Using SWAT, Bacteroidales microbial source tracking markers, and fecal indicator bacteria to predict waterborne pathogen occurrence in an agricultural watershed

Using watershed characteristics to enhance fecal source identification

Fecal pollution is one of the most prevalent forms of pollution affecting waterbodies worldwide, threatening public health and negatively impacting aquatic environments. Microbial source tracking (MST) applies polymerase chain reaction (PCR) technology to help identify the source of fecal pollution. In this study, we combine spatial data for two watersheds with general and host-associated MST markers to target human (HF183/BacR287), bovine (CowM2), and general ruminant (Rum2Bac) sources. Concentrations of MST markers in samples were determined with droplet digital PCR (ddPCR). The three MST markers were detected at all sites (n = 25), but bovine and general ruminant markers were significantly associated with watershed characteristics. MST results, combined with watershed characteristics, suggest that streams draining areas with low-infiltration soil groups and high agricultural land use are at an increased risk for fecal contamination. Microbial source tracking has been applied in numerous studies to aid in identifying the sources of fecal contamination, but these studies usually lack information on the involvement of watershed characteristics. Our study combined watershed characteristics with MST results to provide more comprehensive insight into the factors that influence fecal contamination in order to implement the most effective best management practices.

Microbial water quality at contrasting recreational areas in a mixed-use watershed in eastern Canada

Recreational water use is an important source of human enteric illness. Enhanced (episodic) surveillance of natural recreational waters as a supplement to beach monitoring can enrich our understanding of human health risks. From 2011 to 2013, water sampling was undertaken at recreational sites on a watershed in eastern Canada. This study compared the prevalence and associations of human enteric pathogens and fecal indicator organisms. Beach water samples had lower pathogen presence than those along the main river, due to different pollution sources and the hydrological disposition. Pathogen profiles identified from the beach sites suggested a more narrow range of sources, including birds, indicating that wild bird management could help reduce public health risks at these sites. The presence and concentration of indicator organisms did not differ significantly between beaches and the river. However, higher concentrations of generic Escherichia coli were observed when Salmonella and Cryptosporidium were present at beach sites, when Salmonella was present at the river recreational site, and when verotoxigenic E. coli were present among all sites sampled. In this watershed, generic E. coli concentrations were good indicators of potential contamination, pathogen load, and elevated human health risk, supporting their use for routine monitoring where enhanced pathogen testing is not possible.

Modelling Watershed and River Basin Processes in Cold Climate Regions: A Review

Watersheds in cold regions provide water, food, biodiversity and ecosystem service. However, the increasing demand for water resources and climate change challenge our ability to provide clean freshwater. Particularly, watersheds in cold regions are more sensitive to changing climate due to their glaciers’ retreat and permafrost. This review revisits watershed system and processes. We analyze principles of watershed modelling and characteristics of watersheds in cold regions. Then, we show observed evidence of their impacts of cold processes on hydrological and biogeochemical processes and ecosystems, and review the watershed modeling and their applications in cold regions. Finally, we identify the knowledge gaps in modeling river basins according to model structures and representations of processes and point out research priorities in future model development.

Evaluation of the soil and water assessment tool (SWAT) for simulating E. coli concentrations at the watershed-scale

Water quality management at the watershed level requires a framework to identify sources, apportion water quality risks and develop mitigation strategies to reduce health risks. Watershed-scale models have been used as a support tool to understand the sources, fate and transport of fecal bacteria and pathogens in the environment. The Soil and Water Assessment Tool (SWAT) model was applied in this study to understand the sources and drivers of microbial water quality in the Clouds Creek watershed in Georgia, USA. A criterion to evaluate the performance of the SWAT bacterial model was also developed in this study using the Nash-Sutcliffe Efficiency (NSE) performance measure. The SWAT model was successfully calibrated and validated for flow with Nash-Sutcliffe Efficiency (NSE) of 0.81 and 0.55, respectively. Escherichia coli (E. coli) predictions were good with NSE of 0.32 and 0.34 for the calibration and validation timeframes, respectively. Based on the criteria developed in this study, SWAT bacterial model for E. coli and fecal coliform can be judged as "satisfactory" when NSE > 0.20. The contribution of sources followed this order: in-stream cattle manure deposition > cattle manure application > poultry manure application > septic systems > wildlife manure, suggesting that a reduction in livestock access to streams would be the most effective approach to reduce fecal bacterial loads in this watershed and others impacted by fecal contamination. Finally, our results suggest that the SWAT model is capable of simulating E. coli dynamics in the Clouds Creek watershed and can provide insights into source impacts for risk management.

