Water Quality Topics: Pathogens

Background

Waterborne pathogens, including bacteria, viruses, and protozoa, are a direct threat to human health. Health-care costs attributed to some of the leading causes of waterborne diseases in the United States are estimated at more than $1 billion annually. This includes more than 40,000 related hospitalizations (Collier et al. 2012). The majority of commonly occurring waterborne pathogens in the United States are linked to fecal sources on land (e.g., Escherichia coli [E. coli] O157:H7 and Cryptosporidium), while others occur naturally in waterbodies (e.g., Naegleria fowleri and Vibrio species in coastal systems). The fate and transport of waterborne pathogens, into, and within waterbodies is influenced by factors that include precipitation and runoff; the type and location of sources on land; and the survival characteristics of individual organisms. Organism survival in environmental matrices such as soil, water, and fecal waste is influenced by moisture, nutrient availability, temperature and sunlight. Climate change will have direct and cascading effects on these and other factors (e.g., on sources on land), leading potentially to increased water quality impairment and the risk of human exposure (Coffey et al. 2014; Sterk et al. 2013).

Commonly Occurring Waterborne Pathogens

The origin of most common waterborne pathogens in the United States can be traced to the fecal wastes of animals and humans (see Table Path-1) (USEPA 2001, 2013; Hilborn et al. 2013; Hlavsa et al. 2014). Other pathogenic microorganisms, such as Legionella, Naegleria fowleri, Vibrio spp., and Pfiesteria, occur naturally in waters and can multiply in response to environmental changes such as increased water temperature (Legionella) or excess nutrients (Pfiesteria) (ASM 1998). More than 100 different types of pathogens can be found in contaminated water (ASM 1998).

Waterborne pathogens spread to humans through ingestion of contaminated drinking water, exposure to contaminated water from recreational activities like swimming, or indirectly through contaminated food (Rose et al. 2001; Charron et al. 2004). Outbreaks of waterborne illness are most prevalent in economically disadvantaged communities where water supplies and sanitation are often inadequate. Human exposure can cause gastrointestinal, respiratory, eye, ear, nose, and throat irritation; skin diseases; impairment of cells of the digestive tract and organs; and life-threatening infections in people with depressed immune systems (see Table Path-1) (USEPA 2001).

• Table Path-1. Waterborne pathogens sourced to fecal waste and their associated diseases

Many waterborne pathogens are difficult to identify and isolate. As a result, scientists and public health officials typically monitor nonpathogenic fecal indicator bacteria (FIB) (e.g., fecal coliform, E. coli, and fecal streptococci and enterococci), which are currently a leading cause of stream/river water quality impairment and coastal shoreline impairment in the United States (USEPA 2015; Pandey et al. 2014). FIB are more easily detected and point to the possible presence of pathogens associated with fecal waste (USEPA 2001). FIB are not, however, considered to be effective as an indicator of enteric viruses and protozoa from fecal waste or naturally occurring waterborne pathogens (Fujioka et al. 2015). State and federal recreational water quality standards commonly include criteria for three FIB: E. coli, enterococci, and fecal coliform bacteria (USEPA 1986, 2001, 2012).

Drivers of Waterborne Pathogens

The following is a review of major climatic, hydrologic, and other factors that influence the occurrence of pathogenic organisms in U.S. waterbodies.

Introduction

The pathways between waterborne pathogens, their sources, and waterbodies is dependent on interactions between climate, hydrology, and land use (see Figure Path-1). Climate change can affect waterborne pathogens through changes in precipitation and runoff, which drive the transport of fecal waste (which may contain pathogenic organisms) from upland sources to waterbodies, as well as in sunlight, air temperature, moisture conditions, salinity, and other factors affecting survival in the natural environment (USEPA 2001). Scientific evidence has linked the occurrence of many waterborne disease outbreaks to climate events (see Figure Path-2) (Galway et al. 2015; Altizer et al. 2013; WHO 2003; Rose et al. 2000).

• Figure Path-1. Conceptual model of climate change effects on waterborne pathogens

• Figure Path-2. Accounts of extreme weather events and global waterborne disease outbreaks from 1910 to 2010

Changes in human land use and management also can affect the fate and transport of waterborne pathogens in U.S. waterbodies. Surface water and groundwater are susceptible to fecal contamination (which may contain pathogenic organisms) from agricultural runoff, sewage, and domesticated animals (Coffey et al. 2007, 2010a, 2010b, 2010c, 2014; Cho et al. 2010). Fecal waste can be discharged directly into waterbodies as point sources or transported to waterbodies in runoff from nonpoint sources (NPSs) or subsurface water flow (Schijven and Husman 2005; Arnone and Walling 2007; Patz et al. 2008; Beaudeau et al. 2011; Coffey et al. 2014). Major point source discharges originate from wastewater treatment plants (WWTPs) and aging/failing infrastructure, sanitary sewer overflows (SSOs) and combined sewer overflows (CSOs). NPSs of fecal contamination include septic tank leachate, runoff from land, urban litter, contaminated refuse, domestic pet and wildlife excrement (Table Path-2) (USEPA 2001; Benham et al. 2006).

• Table Path-2. Common bacteria sources considered in Total Maximum Daily Load studies

Solar Radiation and Air Temperature

The persistence of pathogens in the environment depends on the organism and environmental conditions in upland sources (e.g., soils, manure) and waterbodies. Temperature and solar radiation are primary climate drivers that affect pathogen survival. Cooler temperatures generally enable longer survival times for many common waterborne pathogens (USEPA 2013). The effect of temperature on waterborne pathogens can differ, however, depending on the species/strain of organism (Hofstra 2011; Vermeulen and Hofstra 2014; Herrador et al. 2015). For example, some naturally occurring waterborne pathogens such as Naegleria fowleri and Vibrio spp in coastal systems survive longer in warmer water than in cool or cold water. Sunlight directly affects the survival of pathogens that are vulnerable to ultraviolet radiation and desiccation (Tyrrel and Quinton 2003). Exposure of organisms to sunlight has been shown to contribute to decreased survival (USEPA 2013).

In manure and soils, bacterial pathogens such as Salmonella and pathogenic E. coli can survive—or even grow—for several months when environmental conditions are favorable (i.e., low temperatures, protection from sunlight, good moisture level, and availability of nutrients). Survival rates typically decrease at temperatures above certain thresholds (Rogers and Haines 2005; USEPA 2001). This decrease varies by organism, but survival in manure has been shown to drop markedly at temperatures exceeding 20–30 degrees Celsius (^oC) compared with survival at cooler temperatures in the range of 1–9 ^oC (Rogers and Haines 2005). Viruses can remain infectious in the environment even after freezing (Ziemer et al. 2010), and Cryptosporidium oocysts have been shown to survive freezing in manure and soil for up to 1 year (Rogers and Haines 2005).

Solar radiation and air temperature have a direct effect on water temperature (Hannah and Garner 2015), which can strongly influence growth and survival rates of bacteria in waterbodies (Mancini 1978; Noble et al. 2004; Rhodes and Kator 1988). Cooler water temperatures can increase survival or growth for many common pathogens sourced to fecal waste (e.g., pathogenic E. coli) (Uejio et al. 2014), while warmer water can allow some naturally occurring waterborne pathogens such as Naegleria fowleri to grow faster or survive longer (Freeman et al. 2009; Martinez-Urtaza et al. 2010; Hunter 2003). Cho et al. (2016) reported that the growth rate of FIB was higher at temperatures ranging from 25 to 30 ^oC, but sharply decreased at temperatures above that range. In some eastern U.S. waterbodies in Massachusetts, Pennsylvania, and North Carolina, FIB levels were relatively higher in summer and lower in winter due to seasonal differences in temperature that affect survival in soil and in water (Cho et al. 2016). E. coli O157:H7 can survive longer in waterbodies at lower temperatures and up to two or three times longer in river and lake sediments at the same temperatures (USEPA 2009a). Survival times for protozoans (e.g., Giardia and Cryptosporidium) can range from months to more than 1 year in cool water (i.e., 5 ^oC or less) (Ziemer et al. 2010). At warmer water temperatures, survival time typically decreases. For example, Giardia cysts survive less than 14 days at 25 ^oC but can survive up to 77 days at 4–8 ^oC (Ziemer et al. 2010). Viruses survive longer in waters at lower temperatures, but survival varies depending on the strain (USEPA 2009a). Increased water temperatures also can promote the expansion of microorganisms, vectors, and intermediary hosts (Harrus and Baneth 2005). For example, naturally occurring Naegleria fowleri and Vibrio spp. favor warmer waterbodies (Twilley et al. 2001; Haley et al. 2009; Obeysekera et al. 2011; Melillo et al. 2014).

Air temperature and solar radiation also affect microorganism survival through effects on soil moisture and runoff. Evapotranspiration (ET) is strongly influenced by changes in air temperature and solar energy as well as other factors including wind, humidity, and moisture availability at the land surface. ET affects soil moisture content, which can influence pathogen survival on land. Increased moisture generally favors pathogen survival (Rogers and Haines 2005). ET also affects surface runoff and thus the mobilization and transport of fecal waste—some of which can contain pathogens—from upland sources to waterbodies (Mueller et al. 2011; Melillo et al. 2014).

Precipitation

Precipitation and runoff transport fecal waste from upland sources to waterbodies and usually correlate positively with FIB levels in waterbodies (Curriero et al. 2001; Kistemann et al. 2002; Schijven and Husman 2005; Nichols et al. 2009; Kratt et al. 2010; Hofstra 2011; Funari et al. 2012; Cann et al. 2013; Herrador et al. 2015; Tryland et al. 2011; Vermeulen and Hofstra 2014). Outbreaks of cryptosporidiosis, giardiasis, leptospirosis, and other infections also have been shown to be associated with heavy rainfall and storm events (WHO 2003). For example, Cann et al. (2013) found that heavy rainfall and flooding events between 1910 and 2010 often preceded waterborne disease outbreaks (Figure Path-3). Common transport pathways for fecal waste during heavy rainfall include (1) SSO and CSO events, which can result in raw sewage discharges and sewer overflows at collection systems and WWTPs (Gibson et al. 1998; Patz et al. 2008; Cann et al. 2013); (2) stormwater runoff, which carries particulate matter and associated fecal waste (Kistemann et al. 2002; Kratt et al. 2010; Coffey et al. 2014); and (3) remobilization and redistribution of contaminated sediments, which often contain pathogenic organisms (Cho et al. 2010; Wilkes et al. 2011; Coffey et al. 2014).

The timing of snowmelt and heavy spring rainfall events also have been linked to a number of waterborne disease outbreaks. For example, severe winter storms and other combined factors were associated with the largest reported cryptosporidiosis outbreak in the United States, which occurred in Milwaukee in 1993 (MacKenzie et al. 1994). Charron et al. (2004) and St. Laurent and Mazumder (2014) also have found links between disease outbreaks, timing of snowmelt, and the annual snow-to-precipitation ratio at locations in Canada.

Direct effects of precipitation-driven changes in runoff and streamflow include alteration of pathogen loads and transport downstream. Higher streamflow typically corresponds to greater fecal loading in runoff from NPSs (Hofstra 2011; Coffey et al. 2014). Streamflow also affects transport distance, as higher flow velocities can transport pathogens longer distances and potentially affect downstream communities. The survival of pathogens also is influenced by the time spent in a waterbody, which is a function of flow rate. Schijven and Husman (2005) found reduced survival for enteric pathogens with residence times in waterbodies of more than 1 month. Residence times of up to 10 days did not affect survival. Enteric viruses and protozoa, however, can be relatively stable in the water column over large distances (USEPA 2009a; Ziemer et al. 2010).

Extended dry periods between precipitation events reduce streamflow volume and sometimes can increase density of pathogens in the water column (Senhorst and Zwolsman 2005; Johnson et al. 2009; Hofstra 2011; Cann et al. 2013; Coffey et al. 2014). For example, reduced streamflow volumes often are associated with increased FIB levels downstream of point source discharges (Senhorst and Zwolsman 2005; Johnson et al. 2009; Hofstra 2011; Cann et al. 2013; Coffey et al. 2014). This is important as recreational WQS are concentration based. In several locations, periods of dry weather followed by heavy rainfall events also have preceded large outbreaks of waterborne disease (TDOH 1999; Patz et al. 2000; Funari et al. 2012). Preceding such outbreaks, extended dry periods can allow fecal waste to accumulate on land (e.g., beaches, pastures, forestry) and then be flushed by precipitation to waterbodies (Stewart et al. 2013; Funari et al. 2012).

Climate Variability: Decadal Oscillations

Decadal or multidecadal oscillations are cyclic anomalies over different portions of the ocean that affect sea surface temperatures and atmospheric moisture content. These cyclic changes occur over different periods and can alter regional and global climate and weather because they affect sea surface temperatures and atmospheric moisture content. The most well-known in North America is the El Niño Southern Oscillation (ENSO), which is a 3-6 year cycle driven by changes in the strength of the Pacific trade winds that causes alternate cooling and warming of the Pacific Ocean and affect air temperatures and precipitation predominantly in the western and southern United States. Other periodic oscillations affecting the U.S. climate include the Atlantic Multi Decadal Oscillation (AMO), the North Atlantic Oscillation (NAO)/Arctic Oscillation (AO), and the Pacific Decadal Oscillation (PDO). Each of these oscillations can influence temperatures and precipitation over large portions of the United States. The AMO, for example, has been linked to droughts in the Midwest and Southwest, including the great Dust Bowl of the 1930s, as well as rainfall patterns in the Pacific Northwest and Florida (NOAA 2017). The PDO occurs on 20–30-year cycles and, in the United States, predominantly affects temperatures and precipitation in Alaska, the Pacific Northwest, the Southwest, and Mexico. Globally, natural variations can be as large as human-induced climate change variations over timescales of up to a few decades. Changes in climate at the global scale observed over the past 50 years, however, are more significant than can be attributed to natural variability (Walsh et al. 2014).

• Figure Path-3. Linkages between ENSO and Disease

These natural cyclic anomalies can affect waterborne disease outbreaks by causing extreme weather events such as droughts and floods (Patz 2001; WHO 2003). Figure Path-3 illustrates how ENSO events can cause physical effects such as droughts and floods (blue circle). Where these overlap and interact with suitable ecological and socioeconomic conditions (within dotted lines), they can cause disease outbreaks (dark shaded area) (WHO 2003). In the Chesapeake Bay, links have been suggested between atmospheric patterns (that influence both extratropical and tropical storm tracks) and years when very high fecal coliform levels have occurred (Leight et al. 2016). Regional precipitation also was found to be closely linked with the AMO and the Pacific / North American Pattern (Leight et al. 2016). A number of studies also have linked the ENSO and increases in sea-surface temperature to large-scale cholera outbreaks (e.g., in South Asia and Peru), which are caused by the pathogenic bacteria Vibrio cholerae (Pascual et al. 2000; Speelmon et al. 2000).

