reported (instead of geometric

mean). High spatial variability in reach.

Cinotto (2005) Inland flowing

- small 45 One baseflow sample, all sites 960 <1 11,000 Membrane filtration For baseflow samples only. Median reported (instead of geometric

mean). High spatial variability in reach.

Crowther et al. (2002) Inland flowing

- small see duration
note Samples at 2

-

3 da y s interval, 1

- 2

mos Baseflow mean = 6200 High flow

mean = 140,000 Membrane

filtration Land use is primarily livestock grazing, multiple types

Crowther et al. (2002) Inland flowing

- small see duration
note Samples at 2

-

3 days interval, 1

- 2

mos Baseflow mean = 3100 High flow

mean = 200,000 Membrane

filtration Land use is primarily livestock grazing, multiple types

Donnison et a l. (2004) Inland flowing

- small 52 2 years, fortnightly Pastoral lands,

summer median = 1070 Upslope

stream, newly planted,

summer median = 68 Colilert

(MPN) Upslop e catchment were believed relatively free of human impacts. Large

seasonal variation observerd. EC concentration surprisingly high in unimpacted drainages

Giddings and Oblinger (2004) Inland flowing

- small High flow and low flow samples collected 2 days 140 29,000 Membrane filtration Land use is primarily forested and agriculture. Figure 5 shows minimal

difference in concentrations observed in tributaries and main stem

Hyer et al. (2007) Inland flowing

- small See max and min 2 yrs Low flow = 12 Storm flow = 34 Membrane

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

are wildlife Hyer et al. (2007) Inland flowing

- small See max and min 2 yrs Low flow = 23 (n=8) Storm flow =

176 (n=4) Membrane

filtration Data reported are chosen because stream order is higher site is

designated “recreational” Petersen et al. (2005) Inland flowing

- small 147 4 yrs 4664 <10 >10,000 IDEXX Numerous sites on Bayou samples. EC increased with stream mile. Tiefenthaler et al. (2008) Inland flowin g

- 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 Basefl ow = 682

– 3396 (n=22) High flow =

2759

– 5759 (n=13) MPN Land use in drainages is mainly agricultural (row crops)

Whitman et al. (2008) Inland flowing

- small ? ? 20.4 1412.5 Membrane filtration Only data prior to building a pond re ported. 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 w ere chosen because they were for one entire year of

sampling

## U.S. Environmental Protection Agency

August 2010 24

Table 3 . Studies of Enterococci Occurrence

Indicator Study Setting # samples Study
Duration Geometric

Mean Min Max Methods Notes

Enterococcus Haugland et al. (2005) Coastal fresh 47 2 mos 27 NA NA Membrane filtration Reported data are composite for one of two beaches studied

Haugland et al. (2005) Coastal fresh 47 2 mos 143 NA NA QPCR Reported data are composite for one of two beaches studied
Wade et al. (2008) Coastal fresh 1359 2 summers 770 0.05 376,000 QPCR Data f or all beaches used
Colford et al. (2007) Coastal marine waters 1897 6 days 29 ND 57,940 Chromogenic substrate Samples were taken hourly. Beach was in southern CA

Colford et al. (2007) Coastal marine waters 790 6 days 65 ND 141,053 QPCR Samples were taken hourly. Beach was in southern CA
Fattal. et al. (1987) Coastal marine waters 77 Summer 20 0 450 Not stated (reported as CFU) Reported values are based on data collected at 3 beaches on the

Mediterranean Sea

Gersberg et al. (2006) Coastal marine waters 14 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 cho sen because of 12 sites sampled, this had the

highest conc. Lipp et al. (2001b) Estuary 12 1 yr 79 19 395 Membrane
filtration Data reported were chosen because of 12 sites sampled, this had the

highest conc. Mill et al. (2006) Estuary NA 1 mo 1 68 Membrane
filtration Estuary has known high FC concentration

Mill et al. (2006) Estuary NA 1 mo 19 88 Membrane
filtration Estuary has known high FC concentration

Buckwalter et al. (2006) Inland flowing

- main stem 135 1 yr 15 <10 320 Membrane
filtrati on Upstream reach of the Monongahela River

Buckwalter et al. (2006) Inland flowing

- main stem 143 1 yr 30 <10 3,400 Membrane
filtration Downstream reach of the Monongahela River (Pittsburgh)

Chandramouli et al. (2007) Inland flowing

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

- main stem 171 2 yrs 108 10 270 MPN Heavily impacted waters (urban stormwater)
Buckwalter et al. (2006) Inland flow ing

- 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 Tributa ry 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 Membra ne 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 Enterol ert Reported values are for highest and lowest observed geometric mean among sites sampled

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

## U.S. Environmental Protection Agency

August 2010 25 Table 4 . Studies of Fecal Coliform Occurrence

Indicator Study Setting # sam ples Study Duration Geometric

Mean Min Max Methods Notes

Fecal Coliform Bordalo Coastal marine waters 184 3 weeks 4720 300 35,600 Membrane filtration Urban beach

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

Colford et al. (2007) Coastal marine waters 1897 6 days 25 ND 48,000 Membrane filtration and chromogenic substrate Samples were taken hourly. Beach was in southern CA

Crowther et al. (2001) Coastal marine waters 77 Uncertain 200 NA NA Membrane filtration Samples taken in bathing waters. Data after sewer repairs reported

Crowther et al. (2001) Coastal marine waters 77 Uncertain 920 NA NA Membrane filtration Samples taken in bathing waters. Data after sewer repairs reported

Fattal. et al. (1987) Coastal marine waters 77 Summer 46 1 650 Not stated (reported as CFU) Reported values are based on data collected at 3 beaches on the

Mediterranean Sea

Lipp et al. (2001b) E stuary 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 ch osen because of 12 sites sampled, this had the

highest conc. Buckwalter et al. (2006) Inland flowing

- main stem 135 1 yr 135 <10 690 Membrane filtration Upstream reach of the Monongahela River

Buckwalter et al. (2006) Inland flowing

- main stem 143 1 yr 360 <10 50,00 0 Membrane filtration Downstream reach of the Monongahela River (Pittsburgh)

Buckwalter et al. (2006) Inland flowing

- main stem 143 1 yr 260 <10 39,000 Membrane filtration Downstream reach of the Monongahela River (Pittsburgh)

Chandramouli et a l. (2007) Inland flowing

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

- main stem 171 2 yrs 360 20 1300 MPN Heavily impacted waters (urban stormwater)
Buckwalter et al. (2006) Inland flowing

- small 24 1 yr 435 10 13,000 Membrane filtration Tributary to the Monagahela River, presumed urban

Buckwalter et al. (2006) Inland flowing

- small 24 1 yr 100 <10 34,000 Membrane filtration Tributary to the Monongahela River, presumed urban

Buckwalter et al. (2006) Inland flowing

- small 52 1 yr 17000 220 410,000 Membrane filtration Tributary to the Monongahela River, presumed urban

Buckwalter et al. (2006) Inland flowing

- small 52 1 y r 10500 70 510,000 Membrane filtration Tributary to the Monongahela River, presumed urban

Edwards et al. (1997) Inland flowing

- small Unknown 3 yrs, storm and base samples 310 NA 75,000 Membrane filtration Uses are mainly pastoral and forested. One site ( out of 5) reported here.

Sites were similar. Seasonal variation observed.

Giddings and Oblinger (2004) Inland flowing

- small High flow and low flow samples collected 2 days 92 27,000 Membrane filtration Land use is primarily forested and agriculture. Figure 5 shows minimal

difference in concentrations observed in tributaries and main stem

Obiri

- Danso and Jones (1999) Inland flowing

- small 24 2 yrs 1333 NA NA MPN and Membrane filtration Sample sites were beaches on inland flowing waters. Data are for one of

two sample years

Petersen at al. (2006) Inland flowing

- small 625 5 yrs 1570 NA 200,000 Unknown Long

- term trends may be found in paper. Data since 2000 reported here.

Peterse n at al. (2006) Inland flowing

- small 410 5 yrs 4623 NA 200,000 Unknown Long

- term trends may be found in paper. Data since 2000 reported here.

Bragg and Clark (1992) Inland nonflowing waters 14 7 months 13 std dev = 42 Membrane filtration Reservoir with recreational use and drinking water source

Bragg and Clark (1992) Inland nonflowing waters 18 7 months 2097 std dev =
3145 Membrane filtration Reservoir with recreational use and drinking water source

He et al. (2007) Inland no nflowing waters 58 2 yrs 62,000 70 160,000 MPN Heavily impacted waters (urban stormwater)
Francy et al. (2000) Inland waters, multiple watersheds 136 7 mos 280 <1 16,000 Membrane filtration Data base is composite of results from NAWQA sites across the

continental US

## U.S. Environmental Protection Agency

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

Indicator Study Setting # samples Study
Duration Geometric

Mean Min Max Methods Notes

Fecal Streptococcus Crowther et al. (2001) Coastal marine waters 58 Uncertain 110 NA NA Membrane
filtration Samples taken in bathing waters. Data after sewer repairs reported

Crowther et al. (2001) Coastal marine waters 52 Uncertain 240 NA NA Membrane
filtration Samples taken in bathing waters. Data after sewer repairs reported

Crowther et al. (2002) Inland flowing

- s mall see duration

note Samples at 2

-

3 days interval, 1

- 2

mos Baseflow
mean = 1600 High flow

mean = 94,000 Membrane

filtration Land use is primarily livestock grazing, multiple types

Crowther et al. (2002) Inland flowing

- small see duration

note Samples at 2

-

3 days interval, 1

- 2

mos Baseflow
mean = 260 High flow

mean = 16,000 Membrane

filtration Land use is primarily livestock grazing, multiple types

Edwards et al. (1997) Inland flowing

- small Unkn own 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) Inlan d flowing

- small 24 2 yrs 182 NA NA MPN and
Membrane
filtration Sample sites were beaches on inland flowing waters. Data are from one

of two sample years.

Total
Coliform Bordalo (2003) Coastal marine waters 184 3 weeks 8790 150 72000 M embrane
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
substr ate Samples were taken hourly. Beach was in southern CA

Crowther et al. (2001) Coastal marine waters 59 Uncertain 320 NA NA Membrane
filtration Samples taken in bathing waters. Data after sewer repairs reported

Crowther et al. (2001) Coastal marine wat ers 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 m onths 34,761 std dev = 77,902 Membrane
filtration Reservoir with recreational use and drinking water source

Hoyer et al. (2006) Inland nonflowing waters 3107 1 yr 2070 0 23,800 Membrane
filtration Data reported were chosen because they were for one entire year of

sampling Francy et al. (2000) Inland waters, multiple
watersheds 115 7 mos 1200 <1 190,000 Membrane
filtration Data base is composite of results from NAWQA sites across the

continental US

## U.S. Environmental Protection Agency

August 2010 27 Figure 5 . Summary of Reported E. coli Densities in Various Water Types ( d ata shown are min imum , g eometric mean , and max imum v alues )

.

Figure 6 . Summary of Reported Enterococci Densities in Various Water Types (data s hown are min imum , g eometric mean , and max imum values )

.

## U.S. Environmental Protection Agency

August 2010 28 Figure 7 . Summary of Reported Fecal Coliform Densitie s in Various Water Types ( d ata s hown are min imum , g eometric mean , and max imum values )

.

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

## U.S. Environmental Protection Agency

August 2010 29 Figure 9

. Summary of Reported Total Coliform Densities in Various Water Types ( d ata s hown are min imum , g eometric mean , and max imum values )

.


## Total coliform occurrence is not substantially different between coastal marine waters compared to inla nd flowing main stem and inland non

- flowing waters. However, the amount of data available for this comparison is less than that for E. coli , enterococci, or fecal coliforms. Very limited data are available to compare the occurrence of fecal Streptococcus in coastal waters compared to those for inland waters. Nevertheless, based on the data that are available, the occurrence of fecal Streptococcus is not substantially different between coastal and inland waters.

These qualitative comparisons and observati ons 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 chromogeni c 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 di d not specify or fully articulate their detection methods. The extent to which the FIB occurrence results

— especially for studies using different methods or measurement units (e.g., MPN, CFU, cell equivalents, etc.)

— can be compared accurately is not clear. Second, the extent to which variations in the sampling regimes influence the reported FIB occurrence results is not known. For example, several studies reported that temporal and spatial variability was substantial (e.g., based on seasonal effects and/o r rainfall) and other studies appear to have established their monitoring protocol based on a fixed schedule (e.g., monthly samples). Third, the studies were conducted in locations with diverse fecal pollution sources. For example, the

## U.S. Environmental Protection Agency

August 2010 30 dataset comprises sources as diverse as urban storm water impacted sites, agricultural lands used for livestock grazing, and a watershed believed to be relatively free of human impacts. Thus, there are insufficient data available to unambiguously determine whether FIB leve l trends, if they exist, are primarily due to water type (inland or coastal) or predominant source of fecal contamination.

Event

- Scale Variability : Rainfall and Runoff

Rainfall and runoff effects on FIB density include loading (e.g., wash

- off of indica tors with surface flow, washout of indicators from beach sands or river bank sediments, initiation of CSO or SSO events) and dilution (Gentry et al., 2006; Vidon et al., 2008) . The complex relationship between hydrology and indicator organism density freq uently results in poor correlation between hydrologic variables (e.g., stream flow and precipitation) and indicator organism density

, but better correlation between hydrologic variables and indicator load . As noted by Petersen et al. (2005) , ―bacterial po llution is characterized in terms of concentrations, but concentration data may be misleading if not related to the flows from each source as loads are additive, while concentrations are not.‖

Inland Sites

Traister and Anisfeld (2006) noted that stream E. coli density response to storms was not simply related to precipitation and that response varied greatly between storms. They also reported that changes in E. coli density may be related to land use, with more urbanized stream reaches showing a smalle r response (change in density) for a given storm than less urbanized reaches. The response of stream indicator density to rainfall events varies significantly from storm

- to

storm (Dorner et al., 2007) and within storms (Baxter

- Potter and Gilliland 1988; J amieson 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 studi es of FIB density changes in streams during storms, Edwards et al. (1997)

, Haack et al. (2003) , and Jamieson et al. (2005) all also observed higher densities associated with the rising limb of the hydrograph. Jamieson and colleagues speculated that indica tor densities are higher during the rising limb because there is a greater availability of particle

- associated bacteria to be resuspended.

Rainfall influences on indicator organism densities in inland streams and coastal sites located near the outlet of streams have been observed in relatively undeveloped watersheds as well as in watersheds dominated by storm water or POTW discharges. In an agriculture

- and woodland

dominated watershed in Jersey, U.K., FIB density (total coliforms, E. coli , and Streptoc occus ) 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 ind icator 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 down stream of the bird sources could be attributed to sedimentation. These studies provide further evidence of the complex interactions between precipitation, loading, and geography that give rise to temporal changes in FIB density.

## U.S. Environmental Protection Agency

August 2010 31 The importance of individu al fecal sources in determining the indicator density in a waterbody may also vary significantly with rainfall. For example, using combined water quality data and microbial source tracking (MST) data, Shehane et al. (2005) observed that a coastal stream i n Florida was predominantly impacted by animal sources during a period of drought while being predominantly impacted by human sources during periods of normal precipitation. The authors demonstrated that a composite index based on measurements of multiple FIB was a better indicator of water quality and provided a better correlation with rainfall than the occurrence of any individual indicator organism. This finding is consistent with the observation that there are typically multiple sources influencing th e microbial water quality of a given water body and that their relative importance changes temporally (Ferguson et al., 2009; Till et al., 2008).

Thresholds at which rainfall and runoff produce large changes in FIB density have been shown to differ betwee n 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 signi ficantly different after storms with net precipitation of ≥2.5 cm than when rainfall was <2.5 cm. This difference was observed at stations relatively near the coast (within 250 m) and for stations further offshore.

Coastal Sites

The duration of the ef

fect a rainfall event has on the microbial water quality of a coastal site is variable. For a marine beach in harbors receiving storm water runoff from urbanized areas, Hose (2005) reported that rainfall during the previous 24 hours accounted for 5 to 10× more variability in FIB density using a regression models than rainfall in other time periods (previous 48 hours, 22 hours, etc.). Chigbu et al. (2005) observed that in an estuary on the Gulf of Mexico, the time required for fecal coliform density in the estuary to fall to a geometric mean of 14 fecal coliforms (MPN) per 100 mL ranged from 0.3 to 12.9 days. Similarly, Haramoto et al. (2006) found that E. coli levels in marine coastal sites fell to pre

- storm levels ―within a few days‖ of the rain event in Tokyo Bay. The lag between a rainfall event and a subsequent change in indicator organism density at a coastal site may vary significantly with the orientation of the site to storm water outfalls, river outlets, or other point or contained sources of ind icator organisms. Haack et al. (2003) noted that on the Grand Traverse Bay, Lake Michigan (which is considered a coastal water under the BEACH Act of 2000 and within this report), there was a 48 to 72 hour lag between rainfall and elevated E. coli density at southern shoreline beaches, but no such lag was observed for western and eastern shoreline beaches.

The influence of rainfall events on beach water quality along the California coast has been observed to be much higher near storm drains, particularly those in urbanized areas, and to persist for more than 36 hours after a large storm (Noble et al., 2003) . The authors reported that following a large storm with total precipitation between 2.7 and 7.8 cm, 87% of beaches in close proximity to urban runoff outlets failed to meet California numeric WQS (10,000 MPN or CFU per 100 mL total coliforms; 400 MPN or CFU per 100 mL fecal coliforms; or 104 MPN or CFU per 100 mL enterococci) based on single samples. The extent of California shoreline exceeding

one or more of these criteria following the storm was 10× greater than during dry weather conditions. Among samples with FIB levels exceeding the WQS, the measured indicator density was generally far greater than the standards. In contrast, exceedences during d ry weather

## U.S. Environmental Protection Agency

August 2010 32 conditions tend to be only slightly above the standards. This study indicates both the importance of rainfall events on FIB occurrence in coastal sites and the persistence of effects of rainfall on microbial water quality for a significant peri od following the event. In other words, dilution cannot be assumed to completely mitigate rainfall effects at coastal sites or to ensure rapid return of FIB density to pre

- storm levels.

Rainfall and runoff generate indicator organism loads from sands and sediments on beaches in addition to from external sources such as storm drains and stream discharges. Whitman et al. (2006) observed E. coli response to a rainfall event for hydrologically

- connected sand, pore water, and lake water. E. coli density in a ll three media increased in the early stage of the rainfall event, with sand E. coli density falling more sharply and rapidly than in pore and lake water following the event. This observation indicates the potential for high loading of indicator organisms originating from beach sands or stream sediments early in storms, and lower loadings after sediments and sands are depleted of FIB, late in rainfall events. This observation is consistent with the findings of Yamahara et al. (2007) who observed mobilizat ion of enterococci during a rising tide or due to wave action, followed by reduced loading as sediment indicator bacteria were depleted.

Summary: Event

- Scale Indicator Variability

Event

- scale variability is the single greatest variability (including both temporal and spatial variabilities) of fecal indicator organism density for coastal and inland waters, which vary in terms of hydrodynamics. During events, FIB densities at inland and coastal sites may undergo orders

- of

- magnitude changes. Events account for a large fraction of indicator organism loadings to source waters for drinking water, inland lakes and reservoirs, and coastal sites. For inland settings, indicator densities correlate poorly with rainfall amounts due to dependence of indicator

respon se on factors such as antecedent rainfall (which relates to soil capacity to retain storm water and the number of indicator organisms available for runoff into receiving waters) and the input of FIB from sources such as CSO discharges. In general, FIB den sity peaks during the rising limb of the storm hydrograph when loading to the stream is high and streams are turbulent, promoting resuspension of sediment

- associated indicators. Indicator densities also generally decline faster than the hydrograph after in dicators are (temporarily) depleted. The time required for the indicator density in a flowing or impounded inland water body to recede to pre

- storm levels is highly variable among drainages and even within a particular drainage. Similar trends have been observed for coastal sites

— indicator densities rise quickly during storms due to loading from stormwater runoff, near

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

scale variability to be of less significance at coastal sites vs. inland streams, poor mixing in the vicinity of stream outlets and stormwater outfalls appears to contribute to extreme changes in indicators densities associated with events.

Summary

Ba sed on a literature review of FIB occurrence in a wide variety of inland and coastal water bodies, and presuming t hat it is reasonable to directly compare the se results, a qualitative inspection of the summarized study data indicates that there do not appe ar to be substantial

## U.S. Environmental Protection Agency

August 2010 33 differences between inland and coastal waters for E. coli , fecal coliforms, fecal Streptococcus (enterococci), or total coliforms. The hydrodynamics of inland and coastal sites are different and are associated with apparent difference s in the responses of indicator organism densities to precipitation events. These differences have clear implications with respect to implementation of new or revised recreational water quality criteria. Knowledge of the period(s) during which rainfall i nfluences FIB density most significantly can inform when to conduct monitoring and when beaches should be closed or when to issue beach advisories in the event of adverse microbial water quality. Such information could be used in conjunction with monitori ng and (predictive) modeling approaches for risk management approaches (USEPA, 2007a). The direct implications of event

- scale variability on differences of FIB occurrence in inland and coastal settings for the development of new or revised recreational wa ter quality criteria are less certain

— both types of settings exhibit extreme variability in indicator organism density following significant rainfall. Although coastal sites may respond to storms later and for prolonged durations compared to inland sites, FIB responses at locations near tributary or storm water outfalls may be similar to inland waters responses. Insufficient data are currently available to evaluate whether FIB densities are correlated differently with health risks at inland and coastal si tes during rainfall events (see Section 3). Similarly, insufficient data are currently available to assess whether pathogen

- to

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

## U.S. Environmental Protection Agency

August 2010 34

Survival of Fecal Indicator Bacteria in Inland and Coastal Settings

In this section, the survival (inactivation, removal, predation or growth) of indicator organisms in coastal and inland settings is compared and contrasted. General descriptions of indicator survival and condition s under which growth has been observed are provided. Survival data taken from in situ and laboratory experiments conducted in or with waters from different settings are then compared.

General Description of Indicator Decay in Natural Waters

General fe atures of E. coli decay in coastal fresh water (from Whitman et al., 2004) are illustrated in Figure 10 , while Figures 11 and 12 cover estuarine (coastal) seawater and inland flowing waters, respectively. The survival curves chosen to illustrate decay in the three settings are representative of those found in the literature and were chosen because they are the result of experiments conducted in situ under comparable conditions. The curves for the three settings are similar, all displaying ―shoulder‖ behav ior (i.e., slow removal/die

- off or perhaps growth early in the experiment) followed by apparent first

- order decay.

Figure 10 . Survival Curves for E. coli from in situ Mesocosm Experiments in Coastal Fresh Waters. O pen triang les denote counts from experiments in dark bags, filled inverted triangles denote counts for experiments conducted in ambient lake water

, and open circles show counts for experiments conducted in transparent bags (SOURCE: Reprinted, with permission, from W hitman et al., 2004 © American Society for Microbiology )

.

## U.S. Environmental Protection Agency

August 2010 35 Figure 11 . Survival Curves for E. coli in Seawater. S ymbols denote the month in which experiments were conducted

— open circles: February; filled circles: March; open tria ngles: April; filled triangles: May; open squares: July; filled squares: November ( SOURCE: Reprinted, with permission, from Rhodes and Kator, 1988 © American Society for Microbiology )

.

Figure 12 . Survival Curves for E. coli i n Freshwater, Stream Settings. O pen symbols denote results from experiments conducted in situ ; filled symbols denote results from experiments conducted in natural waters in the laboratory (SOURCE: Reprinted, with permission, from McFeters and Stuart

, 1972 © American Society for Microbiology )

.

## U.S. Environmental Protection Agency

August 2010 36 Non

- first

- order behavior observed in the decay of E. coli has been attributed to the availability of substrate (Hijnen et al., 2007; in explanation of shoulders) and predation (e.g., Davies et al., 1995; based on obse rvations in sediments with and without predators). Despite frequent non

first

- order behavior, experimental studies of indicator survival typically report decay rates as first

- order decay constants. 8



## Phenomena Contributing to Indicator Removal

The thr ee primary factors demonstrated to influence the survival of FIB in all settings are solar radiation (e.g., Anderson et al., 2005; Bordalo et al., 2002; Harwood, 2004; He et al., 2007; Jeong et al ., 2005; Lipp et al., 2001a; Šolić and Krstulović, 1992), temperature (e.g., Alkan et al., 1995; Noble et al., 2004; Okabe and Shimazu, 2007; Rhodes and Kator, 1988; Šolić and Krstulović, 1992; Wait and Sobsey, 2001), and salinity ( e.g., Anderson et al., 2 005; Bordalo et al., 2002; Fujioka et al., 1980; Šolić and Krstulović, 1992). Other factors, such as nutrient availability, turbidity, organic matter, and pH, appear to play a smaller role in FIB survival within the range of values usually encountered in natural surface waters. In general, solar radiation greatly enhances die

- off, higher temperature promotes faster decay (though some reports indicate this may not be universally true), and decay of FIB is faster in saline waters than fresh. The influence of temperature on survival is complex, partly due to predation on removal of indicator organisms and the dependence of predator density on temperature.

