Fecal Indicator Bacteria Concentrations Research Articles

Evaluating Microbial Water Quality and Potential Sources of Fecal Contamination in the Musconetcong River Watershed in New Jersey, USA

Microbial pathogens and indicators have contributed to major part of water quality degradation in the United States. Located in the northwestern New Jersey, the Musconetcong River has been included in the New Jersey Impaired Waters List or the 303(d) List due to high concentrations of fecal indicator bacteria. Hence, a Total Maximum Daily Load plan was established to address microbial water quality issues in the watershed. The objectives of this study were to assess the current status of microbial water quality and to determine potential sources of fecal contamination in the Musconetcong River Watershed using microbial source tracking techniques. Fifteen sampling events in total were carried out at nine sites throughout the Musconetcong River Watershed in August 2016, July and August 2017. E. coli enumeration was performed to determine the possible presence of fecal contaminations. Microbial source tracking techniques, specifically Canada goose, cow, deer, horse, and human-specific molecular markers, were used for real-time polymerase chain reaction (qPCR) analysis in order to identify and quantify potential sources of fecal contamination. The results indicated that E. coli was found present at all nine study sites. Two of the nine sites violated the New Jersey Surface Water Quality Standards in August 2016, while all of the nine sites exceeded the standards in both July and August 2017. Water temperature, dissolved oxygen (DO), and specific conductance at the study sites ranged from 13.5˚C to 25.3˚C, from 7.7 mg/L to 13.0 mg/L, and 278.5 μS/cm to 1335.0 μS/cm, respectively, at the time of sample collection. E. coli counts were found to be negatively correlated with temperature and specific conductance (p p < 0.05). Higher percentage of presence of human, Canada goose and deer markers were observed at all fifteen sampling events indicating human and wildlife were the two major sources of fecal contaminations in the Musconetcong River Watershed. The study suggested applying restoration measures to reduce fecal contaminations from anthropogenic and wildlife sources in order to improve microbial water quality of the Musconetcong River. However, more frequent and strategic sampling plan is recommended to supply more comprehensive data to aid in future planning of best management efforts on controlling fecal contaminations.

Intra-event variability of bacterial composition in stormwater runoff from mixed land use and land cover catchment

Microbial community and composition in stormwater runoff from mixed land use land cover (LULC) catchment with ongoing land development was diverse across the hydrological stage due different environmental parameters (hydrometeorological and physicochemical) and source of runoff. However, limited studies have been made for bacterial composition in this catchment. Therefore, this study aims to: (1) quantify the concentration of fecal indicator bacteria (FIB), stormwater quality and bacterial composition and structure according to hydrological stage; and (2) determine their correlation to environmental parameters. The 454 pyrosequencing was used to determine the bacterial community and composition; while Pearson\'s correlation was used to determine the correlation among parameters—FIB, stormwater quality, bacterial composition and structure-to environmental parameters. Results demonstrated that the initial and peak runoff has the highest concentration of FIB, stormwater quality and bacterial composition and structure. Proteobacteria, Bacteroidetes, Actinobacteria and Firmicutes were dominant bacteria identified in this catchment. Furthermore, the 20 most abundant genera were correlated with runoff duration, average rainfall intensity, runoff volume, runoff flow, temperature, pH, organic matter, nutrients, TSS and turbidity. An increase of FIB and stormwater quality concentration, diversity and richness of bacterial composition and structure in this study was possibly due to leakage from septic tanks, cesspools and latrines; feces of domestic and wild animals; and runoff from forest, destroyed septic system in land development site and urban LULC. Overall, this study will provide an evidence of hydrological stage impacts on the runoff microbiome environment and public health perspective.