Real-time quantitative PCR assay development and application for assessment of agricultural surface water and various fecal matter for prevalence of Aliarcobacter faecis and Aliarcobacter lanthieri

BACKGROUND

Aliarcobacter faecis and Aliarcobacter lanthieri are recently identified as emerging human and animal pathogens. In this paper, we demonstrate the development and optimization of two direct DNA-based quantitative real-time PCR assays using species-specific oligonucleotide primer pairs derived from rpoB and gyrA genes for A. faecis and A. lanthieri, respectively. Initially, the specificity of primers and amplicon size of each target reference strain was verified and confirmed by melt curve analysis. Standard curves were developed with a minimum quantification limit of 100 cells mL^- 1 or g^- 1 obtained using known quantities of spiked A. faecis and A. lanthieri reference strains in autoclaved agricultural surface water and dairy cow manure samples.

RESULTS

Each species-specific qPCR assay was validated and applied to determine the rate of prevalence and quantify the total number of cells of each target species in natural surface waters of an agriculturally-dominant and non-agricultural reference watershed. In addition, the prevalence and densities were determined for human and various animal (e.g., dogs, cats, dairy cow, and poultry) fecal samples. Overall, the prevalence of A. faecis for surface water and feces was 21 and 28%, respectively. The maximum A. faecis concentration for water and feces was 2.3 × 10⁷ cells 100 mL^{- 1} and 1.2 × 10⁷ cells g^- 1, respectively. A. lanthieri was detected at a lower frequency (2%) with a maximum concentration in surface water of 4.2 × 10⁵ cells 100 mL^- 1; fecal samples had a prevalence and maximum density of 10% and 2.0 × 10⁶ cells g^- 1, respectively.

CONCLUSIONS

The results indicate that the occurrence of these species in agricultural surface water is potentially due to fecal contamination of water from livestock, human, or wildlife as both species were detected in fecal samples. The new real-time qPCR assays can facilitate rapid and accurate detection in < 3 h to quantify total numbers of A. faecis and A. lanthieri cells present in various complex environmental samples.

Verification of Bacteroidales 16S rRNA markers as a complementary tool for detecting swine fecal pollution in the Yangtze Delta

To correctly assess and properly manage the public health risks associated with exposure to contaminated water, it is necessary to identify the source of fecal pollution in a watershed. In this study, we evaluated the efficacy of our two previously developed real time-quantitative PCR (qPCR) assays for the detection of swine-associated Bacteroidales genetic markers (gene 1-38, gene 3-53) in the Yangtze Delta watershed of southeastern China. The results indicated that the gene 1-38 and 3-53 markers exhibited high accuracy (92.5%, 91.7% conditional probability, respectively) in detecting Bacteroidales spp. in water samples. According to binary logistic regression (BLR), these two swine-associated markers were well correlated (P < 0.05) with fecal indicators (Escherichia coli and Enterococci spp.) and zoonotic pathogens (E. coli O157: H7, Salmonella spp. and Campylobacter spp.) in water samples. In contrast, concentrations of conventional fecal indicator bacteria (FIB) were not correlated with zoonotic pathogens, suggesting that they are noneffective at detecting fecal pollution events. Collectively, the results obtained in this study demonstrated that a swine-targeted qPCR assay based on two Bacteroidales genes markers (gene 1-38, gene 3-53) could be a useful tool in determining the swine-associated impacts of fecal contamination in a watershed.

Applicability of water quality models around the world-a review

Water quality models are important tools used in the management of water resources. The models are usually developed for specific regions, with particular climates and physical characteristics. Thus, applying these models in regions other than those they were designed for can generate large simulation errors. With consideration to these discrepancies, the goal of this study is to identify the models employed in different countries and assist researchers in the selection of the most appropriate models for management purposes. Published studies from the last 21 years (1997-2017) that discuss the application of water quality models were selected from three engineering databases: SpringerLink, Web of Science, and Scopus. Seven models for water quality simulations have been widely applied around the world: AQUATOX, CE-QUAL-W2, EFDC, QUALs, SWAT, SPARROW, and WASP. The countries most frequently applying water quality models are the USA, followed by China, and South Korea. SWAT was the most used model, followed by the QUAL group and CE-QUAL-W2. This study provides the opportunity for researchers, who wish to study countries with fewer cases of applied water quality models, to easily identify the work from that region. Furthermore, this work collated central themes of interest and the most simulated parameters for the seven countries that most frequently employed the water quality models.