Land Use, Water Management and Other Drivers

Land Use Change

Agricultural and urban land use can have local, interactive effects with climate that affect the transport of pathogenic organisms to waterbodies. Increased impervious cover associated with urban development reduces water infiltration and increases surface runoff during storm events. Urban runoff often contains fecal waste that can contain pathogens and other contaminants and has been linked to adverse public health effects (Bannerman et al. 1993; Gaffield et al. 2003; Patz et al. 2008). Beaches used for human recreation often are located near urbanized areas and can be highly susceptible to fecal contamination from stormwater runoff (Strauch et al. 2014; Dwight et al. 2002; Whitman and Nevers 2003; Scopel et al. 2006; Yamahara et al. 2007; Patz et al. 2008). For example, impervious cover in southeastern North Carolina coastal watersheds was found to cause 95 percent of the changes in average estuarine FIB abundance (Mallin et al. 2007). Fisher and Katz (1988) suggest that more than 60 percent of the annual contaminant load is transported during storm events in urban watersheds.

In agricultural areas, manure (from animal waste) applied as fertilizer can be a major contributor to microbial water quality impairment (Crowther et al. 2002; Patz et al. 2008). Direct deposition of livestock manure to waterbodies is a major source of pathogenic E. coli and Cryptosporidium, since fresh fecal waste is introduced to the system without any natural environmental filters or influences (e.g., temperature, sunlight, filtering by soils or vegetation) (Crowther et al. 2003; Baffaut and Benson 2003). Direct deposits are typically greatest during the warm summer months when livestock drink more and seek out waterbodies to reduce thermal stress (Nardone et al. 2010; Soller et al. 2010). Confined animal feed operations—which share many of the traits of an NPS but are regulated as a point source under the National Pollutant Discharge Elimination System program—are another source of fecal contamination to adjacent waterbodies. Increasing intensity of agricultural production is likely to increase the delivery of fecal waste to waterbodies (Boxall et al. 2009; Zeleznik et al. 2011; Coffey et al. 2014).

Contaminated irrigation water can expose fruit and vegetables to waterborne pathogens (Steele and Odumeru 2004), and has been reported as a cause for some of the large fresh produce outbreaks that have occurred in the United States (CFERT 2008; Mandrell 2011; Pachepsky et al. 2011).

Water Management

In developed countries like the United States, the majority of waterborne illnesses result from inadequate source water protection, water treatment, and other infrastructure failings (e.g., distribution) (Cann et al. 2013). Conventional drinking water treatment processes used in public water systems are highly effective at removing waterborne pathogens.

Conversely, improper treatment and disposal of wastewaters present a risk to water quality and public health during recreation and other activities (e.g., water reuse) (ASM 1998). Discharges from WWTPs, SSOs, and CSOs are major point sources of fecal contamination (USEPA 2001; McLellan et al. 2007). CSOs empty directly into waterbodies during high-intensity runoff events. Stormwater discharges carrying waterborne pathogens and other pollutants can contaminate downstream drinking water sources, beaches, fish, and shellfish (Gibson et al. 1998; Charron et al. 2004; Patz et al. 2008). Studies in the Milwaukee estuary (Lake Michigan) have shown significantly higher E. coli levels following CSO events (McLellan et al. 2007; Patz et al. 2008). Waterbody contamination from CSOs is expected to become a greater problem in the future as urban areas expand and storm events increase in frequency and magnitude (Patz et al. 2008). In addition, flooding often can lead to inundation of low-lying infrastructure, including drinking water and sewage treatment facilities, and increase the risk of human exposure (Patz et al. 2008; Marcheggiani et al. 2010; ten Veldhuis et al. 2010; Taylor et al. 2011).

Alternatively, water demand can increase during dry periods, causing greater reuse of wastewaters and poorer hygienic conditions (e.g., for cleaning, bathing, and drinking). These conditions have the potential to increase the risk of human exposure to pathogens from waters with inadequate treatment (WHO 2003; Funari et al. 2012).

Interactions within Ecosystems

The occurrence, fate, and transport of waterborne pathogens in U.S. waterbodies are influenced by and will interact with changes in other water quality variables, including sediment, nutrients, and salinity. The following is a brief summary of those interactions.

Sediment and Nutrients

Sediment and nutrient loading to waterbodies is influenced by many of the same transport mechanisms as microorganisms. Sediment interacts directly with microorganisms through adsorption/desorption – these processes are extremely important in governing the mobility of microorganisms. For example, viruses can be removed by adsorption in the first few inches of soil during infiltration. Conversely, flushing by rainfall can cause desorption and transport to waterbodies (USEPA 2013).

Sediment and manure can provide a favorable environment for pathogen survival because of the availability of nutrients and protection from sunlight and other conditions it provides (Rogers and Haines 2005). Pathogen and FIB survival rates in bedded sediments can be increased because of the availability of soluble organic matter and nutrients (Pommepuy et al. 1992). Bedded sediments also provide protection from harmful factors such as sunlight and warmer temperatures (Davies et al. 1995; Decamp and Warren 2000; Jamieson et al. 2004; Koirala et al. 2008; Kim et al. 2010; Characklis et al. 2005; Sherer et al. 1992). Pathogenic bacteria can survive for up to several months in the sediment reservoir, presenting a risk of resuspension in the water column (Burton et al. 1987; USEPA 2001). For example, E. coli O157:H7 can survive up to two or three times longer in river and lake sediments at lower temperatures (USEPA 2009a). Beach sands and sediments also have been documented as containing high concentrations of FIB, which can often be flushed to nearby waters during runoff events (Stewart et al. 2013).

Numerous studies have found higher concentrations of FIB adsorbed to sediments than in the water column (Kim et al. 2010; de Brauwere et al 2014; Soupir and Pandey 2016). FIB loads also are strongly correlated (positive) with stream sediment loads (Burton et al. 1987; Mallin et al. 2000). Studies also have shown elevated turbidity levels associated with higher streamflow to be correlated with increases in waterborne illness (Abia et al. 2016; Morris et al. 1996; Schwartz et al. 1997). Higher turbidity waters can provide microorganisms with some protection from ultraviolet light (USEPA 2013). Some pathogenic organisms can be protected from disinfection during the drinking water treatment process by remaining attached to sediment particles.

Salinity

Most waterborne pathogens have significantly lower survival rates in high-salinity environments than in less saline environments (Canteras et al. 1995; Bordalo et al. 2002). For example, the survival rate of Cryptosporidium has been reported to be lower when exposed to seawater and sunlight (Nasser et al. 2007). The distribution of Vibrio species in coastal systems also varies depending on the salinity of the water and other factors such as temperature. Vibrio vulnificus favors more moderate salinities, while Vibrio parahaeomolyticus and Vibrio alginolyticus favor higher salinities (Trtanj et al. 2016). Potential future changes in the salinity of coastal and estuarine waters as a result of sea level rise and changes in the delivery of freshwater would thus alter the survival of waterborne pathogens (Burge et al. 2014).

Regional Effects

The following is a regional summary pathogen responses to observed historical and projected future climate change. Content is organized by 8 geographic regions using the same regional divisions as in the 2014 U.S. Third National Climate Assessment (NCA3) (Melillo et al. 2014) - see box with "Related Links".

Introduction

To characterize the potential effects and risk presented by climate change, it is useful and a common practice to consider system response, or sensitivity, to either historical climate variability (short-term, days to years) or to run numerical model simulations of system response to a range of future climate change scenarios (decades). Knowledge of how pathogenic microorganisms respond to climate changes can help define the range of potential impacts, identify vulnerabilities, and inform the development of adaptation strategies for reducing future risks.

Studies of system responses to historical climatic variability typically focus on trends and the correlation between waterborne pathogens and climatic variables. In this context, climatic variability refers to the inherent heterogeneity of observed data over time (e.g., temperature, precipitation, environmental factors) (USEPA 2011). Although these studies provide important insights, the range of future conditions and events that can be evaluated is limited to the range of observed past climatic events.

Modeling studies use statistical or numerical simulation models to assess FIB responses to scenarios of potential future climate change. Scenarios typically include a range of potential futures based on either different climate models, different assumptions about future greenhouse gas (GHG) emissions, and/or different future time periods (in this review, classified as early century: 2020–2040, mid-century: 2041–2070, and late century: 2071–2100). Climate model output is used to drive a hydrologic or watershed model (e.g., SWAT, HSPF, or GWLF), providing a capability to evaluate a wide range of potential climate futures, as well as interactions with changes in land use and other factors affecting waterborne pathogens. Simulated results are commonly presented as average changes (annual or seasonal) in load (median or average) relative to a historical baseline period. It should be noted that, while most studies report changes in load (mass/time), others report changes in concentrations (mass/volume), and that increases or decreases in one do not imply similar changes in the other.

Most modeling studies report a range of load or concentration responses to different climate scenarios. In many cases, this range includes responses that differ in the direction of change, driven largely by variability in projected future precipitation. While in some cases the ensemble range of responses (i.e., the group of scenarios evaluated) can suggest a more likely direction of change, each individual scenario simulation within an ensemble should be considered equally likely, and no single scenario should be considered most likely. In addition, the results of all modeling studies are also directly conditional on the specific methods, models, and climate change scenarios evaluated (See "Scenario Sources"; note: all links will open in a new tab or window).

The lack of studies about potential future water quality changes can be a challenge to managers who must make specific decisions in the best interest of their programs and clients. This should not, however, obscure the significant, system-level understanding we have of hydrologic and water quality endpoint responses to climate change (e.g., increases in precipitation generally lead to proportionate increases in streamflow and many water quality endpoints are correlated with streamflow). Certain aspects of future climate change are also much better understood than others (e.g., continued warming is expected throughout the U.S. and will affect snow and snowmelt runoff, an increased proportion of annual precipitation is likely to occur in larger magnitude events throughout the nation, sea level rise will continue on all U.S. coasts). For a more detailed discussion of accounting for uncertainty, including methods for developing and using scenarios to inform adaptation decision making, see "Framework and Methods".

Northeast

 

No studies identified in this review explicitly assessed potential future climate change effects on waterborne pathogens in the Northeast. General inferences can be made, however, about future changes based on mechanistic knowledge of how changes in climate and hydrology affect waterborne pathogens. Table Path-3 summarizes potential changes for the Northeast.

Table Path-3. A summary of potential future waterborne pathogen responses in the Northeast.

Projected increases in air and water temperatures in the Northeast (see "Water Temperature"; note: links will open in a new tab or window) could reduce survival for some waterborne pathogens (e.g., pathogenic E. coli), particularly during summer-fall. Those increases, however, also are likely to favor the expansion of other pathogenic organisms (e.g., Vibrio species in coastal systems). In the Chesapeake Bay, projected increases in temperature (moderate emission scenario, representative concentration pathway [RCP] 6.0) were suggested to lengthen the seasonal window of Vibrio spp occurrence through the end of the 21st century (Jacobs et al. 2015). Warmer water temperatures could increase human exposure to waterborne pathogens by extending the period of warm-weather recreational uses. For example, in New York State, Lin et al. (2016) found that, between 1991 and 2004, for each 1 ^oC increase in temperature during summer months, there was an increase in daily gastrointestinal illness. No distinction was made, however, between foodborne and waterborne illnesses.

Locally variable changes in the amount and seasonal timing of precipitation are projected for the Northeast. Generally, increased winter-spring precipitation and a greater proportion of annual precipitation occurring in heavy events are projected (Prein et al. 2016; Kunkel et al. 2013; Horton et al. 2014). These changes, if realized, could increase fecal loading from upland sources to waterbodies. High streamflow events (associated with heavy precipitation) could also agitate and re-suspend pathogens stored in bed sediment (Hofstra 2011; Coffey et al. 2014). Observed waterborne illness outbreaks in the region have previously been linked to increases in precipitation intensity (see Table Path-4). For example, two previous waterborne disease outbreaks in Pennsylvania and Vermont were linked to heavy precipitation events as well as to inadequate water treatment (Table Path-3) (Lippy 1981; Vogt et al. 1982).

In Maryland's portion of the Chesapeake Bay, annual and seasonal precipitation totals from 1979 to 2013 had a strong positive relationship with average FIB levels in shellfish harvest waters and the proportion of shellfish samples with bacterial densities above Food and Drug Administration regulatory criteria (Leight et al. 2016). FIB levels tended to be higher in years when the bulk of precipitation occurred throughout the summer-fall (i.e., August–September). No strong relationship was found between seasonal or annual air temperature and FIB levels (Leight et al. 2016). The findings indicated that changes in climate conditions and sea level pressure patterns influencing extratropical and tropical storm tracks are important for predicting periods when high FIB levels could occur. Jiang et al. (2015) also reported small increases in waterborne and food-borne salmonellosis risk in Maryland for each unit increase in extreme precipitation events (+5.6-percent increase in risk of exposure) and 2-unit increase in extreme temperature events (+4.1-percent increase in risk of exposure) based on a 30-year climate baseline (i.e., 1960–2012).

Episodic high pathogen loading could also occur when fecal waste that accumulates on land during dry periods is transported to waterbodies by precipitation events. For example, a large outbreak of E. coli O157:H7 that occurred at the Washington County Fair in New York in September 1999 and was linked to contaminated well water, resulted from unusually heavy rainfall that had been preceded by drought (Novello 2000; Patz et al. 2000). In addition, longer and more frequent summer dry periods could lead to episodic increases in fecal levels downstream of point source discharges due to lower flow volumes and reduced dilution (Coffey et al. 2014). Such events would increase the risk of exceedances of concentration-based recreational water quality guidelines in some watersheds.

• Table Path-4. Occurrence of waterborne disease outbreaks following weather events in the Northeast

Southeast

 

The sensitivity of FIB to climate change in the Southeast—indicating the possible presence of pathogens—has been assessed in a small number of watershed modeling studies (Table Path-5). Model simulations show a range of projected future annual and/or seasonal changes in FIB responses to different climate change scenarios. As a whole, these studies generally suggest increases in average annual FIB loads and concentrations reflecting potential future changes in precipitation (Coffey et al. 2015a, 2015b; Jayakody et al. 2015; Liu et al. 2010). Locally variable changes in the amount and seasonal timing of precipitation, however, are projected for the Southeast (Carter et al. 2014), which limits the confidence in simulated changes. Table Path-6 summarizes potential changes for the region.