Patterns of sediment-associated fecal indicator bacteria in an urban estuary: Benthic-pelagic coupling and implications for shoreline water quality

Estuarine and coastal waterways are commonly monitored for fecal and sewage contamination to protect recreator health and ecosystem functions. Such monitoring programs commonly rely on cultivation-based counts of fecal indicator bacteria (FIB) in water column samples. Recent studies demonstrate that sediments and beach sands can be heavily colonized by FIB, and that settling and resuspension of colonized particles may significantly influence the distribution of FIB in the water column. However, measurements of sediment FIB are rarely incorporated into monitoring programs, and geographic surveys of sediment FIB are uncommon. In this study, the distribution of FIB and the extent of benthic-pelagic FIB coupling were examined in the urbanized, lower Hudson River Estuary. Using cultivation-based enumeration, two commonly-measured FIB, enterococci and Escherichia coli, were widely distributed in both sediment and water, and were positively correlated with each other. The taxonomic identity of FIB isolates from water and sediment was confirmed by DNA sequencing. The geometric mean of FIB concentration in sediment was correlated with both the geometric mean of FIB in water samples from the same locations and with sediment organic carbon. These two positive associations likely reflect water as the FIB source for underlying sediments, and longer FIB persistence in the sediments compared to the water, respectively. The relative representation of other fecal associated bacterial genera in sediment, determined by 16S rRNA gene sequencing, increased with the sequence representation of the two FIB, supporting the value of these FIB for assessing sediment contamination. Experimental resuspension of sediment increased shoreline water column FIB concentrations, which may explain why shoreline water samples had higher average FIB concentrations than samples collected nearby but further from shore. In combination, these results demonstrate extensive benthic-pelagic coupling of FIB in an urbanized estuary and highlight the importance of sediment FIB distribution and ecology when interpreting water quality monitoring data.

Occurrence of Bacterial Pathogens and Human Noroviruses in Shellfish-Harvesting Areas and Their Catchments in France.

During a 2-year study, the presence of human pathogenic bacteria and noroviruses was investigated in shellfish, seawater and/or surface sediments collected from three French coastal shellfish-harvesting areas as well as in freshwaters from the corresponding upstream catchments. Bacteria isolated from these samples were further analyzed. Escherichia coli isolates classified into the phylogenetic groups B2, or D and enterococci from Enterococcus faecalis and E. faecium species were tested for the presence of virulence genes and for antimicrobial susceptibility. Salmonella members were serotyped and the most abundant serovars (Typhimurium and its monophasic variants and Mbandaka) were genetically characterized by high discriminative subtyping methods. Campylobacter and Vibrio were identified at the species level, and haemolysin-producing Vibrio parahaemolyticus were searched by tdh- and trh- gene detection. Main results showed a low prevalence of Salmonella in shellfish samples where only members of S. Mbandaka were found. Campylobacter were more frequently isolated than Salmonella and a different distribution of Campylobacter species was observed in shellfish compared to rivers, strongly suggesting possible additional inputs of bacteria. Statistical associations between enteric bacteria, human noroviruses (HuNoVs) and concentration of fecal indicator bacteria revealed that the presence of Salmonella was correlated with that of Campylobacter jejuni and/or C. coli as well as to E. coli concentration. A positive correlation was also found between the presence of C. lari and the detection of HuNoVs. This study highlights the importance of simultaneous detection and characterization of enteric and marine pathogenic bacteria and human noroviruses not only in shellfish but also in catchment waters for a hazard assessment associated with microbial contamination of shellfish.

Development of a Nowcasting System Using Machine Learning Approaches to Predict Fecal Contamination Levels at Recreational Beaches in Korea.