Estimating cumulative wastewater treatment plant discharge influences on acesulfame and Escherichia coli in a highly impacted watershed with a fully-integrated modelling approach

Wastewater treatment plant (WWTP) discharge is often considered a principal source of surface water contamination. In this study, a three-dimensional fully-integrated groundwater-surface water model was used to simulate the transport characteristics and cumulative loading of an artificial sweetener (acesulfame) and fecal indicator bacteria (Escherichia coli) from WWTPs within a 6800 km² mixed-use, highly impacted watershed in Ontario, Canada. The model, which employed 3.5 × 10⁶ computational nodes and 15 layers, facilitated a comprehensive assessment of groundwater-surface water interactions under high and low flow conditions; processes typically not accounted for in WWTP cumulative effects models. Simulations demonstrate that the model had significant capacity in reproducing the average and transient multi-year groundwater and surface water flow conditions in the watershed. As a proxy human-specific conservative tracer, acesulfame was useful for model validation and to help inform the representation of watershed-scale transport processes. Using a uniform WWTP acesulfame loading rate of 7.14 mg person^-1 day^-1, the general spatial trends and magnitudes of the acesulfame concentration profile along the main river reach within the watershed were reproduced; however, model performance was improved by tuning individual WWTP loading rates. Although instream dilution and groundwater-surface water interactions were strongly dependent on flow conditions, the main reach primarily consisted of groundwater discharge zones. For this reason, hydrodynamic dispersion in the hyporheic zone is shown as the predominant mechanism driving acesulfame into near-stream shallow groundwater, while under high flow conditions, the simulations demonstrate the potential for advective flushing of the shallow groundwater. Regarding the cumulative impact of the WWTPs on E. coli concentrations in the surface flow system, simulated transient E. coli levels downstream of WWTPs in the watershed were significantly lower than observed values, thus highlighting the potential importance of other sources of E. coli in the watershed.

Do reductions in agricultural field drainage during the growing season impact bacterial densities and loads in small tile-fed watersheds?

Predicting bacterial levels in watersheds in response to agricultural beneficial management practices (BMPs) requires understanding the germane processes at both the watershed and field scale. Controlling subsurface tile drainage (CTD) is a highly effective BMP at reducing nutrient losses from fields, and watersheds when employed en masse, but little work has been conducted on CTD effects on bacterial loads and densities in a watershed context. This study compared fecal indicator bacteria (FIB) [E. coli, Enterococcus, Fecal coliform, Total coliform, Clostridium perfringens] densities and unit area loads (UAL) from a pair of flat tile-drained watersheds (∼250-467 ha catchment areas) during the growing season over a 10-year monitoring period, using a before-after-control-impact (BACI) design (i.e., test CTD watershed vs. reference uncontrolled tile drainage (UCTD) watershed during a pre CTD intervention period and a CTD-intervention period where the test CTD watershed had CTD deployed on over 80% of the fields). With no tile drainage management, upstream tile drainage to ditches comprised ∼90% of total ditch discharge. We also examined FIB loads from a subset of tile drained fields to determine field load contributions to the watershed drainage ditches. Statistical evidence of a CTD effect on FIB UAL in the surface water systems was not strong; however, there was statistical evidence of increased FIB densities [pronounced when E. coli >200 most probable number (MPN) 100 mL^-1] in the test CTD watershed during the CTD-intervention period. This was likely a result of reduced dilution/flushing in the test CTD watershed ditch due to CTD significantly decreasing the amount of tile drainage water entering the surface water system. Tile E. coli load contributions to the ditches were low; for example, during the 6-yr CTD-intervention period they amounted to on average only ∼3 and ∼9% of the ditch loads for the test CTD and reference UCTD watersheds, respectively. This suggests in-stream, or off-field FIB reservoirs and bacteria mobilization drivers, dominated ditch E. coli loads in the watersheds during the growing season. Overall, this study suggested that decision making regarding deployment of CTD en masse in tile-fed watersheds should consider drainage practice effects on bacterial densities and loads, as well as CTD's documented capacity to boost crop yields and reduce seasonal nutrient pollution.