These three primary factors (solar radiation, temperature, and salinity) may differ between inland

an d coastal sites. For example, tree shading of inland (riparian) sites may result in both lower average temperature and insolation in comparison with coastal sites, where shading is minimal. Temperatures of inland waters may be, on aggregate, systematical ly different from those of coastal waters. For example, during warm months small spring

- fed streams are expected to be cooler than nearby lakes and coastal waters and smaller bodies of water are expected to experience greater temperature fluctuations than larger water bodies with higher thermal capacity. Temperature and insolation differences can exert direct influence on FIB growth and survival or produce a secondary influence on survival via changes in predator populations. An additional possible secon dary effect of solar radiation and temperature is the differential survival of indicators and pathogens. If indicators and pathogens have different sensitivities to temperature change and solar radiation, differences in these factors may alter relative ab undance

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

.

## U.S. Environmental Protection Agency

August 2010 37 of the pathogens and indicators, resulting in a difference in the association of indicators with specific pathogens (one feature of an effective indicator) in coastal and inland settings.

## U.S. Environmental Protection Agency

August 2010 38 Growth Observations

Several researchers (e.g., Carillo et al., 1985; Hardina and Fujioka, 1991) have demonstrated that fecal indicators (especially E. coli and fecal coliforms) grow in tropical climates under the right conditions and have greater persistence (if not growth) in sediments than in the water column. There is an increasing awareness that growth of FIB occurs in other climates and under a variety of conditions, including temperate conditions in the continental United States. Reports of growth in the water column for a variety of settings are summarize d 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 F IB are selectively cultured. It may be assumed that bacterial populations used in growth experiments were mixtures of viable, non

- viable, and perhaps damaged cells. Because growth was observed in controlled settings, it can be assumed that viable cells a re capable of growth under equivalent conditions in situ . In addition to the studies listed in Table 6, many studies have demonstrated growth of FIB in sediments and soils from a variety of settings. The general features that are the most important in fo stering 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. Fewe r studies have reported growth of enterococci than of E. coli and fecal coliforms; however, it is not certain whether this is because enterococci growth is less prevalent than that of the other indicators or whether fewer studies have been made of enteroco cci.

There are relatively few features of inland and coastal sites that could distinguish these settings with respect to their ability to support FIB growth. For example, Davis et al. (1995) assessed the effect of dechlorination on FIB concentrations in WWTP effluent and found that, regardless of setting, the regrowth of FIB in dechlorinated WWTP effluent was minimal. Two potential differences between coastal and inland sites relate to growth of FIB in sediments. The sediments of coastal and inland sit es 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 an d pathogens from sediments is highly variable. This is because the fluid dynamics of both inland and coastal settings are highly variable and, at present, are not well characterized. Coastal and inland resuspension may be driven by different features of the setting. In coastal settings, wave action and tidal fluctuations may dominate whereas bed scouring during rainfall events could be the dominant cause in inland flowing settings. In inland non

- flowing settings one study implicated motor boat use in in creases in indicator concentration in the water column, presumably through resuspension (An et al., 2002).

## U.S. Environmental Protection Agency

August 2010 39 Table 6 . Reports in which Fecal Indicator Bacteria Growth has been Observed or Inferred

Study Climate Water Type Media Gro wth Conditions Growth Observation s 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

reac h; some study sites characterized as relatively unimpacted by sewage and others directly impacted by sewage B ifidobacterium adolescentis (an alternative bacterial indicator organism evaluated by the study authors) did not increase over time for in situ gro wth experiments Desmarais et al., 2002 Tropical Estuarine Waters from a brackish creek mixed with sterile sediments Laboratory experiments conducted with waters from a brackish creek Within 30 hours of addition of small amounts of sterile soils to water s amples, 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 domest ic sewage pollution Experiments performed with and without sterilization of the media, with and without sediments mixed with waters and with and without nutrients eluted from sediments Growth and sustained high levels of E. coli occurred in waters dosed wi th nutrients eluted from sediments; growth of approximately 5

- logs realized within 3 days

Hardina and Fujioka, 1991 Tropical Fresh Water from a tropical stream with known impacts of human sewage; observations performed in situ and in laboratory experiment s 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 dra wn from a tropical stream and with incubation temperature in the range 23 to 25 C Under laboratory conditions, fecal coliforms concentration increased by more than 2

- logs within two days and maintained high concentration through a third day E. coli obse rved to grow in both laboratory and field conditions during the first 24 hours of incubation; growth greater under field conditions Enterococci did not experience growth under laboratory or filed conditions Although growth observed in water, multiplication in streams deemed unlikely to be the cause of high levels of E. coli and enterococci in streams because the residence time in streams is low and because growth conditions are less than ideal due to suboptimal temperatures, nutrients and competition with o ther bacteria

## U.S. Environmental Protection Agency

August 2010 40 Study Climate Water Type Media Gro wth Conditions Growth Observation s 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 are a (Tokyo) has four seasons and water temperature ranged from below 10 C to above 25 C Total coliforms

, E. coli

, and fecal streptococci (enterococci) detected at control sites irrespective of season Coprostanol concentrations measured at control sites con current with FIB concentrations were below the detection limit, indicating that E. coli and fecal streptococci were naturally present in soils or feces of animal origin Lee et al., 2006 Subtropical Marine Water from the water column with or without sedime nt 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

s ediments Sediments may contribute organic content required for growth Okabe and Shimazu, 2007 Temperate Fresh and low salinity
waters Unfiltered river water

and unfiltered marine water diluted with unfiltered river water Laboratory observations made of
gr owth/decay of 6 fecal indicators ; f resh 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 p pt ( k = 0.11 d - 1 

### ) and 10 ppt ( k

= 0.07 d - 1 

### ) Net decay of total coliforms observed at salinities greater than 10 ppt Net decay of fecal coliforms observed at all salinities and temperatures, though decay rate in fresh water at water temperature of 10 C was very low (0.02 d - 1 

### ) Rhodes and Kator, 1988 Temperate Estuarine Filtered and unfiltered estuarine water inoculated with suspensions of E. coli and Salmonella spp. In situ experiments in diffusion chambers ; g rowth and decay monitored during all 4 seasons an d 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

## U.S. Environmental Protection Agency

August 2010 41 Comparison of Measured Decay Rates

To assess potential differences in decay related to setting, observed decay rates from mesocosm studies are compared. Because in situ studies appear best suited to demonstrating differences related to setting, attempts were made to u se 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 plotte d in Figure 13 . In Figure 13, the lines are the range of the decay rates in a particular study and the symbols correspond to the setting in which the study was conducted. Except for one study that reported extreme variability in decay rate (Beaudeau et a l., 2001), decay rates appear to be comparable, regardless of setting or water type. This finding is counter to the observation that E. coli survival is greater in fresh waters than marine waters.

No in situ mesocosm studies were found for enterococci, though numerous laboratory mesocosm studies were found (Table 8). Decay rates corresponding to different light conditions are reported, though comparison of these decay rates is not possible, since the light conditions (artificial versus natural light sou rce, net UV radiation dose received, turbidity, etc.) varied widely between experiments. One series of studies (Sinton et al., 1994, 1999, 2002) introduced a different rate expression for microorganism decay based on the net dose of solar radiation receiv ed 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.

## U.S. Environmental Protection Agency

August 2010 42 Table 7 . Decay Rates for E. coli Reported in Studies Conduct ed with in situ Mesocosms

Study Setting Indicator Temperature or Month Average or

Median Decay Rate (d - 1 

### ) Decay Rate

Range (d - 1 

### ) Notes Beaudeau et al., 2001 Inland flowing, small

and medium

- sized
streams E. coli 11.9 5.86 0.221 to 41.1 Decay rate for smal l 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 cli mate 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 Coas tal marine

setting E. coli February (Australia) 1.80

— Studies conducted in a subtropical climate Reported decay rate calculated based on reported T 90 

### and assuming first

- order decay Decay rates determined in laboratory microcosm studies comparable with tho se 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 Re ported values calculated based on survival times reported and assuming decay follows first

- order kinetics E. coli densities determined via Coulter Counter (CC) and acridine orange ( stain ) direct count (AODC) ;

r esults reported based on CC determination ; g ro wth inferred from AODC counts V. cholerae more persistent than E. coli and growth of V. cholerae o bserved Pérez

- Rosas and Hazen, 1989 Inland flowing setting,

small stream E. coli 22 0 (stability)

— Studies conducted at two sites Studies conducted in a tro pical climate E. coli densities determined via CC and AODC ; r esults reported based on CC determination ; d ecay at a low rate inferred from AODC counts Rhodes and Kator, 1988 Inland flowing,

tributary in estuary upstream waters E. coli 25.1 (range 6.7 to 28. 2) 0.65

- 0.36 to 0.86 Studies were conducted in a temperate climate Salinity corresponding to mean decay rate was 8.2‰

## U.S. Environmental Protection Agency

August 2010 43 Study Setting Indicator Temperature or Month Average or

Median Decay Rate (d - 1 

### ) Decay Rate

Range (d - 1 

### ) Notes Rhodes and Kator, 1988 Coastal/estuarine,

estuary mouth E. coli 27.9 (range 5.9 to 27.9) 0.51

- 0.72 to 0.51 Studies conducted in a tempe rate climate Salinity corresponding to mean decay rate 18.2‰ Experiments conducted with filtered and unfiltered water; filtering water reduced removal rates significantly and resulted in growth for experiments conducted in July Wait and Sobsey, 2001 Coast al/marine E. coli 22 to 24 (full range 4 to 24) 0.58 0.58 to 2.56 Studies conducted in a temperate climate Studies conducted at depths of 3 and 10 m ; d ata reported are for 3 m depths ; r esults at both depths similar Results inconsistent with typical temper ature trends

— the lowest decay rate observed at the highest temperature; this finding inconsistent with findings in laboratory microcosm studies Whitman et al., 2004 Coastal, freshwater E. coli 0 (stability) 0 to 0.746 Studies conducted at a depth of 45 c m in dark and clear bags ; n o decay observed during 12 hours in the dark bags Studies conducted in a temperate climate Against expectations, measured decay rates for transparent mesocosm studies greater at 90 cm depth than 45 cm depth and greater on variab ly cloudy days than sunny days

## U.S. Environmental Protection Agency

August 2010 44 ,

where k

S 

## is a solar radiation decay constant (m 2 

## /MJ), S is the 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 enteroco cci decay rates among settings. The decay rates observed in mesocosms kept dark are comparable (0.561 d - 1 

## for fresh water 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 Sinto n and colleagues shows that there was variation in the decay rates for experiments conducted in marine and freshwaters and results cannot be used to infer differences in decay rate for enterococci in different settings. However, as noted above, regardles s of setting, light has a strong impact on decay rate and growth in the water column and can be observed when small amounts of sediment are included in the mesocosm.

Table 8 . Decay Rates for Enterococci from Laboratory Mesocosm S tudies

Study

Water T ype

Media Organism †



### Decay Constant or Range (min - 1 

### ) Experimental Conditions

Alkan et al.

, 1995 Marine 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 ‡ 

### Fres h Water Ent k min 

### = 0.561 Dark, ambient temperature (Bangkok) k max 

### = 1.354 Natural sunlight, ambient temperature Marine 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 present, T = 28° C, dark Decay No sediment present, T = 28° C, dark Hartel et al.

, 2005 Marine Sed Ent Growth Dark, T = 25° C Sinton et al.

, 1994 Marine Water Ent k min 

### = 0.115 Dark, cold, with sewage addition k max 

### = 0.187 Dark, warm, with sewage addition 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 stabil ization 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 ; i n 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 

### )

## U.S. Environmental Protection Agency

August 2010 45 Summary

Bacterial indicator organism survival is largely determined by the insolation, temperature, and sal inity of the setting in which they live. These features vary from site

- to

- site and do not appear to be related to whether a site is coastal or inland. Possible connections between the site setting and the factors determining survival include differences in shading associated with inland and coastal sites, temperature differences typical of coastal and inland waters, growth potential in sediments typical of inland and coastal waters, and potential for resuspension by different mechanisms in coastal and inl and waters.

To evaluate whether systematic differences in survival have been observed in coastal and inland settings, decay rate data from in situ and laboratory mesocosm studies were compared. In situ mesocosm decay rates for E. coli were surprisingly s imilar, even between fresh and marine waters. Fewer data were available to evaluate differences in enterococci decay. The assembled decay rates for enterococci indicate solar radiation has a strong effect on decay rate and that decay/growth is radically different in mesocosms with a small mass of sediment compared to mesocosms with only water. Neither of these findings seems to indicate specific differences between inland and coastal waters.

Several features were not considered in this discussion of sur vival, but are potentially important, and include the following:

removal via settling in different settings (e.g., coastal marine, inland flowing stream, inland non

- flowing waters); differences in microbial ecology in different settings; and fluid dynami cs of different settings

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

Each of the above phenomena is complex and the studies reviewed in preparation of this report did not provide a means for assessing them. It is likely th at additional research is required before their impact on indicator survival can be estimated for coastal and inland settings.

## U.S. Environmental Protection Agency

August 2010 46

Indicator

- Pathogen Association in Inland and Coastal Settings

As noted previously, effective indicator s should be specifi c to t he target organism yet retain broad applicability (NRC, 2004) . In this section

, the ability of indicator organisms to meet these

two related criteria in coastal marine waters, coastal fresh waters, inland flowing waters

, and inland non

- flowing waters are compared and contrasted.

Studies assessing correlations or relationships between indicators for inland and coastal settings were compared in an attempt to discern differences in the association of indicators with pathogens in those settings. In general, few statistically significant correlations were reported between any of the traditional indicators and any pathogenic organism for site

- specific studies

— though more highly fecal polluted waters do have a higher incidence of both pathogens and indicators. Temporal and spatial trends in indicator density and pathogen concentration are frequently contrary. Different trends in pathogens and indicators may arise because (1) their primary sources may be different ; (2) pathogen loadings may be episodic (e.g., r elated to short

lived activities or conditions in a watershed or to an outbreak of a disease in a human or animal population) ; (3) their environmental fate and transport are different (e.g., differences in attachment to settleable particles or differences in optimal temperature or sunlight inactivation rate) ; or (4) other factors. In the following section, studies that report the relationship (or lack thereof) between pathogens and indicator organisms are reviewed and compared, as are the characteristics o f inland and coastal waters. See Appendix A for further information.

Cryptosporidium and Fecal Indicators

A l ack of correlation between Cryptosporidium concentration and fecal indicator organism density or turbidity has been observed in numerous studies

, including those of surface waters in central Arizona (Ryu and Abbaszadegan, 2008) , surface waters in central Massachusetts (Rees et al., 2005) , WWTP effluent in southern France (Lemarchand and Lebaron, 2003) , southern Florida estuarine waters (Lipp et al ., 2001a) , and canals and lakes used for recreation in the Netherlands (Schets et al., 2008) . In contrast to these findings, LeChevallier et al. (1991) found a significant correlation between fecal coliform density and Cryptosporidium concentration based on a review of a database of occurrence of Cryptosporidium and fecal coliforms in water samples collected from 66 source waters for drinking water located throughout the United States. LeChevallier and colleagues reported a general tendency of waters with high fecal indicator densities to also have higher concentrations of Cryptosporidium . However, they did not report that E. coli or other fecal indicators are predictive of Cryptosporidium concentration s in source

waters.

At specific sites, temporal va riations 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)

. The se reported variations in Cryptosporidium concentration and differences between Cryptosporidium and fecal indicator organism temporal variations arise from different loadin gs of Cryptosporidium and indicator organisms in source waters. Rees et al. (2005) found that small rainfall events washed oocysts retained in near

- stream sediment into streams, elevating stream

## U.S. Environmental Protection Agency

August 2010 47 concentration. The authors asserted that production of oocy sts by wildlife is seasonal and that seasonal variations in production may differ from variations in indicator organisms. Other

s tudies have confirmed seasonal variation in Cryptosporidium oocysts loading of surface waters for wildlife (e.g., Atwill et al ., 2004) and domestic animal s ources (Atwill et al., 2003), and have suggested variation in Cryptosporidium concentration related to human outbreaks of cryptosporidiosis (Lemarchand and Lebaron, 2003)

.

Schets et al. (2008) reported d ifferences in the natu re of Cryptosporidium and FIB sources. In that study, the authors found that at two similar sites (canals) ―the levels of fecal indicators in the canal with houseboats (Prinsengracht) and the canal without houseboats (Herengracht) were almost equal and di d 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, su ggesting that wastewater from the houseboats may have been a source of those parasites.‖ This finding is significant both in what it says about the ability of fecal indicators to predict risk related to a specific pathogen and because Cryptosporidium is p articularly 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 co liforms and fecal coliforms, E. coli

, and other microorganisms. Based on all data collected, the authors found that Giardia correlated significantly with the presence of fecal coliforms, whereas Cryptosporidium did not. In a study of flowing inland wate rs, Roser and Ashbolt (2004) observed increases in E. coli and enterococc i densities, but not Cryptosporidium concentration, during rain events in watersheds that were not suspected to be impacted by human fecal pollution. This finding reflects difference s 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 b y the presence or absence of traditional indicator organisms or source

- specific organisms. They observed that small rainfall events can wash oocysts in the near

- stream sediments into streams, elevating stream concentration (spatial variability). The auth ors assert ed that production of oocysts by wildlife may be seasonal and may occur with a different seasonality compared to i ndicators.

A potential difference in indicator organism and Cryptosporidium behavior in flowing v ersus

non

- flowing waters may be related to the settling of oocysts and FIB associated with particles. Brookes et al. (2005) determined that Cryptosporidium partitions predominantly to particles in the size range 14.3 to 27.7 m while E. coli and enterococci partition predominantly to la rger particles (> 63.3 m). With all other factors being equal, this indicates that removal of FIB from the water column by settling is greater than that of Cryptosporidium (by a factor of 3 in the Brookes and colleagues study). One potential implication of this finding is that the fecal indicator

- Cryptosporidium ratio could differ between flowing and non

- flowing waters (coastal and inland non

- flowing).

A l ack of correlation between Cryptosporidium and Giardia concentration and indicator concentration wa s also observed in an estuary (Lipp et al., 2001a)

. These researchers found that

## U.S. Environmental Protection Agency

August 2010 48 over a 12

- month period of water quality sampling at multiple sites, the concentrations of fecal indicators (fecal coliforms, enterococci, C. perfringens

, and coliphage) were not correlated with the occurrence of Cryptosporidium or Giardia . As with inland flowing and non

- flowing waters, this study supports the conclusion that Cryptosporidium and Giardia loads are episodic and sporadic in all settings (inland flowing, inland no n

- flowing

, and coastal) . In contrast, indicator organisms have both increased sources and sources that are more consistent . Thus, fecal indicators are more consistently present than pathogens

. V ariability in Cryptosporidium loading

was also demonstrated by Lemarchand and Lebaron (2003) in their analyses of WWTP influent and effluent and surface water samples. In that study, the authors did not find a significant correlation between Cryptosporidium and fecal coliforms or fecal streptococci (enterococci) in WWTP influent . However, they did report a significant correlation between Cryptosporidium and fecal coliform (but not fecal streptococci) in WWTP e ffluent and between Cryptosporidium concentration and both fecal coliform and fecal streptococc i concentr ation for surface waters. The y also reported higher Cryptosporidium concentration s in plant effluent than in plant influent on several occasions , which was attribute d to high temporal variability in Cryptosporidium concentration

, and concluded that Crypto sporidium loads depend on the level of Cryptosporidium infection in communities whereas indicator loads do not.

Other sporadic or episodic loadings of Cryptosporidium may arise from nearby livestock operations or wildlife contributions . For example, Ke eley and Faulkner (2008) found that in an inland flowing water

, the highest Cryptosporidium concentrations occurred during calving season. Calving season coincide d with the wettest time of year in the study area. Perhaps because the role of calves in Cry ptosporidium loading or different fate and survival characteristics was not evaluated

, they did not observe a correlation between concentration of fecal indicators and Cryptosporidium

.

Viruses and Fecal Indicators

The literature review included studies o f the co

- occurrence of various human enteric viruses (adenovirus, enterovirus, N orovirus, rotavirus

, and hepatitis A virus [HAV]) and fecal indicator organisms . It also included studies that reported decay rates of th e se viruses in some environmental wate rs . The results of these reviews are provided in the sections that follow.

Co

- occurrence and Correlation of Enteric Viruses and Fecal Indicators

General features of enteric viruses in aquatic environments are

higher occurrence at low temperature s vers us high temperature s (Fong and Lipp, 2005b; Griffin et al., 2003); frequent low concentration s or non

- detection s (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 association s between viral, bacterial

, and protozoan pathogens with suspended particles than that of fecal indicator organisms.

## U.S. Environmental Protection Agency

August 2010 49 As described below, these observations indicate significant differen ces between environmental behavior of enteric viruses and FIB , including seasonal variations, possible different trend s in inactivation with temperature, and differences in the net loadings from all sources for specific r eceiving waters.

Enterovirus

A st udy of enterovirus es , fecal coliform s, and fecal Streptococcus concentrations by Wyer et al. (1995) in marine coastal waters produced mixed results in attempts to correlate enterovirus with fecal indicator organisms . This led the authors to conclude that fecal indicator organisms had ―low predictive capability‖ for enterovirus in marine coastal waters. In that study, a large data base ( n = 40,449 for fecal coliforms, n = 33,459 for fecal streptococci, and n = 3015 for enterovirus samples) was used to atte mpt to establish a parametric relationship between the indicator organisms and enterovirus es

. T he indicator organism densitie s were assumed to fit log

normal distributions . Al though the distributions of the residuals associated with the fit ted data

were not assessed, a visual inspection of the fits indicates that the log

- normal distribut ion seems reasonable . Enterovirus data fit poorly with a log

- normal distribution because the data contained many zero observations. An adequate fit for enteroviruses was obtained when zero values were omitted and the data were log

- transformed. When the transformed enterovirus data were correlated with indicator organism data, positive, significant correlations were found . However, the correlations were weak, indicating that even for this relatively large data set, indicator bacteria are relatively poor predictors of enterovirus concentration.

When enteric virus concentration and indicator organism density data for individual sites (rather than aggregated data) are asse ssed, 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 t hat is opposite of FIB ( total coliform, fecal coliform, enterococci ), with enteroviruses more prevalent during the dry season and FIB more prevalent during the wet season. The observed temporal variations in viruses were attributed to temporal trends in v iral shedding or ―heightened anthropogenic activities‖ (e.g., primary contact recreation) during summer months.

A similar lack of correlation between FIB (in this case, fecal coliforms) and enterovirus was noted in a study of river waters by Skraber et al. (2004) . In that study, trends in enterovirus and fecal coliform concentrations were found to be the opposite . F ecal coliforms were more abundant at lower temperature s while enterovirus concentration s were characterized by frequent

non

- detect values a nd lower concentrations at low temperature (around 7° C) and more frequent detection at higher temperatures. These observations either indicate that the loadings of enterovirus are different than those of the indicator bacteria or that the fate of the ind icator bacteria ( e.g., die

- off or removal via predation) has a much different temperature dependence than does that of enterovirus. Fong et al. (2005a) likewise found a lack of correlation between
FIB (fecal coliforms and total coliforms) and enteric vir uses (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 speculate d that more frequent occurrence of enterovirus may

## U.S. Environmental Protection Agency

August 2010 50 be a result of improved persistence at low temperature or higher loading, though the authors saw no increase in viral loads associated with rainfall.

I n a n early study of both fresh and marine waters by Vaughn et al., (1979), a similar lack of co

occurrence was observed between fecal coliforms and enterovirus, with enterovirus occurring at sites with low fecal coliform concentration

, and not occurring at sites with high fecal colifor m concentration

. In a comparison of marine and freshwater sites, Rex et al. (2005) found no significant correlation between indicators ( E. coli , fecal coliforms, enterococc i , and coliphage s) and viral pathogens (adenovirus, astrovirus, rotavirus, enterovi rus) for freshwater or marine sites.