Microbial contamination in beach water poses a public health threat due to waterborne diseases. To reduce the risk of exposure to fecal contamination, informing beachgoers in advance about the microbial water quality is important. Currently, determining the level of fecal contamination takes 24 h. The objective of this study is to predict the current level of fecal contamination (enterococcus [ENT] and ) using readily available environmental variables. Artificial neural network (ANN) and support vector regression (SVR) models were constructed using data from the Haeundae and Gwangalli Beaches in Busan City. The input variables included the tidal level, air and water temperature, solar radiation, wind direction and velocity, precipitation, discharge from the wastewater treatment plant, and suspended solid concentration in beach water. The dependence of fecal contamination on the input variables was statistically evaluated; precipitation, discharge from the wastewater treatment plant, and wind direction at the two beaches were positively correlated to the changes in the two bacterial concentrations ( < 0.01), whereas solar radiation was negatively correlated ( < 0.01). The performance of the ANN model for predicting ENT and at Gwangalli Beach was significantly higher than that of the SVR model with the training dataset ( < 0.05). Based on the comparison of residual values between the predicted and observed fecal indicator bacteria concentrations in two models, the ANN demonstrated better performance than SVR. This study suggests an effective prediction method to determine whether a beach is safe for recreational use.

Detection of coliphages and human adenoviruses in a subtropical estuarine lake

Fecal indicator bacteria (FIB) have been used to assess fecal contamination in recreational water. However, enteric viruses have been shown to be more persistent in the environment and resistant to wastewater treatment than bacteria. Recently, U.S Environmental Protection Agency has proposed the use of coliphages as viral indicators to better protect against viral waterborne outbreaks. This study aimed to detect and determine correlation between coliphages (F-specific and somatic), fecal indicator bacteria (enterococci and fecal coliforms), and human enteric viruses (human adenovirus) in a subtropical brackish estuarine lake. Water samples were collected from 9 estuarine recreation sites on Lake Pontchartrain in southeast Louisiana. Water samples (n = 222, collected weekly) were analyzed for coliphages and fecal indicator bacteria using culture-based methods and large volume water samples (n = 54, collected monthly) were analyzed for human adenovirus using quantitative PCR. Somatic coliphage and F-specific coliphage were found in 93.7 and 65.2% of samples with geometric mean concentrations of 30 and 3 plaque forming units (PFU) per 100 mL, respectively. Enterococci, fecal coliforms, and adenovirus were found in all samples with geometric mean concentrations of 27 most probable number (MPN), 77 MPN, and 3.0 × 104 gene copies per 100 mL, respectively. Watersheds in suburban areas exhibited significantly higher concentrations of coliphages and fecal indicator bacteria, indicating potential fecal contamination from septic systems. There was no significant correlation (p > 0.05) observed between the presence of adenoviruses and fecal indicator bacteria and coliphages. The presence of human adenovirus in Lake Pontchartrain poses a significant public health problem for both recreational use and seafood harvesting as it increases exposure risks. This study demonstrated the lack of relationship between fecal indicators and human viral pathogen in Lake Pontchartrain supporting an alternative microbial surveillance system such as direct pathogen detection.

Determination of wild animal sources of fecal indicator bacteria by microbial source tracking (MST) influences regulatory decisions

Fecal indicator bacteria (FIB) are used to assess fecal pollution levels in surface water and are among the criteria used by regulatory agencies to determine water body impairment status. While FIB provide no information about pollution source, microbial source tracking (MST) does, which contributes to more direct and cost effective remediation efforts. We studied a watershed in Florida managed for wildlife conservation that historically exceeded the state regulatory guideline for fecal coliforms. We measured fecal coliforms, enterococci, a marker gene for avian feces (GFD), and a marker gene for human-associated Bacteroides (HF183) in sediment, vegetation, and water samples collected monthly from six sites over two years to: 1) assess the influence of site, temporal factors, and habitat (sediment, vegetation, and water) on FIB and MST marker concentrations, 2) test for correlations among FIB and MST markers, and 3) determine if avian feces and/or human sewage contributed to FIB levels. Sediment and vegetation had significantly higher concentrations of FIB and GFD compared to water and thus may serve as microbial reservoirs, providing unreliable indications of recent contamination. HF183 concentrations were greatest in water samples but were generally near the assay limit of detection. HF183-positive results were attributed to white-tailed deer (Odocoileus virginianus) feces, which provided a false indication of human sewage in this water body. FIB and GFD were positively correlated while FIB and HF183 were negatively correlated. We demonstrated that birds, not sewage, were the main source of FIB, thus avoiding implementation of a total maximum daily load program (TMDL). Our results demonstrate that the concomitant use of FIB and MST can improve decision-making and provide direction when water bodies are impaired, and provides a strategy for natural source exclusion in water bodies impacted by wild animal feces.