• Table Path-5. Projected FIB responses to future climate change scenarios in the Southeast

Mid-century increases in average annual FIB loads (+4 to +49 percent) were projected for the Pigg River watershed in southwest Virginia (low emissions, SRES B2) (Coffey et al. 2015a, 2015b). Simulated changes in FIB loads in the Pigg River were generally consistent with projected seasonal precipitation changes (Coffey et al. 2015a, 2015b). Increases in fall (+50 to +212 percent) and winter (+22 to +81 percent) FIB loads were suggested; however, decreases in spring FIB loads (-33 to -17 percent) and variable summer FIB load changes (-22 to +19 percent) were reported. The work also considered potential future changes in land-based FIB sources, including increased human population density, increased beef and poultry production, and reduced crop and dairy production. Simulations suggested that FIB loads were most sensitive to changes in climate, with increased loads being driven by trends in seasonal and annual precipitation. Limited data on future agricultural land management, however, was identified as a significant gap in the study.

• Table Path-6. A summary of potential future waterborne pathogen responses in the Southeast.

Jayakody et al. (2015) reported increases in average annual FIB concentrations for the Upper Pearl River watershed in central Mississippi (+ 175 percent at mid-century; + 297 percent at late century) under a moderate emission scenario (SRES A1B). Projected FIB concentrations exceeded current recreational standards during the summer months. In the winter months, simulated concentrations generally remained below the recreational WQS (Jayakody et al. 2015). The increases reported in this study are in general agreement with simulations conducted in the St. Louis Bay estuary of Mississippi. Simulations by Liu et al. (2010) showed a higher frequency of recreational WQS exceedances in wet years than in dry years and that nearby urban land use and associated runoff had a significant effect on FIB levels (Liu et al. 2010). Coffey et al (2015b) also found that simulated future FIB loads for Pigg River in Virginia exceeded recreational WQS more frequently than simulations of existing conditions.

It should be noted that the modeling studies reviewed did not consider the potential for extended summer dry periods (more likely in southwestern and central parts of the region) or increases in heavy precipitation events (projected for the entire region) (Carter et al. 2014; Prein et al 2016). Increased heavy precipitation events, if realized, could increase fecal loading from upland sources to waterbodies. High streamflow events (associated with heavy precipitation) could also agitate and re-suspend pathogens stored in bed sediment (Hofstra 2011; Coffey et al. 2014). Longer and more frequent summer dry periods could lead to episodic increases in fecal levels downstream of point source discharges due to lower streamflow volume and reduced dilution (Coffey et al. 2014). Such events would increase the risk of exceedances of concentration-based recreational water quality guidelines in some watersheds. For example, in Brunswick County, North Carolina, it was found that FIB levels in waterbodies were positively associated with rainfall, but frequent high FIB levels at times of no rain indicated other modes of contamination as well, such as groundwater and failing septic/sewer systems (Cahoon et al. 2016).

Future increases in summer-fall water temperatures could increase survival for some naturally occurring pathogenic organisms in waterbodies such as Naegleria fowleri, and Vibrio species in coastal systems (Hill et al. 2014). Warmer water temperatures could also increase human exposure to waterborne pathogens by extending the period of warm-weather recreational uses. Two documented cases of Naegleria fowleri infection in Arkansas were associated with exceptionally warm water temperatures during periods in which air temperatures were above 100 degrees Fahrenheit (^oF). Health officials reported elevated water temperatures (and other factors) as being conducive to Naegleria fowleri at the time of exposure (Matthews et al. 2014). Conversely, warmer air and water temperatures could reduce survival for other waterborne pathogens such as E. coli O157:H7, particularly during summer-fall.

Midwest

 

Few studies identified in this review explicitly assessed potential future climate change effects on waterborne pathogens in the Midwest. General inferences can be made, however, about future changes based on mechanistic knowledge of how changes in climate and hydrology affect waterborne pathogens. Table Path-7 summarizes potential changes for the Midwest.

• Table Path-7. A summary of potential future waterborne pathogen responses in the Midwest

Projected increases in air and water temperatures in the Midwest (see "Water Temperature"; note: links will open in a new tab or window) could reduce survival for some waterborne pathogens (e.g., pathogenic E. coli), particularly in summer-fall, but increase survival for others (e.g., Naegleria fowleri) (Pryor et al. 2014; Hill et al. 2014). Warmer water temperatures could also increase human exposure to waterborne pathogens by extending the period of warm-weather recreational uses. It was suggested that, in Wisconsin, warmer winter air temperatures slightly increased the incidence of waterborne illness in children from water supplies sourced to private wells and treated municipal systems (Uejio et al. 2014). Conversely, previous waterborne disease outbreaks in Missouri also have been associated with colder winter temperatures—which favor survival of some waterborne pathogens such as Cryptosporidium-and inadequate water treatment (Table Path-8) (Swerdlow et al. 1992; Clark et al. 1996; Angulo et al. 1997).

Locally variable changes in the amount and seasonal timing of precipitation are projected for the Midwest (wetter in eastern/northern states, drier in western/southern states). Generally, increased winter-spring precipitation and a greater proportion of annual precipitation occurring in heavy events are projected (Prein et al. 2016; Kunkel et al. 2013; Pryor et al. 2014). These changes, if realized, could transport more fecal waste to waterbodies from upland sources. Increases in high streamflow events (associated with heavy precipitation) also could agitate and re-suspend pathogens stored in bed sediment (Hofstra 2011; Coffey et al. 2014). Conversely, longer and more frequent summer dry periods could lead to episodic increases in fecal levels downstream of point source discharges due to lower streamflow volume and reduced dilution (Coffey et al. 2014). Such events would increase the risk of exceedances of concentration-based recreational water quality guidelines in some watersheds.

Patz et al. (2008) used downscaled future precipitation data for high and low GHG emission scenarios (from the Chicago Climate Impact Assessment) to explore how projected changes in the frequency of heavy precipitation events in Chicago are likely to affect CSO discharges to Lake Michigan. Using a daily precipitation of 6.35 centimeters (or 2.5 inches) as the threshold for initiating CSOs (Hayhoe et al. 2010), the frequency of CSO discharges rose by 50–120 percent by late century (Patz et al. 2008). This would result in increased fecal contamination, more recreational exposures, and possible contamination of drinking water.

In Wisconsin, projected future increases in precipitation (including heavy events) are suggested to promote waterborne disease outbreaks, particularly in untreated water supplies (Vavrus and Behnke 2013; Uejio et al. 2014). Observational studies in Wisconsin have also reported an association between rainfall events and increased childhood gastrointestinal illness in areas that accessed untreated source water (Drayna et al. 2010, Uejio et al 2014).

The largest outbreak of waterborne illness in the United States (cryptosporidiosis) occurred in Milwaukee in 1993 and affected an estimated 400,000 people, resulting in 54 deaths (Table Path-8). The outbreak was linked in part to severe winter storms and snow melt, which caused cold and unusually turbid conditions in drinking water supplies (MacKenzie et al. 1994; Hoxie et al. 1997). These conditions favor Cryptosporidium survival in waterbodies. Human sewage was later identified as the main cause (Peng et al. 1997; Sulaiman et al. 1998; MacKenzie et al. 1994).

• Table Path-8. Occurrence of waterborne disease outbreaks following weather events in the Midwest

Great Plains

 

No studies identified in this review explicitly assessed potential future climate change effects on waterborne pathogens the Great Plains. General inferences can be made, however, about future changes based on mechanistic knowledge of how changes in climate and hydrology affect waterborne pathogens. Table Path-9 summarizes potential changes for the Great Plains.

• Table Path-9. A summary of potential future waterborne pathogen responses in the Great Plains

Projected increases in air and water temperatures for the Great Plains (see "Water Temperature"; note: links will open in a new tab or window) could reduce survival for some waterborne pathogens (e.g., pathogenic E. coli), particularly in summer-fall, but also are likely to favor others (e.g., Naegleria fowleri) (Shafer et al. 2014; Hill et al. 2014). Warmer water temperatures could also increase human exposure to waterborne pathogens by extending the period of warm-weather recreational uses.

Locally variable changes in the amount and seasonal timing of precipitation are projected for the Great Plains (drier in central/southern states, wetter in northern states). Generally, increased winter-spring precipitation and a greater proportion of annual precipitation occurring in heavy events are projected (Prein et al. 2016; Kunkel et al. 2013; Shafer et al. 2014). These changes, if realized, could increase fecal loading from upland sources to waterbodies. Increases in high streamflow events (associated with heavy precipitation) also could re-suspend pathogens stored in bed sediment (Hofstra 2011; Coffey et al. 2014). Waterborne disease outbreaks in Montana, Texas, and Wyoming have been linked to periods of heavy rainfall and runoff events (Table Path-10).

Longer and more frequent summer dry periods could reduce water availability (Kunkel et al. 2013; Shafer et al. 2014) and affect the concentration of pathogens in source waters. A 1998 cryptosporidiosis outbreak in Brushy Creek, Texas, was linked to drought conditions which increased water demand, depleting the local groundwater water supply. The aquifer subsequently became contaminated with sewage after extreme heat caused fractures in the bedrock and exposed consumers to Cryptosporidium spp. (TDOH 1999). During dry periods, episodic increases in fecal levels could also occur downstream of point source discharges due to lower flow volumes and reduced dilution (Coffey et al. 2014). Such events would increase the risk of exceedances of concentration-based recreational water quality guidelines in some watersheds.

• Table Path-10. Occurence of waterborne disease outbreaks following weather events in the Great Plains

Southwest

 

No studies identified in this review explicitly assessed potential future climate change effects on waterborne pathogens in the Southwest. General inferences can be made, however, about future changes based on mechanistic knowledge of how changes in climate and hydrology affect waterborne pathogens. Table Path-11 summarizes potential changes for the Southwest.

• Table Path-11. A summary of potential future waterborne pathogen responses in the Southwest.

Projected increases in air and water temperatures for the Southwest (see "Water Temperature"; note: links will open in a new tab or window) could reduce survival for some waterborne pathogens (e.g., pathogenic E. coli), particularly in summer-fall, but also are likely to favor others (e.g., Naegleria fowleri and Vibrio species in coastal systems) (Garfin et al. 2014; Hill et al. 2014). Warmer water temperatures could also increase human exposure to waterborne pathogens by extending the period of warm-weather recreational uses.

Locally variable changes in the amount and seasonal timing of precipitation are projected for the Southwest (wetter in northwestern parts, drier in central/southern states). Generally, increases in winter-spring precipitation, earlier snowmelt, and more rain-on-snow events in mountain regions are suggested (Kunkel et al. 2013; Garfin et al. 2014). It also is generally suggested that precipitation is likely to occur in more intense events for the region (Prein et al. 2016). These changes, if realized, could increase fecal loading to waterbodies. Increases in high streamflow events (associated with heavy precipitation) also could agitate and re-suspend pathogens stored in bed sediment (Hofstra 2011; Coffey et al. 2014). Increases in fecal loading from upland sources is likely to have implications for both coastal and inland water quality. For example, Ackerman and Weisberg (2003) analyzed 5 years of daily FIB data from 20 sites in southern California and found that increases in ocean FIB concentrations were associated with most storm events larger than 6 millimeters (mm) and with all storms events larger than 25 mm. FIB concentrations remained elevated for as long as 5 days following storm events, although they generally returned to levels below state WQS within 3 days (Ackerman and Weisberg 2003). Semenza et al. (2012) suggest that potential future decreases in precipitation would decrease Enterococcus levels at California beaches, although episodic increases could occur during heavy precipitation events (Prein et al. 2016).

Northwest

 

No studies identified in this review explicitly assessed potential future climate change effects on waterborne pathogens in the Northwest. General inferences can be made, however, about future changes based on mechanistic knowledge of how changes in climate and hydrology affect waterborne pathogens. Table Path-12 summarizes potential changes for the Northwest.

• Table Path-12. A summary of potential future waterborne pathogen responses in the Northwest.

Projected increases in air and water temperature for the Northwest (see "Water Temperature"; note: links will open in a new tab or window) could reduce survival for some waterborne pathogens (e.g., pathogenic E. coli), particularly during summer-fall, but also are likely to favor others (e.g., Naegleria fowleri and Vibrio species) (Mote et al. 2014; Hill et al. 2014). Warmer water temperatures could also increase human exposure to waterborne pathogens by extending the period of warm-weather recreational uses.

Locally variable changes in the amount and seasonal timing of precipitation are projected for the Northwest. Generally, there is no consensus about the future direction of precipitation change for the region (Kunkel et al. 2013; Mote et al. 2014). Precipitation increases (potentially falling in heavier events) are most likely in winter-spring and could cause increases in fecal loading from upland sources (Kunkel et al. 2013; Mote et al. 2014; Prein et al. 2016). High intensity runoff and streamflow events (associated with heavy precipitation) also could agitate and re-suspend pathogens stored in bed sediments (Hofstra 2011; Coffey et al. 2014). Earlier snow and ice melt in winter-spring also could contribute to increases in fecal loading from upland sources.

Conversely, longer and more frequent summer dry periods could cause sustained periods of lower flow volume (Kunkel et al. 2013; Mote et al. 2014). Increases in fecal levels downstream of point source discharges could occur during these periods due to reduced dilution (Coffey et al. 2014). In addition, longer dry periods could lead to episodic flushing events – storm events that transport fecal waste that has built up on land during dry periods to waterbodies. For example, in Jackson County, Oregon, an intense rainfall event in 1992 after a long period of drought triggered a cryptosporidiosis outbreak (linked to sewage) in the surface drinking water supply (Leland et al. 1993; Geldreich et al. 1992).

Alaska

 

No studies identified in this review explicitly assessed potential future climate change effects on waterborne pathogens in Alaska. General inferences can be made, however, about future changes based on mechanistic knowledge of how changes in climate and hydrology affect waterborne pathogens . 

Projected increases in air and water temperatures could reduce survival for some waterborne pathogens (e.g., pathogenic E. coli O157:H7), particularly during summer, but favor higher survival for others (e.g., Vibrio species in coastal systems) (Leong et al. 2014; Kyle and Brabets 2001). For example, 60 percent of Alaskan coastal waters are projected to have sea surface temperatures favorable to Vibrio growth in the month of August by late century (moderate emissions, RCP 6.0) (Jacobs et al. 2015).

Potential increases in seasonal and annual precipitation and runoff (including the frequency of heavy precipitation) could transport more fecal contamination to waterbodies (Chapin et al. 2014). Earlier snow and ice melt in winter-spring also could contribute to increases in fecal loading from upland sources. Additionally, higher streamflow rates also could agitate and re-suspend pathogens stored in bed sediments (Hofstra 2011; Coffey et al. 2014). 