Linking landscape patterns to sources of water contamination: Implications for tracking fecal contaminants with geospatial and Bayesian approaches

Microbial source tracking (MST) techniques have been designed to identify the host source of fecal contamination in water. However, current MST techniques cannot provide geographic origins of particular sources because they do not provide any spatial information beyond the points of observation. In this study, the associations between landscape patterns and the major sources of microbial contamination were examined and the application of geospatial techniques (e.g., remote sensing and geographic information systems) and Bayesian modeling was explored to track microbial sources over the landscape. The land cover information of three watersheds (the lower Dungeness Watershed, the Middle Rio Grande Watershed, and the Arroyo Burro Watershed) in the United States was obtained either by classifying high resolution satellite images or directly using land cover datasets (e.g., National Land Cover Dataset, 2006 and 2011). Then, the relationship between land use/land cover (LULC) and microbial sources from these three geographically disparate watersheds were analyzed using Bayesian hierarchical models. The results showed the predictive positive associations between human sources of fecal contamination and developed area, between dog sources and grassland, and between bird sources and water, but negative associations between human sources and forest and water areas. Furthermore, the diversity of microbial sources had positive associations with landscape fragmentation and diversity indices. This study demonstrates associations between landscape patterns and major microbial sources and offers new insight in tracking the dominant sources of fecal contamination in water using geospatial and Bayesian techniques.

Fecal source tracking methods to elucidate critical sources of pathogens and contaminant microbial transport through New Zealand agricultural watersheds - A review

In New Zealand, there is substantial potential for microbial contaminants from agricultural fecal sources to be transported into waterways. The flow and transport pathways for fecal contaminants vary at a range of scales and is dependent on chemical, physical and biological attributes of pathways, soils, microorganisms and landscape characteristics. Understanding contaminant transport pathways from catchment to stream can aid water management strategies. It is not practical, however to conduct direct field measurement for all catchments on the fate and transport of fecal pathogens due to constraints on time, personnel, and material resources. To overcome this problem, fecal source tracking can be utilised to link catchment characteristics to fecal signatures identifying critical sources. In this article, we have reviewed approaches to identifying critical sources and pathways for fecal microorganisms from agricultural sources, and make recommendations for the appropriate use of these fecal source tracking (FST) tools.

Explaining and modeling the concentration and loading of Escherichia coli in a stream-A case study

Escherichia coli (E. coli) level in streams is a public health indicator. Therefore, being able to explain why E. coli levels are sometimes high and sometimes low is important. Using citizen science data from Fall Creek in central NY we found that complementarily using principal component analysis (PCA) and partial least squares (PLS) regression provided insights into the drivers of E. coli and a mechanism for predicting E. coli levels, respectively. We found that stormwater, temperature/season and shallow subsurface flow are the three dominant processes driving the fate and transport of E. coli. PLS regression modeling provided very good predictions under stormwater conditions (R² = 0.85 for log (E. coli concentration) and R² = 0.90 for log (E. coli loading)); predictions under baseflow conditions were less robust. But, in our case, both E. coli concentration and E. coli loading were significantly higher under stormwater condition, so it is probably more important to predict high-flow E. coli hazards than low-flow conditions. Besides previously reported good indicators of in-stream E. coli level, nitrate-/nitrite-nitrogen and soluble reactive phosphorus were also found to be good indicators of in-stream E. coli levels. These findings suggest management practices to reduce E. coli concentrations and loads in-streams and, eventually, reduce the risk of waterborne disease outbreak.

Dynamics of culturable mesophilic bacterial communities of three fresh herbs and their production environment

AIM

Investigate dynamics of culturable mesophilic bacteria and selected food-contaminating bacteria from three herbs and their production environment.