On the implementation of reliable early warning systems at European bathing waters using multivariate Bayesian regression modelling

For ensuring microbial safety, the current European bathing water directive (BWD) (76/160/EEC 2006) demands the implementation of reliable early warning systems for bathing waters, which are known to be subject to short-term pollution. However, the BWD does not provide clearly defined threshold levels above which an early warning system should start warning or informing the population. Statistical regression modelling is a commonly used method for predicting concentrations of fecal indicator bacteria. The present study proposes a methodology for implementing early warning systems based on multivariate regression modelling, which takes into account the probabilistic character of European bathing water legislation for both alert levels and model validation criteria. Our study derives the methodology, demonstrates its implementation based on information and data collected at a river bathing site in Berlin, Germany, and evaluates health impacts as well as methodological aspects in comparison to the current way of long-term classification as outlined in the BWD.

Precipitation influences pathogenic bacteria and antibiotic resistance gene abundance in storm drain outfalls in coastal sub-tropical waters

Stormwater contamination can threaten the health of aquatic ecosystems and human exposed to runoff via nutrient and pathogen influxes. In this study, the concentrations of 11 bacterial pathogens and 47 antibiotic resistance genes (ARGs) were determined by using high-throughput microfluidic qPCR (MFQPCR) in several storm drain outfalls (SDOs) during dry and wet weather in Tampa Bay, Florida, USA. Data generated in this study were also compared with the levels of fecal indicator bacteria (FIB) and sewage-associated molecular markers (i.e., Bacteroides HF183 and crAssphage markers) in same SDOs collected in a recent study (Ahmed et al., 2018). Concentration of FIB, sewage-associated markers, bacterial pathogens and many ARGs in water samples were relatively high and SDOs may be potentially hotspots for microbial contamination in Tampa Bay. Mean concentrations of culturable E. coli and Enterococcus spp. were tenfold higher in wet compared to dry weather. The majority of microbiological contaminants followed this trend. E. coli eaeA, encoding the virulence factor intimin, was correlated with levels of 20 ARGs, and was more frequently detected in wet weather than dry weather samples. The blaKPC gene associated with carbapenem resistant Enterobacteriaceae and the beta-lactam resistant gene (blaNPS) were only detected in wet weather samples. Frequency of integron genes Intl2 and Intl3 detection increased by 42% in wet weather samples. Culturable E. coli and Enterococcus spp. significantly correlated with 19 of 47 (40%) ARG tested. Sewage-associated markers crAssphage and HF183 significantly correlated (p < 0.05) with the following ARGs: intl1, sul1, tet(M), ampC, mexB, and tet(W). The presence of sewage-associated marker genes along with ARGs associated with sewage suggested that aging sewage infrastructure contributed to contaminant loading in the Bay. Further research should focus on collecting spatial and temporal data on the microbiological contaminants especially viruses in SDOs.

Hydrogeological controls of variable microbial water quality in a complex subtropical karst system in Northern Vietnam

Karst aquifers are particularly vulnerable to bacterial contamination. Especially in developing countries, poor microbial water quality poses a threat to human health. In order to develop effective groundwater protection strategies, a profound understanding of the hydrogeological setting is crucial. The goal of this study was to elucidate the relationships between high spatio-temporal variability in microbial contamination and the hydrogeological conditions. Based on extensive field studies, including mapping, tracer tests and hydrochemical analyses, a conceptual hydrogeological model was developed for a remote and geologically complex karst area in Northern Vietnam called Dong Van. Four different physicochemical water types were identified; the most important ones correspond to the karstified Bac Son and the fractured Na Quan aquifer. Alongside comprehensive investigation of the local hydrogeology, water quality was evaluated by analysis for three types of fecal indicator bacteria (FIB): Escherichia coli, enterococci and thermotolerant coliforms. The major findings are: (1) Springs from the Bac Son formation displayed the highest microbial contamination, while (2) springs that are involved in a polje series with connections to sinking streams were distinctly more contaminated than springs with a catchment area characterized by a more diffuse infiltration. (3) FIB concentrations are dependent on the season, with higher values under wet season conditions. Furthermore, (4) the type of spring capture also affects the water quality. Nevertheless, all studied springs were faecally impacted, along with several shallow wells within the confined karst aquifer. Based on these findings, effective protection strategies can be developed to improve groundwater quality.