Increased fecal levels could occur downstream of point source discharges during dry spells due to lower streamflow volumes and reduced dilution of effluent (Coffey et al. 2014). Such events would increase the risk of exceedances of concentration-based recreational water quality guidelines in some watersheds.

Hawai'i

 

One study was identified in Hawai'i that specifically assessed potential future climate change effects on FIB. Strauch et al. (2014) reported that decreases in average annual rainfall (projected to occur for some climate change scenarios) significantly increased FIB concentrations in Hawaiian watersheds. Increases in 24-hour rainfall intensity mobilized more soil and FIB in runoff for watersheds with lower average annual rainfall and drier soil conditions, causing rapid increases in FIB load. Other studies also have indicated that increases in the frequency and magnitude of heavy precipitation and high streamflow events could agitate and re-suspend pathogens stored in bed sediments (Hofstra 2011; Coffey et al. 2014). In addition, the study by Strauch et al. (2014) also reported that a decline in FIB was apparent as the percentage of forest cover increased and urbanization decreased.

This study, however, did not explicitly provide information on how increases in temperature might affect waterborne microorganisms in Hawai'i. Anticipated increases in air and water temperature on the islands could decrease survival times for some common waterborne pathogens (e.g., pathogenic E. coli), but also are likely to favor others (e.g., Vibrio species) (Leong et al. 2014).

In addition, increases in fecal levels could occur downstream of point source discharges during dry spells due to lower streamflow volumes and reduced dilution of effluent (Coffey et al. 2014). Such events would increase the risk of exceedances of concentration-based recreational water quality guidelines in some watersheds.

National Summary

The following is a national-scale review of waterborne pathogen responses to observed and projected climate change.

Anticipated Climate Change

Climate change in most U.S. regions is anticipated to include warming temperatures, with less certain and regionally variable changes in the amount and seasonal timing of precipitation (Melillo et al. 2014). Warming air temperatures will affect the timing and seasonality of snow and snowmelt, including potentially more winter precipitation in the form of rain as opposed to snow.

An increasing frequency of heavy precipitation events and longer dry periods between events are also likely in most regions (Prein et al. 2016). The effect of these changes on runoff will reflect the balance between drying associated with increased air temperature and ET, and the amount and direction of future changes in precipitation in different regions and watershed settings. Generally, in the United States historically wetter regions (e.g., northern and eastern regions) are projected to receive more precipitation with corresponding increases in total runoff; whereas historically drier regions (primarily the arid southwest, southern Great Plains, and parts of the southeast) are projected to see less precipitation and decreases in runoff/streamflow (Arnell 2003; Milly et al. 2005; USEPA 2013). The specific effects of climate change on waterborne pathogens will vary in different watershed settings, and interact with the effects of local watershed land use, water management and other human activities affecting sources. Linking outbreaks of waterborne illness to climatic drivers is thus difficult due to the many interactions involved (e.g., transport, exposure).

Waterborne Pathogen Changes

Waterborne pathogens can survive for long periods in different environmental matrices (e.g., soil, manure, and water) when conditions are favorable. Low temperatures, appropriate moisture levels, nutrient availability, and protection from external factors, such as ultraviolet radiation, can prolong survival for many common waterborne pathogens. Temperature, in particular, is an important factor affecting survival (Cho et al. 2016). Higher air and water temperatures are projected to occur throughout the United States (Melillo et al. 2014; Hill et al. 2014) and could reduce survival rates for some common pathogenic organisms such as pathogenic strains of E. coli (Schijven and Husman 2005). Conversely, other species could experience faster growth and prolonged survival (Hunter 2003; Freeman et al. 2009; Karvonen et al. 2010; Coffey et al. 2014). For example, naturally occurring Vibrio spp. and Legionella grow faster in warmer water and could become more common geographically and seasonally throughout the year (Lipp et al. 2002; Trtanj et al. 2016). A warmer climate also could lead to the expansion of new microorganisms such as amoeboid pathogens (e.g., Naegleria and Acanthamoeba), vectors, and/or intermediary hosts (Harrus and Baneth 2005). Some waterborne pathogens also could spread to new areas due to warming temperatures (Hoskisson and Trevors 2010).

Climate change effects on runoff are likely to influence pathogen survival and transport from upland sources to waterbodies. The delivery of fecal waste (which can contain pathogenic organisms) to waterbodies is largely episodic, driven by precipitation and runoff events. Changes in precipitation, together with other climatic drivers that affect runoff (e.g., air temperature, solar radiation, wind, humidity) are thus likely to influence pathogen loads within waterbodies. While uncertainty remains regarding regional changes in precipitation volume (Melillo et al. 2014), future increases in the proportion of precipitation occurring in large-magnitude events are likely to present an increased risk of pathogen loading from upland sources to waterbodies (e.g., NPSs as well as urban SSOs and CSOs) (Hofstra 2011; Coffey et al. 2014; Cann et al. 2013; Trtanj et al. 2016). Associated increases in streamflow also could re-suspend and mobilize pathogens stored in river and lake bed sediments (Soupir and Pandey 2016; Wu et al. 2009; Garzio-Hadzick et al. 2010). A number of studies indicate links between precipitation events and waterborne disease outbreaks (Rizak and Hrudey 2008; Curriero et al. 2001; Kistemann et al. 2002). For example, Curriero et al. (2001) analyzed 548 waterborne disease outbreaks that occurred in the United States between 1948 and 1994 and found that over half of them were preceded by heavy rainfall events.

Longer and more frequent summer dry periods also are anticipated in much of the United States (particularly in the southern Great Plains, Southwest, and Northwest) (Melillo et al. 2014). Lower flow volumes during these periods could result in episodic increases in fecal levels downstream of point-source discharges (e.g., wastewater treatment plants) due to reduced dilution (Senhorst and Zwolsman 2005; Johnson et al. 2009; Hofstra 2011; Funari et al. 2012; Cann et al. 2013; Coffey et al. 2014). Precipitation events after dry periods also could lead to more frequent, episodic increases in pathogen loading from the flushing of fecal waste accumulated on land.

While relatively few studies explicitly address future climate change effects on waterborne pathogens, changes in temperature, precipitation, and runoff are known drivers of pathogen fate and transport, and thus could present an increased risk of waterbody contamination and human exposure. These findings are broadly consistent with those reported in other large-scale assessments such as the U.S. Global Change Research Program (USGCRP) Third National Climate Assessment and the USGCRP Climate and Health Assessment (Melillo et al. 2014; Trtanj et al. 2016).

The potential for increased pathogen loads in source waters used as a drinking water supply presents a challenge in designing and operating drinking water treatment plants to meet Safe Drinking Water Act maximum contaminant levels (Clark et al. 2011; Albert 2008; USEPA 2002, 2016) as well as for managing levels of disinfection by-products in distribution systems (Zwolsman et al. 2011; Tratanj et al. 2016; Li et al. 2014). Climate change also could increase the risk of human exposure to waterborne pathogens from groundwater sources used as a drinking water supply. Shallow groundwater wells are likely to be more vulnerable to fecal contamination as they are most influenced by surface runoff (Levin et al. 2002). Many previous waterborne disease outbreaks have been linked to drinking water supplies sourced from groundwater (Levin et al. 2002). The risk of human exposure through recreational water use could also be affected. The majority of waterborne disease outbreaks from recreational water use occur during summer (Hlavsa et al. 2014; Curriero et al. 2001; Freeman et al. 2009; McBride et al. 2014). As climate warms, warmer seasonal air temperatures are expected to expand the window of recreational water use and increase the risk of human exposure to waterborne pathogens (Casman et al. 2001; Schijven and Husman 2005).

Adaptation Resources

Successful climate change adaptation strategies will need to encompass practices and decisions to reduce vulnerabilities across a range of plausible future conditions. For a detailed discussion of methods for developing and using information about climate change to inform adaptation decision making see "Framework and Methods". Use the "Tools and Data" and "Case Studies" sections to search resources that may be useful for adaptation planning.

Research Needs

The following questions highlight knowledge gaps where the need for information is greatest.

How can monitoring be improved to better detect waterborne pathogen repsonses?

Observational data are essential to understanding the current status and trends in waterborne pathogens, including historical and potential future effects of climate change and other nonclimatic drivers. Currently available observational data about microbial water quality are limited in space and time. Existing traditional monitoring and especially long-term microbial water quality monitoring programs need to continue to be supported and expanded (Urquhart et al. 2014). For many waterborne pathogens, efficient detection and/or quantification methods for water samples are not readily available (Figueras and Borrego 2010; Levin et al. 2002; Coffey et al. 2014). The development of simple, fast, and affordable detection methods would permit streamlined analysis and assessment (Jung et al. 2014). In addition, data available for linking exposure to climate events are limited, partly from underreporting, which is an inherent problem in disease surveillance systems (Hofstra 2011; Coffey et al. 2014) and partly from a lack of data collected during periods of elevated risk such as after heavy rainfalls (Tryland et al. 2011).

Monitoring also should be expanded, as appropriate, to include hydrologic and water quality parameters useful as indicators of climate change. In addition, new technologies should be explored to expand the use of continuous in-situ monitoring, regular remotely sensed monitoring, or other approaches that can provide efficient, accurate, and reliable detection and tracking of observed changes. Observational data also are a key component in calibrating hydrological and water quality models (particularly process-based models), which can subsequently be used to extrapolate potential changes in water quality beyond current conditions.

How can water quality models be improved to better simulate future waterborne pathogen responses?

Model-based assessments of climate change effects on hydrology and water quality are subject to a cascade of uncertainty associated with future climate change projections, together with uncertainty in simulating watershed responses to changing climate (see "Framework and Methods"). One of the greatest sources of variability in current assessments of climate change effects on water quality is in regional scale GCM projections for long-term changes in precipitation. The application of ensemble approaches mitigates some of the variability associated with projections. Improvements in our understanding of future changes in precipitation at local-to-regional scales is important to further advance our understanding of potential effects (WMO 2009).

Improved capabilities to simulate watershed hydrologic and microorganism responses to climate change also are important in anticipating and responding to the impacts of climate change. Modeling pathogen fate and transport is difficult and, at present, prone to error (Oliver et al. 2016; Novotny 2003; Novotny and Stefan 2007). Modeling limitations have been detailed in many studies (Tu 2009; Crossman et al. 2013; Jha et al. 2013; Johnson et al. 2015). Areas of particular concern include sediment resuspension (Jamieson et al. 2004; Droppo et al. 2009; Coffey et al. 2010a, 2010c) and subsurface transport (Baffaut and Sadeghi 2010), as well as improved ability to simulate hydrology during extreme low and high flow events (Benham et al. 2006; Beckers et al. 2009; Kim et al. 2010).

How can we improve the characterization of pathogen sources on land?

Identifying sources of pathogens and tracking the movement of pathogens are often difficult and resource-intensive tasks that have hindered the development of effective modeling applications, management strategies, and watershed assessments. Although a variety of potential future land management scenarios for urban and residential areas have been established (e.g., EPA ICLUS), limited information is available on potential changes in agricultural, forestry, and other land uses. In addition, population densities for livestock, wildlife, and other potential microbial pollution sources are not precise. Current data on contributions from wildlife populations are insufficient and, under a changing climate, are likely to be further complicated by migration patterns (e.g., geese in waterbodies). While progress has been made in the field of microbial source tracking as a method for identifying key sources, implementation is still limited, as it requires extensive validation, further assay development, and standardization of parameters (Patz et al. 2008; Oliver et al. 2015).

How important are climate change effects on waterborne pathogens compared to the effects of land use change?

Waterborne pathogens sourced to fecal waste are affected by urban and agricultural land use, pollutant discharges and water management infrastructure. The effects of climate change will interact with fecal sources on land (e.g., human, livestock and wildlife) in different regional and watershed settings. Combined effects of changes in climate and land use on pathogens, however, are yet to be fully integrated in most studies. More information on the interaction of land use, water management and climate, including model simulations using combined land use, BMP and climate scenarios, would help guide strategies for reducing pathogen loads. Evaluation of potential changes in water management infrastructure and how these changes compare to the potential effects of climate change would also improve our understanding of the significance of climate change in a holistic watershed context.

A related research question specific to climatic drivers is the relative influence of changes in air temperature and precipitation on waterborne pathogens. Future changes in temperature affect organism survival and are better understood than changes in precipitation in most regions of the U.S. Improved understanding of the effects of more certain increases in air temperature compared to those of more locally variable future changes in precipitation could help frame uncertainty in a more useful way to inform strategies for managing waterborne pathogens.

How can we manage potential future climate change effects on waterborne pathogens?

Future changes in waterborne pathogens in many areas of the country could result in significant impacts to water quality and aquatic ecosystems (e.g., for drinking water, recreation, ecosystem services). Impacts will vary regionally and in different watershed settings and, in most locations, the effects of climate change will be mediated by or influence other nonclimatic changes such as land use and water management infrastructure. Responding to this challenge requires an improved understanding of the type and scope of management responses necessary to reduce the risk of impacts. Research is needed to better understand the effectiveness and application of alternative strategies, including water quality best management practices, water treatment, and other approaches to meeting water quality goals.

Are there differences in the regional vulnerability of climate change effects on waterborne pathogens?

Effects of climate change on waterborne pathogens will vary regionally and in different watershed settings, and in most locations climate change will interact with other non-climatic changes (e.g., land use and water management infrastructure). While basic principles about system response to changes in climatic drivers can be broadly applied, it is important to have local-scale, representative studies to inform adaptation planning. In all regions, however, few studies were identified in the literature addressing the effects of climate change on waterborne pathogens. Increased efforts to understand the implications of projected climate change on waterborne pathogens in different U.S. regions would provide much needed support for adaptation planning by local stakeholders.

How will climate change affect the provision of safe potable water?

In the coming decades, climate change is only one of many issues water utilities across the country will face, including upgrading drinking water infrastructure. Additional research might be required to assess the combined effects of aging infrastructure, increased water demand, and climate change (Levin et al. 2002). There are approximately 1 million miles of water distribution systems in the United States that produce 34 billion gallons of water per day for public water supplies (Beach 2015). Pipes and water treatment plants are 50–100 years old in many areas of the United States, however, which leads to an increased risk of drinking water contamination if infrastructure is not replaced or upgraded (Levin et al. 2002). It was estimated that 13 percent of waterborne disease outbreaks in the United States between 2002 and 2006 were caused by infrastructure deficiencies in public water supplies (Beach 2015). Infrastructure projects totaling $334.8 billion are suggested to be needed in coming decades for utilities to continue to reliably provide safe drinking water to the public (USEPA 2009b).

Literature Cited

• Literature cited in "Water Quality Topics: Pathogens" is listed below.
• A comprehensive list of all literature cited in the WQCR is provided in the Literature Database.