Hepatitis A Virus (HAV)

Conflicting results regarding the correlation of HAV with fecal indicator organisms were obtained in studies of an inland flowing water (Fernandez

- Molina et al.

, 2004) and coastal marine wate rs (Gersberg et al.

, 2006). Fernández

- Moilna et al. (2004) collected samples from springs and a stream located in a region whose land use is primarily agricultural. The springs were perceived (and confirmed) to be relatively free of fecal pollution

, whil e a small WWTP discharged into the stream. Among stream samples, no correlation was observed between the concentration of several fecal indicator organisms (total coliforms, fecal coliforms, enterococci, and sulfite

- reducing Clostridia ) and HAV. In addit ion, spatial trends in HAV concentration and concentration of the indicators were drastically different. A plot from Fernández

- Mol i na et al. ( 2004) showing the trend in HAV and indicator organisms with river station is presented in Figure 14 . The designa tions on the x

- axis refer to stream locations, with A being the furthest upstream sample location, B corresponding to a station immediately downstream of a WWTP, and E being the furthest downstream station. The trends in all of the FIB are the same and ar e different from HAV. The authors suggest ed the lack of correlation between indicator organisms and HAV is a result of different environmental fates of the microorganisms and spatial and temporal differences in the net loadings of the microorganisms.

In contrast to the above findings for an inland water, Gersberg et al. (2006) found a significant correlation between E. coli and enterococci and both HAV and enteroviruses in a marine coastal setting. In that study, samples were drawn from a wider, more div erse study area in which human fecal pollution was more prevalent than that of Fernández

- Mol i na et al. (2004). Gersberg and colleagues collected and analyzed both dry weather and wet weather samples, finding wide variation in concentrations of all microor ganisms in all samples

, and among samples collected during wet weather events

.

Adenovirus

In a study of coastal marine waters by Jiang et al. ( 2001), exceedance of indicator standards did not correlate with presence of adenovirus. In fact, high viral concentrations (2300 and 924

genomes / L; as determined by nested PCR ) were observed at two locations (river mouths) where indicator organism density did not exceed FIB criteria. Similar observations were made by Xagoraraki et al. ( 2007 ) in a study of fresh coastal waters in which adenovirus densities were observed to vary significantly

— spatially and temporally. Although co

- occurrence of adenovirus

## U.S. Environmental Protection Agency

August 2010 51 Figure 14 . Spatial Trends in HAV and Fecal Indicator Bacteria in a Small Stream Located in an Area whose Land Use is Primarily Agriculture

. He terotrop h ic plate count bacteria [HPC]; total coliform ( TC ) ; fecal coliform ( FC ) ; fecal streptococci ( FS ) ; sulfite

- reducing clostridi a ( SRC ) ; human adenovirus ( HAV ) (SOURCE: Reprinted, with
p ermission, from Fernandez

- Molina et al., 2004 © Kluwer Academic Publishers )

.


## with FIB was not assessed in that study, the heterogeneity of adenovirus presence/absence and the trends in adenovirus concentration appear to differ from those typical of FIB. Xagoraraki and colleagues observed generally low adenovirus concentrations or non

- detection, with minimal difference in adenovirus concentration between morning and afternoon samples. This lack of diurnal variation is a difference from trends of FIB and was attributed to the suspected source of the viruses (municipal WWTP effluent). Different seasonal trends in adenovirus concentration were observed at the two study sites, with adenovirus concentration highest in the early summer at one site and in late summer at the other site.

In a study of a n urban river, trends in adenovirus detection and concentration were opposite to those of FIB and coliphages (Choi and Jiang

, 2005 a ). Indicator organism concentrations tended to be higher during early winter mon ths (the onset of the rainy season) and could be described by a log

- normal distribution . Ad enovirus presence and concentrations were greatest in March, May

, and December and adenovirus were not log

- normal ly distributed

. In that study, adenovirus density was determined by QPCR. In one of the river s studied by Choi and Jiang (2005 a )

, 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 52

Summary of Co

- occurrence and Correlation of Enteric Viruses with Fecal Indicator Bacteria

Fecal indicator bacteria are relatively poor predictors of enteric virus occurr ence for both inland and coastal waters . In both settings, loadings and occurrence of enteric viruses have different sources and seasonal trends than the bacterial indicators . These seasonal trends may be related to relative differences in survival of FI B 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 fec ally polluted waters that are more likely to contain HAV. However, on a site

- by

- site basis

, relationships between indicator organism density and HAV concentration do not appear valid

— particularly in the case of streams

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

- occurrence of fecal indicator organisms with other enteric viruses, some bacterial pathogens, and some pathogenic protozoa.

Inactivation Rates of Enteric Virus es in Different Settings

Studies of infectious rotavirus decay in seawater and fresh water by Caballero et al., (2004) indicate rotavirus inactivation follows first

- order kinetics, with T 90 

## (the time to reduce the density by 90% [i.e., time for 1 log 10 

## re moval] ) of approximately 30 days in fresh water. In that study, the authors demonstrated that significantly higher UV doses were required to achieve 1 log reduction in rotavirus concentration in seawater than in freshwater. In a study of rotavirus survi val in freshwaters from two different sources, Pancorbo et al. (1987) observed shoulder behavior for one of the waters (lake water) but not the other (creek water). Decay rates (calculated assuming first

- order decay) for the lake and creek water were 0.13 9 d - 1 

## and 0.237 d - 1



## , respectively, for experiments performed at 20° C. The authors speculated that the difference in decay rate between the creek and lake waters may be the result of differences in water quality, especially pH and chloride concentration.

Dependence of inactivation rate on water type/quality was also observed by Hurst and Gerba (1980). In that study, simian rotavirus inactivation was observed in polluted and unpolluted fresh water and in estuary water at three salinities. Their surviva l curves, shown below in Figure 15 , did not exhibit shoulders in that study, though tailing behavior was observed for some experiments conducted in fresh waters. Survival during the first two days was similar in all waters studied (T 99 

## ~ 2 to 3 days for a ll waters). After 3 days, decay rate reduced drastically in freshwater but not in estuarine water, though within the salinity range studied salinity did not appear to influence inactivation. Ward et al. (1986) found only minor differences in inactivation rate of simian rotavirus in waters from four sources of drinking water ranging from very polluted (Ohio River) to presumably unpolluted (groundwater source). In a study of simian rotavirus survival in marine water and sediments by Rao et al. ( 1984), rot avirus was observed to survive significantly longer in sediments than in water alone at 25° C. Based on inactivation during the first 3 days of experiments, the decay constant for marine water alone was 1.16 d - 1 

## while the decay constant for sediments was 0.462 d - 1 

## . Rotavirus inactivation rate data are summarized in Figure 15.

## U.S. Environmental Protection Agency

August 2010 53 Figure 15 . Inactivation of Simian Rotavirus in Unpolluted Fresh Water (open squares), Polluted Fresh Water (filled squares), Low Salinity Estuary Water ( open circles), Medium Salinity Estuary Water (open triangles), and High Salinity Estuary Water (crosses) (SOURCE: Reprinted, with permission, from Hurst and Gerba

, 1980 © American Society for Microbiology )

.


## Survival curves for poliovirus 1 and coxsackievi rus B

- 1 for in situ (membrane diffusion chamber) studies done in flowing river water at 23 to 25° C exhibited neither shoulders nor tails,

as seen in Figure 16 from O’Brien and Newman (1977). Similarly rapid inactivation (T 90 

## < 24 hr) with no shoulder or tail was observed for poliovirus type 1 at 24° C in seawater from 3 l ocations 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 stab le, indicating that both temperature and predation by microorganisms play roles in removal of poliovirus at relatively high temperature. In a comparison of poliovirus 1 and rotavirus (SA11)

, survival in estuarine water, estuarine sediments, and two type s 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 particle s has been observed for FIB in all relevant settings (inland flowing waters, inland non

- flowing waters, coastal fresh waters, and coastal marine waters).

In summary, enteric viruses generally decay according to first

- order kinetics, exhibiting fewer

ten dencies toward shoulders or tails in survival curves than FIB . Inspection of the inactivation rates reported for the enteric viruses in various studies

, and summarized in Table 9

, reveals variability in decay rate estimated among studies, but does not ind icate differences in decay rate that may be attributed to the setting (inland v s. coastal).

## U.S. Environmental Protection Agency

August 2010 54 Figure 16

. Survival Curves for Coxsackievirus B

- 1 and Poliovirus 1 in Membrane Diffusion Chambers in Fresh Water (SOURCE: Reprinted, w ith permission, from O’Brien and Newman, 1977 © American Society for Microbiology )

.

Table 9 . Summary of Enteric Virus Inactivation Rate Data

Virus Setting Temperature (°C) Decay

R ate (d - 1 

### ) Reference

Rotavirus Lake/Inland 20 0.13 9 Pancorbo et al.

, 1987

Stream/Inland 20 0.237 Pancorbo et al., 1987 Marine/Coastal 25 1.16 Rao et al., 1984

Adenovirus 40 Tap water 23 0.0709 Enriquez et al., 1995

Marine/coastal 15 0.0592 Enriquez et al., 1995

Adenovirus 41 Tap water 23 0.0608 En riquez et al., 1995

Marine/coastal 15 0.0582 Enriquez et al., 1995 Coxsackievirus B

- 1 Stream/Inland 25 2.36 a 

### O’Brien and 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/inl and 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 55 Bacterial Pathogens and Indicators

One factor that favors the association of FIB with bacterial pathogens is that

, compared to enteric viruses or protozoa

, they are biologically similar. Factors that work against an association are

t emporal and spatial differences in their loadings to surface waters, differences in their abilities to assume a viable but nonculturable (VBNC) state, differences in sensitivity to salinity, and existence of nonhuman hosts of organisms pathogenic to humans

. All of these behaviors/features are exhibited by both pathogens and indicators, but to different extents and at different rates. Similarly with viruses and protozoa, processes that could give rise to differences in the ability of indicators to predict bacterial pathogen concentrations in different settings are different substrate and nutrient requirements, association with particles of different sizes (differential settling, especially in non

- flowing waters), predation, and different susceptibility to U V 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 Heli c obacter spp. or H. pylori

. Fecal indicator bacteria were frequently present when H. pylori was detected, but not vice versa

, and only weak correlations between Heli c obacter spp. and E. coli and fecal coliforms were observed. Correlation of Heli c obacter s pp. concentration with enterococc i concentration was poor. This lack of correlation is somewhat surprising given the prevalence of H. pylori infection in human populations worldwide, which would be expected to make H. pylori concentration in surface

water s less variable. The tendency for H. pylori concentration to vary significantly does not appear to be different for waters from inland and coastal settings . This is because , as demonstrated for viruses and protozoa, coastal waters are also subject to wid e variation in occurrence of pathogens and in pathogen loadings that are different from those of FIB

.
Variability (both spatial and temporal) in bacterial pathogen occurrence was also reported in a study of three bacterial pathogens by Walters et al. (2 007) in inland flowing waters in a watershed with widespread livestock operations. In that study, very little co

- occurrence was observed of E. coli O157, Salmonella

, and Campylobacter . Among 406 samples analyzed for these pathogenic bacteria, only 3 samp les 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 enterococc i ) concentration. In their study of the Seine estuary in France

, they found a strong correlation between Salmonella and all three of the se indicator s at a station located in an upstream por tion of the estuary . They also found a correlation between Salmonella and enterococc i at the mouth of the estuary. Notably, Salmonella was not correlated with any indicator organisms in an urban reach of the river. In contrast, Lemarchand and Lebaron (2 003) observed no correlation between Salmonella and any fecal indicator in an inland flowing water setting. Other researchers have previously reported a tendency for waters with very high

## U.S. Environmental Protection Agency

August 2010 56 concentration of fecal coliforms (> 2000 CFU/100 mL) to contain Sal monella (e.g., Goyal et al.

, 1977). In that study, sediments were found to be more abundant in Salmonella than in the water (though the ratio of Salmonella concentration to fecal coliform concentration was not constant), indicating that the sediments may have been a source of Salmonella during rainfall periods of increased turbulence at the sediment

- water interface.

Experimental survival studies of bacterial pathogens in waters from different settings indicate that bacterial pathogens have survival charac teristics more similar to those of FIB than do enteric viruses or protozoa. In a study on the survival of E. coli O157 in waters collected from non

flowing inland sources by Wang and Doyle ( 1998), water quality and temperature both influenced survival, th e 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, a nd an inland non

- flowing source (Vital et al.

, 2008). Alt hough growth was observed under the same conditions for an environmental E. coli isolate and an E. coli lab strain, growth curves for the three E. coli strains were different, with the E. coli O157 growth curve bearing greater similarity to that of the environmental isolate.

While Craig et al. (2003) could not establish direct correlations between decay rates in overlying water (marine water from a coastal site) of Salmonella spp. and indicators, they observed that decay of Salmonella most resembled that of E. coli

— the indicator with the highest decay rate among those studied. As with all FIB , the authors also noted greater survival of S. typhimurium and S. derby in sediments than in the overlying water and greater inactivation rate at 30° C than at 20° C. For S. typhimurium in marine waters in the absence of sediments, Craig et al. determined the decay rate to be

- 0.78 d - 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 Sa lmonella survival data do not necessarily fit first

- order rate curves. Figure 17 shows decay rates from several different studies (Maki and Hicks, 2002; McCambridge and McMeekin, 1981; Rhodes and Kator, 1988; Sinton et al., 2007; Wait and Sobsey, 2001) of waters from different settings. Note that a negative decay rate indicates growth. Despite their correspondence to waters from various settings, the decay rates are relatively consistent and have the same general trend with temperature. Collectively, t h ese data from laboratory survival studies do not indicate a difference in Salmonella decay that is related to setting inland v ersus coastal water.

1.1. Summary

C onsistent co

- occurrence or correlation between the waterborne pathogens evaluated in this report a nd FIB were not found

— regardless of the setting (coastal, inland flowing

, or inland non

flowing). In many cases, p athogen occurrence seems to be driven by events such as rainfall, epidemics

, or large releases from wildlife or livestock, and these events s eem to have differen t

## U.S. Environmental Protection Agency

August 2010 57 fate and transport c haracteristics than indicator organisms. Because coastal and inland sites are both subject to pathogen loads from these and other types of events, the lack of correlation noted bet ween pathogens and (predominantly bacterial) indicators does not distinguish these site types from each other.

The following f

actors have the potential for causing different indicator

- pathogen behavior in different aquatic settings :

different removal rat es of indicators and pathogens via settling in flowing and non

flowing settings; different removal rates of indicators and pathogens via UV inactivation (assuming the incident UV radiation is different in coastal and inland settings due to shading or other features); and different sources or loading rates associated with different settings.

Based on the information obtained for this report, it is not possible at present to assess the significance of these potential differences. Figure 17

. Decay Rates for Salmonella for Various S ettings and Temperatures

.

## U.S. Environmental Protection Agency

August 2010 58 References

Abdelzaher, A., Wright, M., Ortega, C., Solo

- Gabriele, H., Miller, G., Elmir, S., Newman, X., Shih, P., Bonilla, T.D., Palmer, C.J., Scott, T., Lukasik, J., Harwood, V.J., McQuaig, S., Sinigalliano, C., Gidley, M., Plano, L., Zhu, X., Wang, J.D., Fleming, L., 2010. P resence of pathogens and indicator microbes at a non

- pointsource subtropical recreational marine beach. Applied and Environmental Microbiology 76(3): 724

- 732. Ahn, J.H., Grant, S.B., Surbeck, C.Q., Digiacomo, P.M., Nezlin, N.P., Jiang, S. 2005. Coastal

wat er quality impact of stormwater runoff from an urban watershed in southern California. Environmental Science and Technology 39(16): 5940

- 5953. Alkan, U., Elliott, D.J., Evison, L.M. 1995. Survival of enteric bacteria in relation to simulated solar radiatio n and other environmental factors in marine waters. Water Research 29(9): 2071

- 2081. An, Y.

- J., Kampbell, D.H., Breidenbach, G.P. 2002. Escherichia coli and total coliforms in water and sediments at lake marinas. Environmental Pollution 120: 771

- 778. Ander son, K., Nelson, K., Marchin, G., Rice, C.W. 1999. Seasonal dynamics of fecal bacteria in selected Kansas streams as affected by land use. 99 th 

## General Meeting of the American Society for Microbiology , Chicago, IL. Anderson, K., Whitlock, J.E., Harwood, V. J. 2005. Persistence and differential survival of fecal indicator bacteria in subtropical waters and sediments. Applied and Environmental Microbiology 71(6): 3041

- 3048. Ashbolt, N.J., Dorsch, M.R., Cox, P.T., Banens, B. 1997. Blooming E. coli , what do they mean? In Coliforms and E. coli : Problem or Solution? The Royal Society of Chemistry, Cambridge, UK. Atwill, E.R., Hoar, B., Pereira, M.G.C., Tate, K.W., Rulofson, F., Nader, G. 2003. Improved quantitative estimates of low environmental loading and sporadi c periparturient shedding of Cryptosporidium parvum in adult beef cattle. Applied and Environmental Microbiology 69(8): 4604

- 4610. Atwill, E.R., Phillips, R., das Graças, M., Pereira, C., Li, X., McCowan, B. 2004. Seasonal shedding of multiple Cryptosporid ium genotypes in California ground squirrels ( Spermophilus beechyi ). Applied and Environmental Microbiology 70(11): 6748

- 6752. Baums, I.B., Goodwin, K.D., Kiesling, T., Wanless, D., Diaz, M.R., Fell, J.W. 2007. Luminex detection of fecal indicators in rive r samples, marine recreational water, and beach sands. Marine Pollution Bulletin 54: 521

- 536. Baxter

- Potter, W.R., Gilliland, M.W. 1988. Bacterial pollution run

- off from agricultural lands. Journal of Environmental Quality 17(1): 27

- 34. Beaudeau, P., Touss et, N., Bruchon, F., Lefèvre, A., Taylor, H.D. 2001. In situ measurement and statistical modeling of Escherichia coli decay in small rivers. Water Research 35(13): 3168

- 3178. Bell, A.K., Layton, A.C., Williams, D.E., McKay, L.D. 2007. Physical factors infl uencing fecal persistence and concentration in stream water. 107 th 

## Annual Meeting of the ASM

. Toronto, Ontario. Benham, B.L., Baffaut, C., Zeckoski, R.W., Mankin, K.R., Pachepsky, Y.A., Sadeghi, A.M., Brannan, K.M., Soupir, M.L., Habersack, M.J. 2006. Mode ling bacteria fate and transport in water to support TMDLs. Transactions of the American Society of Agricultural and Biological Engineers 49(4): 987

- 1002.

## U.S. Environmental Protection Agency

August 2010 59 Benham, B.L., Brannan, K.M ., Yagow, G., Zeckosk, I .W., Dillaha, T.A., Mostaghimi, S., Wynn, J.W. 2005 . Development of bacteria and benthic total maximum daily loads: a case study, Linville Creek, Virginia. Journal of Environmental Quality 34: 1860

- 1872. Bernhard, A.E., Field, K.G. 2000. A PCR assay to discriminate human and ruminant feces on the basis of host differences in Bacteroides

- Prevotella genes encoding 16S rRNA. Applied and Environmental Microbiology 66(10): 4571

- 4574. Boehm, A.B., Weisberg, S.B. 2005. Tidal forcing of enterococci at marine recreational beaches at fortnightly and semidiurnal frequ encies. Environmental Science and Technology 39: 5575

- 5583. Boehm, A.B., Ashbolt, N., Colford, J., Dunbar, L., Fleming, L., Gold, M., et al. 2009. A sea change ahead for recreational water quality criteria. Journal of Water and Health 7 : 9

- 20. Bonilla, A.J ., Rijal, G.K., Fujioka, R.S. 1999. Use of Clostridium perfringens to detect site of sewage pollution in freshwater streams. 99 th 

## General Meeting of the ASM , Chicago, IL. Bordalo, A.A. 2003. Microbiological water quality in urban coastal beaches: the influ ence of water dynamics and optimization of the sampling strategy. Water Research 37: 3233

- 3241. Bordalo, A.A., Onrassami, R., Dechsakulwatana, C. 2002. Survival of faecal indicator bacteria in tropical estuarine waters (Bangpakong River, Thailand). Journal of Applied Microbiology 93: 864

- 871. Bowen, J.D., Oliver, J.D. 2008. Linkage of Bacterial Pathogens to Human Infectious Disease in an Estuary Subjected to Extreme Climatic Events. National Science Foundation. Bragg, J.D., Clark, M.E., 1992, Bacteriologic al w ater q uality o f Beaver Reservoir, Arkansas. Proceedings of the Arkansas Academy of Science (46): 20

- 21

. Brookes, J.D., Hipsey, M.R., Burch, M.D., Regel, R.H., Linden, L.G., Ferguson, C.M., Antenucci, J.P. 2005. Relative value of surrogate indicators for detecting pathogens in lakes and reservoirs. Environmental Science and Technology 39(22): 8614

- 8621. Brownell, M.J., Harwood, V.J., Kurz, R.C., McQuaig, S.M., Lukasik, J., Scott, T.M. 2007. Confirmation of putative stormwater impact on water quality a t a Florida beach by microbial source tracking methods and structure of indicator organism populations. Water Research 41: 3747

- 3757. Buckley, R., Clough, E., Warnken, W., Wild, C. 1998. Coliform bacteria in streambed sediments in a subtropical rainforest conservation reserve. Water Research 32(6): 1852

- 1856. Buckwalter, T., Zimmerman, T.M., Fulton, J.W. 2006. Fecal

- Indicator B acteria in the Allegheny, Monongahela, and Ohio Rivers and Selected Tributaries, Allegheny County, Pennsylvania, 2001

- 2005. U.S. Geo logical Survey. Scientific Investigations Report 2006

- 5216. Burkholder, J., Libra, B., Weyer, P., Heathcote, S., Kolpin, D., Thorne, P.S. 2007. Impacts of waste from concentrated animal feeding operations on water quality. Environmental Health Perspective s 115(2): 308

- 312. Byappanahalli, M., Fowler, M., Shively, D., Whitman, R. 2003. Ubiquity and persistence of Escherichia coli in a midwestern coastal stream. Applied and Environmental Microbiology 69(8): 4549

- 4555. Byappanahalli, M.N., Whitman, R.L., Shive ley, D., Ferguson, J., Ishii, S., Sadowsky, M.J. 2007. Population structure of Cladophora

- borne Escherichia coli in nearshore water of Lake Michigan. Water Research 41(8): 3649

- 3654.