Comparison of pathogen-derived ‘total risk’ with indicator-based correlations for recreational (swimming) exposure

Typical recreational water risk to swimmers is assessed using epidemiologically derived correlations by means of fecal indicator bacteria (FIB). It has been documented that concentrations of FIB do not necessarily correlate well with protozoa and viral pathogens, which pose an actual threat of illness and thus sometimes may not adequately assess the overall microbial risks from water resources. Many of the known pathogens have dose-response relationships; however, measuring water quality for all possible pathogens is impossible. In consideration of a typical freshwater receiving secondarily treated effluent, we investigated the level of consistency between the indicator-derived correlations and the sum of risks from six reference pathogens using a quantitative microbial risk assessment (QMRA) approach. Enterococci and E. coli were selected as the benchmark FIBs, and norovirus, human adenovirus (HAdV), Campylobacter jejuni, Salmonella enterica, Cryptosporidium spp., and Giardia spp. were selected as the reference pathogens. Microbial decay rates in freshwater and uncertainties in exposure relationships were considered in developing our analysis. Based on our exploratory assessment, the total risk was found within the range of risk estimated by the indicator organisms, with viral pathogens as dominant risk agents, followed by protozoan and bacterial pathogens. The risk evaluated in this study captured the likelihood of gastrointestinal illnesses only, and did not address the overall health risk potential of recreational waters with respect to other disease endpoints. Since other highly infectious pathogens like hepatitis A and Legionella spp. were not included in our analysis, these estimates should be interpreted with caution.

Spatial distribution of sewage pollution on a Hawaiian coral reef

While sewage pollution is contributing to the global decline of coral reefs, its offshore extent and direct reef impacts from water column mixing and benthic seeps are poorly documented. We addressed this knowledge gap on a Hawaiian coral reef using sewage indicator and benthic cover measurements, macroalgal bioassays, and a pollution scoring tool. Fecal indicator bacteria (FIB) and nutrient concentrations were spatially variable in surface and benthic waters, with shoreline values being highest. Shoreline macroalgae δ15N and %N indicated high nitrogen loads containing sewage, while offshore surface and benthic values suggested lower nitrogen loads from environmental sources. Coral cover was negatively correlated with FIB, macroalgal δ15N, and nutrient concentrations. Benthic salinity and temperature measurements detected daily tidal groundwater pulses which may explain these associations. While pollution scores revealed that sewage was largely concentrated along the shoreline, results showed some reached the reef and may be contributing to its declining condition.

Quantification of pathogens and markers of fecal contamination during storm events along popular surfing beaches in San Diego, California