Pathogens Citations

• Abia, A.L., E. Ubomba-Jaswa, B. Genthe, and M.N. Momba. 2016. Quantitative microbial risk assessment (QMRA) shows increased public health risk associated with exposure to river water under conditions of riverbed sediment resuspension. Science of the Total Environment 566-567:1143-1151. doi: 10.1016/j.scitotenv.2016.05.155.
• Ackerman, D., and S.B. Weisberg. 2003. Relationship between rainfall and beach bacterial concentrations on Santa Monica Bay beaches. Journal of Water and Health 1(2):85-89.
• Albert, J. 2008. Climate change and water quality issues. Drinking Water Research: Climate Change and Drinking Water Climate Change Special Issue 2008 18(2):11-14.
• Alderisio, K.A., and N. DeLuca. 1999. Seasonal enumeration of fecal coliform bacteria from the feces of Ring−Billed Gulls (Larus delawarensis) and Canada Geese (Branta canadensis). Applied and Environmental Microbiology 65(12):5628-5630.
• Altizer, S., R.S. Ostfeld, P.T.J. Johnson, S. Kutz, and C.D. Harvell. 2013. Climate change and infectious diseases: From evidence to a predictive framework. Science 341(6145):514-519. doi: 10.1126/science.1239401.
• Angulo, F.J., S. Tippen, D.J. Sharp, B.J. Payne, C. Collier, J.E. Hill, T.J. Barrett, R.M. Clark, E.E. Geldreich, H.D. Donnell, and D.L. Swerdlow. 1997. A community waterborne outbreak of salmonellosis and the effectiveness of a boil water order. American Journal of Public Health 87(4):580-584. doi: 10.2105/ajph.87.4.580.
• Arnell, N.W. 2003. Effects of IPCCSRES emissions scenarios on river runoff: A global perspective. Hydrology and Earth System Sciences 7(5):619-641.
• Arnone, R.D., and J.P. Walling. 2007. Waterborne pathogens in urban watersheds. Journal of Water and Health 5(1):149-162. doi: 10.2166/wh.2006.001.
• ASM (American Society for Microbiology). 1998. Microbial Pollutants in Our Nation's Water: Environmental and Public Health Issues. American Society for Microbiology. Washington, DC. http://www.asm.org/index.php/mentoring/110-publications/public-affairs-report/2847-microbial-pollutants-in-our-nation-s-water-environmental-and-public-health-issues.
• Baffaut, C., and A. Sadeghi. 2010. Bacteria modeling with SWAT for assessment and remediation studies: A review. Transactions of the ASABE 53(5):1585-1594.
• Baffaut, C., and V.W. Benson. 2003. A bacteria TMDL for Shoal Creek using SWAT modeling and DNA source tracking. In Total Maximum Daily Load (TMDL) Environmental Regulations II Proceedings, American Society of Agricultural Engineers, Albuquerque, New Mexico, November 8-12, 2003, pp.35-40.
• Bannerman, R.T., D.W. Owens, R.B. Dodds, and N.J. Hornewer. 1993. Sources of pollutants in Wisconsin stormwater. Water Science and Technology 28(3-5):241-259.
• Bates, B., Z.W. Kundzewicz, S. Wu, and J.P. Palutikof (eds.). 2008. Climate Change and Water. Technical Paper of the Intergovernmental Panel on Climate Change, IPCC Secretariat. Geneva, Switzerland.
• Beach, M.J. 2015. The Changing Epidemiology of Waterborne Disease Outbreaks in the United States: Implications for System Infrastructure and Future Planning. PowerPoint presentation. Centers for Disease Control and Prevention, National Center Zoonotic, Vector-borne, and Enteric Disease. Atlanta, GA. http://www.nationalacademies.org/hmd/~/media/ECA5BAE13B3B4946AC2BC16F52EF3764.ashx.
• Beaudeau, P., M. Pascal, D. Mouly, C. Galey, and O. Thomas. 2011. Health risks associated with drinking water in a context of climate change in France: A review of surveillance requirements. Journal of Water and Climate Change 2(4):230-246. doi: 10.2166/wcc.2011.010.
• Beckers, J., B. Smerdon, and M. Wilson. 2009. Review of Hydrologic Models for Forest Management and Climate Change Applications in British Columbia and Alberta. FORREX Forum for Research and Extension in Natural Resources. Kamloops, British Columbia, Canada. http://www.forrex.org/publications/forrexseries/fs25.pdf.
• Benham, B.L., C. Baffaut, R.W. Zeckoski, K.R. Mankin, Y.A. Pachepsky, A.A. Sadeghi, K.M. Brannan, M.L. Soupir, and M.J. Habersack. 2006. Modeling bacteria fate and transport in watersheds to support TMDLs. Transactions of the ASABE 49(4):987-1002.
• Bordalo, A.A., R. Onrassami, and C. Dechsakulwatana. 2002. Survival of faecal indicator bacteria in tropical estuarine waters (Bangpakong River, Thailand). Journal of Applied Microbiology 93(5):864-871. doi: 10.1046/j.1365-2672.2002.01760.x.
• Boxall, A.B.A., A. Hardy, S. Beulke, T. Boucard, L. Burgin, P.D. Falloon, P.M. Haygarth, T. Hutchinson, R.S. Kovats, G. Leonardi, L.S. Levy, G. Nichols, S.A. Parsons, L. Potts, D. Stone, E. Topp, D.B. Turley, K. Walsh, E.M.H. Wellington, and R.J. Williams. 2009. Impacts of climate change on indirect human exposure to pathogens and chemicals from agriculture. Environmental Health Perspectives 117(4):508-514. doi: 10.1289/ehp.0800084.
• Burge, C.A., C.M. Eakin, C.S. Friedman, B. Froelich, P.K. Hershberger, E.E. Hofmann, L.E. Petes, K.C. Prager, E. Weil, B.L. Willis, S.E. Ford, and C.D. Harvell. 2014. Climate change influences on marine infectious diseases: Implications for management and society. Annual Review of Marine Science 6:249-277.
• Burton, G.A., D. Gunnison, and G.R. Lanza. 1987. Survival of pathogenic bacteria in various freshwater sediments. Applied and Environmental Microbiology 53(4):633-638.
• Cahoon, L.B., J.C. Hales, E.S. Carey, S. Loucaides, K.R. Rowland, and B.R. Toothman. 2016. Multiple modes of water quality impairment by fecal contamination in a rapidly developing coastal area: southwest Brunswick County, North Carolina. Environmental Monitoring and Assessment 188(2):89. doi: 10.1007/s10661-015-5081-6.
• Cann, K.F., D.R. Thomas, R.L. Salmon, A.P. Wyn-Jones, and D. Kay. 2013. Extreme water-related weather events and waterborne disease. Epidemiology and Infection 141(4):671-686. doi: 10.1017/s0950268812001653.
• Canteras, J.C., J.A. Juanes, L. Perez, and K.N. Koev. 1995. Modeling the coliforms inactivation rates in the Cantabrian Sea (Bay of Biscay) from in-situ and laboratory determinations of T-90. Water Science and Technology 32(2):37-44. doi: 10.1016/0273-1223(95)00567-7.
• Carter, L.M., J.W. Jones, L. Berry, V. Burkett, J.F. Murley, J. Obeysekera, P.J. Schramm, and D. Wear. 2014. Southeast and the Caribbean. Chapter 17 in Climate Change Impacts in the United States: The Third National Climate Assessment, ed. J.M. Melillo, T.C. Richmond and G.W. Yohe, pp. 396-417. U.S. Global Change Research Program, Washington, DC.
• Casman, E., B. Fischhoff, M. Small, H. Dowlatabadi, J. Rose, and M.G. Morgan. 2001. Climate change and cryptosporidiosis: A qualitative analysis. Climatic Change 50(1-2):219-249. doi: 10.1023/a:1010623831501.
• CFERT (California Food Emergency Response Team). 2008. Investigation of the Taco John’s Escherichia coli O157:H7 Outbreak Associated with Iceberg Lettuce. California Department of Public Health. Sacramento, CA.
• Chapin, III, F.S., S.F. Trainor, P. Cochran, H. Huntington, C. Markon, M. McCammon, A.D. McGuire, and M. Serreze. 2014. Alaska. Chapter 22 in Climate Change Impacts in the United States: The Third National Climate Assessment, ed. J.M. Melillo, T.C. Richmond and G.W. Yohe, pp. 514-536. U.S. Global Change Research Program, Washington, DC.
• Characklis, G.W., M.J. Dilts, O.D. Simmons, C.A. Likirdopulos, L.A.H. Krometis, and M.D. Sobsey. 2005. Microbial partitioning to settleable particles in stormwater. Water Research 39(9):1773-1782. doi: 10.1016/j.watres.2005.03.004.
• Charron, D.F., M.K. Thomas, D. Waltner-Toews, J.J. Aramini, T. Edge, R.A. Kent, A.R. Maarouf, and J. Wilson. 2004. Vulnerability of waterborne diseases to climate change in Canada: A review. Journal of Toxicology and Environmental Health, Part A: Current Issues 67(20-22):1667-1677. doi: 10.1080/15287390490492313.
• Cho, K.H., S.M. Cha, J.H. Kang, S.W. Lee, Y. Park, J.W. Kim, and J.H. Kim. 2010. Meteorological effects on the levels of fecal indicator bacteria in an urban stream: A modeling approach. Water Research 44(7):2189-2202. doi: 10.1016/j.watres.2009.12.051.
• Cho, K.H., Y.A. Pachepsky, M. Kim, J. Pyo, M.-H. Park, Y.M. Kim, J.-W. Kim, and J.H. Kim. 2016. Modeling seasonal variability of fecal coliform in natural surface waters using the modified SWAT. Journal of Hydrology 535:377-385. doi: 10.1016/j.jhydrol.2016.01.084.
• Clark, R.M., E.E. Geldreich, K.R. Fox, E.W. Rice, C.H. Johnson, J.A. Goodrich, J.A. Barnick, and F. Abdesaken. 1996. Tracking a Salmonella serovar typhimurium outbreak in Gideon, Missouri: Role of contaminant propagation modelling. Journal of Water Supply Research and Technology-Aqua 45(4):171-183.
• Clark, R.M., L.I. Zhiwei, and S.G. Buchberger. 2011. Adapting water treatment design and operations to the impacts of global climate change. Frontiers in Earth Science 5(4):363-370. doi: 10.1007/s11707-011-0197-7.
• Coffey, R., B. Benham, K. Kline, M.L. Wolfe, and E. Cummins. 2015a. Modeling the impacts of climate change and future land use variation on microbial transport. Journal of Water and Climate Change 6(3):449-471.
• Coffey, R., B. Benham, K. Kline, M.L. Wolfe, and E. Cummins. 2015b. Potential microbial load reductions required to meet existing freshwater recreational water quality standards for a selection of mid-century environmental change scenarios. Environmental Processes 2(4):609-629. doi: 10.1007/s40710-015-0114-2.
• Coffey, R., B. Benham, L.-A. Krometis, M.L. Wolfe, and E. Cummins. 2014. Assessing the effects of climate change on waterborne microorganisms: Implications for EU and U.S. water policy. Human and Ecological Risk Assessment: An International Journal 20(3):724-742. doi: 10.1080/10807039.2013.802583.
• Coffey, R., E. Cummins, M. Cormican, V.O. Flaherty, and S. Kelly. 2007. Microbial exposure assessment of waterborne pathogens. Human and Ecological Risk Assessment 13(6):1313-1351. doi: 10.1080/10807030701655582.
• Coffey, R., E. Cummins, V. O’ Flaherty, and M. Cormican. 2010a. Pathogen sources estimation and scenario analysis using the Soil and Water Assessment Tool (SWAT). Human and Ecological Risk Assessment: An International Journal 16(4):913-933. doi: 10.1080/10807039.2010.502051.
• Coffey, R., E. Cummins, V. O'Flaherty, and M. Cormican. 2010b. Analysis of the Soil and Water Assessment Tool (SWAT) to model cryptosporidium in surface water sources. Biosystems Engineering 106(3):303-314. doi: 10.1016/j.biosystemseng.2010.04.003.
• Coffey, R., E. Cummins, N. Bhreathnach, V. O. Flaherty, and M. Cormican. 2010c. Development of a pathogen transport model for Irish catchments using SWAT. Agricultural Water Management 97(1):101-111. doi: 10.1016/j.agwat.2009.08.017.
• Collier, S.A., L.J. Stockman, L.A. Hicks, L.E. Garrison, F.J. Zhou, and M.J. Beach. 2012. Direct healthcare costs of selected diseases primarily or partially transmitted by water. Epidemiology and Infection 140(11):2003-2013. doi: 10.1017/s0950268811002858.
• Crossman, J., M.N. Futter, S.K. Oni, P.G. Whitehead, L. Jin, D. Butterfield, H.M. Baulch, and P.J. Dillon. 2013. Impacts of climate change on hydrology and water quality: Future proofing management strategies in the Lake Simcoe Watershed, Canada. Journal of Great Lakes Research 39(1):19-32. doi: 10.1016/j.jglr.2012.11.003.
• Crowther, J., D. Kay, and M.D. Wyer. 2002. Faecal-indicator concentrations in waters draining lowland pastoral catchments in the UK: Relationships with land use and farming practices. Water Research 36(7):1725-1734. doi: 10.1016/s0043-1354(01)00394-3.
• Crowther, J., M.D. Wyer, M. Bradford, D. Kay, C.A. Francis, and W.G. Knisel. 2003. Modelling faecal indicator concentrations in large rural catchments using land use and topographic data. Journal of Applied Microbiology 94(6):962-973. doi: 10.1046/j.1365-2672.2003.01877.x.
• Curriero, F.C., J.A. Patz, J.B. Rose, and S. Lele. 2001. The association between extreme precipitation and waterborne disease outbreaks in the United States, 1948-1994. American Journal of Public Health 91(8):1194-1199. doi: 10.2105/ajph.91.8.1194.
• Davies, C.M., J.A.H. Long, M. Donald, and N.J. Ashbolt. 1995. Survival of fecal microorganisms in marine and fresh-water sediments. Applied and Environmental Microbiology 61(5):1888-1896.
• de Brauwere, A., N.K. Ouattara, and P. Servais. 2014. Modeling fecal indicator bacteria concentrations in natural surface waters: A review. Critical Reviews in Environmental Science and Technology 44(21):2380-2453. doi: 10.1080/10643389.2013.829978.
• Decamp, O., and A. Warren. 2000. Investigation of Escherichia coli removal in various designs of subsurface flow wetlands used for wastewater treatment. Ecological Engineering 14(3):293-299. doi: 10.1016/s0925-8574(99)00007-5.