METHODS AND RESULTS

Marjoram, basil and thyme were investigated during one growing season by sampling plants, organic fertilizers, soil, irrigation water and marketed products. Mesophilic bacteria and selected food-contaminating bacteria (Escherichia coli, Enterococcus spp., Bacillus cereus group) were cultured and identified by MALDI biotyping. Culturable mesophilic bacteria on marjoram and basil plants decreased over time by two orders of magnitude starting at above 10⁶ colony forming units per gram (CFU per g), while they remained constant on thyme (~10⁴  CFU per g). Compared to the last field sample, mesophilic bacteria were increased on all market-ready products by one order of magnitude. Marjoram and basil were dominated by B. cereus group, Enterobacter spp. and Pseudomonas spp., thyme by Bacillus spp. and Pseudomonas spp. All selected food-contaminating bacteria were detected in soil and reservoir-sourced irrigation water, whereas in municipal water, only B. cereus group and rarely Enterococcus spp. were found. Escherichia coli was detected only on young marjoram and basil plants (5 × 10² and 5 × 10¹  CFU per g, respectively), whereas Enterococcus spp. and B. cereus group were consistently detected on these two herbs. Thyme plants only contained B. cereus group consistently (above 10³ CFU per g). Marketed marjoram and thyme contained Enterococcus spp. (5 × 10² and 10⁴ CFU per g) and B. cereus group (~5 × 10² CFU per g), while no selected food-contaminating bacteria were found on marketed basil.

CONCLUSIONS

Overall, culturable mesophilic bacteria were dominated by Pseudomonas spp. and Bacillus spp., with increased numbers on market-ready products. Selected food-contaminating bacteria were readily detectable, however, only the B. cereus group was found throughout in all systems.

SIGNIFICANCE AND IMPACT OF THE STUDY

Insight into composition and development of mesophilic bacterial communities and selected food-contaminating bacteria of fresh herbs contributes to estimating consumer exposure.

Predicting fecal coliform using the interval-to-interval approach and SWAT in the Miyun watershed, China

Pathogens in manure can cause waterborne-disease outbreaks, serious illness, and even death in humans. Therefore, information about the transformation and transport of bacteria is crucial for determining their source. In this study, the Soil and Water Assessment Tool (SWAT) was applied to simulate fecal coliform bacteria load in the Miyun Reservoir watershed, China. The data for the fecal coliform were obtained at three sampling sites, Chenying (CY), Gubeikou (GBK), and Xiahui (XH). The calibration processes of the fecal coliform were conducted using the CY and GBK sites, and validation was conducted at the XH site. An interval-to-interval approach was designed and incorporated into the processes of fecal coliform calibration and validation. The 95% confidence interval of the predicted values and the 95% confidence interval of measured values were considered during calibration and validation in the interval-to-interval approach. Compared with the traditional point-to-point comparison, this method can improve simulation accuracy. The results indicated that the simulation of fecal coliform using the interval-to-interval approach was reasonable for the watershed. This method could provide a new research direction for future model calibration and validation studies.

The INCA-Pathogens model: An application to the Loimijoki River basin in Finland

Good hygienic quality of surface waters is essential for drinking water production, irrigation of crops and recreation. Predictions of how and when microbes are transported by rivers are needed to protect downstream water users. In this study we tested the new process-based INCA-Pathogens model in the agricultural Loimijoki River basin (3138km²) in Finland, and we quantified ecosystem services of water purification and water provisioning for drinking and recreation purposes under different scenarios. INCA is a catchment scale process based model to calculate pollutant transfer from terrestrial environment and point sources to the catchment outlet. A clear gradient was observed in the numbers of faecal coliforms along the River Loimijoki. The highest bacterial counts were detected in the middle part of the main stream immediately after small industries and municipal sewage treatment plants. In terms of model performance, the INCA-Pathogen model was able to produce faecal coliform counts and seasonality both in the low pollution level sampling points and in the high pollution level sampling points. The model was sensitive to the parameters defining light decay in river water and in soil compartment, as well as to the amount of faecal coliforms in the manure spread on the fields. The modeling results showed that the number of faecal coliforms repeatedly exceeded 1000 bacteria 100ml^-1. Moreover, results lead to the following conclusions: 1) Climate change does not cause a major threat to hygienic water quality as higher precipitation increases runoff and causes diluting effect in the river, 2) Intensification of agriculture is not a threat as long as animal density remains relatively low and environmental legislation is followed, 3) More intensive agriculture without environmental legislation causes a threat especially in tributaries with high field percentage and animal density, and 4) Hygienic water quality in the River Loimijoki can best be improved by improving sewage treatment. We conclude that this catchment scale model is a useful tool for addressing catchment management and water treatment planning issues.