Along southern California beaches, the concentrations of fecal indicator bacteria (FIB) used to quantify the potential presence of fecal contamination in coastal recreational waters have been previously documented to be higher during wet weather conditions (typically winter or spring) than those observed during summer dry weather conditions. FIB are used for management of recreational waters because measurement of the bacterial and viral pathogens that are the potential causes of illness in beachgoers exposed to stormwater can be expensive, time-consuming, and technically difficult. Here, we use droplet digital Polymerase Chain Reaction (digital PCR) and digital reverse transcriptase PCR (digital RT-PCR) assays for direct quantification of pathogenic viruses, pathogenic bacteria, and source-specific markers of fecal contamination in the stormwater discharges. We applied these assays across multiple storm events from two different watersheds that discharge to popular surfing beaches in San Diego, CA. Stormwater discharges had higher FIB concentrations as compared to proximal beaches, often by ten-fold or more during wet weather. Multiple lines of evidence indicated that the stormwater discharges contained human fecal contamination, despite the presence of separate storm sewer and sanitary sewer systems in both watersheds. Human fecal source markers (up to 100% of samples, 20-12440 HF183 copies per 100 ml) and human norovirus (up to 96% of samples, 25-495 NoV copies per 100 ml) were routinely detected in stormwater discharge samples. Potential bacterial pathogens were also detected and quantified: Campylobacter spp. (up to 100% of samples, 16-504 gene copies per 100 ml) and Salmonella (up to 25% of samples, 6-86 gene copies per 100 ml). Other viral human pathogens were also measured, but occurred at generally lower concentrations: adenovirus (detected in up to 22% of samples, 14-41 AdV copies per 100 ml); no enterovirus was detected in any stormwater discharge sample. Higher concentrations of avian source markers were noted in the stormwater discharge located immediately downstream of a large bird sanctuary along with increased Campylobacter concentrations and notably different Campylobacter species composition than the watershed that had no bird sanctuary. This study is one of the few to directly measure an array of important bacterial and viral pathogens in stormwater discharges to recreational beaches, and provides context for stormwater-based management of beaches during high risk wet-weather periods. Furthermore, the combination of culture-based and digital PCR-derived data is demonstrated to be valuable for assessing hydrographic relationships, considering delivery mechanisms, and providing foundational exposure information for risk assessment.

Comparative predictive modelling of the occurrence of faecal indicator bacteria in a drinking water source in Norway

Presently, concentrations of fecal indicator bacteria (FIB) in raw water sources are not known before water undergoes treatment, since analysis takes approximately 24h to produce results. Using data on water quality and environmental variables, models can be used to predict real time concentrations of FIB in raw water. This study evaluates the potentials of zero-inflated regression models (ZI), Random Forest regression model (RF) and adaptive neuro-fuzzy inference system (ANFIS) to predict the concentration of FIB in the raw water source of a water treatment plant in Norway. The ZI, RF and ANFIS faecal indicator bacteria predictive models were built using physico-chemical (pH, temperature, electrical conductivity, turbidity, color, and alkalinity) and catchment precipitation data from 2009 to 2015. The study revealed that pH, temperature, turbidity, and electrical conductivity in the raw water were the most significant factors associated with the concentration of FIB in the raw water source. Compared to the other models, the ANFIS model was superior (Mean Square Error=39.49, 0.35, 0.09, 0.23CFU/100ml respectively for coliform bacteria, E. coli, Intestinal enterococci and Clostridium perfringens) in predicting the variations of FIB in the raw water during model testing. However, the model was not capable of predicting low counts of FIB during both training and testing stages of the models. The ZI and RF models were more consistent when applied to testing data, and they predicted FIB concentrations that characterized the observed FIB concentrations. While these models might need further improvement, results of this study indicate that ZI and RF regression models have high prospects as tools for the real-time prediction of FIB in raw water sources for proactive microbial risk management in water treatment plants.

A multi-indicator approach for identifying shoreline sewage pollution hotspots adjacent to coral reefs

Sewage pollution is contributing to the global decline of coral reefs. Identifying locations where it is entering waters near reefs is therefore a management priority. Our study documented shoreline sewage pollution hotspots in a coastal community with a fringing coral reef (Puakō, Hawai'i) using dye tracer studies, sewage indicator measurements, and a pollution scoring tool. Sewage reached shoreline waters within 9 h to 3 d. Fecal indicator bacteria concentrations were high and variable, and δ15N macroalgal values were indicative of sewage at many stations. Shoreline nutrient concentrations were two times higher than those in upland groundwater. Pollution hotspots were identified with a scoring tool using three sewage indicators. It confirmed known locations of sewage pollution from dye tracer studies. Our study highlights the need for a multi-indicator approach and scoring tool to identify sewage pollution hotspots. This approach will be useful for other coastal communities grappling with sewage pollution.