• Drayna, P., S.L. McLellan, P. Simpson, S.H. Li, and M.H. Gorelick. 2010. Association between rainfall and pediatric emergency department visits for acute gastrointestinal illness. Environmental Health Perspectives 118(10):1439-1443. doi: 10.1289/ehp.0901671.
• Droppo, I.G., S.N. Liss, D. Williams, T. Nelson, C. Jaskot, and B. Trapp. 2009. Dynamic existence of waterborne pathogens within river sediment compartments: Implications for water quality regulatory affairs. Environmental Science & Technology 43(6):1737-1743. doi: 10.1021/es802321w.
• Dwight, R.H., J.C. Semenza, D.B. Baker, and B.H. Olson. 2002. Association of urban runoff with coastal water quality in Orange County, California. Water Environment Research 74(1):82-90. doi: 10.2175/106143002x139776.
• Figueras, M.J., and J.J. Borrego. 2010. New perspectives in monitoring drinking water microbial quality. International Journal of Environmental Research and Public Health 7(12):4179-4202. doi: 10.3390/ijerph7124179.
• Fisher, G.T., and B.G. Katz. 1988. Urban Stormwater Runoff: Selected Background Information and Techniques for Problem Assessment with a Baltimore, Maryland Case Study. United States Geological Survey Water-Supply Paper 2347. United States Geological Survey. Baltimore, MD. https://pubs.usgs.gov/wsp/2347/report.pdf.
• Fox, K.R., and D.A. Lytle. 1996. Milwaukee's crypto outbreak: Investigation and recommendations. Journal American Water Works Association 88(9):87-94.
• Freeman, J.T., D.J. Anderson, and D.J. Sexton. 2009. Seasonal peaks in Escherichia coli infections: Possible explanations and implications. Clinical Microbiology and Infection 15(10):951-953. doi: 10.1111/j.1469-0691.2009.02866.x.
• Fujioka, R.S., H.M. Solo-Gabriele, M.N. Byappanahalli, and M. Kirs. 2015. U.S. recreational water quality criteria: A vision for the future. International Journal of Environmental Research and Public Health 12(7):7752-7776. doi: 10.3390/ijerph120707752.
• Funari, E., M. Manganelli, and L. Sinisi. 2012. Impact of climate change on waterborne diseases. Annali Dell Istituto Superiore Di Sanita 48(4):473-487. doi: 10.4415/ann_12_04_13.
• Gaffield, S.J., R.L. Goo, L.A. Richards, and R.J. Jackson. 2003. Public health effects of inadequately managed stormwater runoff. American Journal of Public Health 93(9):1527-1533. doi: 10.2105/ajph.93.9.1527.
• Galway, L.P., D.M. Allen, M.W. Parkes, L. Li, and T.K. Takaro. 2015. Hydroclimatic variables and acute gastro-intestinal illness in British Columbia, Canada: A time series analysis. Water Resources Research 51(2):885-895. doi: 10.1002/2014wr015519.
• Garfin, G., G. Franco, H. Blanco, A. Comrie, P. Gonzalez, T. Piechota, R. Smyth, and R. Waskom. 2014. Southwest. Chapter 20 in Climate Change Impacts in the United States: The Third National Climate Assessment, ed. J.M. Melillo, T.C. Richmond and G.W. Yohe, pp. 462-486. U.S. Global Change Research Program, Washington, DC.
• Garzio-Hadzick, A., D.R. Shelton, R.L. Hill, Y.A. Pachepsky, A.K. Guber, and R. Rowland. 2010. Survival of manure-borne E. coli in streambed sediment: Effects of temperature and sediment properties. Water Research 44(9):2753-2762. doi: 10.1016/j.watres.2010.02.011.
• Geldreich, E.E., K.R. Fox, J.A. Goodrich, E.W. Rice, R.M. Clark, and D.L. Swerdlow. 1992. Searching for a water supply connection in the Cabool, Missouri disease outbreak of Escherichia coli O157-H7. Water Research 26(8):1127-1137. doi: 10.1016/0043-1354(92)90150-3.
• Gibson, C.J., K.L. Stadterman, S. States, and J. Sykora. 1998. Combined sewer overflows: A source of cryptosporidium and giardia? Water Science and Technology 38(12):67-72. doi: 10.1016/s0273-1223(98)00802-6.
• Haley, B.J., D.J. Cole, and E.K. Lipp. 2009. Distribution, diversity, and seasonality of waterborne salmonellae in a rural watershed. Applied and Environmental Microbiology 75(5):1248-1255. doi: 10.1128/aem.01648-08.
• Hannah, D.M., and G. Garner. 2015. River water temperature in the United Kingdom: Changes over the 20th century and possible changes over the 21st century. Progress in Physical Geography 39(1):68-92. doi: 10.1177/0309133314550669.
• Harrus, S., and G. Baneth. 2005. Drivers for the emergence and re-emergence of vector-borne protozoal and bacterial diseases. International Journal for Parasitology 35(11-12):1309-1318. doi: 10.1016/j.ijpara.2005.06.005.
• Hayhoe, K., J. VanDorn, T. Croley, II, N. Schlegal, and D. Wuebbles. 2010. Regional climate change projections for Chicago and the U.S. Great Lakes. Journal of Great Lakes Research 36(Supplement 2):7-21. doi: 10.1016/j.jglr.2010.03.012.
• Hejkal, T.W., B. Keswick, R.L. Labelle, C.P. Gerba, Y. Sanchez, G. Dreesman, B. Hafkin, and J.L. Melnick. 1982. Viruses in a community water-supply associated with an outbreak of gastroenteritis and infectious-hepatitis. Journal American Water Works Association 74(6):318-321.
• Herrador, B.R.G., B.F. de Blasio, E. MacDonald, G. Nichols, B. Sudre, L. Vold, J.C. Semenza, and K. Nygard. 2015. Analytical studies assessing the association between extreme precipitation or temperature and drinking water-related waterborne infections: A review. Environmental Health 14:29. doi: 10.1186/s12940-015-0014-y.
• Hilborn, E.D., T.J. Wade, L. Hicks, L. Garrison, J. Carpenter, E. Adam, B. Mull, J. Yoder, V. Roberts, and J.W. Gargano. 2013. Surveillance for waterborne disease outbreaks associated with drinking water and other nonrecreational water - United States, 2009-2010. Morbidity & Mortality Weekly Report 62(35):714-720.
• Hill, R.A., C.P. Hawkins, and J. Jin. 2014. Predicting thermal vulnerability of stream and river ecosystems to climate change. Climatic Change 125(3-4):399-412. doi: 10.1007/s10584-014-1174-4.
• Hlavsa, M.C., V.A. Roberts, A.M. Kahler, E.D. Hilborn, T.J. Wade, L.C. Backer, and J.S. Yoder. 2014. Recreational water-associated disease outbreaks - United States, 2009-2010. Morbidity & Mortality Weekly Report 63(1):6-10.
• Hofstra, N. 2011. Quantifying the impact of climate change on enteric waterborne pathogen concentrations in surface water. Current Opinion in Environmental Sustainability 3(6):471-479. doi: 10.1016/j.cosust.2011.10.006.
• Horton, R., G. Yohe, W. Easterling, R. Kates, M. Ruth, E. Sussman, A. Whelchel, D. Wolfe, and F. Lipschultz. 2014. Northeast. Chapter 16 in Climate Change Impacts in the United States: The Third National Climate Assessment, ed. J.M. Melillo, T.C. Richmond and G.W. Yohe, pp. 371-395. U.S. Global Change Research Program, Washington, DC.
• Hoskisson, P.A., and J.T. Trevors. 2010. Shifting trends in pathogen dynamics on a changing planet. Antonie Van Leeuwenhoek International Journal of General and Molecular Microbiology 98(4):423-427. doi: 10.1007/s10482-010-9485-6.
• Hoxie, N.J., J.P. Davis, J.M. Vergeront, R.D. Nashold, and K.A. Blair. 1997. Cryptosporidiosis-associated mortality following a massive waterbome outbreak in Milwaukee, Wisconsin. American Journal of Public Health 87(12):2032-2035.
• Hunter, P.R. 2003. Climate change and waterborne and vector-borne disease. Journal of Applied Microbiology 94:37S-46S.
• IPCC (Intergovernmental Panel on Climate Change). 2000. Special Report on Emissions Scenarios. ed. N. Nakićenović and R. Swart. Cambridge University Press. Cambridge, United Kingdom. http://www.ipcc.ch/ipccreports/sres/emission/index.php?idp=0.
• IPCC (Intergovernmental Panel on Climate Change). 2013. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. ed. T.F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. http://www.ipcc.ch/report/ar5/wg1/.
• Jacobs, J.H., S.K. Moore, K.E. Kunkel, and L. Sun. 2015. A framework for examining climate-driven changes to the seasonality and geographical range of coastal pathogens and harmful algae. Climate Risk Management 8:16-27. doi: 10.1016/j.crm.2015.03.002.
• Jamieson, R.C., J.H. Lee, R. Kostaschuk, and R.J. Gordon. 2004. Persistence of enteric bacteria in alluvial streams. Journal of Environmental Engineering and Science 3(3):203-212. doi: 10.1139/s04-001.
• Jayakody, P., P.B. Parajuli, and J.P. Brooks. 2015. Assessing climate variability impact on thermotolerant coliform bacteria in surface water. Human and Ecological Risk Assessment 21(3):691-706. doi: 10.1080/10807039.2014.909188.
• Jha, M.K., P.W. Gassman, and Y. Panagopoulos. 2015. Regional changes in nitrate loadings in the Upper Mississippi River Basin under predicted mid-century climate. Regional Environmental Change 15(3):449-460. doi: 10.1007/s10113-013-0539-y.
• Jiang, C., K.S. Shaw, C.R. Upperman, D. Blythe, C. Mitchell, R. Murtugudde, A.R. Sapkota, and A. Sapkota. 2015. Climate change, extreme events and increased risk of salmonellosis in Maryland, USA: Evidence for coastal vulnerability. Environment International 83:58-62.
• Johnson, A.C., M.C. Acreman, M.J. Dunbar, S.W. Feist, A.M. Giacomello, R.E. Gozlan, S.A. Hinsley, A.T. Ibbotson, H.P. Jarvie, J.I. Jones, M. Longshaw, S.C. Maberly, T.J. Marsh, C. Neal, J.R. Newman, M.A. Nunn, R.W. Pickup, N.S. Reynard, C.A. Sullivan, J.P. Sumpter, and R.J. Williams. 2009. The British river of the future: How climate change and human activity might affect two contrasting river ecosystems in England. Science of the Total Environment 407(17):4787-4798. doi: 10.1016/j.scitotenv.2009.05.018.
• Johnson, T., J. Butcher, D. Deb, M. Faizullabhoy, P. Hummel, J. Kittle, S. McGinnis, L. O. Mearns, D. Nover, A. Parker, S. Sarkar, R. Srinivasan, P. Tuppad, M. Warren, C. Weaver, and J. Witt. 2015. Modeling streamflow and water quality sensitivity to climate change and urban development in 20 U.S. watersheds. Journal of the American Water Resources Association 51(5):1321-1341.
• Jung, A.V., P. Le Cann, B. Roig, O. Thomas, E. Baures, and M.F. Thomas. 2014. Microbial contamination detection in water resources: Interest of current optical methods, trends and needs in the context of climate change. International Journal of Environmental Research and Public Health 11(4):4292-4310. doi: 10.3390/ijerph110404292.
• Karvonen, A., P. Rintamaki, J. Jokela, and E.T. Valtonen. 2010. Increasing water temperature and disease risks in aquatic systems: Climate change increases the risk of some, but not all, diseases. International Journal for Parasitology 40(13):1483-1488. doi: 10.1016/j.ijpara.2010.04.015.
• Kim, J.W., Y.A. Pachepsky, D.R. Shelton, and C. Coppock. 2010. Effect of streambed bacteria release on E. coli concentrations: Monitoring and modeling with the modified SWAT. Ecological Modelling 221(12):1592-1604. doi: 10.1016/j.ecolmodel.2010.03.005.
• King, K.W., J.C. Balogh, and R.D. Harmel. 2007. Nutrient flux in stormwater runoff and baseflow from managed turf. Environmental Pollution 150:321-328.
• Kistemann, T., T. Classen, C. Koch, F. Dangendorf, R. Fischeder, J. Gebel, V. Vacata, and M. Exner. 2002. Microbial load of drinking water reservoir tributaries during extreme rainfall and runoff. Applied and Environmental Microbiology 68(5):2188-2197. doi: 10.1128/aem.68.5.2188-2197.2002.
• Koirala, S.R., R.W. Gentry, E. Perfect, J.S. Schwartz, and G.S. Sayler. 2008. Temporal variation and persistence of bacteria in streams. Journal of Environmental Quality 37(4):1559-1566. doi: 10.2134/jeq2007.0310.
• Kratt, K., D. Maraldo, and B. Cleland. 2010. Climate Change and TMDLs: Anticipating Potential Effects/Weighing Options. In Watershed Management Conference 2010, American Society of Civil Engineers, Madison, Wisconsin, August 23-27, 2010, pp.35-45, http://dx.doi.org/10.1061/41143(394)4
• Kunkel, K.E., T.R. Karl, H. Brooks, J. Kossin, J.H. Lawrimore, D. Arndt, L. Bosart, D. Changnon, S.L. Cutter, N. Doesken, K.Y. Emanuel, P.Y. Groisman, R.W. Katz, T. Knutson, J. O'Brien, C.J. Paciorek, T.C. Peterson, K. Redmond, D. Robinson, J. Trapp, R. Vose, S. Weaver, M. Wehner, K. Wolter, and D. Wuebbles. 2013. Monitoring and understanding trends in extreme storms: State of knowledge. Bulletin of the American Meteorological Society 94(4):499-514. doi: 10.1175/bams-d-11-00262.1.
• Kyle, R.E., and T.P. Brabets. 2001. Water Temperature of Streams in the Cook Inlet Basin, Alaska, and Implications of Climate Change. Water-Resources Investigations Report 01-4109. U.S. Department of the Interior, U.S. Geological Survey. Anchorage, Alaska.
• Leight, A.K., R. Hood, R. Wood, and K. Brohawn. 2016. Climate relationships to fecal bacterial densities in Maryland shellfish harvest waters. Water Research 89:270-281. doi: 10.1016/j.watres.2015.11.055.