## U.S. Environmental Protection Agency

August 2010 60 Caballero, S., Abad, F.X., Loisy, F., Le Guyader, F.S., Cohen, J., Pintó, R.M., Bosch, A. 2004. Rotavirus virus

- like particles as surrogates in environmental persistence and inactivation studies. Applied and Environmental Microbiology 70(7): 3904

- 3909. Cabelli, V.J. 1983. Health Effects Criteria for Marine Recreational Water. U S EPA Health Effects Research Laboratory, EPA

- 600/1

- 80

- 031 Research Triangle Park, NC. Calderon, R.L., Mood, E.W., Dufour, A.P. 1991. Health effects of swimmers and nonpoint sources of contaminated water. International Journal of Environmental Health Resea rch 1: 21

- 31. Campbell, H.M.K., Hendricks, C.W., Harding, A.K. 1999. Spatial and temporal variation of microbial indicators of water quality in Oregon streams. 99 th 

## General Meeting of the ASM . Chicago, IL. Carillo, M., Estrada, E., Hazen, T.C. 1985. Surviv al and enumeration of the fecal indicators Bifidobacterium adolescentis and Escherichia coli in a tropical rain forest. Applied and Environmental Microbiology 50(2): 468

- 476. Chambers, M.K., Ford, M.R., White, D.M., Barnes, D.L., Schiewer, S. 2008. Distrib ution and transport of fecal bacteria at spring thaw in a rural Alaskan community. Journal of Cold Regions Engineering 22: 16

- 37. Chambers, M.K., Ford, M.R., White, D.M., Scheiwer, S., Barnes, D.L. 2005. Distribution and transport of fecal bacteria in a ru ral Alaskan community. World Water and Environmental Resources Congress . ASCE. Anchorage, AK. Chandramouli, V., Brion, G., Neelakantan, T.R., Lingireddy, S. 2007. Backfilling missing microbial concentrations in a riverine database using artificial neural n etworks. Water Research 41: 217

- 227. Chigbu, P., Gordon, S., Strange, T.R. 2005. Fecal coliform disappearance rates in a north

- central Gulf of Mexico estuary. Estuarine, Coastal and Shelf Science 65(1

- 2): 309

- 318. Choi, S.B., Jiang, S. 2005a. Inactivation of human adenoviruses and fecal indicator bacteria in marine water. 105 th 

## Annual General Meeting of the ASM , Atlanta, GA. Choi, S., Jiang, S.C. 2005b. Real

- time PCR quantification of human adenoviruses in urban rivers indicates genome prevalence but low in fectivity. Applied and Environmental Microbiology 71(11): 7426

- 7433. Chu, W., Jiang, K., McLaughlin, K., Grant, S. 2007. Growth or death: fate of fecal indicator bacteria in th aquatic environment. 107 th 

## General Meeting of the ASM . Toronto, Ontario. Cinott o, P.J. 2005. Occurrence of Fecal

- Indicator Bacteria and Protocols for Identification of Fecal

- Contamination Sources in Selected Reaches of the West Branch Brandywine Creek, Chester County, Pennsylvania. U.S. Department of the Interior, U.S. Geological Sur vey. Reston, VA. Clark, C.D., De Bruyn, W.J., Jakubowski, S.D., Grant, S.B. 2008. Hydrogen peroxide production in marine bathing waters: implications for fecal indicator bacteria mortality. Marine Pollution Bulletin 56: 397

- 401. Coffey, R., Cummins, E., C ormican, M., Flaherty, V.O., Kelly, S. 2007. Microbial exposure assessment of waterborne pathogens. Human and Ecological Risk Assessment 13(6): 1313

- 1351. Cole, D., Hill, V., Line, D., Harman, W., Jennings, G., Sobsey, M. 2000. Environmental factors influe ncing different microbial indicators of fecal contamination in surface waters. 100 th 

## General Meeting of the ASM , Los Angeles, CA.

## U.S. Environmental Protection Agency

August 2010 61 Colford, J.M.J., Wade, T.J., Schiff, K.C., Wright, C.C., Griffith, J.F., Sandhu, S.K., Burns, S., Sobsey, M., Lovelace, G., We isberg, S.B. 2007. Water quality indicators and the risk of illness at beaches with nonpoint sources of fecal contamination. Epidemiology 18(1): 27

- 35. Coulliette, A.D., Noble, R.T. 2008. Impacts of rainfall on the water quality of the Newport River Estuar y (Eastern North Carolina, USA). Journal of Water and Health 6(4): 473

- 482. Craig, D.L., Fallowfield, H.J., Cromar, N.J. 2003. Effectiveness of guideline faecal indicator organism values in estimation of exposure risk at recreational coastal sites. Water S cience and Technology 47(3): 191

- 198. Craig, D.L., Fallowfield, H.J., Cromar, N.J. 2004. Use of microcosms to determine persistence of Escherichia coli in recreational coastal water and sediment and validation with in situ measurements. Journal of Applied Bacteriology 96: 922

- 930. Crowther, J., Kay, D., Wyer, M.D. 2001. Relationships between microbial water quality and environmental conditions in coastal recreational waters: The Fylde Coast, UK. Water Research 35(17): 4029

- 4038. Crowther, J., Kay, D., Wyer, M.D. 2002. Faecal

- indicator concentrations in waters draining lowland pastoral catchments in the UK: relationships with land use and farming practices. Water Research 36: 1725

- 1734. Crysup, K.A., Mott, J.B. 2001. Fecal coliforms, enterococci and E. coli a s indicators of water quality in the Oso Creek/Oso Bay watershed, Corpus Christi, Texas. 101 st 

## General Meeting of the ASM . Orlando, FL. Davies, C.M., Long, J.A.H., Donald, M., Ashbolt, N.J. 1995. Survival of fecal microorganisms in marine and freshwater se diments. Applied and Environmental Microbiology 61(5): 1888

- 1896. Davies

- Colley, R. Nagels, J., Nally, R.A. 2008, Stormflow

- dominated loads of faecal pollution from an intensively dairy

- farmed catchment. Water Science and Technology 57(10): 1519

- 1523. Davi s, E.M., M.T., G., T.D., S. 1995. Significance of indicator bacteria changes in an urban stream. Water Science and Technology 31(5

- 6): 243

- 246. Davis, K., Anderson, M.A., Yates, M.V. 2005. Distribution of indicator bacteria in Canyon Lake, California. Wate r Research 39: 1277

- 1288. Deller, S., Mascher, F., Platzer, S., Reinthaler, F.F., Marth, E. 2006. Effect of solar radiation on survival of indicator bacteria in bathing waters. Central European Journal of Public Health 14(3): 133

- 137. Denis

- Mize, K., Fout, G.S., Dahling, D.R., Francy, D.S. 2004. Detection of human enteric viruses in stream water with RT

- PCR and cell culture. Journal of Water and Health 2(1): 37

- 47. Desmarais, T.R., Solo

- Gabriele, H., Palmer, C. 2000. Identifying sources of E. coli in a tida l influenced sub

- tropical river. 100 th 

## General Meeting of the ASM , Los Angeles, CA. Desmarais, T.R., Solo

- Gabriele, H.M., Palmer, C.J. 2002 Influence of soil on fecal indicator organisms in a tidally influenced subtropical environment. Applied and Environm ental Microbiology 68(3): 1165

- 1172. Donisson, A., Ross, C., Thorrold, B. 2004. Impact of land use on the faecal microbial quality of hill

- country streams. New Zealand Journal of Marine and Freshwater Research 38: 845

- 855.

## U.S. Environmental Protection Agency

August 2010 62 Dorevitch, S., Ashbolt, N.J., Fer guson, C.M., Fujioka, R., McGee, C.D., Soller, J.A., Whitman, R.L. 2010. Meeting report: knowledge gaps in developing microbial criteria for inland recreational waters. Environmental Health Perspectives 118: 871

- 876. Dorner, S.M., Anderson, W.B., Gaulin, T ., Candon, H.L., Slawson, R.M., Payment, P., Huck, P.M. 2007. Pathogen and indicator variability in a heavily impacted watershed. Journal of Water and Health 5(2): 241

- 57. Dufour, A.P. 1984. Health Effects Criteria for Fresh Recreational Water. U.S. EPA Of fice of Research and Development. EPA

- 600/1

- 84

- 004. Research Triangle Park, NC. Edwards, D.R., Coyne, M.S., Daniel, T.C., Vendrell, P.F., Murdoch, J.F., Moore, P.A.J. 1997. Indicator bacteria concentrations of two northwest Arkansas streams in relation to flow and season. Transactions of the American Society of Agricultural Engineers 40(1): 103

- 109. Ellis, J.B., Yu, W. 1995. Bacteriology of urban runoff: the combined sewer as a bacterial reactor and generator. Water Science and Technology 31(7): 303

- 310. El mir, S.M., Wright, M.E., Abdelzaher, A., Solo

- Gabriele, H.M., Fleming, L.E., Miller, G., Bybolowik, M., Shih, M.

- T.P., Pillai, S.P., Cooper, J.A., Quaye, E.A. 2007. Quantitative evaluation of bacteria released by bathers in a marine water. Water Research 4 1: 3

- 10. Enriquez, C.E., Hurst, C.J., Gerba, C.P. 1995. Survival of the enteric adenoviruses 40 and 41 in tap, sea, and waste water. Water Research 29(11): 2548

- 2553. EP/CEU (European Parliament/Council of the European Union). 2006. 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. Official Journal of the European Union L64/37

- L64/51. Epibathe. 2009a. Accessible Report to Commission Sta ff Responsible for Reporting to the Parliament and to the Council Under Article 14 of the Bathing Water Directive of 15th February 2006. EU Framework 6. Specific Targetted Research Project Fp6 Reference 022618. Epibathe. 2009b. Appendix 2 Section 1. Risk of Gastroenteritis from Recreational Bathing Water: Analysis of Epibathe data from Hungary and Spain. Evanson, M., Ambrose, R.F. 2006. Sources and growth dynamics of fecal indicator bacteria in a coastal wetland system and potential impacts to adjacent wat ers. Water Research 40: 475

- 486. Fattal, B., Peleg

- Olevsky E.

, Agursky

, T.

, Shuval

, H. 1987

. Association between seawater pollution as measured by bacterial indicators and morbidity among bathers at Mediterranean bathing beaches of Israel. Chemosphere 16: 565

- 570. Fattal, B., Vasi, R.J., Katzenelson, E., Shuval, H.I. 1983. Survival of bacterial indicator organisms and enteric viruses in the Mediterranean coastal waters off Tel

- Aviv. Water Research 17(4): 397

- 402. Ferguson, C.M., Coote, B.G., Ashbolt, N.J., Stevenson, I.M. 1996. Relationships between indicators, pathogens and water quality in an estuarine system. Water Research 30(9): 2045

- 2054. Ferguson, C., de Roda Husman, A.M., Altavilla, N., Deere, D., Ashbolt, N.J. 2003. Fate and Transport of surface wa ter pathogens in watersheds. Critical Reviews in Environmental Science and Technology 33(3): 299

- 361. Ferguson, C.M., Charles, K., Deere, D.A. 2009. Quantification of microbial sources in drinking

water catchments. Critical Reviews in Environmental Science and Technology 39: 1

- 40.

## U.S. Environmental Protection Agency

August 2010 63 Ferley, J.P., Zmirou, D., Balducci, F., Baleux, B., Fera, P., Larbaigt, G.

, et al. 1989. Epidemiological significance of microbiological pollution criteria for river recreational waters. International Journal of Epidemiology 18: 1 98

- 205. Fernandez

- Molina, M.C., Alvarez, A., Espigares, M. 2004. Presence of hepatitis a virus in water and its relations with indicators of fecal contamination. Water, Air, and Soil Pollution 159(1): 197

- 208

. Fewtrell, L., Godfree, A.F., Jones, F., Kay, D., Salmon, R.L., Wyer, M.D. 1992 Health effects of white

- water canoeing. Lancet 339:1587

- 1589. Fleisher, J.M., Kay, D., Salmon, R.L., Jones, F., Wyer, M.D., Godfree, A.F. 1996. Marine waters contaminated with domestic sewage: nonenteric illnesses associa ted with bather exposure in the United Kingdom. American Journal of Public Health 86(9): 1228

- 1234. Fleisher, J.M., Fleming, L.E., Solo

- Gabriele, H.M., Kish, J.K., Sinigalliano, C.D., Plano, L., Elmir, S.M., Wang, J.D., Withum, K., Shibata, T., Gidley, M.L ., Abdelzaher, A., He, G., Ortega, C., Zhu, X., Wright, M., Hollenbeck, J., Backer, L.C. 2010. The BEACHES Study: health effects and exposures from non

- point source microbial contaminants in subtropical recreational marine waters. International Journal of Epidemiology : 1

- 8

. Fong, T.

- T., Griffin, D.W., Lipp, E.K. 2005a. Molecular assays for targeting human and bovine enteric viruses in coastal waters and their application for library

- independent source tracking. Applied and Environmental Microbiology 71(4): 2070

- 2078. Fong, T.

- T., Lipp, E.K. 2005b. Enteric viruses of humans and animals in aquatic environments: health risks, detection, and potential water quality assessment tools. Microbiology and Molecular Biology Reviews 69(2): 357

- 371. Francy, D.S., Helsel, D.R., Nally, R.A. 2000. Occurrence and distribution of microbiological indicators in groundwater and stream water. Water Environment Research 72(2): 152

- 161. Fujioka, R.S., Loh, P.C., Lau, S. 1980. Survival of human enteroviruses in the Hawaiian ocean

env ironment: evidence for virus

- inactivating microorganisms. Applied and Environmental Microbiology 39(6): 1105

- 1110. Fujioka, R.S., Sian

- Denton, C., Borja, M., Castro, J. Morphew, K. 1999 Soil: the environmental source of Escherichia Coli and Enterococci in Guam’s streams. Journal of Applied Microbiology Symposium Supplement 85: 83S

- 89S. Garcia

- Armisen, T., Servais, P. 2007. Respective contributions of point and non

- point sources of E. coli and enterococci in a large urbanized waters (the Seine River, France) . Journal of Environmental Management 82: 512

- 518. Gentry, R.W., Layton, A.C., McKay, L.D., McCarthy, J.F., Williams, D.E., Koirala, S.R., Sayler, G.S. 2007. Efficacy of Bacteroides measurements for reducing statistical uncertainty associated with hydrolog ic flow and fecal loads in a mixed used watershed. Journal of Environmental Quality 36: 1324

- 1330. Gerba, C., Mcleod, J. 1976. Effects of sediments on the survival of Escherichia coli in marine waters. Applied and Environmental Microbiology 32: 114

- 120. Ge rsberg, R.M., Rose, M.A., Robles

- Sikisaka, R., Dhar, A.K. 2006. Quantitative detection of hepatitis A virus and enteroviruses near the United States

- Mexico border and correlation with levels of fecal indicator bacteria. Applied and Environmental Microbiolo gy 72(12): 7438

- 7444.

## U.S. Environmental Protection Agency

August 2010 64 Giddings, E.M., Oblinger, C.J. 2004. Fecal Indicator Bacteria in the Newfound Creek Watershed, Western North Carolina, During a High and Low Streamflow Condition, 2003. U.S. Geological Survey Scientific Investigations Report 2004

- 5257 Reston, VA. Goyal, S.M., Gerba, C.P., Melnick, J.L. 1977. Occurrence and distribution of bacterial indicators and pathogens in canal communities along the Texas coast. Applied and Environmental Microbiology 34(2): 139

- 149. Griffin, D.W., Lipp, E.K., McLau ghlin, M.R., Rose, J.B. 2001. Marine recreation and public health microbiology: quest for the ideal indicator. BioScience 51(10): 817

- 825. Griffin, D.W., Donaldson, K.A., Paul, J.H., Rose, J.B. 2003. Pathogenic human viruses in coastal waters. Clinical Mic robiology Reviews 16(1): 129

- 143. Griffin, D.W., Gibson, C.J.I., Lipp, E.K., Riley, K., Paul, J.H.I., Rose, J.B. 1999. Detection of viral pathogens by reverse transriptase PCR and of microbial indicators by standard mathods in the canals of the Florida Key s. Applied and Environmental Microbiology 65(9): 4118

- 4125. Groenwold, A.D., Borsuk, M.E., Wolpert, R.L., Reckhow, K.H. 2008. An assessment of fecal indicator bacteria

- based water quality standards. Environmental Science and Technology 42(13): 4676

- 4682.
H aack, S.K., Fogarty, L.R., Wright, C.C. 2003. Escherichia coli and enterococci at beaches in the Grand Traverse Bay, Lake Michigan: sources, characteristics, and environmental pathways. Environmental Science and Technology 37(15): 3275

- 3283. Haile, R.W., W itte, J.S., Gold, M., Cressey, R., McGee, C., Millikan, R.C., Glasser, A., Harawa, N., Ervin, C., Harmon, P., Harper, J., Dermand, J., Alamillo, J., Barrett, K., Nides, M., Wang, G. 1999. The health effects of swimming in ocean water contaminated by storm drain runoff. Epidemiology 10(4): 355

- 363. Hall, K.K., Gallangher, L.K., Evanshen, B.G., Maier, K.J., Scheuerman, P.R. 2007. Comparison of microbial water quality parameters in four geographically similar creeks in northeast Tennessee using multivariate st atistical analyses. 107 th 

## General Meeting of the ASM

, Toronto, Ontario. Haramoto, E., Katayama, H., Oguma, K., Koibuchi, Y., Furumai, H., Ohgaki, S. 2006. Effects of rainfall on the occurrence of human adnoviruses, total coliforms, and Escherichia coli in seawater. Water Science and Technology 54(3): 225

- 230. Hardina, C.M., Fujioka, R.S. 1991. Soil: the environmental source of Escherichia coli and Enterococci in Hawaii’s streams. Environmental Toxicology and Water Quality 6: 185

- 195. Hartel, P.G., Rodgers, K., Fisher, J.A., McDonald, J.L., Gentit, L.C., Otero, E., Rivera

- Torres, Y., Bryant, T.L., Jones, S.H. 2005. Survival and regrowth of fecal enterococci in desiccated and rewetted sediments. In: K.J. Hatcher (ed.) Proceedings of the 2005 Georgia Water Reso urces Conference , Athens, GA. Hartel, P.G., McDonald, J.L., Gentit, L.C., Hemmings, S.N.J., Rodgers, K., Smith, K.A., Belcher, C.N., Kuntz, R.L., Rivera

- Torres, Y., Otero, E., Schroder, E.C. 2007. Improving fluorometry as a source tracking method to detect human fecal contamination. Estuaries and Coasts 30(3): 551

- 561. Harwood, V.J. 2004. Understanding the sources and fate of conventional and alternative indicator organisms in subtropical waters. University of South Florida. EPA Agreement Number: STAR Grant R8228829.

## U.S. Environmental Protection Agency

August 2010 65 Haugland, R.A., Siefring, S.C., Wymer, L.J., Brenner, K.P., Dufour, A.P. 2005. Comparison of
Enterococcus measurements in freshwater at two recreational beaches by quantitative polymerase chain reaction and membrane filter culture analysis. Wat er Research 39: 559

- 568. He, L.

- M., He, Z.

- L. 2008. Water quality prediction of marine recreational beaches receiving watershed baseflow and stormwater runoff in Southern California, USA. Water Research 42: 2563

- 2573. He, L.

- M., Lu, J., Shi, W. 2007. Varia bility of fecal indicator bacteria in flowing and ponded water in southern California: implications for bacterial TMDL development and implementation. Water Research 41: 3132

- 3140. Heaney, C.D., Sams, E., Wing, S., Marshall, S., Brenner, K., Dufour, A.P., Wade, T.J. 2009. Contact with beach sand among beachgoers and risk of illness. American Journal of Epidemiology 170(2): 164

- 172. Heilman, S.L., Mott, J.B. 2000. Fecal coliforms, enterococci, Escherichia coli and total coliform as indicators of water qualit y in Oso Bay, Corpus Christi, Texas. 100 th 

## General Meeting of the ASM , Los Angeles, CA. Hendry, G.S., Toth, A. 1982. Some effects of land use on bacteriological water quality in a recreational lake. Water Research 16: 105

- 112. Hijnen, W.A.M., Lutenberg, A. T., Ruiter, H., Vink, R.R.J., Medema, G. 2007. Decay rate index for E. coli and enterococci in fresh and salt bathing waters. Water Quality Technology Conference ( WQTC) . Charlotte, NC. Hood, K.I., Whitlock, J.E., Harwood, V.J. 2003. Factors that influence the persistence of bacterial indicator organisms in fresh and saline subtropical waters. 103 rd 

## General Meeting of the ASM , Washington DC. Hose, G.C., Gordon, G., McCullough, F.E., Pulver, N., Murray, B.R. 2005. Spatial and rainfall related patterns of bact erial contamination in Sydney Harbour estuary. Journal of Water and Health 3(4): 349

- 3 58. Hoyer, M.V., Donze, J.L., Schulz, E.J., Willis, D.J., Canfield, D.E.J. 2006. Total coliform and Escherichia coli counts in 99 Florida lakes, with relations to some co mmon limnological factors. Lake and Reservoir Management 22(2): 141

- 150. Hurst, C.J., Gerba, C.P. 1980. Stability of simian rotavirus in fresh and estuarine water. Applied and Environmental Microbiology 39(1): 1

- 5. Available online at http://aem.asm.org/cgi/reprint/39/1/1.pdf

. Hyer, K.E. 2007 Escherichia coli Concentrations in Recreational Streams and Backcountry Drinking

- Water Supplies in Shenandoah National Park, Virginia, 2005

- 2006. U.S. Departme nt of the Interior, U.S. Geological Survey. Scientific Investigations Report 2007

- 5160 Reston, VA. Ishii, S., Ksoll, W.B., Hicks, R.E., Sadowsky, J. 2006 a . Presence and growth of naturalized Escherichia coli in temperate soils from Lake Superior watersheds . Applied and Environmental Microbiology 72: 612

- 621. Ishii, S., Dawn, T.Y., Shively, D.A., Byappanahalli, M.N., Whitman, R.L., Sadowsky, M.J. 2006 b

. Cladophora (Chlorophyta) spp. harbor human bacterial pathogens in nearshore water of Lake Michigan. Applie d and Environmental Microbiology 72(7): 4545

- 4553. Isobe, K.O., Tarao, M., Chiem, N.H., Minh, L.Y., Takada, H. 2004. Effect of environmental factors on the relationship between concentrations of coprostanol and fecal indicator

## U.S. Environmental Protection Agency

August 2010 66 bacteria in tropical (Mekong Delta) and temperate (Tokyo) freshwaters. Applied and Environmental Microbiology 70: 814

- 821. Iwamoto, M., Hlady, G., Jeter, M., Burnett, C., Drenzek, C., Lance, S., Benson, J., Page, D.P.B. 2005. Shigellosis among swimmers in a freshwater lake. The Southe rn Medical Association: 774

- 778. Jamieson, R.C., Gordon, R., Joy, D., Lee, H. 2004a. Assessing microbial pollution of rural surface waters. A review of current watershed scale modeling approaches. Agricultural Water Management 70: 1

- 17. Jamieson, R.C., Joy , D.M., Lee, H., Kostaschuk, R., Gordon, R.J. 2004b. Persistence of enteric bacteria in alluvial streams. Journal of Environmental Engineering and Science 3: 203

- 212. Jamieson, R.C., Joy, D.M., Lee, H., Kostaschuk, R., Gordon, R.J. 2005. Resuspension of

se diment

- associated Escherichia coli in a natural stream. Journal of Environmental Quality 34: 581

- 589. Jeong, Y., Grant, S.B., Ritter, S., Pednekar, A., Candelaria, L,. Winant, C.L. 2005. Identifying pollutant sources in tidally mixed systems: case study of fecal indicator bacteria from marinas in Newport Bay, Southern California. Environmental Science and Technology. 39: 9083

- 9093. Jiang, S., Noble, R.T., Chu, W. 2001. Human adenovirus and coliphages in urban runoff

impacted coastal waters of southern Calif ornia. Applied and Environmental Microbiology 67(1): 179

- 184. Jiang, S.C., Chu, W., He, J.

- W. 2007. Seasonal detection of human viruses and coliphage in Newport Bay, California. Applied and Environmental Microbiology 73(20): 6468

- 6474. Jones, S.H., Bryant, T. 2002. Ribotyping to identify source species of Escherichia coli in two Vermont watersheds. 102 nd 

## General Meeting of the ASM , Salt Lake City, UT. Kay, D., Edwards, A.C., Ferrier, R.C., Francis, C., C., K., Rushby, L., Watkins, J., McDonald, A.T., Wyer, M., Crowther, J., Wilkinson, J. 2007. Catchment microbial dynamics: the emergence of a research agenda. Progress in Physical Geography 31(1): 59

- 76. Kay, D., Fleisher, J.M., Salmon, R.L., Wyer, M.D., Godfree, A.F., Zelenauch

- Jacquotte, Z., Shore, R. 1994. Predicting likelihood of gastroenteritis from sea bathing; results from randomized exposure. Lancet 344(8927): 905

- 909. Keeley, A., Faulkner, B.R. 2008. Influence of land use and watershed characteristics on protozoa contamination in a potential drinking w ater resources reservoir. Water Research 42: 2803

- 2813. Ki, S.J., Ensari, S., Kim, J.H. 2007. Solar and tidal modulations of fecal indicator bacteria in coastal water at Huntington Beach, California. Environmental Management 39: 867

- 875. Lavender, J.S., an d Kinzelman, J.L. (2009) A cross comparison of QPCR to agar

- based or defined substrate methods for determination of Escherichia coli and enterococci in municipal water quality monitoring programs. Water Research 43 : 4967

- 4979. LeChevallier, M.W., Norton, W .D., Lee, R.G. 1991. Occurrence of Giardia and Cryptosporidium spp. in surface water supplies. Applied and Environmental Microbiology 57(9): 2610

- 2616. Lee, C.M., Lin, T.Y, Lin, C.

- C.; Kohbodi, G.A., Bhatt, A., Lee, R., Jay, J.A. 2006. Persistence of feca l indicator bacteria in Santa Monica Bay beach sediments. Water Research 40:2593

- 2 602.