Fecal Contamination on Produce from Wholesale and Retail Food Markets in Dhaka, Bangladesh.

Fresh produce items can become contaminated with enteric pathogens along the supply chain at the preharvest (e.g., irrigation water, soil, fertilizer) or postharvest (e.g., vendor handling or consumer handling) stages. This study assesses the concentrations of fecal indicator bacteria Escherichia coli, enterococci (ENT), and Bacteriodales on surfaces of carrots, eggplants, red amaranth leaves, and tomatoes obtained from both a wholesale market (recently harvested) and neighborhood retail markets in Dhaka, Bangladesh. We detected E. coli in 100% of carrot and red amaranth rinses, 92% of eggplant rinses, and 46% of tomato rinses. Using a molecular microbial source tracking assay, we found that 32% of produce samples were positive for ruminant fecal contamination. Fecal indicator bacteria were more likely to be detected on produce collected in retail markets compared with that in the wholesale market; retail market produce were 1.25 times more likely to have E. coli detected (P = 0.03) and 1.24 times more likely to have ENT detected (P = 0.03) as compared with wholesale market produce. Bacteriodales was detected in higher concentrations in retail market produce samples compared with wholesale market produce samples (0.40 log10 gene copies per 100 cm2 higher, P = 0.03). Our results suggest that ruminant and general fecal contamination of produce in markets in Dhaka is common, and suggest that unsanitary conditions in markets are an important source of produce fecal contamination postharvest.

Modelling the impact of future socio-economic and climate change scenarios on river microbial water quality.

Microbial surface water quality is important, as it is related to health risk when the population is exposed through drinking, recreation or consumption of irrigated vegetables. The microbial surface water quality is expected to change with socio-economic development and climate change. This study explores the combined impacts of future socio-economic and climate change scenarios on microbial water quality using a coupled hydrodynamic and water quality model (MIKE21FM-ECOLab). The model was applied to simulate the baseline (2014-2015) and future (2040s and 2090s) faecal indicator bacteria (FIB: E. coli and enterococci) concentrations in the Betna river in Bangladesh. The scenarios comprise changes in socio-economic variables (e.g. population, urbanization, land use, sanitation and sewage treatment) and climate variables (temperature, precipitation and sea-level rise). Scenarios have been developed building on the most recent Shared Socio-economic Pathways: SSP1 and SSP3 and Representative Concentration Pathways: RCP4.5 and RCP8.5 in a matrix. An uncontrolled future results in a deterioration of the microbial water quality (+75% by the 2090s) due to socio-economic changes, such as higher population growth, and changes in rainfall patterns. However, microbial water quality improves under a sustainable scenario with improved sewage treatment (-98% by the 2090s). Contaminant loads were more influenced by changes in socio-economic factors than by climatic change. To our knowledge, this is the first study that combines climate change and socio-economic development scenarios to simulate the future microbial water quality of a river. This approach can also be used to assess future consequences for health risks.

Spatial and temporal variability of bacterial indicators and pathogens in six California reservoirs during extreme drought

California has one of the largest systems of surface water reservoirs in the world, providing irrigation water to California's agriculturally productive Central Valley. Irrigation water is recognized as a vehicle for the microbial contamination of raw produce and must be monitored according to new federal regulation. The purpose of this study was to further understanding of the variability of fecal indicator bacteria (Escherichia coli and fecal coliforms) and pathogens (E. coli O157:H7 (O157), non-O157 Shiga toxin-producing E. coli (STEC) and Salmonella) along both horizontal and vertical profiles within California reservoirs. Monthly sampling was conducted in six reservoirs located in the foothills of the Western Sierra Nevada during the summer irrigation season and extreme drought conditions of 2014 (n = 257). Concentrations of fecal indicator bacteria were highly variable between reservoirs (p < 0.05) and along the horizontal profile (p < 0.001) from upstream to downstream, with higher concentrations typically found outside of the reservoirs than within. Though many of the reservoirs were thermally stratified, bacterial concentrations were not associated with water temperature (p > 0.05) or any one particular depth strata (p < 0.05). However, prevalence of Salmonella and STEC (16/70 and 9/70 respectively) was higher in the deep strata than in mid or surface layers. We found no statistical association between samples collected downstream of reservoirs and those from the reservoirs themselves. Continued monitoring and modeling of both bacterial indicators and enteric pathogens are critical to our ability to estimate the risk of surface irrigation water supplies and make appropriate management decisions.