• Leland, D., J. McAnulty, W. Keene, and G. Stevens. 1993. A cryptosporidiosis outbreak in a filtered-water supply. Journal American Water Works Association 85(6):34-42.
• Leong, J.-A., J.J. Marra, M.L. Finucane, T. Giambelluca, M. Merrifield, S.E. Miller, J. Polovina, E. Shea, M. Burkett, J. Campbell, P. Lefale, F. Lipschultz, L. Loope, D. Spooner, and B. Wang. 2014. Hawai'i and U.S. Affiliated Pacific Islands. Chapter 23 in Climate Change Impacts in the United States: The Third National Climate Assessment, ed. J.M. Melillo, T.C. Richmond and G.W. Yohe, pp. 537-556. U.S. Global Change Research Program, Washington, DC.
• Levin, R.B., P.R. Epstein, T.E. Ford, W. Harrington, E. Olson, and E.G. Reichard. 2002. U.S. drinking water challenges in the twenty-first century. Environmental Health Perspectives 110:43-52.
• Li, Z., R.M. Clark, S.G. Buchberger, and Y.Y. Jeffrey. 2014. Evaluation of climate change impact on drinking water treatment plant operation. Journal of Environmental Engineering 140(9):A4014005. doi: 10.1061/(asce)ee.1943-7870.0000824.
• Lin, S., M. Sun, E. Fitzgerald, and S.-A. Hwang. 2016. Did summer weather factors affect gastrointestinal infection hospitalizations in New York State? Science of the Total Environment 550:38-44. doi: 10.1016/j.scitotenv.2015.12.153.
• Lipp, E.K., A. Huq, and R.R. Colwell. 2002. Effects of global climate on infectious disease: The cholera model. Clinical Microbiology Reviews 15(4):757-770. doi: 10.1128/cmr.15.4.757-770.2002.
• Lippy, E.C. 1981. Waterborne disease--Occurrence is on the upswing. Journal American Water Works Association 73(1):57-62.
• Liu, Z.J., N.B. Hashim, W.L. Kingery, and D.H. Huddleston. 2010. Fecal coliform modeling under two flow scenarios in St. Louis Bay of Mississippi. Journal of Environmental Science and Health, Part A: Toxic/Hazardous Substances & Environmental Engineering 45(3):282-291. doi: 10.1080/10934520903467949.
• MacKenzie, W.R., N.J. Hoxie, M.E. Proctor, M.S. Gradus, K.A. Blair, D.E. Peterson, J.J. Kazmierczak, D.G. Addiss, K.R. Fox, J.B. Rose, and J.P. Davis. 1994. A massive outbreak in Milwaukee of cryptosporidium infection transmitted through the public water supply. New England Journal of Medicine 331(3):161-167. doi: 10.1056/NEJM199407213310304.
• Mallin, M.A., L.B. Cahoon, B.R. Toothman, D.C. Parsons, M.R. McIver, M.L. Ortwine, and R.N. Harrington. 2007. Impacts of a raw sewage spill on water and sediment quality in an urbanized estuary. Marine Pollution Bulletin 54(1):81-88. doi: 10.1016/j.marpolbul.2006.09.003.
• Mallin, M.A., K.E. Williams, E.C. Esham, and R.P. Lowe. 2000. Effect of human development on bacteriological water quality in coastal watersheds. Ecological Applications 10(4):1047-1056. doi: 10.2307/2641016.
• Mancini, J.L. 1978. Numerical estimates of coliform mortality-rates under various conditions. Journal Water Pollution Control Federation 50(11):2477-2484.
• Mandrell, R.E. 2011. Tracing Pathogens in Fruit and Vegetable Production Chains. Chapter 23 in Tracing Pathogens in the Food Chain, ed. S. Brul, P.M. Fratamico and T.A. Mcmeekin, pp. 548-595. Woodhead Publishing, Cambridge, UK.
• Marcheggiani, S., C. Puccinelli, S. Ciadamidaro, V. Della Bella, M. Carere, M. F. Blasi, N. Pacini, E. Funari, and L. Mancini. 2010. Risks of water-borne disease outbreaks after extreme events. Toxicological and Environmental Chemistry 92(3):593-599.
• Martinez-Urtaza, J., J.C. Bowers, J. Trinanes, and A. DePaola. 2010. Climate anomalies and the increasing risk of Vibrio parahaemolyticus and Vibrio vulnificus illnesses. Food Research International 43(7):1780-1790. doi: 10.1016/j.foodres.2010.04.001.
• Matthews, H.S., R. Hulitt, T. Paul, T. Jones, J.G. Wheeler, and D.T. Haselow. 2014. Environmental Investigation and Response to Second Naegleria Fowleri Case Associated with a Community Water Park in Arkansas July 2013. In 2014 Council of State and Territorial Epidemiologists Annual Conference, Nashville, Tennessee, June 22-26, 2014.
• McBride, G., A. Tait, and D. Slaney. 2014. Projected changes in reported campylobacteriosis and cryptosporidiosis rates as a function of climate change: A New Zealand study. Stochastic Environmental Research and Risk Assessment 28(8):2133-2147. doi: 10.1007/s00477-014-0920-5.
• McLellan, S.L., E.J. Hollis, M.M. Depas, M. Van Dyke, J. Harris, and C.O. Scopel. 2007. Distribution and fate of Escherichia coli in Lake Michigan following contamination with urban stormwater and combined sewer overflows. Journal of Great Lakes Research 33(3):566-580. doi: 10.3394/0380-1330(2007)33[566:dafoec]2.0.co;2.
• Melillo, J.M., T.C. Richmond, and G.W. Yohe (eds.). 2014. Climate Change Impacts in the United States: The Third National Climate Assessment. U.S. Global Change Research Program. Washington, DC.
• Milly, P.C.D., K.A. Dunne, and A.V. Vecchia. 2005. Global pattern of trends in streamflow and water availability in a changing climate. Nature 438(7066):347-350. doi: 10.1038/nature04312.
• Morris, R.D., E.N. Naumova, R. Levin, and R.L. Munasinghe. 1996. Temporal variation in drinking water turbidity and diagnosed gastroenteritis in Milwaukee. American Journal of Public Health 86(2):237-239. doi: 10.2105/ajph.86.2.237.
• Mote, P., A.K. Snover, S. Capalbo, S.D. Eigenbrode, P. Glick, J. Littell, R. Raymondi, and S. Reeder. 2014. Northwest. Chapter 21 in Climate Change Impacts in the United States: The Third National Climate Assessment, ed. J.M. Melillo, T.C. Richmond and G.W. Yohe, pp. 487-513. U.S. Global Change Research Program, Washington, DC.
• Mueller, B., S.I. Seneviratne, C. Jimenez, T. Corti, M. Hirschi, G. Balsamo, P. Ciais, P. Dirmeyer, J.B. Fisher, Z. Guo, M. Jung, F. Maignan, M.F. McCabe, R. Reichle, M. Reichstein, M. Rodell, J. Sheffield, A.J. Teuling, K. Wang, E.F. Wood, and Y. Zhang. 2011. Evaluation of global observations-based evapotranspiration datasets and IPCC AR4 simulations. Geophysical Research Letters 38:L06402. doi: 10.1029/2010gl046230.
• Nardone, A., B. Ronchi, N. Lacetera, M.S. Ranieri, and U. Bernabucci. 2010. Effects of climate changes on animal production and sustainability of livestock systems. Livestock Science 130(1-3):57-69. doi: 10.1016/j.livsci.2010.02.011.
• Nasser, A.M., L. Telser, and Y. Nitzan. 2007. Effect of sunlight on the infectivity of Cryptosporidium parvum in seawater. Canadian Journal of Microbiology 53(9):1101-1105. doi: 10.1139/W07-043.
• Nichols, G., C. Lane, N. Asgari, N.Q. Verlander, and A. Charlett. 2009. Rainfall and outbreaks of drinking water related disease and in England and Wales. Journal of Water and Health 7(1):1-8. doi: 10.2166/wh.2009.143.
• NOAA (National Ocean and Atmospheric Administration). 2005. Frequently Asked Questions about the Atlantic Multidecadal Oscillation (AMO). Accessed May 10, 2015. http://www.aoml.noaa.gov/phod/amo_faq.php.
• Noble, R.T., I.M. Lee, and K.C. Schiff. 2004. Inactivation of indicator micro-organisms from various sources of faecal contamination in seawater and freshwater. Journal of Applied Microbiology 96(3):464-472. doi: 10.1111/j.1365-2672.2004.02155.x.
• Novello, A. 2000. The Washington County Fair Outbreak Report. New York Department of Health. Albany, NY.
• Novotny, E.V., and H.G. Stefan. 2007. Stream flow in Minnesota: Indicator of climate change. Journal of Hydrology 334(3-4):319-333. doi: 10.1016/j.jhydrol.2006.10.011.
• Novotny, V. 2003. Water Quality: Diffuse Pollution and Watershed Management. 2nd ed. John Wiley and Sons, Inc., Hoboken, NJ.
• Obeysekera, J., M. Irizarry, J. Park, J. Barnes, and T. Dessalegne. 2011. Climate change and its implications for water resources management in South Florida. Stochastic Environmental Research and Risk Assessment 25(4):495-516. doi: 10.1007/s00477-010-0418-8.
• Oliver, D.M., K.D. Porter, Y.A. Pachepsky, R.W. Muirhead, S.M. Reaney, R. Coffey, D. Kay, D.G. Milledge, E. Hong, S.G. Anthony, T. Page, J.W. Bloodworth, P.E. Mellander, P.E. Carbonneau, S.J. McGrane, and R.S. Quilliam. 2016. Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments. Science of the Total Environment 544:39-47. doi: 10.1016/j.scitotenv.2015.11.086.
• Olsen, S.J., G. Miller, T. Breuer, M. Kennedy, C. Higgins, J. Walford, G. McKee, K. Fox, W. Bibb, and P. Mead. 2002. A waterborne outbreak of Escherichia coli O157:H7 infections and hemolytic uremic syndrome: Implications for rural water systems. Emerging Infectious Diseases 8(4):370-375.
• Pachepsky, Y., D.R. Shelton, J.E.T. McLain, J. Patel, and R.E. Mandrell. 2011. Irrigation Waters as a Source of Pathogenic Microorganisms in Produce: A Review. Chapter 2 in Advances in Agronomy, Volume 113, pp. 73-138. Elsevier, Inc.
• Pandey, P.K., P.H. Kass, M.L. Soupir, S. Biswas, and V.P. Singh. 2014. Contamination of water resources by pathogenic bacteria. AMB Express 4(1):1-16. doi: 10.1186/s13568-014-0051-x.
• Pascual, M., X. Rodo, S.P. Ellner, R. Colwell, and M.J. Bouma. 2000. Cholera dynamics and El Nino-Southern Oscillation. Science 289(5485):1766-1769. doi: 10.1126/science.289.5485.1766.
• Patz, J.A. 2001. Public health risk assessment linked to climatic and ecological change. Human and Ecological Risk Assessment 7(5):1317-1327. doi: 10.1080/20018091095023.
• Patz, J.A., M.A. McGeehin, S.M. Bernard, K.L. Ebi, P.R. Epstein, A. Grambsch, D.J. Gubler, P. Reiter, I. Romieu, J.B. Rose, J.M. Samet, and J. Trtanj. 2000. The potential health impacts of climate variability and change for the United States: Executive summary of the report of the health sector of the U.S. National Assessment. Environmental Health Perspectives 108(4):367-376. doi: 10.2307/3454357.
• Patz, J.A., S.J. Vavrus, C.K. Uejio, and S.L. McLellan. 2008. Climate change and waterborne disease risk in the Great Lakes region of the US. American Journal of Preventive Medicine 35(5):451-458. doi: 10.1016/j.amepre.2008.08.026.
• Peng, M.M., L.H. Xiao, A.R. Freeman, M.J. Arrowood, A.A. Escalante, A.C. Weltman, C.S.L. Ong, W.R. MacKenzie, A.A. Lal, and C.B. Beard. 1997. Genetic polymorphism among Cryptosporidium parvum isolates: Evidence of two distinct human transmission cycles. Emerging Infectious Diseases 3(4):567-573.
• Pommepuy, M., J.F. Guillaud, E. Dupray, A. Derrien, F. Leguyader, and M. Cormier. 1992. Enteric bacteria survival factors. Water Science and Technology 25(12):93-103.
• Prein, A.F., R.M. Rasmussen, K. Ikeda, C. Liu, M.P. Clark, and G.J. Holland. 2016. The future intensification of hourly precipitation extremes. Nature Climate Change 7:48-52. doi: 10.1038/nclimate3168.
• Pryor, S.C., D. Scavia, C. Downer, M. Gaden, L. Iverson, R. Nordstrom, J. Patz, and G.P. Robertson. 2014. Midwest. Chapter 18 in Climate Change Impacts in the United States: The Third National Climate Assessment, ed. J.M. Melillo, T.C. Richmond and G.W. Yohe, pp. 418-440. U.S. Global Change Research Program, Washington, DC.
• Rhodes, M.W., and H. Kator. 1988. Survival of Escherichia-coli and Salmonella spp in estuarine environments. Applied and Environmental Microbiology 54(12):2902-2907.
• Rizak, S., and S.E. Hrudey. 2008. Drinking-water safety--Challenges for community-managed systems. Journal of Water and Health 6:33-41. doi: 10.2166/wh.2008.033.
• Rogers, S., and J. Haines. 2005. Detecting and Mitigating the Environmental Impact of Fecal Pathogens Originating from Confined Animal Feeding Operations: Review. EPA/600/R-06/021. U.S. Environmental Protection Agency, National Risk Management Research Laboratory, Land Remediation and Pollution Control Division. Cincinnati, OH.
• Rose, J.B., S. Daeschner, D.R. Easterling, F.C. Curriero, S. Lele, and J.A. Patz. 2000. Climate and waterborne disease outbreaks. Journal American Water Works Association 92(9):77-87.
• Rose, J.B., P.R. Epstein, E.K. Lipp, B.H. Sherman, S.M. Bernard, and J.A. Patz. 2001. Climate variability and change in the United States: Potential impacts on water- and foodborne diseases caused by microbiologic agents. Environmental Health Perspectives 109:211-221. doi: 10.2307/3435011.
• Schijven, J.F., and A.M.D. Husman. 2005. Effect of climate changes on waterborne disease in The Netherlands. Water Science and Technology 51(5):79-87.
• Schwartz, J., R. Levin, and K. Hodge. 1997. Drinking water turbidity and pediatric hospital use for gastrointestinal illness in Philadelphia. Epidemiology 8(6):615-620. doi: 10.1097/00001648-199710000-00001.
• Scopel, C.O., J. Harris, and S.L. McLellan. 2006. Influence of nearshore water dynamics and pollution sources on beach monitoring outcomes at two adjacent Lake Michigan beaches. Journal of Great Lakes Research 32(3):543-552. doi: 10.3394/0380-1330(2006)32[543:ionwda]2.0.co;2.