## U.S. Environmental Protection Agency

August 2010 67 Lee, J.V., Dawson, S.R., Ward, S., Surman, S.B., Neal, K.R. 1997. Bacteriophages are a better indicator of illness rates than bacteria amongst users of a white water cou rse fed by a lowland river. Water Science and Technology 35 : 165

- 170. Lee, J.H., Bang, K.W. 2000. Characterization of urban stormwater runoff. Water Research 34(6): 1773

- 1780. Lemarchand, K., Lebaron, P. 2003. Occurrence of Salmonella spp and Cryptosporidi um spp in a French coastal watershed: relations with fecal indicators. Federation of European Microbiological Societies (FEMS) Microbiology Letters 218: 203

- 209. Levesque, B., Gauvin, D. 2007. Microbiological guideline values for recreational bathing in Ca nada: Time for change? Canadian Journal of Infectious Diseases & Medical Microbiology. 18(2): 153

- 157. Lipp, E.K., Kurz, R., Vincent, R., Rodrigues

- Palacios, C., Farrah, S.R., Rose, J.B. 2001a. The effects of seasonal variability and weather on microbial f ecal pollution and enteric pathogens in a subtropical estuary. Estuaries 24(2): 266

- 276. Lipp, E.K., Schmidt, N., Luther, M.E., Rose, J.B. 2001b. Determining the effects of El

- Nino

Southern oscillation events on coastal water quality. Estuaries 24(4): 491

- 497. López

- Pila, J.M., Szewzyk, R. 2000. Estimating the infection risk in recreational waters from the faecal indicator concentration and from the ratio between pathogens and indicators. Water Research 34: 4195

- 4200. Lopez, R.D., Nash, M.S., Heggem, D.T., Ebert, D.W. 2008. Watershed vulnerability predictions for the Ozarks using landscape models. Journal of Environmental Quality 37: 1769

- 1780. Maki, R.P., Hicks, R.E. 2002. Salmonella typhimurium survival and viability is unaltered by suspended particles in freshwater. Journal of Environmental Quality 31(5): 1702

- 1709. Marino, F., Morinigo, M., Martinez

- Manzanares, E., Borrego, J. 1995. Microbiological

epidemiological study of selected marine beaches in Malaga (Spain). Water Science and Technology 31(5): 5

- 9. Marion, J.W., Lee, J., Lemeshow, S., Buckley, T.J. 2010. Association of illness and recreational water exposure during advisory and non

- advisory conditions at an inland U.S. beach. Water Research: accepted for publication

. Mathes, M.V., O’Brien, T.L., Str ickler, K.M., Hardy, J.J., Schill, W.B., Lukasik, J., Scott, T.M., Bailey, D.E., Fenger, T.W. 2007. Presumptive Sources of Fecal Contamination in Four Tributaries to the New River Gorge National River, West Virginia, 2004. U.S. Department of the Interior, U.S., Geological Survey. Open

- File Report 2007

- 1107 Reston, VA. McCambridge, J., McMeekin, T.A. 1981. Effect of solar radiation and predacious microorganisms on survival of fecal and other bacteria. Applied and Environmental Microbiology 41(5): 1083

- 1087. McFeters, G.A., Stuart, D.G. 1972. Survival of coliform bacteria in natural waters: field and laboratory studies with membrane filter chambers. Applied Microbiology 24(5): 805

- 811. Abstract available online at http://aem.asm.org/cgi/content/abstract/24/5/805

. Menon, P., Billen, G., Servais, P. 2003. Mortality rates of autochthonous and fecal bacteria in natural aquatic ecosystems. Water Research 37: 4151

- 4158. Mill, A., Schlacher

, T.

, Katouli

, M. 2006

. Tidal and longitudinal variation of faecal indicator bacteria in an estuarine creek in south

- east Queensland, Australia. Marine Pollution bulletin 52: 881

- 891.

## U.S. Environmental Protection Agency

August 2010 68 Molina, M., Maimes, J., Fisher, J., Johnson, B. 2005. Temporal variability of enteroc occi species in streams impacted by cattle fecal contamination. Myers, D.M., Koltun, G.F., Francy, D.S. 1993. Effects of Hydrologic, Biological, and Environmental Processes on Sources and Concentrations of Fecal Bacteria in the Cuyahoga River, With Implic ations for Management of Recreational Waters in Summit and Cuyahoga Counties, Ohio. US Geological Survey. Water

- Resources Investigations Report 98

- 4089 Reston, VA. Noble, R.T., Lee, I.M., Schiff, K.C. 2003. Inactivation of Indicator Bacteria from Various S ources of Fecal Contamination in Seawater and Freshwater. Southern California Coastal Water Research Project. 2001

- 02 Biennial Report, pp. 164

- 163. Noble, R.T., Lee, I.M., Schiff, K.C. 2004. Inactivation of indicator micro

- organisms from various sources o f faecal contamination in seawater and freshwater. Journal of Applied Microbiology 96: 464

- 472. NRC (National Research Council). 2004. Indicators for Waterborne Pathogens. Washington DC: National Academies Press. O’Brien, R.T., Newman, J.S. 1977. Inactivat ion of poliovirus and coxsackievirus in surface water. Applied and Environmental Microbiology 33(2): 334

- 340. Available online at: http://aem.asm.org/cgi/reprint/33/2/334.pdf

. Obiri

- Danso, K., Jo nes, K. 1999. Distribution and seasonality of microbial indicators and thermophilic campylobacters in two freshwater bathing sites on the River Lune in northwest England. Journal of Applied Bacteriology 87: 822

- 832. Okabe, S., Shimazu, Y. 2007. Persistence of host

- specific Bacteroides

- Prevotella 16S rRNA genetic markers in environmental waters: effects of temperature and salinity. Applied Microbiology Biotechnology 76: 935

- 944. Okhuysen, P.C., Rich, S.M., Chappell, C.L., Grimes, K.A., Widmer, G., Feng, X., Tzipori, S. 2002. Infectivity of a Cryptosporidium parvum isolate of cervine origin for healthy adults and interferon

- gamma knockout mice. Journal of Infectious Diseases 185(9): 1320

- 1325. Olapade, O.A., Depas, M.M., Jensen, E.T., McLellan, S.L. 2006. Micr obial communities and fecal indicator bacteria associated with Cladophora mats on beach sites along Lake Michigan shores. Applied and Environmental Microbiology 72: 1932

- 1938. Olyphant, G.A. 2005. Statistical basis for predicting the need for bacterially i nduced beach closures: emergence of a paradigm? Water Research 39: 4953

- 4960. Olyphant, G.A., Thomas, J., Whitman, R.L., Harper, D. 2003. Characterization and modeling of bacterial ( Escherichia coli ) outflows from watersheds that discharge into southern Lake Michigan. Environmental Monitoring and Assessment 81: 289

- 300. Pancorbo, O.C., Evanshen, B.G., Campbel, W.F., Lambert, S., Curtis, S.K., Woolley, T.W. 1987. Infectivity and antigenicity reduction rates of human rotavirus strain Wa in fresh waters. App lied and Environmental Microbiology 53(8): 1803

- 1811. Paul, J.H., Rose, J.B., Jiang, S., Kellog, C., Shinn, E.A. 1995. Occurrence of fecal indicator bacteria in surface water and the subsurface aquifer in Key Largo, Florida. Applied and Environmental Micro biology 61(6): 2235

- 2241. Pennington, A.T., Harding, A.K., Hendricks, C.W., Campbell, H.K. 2001. Evaluating microbial indicators of environmental condition in Oregon rivers. Environmental Management 28(6): 833

- 841. Pérez

- Rosas, N., Hazen, T.C. 1988. In sit u survival of Vibrio cholrea and Escherichia coli in tropical coral reefs. Applied and Environmental Microbiology 54(1): 1

- 9.

## U.S. Environmental Protection Agency

August 2010 69 Pérez

- Rosas, N., Hazen, T.C. 1989. In situ survival of Vibrio cholera and Escherichia coli in a tropical rain forest watershed. Ap plied and Environmental Microbiology 55(2): 495

- 499. Petersen, T.M., Rifai, H.S., Suarez, M.P., Stein, A.R. 2005. Bacteria loads from point and nonpoint sources in an urban watershed. Journal of Environmental Engineering 131(10): 1414

- 1425. Petersen, T.M., Suarez, M.P., Rifai, H.S., Jensen, P., Su Y.

- C., Stein, R. 2006. Status and trends of fecal indicator bacteria in two urban watersheds. Water Environment Research 78(12): 2340

- 2355. Power, M.L., Littlefield

- Wyer, J., Gordon, D.M., Veal, D.A., Slade, M.B. 2005. Phenotypic and genotypic characterization of encapsulated Escherichia coli from blooms in two Australian lakes. Environmental Microbiology 7(5): 631

- 640. Pruss, A. 1998. Review of epidemiological studies on health effects from exposure to recreation al water. International Journal of Epidemiology 27(1): 1

- 9. Rao, V.C., Seidel, K.M., Goyal, S.M., Metcalf, T.G., Melnick, J.L. 1984. Isolation of enteroviruses from water, suspended soilds, and sediments from Galveston Bay: survival of poliovirus and rotav irus adsorbed to sediments. Applied and Environmental Microbiology 48(2): 404

- 409. Rees, P.L.S., Baker, R., Long, S.C., Barten, P.K. 2005. Transport of Cryptosporidium and Giardia in Massachusetts waters during storm events. Proceedings of Managing Watersh eds for Human Health and Natural Impacts, Watershed 2005 , Williamsburg, VA. Rex, A.C., Coughlin, K.A., Ballester, N.A. 2005. A survey of pathogenic viruses and indicators in Boston Harbor and the Charles River. 105 th 

## General Meeting of the ASM , Atlanta, GA

. Rhodes, M.W., Kator, H. 1988. Survival of Escherichia coli and Salmonella spp. in estuarine environments. Applied and Environmental Microbiology 54(12): 2902

- 2907. Available online http://aem.a sm.org/cgi/reprint/54/12/2902.pdf

. Riou, P., Le Saux, J.C., Dumas, F., Caprais, M.P., Le Guyader, S.F., Pommepuy. 2007. Microbial impact of small tributaries on water and shellfish quality in shallow coastal areas. Water Research 41: 2774

- 2786. Roser, D. , Ashbolt, N. 2004. Source water quality assessment and the management of pathogens in tributaries. WQTC , San Antonio, TX. Ryu, H., Abbaszadegan, M. 2008. Long

- term study of Cryptosporidium and Giardia occurrence and quantitative microbial risk assessment in surface water of Arizona in the USA. Journal of Water and Health 6(2): 263

- 273. Santo

- Domingo, J.W. 2000 Test for E nteric B acteria in T ropical R ecreational W aters. U

. S

. Department of Health and Human Services. Santoro, A.E., Boehm, A.B. 2007. Frequent occurrence of the human

- specific Bacteroides fecal marker at an open coast marine beach: relationship to waves, tides and traditional indicators. Environmental Microbiology 9(8): 2038

- 2049. SCCWRP. 2008 Southern California Coastal Water Research Project A uthority: FY 2008/2009 Research Plan. SCCWRP. Westminster, CA. Schaub, S. 2004. A risk assessment framework for water pathogens and requirements for producing a complete protocols. Human and Ecological Risk Assessment 10(1): 151

- 158. Schets, F.M., van Vij nen, J.H., Schijven, J.F., Schoon, H., Husman, A.M.R. 2008. Monitoring of waterborne pathogens in surface waters in Amsterdam, the Netherlands, and the potential

## U.S. Environmental Protection Agency

August 2010 70 health risk associated with exposure to Cryptosporidium and Giardia in these waters. Applied a nd Environmental Microbiology 74(7): 2069

- 2078. Schoen, M.E., Ashbolt, N.J., 2010. Assessing pathogen risk to swimmers at non

- sewage impacted recreational beaches. Environmental Science and Technology. 44(7): 2286

- 2291. Schwab, K.J. 2007. Are existing bact erial indicators adequate for determining recreational water illness in waters impacted by non

- point pollution? Epidemiology. 18(V1):21

- 22. Servais, P., Garcia

- Armisen, T., George, I., Billen, G. 2007. Fecal bacteria in the rivers of the Seine drainage netw ork (France): sources, fate and modelling. Science of the Total Environment 375: 152

- 167. Seyfried, P.L., Tobin, R.S., Brown, N.E., Ness, P.F. (1985a) A prospective study of swimming

related illness. I. Swimming

- associated health risk. American Journal of Public Health 75: 1068

- 1070. Seyfried, P.L., Tobin, R.S., Brown, N.E., Ness, P.F. (1985b) A prospective study of swimming

related illness. II. Morbidity and the microbiological quality of water. American Journal of Public Health 75: 1071

- 1075. Shehane. 200 3. The influence of climate on the incidence of microbial fecal indicators and the source of fecal contamination within the lower St. Johns River Basin, Florida. 103 rd 

## General Meeting of the ASM , Washington, DC. Shehane, S.D., Gennaccaro, A.I., Whitlock, J., Harwood, V.J., Rose, J.B. 2002. The occurrence of microbial fecal indicators and the determination of the source of fecal contamination in the St. John’s River, Florida. 102 nd 

## General Meeting of the ASM , Salt Lake City, UT. Shehane, S.D., Harwood, V.J. , Whitlock, J.E., Rose, J.B. 2005. The influence of rainfall on the incidence of microbial faecal indicators and the dominant sources of faecal pollution in a Florida river. Journal of Applied Microbiology 98(5): 1127

- 36. Shellenbarger, G.G., Athearn, N.D. , Takekawa, Boehm, A.A. 2008. Fecal indicator bacteria and Salmonella in ponds managed as bird habitat, San Francisco Bay, California, USA. Water Research 42: 2921

- 2930. Sherer, B.M., Miner, J.R., Moore, J.A., Buckhouse, J.C. 1992. Indicator bacterial surv ival in stream sediments. Journal of Environmental Quality 21: 591

- 595. Signoretto, C., Burlacchini, G., Leo, M.d.M., Pruzzo, C., Zampini, M., Giorgio, F., Canepari, P. 2004. Adhesion of Enterococcus faecalis in the nonculturable state to plankton is the

m ain mechanism responsible for persistence of this bacterium in both lake and seawater. Applied and Environmental Microbiology 70(11): 6892

- 6896. Sinigalliano, C.D., Fleisher, J.M., Gidley, M.L., Solo

- Gabriele, H.M., Shibata, T., Plano, L.R.W. et al. 2010. Traditional and molecular analyses for fecal indicator bacteria in nonpoint source subtropical recreational marine waters. Water Research 44: 3763

- 3772. Sinton, L., Hall, C., Braithwaite, R. 2007. Sunlight inactivation of Campylobacter jejuni and Salmonell a enterica , compared with Escherichia coli , in seawater and river water. Journal of Water and Health 5(3): 357

- 365. Sinton, L.W., Hall, C.H., Lynch, P.A., Davies

- Colley, R.J. 2002. Sunlight inactivation of fecal indicator bacteria and bacteriophages from w aste stabilization pond effluent in fresh and saline waters. Applied and Environmental Microbiology 68(3): 1122

- 1131. Sinton, L.W., Davies

- Colley, R.J., Bell, R.G. 1994. Inactivation of enterococci and fecal coliforms from sewage and meatworks effluents in seawater chambers. Applied and Environmental Microbiology 60(6): 2040

- 2048.

## U.S. Environmental Protection Agency

August 2010 71 Sinton, L.W., Finlay, R.K., Lynch, P.A. 1999. Sunlight inactivation of fecal bacteriophages and bacteria in sewage

- polluted seawater. Applied and Environmental Microbiology 65(8): 3605

- 3613. Skraber, S., Gaasilloud, B., Gantzer, C. 2004. Comparison of coliforms and coliphages as tools for assessment of viral contamination in river water. Applied and Environmental Microbiology 70(6): 3644

- 3649. Smith, J., Edwards, J., Hilger, H., St eck, T.R. 2008. Sediment can be a reservoir for coliform bacteria released into streams. Journal of General and Applied Microbiology 54: 173

- 179. Šolić, M., Krstulović, N. 1992. Separate and combined effects of solar radiation, temperature, salinity and pH on the survival of fecal coliforms in seawater. Marine Pollution Bulletin 24: 411

- 416. Soller, J.A., Eisenberg, J.N.S., DeGeorge, J.F., Cooper, R.C., Tchobanoglous, G., Olivieri, A.W. 2006. A public health evaluation of recreational water impairment. Jour nal of Water and Health 04.1: 1

- 19. Soller, J.A., Schoen, M.E., Bartrand, T.A., Ravenscroft, J.E., Ashbolt, N.J. 2010. Estimated human health risks from exposure to recreational waters impacted by human and non

human sources of faecal contamination. Water Research : doi:10:1016/j.watres.2010.07.064

. Accepted for publication Soonthornnonda, P., Christensen, E.R., Liu, Y., Li, J. 2008. A washoff model for stormwater pollutants. Science of the Total Environment 402: 248

- 256. Sorensen, D.L., Eberl, S.G., Dicks a, R.A. 1989. Clostridium perfringens as a point source indicator in non

- point polluted streams. Water Research 23(2): 191

- 197. Stewart, J.R., Thompson, B.C., Webster, L.F., Scott, G.I. 2000. Escherichia coli and coliphage analyses to differentiate polluti on sources in surface water of South Carolina. 100 th 

## General Meeting of the ASM , Los Angeles, CA. Tiefenthaler, L.L., Stein, E.D., Lyon, G.S. 2008. Fecal indicator bacteria (FIB) levels during dry weather from Southern California reference streams. Environ mental Monitoring Assessment 155 (1

- 4): 477

- 492. Till, D., McBride, G., Ball, A., Taylor, K., Pyle, E. 2008. Large

- scale freshwater microbiological study: rationale, results and risks. Journal of Water and Health 6: 443

- 459. Touron, A., Berthe, T., Gargal a, G., Fournier, M., Ratajczak, M., Servais, P., Petit, F. 2007. Assessment of faecal contamination and the relations between pathogens and faecal b acterial indicators in an estuarine environment (Seine, France). Marine Pollution Bulletin 54: 1441

- 1450.
Tr aister, E., Anisfeld, S.C. 2006. Variability of indicator bacteria at different time scales in the upper Hoosic River watershed. Environmental Science and Technology 40: 4990

- 4995. Tranter, J., Hunter, C., Gunn, J., Perkins, J. 1996. The bacterial quality of an upland stream. Journal of the Chartered Institution of Water and Environmental Management. 10: 273

- 279. USEPA (U.S. Environmental Protection Agency). 1983

. Health Effects Criteria for Marine Recreational Waters. U.S. Environmental Protection Agency. EPA

- 600/1

- 80

- 031

. Cincinnati, OH. USEPA. 1984. Health Effects Criteria for Fresh Recreational Waters. EPA

- 600

- 1

- 84

- 004. Cincinnati, OH. USEPA. 1986. Ambient Water Quality for Bacteria

– 1986. EPA440/5

- 84

- 002.

## U.S. Environmental Protection Agency

August 2010 72 USEPA. 2004. Water Quality Standards for Coasta l and Great Lakes Recreation Water. Federal Register 69(220): 67217

- 67243. USEPA. 2007 a. Critical Path Science Plan for Development of New or Revised Recreational Water Quality Criteria. U.S. Environmental Protection Agency. EPA 823

- R

- 08

- 002

. Washington, D C. USEPA. 2007 b. Report of the Experts Scientific Workshop on Critical Research Needs for the Development of New or Revised Recreational Water Quality Criteria. U.S. Environmental Protection Agency. EPA 823

- R

- 07

- 006. Washington, DC. USEPA. 2009. Review of Published Studies t o Characterize Relative Risks f rom Different Sources o f Fecal Contamination i n Recreational Water

. EPA 822

- R

- 09

- 001 . Washington, DC. Vaughn, J.M., Landry, E.F., Thomas, M.Z., Vicale, T.J., Penellot, W.F. 1979. Survey of human enterovirus occurrence in fresh and marine surface waters on Long Island. Applied and Environmental Microbiology 38(2): 290

- 296. Vidon, P., Tedesco, L.P., Wilson, J., Campbell, M.A., Casey, L.R. 2008. Direct and indirect hydrological controls on E. coli concentration and loading in midwestern streams. Journal of Environmental Quality 37: 1761

- 1768. Vital, M., Hammes, F., Egli, T. 2008. Escherichia coli O157 can grow in natural freshwater at low carbon concentration. Environmental Microbiology 10(9): 2387

- 2396. Voytek, M.A., Ashen, J.B., Fogarty, L.R., Kishtein, J.D., Landa, E.R. 2005. Detection of Helicobacter pylori and fecal indicator bacteria in five North American rivers. Journal of Water and Health 3(4): 405

- 422. Wade, T.J., Pai, N., Eisenberg, J.N., Colford, J.M. 2003. Do U.S. Environmental Protection Agency water quality guidelines for recreational waters prevent gastrointestinal illness? A systematic review and meta

- analysis. Environmental Health Perspectives 111(8): 1102

- 1109. Wade, T.J., Calderon, R.L., Sams, E., Beach, M., Brenner, K.P., Williams, A.H., Dufour, A.P. 2006. Rapidly measured indicators of recreational water quality are predictive of swimming

- associated gastrointestinal illness. Environmental Health Perspectives 114(1): 24

- 28. Wade, T.J., Calderon , R.L., Brenner, K.P., Sams, E., Beach, M., Haugland, R., Wymer, L., Dufour, A.P. 2008. High sensitivity of children to swimming

- associated gastrointestinal illness

- Results using a rapid assay of recreational water quality. Epidemiology 19(3): 375

- 383. W ait, D.A., Sobsey, M.D. 2001. comparative survival of enteric viruses and bacteria in Atlantic Ocean seawater. Water Science and Technology 43(12): 139

- 142. Waldron, M.C., Cooke, M.G., Ragnelli, C.M. 2002. Storms, Streams, and Reservoirs

– Assessing Water Quality in the Cambridge, Massachusetts, Drinking

- Water Source Area. USGS. Walters, S.P., Gannon, V.P.J., Field, K.G. 2007. Detection of Bacteroidales fecal indicators and the zoonotic pathogens E. coli 0157:H7, Salmonella , and Campylobacter in river wat er. Environmental Science and Technology 41(6): 1856

- 1862. Wang, G., Doyle, M.P. 1998. Survival of enterohemorrhagic Escherichia coli O157:H7 in water. Journal of Food Protection 61(6): 662

- 667. Ward, R.L., Knowlton, D.R., Winston, P.E. 1986. Mechanism of inactivation of enteric viruses in fresh water. Applied and Environmental Microbiology 52(3): 450

- 459.

## U.S. Environmental Protection Agency

August 2010 73 WERF (Water Environment Research Federation). 2009. Report on the Experts Scientific Workshop on Critical Research and Science Needs for the Development of Recreational Water Quality Criteria for Inland Waters. Dallas/Ft. Worth, Texas, February 18

- 20, 2009. PATH4W0. Alexandria, Virginia. Whitman, R., Nevers M. 2003. Foreshore sand as a source of Escherichia coli in nearshore water of a Lake Michigan beach. Applied and Environmental Microbiology 69: 5555

- 5562. Whitman, R.L., Shively, D.A., Pawlik, H., Nevers, M.B., Byappanahalli, M.N. 2003. Occurrence of Escherichia coli and enterococci in Cladophora ( Chlorophyta ) in nearshore water and beach sand of Lake Mi chigan. Applied and Environmental Microbiology 69(8): 4714

- 4719. Whitman, R., Nevers, M.B., Korinek, G.C., Byappanahalli, M. 2004. Solar and temporal effects

on Escherichia coli concentration at a Lake Michigan swimming beach. Applied and Environmental Mi crobiology 70(7): 4276

- 4285. Whitman, R.L., Nevers, M.B., Byappanahalli, M.N. 2006. Examination of the watershed

- wide distribution of Escherichia coli along southern Lake Michigan: an integrated approach. Applied and Environmental Microbiology 72(11): 730 1

- 7310. Whitman, R.L., Przybyla

- Kelly, K., Shively, D.W., Nevers, M.B., Byappanahalli, M. 2008. Sunlight, season, snowmelt, storm, and source affect E. coli populations in an artificially ponded stream. Science of the Total Environment 390: 448

- 455. WHO (W orld Health Organization). 2003 Guidelines for Safe Recreational Water Environments. Volume 1 Coastal and Fresh Waters. World Health Organization. Geneva, Switzerland. WHO. 2006 Guidelines for Drinking Water Quality: Cryptosporidium. Technical R eport. Wor ld Health Organization. Geneva, Switzerland. Wiedenmann, A., Kruger, P., Dietz, K., Lopes

- Pila, J.M., Szewzyk, R., Botzenhart, K. 2006. A randomized controlled trial assessing infectious disease risks from bathing in fresh recreational waters in relation to the concentration of Escherichia coli , intestinal Enterococci, Clostridium perfringens , and somatic coliphages. Environmental Health Perspectives 114(2): 228

- 236. Wijesinghe, R.U., Feng, Y., Stoeckel, D.M., Wood, C.W. 2005. Comparison of Rep

- PCR DNA fin gerprints of Escherichia coli Isolated from multiple sources. 105 th 

## General Meeting of the ASM , Atlanta, GA. Wilson, T.L., Stahnke, G., Schnabel, W., Duddleston, K. 2005. Seasonal variations in fecal coliform bacteria in a cold region stream. Proceedings o f the 2005 World Water and Environmental Resources Congress

. Wyer, M.D., Fleisher, J.M., Gough, J., Kay, D., Merrett, H. 1995. An investigation into parameteric relationships between enterovirus and faecal indicator organisms in the coastal waters of Engla nd. Water Research 29(8): 1863

- 1868. Wymer, L., Brenner, K.P., Martinson, J.W., Stutts, W.R., Schaub, S.A., Dufour, A.P. 2005. The EMPACT beaches project: results from a study on microbiological monitoring in recreational waters. US EPA. EPA 600/R

- 04/023. Cincinnati, OH. Wymer, L., McGee, C., Dufour, A.P. 2007. Temporal variability of microbial indicators of fecal contamination at marine anda fresh water beach. 107 th 

## General Meeting of the ASM

, Toronto, Ontario. Xagoraraki, I., Kuo, D.H.