Characterizing relationships among fecal indicator bacteria, microbial source tracking markers, and associated waterborne pathogen occurrence in stream water and sediments in a mixed land use watershed

Bed sediments of streams and rivers may store high concentrations of fecal indicator bacteria (FIB) and pathogens. Due to resuspension events, these contaminants can be mobilized into the water column and affect overall water quality. Other bacterial indicators such as microbial source tracking (MST) markers, developed to determine potential sources of fecal contamination, can also be resuspended from bed sediments. The primary objective of this study was to predict occurrence of waterborne pathogens in water and streambed sediments using a simple statistical model that includes traditionally measured FIB, environmental parameters and source allocation, using MST markers as predictor variables. Synoptic sampling events were conducted during baseflow conditions downstream from agricultural (AG), forested (FORS), and wastewater pollution control plant (WPCP) land uses. Concentrations of FIB and MST markers were measured in water and sediments, along with occurrences of the enteric pathogens Campylobacter, Listeria and Salmonella, and the virulence gene that carries Shiga toxin, stx2. Pathogens were detected in water more often than in underlying sediments. Shiga toxin was significantly related to land use, with concentrations of the ruminant marker selected as an independent variable that could correctly classify 76% and 64% of observed Shiga toxin occurrences in water and sediment, respectively. FIB concentrations and water quality parameters were also selected as independent variables that correctly classified Shiga toxin occurrences in water and sediment (54%-87%), and Salmonella occurrences in water (96%). Relationships between pathogens and indicator variables were generally inconsistent and no single indicator adequately described occurrence of all pathogens. Because of inconsistent relationships between individual pathogens and FIB/MST markers, incorporating a combination of FIB, water quality measurements, and MST markers may be the best way to assess microbial water quality in mixed land use systems.

Spatiotemporal Analysis of Microbiological Contamination in New York State Produce Fields following Extensive Flooding from Hurricane Irene, August 2011

Although flooding introduces microbiological, chemical, and physical hazards onto croplands, few data are available on the spatial extent, patterns, and development of contamination over time postflooding. To address this paucity of information, we conducted a spatially explicit study of Escherichia coli and Salmonella contamination prevalence and genetic diversity in produce fields after the catastrophic flooding that occurred in New England during 2011. Although no significant differences were detected between the two participating farms, both random forest and logistic regression revealed changes in the spatial pattern of E. coli contamination in drag swab samples over time. Analyses also indicated that E. coli detection was associated with changes in farm management to remediate the land after flooding. In particular, E. coli was widespread in drag swab samples at 21 days postflooding, but the spatial pattern changed by 238 days postflooding such that E. coli was then most prevalent in close proximity to surface water features. The combined results of several population genetics analyses indicated that over time postflooding E. coli populations on the farms (i) changed in composition and (ii) declined overall. Salmonella was primarily detected in surface water features, but some Salmonella strains were isolated from soil and drag swab samples at 21 and 44 days postflooding. Although postflood contamination and land management responses should always be evaluated in the context of each unique farm landscape, our results provide quantitative data on the general patterns of contamination after flooding and support the practice of establishing buffer zones between flood-contaminated cropland and harvestable crops in produce fields.

Quantifying faecal indicator organism hydrological transfer pathways and phases in agricultural catchments

Faecal indicator organisms (FIOs) can impact on water quality and pose a health and environmental risk. The transfer of FIOs, such as Escherichia coli (E. coli), from land to water is driven by hydrological connectivity and may follow the same flowpaths as nutrients, from agricultural and human sources. This study investigated E. coli transfer in two catchment areas with high source and transport pressures. These pressures were: organic phosphorus (P) loading; human settlement; conduits and fissures in a grassland karst area; and clay rich and impermeable soils in a mixed arable area. The occurrence of E. coli and its transport pathways, along with the pathways of nutrients, were studied using a combination of targeted FIO sampling, during different hydrological phases and events, and high resolution nutrient analysis. The quick flow component in both catchments was found to be a more potent vector for E. coli, and was coincident with the total P flowpaths using a P Loadograph Recession Analysis (LRA). The karst grassland catchment was found to be a transport limited system and the mixed arable catchment a source limited system. Hence, despite the grassland catchment being a potentially higher FIO source, the E. coli loads leaving the catchment were low compared to the mixed arable catchment. E. coli load whole-event comparisons also indicated that the grassland karst transfers tended to be much lower on falling phases of runoff, while the arable catchment, over greywacke and mudstone geology, showed little change between the phases. Furthermore, the arable catchment showed asymptotic decline of sustained E. coli loads towards low flows, which may be indicative of chronic point sources. These results indicate the dominance of transport mechanisms over source mechanisms for mass E. coli loads and also chronic loads during low flow. These will be important considerations for risk assessment and mitigation.