The application of bacteriophages as novel indicators of viral pathogens in wastewater treatment systems

Many wastewater treatment technologies have been shown to remove bacterial pathogens more effectively than viral pathogens and, in aquatic environments, levels of traditional faecal indicator bacteria (FIB) do not appear to correlate consistently with levels of human viral pathogens. There is, therefore, a need for novel viral indicators of faecal pollution and surrogates of viral pathogens, especially given the increasing importance of indirect and direct wastewater reuse. Potential candidates include bacteriophages (phages) and the study described here sought to elucidate the relationship between three groups of phages (somatic coliphages (SOMPH), F-RNA coliphages (F-RNAPH) and human-specific phages infecting B. fragilis (Bf124PH) – enumeration using double layer agar technique) and viral pathogens (human adenovirus (HuAdV) and norovirus (NoV) – enumeration using molecular methods) through full-scale municipal wastewater treatment processes. FIB (faecal coliforms (FC) and intestinal enterococci (ENT) – enumeration using membrane filtration) were also monitored. Samples were collected every fortnight, during a twelve-month period, at each stage of four full-scale wastewater treatment plants (WWTP) in southern England (two activated sludge (AS) and two trickling filter (TF) plants) (n = 360 samples). FIB and SOMPH were consistently found in all samples tested, whereas F-RNAPH, Bf124PH and HuAdV were less frequently detected, especially following AS treatment. The detection rate of NoV was low and consequently discussion of this group of viruses is limited. Concentrations of SOMPH and FIB were statistically higher (p value < 0.05) than concentrations of F-RNAPH, Bf124PH and HuAdV in raw wastewater. FIB were more effectively removed than phages in both systems. Removal rates of HuAdV were similar to those of phages at the secondary treatment stage of both systems. In TF systems, HuAdV were removed at the same rate as F-RNAPH, but at lower rates than SOMPH and Bf124PH. The findings suggest that phages (in particular SOMPH) are better indicators of the fate of viral pathogens in WWTP than existing FIB and that these organisms may have a useful role to play in future sanitation safety planning.

Development and evaluation of the bacterial fate and transport module for the Agricultural Policy/Environmental eXtender (APEX) model

The Agricultural Policy/Environmental eXtender (APEX) is a watershed-scale water quality model that includes detailed representation of agricultural management. The objective of this work was to develop a process-based model for simulating the fate and transport of manure-borne bacteria on land and in streams with the APEX model. The bacteria model utilizes manure erosion rates to estimate the amount of edge-of-field bacteria export. Bacteria survival in manure is simulated as a two-stage process separately for each manure application event. In-stream microbial fate and transport processes include bacteria release from streambeds due to sediment resuspension during high flow events, active release from the streambed sediment during low flow periods, bacteria settling with sediment, and survival. Default parameter values were selected from published databases and evaluated based on field observations. The APEX model with the newly developed microbial fate and transport module was applied to simulate fate and transport of the fecal indicator bacterium Escherichia coli in the Toenepi watershed, New Zealand that was monitored for seven years. The stream network of the watershed ran through grazing lands with daily bovine waste deposition. Results show that the APEX with the bacteria module reproduced well the monitored pattern of E. coli concentrations at the watershed outlet. The APEX with the microbial fate and transport module will be utilized for predicting microbial quality of water as affected by various agricultural practices, evaluating monitoring protocols, and supporting the selection of management practices based on regulations that rely on fecal indicator bacteria concentrations.