- W., Wong, K., Wong, M., Rose, J.B. 2007. Occurrence of human adenoviruses at two recreational beaches of the Great Lakes. Applied and Environmental Microbiology 73(24): 7874

- 7881.

## U.S. Environmental Protection Agency

August 2010 74 Yamahara, K.M., Layton, B.A., Santoro, A.E., Boehm, A.B. 2007. Beach sands along the California coast are diffuse sources of fecal bacteria to coastal water. Environmental Science and Technology 41(13): 4515

- 4521. Yamahara, K.M., Walters, S.P., Boehm, A.B. 2009. Growth of enterococci in unaltered, unseeded beach sands subjected to tidal wetting. App lied and Environmental Microbiology 75: 1517

- 1524. Zmirou, D., Pena, L., Ledrans, M., Letertre, A. 2003. Risks associated with the microbiological quality of bodies of fresh and marine water used for recreational purposes: summary estimates based on publis hed epidemiological studies. Archives of Environmental Health 58(11): 703

- 711.

## 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

– C AFO: concentrated animal feeding operations; CFU: colony forming units; CSO: combined sewer overflow; EMAP: (EPA) Environment al Monitoring and Assessment Program; FIB: fecal indicator bacteria; NA: not applicable; NAWQA: USGS’s National Water Quality Asses sment Program; NOAELs: no observable adverse effect levels; PFU: plaque forming units; QPCR: quantitative polymerase chain reaction; TMDL: total maximum daily load; WWTP: waste water treatment plant

Water Type

– F: fresh; E: estuarine; M: marine; U: Unkno wn (not specified) Setting

– IF: inland flowing; IN: inland non

- flowing; C: coastal; GW: groundwater; TI: Tidal influence; U: unknown (not specified) Climate

– temp: temperate; sub: subtropical; trop: tropical; U: unknown (not specified) Media

– WC: water column; sed: sediments; soil: soils; GW: groundwater; U: unknown (not specified) Alternate Indicators

– BF: Bacteroides fragilis ; CP: Clostridium perfring e ns ; HPC: heterotrophic plate count; SP: Streptococcus faecium Indicator Organisms

– FIB: fecal indica tor bacteria (not specified); TC: total coliforms; FC: fecal coliforms; EC: Escherichia coli ; Ent: enterococci (also called fecal streptococci or FS) Pathogens

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

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

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) Ahn et al.

, 2005 M C Sub WC TC, FC, E nt

, EC F+ coli

phage A d v ,

EV A 17 stations in the

surf zone

– water samples collected 5 days during weekdays No Large urban watershed (Sant a Ana River , CA ) Stormwater runoff from the Sant a Ana River negatively impacted coastal water quality (surf zone and offshore) Bacteria and viruses in the offshore
stormwat er plumes associated with small particles Alkan et al. , 1995 M C Temp WC E C

, E nt B, F Yes Water used in mesocosm studies taken from Seaton Point, England

, North Sea coast Higher rates of die

- off resulted from high levels of light intensity and mixing with low levels of turbidity and sewage content of the
water Survival capabilities of EC and Ent on exposure to light not significant ly different Anderson et al. , 1999 F IF Temp WC, S oil, S ed FC

,

E nt

, EC A Samples collected every 2 weeks in several
stre ams No Select Kansas streams V ariable FC levels from 50 to 700 CFU H igher concentrations of FIB in streams impacted by humans FIB concentrations related to rainfall events

## August 2010 A

- 2

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) Baums et al. , 2007 F,

M C Trop WC, S ed EC,

E nt Bacter

ioides Shig B, E, F No Sampl es collected from

u rbanized, tidally influenced river sites and a beach located downstream from flood control gates near Miami, FL Technolog ical approach evaluated has the potential to simultaneously detect multiple 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 T emperature reduced considerably presence of Bacteroides in unfiltered stream water C omplete removal of Bacteroides occurred in 7 days at 25 ° C Benhan et al. , 2006 F IF Temp WC F C

, TC

, E nt

, E C 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 fo rest Kansas River

– large watershed

, predominantly agricultural B acterial modeling using hydrological models for TMDL purposes M odels limited to describe bacterial life cycles and determine bacteria concentrations during extreme events

Benhan et al. , 2005 F IF Temp WC E C G No Primarily rural stream in VA; p asture i s the main land use (49%) ;

r esidential and urban

uses account for 9% M odel results suggest up to 100% reduction in cattle manure and wildlife direct deposits and non

- point fecal source loading to the stream

Ber n hard and Field

, 2000 M C Temp WC Bacter

oides Prevotella E, A Six 1 L water samples No Samples obtained from Tillamook Bay, OR

, which is f requently contaminated with fecal pollution S pecific PCR primers that discriminate human and ru minant sources of fecal contamination

Bonilla et al. , 1999 M,

F C, IF Tropic WC FC, EC CP,

BF

, FRNA phage A No Unspecified beach and inland stream in Hawaii Abstract only FC and EC elevated at all up

- stream sites did not indicate sources FRNA low and al so did not indicate source; however, C P clearly indicated that the

## August 2010 A

- 3

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) contributing source was only one of the two tributary streams Bordalo, 2003 M C Temp WC T C, FC A S urvey lasted 18 consecutive summer days, 3 times a day

, a total of 184 samples collected No Two urban beaches in Portugal P eriodicity of fecal indicators in raw sewage, tidal status

, and wind conditions influenced water quality Microbial water quality decreased in morning regardless of tide conditions, but improved during high tide and aftern oon ( NW ) winds

Bowen and Oliver

, 2008 E C Temp WC, S ed Not

speci

- fied A, G No North Carolina w atershed ( Neuse River Estuary ) with known public health problems related to municipal and agricultural wastewater discharge, storm runoff Abstract only (of p roposed integrated water quality research and modeling) I mpact of extreme climatic storm events is

enormous

Brookes et al. , 2005 F IF,

IN Temp WC E C, Ent CP,

aerobic
spores, somatic coliphage particle size, turbidity Crypto

,

Giardia A Sampling during

a l arge runoff event following intense rainfall No South Australia, reservoir and inland stream,

m ixed land use, including pasture and vegetation CP and Ent most highly correlated with Crypto Crypto associated with small sized particles A ll of the indicators except CP associated with large particle size

Brownell et al. , 2007 M C Sub WC, S ed FC,

Ent, EC A, D Two sampling events : one within 48 h ours of heavy rainfall and one after a dry period (6 days of no precip ita

- tion ) No Siesta Key Beach on west coast of Florida with an adjacent (parallel) stormwater conveyance system H igh indicator bacteria levels attributable to a storm water system that acted as a reservoir and conduit, flushing high levels of indicator bacteria to the beach during the rain event N o evidence of human fecal contamination found by MST methods

Buckley et al. , 1998 F O

, F Sub WC, S ed TC,

(Ent), (EC) PS,

A H A total of 240

samples were analyzed for TC, and 306 for individual bacterial species No Stream in a subtropical rainforest res erve but with significant tourism in Queensland, Australia TC concentrations in sediment not correlated with sampling site, rainfall, streamflow

, or visitor number TC in sediment 1000 × higher than in the WC Fi rst report of PS in natural surface water in Au stralia

Buckwa l ter et al. , 2006 F IF Temp WC E C, Ent, A USGS s urvey from July No T he Allegheny, Monongahela, an d S amples collected in the 3 rivers and tributaries frequently exceed established

## August 2010 A

- 4

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) FC 2001

- August 2005 during dry and wet

- weather periods;

s amples collected from 5 sites on the Three Rivers and from 8 sites on 4 tributaries Ohio River Basins within Allegheny County and City of Pittsburgh, PA recreational standards and criteria for bacteria FIB from tributaries most strongly correlated with strea mflow, specific conductance, and turbidity

Burkholder et al. , 2007 F IF,

IN, GW 1° Temp ( All U

. S .) WC,

S ed

, S oil, GW Not

spec

- ified Not

specified Not

specified I No NA CAFO workshop proceedings and recommendations A ccepted livestock waste management
p ractices do not adequately or effectively protect water resources from contamination with excessive nutrients, microbial pathogens I mpacts 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 S ed

,

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

- November 1999 and from February

- November 200, for a total of 710 samples No Dunes Creek watershed (primarily nondeveloped A quatic or wetland habi tat ; remaining land

use R esidential a nd agricultural ) in northern IN, drains into Lake Michigan at a major recreational beach E C in d unes Creek and beach water signif icantly c orrelated C hronic loading of EC throughout the stream Significant c orrelations b etween E C in stream

wa t er and sediment, submerged sediment and margin, and margin and 1 m from shore E C is ubiquitous and persistent in the basin E C in riparian sed iments increased bacteria in the creek E nlargement of the stream, increase drainage, and wet land loss may account for high EC levels Byappana

- hallii et al.

, 2007 F IN,

C Temp S ed,

soil E C A Monthly sampling between May

- A ugust 2003 ; 5 samples were collected from 5 different rocks in each No Shoreline waters of lake Michig an (Ogden Dunes Beach, IN); Combination of urban and rural wastes, including sewage overflows, septic field leachate, and runoff EC associated with Cladophora (blue

- green algae) may be a recurring source of in dicator bacteria to the nearshore beach

## August 2010 A

- 5

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) of the 2 beach sites from nearby urban areas and agricultural farms Cabelli, 1983 M

,

F C, IN Temp WC TC, FC, E nt

, E C Male

specific coli

- phage, C P AH,

Acineto

- b acter sp, PA

, VP I,

J, A, H Epi /microbial data collected 1972

- 1979 ; samples collected below the surface of the water duri ng the time when people were in the water ;

c ollected 2

- 3 locations along each beach No S ampling sites included beaches at New York City, NY ; Lake Pontchartrain, New Orleans, LA ; and Boston Harbor, MA A ssessment of the relationship between microbiological indicators of water quality and illness that may have resulted from swimming D ata resulted from EPA internal and extramural epi

- micro projects Epi studies used to e stablish 1986 EPA health effects criteria for marine recreational waters Large number of pat hogenic bacteria and viruses in municipal sewage

Campbell et al.

, 1999 * F C,

IF Temp WC TC, FC

, E C HPC A Summer sampling in 1997 ; a total of 26 sites were resampled No Random selection (EMAP protocol) of 146 streams located throughout Oregon Abstract onl y 17% of streams exceeded t he then current Oregon standard for water

- contact recreation FIB levels differed significantly among the 8 O regon ecoregions Chambers et al.

, 2005, 200 8 F IF,

IN Temp WC,

S oil TC,

EC A WC and soil samples collected from lakes

, river

, and puddles at intersections of major boardwalk s and along the main road No Rural Alaska: Yup’ik village on the Yukon

- Kiskokwim Delta south of Bethel in a tund r a

eco s ystem S tudy conducted to determine main pathways (vehicles, shoes, and surface fl ow) of microbial water contamination I n early summer, many ponds and puddles in and around town tested positive for TC and E C E C also detected on tested shoes, dog paws

, and tires of all terrain vehicles returning from nearby dump

Chamdra

- mouli et al.

, 2 007 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 ; W ater quality data No Kentucky River system : essentially a series of small lakes separated by locks, which behaves differently under high and low flow conditions as well as seasonally O bjective wa s to predict peak indicator bacteria conc entra tion in surface water from 44 related physical, chemical, and bacterial data M odel provided slightly superior prediction of actual microb ial conc entrations when compared to multiple linear regression models

## August 2010 A

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Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

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Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) augmented with flow and rainfall USGS data from several upstream sites at locks and gauging stations Choi and Jiang

, 2005 b* M C Sub E nt

, FC F

- speci fic

coliphage Ad v40 A, F, B 100 mL of sewage mixed with 900 mL of marine water seeded with 1 mL of 10 7
PFU /mL A dv 40 (Adv serotype 40); i nactivation results with sodium hypochlorite

were compared at 0, 1, 2, 3, 24, and 48 hours Yes Southern CA beaches (not specified) Abstract only P reliminary 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 resi stance to inactivation by chlorine FC and E nt 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 , C A Abstract only No FIB growth in microcosms; FIB survival or growth appeared to be better in freshwater added with nutrient from bird feces and

macro

- algae in the dark (lab experiment) D ifferences in bacteria species and community composition between fresh and marine microcosm T otal bacterial and viral direct counts increased in microcosms seeded with bird feces and macro

- algae S alinity, nutrients

, and competition with indigenous microbial community contributed to the growth or death of FIB in WC Cinotto, 2005 F IF Temp WC, S ed EC,

Ent, FC, A USGS s ampling from Sep tember No West Branch Brandywine Creek, Coatesville, PA ; urban/ industrial land USGS a ssessment of effects of sediment particle size, climatic conditions, aquatic growth, environmental chemistry,

## August 2010 A

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Study

Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

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Study Type(s)

Frequency and

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Decay Data?

Watershed Description Note ( s ) FS (Ent) 20 02

- Aug ust 2003; a total of 64 baseflow and 15 stormflow sampling sites use serving as water supply, irr igation, and recreation uses impervious surfaces, sediment, and soil filtration and dams on FIB E C and E nt appeared to be relate d to specifi c particle size Climate conditions affected FIB ; e.g., drought of 2002 had lower overall bacteria concentrations than wet year of 2003 S ymbiotic relations hip between bacteria and aquatic growth likely responsible for increased bacteria observed within a

s ampled impoundment area N utrients increased during both base

- flow and stormflow that could had contributed to accelerate aquatic growth I mpervious surfaces found to increase bacteria conc entrations along the creek T urbidity show n to indicate higher

conc ent ration of bacteria but the relation ship 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 M easured peak hydrogen peroxide

conc entration 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 P eroxide levels in the surf zone may be increased by additional peroxide production mechanism s such as deposition, sediments

, and stressed marine biota, which may further enhanc e impacts on FIB in marine bathing waters

Coffey et al. , 2007 F U U U None Crypto, EC O157, Salm, Campy, Giardia

, R ota

- vir us , N oro

virus G No Not specified, ―agricultural watersheds‖ Evaluation of 13 quantitative simulations (microbial risk assessment models) for

mo deling bacterial pollutants in agricultural watersheds N o one model suits all modeling criteria or needs P athogen predictions have proved variable and no model was capable of accounting for all geological and hydrological factors in addition to modeling t he physical transport

## August 2010 A

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Study

Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) of bacteria in surface runo f f Cole et al.

, 2000 * F U Temp U FC, EC

, E nt C P,

somatic coliphage male

- specific coliphage A, F Measured quarterly for 3 years and during storm events for 8 months No 2 unspecified watersheds impacted by animal agriculture, urban development

, and rural residence Abstract only Geometric mean of FC, EC, and somatic phage generally higher at sites impacted by animal and human inputs (e.g., CAFOs ) than at rural residential and background stations Differences i n indicator levels with land use most often statistically signif icant for somatic phages FC levels dropped at C AFO after application of best management practices for animal
wastes L evels of all FIB increased during rainfall events at all sites FIB correlat ed with total suspended solids, but correlation differed for base and storm flows E nt and somatic phages were most season al with higher levels in summer Colford et al. , 2007 M C Sub WC E nt

, FC, TC Bacter

oides

, coliphage Adv

N oro

- virus H Var ied

depending on the specific indicator ; p articipants recruited each sampling day ; microbial water quality sampled at multiple sites per beach and multiple time periods per day No Mission Bay, Southern CA: w ater quality standards ha d been exceeded

~ 20% of the time ; r ec ent MST studies suggested tha t human fecal material constitutes a minor proportion of fecal inputs to the Bay T raditional FIB used to monitor these beaches not associated with adverse health risks Epidemiological results suggest a need for alternative indi cators of water quality where

non

- point sources are dominant fecal contributors

Craig et al.

, 2003 M C Sub WC, S ed EC

E nt C oliphage Salm Typh

- imurium

, Salm derby B,

F Microcosms maintained at10° C, 20 ° C, and 30 ° C and inoculated with prepared strains of i ndicator s and Yes NA; WC and sed samples taken from recreational coastal sites in Adelaide

, Australia D ecay rate of Salm spp. greater than either E nt or coliphag e in WC and Sed D ecay rate of EC similar to Salm spp in WC

, although greater in S ed Increased temperature s resulted in an increased decay rate for all organisms in the WC but to a lesser extent in S ed D ecay rates for both S alm greater in WC than

## August 2010 A

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Study

Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) pathogens; micro

- organism s enumerated and decay
rates determined for Days 0,1

, 2, 7, 14 and 28 in S ed, wh ich suggest s that S ed 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 r ecent major investmen t in the sewerage infrastructure (new WWTP) B efore the WWTP , higher bacterial

conc entrations strongly associated with rainfall TC and FC originated from the sewage sources but not FS (Ent) that may have been more strongly affected by diffuse catchment sour ces and did not decrease after WWTP After the WWTP , catchment sources
appear ed to be of greater significan ce ; however, rainfall remain ed as a significant, though less important predictor of FIB concentrations A fter the WWTP, tide height at time of sampling , together with variables including sunshine and the proportion of onshore winds became of greater significance to FIB concentrations Crysup and Mott , 2001 * F,

E IF Temp U FC, E C, Ent October 19 99

- Sep tember 2000; 8 stations sampled monthly and during

s ignificant rainfall (>0.9 in ches ) No Oso Creek/ Bay Watershed, TX : ch aracter ized by a wide range of salinity and temperature ; Oso Creek receives uncontrolled agricultural and urban runoff Abstract only Bacterial densities exceeded 1986 EPA rec water standa rds in 19% (FC), 20% (EC), 39% (Ent) of dry weather samples at the mouth of Oso Creek D uring rainfall, all bacterial standards exceeded most frequently in the freshwater stations and for up to 72 hours E nt persisted both in both saline and freshwater envir onments L owest bacterial counts recorded during drought conditions and warmer air temperatures Davies

- Colley et al. , 2008 F IF Temp WC TC E C A B aseflow sampling done monthly ; 30 No Toenepi Stream/Catchment, Waikato Region, New EC peaks well ahead of flo w during storms and concentrations increased with storm event size

## August 2010 A

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Study

Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

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Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) individual
storm events sampled during a 1

- year period, during
storm event s , samples taken every 2 h ou rs during 2 days Zealand : o ne of the most intensively dairy

- farmed areas in the country , which is most ly flat with artificial drainage with 100% pasture Because E C correlate d 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 / E nt A

, B S ampling from M arch

- May

, 1992 ; 8 sampling
surveys conducted :

s amples taken during low and high flow periods from
stormwater inflow ; a 48

- hour laboratory static effluent/stream mixture also assessed No Coastal stream, a bove tidal influence , and 3 nearby WWTP effluents at Galvest on Bay (Houston)

, TX, which is a heavily urban environment Study assessed the effect of dechlorination on FIB concentrations above and below WWTPs I mprovement in bacterial water quality found, principall y due to municipality efforts to correct illicit conn ections and other sewerage system problems R egrowth 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 E C Ent P A,

Staphyl

- ococcus

aureus B

, F Microcosm experiments conducted

summers 2001

- 2003 Yes NA, source of water used in experiments not specified (studies conducted in Austria) E nt showed to be the most resistant organis m and the most sensitive to solar irradiation R esults show ed a significant correlation between radiation intensity and reduction rates B est elimination of organisms occurs on the water surface with deeper water having less UV H igh 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, E Three water

samples collected at each site between Dec ember

- No Inland and coastal basin in OH, WA, IA, SC, WV Cuyahoga River Basin (OH)

– urban and agricultural Thornton Creek (WA)

– All sites showed evidence of fecal contamination and were positive for EC All 5 sampling sites positive for viruses by both molecular and cell culture

- based virus
assays ; overall, 87% of unseeded sampl es contained culturable viruses

## August 2010 A

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Study

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Indicator Organism(s) Alternative Indicators

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Study Type(s)

Frequency and

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Decay Data?

Watershed Description Note ( s ) HAV May 19 98 for

ra nge of streamflows; at least 1 sample from each site collected during or after
a storm event urban Iowa River (IA)

– agricultural row crop and confined animal Cow Castle Creek (SC)

– agricultura l Clear For k (WA)

– mining / rural residential with septic systems After excluding potentially false

- positive results, PCR assays identified reovirus in 30% of the samples, rotavirus in 20%

, and H A V in 17% of samples

Desmarais et al.

, 2000 * E C Sub WC, S ed E C CP A, B, F Field samples coll ected along the length of the river, a t both high and low tide, in 150 M increments North Fork of the New River Fort Lauderdale, FL Abstract only R esults along the river indicate that large numbers of E C are associated with low levels of conductivity and chloride and elevated levels of phosphate C P found to increase with the overall tidal stage of the river and with wet conditions R esults from soil experiment indicate that E C is cap able of multiplying by two orders of magnitude when subjected to wetting a nd drying cycles and have a significant impact on the concentration in the water column Authors concluded that C P is generally 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 collected from each of 15 site s No Rural ( hill

- country ) streams in the Whatawhata district

, Waikato, New Zealand that were impacted by pastoral farming with grazing animals

, indigenous forest, or pine f orest s EC detected in virtually all samples and highest in streams flowing through grazed pasture T here was a noticeable seasonal pattern in all
streams regardless of land use, with highest bacterial co unts in summer and autumn and lowest in winter and early spring N o obvious correlation between E C and rainfall or streamflow 28% of pastoral samples, 25% of indigenous forest samples, 14% of 7

- year pine forest samples, and 5% in n ew p ines stream samples (after planting) had EC concentrations associated with a high level of risk for contact recreation ; the high est EC usually occurred in summer Dufour, 1984 F IN Temp WC E C, FC, Ent H E pi

- micro study of recreational
water No Keystone Lake, about 15 miles from Tulsa, OK. Sampling sites located A good correlation was observed between swimming

- associated GI symptoms and either E C or E nt densities in the water

## August 2010 A

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Study

Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

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Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) exposure and health conducted 1979

- 1982 near sewage discharge and outfall ; Lake Erie, PA with 2 sites , 1 near

a sewage outfall FC showed little or no correlation to GI illness rates in s w immers In gene ral, high GI illness rates associated with high densities of FIB Freshwater studies to form basis for 1986 EPA recreational water criteria (see also Cabelli, 1983) Edwards et al. , 1997 F IF Temp WC FC, FS (Ent) A, F FIB measured for up to 3 years (Sep te mber 19 91

- April 19 94) at 5 sites ; flow data collected from 2 of 5 sites No Two NW Arkansas streams: land use
p rimarily pasture (57

- 90% ; beef production and poultry CAFOs ) and forest (6

- 40%) For on the two sites with flow data, flow rate generally increased when FC and FS (Ent) also increased during all seasons R atios of FC and FS did not appear to reliably differentiate between animal and human sources of fecal pollution H ighest concentrations of FC and FS observed during the summer Ellis and Yu , 1995 F I F Temp WC, S ed TC,

FC, FS (Ent) Somatic

phage PA,

Salm A,

F Weekly and storm event sampling from Oct ober 19 90

- Feb ruary 1991 No 4 CSO outfalls , the serving trunk sewer, and a downstream site

on the main stream within the Pymmes Brook (urban) catchment in N orth London, UK CSO s serve as effective generator of bacteria and pathogens to urban receiving water I n

- stream S ed from sewer source function as reservoirs for high bacterial con centrations over extended periods following wet weather conditions FC and FS (Ent) demonstrated a clear ability to multiply and survive in S ed 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 i ndicate that a biotic balance is achieved between reproduction and predation rates Elmir et al.