Rainfall-induced runoff from exposed streambed sediments: an important source of water pollution

When surface water levels decline, exposed streambed sediments can be mobilized and washed into the water course when subjected to erosive rainfall. In this study, rainfall simulations were conducted over exposed sediments along stream banks at four distinct locations in an agriculturally dominated river basin with the objective of quantifying the potential for contaminant loading from these often overlooked runoff source areas. At each location, simulations were performed at three different sites. Nitrogen, phosphorus, sediment, fecal indicator bacteria, pathogenic bacteria, and microbial source tracking (MST) markers were examined in both prerainfall sediments and rainfall-induced runoff water. Runoff generation and sediment mobilization occurred quickly (10-150 s) after rainfall initiation. Temporal trends in runoff concentrations were highly variable within and between locations. Total runoff event loads were considered large for many pollutants considered. For instance, the maximum observed total phosphorus runoff load was on the order of 1.5 kg ha. Results also demonstrate that runoff from exposed sediments can be a source of pathogenic bacteria. spp. and spp. were present in runoff from one and three locations, respectively. Ruminant MST markers were also present in runoff from two locations, one of which hosted pasturing cattle with stream access. Overall, this study demonstrated that rainfall-induced runoff from exposed streambed sediments can be an important source of surface water pollution.

Long-term monitoring of waterborne pathogens and microbial source tracking markers in paired agricultural watersheds under controlled and conventional tile drainage management

Surface waters from paired agricultural watersheds under controlled tile drainage (CTD) and uncontrolled tile drainage (UCTD) were monitored over 7 years in order to determine if there was an effect of CTD (imposed during the growing season) on occurrences and loadings of bacterial and viral pathogens, coliphages, and microbial source tracking markers. There were significantly lower occurrences of human, ruminant, and livestock (ruminant plus pig) Bacteroidales markers in the CTD watershed in relation to the UCTD watershed. As for pathogens, there were significantly lower occurrences of Salmonella spp. and Arcobacter spp. in the CTD watershed. There were no instances where there were significantly higher quantitative loadings of any microbial target in the CTD watershed, except for F-specific DNA (F-DNA) and F-RNA coliphages, perhaps as a result of fecal inputs from a hobby farm independent of the drainage practice treatments. There was lower loading of the ruminant marker in the CTD watershed in relation to the UCTD system, and results were significant at the level P = 0.06. The odds of Salmonella spp. occurring increased when a ruminant marker was present relative to when the ruminant marker was absent, yet for Arcobacter spp., the odds of this pathogen occurring significantly decreased when a ruminant marker was present relative to when the ruminant marker was absent (but increased when a wildlife marker was present relative to when the wildlife marker was absent). Interestingly, the odds of norovirus GII (associated with human and swine) occurring in water increased significantly when a ruminant marker was present relative to when a ruminant marker was absent. Overall, this study suggests that fecal pollution from tile-drained fields to stream could be reduced by CTD utilization.

Relationship between water quality parameters and bacterial indicators in a large prairie reservoir: Lake Diefenbaker, Saskatchewan, Canada

Lake Diefenbaker (LD) is a large reservoir on the South Saskatchewan River used for agricultural irrigation, drinking water, and recreation. Our objectives were to determine the distribution and abundance of bacterial indicators in embayments and the main channel of LD and to relate these to environmental factors. Total coliforms (TCs), fecal coliforms (FCs), and fecal indicator bacteria (i.e., Escherichia coli) were measured concurrently with water quality parameters. Although TCs, FCs, and E. coli were present in LD, they rarely exceeded the TC and FC Canadian Council of Ministers of the Environment (CCME) water quality standards for agricultural use (1000 colony-forming units (CFU) per 100 mL and 100 CFU per 100 mL, respectively). The correlation between the bacterial indicators in the sediments and the water column indicates that higher embayment abundances may be related to sediment loading and (or) resuspension events in these frequently mixed embayments. With higher water temperatures and water levels, as well as higher microbial activity, CCME bacterial limits may be exceeded. The greatest contributor to bacterial indicator abundance was water temperature. We predict that water quality standards will be exceeded more frequently with climate warming.