• Semenza, J.C., J.S. Caplan, G. Buescher, T. Das, M.V. Brinks, and A. Gershunov. 2012. Climate change and microbiological water quality at California beaches. Ecohealth 9(3):293-297. doi: 10.1007/s10393-012-0779-1.
• Senhorst, H.A.J., and J.J.G. Zwolsman. 2005. Climate change and effects on water quality: A first impression. Water Science and Technology 51(5):53-59.
• Shafer, M., D. Ojima, J.M. Antle, D. Kluck, R.A. McPherson, S. Petersen, B. Scanlon, and K. Sherman. 2014. Great Plains. Chapter 19 in Climate Change Impacts in the United States: The Third National Climate Assessment, ed. J.M. Melillo, T.C. Richmond and G.W. Yohe, pp. 441-461. U.S. Global Change Research Program, Washington, DC.
• Sherer, B.M., J.R. Miner, J.A. Moore, and J.C. Buckhouse. 1992. Indicator bacterial survival in stream sediments. Journal of Environmental Quality 21(4):591-595.
• Soller, J.A., M.E. Schoen, T. Bartrand, J.E. Ravenscroft, and N.J. Ashbolt. 2010. Estimated human health risks from exposure to recreational waters impacted by human and non-human sources of faecal contamination. Water Research 44(16):4674-4691. doi: 10.1016/j.watres.2010.06.049.
• Soupir, M., and P. Pandey. 2016. Sediment E. coli as a source of stream impairment. Resource: Engineering & Technology for a Sustainable World 23(2):4-5.
• Speelmon, E.C., W. Checkley, R.H. Gilman, J. Patz, M. Calderon, and S. Manga. 2000. Cholera incidence and El Nino-related higher ambient temperature. Journal of the American Medical Association 283(23):3072-3074. doi: 10.1001/jama.283.23.3072-a.
• St. Laurent, J., and A. Mazumder. 2014. Influence of seasonal and inter-annual hydro-meteorological variability on surface water fecal coliform concentration under varying land-use composition. Water Research 48:170-178. doi: 10.1016/j.watres.2013.09.031.
• Steele, M., and J. Odumeru. 2004. Irrigation water as source of foodborne pathogens on fruit and vegetables. Journal of Food Protection 67(12):2839-2849.
• Sterk, A., J. Schijven, T. de Nijs, and A.M.D. Husman. 2013. Direct and indirect effects of climate change on the risk of infection by water-transmitted pathogens. Environmental Science & Technology 47(22):12648-12660. doi: 10.1021/es403549s.
• Stewart, B.C., K.E. Kunkel, L.E. Stevens, L. Sun, and J.E. Walsh. 2013. Regional Climate Trends and Scenarios for the U.S. National Climate Assessment. Part 7. Climate of Alaska. NOAA Technical Report NESDIS 142-7. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service. Washington, DC.
• Strauch, A.M., R.A. Mackenzie, G.L. Bruland, R. Tingley, and C.P. Giardina. 2014. Climate change and land use drivers of fecal bacteria in tropical Hawaiian rivers. Journal of Environmental Quality 43(4):1475-1483.
• Sulaiman, I.M., L.H. Xiao, C.F. Yang, L. Escalante, A. Moore, C.B. Beard, M.J. Arrowood, and A.A. Lal. 1998. Differentiating human from animal isolates of Cryptosporidium parvum. Emerging Infectious Diseases 4(4):681-685.
• Swerdlow, D.L., B.A. Woodruff, R.C. Brady, P.M. Griffin, S. Tippen, H.D. Donnell, E. Geldreich, B.J. Payne, A. Meyer, J.G. Wells, K.D. Greene, M. Bright, N.H. Bean, and P.A. Blake. 1992. A waterborne outbreak in Missouri of Escherichia-coli-O157-H7 associated with bloody diarrhea and death. Annals of Internal Medicine 117(10):812-819.
• Taylor, J., K.M. Lai, M. Davies, D. Clifton, I. Ridley, and P. Biddulph. 2011. Flood management: Prediction of microbial contamination in large-scale floods in urban environments. Environment International 37(5):1019-1029. doi: 10.1016/j.envint.2011.03.015.
• TDOH (Texas Department of Health). 1999. Cryptosporidiosis at Brushy Creek. In Epidemiology in Texas: 1998 Annual Report. Austin, TX. http://www.tdh.state.tx.us/epidemiology.
• ten Veldhuis, J.A.E., F. Clemens, G. Sterk, and B.R. Berends. 2010. Microbial risks associated with exposure to pathogens in contaminated urban flood water. Water Research 44(9):2910-2918. doi: 10.1016/j.watres.2010.02.009.
• Trtanj, J., L. Jantarasami, J. Brunkard, T. Collier, J. Jacobs, E. Lipp, S. McLellan, S. Moore, H. Paerl, J. Ravenscroft, M. Sengco, and J. Thurston. 2016. Climate Impacts on Water-Related Illness. Chapter 6 in The Impacts of Climate Change on Human Health in the United States: A Scientific Assessment, pp. 157-188. U.S. Global Change Research Program, Washington, DC.
• Tryland, I., L. Robertson, A.G.B. Blankenberg, M. Lindholm, T. Rohrlack, and H. Liltved. 2011. Impact of rainfall on microbial contamination of surface water. International Journal of Climate Change Strategies and Management 3(4):361-373. doi: 10.1108/17568691111175650.
• Tu, J. 2009. Combined impact of climate and land use changes on streamflow and water quality in eastern Massachusetts, USA. Journal of Hydrology 379(3-4):268-283. doi: 10.1016/j.jhydrol.2009.10.009.
• Twilley, R.R., E. Barron, H.L. Gholz, M.A. Harwell, R.L. Miller, D.J. Reed, J.B. Rose, E. Siemann, R.G. Wetzel, and R.J. Zimmerman. 2001. Confronting Climate Change in the Gulf Coast Region: Prospects for Sustaining Our Ecological Heritage. Union of Concerned Scientists, Cambridge, MA and Ecological Society of America, Washington, DC.
• Tyrrel, S.F., and J.N. Quinton. 2003. Overland flow transport of pathogens from agricultural land receiving faecal wastes. Journal of Applied Microbiology 94(s1):87-93.
• Uejio, C.K., S.H. Yale, K. Malecki, M.A. Borchardt, H.A. Anderson, and J.A. Patz. 2014. Drinking water systems, hydrology, and childhood gastrointestinal illness in central and northern Wisconsin. American Journal of Public Health 104(4):639-646. doi: 10.2105/ajph.2013.301659.
• Urquhart, E.A., B.F. Zaitchik, D.W. Waugh, S.D. Guikema, and C.E. Del Castillo. 2014. Uncertainty in model predictions of Vibrio vulnificus response to climate variability and change: A Chesapeake Bay case study. PLoS One 9(5):e98256. doi: 10.1371/journal.pone.0098256.
• USEPA (U.S. Environmental Protection Agency). 1986. Ambient Water Quality Criteria for Bacteria – 1986. EPA 440/5-84-002. U.S. Environmental Protection Agency, Office of Water. Washington, DC.
• USEPA (U.S. Environmental Protection Agency). 2001. Protocol for Developing Pathogen TMDLs. EPA 841-R-00-002. U.S. Environmental Protection Agency, Office of Water. Washington, DC.
• USEPA (U.S. Environmental Protection Agency). 2002. An Overview of the Safe Drinking Water Act. PowerPoint presentation. U.S. Environmental Protection Agency. Washington, DC. https://cfpub.epa.gov/watertrain/pdf/sdwa.pdf.
• USEPA (U.S. Environmental Protection Agency). 2009a. Drinking Water Infrastructure Needs Survey and Assessment: Fourth Report to Congress. EPA 816-R-09-001. U.S. Environmental Protection Agency, Office of Water, Office of Ground Water and Drinking Water, Drinking Water Protection Division. Washington, DC.
• USEPA (U.S. Environmental Protection Agency). 2009b. Review of Zoonotic Pathogens in Ambient Waters. EPA 822-R-09-002. U.S. Environmental Protection Agency, Office of Water, Health and Ecological Criteria Division. Washington, DC.
• USEPA (U.S. Environmental Protection Agency). 2010. Quantitative Microbial Risk Assessment to Estimate Illness in Freshwater Impacted by Agricultural Animal Sources of Fecal Contamination. EPA 822-R-10-005. U.S. Environmental Protection Agency, Office of Water. Washington, DC.
• USEPA (U.S. Environmental Protection Agency). 2011. Exposure Factors Handbook: 2011 Edition. EPA/600/R-09/052F. U.S. Environmental Protection Agency, Office of Research and Development, National Center for Environmental Assessment. Washington, DC.
• USEPA (U.S. Environmental Protection Agency). 2012. Recreational Water Quality Criteria. EPA 820-F-12-058. U.S. Environmental Protection Agency, Office of Water. Washington, DC. http://water.epa.gov/scitech/swguidance/standards/criteria/health/recreation/upload/RWQC2012.pdf.
• USEPA (U.S. Environmental Protection Agency). 2013. Literature Review of Contaminants in Livestock and Poultry Manure and Implications for Water Quality. EPA 820-R-13-002. U.S. Environmental Protection Agency, Office of Water. Washington, DC.
• USEPA (U.S. Environmental Protection Agency). 2015. National Summary of State Information. Accessed June 19, 2015. http://ofmpub.epa.gov/waters10/attains_nation_cy.control.
• USEPA (U.S. Environmental Protection Agency). 2016. Table of Regulated Drinking Water Contaminants. https://www.epa.gov/ground-water-and-drinking-water/table-regulated-drinking-water-contaminants.
• Vavrus, S.J., and R.J. Behnke. 2014. A comparison of projected future precipitation in Wisconsin using global and downscaled climate model simulations: Implications for public health. International Journal of Climatology 34(10):3106-3124.
• Vermeulen, L.C., and N. Hofstra. 2014. Influence of climate variables on the concentration of Escherichia coli in the Rhine, Meuse, and Drentse Aa during 1985–2010. Regional Environmental Change 14(1):307-319. doi: 10.1007/s10113-013-0492-9.
• Vermeulen, L.C., N. Hofstra, C. Kroeze, and G.J. Medema. 2015. Advancing waterborne pathogen modelling: Lessons from global nutrient export models. Current Opinion in Environmental Sustainability 14:109-120.
• Vogt, R.L., H.E. Sours, T. Barrett, R.A. Feldman, R.J. Dickinson, and L. Witherell. 1982. Campylobacter enteritis associated with contaminated water. Annals of Internal Medicine 96(3):292-296.
• Walsh, J., D. Wuebbles, K. Hayhoe, J. Kossin, K. Kunkel, G. Stephens, P. Thorne, R. Vose, M. Wehner, J. Willis, D. Anderson, S. Doney, R. Feely, P. Hennon, V. Kharin, T. Knutson, F. Landerer, T. Lenton, J. Kennedy, and R. Somerville. 2014. Our Changing Climate. Chapter 2 in Climate Change Impacts in the United States: The Third National Climate Assessment, ed. J.M. Melillo, T.C. Richmond and G.W. Yohe, pp. 19-67. U.S. Global Change Research Program, Washington, DC.
• Weniger, B.G., M.J. Blaser, J. Gedrose, E.C. Lippy, and D.D. Juranek. 1983. An outbreak of waterborne giardiasis associated with heavy-water runoff due to warm weather and volcanic ashfall. American Journal of Public Health 73(8):868-872. doi: 10.2105/ajph.73.8.868.
• Whitman, R.L., and M.B. Nevers. 2003. Foreshore sand as a source of Escherichia coli in nearshore water of a Lake Michigan beach. Applied and Environmental Microbiology 69(9):5555-5562. doi: 10.1128/aem.69.9.5555-5562.2003.
• WHO (World Health Organization). 2003. Climate Change and Human Health: Risks and Responses. Edited by A.J. Mcmichael, D.H. Campbell-Lendrum, C.F. Corvalan, K.L. Ebi, A.K. Githeko, J.D. Scheraga and A. Woodward. World Health Organization, Geneva, Switzerland.
• Wilkes, G., T.A. Edge, V.P.J. Gannon, C. Jokinen, E. Lyautey, N.F. Neumann, N. Ruecker, A. Scott, M. Sunohara, E. Topp, and D.R. Lapen. 2011. Associations among pathogenic bacteria, parasites, and environmental and land use factors in multiple mixed-use watersheds. Water Research 45(18):5807-5825. doi: 10.1016/j.watres.2011.06.021.
• WMO (World Meteorological Organization). 2009. The Global Framework for Climate Services (GFCS). PowerPoint presentation. World Meteorological Organization, Global Framework for Climate Services (GFCS) Office. http://www.wmo.int/gfcs.
• Wu, J.Y., P. Rees, S. Storrer, K. Alderisio, and S. Dorner. 2009. Fate and transport modeling of potential pathogens: The contribution from sediments. Journal of the American Water Resources Association 45(1):35-44. doi: 10.1111/j.1752-1688.2008.00287.x.
• Yamahara, K.M., B.A. Layton, A.E. Santoro, and A.B. Boehm. 2007. Beach sands along the California coast are diffuse sources of fecal bacteria to coastal waters. Environmental Science & Technology 41(13):4515-4521. doi: 10.1021/es062822n.
• Zeleznik, B.B., B.C. Curk, and P. Souvent. 2011. Drinking Water Quality Under Changing Climate Conditions. in Water Quality: Current Trends and Expected Climate Change Impacts, ed. N.E. Peters, V. Krysanova, A. Lepisto, R. Prasad, M. Thoms, R. Wilby and S. Zandaryaa, pp. 101-105. International Association of Hydrological Sciences, Wallingford, Oxfordshire, UK.
• Ziemer, C.J., J.M. Bonner, D. Cole, J. Vinje, V. Constantini, S. Goyal, M. Gramer, R. Mackie, X.J. Meng, G. Myers, and L.J. Saif. 2010. Fate and transport of zoonotic, bacterial, viral, and parasitic pathogens during swine manure treatment, storage, and land application. Journal of Animal Science 88(13 Suppl):E84-94. doi: 10.2527/jas.2009-2331.
• Zwolsman, G., D. Vanham, P. Fleming, C. Davis, A. Lovell, D. Nolasco, O. Thorne, R. de Sutter, B. Fülöp, P. Staufer, and Å. Johannessen. 2011. Climate Change and the Water Industry – Practical Responses and Actions. International Water Association. London, UK.