, 2007 M C Sub WC, Soil E nt Staphyl

- ococcus

aureus A,

C Two sampling type s , large and small pool : 1) large pool study: microbial shedding from bathers as
gro up ; 2) small pool study : microbial release from Volunteer studies conducted at a marine beach in Miami

- Dade County, FL using off

- shore water and on

- beach sand Demonstrated that bathers shed significant concentratio ns of Ent and S. aureus into the WC; thus human microbial bathing load should be considered as a non

- point source when designing recreational water quality models S. aureus concentrations at least one order of magnitude greater than E nt E nt contribution f rom sand adhered to skin was small (5%) relative to the amount shed directly from the skin E nt and S. aureus decreased significantly

## August 2010 A

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Study

Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

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Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) individuals + beach sand adhered to skin between bathing episodes

Evanson and Ambrose

, 2006 M,

E C S ub WC, S ed TC

,

EC, E nt A Two month study at two sites in

coa stal 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 : r estored wetland designated open space and recreational by Orange County, CA ; a lthough 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 l evels observed in adjacent surf zone waters. In first two rain events, TC/EC/Ent in wetland water and sediment peaked either on the same day or within several days later; t he third rain event resulted in higher wetlands sediment TC levels only TC in adjac ent coastal waters consistently peaked on the same day as the rain event and deceased quickly TC/EC ratios of surf zone samples less than 10, indicating an increase d probability of human fecal contamination Wetland TC/EC ratio were 60 and 14 for the two si tes and do not necessarily indicate human fecal contamination but suggest sediment

- associated FIB may be distinct from those found in the WC samples I ncreases 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 D ifferences between the two wetland sites may be due to sediment differences (organic content and finer grain size) Ferguson et al. , 1996 E C T emp WC, S ed FC,

FS (Ent) CP,

F

- RNA phage Aero

-

monas spp, EV Crypto, Giardia

, Salm A,

F Water and sediment samples collected 10 times between Sep tember 19 92

- June 199 3 from 6 sites with in the No U rban estuary in Sidney, Australia ; t idal regions of the Georges River which is an important recreational and economic resource within the Sydney region, used for the production of shellfish W ater quality affe cted by rainfall and sewage overflows with significant increase in fecal bacteria and pathogens I n sed iment, only FC increased by rainfall but sewage overflow resulted in increased FC, FS, C P, and Aeromonas Salmonella occurrence appeared to coincide with r ain events E nteric virus did not correlate with wet

## August 2010 A

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Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) estuary and as popular venue ; river receives inputs of urban runoff and during wet weather receive sewage weather C P identified as the most useful indicator of fecal pollution C P 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 R eviews the fate and transport of pathogens in watersheds supplying drinking water K ey processes determining the fate and transport of pathogens within watersheds are discussed in the context of changing agricultura l pra c tices, climate, and scale factors M a in factors for inactivation of viral and protozoan pathogens include water/osmotic potential, temperature, sunlight and pH, inorganic (ammonia) and organic nutrients T ransport processes for controlling pathogen
movement include adsorption/desorption effect s, hydrological movement, and mechanical and biological movement Fernandez

- Molina et al. , 2004 F IF Temp WC

, GW TC,

FC, F S (Ent) C P,

HPC H AV A, F 51 samples total, 28 from 11

s prings, and 23 samples from five different locations of the Vilanos River No M ontefr í o munipality (Granada, Spain) which is rural with some agriculture; springs are used as drinking water with no treatment; Vilanos River receives WWTP discharges N o HAV detected in any spring water, but 69.6% of the river water samples positive N o r elationship between HAV and the FIB C onductivity and chemical oxygen demand correlated with all micro bial water quality indicators A mmonia and phosphate correlated best with FC and FS

Francy et al. , 2000 F IF,

GW Temp WC,

GW TC,

EC C P

Colip hage A A total of 136 stream water and 143 groundwater samples collected from 6 NAWQA study units throughout the U.S. (e.g., Kanawa

- New River Basin in VA, WA, and No 3

- 4 stream sites located within 6 NAWQA study units and from a variety of existing wells from 4 of t he study units TC found in 99%, EC in 97%, and C P in 73% of the stream water samples TC found in 20%, EC in less than 1%, and C P in none of the GW samples Coliphage samples became contaminated and not analyzed as part of study L and use ha d the most signifi cant effect on FIB in stream water P resence of septic system near collection site s and well depth related to TCC in GW, although these relationships were not significant ly different

## August 2010 A

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Study

Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) NC) Garcia

- Armisen and Servais

, 2007 F IF Temp WC EC, E nt A For non

- point

s ource s , samples collected in rural areas upstream from WWTPs; S amples also collected at raw and treated effluent of 9 WWTP s No France: Seine river watershed characterized by a high population density, intense industrial activity, and intensive agricultur e , though s ome parts include forest ed

, cultivated

, and grazed areas (small streams) S mall streams flowing through pastures systematically more contaminated than those flowing through forest or cultivated

areas R esults show that the land use of the watersh ed has a significant impact on the quantity of FIB brought to rivers by surface runoff and soil leaching Study demonstrates th e predominant importance of the point sources over the

non

- point sources of FIB

Gentry et al. , 2007 F IF Temp WC E C Bacteroid

es (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 :

m ixed watershed with human, cattle, and wildlife fecal inputs S trong correlation between total fecal l oad, bovine fecal load, EC load rate, 7

- d ay antecedent precipitation, and turbidity T ransport and occurrence of Bacteroides and E C primarily due to runoff

Ge r sberg et al. , 2006 F,

M C Sub WC E C, 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 C oncent ration of HAV and enterovirus below detection for all dry weather samples collected at Imperial Beach R egression analy s es showed a significant correlation between the densities of both Ent and E C and HAV and EV levels

Giddings and Oblinger

, 2004 F IF Temp WC, S ed F C,

EC Coliphage A Sampling at 5 sites i n Newfound Creek and 5 tributary sites during low flow conditions on May 28, 2003, and high flow on November No Newfound Creek Watershed, Western NC USGS report 90% of the E C and FC samples exceeded corresponding EPA (1986) rec/ambient water quality criteria During the high

- flow sampling, all tributaries contained high densities of EC Coliphage results indica ted that non

- human sources of bacteria present in one tributary, and during high flow, human sources of FIB present in another tributary

## August 2010 A

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Study

Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

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Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) 19,2003 A n additional 5 sites sampled for FC and EC in streambed sediments (low flow) and coliph age S ediments do not appear to be a substantial source of bacteria relative to WC concentrations

Gron e wald et al. , 2008 E IF Temp WC F C G Not specified No U s ed FC data from shellfish harvesting waters in the obtained for Newport River Estuary, NC FIB concentration metrics, including MPN and CFU, are not direct measures of the true in situ concentration distribution of FIB, as a result, model and sample

- based assessments can provide different results In response to this problem, an innovative assessment based on Bayesian analysis

was evaluated ; r esults indicate d that areas determined to be compliant according to the sampling may actually have an unacceptably high probability of being in violation of concentration

- based water quality standards/criteria Hall et al.

, 2007 * F IF Temp WC FC A Sampling from 2002

- 2006 on 4 creeks within the Watauga River watershed ; 14 stations

sam pled on Sinking river, 9 stations on Cash Hollow Creek, and 12 stations on Buffalo Creek ;

s tations sampled on a month or quarter ly basis Watauga River watershed

, NE Tennesse e:

a gricultural input is a major source of pollution to for Sinking and Boones Cre ek ;

u rban runoff is a major source of pollution to the Cash Hollow Creek Abstract only Sampling results from Buffalo Creek indicated that FC concentrations were high at stations adjacent to agricultural land R egression analysis indicated that chemical wate r quality parameters do not provide additional information regarding sources of fecal contamination

Hartel et al. , 2007 F,

E, M C

, IF Trop, Temp WC E C,

Ent D 20

- 30 samples from Mayaguez Bay ( Yaguez R iver ) No Mayaguez Bay, western Puerto Rico is dominated by Mayaguez, a modestly T arget ed FIB sampling and fluor o metry (MST) identified two hot spots of human fecal contamination in the Yaguez River and on St. Simons Island

## August 2010 A

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Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) on February 2, 2005 ; 3 separate sampling peri ods in St. Simons

, including a beach, storm drain, and inland creek sized city and ha d a history of fecal contamination problems ; St. Simons Village on the southern end of St. Simons Island, one of the State of Georgia’s (U.S.) barrier islands

Haugland et al. , 2005 F C Temp WC Ent A Sampli ng on weekends and holidays from May

- August, 2003 ; 3

s ampling visits daily ( 8 AM, 11 AM, and 3 PM ) in waist

- level (1m deep) and shin

- level water (0.3m deep) No West Beach at the Indiana Dunes National Lakeshore in Porter, IN on Lake Michigan and Huntingon Beach in Bay Village, Ohio on Lake Erie ; selected, in part, as both generally meeting the state or local water quality standards while having potential for contamination by a human source of fecal pollution Samples collected and analyzed by QPCR and cultu re

- based methods Regression analysis showed a positive correlation between both methods

He et al., 2008 M C Sub WC TC, FC, Ent A, F, G Dry and wet weather sampling Dry event refers to 7 days after a rainstorm and wet event refers to sampling within 0

- 5 d ays after a rainstorm Wet sampling

– daily samples taken from eight locations along the No Coastal watersheds in San Diego County in southern California Beaches receive direct discharges from stormdrains, creeks or rivers, or indir ectly through lagoons Urbanized land uses upstream and year

- round recreational uses for approximately 1

- 2 million visitors yearly S tudy investigated temporal and spatial variations in FIB concentrations in two San Diego beaches Large temporal and spatial v ariations 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, di stance from the outlet channel, wind strength, wind direction, tide height, wave height, rainfall, time lapse after a rain event, or channel flow rate all were factors that significant impacted FIB distribution in the shoreline water quality

## August 2010 A

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Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) shoreline at each beach He et al., 20 07 F C Sub WC, Sed TC,

FC, EC, Ent A Samples taken from randomly selected sites in streams/ creeks (500 samples) No 10 watersheds within the San Diego region in Southern California Land use dominated by undeveloped vacant lands and park/recreational ar eas (75%) and residential and agricultural land uses comprising 10% and 7% FIB levels varied significantly in flowing water, ponded water Associated sediment FIB concentrations in ponded water in waterways significantly higher than in flowing water Sedimen t under ponded water had a high FIB concentration FIB concentrations in ponded water tended to increase with increasing water temperature and to decrease with increasing water salinity

Heilman, 2000 F,

E C Trop WC FC, EC, Ent A, F Year

- long sampling stu dy ; f our sites sampled weekly in August 19 98 through June 19 99 No Shallow bay in gulf coast with frequent bacterial standard exceedances. Abstract only S ometimes high counts of fecal and Ent S ite with the highest count s had e xtensive shorebird usage near t he outfall of a wastewater treatment plant L ow bacterial counts found during drought conditions and warmer air temperature S ignificant negative correlations found between salinity and all fecal FIB A t the two sites with highest salinity, Ent exceeded EPA w ater 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 Ju ne, July 1976 No Shallow eutrophic lake in a region known fecal impacts from agriculture, wildlife, septic systems M ain sources of FIB were cattle watering sites, farms, public beaches, some flooded septic tanks, and a bird sanctuary I mpairment of water qu ality localized to shoreline locations near the suspected source of the input of bacteria FIB concentration increased after rainfall

– about 10 × increase

– however this effect lasted only 2 or 3 days FIB levels low and did not exceeded Canadian levels Hij nen et al., 2007 F,

M IF, IN, C Temp WC EC, Ent B, H 4 different locations of water sampled Yes Waters drawn from a small stagnant lake, a ditch, and a large river EC similar or more persistent than Ent in fr esh water In salt water, Ent more persistent than EC

## August 2010 A

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Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) Experiments conducted in laboratory

mesocosms D ecay 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 source s not fully described. Sources are fresh and brackish Abstract only Ent and fecal persisted longer in sediments than in the WC Ent and fecal persisted longer in the fresh water than in brackish and saline waters coliphage not detected beyon d three days

H oyer et al., 2006 F IN Trop/ Sub WC EC A 79 lakes sampled once during a 9 month study 30 lakes sampled intensively No Lakes sampled located in numerous drainages presumed to be heterogeneous Septic tank sources confirmed for some lakes Spatial variations in lakes studied less than temporal variations in EC density. Open

- water samples (taken away from litteral zone) had consistently fewer EC than littoral samples

Hyer et al., 2007 F IF Temp WC EC A During 2005 and 2006, 20 streams and springs sampled in Shenandoah National Park Most sampling occurred during low flow

co nditions during the warm months; high outdoor recreational and bacterial survivorship Few event sampling No Recreational use for 14 streams out of the 20, and 6 in control basins where minim al recreational activities occurred (very pristine) R elatively low EC concentrations during low

flow conditions N o statist ically significant increase in EC density observed in the recreational streams relative to the control streams R esults showed that rec reational activities had no significant effect on EC density After rain, EC density i ncreased by nearly a factor of 10 and the Virginia instantaneous
water

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

## August 2010 A

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Study

Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) Ishii et al., 2006b F IN Temp Cladophora attached to submerged rocks EC (STEC), Salm Shig, Campy A Samples

collected from Lake side and Ditch side; samples were collected from submerged rocks below the waterline Samples collected in July and Sept 2004 and monthly betw een July and October 2005 No Combination of rural and urban waste, including combined sewage overflows, septic field leachate, urban runoff, sludge or runoff from manure farm fields, sedimentation, and nutrients S tudy 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 sampl es R esults sho w that Cladophora is a likely secondary habitat for pathogenic bacteria in Lake Michigan

Iwamoto et al., 2005 F IN Temp WC FC Shigella sonnei H Samples

collected on 2 occasions; FC enumerated for both samples and Shigella sonnei enumerated for only one No Watershed is in a large park, presumably separated from urban fecal pollution sources The likely source of Shigella sonnei for this outbreak was an infected swimmer Shigella sonnei was detected despite no apparent sewage contamination Routi ne monitoring would not have prevented the outbreak

Jamieson, et al., 2004a F IF NA Soil, sed, WC NA

(gen

- eric) NA (generic) G,

I NA No NA This is a general modeling paper not specific to an indicator or pathogen Deviation of removal processes from first order decay is likely There is a significant data/knowledge gap related to overland transport of microorganisms at the small watershed scale Current models for settling of particle associated bacteria (PAB) are empirical; efforts should be made to develop phenomenological models

## August 2010 A

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Study

Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) Jamieson et al., 2004b F IF Temp WC EC C After initiation of in situ

mesocosm experiments, samples collected at 15 min, 1 hr, 2 hr, 4 hr, 8 hr, 20 hr and daily time intervals for a duration of 20

- 24 days, with sample collection higher during storms Yes Streams are described as ―rural streams.‖ No description is provided on land use in drainages. Inactivation estimated for EC in bed sediment was an order of magnitude less than that estimated for the water column Concentration of r e

- 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 st udy duration, samples collected 5 times per month for dry weather and at unknown frequen cy after rain events > 0.25 cm Sediment samples collected daily for at least three days after rainfall events > 0.25

cm Yes Stormwater drains from a densely urbanized

a rea. Sediment samples drawn near the stormwater outfall. Settling of particle

- associated bacteria (PAB) observed in the laboratory and inferred from filed measurements. The propensity for FIB to attach to particles varied with particle size and FIB type (F C, TC, E nt) The non

- settling fraction of FC, EC

, and Ent varied from 65 to 85% The authors suggest sediments should be sampled in addition to the water column when assessing the health risks associated with waters

Jiang et al., 2001 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 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, E nt). Limited data indicate that urban runoff is the source of adenovirus in the study waters

## August 2010 A

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Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) presumed impacted by fecal pollution. Because virus detection done by PCR, nonviable and damages viruses may have been included in estimates of virus concentration/presence Jiang et al., 200 7 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 bacteria (TC, FC, Ent); the temporal variations in viruses may be the result of temporal trends in viral shedding or ―heightened anthropogenic activities‖ during summer months FIB (TC, FC, E nt) displayed a strong seasonal pattern (high during winter storms) in Newport Bay , CA; g ross mass balance considerations indicate the high FIB loads during storms are not from sewage plants, but from non

- poi nt 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

w atersheds No Not specified Abstract only Isolates indicated contamination by people, cattle, pets, birds, horses, raccoons, and pigeons

Kay et al., 2007 F All All Soil, feces FIB

(cons

- idered

as a group) Crypto, EC O157:H7 and others G,

I, J NA No Thou gh no specific watershed was studied, work pertains to agriculture (livestock) dominated drainages Insufficient temporally

- and spatially

- resolved data are available to calibrate proposed models for indicator organism and pathogen flux from agricultural si tes Small watershed features (buffer strips, other best management practices ) can exert large influences on indicator organism and pathogen fluxes A data gap related to contribution of sediments to indicator organism fluxes is the influence of sediment cha racteristics (grain size, mineralogy, etc) on indicator fate Keeley and F IN Temp WC EC, Turbidity Crypto, A 193 samples No Drainages to sample Occurrence of Crypto and Giardia

## August 2010 A

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Study

Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) Faulkner, 2008 TC Giardia taken at 17 locations on an inland reservoir. Samples collected at frequency between monthly and 3 months ov er a 27

- month study duration. sites varied. Most drainages impacted by agricultural runoff. Some sites located in a wildlife refuge. Several sites impacted by WWTP discharge or septic systems. widespr ead; this finding is consistent with high proportion of rangeland in study area The highest Crypto concentrations obtained during calving season ; c alving season coincides with the wettest period Correlation not found between concentration of fecal indicato rs and Crypto ; authors speculate lack of correlation is a results of different fate (settling) and survival characteristics

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 concentr ations in time series (hourly time step) indicate diurnal pattern of occurrence in the surface zone and ―semi

- diurnal‖ pattern in a tidally

- influenced marsh Decay rate constant values predicted in modeling consistent with those from the literature for site s/waters with similar characteristics

Lee and Bang, 2000 F IF Temp WC NA NA NA A No microbiological analyses conducted No Urban drainages Study primarily concerned with variation of physical and chemical parameters during
storm events

Lemar

- chand and Leb aron, 2003 F IF Temp WC FC, FS Crypto,

Salm A Sampling

strategy not described No Upstream drainages of the study water are mixed forested and animal husbandry land uses; 21 WWTP outfalls located in the study watershed Daily loads of FC and FS much less variable than daily load for Salm and Crypto In analyses of WWTP influent and effluent and surface water samples, did not find a significant correlation between Crypto and FC or FS in WWTP influent, but did find a significant correlation between Crypto and FC (but not FS) in wastewater plant effluent and between Crypto and both FS and FC concentration for surface waters. Higher Crypto concentration in WWTP effluent than influent on several occasions, which was attributed to high temporal variability in Cr ypto concentration; noted

## August 2010 A

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Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) that Crypto loads depend on level of Crypto infection in communities whereas indicator loads do not Lévesque and Gauvin, 2007 F,

M U Temp WC FC, EC, E nt H NA No Study is general and nature and not related to a specific watershe d Authors suggested Canadian water quality standards of 100 CFU EC/100 mL for fresh water and 35 CFU Ent/100 mL for marine
water Lipp et al., 2001 a E,

M C Trop WC, sed FC,

Ent CP

,

c oliphage Crypto,

Giardia

, enteric viruses A Surface water

samples collecte d at 12 sites, monthly samples, study duration of 1 year; sediment samples collected quarterly No Study conducted for shellfish harvesting waters whose drainage includes impacts from residential land use and in some cases high density of on

- site disposal ( septic) systems Levels of CP in sediment up to 5 orders of magnitude greater than those observed in the water column; sediment and water column concentrations of Ent generally within an order of magnitude Bacterial and viral indicator concentrations negati vely correlated with temperature FC negatively correlated with salinity Seasonal variation of bacterial and viral indicators significant; high concentrations in both the water column and sediments observed in August and the study period was December

- Februa ry The concentrations of fecal indicators (FC, Ent, CP , and coliphages) not correlated with the occurrence of Crypto or Giardia Authors suggested that perhaps Crypto and Giardia occurrence is episodic, whereas indicators have more sources and have

sources that are more consistent Lipp et al., 2001 b E,

F C, IF Trop WC FC A W ater quality
measurements taken monthly for a 2

- year period No Drainages above sample locations either primarily agricultural or mixed agricultural

- urban Extreme El N iño winter month s are characterized by greater fecal pollution resulting from greater precipitation

Lopez et al., 200 8 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
agr icultural (poultry farming), forested, urban, and aquatic EC concentration found to be related to drainage urban land use extent Future work will allow prediction of temporal variations in water quality

López

- Pila and F IF Temp WC EC Rotavi rus G No sampling performed No Study conceptual Fecal indicator (EC) concentrations assumed to be log

- normally distributed

## August 2010 A

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Study

Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) Szewzyk

, 2000 The ratio of fecal indicators and rotavirus concentration assumed to be constant over all samples Mathes et al.

, 2007 F IF Temp WC E C Bacter

oides

, Ent marker, human urine marker D Water samples collected twice at each of 4 sites. Samples collected in October and September No Study drainages primarily covered with forest, but characterized by frequent high levels of fecal indicator b acteria Intent of study was evaluating indicators in their ability to determine source of fecal pollution

McCam

bridge and 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 res ult of the interaction of solar radiation effects and predation; one possibility is that solar radiation causes EC to become more susceptible to predation

Menon et al.

, 2003 F,

M IF, C Temp WC EC SP Salm typhim

rium B Experiments

performed over a 1

- month period; sample collection frequency not provided Yes Freshwater samples collected downstream of a large urban area Marine samples collected from a pier in a large urban area Grazing by protozooplankton was the dominant process in mortality of both types

o f fecal bacteria and for autochthonous bacteria Portion of decay attributable to processes other than grazing was well

- characterized by first

- ordered kinetics for EC Mortality rates of fecal bacteria (EC, Salmonlella typhimurium , S . faecium ) not significan tly different Molina et al.

, 2005 * F IF Temp WC, feces Ent D Monthly water and feces samples No Farms where cows have unrestricted access to
streams Abstract only Ent species observed in feces different from those observed in streams Myers et al.

, 1993 F IF Temp WC FC, EC A, C, G Unknown Yes Study area is in a National Recreation Area located in an urbanized area and downstream of a large WWTP Summer decay rates for FC and EC generally greater than winter decay rates

Noble et al.

, 2004 F,

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

specific coliphage B Experiments performed in seawater from Yes For experiments, marine and fresh waters spiked with WWTP All indicators degraded faster at 20° C than at 14° C; the ambiguous effect of temperature and differences between results of this

## August 2010 A

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Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) a bay near a bathing beach or freshwater from a creek flowing through a state park effluent, raw sewage, or urban runoff study and those in other studies is acknowledged Inoculants did not influence decay rates Overall decay rate highest f or 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 indicat e significant temporal and spatial differences may 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 flowi ng through a state park Yes For experiments, marine and fresh waters spiked with WWTP effluent, raw sewage, or urban runoff All indicators degraded faster at 20°C than at 14°C. Inoculants did not influence decay rates Overall decay rate highest for EC and lowest for Ent for all experiments EC growth observed at low solar radiation, low temperature conditions Decay rates of indicators similar in fresh and saline waters Decay rate results at variance with other rates reported in the literature and indicate si gnificant temporal and spatial differences may characterized decay among sites Obiri

- Dans o 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 re ach sample locations downstream of a WWTP outfall ; land use mainly agricultural (extensive sheep and cattle grazing) along the river reach studied In the water column, indicators did not show seasonal variations, Campy more plentiful in winter months, po ssibly due to less die

- off and high wash

- off of Campy from grazing lands during relatively rainy periods In sediments, there was no seasonal variation in Campy occurrence

Okabe and Shimazu

, 2007 F,

M IF, C Temp WC TC, FC BF B Experiments performed in fil tered and unfiltered river water and filtered and unfiltered Yes Drainages not described Decay rates of FC not strongly influenced by salinity; increasing salinity greatly increased TC decay rates; At temperature ≥ 10°C, TC and FC decay rates in unfiltered river water very low or negative (growth); B. fragilis decay greater at all water temperatures and growth curves

## August 2010 A

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Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s )
seawater appeared to have a small shoulder and very long tail Olyphant et al.

, 2003 F IF Temp WC EC A, G Samples collected once per week f or 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 kn own to cause a CSO ; p re

- CSO concentration s of EC elevated ; p ost

- CSO concentration increase d by more than 1

- log Seasonal variation in EC observed ; a plausible explanation for increased warm

- temperature EC concentration is higher soil temperature promoting ― population explosion‖ of EC in soils with subsequent transport of EC to receiving waters during relatively small rainfalls Olyphant

, 2005 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 I n an attempt to eliminate spurious correlations from analyses, authors conducted partial correlations and determined that (1) wave height tended to be the domina nt storm

- related parameter (for predicting EC concentration); that (2) turbidity turned out not to be significant when the effects of other variables accounted for ; and (3) rainfall had only one statistically significant partial correlation Paul et al.

, 1 995 F,

M, G W GW , C Trop WC,

GW Ent C P ,host

16 A Two sampling episodes (March and August) conducted, with samples drawn from observation wells and marine waters No Aquifer and coastal waters are impacted by septic systems from residential land

- use, includ ing tourist sites. Aquifer is subject to treated WWTP effluent Fecal pollution from septic drainfields, WWTP effluent in j ection and other sources apparent sources of aquifer contamination. Observation of fecal indicators in coastal waters is not necessaril y associated with discharge to marine waters from the aquifer; other possibilities are runoff or mobilization of indicators that have grown in waters or sediments

Pennington et al.

, 2001 F IF Temp WC FC, EC, TC A Sampling conducted only during summer No Sample sites widely dispersed Study intent was relating indicator occurrence to human ecosystem impacts Level s of FC, EC

, and TC found to

## August 2010 A

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Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) ( low

- flow) months for 2 years ; s ample colle c tion frequency not provided correspond to level of ecosystem human impac t as measured by physico

- chemical properties of waters and by direct observation of ecosystem in the vicinity of sample sites

Petersen et al., 2005 F IF Temp WC TC, EC, FC A WWTP effluent (36 plants, 2 samples per plant),
stormwater outfalls (52 pipes, each sampled once)

, and in

- stream samples, monthly No Large impacted watershed with multiple WWTPs, agricultural use in upper reaches and urban land use in lower researches Range of TC, FC, and EC shown in figure for WWTP effluent and stormwater outfalls In

- stream geometric mean of EC and FC shown for locations on main stem and a tributary Dry weather water quality dominated by stormwater and WWTP effluent (though authors claimed EC concentration in WWTP effluent typically 5 CFU or less) Event water qualit y dominated by non

- point

sources Relative abundance of indicators determined by regression (though non

- detect may not have been handled effectively) Petersen et al.

, 2006 F IF Temp (in study) WC FC A Data taken from multiple
sources to create an approxi mately 30

- year period of record; samples drawn at different intervals for different collecting agencies No Both study waters are located in an urban area and both are known to be highly impacted by fecal pollution Very high number of exceedances (>90%) obs erved (based on FC concentration) for all sample sites on both study waters Correlation of FC with rainfall and streamflow confounded on one study water by flood

- control retention and releases in a reservoir in the drainage FC correlation with days since l ast rain and rainfall amount was poor for both study
waters

Rees et al.

, 2005 F IF Temp WC TC, FC CP,

F+ and F

- coliphage Sorbitol

- ferment

. Bifido

- bacteria

, Rhodo

- coccus copro

- Crypto,

Giardia 6 locations, 3

-

year study duration, monthly,
storm

- ba sed and continuous sampling No Drainages for sample locations wildlife

- dominated, agriculture

- (cow pasture) dominated, or residential/commercial mixed

- use The occurrence of Crypto and Giardia in tributaries of small watersheds is not easily explained by [ other parameters]...presence or absence of standard indicator organisms

or source

- specific organisms Small rainfall events can wash Crypto oocysts in the near stream area into streams, elevating stream concentration (spatial variability); production of oocys ts by wildlife may be seasonal and may occur with a

## August 2010 A

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Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) philus different seasonality than changes in indicators [temporal variability] Rex et al.

, 2005 * M,

F E, IF Temp WC EC, E nt, FC m

- phage,

s

- phage Ad v, EV

,

rotavirus, astrovirus A Dry and wet

weather samples collected at one freshwater and one marine water site. No Insufficient detail provided Abstract only No significant correlation found between any pathogen and any indicator for both the fresh water and marine sites

Riou et al.

, 2007 M,

E C, TI Temp WC E C FRNA

- specific bacter

- iophages Astrovirus A, G Monthly samples collected during 3

- year study ; s ample times selected to include different hydrodynamic and weather conditions No The coastal area studied has a low population density but receives flow from a large river with significant upstream human and animal fecal impacts EC concentration in coastal tributaries varied significantly during rainfall events, while bacteriophage concentration generally did
not

Roser and Ashbolt

, 2004 F IF Sub WC EC, Ent C P

24

- ethylcopr ostanol, others not specified Crypto,

Campy, others not specified A,

G Intensive sampling conducted at multiple sites for 2

- 6 rainfall
events No Sample sites had one of three drainage types : fully

- protected; light grazing and peri

- urban; and d airy urban with known faulty onsite septic systems Increases in EC and E nt d ensities, but not Crypto concentration, during rain events in watersheds not suspected to be impacted by human fecal pollution High variability fo r all indicators and pathogens obs erved, even when only samples taken during base flow conditions are compared Loading should be considered when assessing risk

— reservoirs and drinking water storage are loaded with indicators and pathogens during precipitation events Ryu and Abbasza

- degan

, 2008 F IF Sub WC EC, TC, FC Male

specific coliphage somatic coliphage Crypto,

Giardia A 192 water

samples from 5 sites analyzed ;

m onthly collection over 5

- year study period No Sample sites correspond to three drainages: one primarily range land, one prima rily 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 se asons For the entire data set, Giardia concentrations correlated with FC, but Crypto concentration did not correlate with FC or other indicator organism concentrations Giardia concentration varied significantly spatially; Crypto concentration did not

## August 2010 A

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Study

Water Type Setting Climate

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Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) Sant o Domingo

, 2008 * U U Trop WC EC, Ent E Not specified No Not specified Abstract only Study proposes development of molecular techniques for better estimate of population densities inclusive of damaged or nonculturable organisms. Santoro and Boehm

, 2007 M C Sub WC TC, E nt, EC Bacter

oides molecular marker (HF marker) A Nightly sampling at multiple locations along a 9 km stretch of b each for 1 month in each of 2 summers ;

s ampling sched u le intended to
expose variation due to tides No Study area in a highly urbanized region with known human and non

- human pollution (particularly seabirds)

sources Occurrence of HF (human

- specific) marker not correlated with fecal indicator (TC, E nt, EC) concentration for individual samples, but correlated when data considered by
year Authors consider ed their estimate of the frequency of exceedance conservative, since samples taken at night Ent abundance significantly greater in low tide samples for the two sites with the most exceedances during the study

Schaub

, 2004 N

A NA NA NA G, I NA No NA Harmonization of risk approaches is encouraged to allow more effective utilization of risk study results Schets et al.

, 2008 F,

E IF, IN Temp WC FC, E nt, FS, EC F

- specific

bacterio

- phage, somatic coliphage Campy,

EC O157, Crypto, Giard ia

, 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 L evels of fecal indicators in the canal with houseboats and the canal without houseboats almost equal and did not suggest that houseboats contributed to the fecal contamination of canals to a larger
extent than other sources did; Crypto and especially Giardia numbers much higher canal with houseboats than in the other canal, suggesting that wastewater from the houseboats may have been a source of those pr otozoan pathogens Indicator counts more closely associated with rainfall in canals than in recreational lakes Servais et al.

, 2007 F IF Temp WC FC, E nt, EC A Between 1

- 6 sampling campaigns conducted on a large river and numerous tributaries of varying order Yes Drainage is ―highly anthropogenically impacted‖ from industrial, WWTP and intensive agriculture

sources No major difference in m ortality associated with small v s. large rivers Mortality of EC dominated by grazing when observed under laboratory conditions In situ decay measurements indicated slightly higher decay rate than observed in laboratory experiments

## August 2010 A

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Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) Shehane et al.

, 2002 * U U Trop WC FC, E nt C P,

S omatic coliphage A Seven sites sampled tw ice each per sampling event during a 2

- year study ;

s ampling conducted during spring,

summer , a n d winter No Not fully described ; k nown sources of fecal pollution in the drainage septic system s and leaking sewer systems Abstract only Impacts of poorly maintained septic systems and leaking sewer systems documented During dry seasonal, the majority of indicators of animal origin

Shehane et al.

, 2003 * U U Trop WC FC, E nt C P

,

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

- year study ;

s ampling conducted during spring,

summer a n d winter No Not fully described ; k nown sources of fecal pollution in the drainage septic systems and leaking sewer systems Abstract only I mpacts of poorly maintained septic systems and leaking sewer systems documented During dry seasonal, the majority of indicators of animal origin

Shellenbar ger et al.

, 2008 TI TI,

IN Sub WC FC, E nt, TC Salm A, G 8 sampling events conducted : 4 events weekl y during the summer and 4 events weekly during the winter No Drainage is in an National Wildlife Refuge with suspected impacts from waterfowl and storm water
conveyances Tidally

- influenced ponds can act as either sources or sinks of indictor organisms, de pending on loading rate from all sources and hydraulics/hydrology Lower occurrence of indicators occurred during the period of lower bird density ; d uring this period the ponds studied not hydrologically connected to sloughs where high indicator organism co ncentrations observed Sherer et al.

, 1992 F IF Temp WC, sed FC,

FS A Sediment and water samples taken from two sites and experiments conducted in the laboratory Yes Land use adjacent to streams studied is primarily rangeland and is expected impacted by animal fecal pollution FC and FS decay much slower in the presence of sediments than in water alone Decay of both FC and FS in water with sediment is characterized by a pronounced shoulder followed by apparent first

- order decay ; t he shoulder may correspond to the time period during which nutrient supplies have not been exhausted FC die

- off in a sandy loam significantly less than in a clay loam (fine sed); FS die in the two sediments not significantly different

## August 2010 A

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Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) The authors believe d 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 rela tively low year

- round residential population and as many as 25 × the resident population during summer months Viable but nonculturable (VBNC) bacteria are present in many samples with no culturable bacteria Plankton is much more plentiful in both marine and fresh waters during summer months When plankton are plentiful, the majority of E nt present in samples is associated with plankton ; w hen plankton are not plentiful, the majority of E nt are free swimming Association of E nt with plankton appears enhance surv ival of E nt Smith et al., 2008 F IF Temp WC, Sed T C 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, rive r stage, temperature

, and rainfall Results demonstrate the contribution of sediment bacteria to water column community Results show that pre

- storm sediment bacteria concentration can be a predictor of post

- storm water quality violations

Soller et al.

, 20 06 E WC Sub WC EC, Ent, FC, TC G, H 26,625 samples analyzed for TC, EC, Ent

, and FC at 35 sites ; d etails of sampling design not provided N Study conducted downstream of large urbanized area in waters known to be impacted by human fecal pollution Though d ry season FC frequently exceed water quality objectives, e xceedances 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 standar ds occurred at sites with recreational use during times of the year when recreational activity was relatively low Limiting controllable pollution is not predicted to have a significant impact on overall water quality or risk of illness due to recreational activity Soonthorn

- nonda et al.

, 2008 F IF Temp WC FC, EC A, G Sampling of
storm water discharges N All drainages primarily residential ; o ne drainage included a Authors claim ed that the proposed EC washoff model fit data well; the fit appears excellent for most storms but very poor for

## August 2010 A

- 33

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) conducted for 3 storms at 4 drains and at 30

- minute intervals for up to 7 samples major high way one storm in two drainages Washoff model validity is suggested for portions of rainfall/washoff events near the hydrograph pea k. A transport coefficient of 6.12 cm - 1 is suggested for wash

- off of EC from mixed residential land use drainages Sorensen et al.

, 1989 F IF Temp WC FC, TC C P,

FS i A Sampling mostly conducted on a single occasion on each of two
streams at

numerous locat ions N Upland streams, not expected to be impacted by human sewage but with livestock/non

- point

sources C P concentrations lower than those of fecal indicators, but a better indicator of fecal pollution, since non

- point livestock associated indicators suspe cted to be entering the stream ; i ndicators increased with distance downstream from WWTP discharge whereas C P decreased Oxbow 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

- derived E C Tiefentha

- ler et al.

, 2008 F IF Sub WC EC, Ent, TC Bateriode

s thetaiota

- omicron A 15 sites sampled weekly during dry season (no rain for 24 hr, flow < 20% above baseflow) over a 1

- year period N All drainages selected based on status as unimpaired and low level of developments and impacts Concentrations of all three indicators under baseflow conditions higher during summer month s Correlation of TC with temp is stronger than those of EC and Ent Based on absence of alternative human fecal indicator, sources of EC, E nt

, 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 C P Crypto, Giardia

, Salm A 45 samples

collected at each of 8 sample sites in an estuary

over a 9

- year period ; b etween 4

- 7 samples collected from 6 locations on tributaries No Upper reaches of the study waters in a large

u rbanized area ; th e study water (estuarine portions of the Seine) end at the Bay of Seine ; i ntensive farming with livestock prevalent in middle reaches Upstream activities impair estuary water quality and pose recreational use risk Relationship between indi cator concentration and Salm concentration varied from site

- to

- site; in an urbanized area there was no relationship At the mouth of the estuary

, Salm correlated with Ent

## August 2010 A

- 34

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) Traister and Anisfeld

, 2006 F IF Temp WC EC A Sampling conducted at seasonal,
stor m

- related

. and diurnal time scales ;

s ampling conducted between March and November at 11 sites in the drainage area No Drainage for sample locations mainly forested ; a g land use accounted for about 10% of drainage for all study sites EC positively correlate d with drainage residential land cover and negatively correlated with forest cove r Greater diurnal fluctuations observed at less shaded, slower flowing sites Storm events have a strong effect on EC concentration though storm influences vary between storms The relation between EC concentration and temperature differed according to the time scale of sampling : EC correlated with temp for seasonal time scale data but inversely correlated with temp for storm

- scale samples Tranter et al.

, 1996 F IF Temp WC FC A Weekly sampling for a 1

- year period No Upland catchment, agricultural land use FC concentration s highly variable at all sites; summer concentrations general higher, possibly due to slurry application A g activities degraded water quality, though the degre e of development of the drainage seemed to play a role in the degree to which ag impacts observed in the streams Vidon et al.

, 2008 F IF Temp WC EC A Samples collected for 2 years either bimonthly, monthly

, or

e very 2 weeks No Watershed for two study
st reams mixed agricultural (60%), low density residential (10%) and forested, herbaceous, roads and open water For all flow conditions, EC concentration correlate d best with 7

- day antecedent discharge (better than precipitation or

same

- day discharge) For bas e flow conditions, E C concentration is not correlated to 7

- day discharge but is correlated with turbidity and current day discharge Vital et al.

, 2008 F IF,

IN Temp WC E C O157:H7 B Growth observed

at approximately 5 minute intervals for 70 hours Yes Not provided E C O157:H7 shown to grow in sterilized freshwater under low carbon conditions, with the yield associated with available carbon Growth rate positively correlated with temperature (max specific growth rate around 30 ° C) Voytek et al.

, 2005 F IF Te mp WC FC, EC, Ent HP F Yukon River (Alaska ), 2 Illinois Rivers

, and 1 East

- coast river sampled for
one year No Yukon River drainage is largely undeveloped but has many fecal inputs from poorly maintain septic systems ; Illi nois drainages primarily H P and Helicobacter spp. often found concurrently with indicator bacteria, but the presence of indicator bacteria not predictive of the presence of HP Indicator or g anism concentrations lowest in the undeveloped watershed

## August 2010 A

- 35

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) (sample frequency not specified ) agricultural ; while East coast drainage in a heavily developed area Wade et al.

, 2008 F C Temp WC Ent Samples collected at 8 AM, 11 AM and 3 PM ; a t otal 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 E nt as determined by culture techniques Relatively low fluctuation observed in Ent concentration during the day when determined by QPCR

Waldron et al.

, 2002 F IF Temp WC FC O Sampling strategy not specified in detail No Drainages for all sample sites described as heavily developed To allow comparison between drainages, FC loads were expressed a s yield (load per drainage area) The highest FC loads associated with an industria l 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

s ampling : May

- O ctober, 2003 and 2004 No Expected to be highly

- impacted by agricultural fecal pollution Ruminant specific Bacteroidales predicted EC O157:H7 occurrence Detection of ruminant

- specific Bacteroiodales increased odds of detecting Salm Detection o f human

- specific Bacteroidales increased odds of detecting Campylobacter
spp. Whitman et al.

, 2008 F IN Temp WC EC Somatic and FRNA coliphage A Pre

- pond construction: samples collected twice monthly for 8 months ; d uring pond construction

, samples collect ed at unknown frequency Post

- pond construction : samples collec ted 3 times per week for 1 month Yes

(qu alita tive) The study water drains

an isolated area in a park and is relatively unimpacted by human and agricultural fecal contamination ; p opulation diversity of E C indicate d human septic sources upslope in catchment Solar radiation reduction in E C estimated at 26% (74% attributable to non

- solar factors) E C removal became more predic table with pond age Pond was less effective at reducing EC during the winter months than during summer months FRNA coliphage rarely occurred under base flow conditions but was frequently seen in flooding and snowmelt, though E C was plentiful in base flow c onditions

## August 2010 A

- 36

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) and before and after 1 rainfal l event and before and after 1 snowmelt event Wiede

- mann et al.

, 2006 F IN,

IF Temp WC EC, E nt C P

,

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 feca l contamination were sewage (treated and untreated), agricultural runoff and waterfowl. Authors stated that the u se of NOAELs for determining acceptable indicator concentration is more robust than use of attributable risk

Wijesing

- he et al.

, 2005 F IF Tem p 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 ;

w eekly sampling conducted July

- F eb ruary No One site in unimpacted headwaters (high order stream?) ; ot her sites are near urban areas and presumed impacted Low variability observed between samples collected at 5

- minute in tervals High variability observed month to month for low flow (baseflow) conditions Suspected sources for FC during baseflow conditions were leaky sewers/septic systems, wildlife, and FC in sediments Although overall levels of FC at the unimpacted site wer e 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 regio ns 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 min ute , 10 min utes

, hourly

, and daily intervals No Not provided (abstract only) Abstract only Coefficient of variation ranged from 0.7 for samples taken seconds from each other to 2.2 for samples taken daily Authors state that single samples cannot adequately characterize water quality Yamahara et al.

, 2007 M C S ub So il, Sed Ent,

EC Bacte

-

roides Salm A Sands, sediments

, and waters No Impacted coastal beaches along the

s outhern California Mass balance of Ent based on water and soil samples during tidal period indicates that Ent persistent or growth is greatest in soils

## August 2010 A

- 37

Study

Water Type Setting Climate

Media

Indicator Organism(s) Alternative Indicators

Pathogens

Study Type(s)

Frequency and

Period of Observations

Decay Data?

Watershed Description Note ( s ) collected from 55 beaches ;

s ampling at 1 beach at 20 min ute intervals for 24 hour s duration coast ; s uspected fecal contamination sour ces were storm drains and agriculture sources ;

s oils (sands) were also determined to be non

point sources and that Ent are readily transported into the water column E nt are ubiquitous in sands of the beaches studied High spatial variability in Ent concentration noted at all beaches E C observed in sands much less often than Ent

## August 2010 A

- 38 Appendix B

Literature Search Strategy and Resul ts

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 DIAL OG searches, individual authors used free search engines on the internet (e.g., PubMed) to find articles pertaining to specific information needed. It is important to note that the titles of literature cited in specific reports, books, review articles, an d conference proceedings were also evaluated for relevance and constituted an important component of the overall literature search.

Initial Literature Search Strategy Conducted by Professional Librarian

Selection of DIALOG data base files used for this s earch:
Biosis
NTIS Enviroline
Embase
WasteInfo Biological & Agricultural Index
Pascal
MedLine
Waternet
FEDRIP Engineering Village and ISI Web of Science

Descriptions of these databases are available at http://library.dialog.com/bluesheets/

.

Retrieve : Titles and year, 1985

- present (2002

- present is more crucial) Additional information : Interested in international and domestic journals and government reports Language : English only Primary s earch t erms i n order of importance to be searched as noted below : 1. Fecal indicator* 2. Fecal contamination 3. Fecal pollution

Search strategies (SETS) used for this search:

SEARCH SET 1 Primary search term [ bolded terms are of increased importance] AND

Applicability
Fate
Tr ansport (fate and transport) TMDL (total maximum daily load)

## August 2010 A

- 39 Fecal source tracking MST (microbial source tracking) (Microbial) water quality Behavior (fate and behavior) Microbial ecology Primary contact Secondary contact Persistence (microbial ecology and persistence)

o (Fecal) pathogen
Performance

o Compliance

o Monitoring (compliance monitoring) Source

o Indigenous

o Environmental*

o Non

- fecal (nonfecal, non fecal)

o Extra(

- )enteric

o Nonhuman (non human, non

- human)

o Zoon* (zoonotic, zoonoses)
Inland (water*)

o Flowing

o Lak e

o Pond

o Stream

o Reservoir

o Creek

o River

o Lentic

o Lotic

o Tributary
Water column Recreational water Ambient water Fresh water* (freshwater)
Coastal
Marine water*
Beach

SEARCH SET 2 Primary search term* AND

Decay (rate) Inactivation pH Hydrology Alkalinity

## August 2010 A

- 40 Temper ature Re(

- )suspension Re(

- )growth Light (duration, intensity)
Rainfall Precipitation
Storm Salinity
Runoff Suspended solids Turbidity
Nutrients Organics Organic foams Biological community in water column Water depth
Stratification Depth Mixing (wind, waves , etc.) Regrowth Presence of aquatic plants

– epiphytic bacterial communities on plants
Biofilms
Predation

SEARCH SET 3 Primary search terms AND

Fecal pathogen* (Environmental) fecal coliform* (Environmental) Escherichia coli (Environmental E. coli (Envir onmental) enterococc* (enterococcus, enterococci) Fecal streptococc* Intestinal enterococc* (Environmantal) f

ecal coliform *
Total coliform* Alternate (alternative) fecal indicator* Clostridium perfringens
sulfite

- reducing Clostridia Bifidobacterium
Rhodoc occus coprophilus
Bacteroid * Human enteric virus * Somatic coliphage *
F

- specific coliphage *

## August 2010 A

- 41 Bacteroide * phage Sanitary plastics grease Fecal steroid * (sterols, stanols, stanones)
Caffeine Detergent *

Partial list of a uthors of interest : R. Fujioka M. Byapp anahalli S. Ishii K. Isobe J.B. Rose H. Solo

- Gabriele G.A. Toranzos J. Tiedje T.C. Hazen R.L. Calderon M.J. Sadowsky F. Genthner E. Akazawa C

. Gerba M. Sobsey T. Slifko M. Yates C. Moe J.A. Jay R.L. Whitman

Summary of Literature Search Results

This proce ss resulted in a total order of 292 citations of which a total of 152 ( 52 % ) were obtained and reviewed for their suitability for use in the original draft report. There are many more papers in the peer

- reviewed literature and this by no means represents a ll of them. Of the articles reviewed, 211 c itations were included in the draft report.

Supplemental Literature Search Activities

In addition to the literature search conducted by the professional librarian, specific reports were obtained and the titles of the references cited in the reports were reviewed for relevance.

NRC . 2004. Indicators for W aterborne P athogens. National Academies Press. Washington, DC.
USEPA

, 2007 b . Report of the Experts Scientific Workshop o n Critical Research Needs f or t he Development o f New o r Revised Recreational Water Quality Criteria. EPA 823

- R

- 07

- 006.

## August 2010 A

- 42

References cited by the Natural Resources Defense Council reviewers of the EPA Critical Path Science Plan.

Lastly, Clancy Environmental Consultants, Inc., Soller Envir onmental, LLC, and EPA’s Health and Ecological Criteria Division all maintain extensive literature bibliographies and reference lists from previously completed projects. All of those in

- house resources were also sources of literature used in this report.