Microbial water pollution: a screening tool for initial catchment-scale assessment and source apportionment

Short-term forecasting of fecal coliforms in shellfish growing waters

This study sought to develop models for predicting near-term (1-3 day) fecal contamination events in coastal shellfish growing waters. Using Random Forest regression, we (1) developed fecal coliform (FC) concentration models for shellfish growing areas using watershed characteristics and antecedent hydrologic and meteorologic observations as predictors, (2) tested the change in model performance associated when forecasted, as opposed to measured, rainfall variables were used as predictors, and (3) evaluated model predictor importance in relation to shellfish sanitation management criteria. Models were trained to 10 years of coastal FC measurements (n = 1285) for 5 major shellfish management areas along the Florida (USA) coast. Model performance varied between the 5 management areas with R2 ranging from 0.36 to 0.72. Antecedent precipitation variables were among the most important predictors in the day-of forecast models in all management areas. When forecasted rainfall was included in the models, wind components became increasingly important.

Model development and initial characterization of Escherichia coli in the shellfish-producing area of Butrinti Lagoon

The purpose of this research was to estimate the correlation between hydrochemicals and Escherichia coli contamination in Mytilus galloprovincialis by using multi-linear regression and statistically processing the monthly mean results. This study was conducted in a traditional cultivation of M. galloprovincialis, sampled and analyzed (n=136) for E. coli microbial analysis with ISO 16649-3. From 2015 to 2017, seawater was measured with a multiparameter apparatus, where four variables [dissolved oxygen (n=115), temperature (n=127) and pH (n=115), salinity (n=127), and local area rainfall monitoring (n=23)] were taken into consideration. The results were compared and shown to have a significant correlation, allowing for the quantification of the impact resulting from adjustments made to the monthly mean computation. During the study period, statistical performance for each year was estimated R2=94.4% (2015), R2=46.8%, and R2=97.5% (2017).

Indexes for the assessment of bacterial pollution in bathing waters from point sources: The northern Adriatic Sea CADEAU service

This paper presents a novel set of water quality indexes to identify the area potentially affected by point sources of bacterial pollution in coastal bathing waters. The indexes, developed in the framework of the CADEAU service, are evaluated on the results of a modelling system based on the integration of a high-resolution ocean model, remote sensing observations and in situ monitoring data for the northern Adriatic Sea. In particular, the system is a downscaling of the Mediterranean Copernicus Marine Environment Monitoring Service and exploits data produced within the Bathing Waters Directive, the Water Framework Directive and the Urban Waste Water Treatment Directive to create added value products. The aim of the proposed indexes is to support the identification of areas of influence for bathing waters by identifying the potential threat from point sources of bacterial pollution, both in standard conditions and peculiar events such as a total bypass of wastewater treatment plants. The results for the Chioggia Municipality case study show the potential of the indexes to significantly improve the geographical identification and quantitative evaluation of the impacts of bacterial pollution sources on bathing waters, facilitating the design of mitigation measures. The proposed methodology represents a new management approach to support local authorities in defining the area of influence within the water bathing profile through the proper characterization of the point sources of bacterial pollution.

Long term reductions of faecal indicator organisms in Chichester Harbour (England) following sewerage infrastructure improvements in the catchment

Quantitative information relating sewerage infrastructure schemes to microbial water quality improvements in recreational and shellfish harvesting areas is lacking. In this study, we assessed the effect of two sewerage schemes on concentrations of faecal indicator organisms (FIO) in Chichester Harbour, an important oyster fishery and water recreation area in the UK. The sewerage schemes comprised the installation of activated sludge and UV disinfection plants and increase in the storage capacity of storm tanks at sewage treatment works that discharge to tidal waters. Analysis of FIO data covering the period 2007-2018 indicated log-order reductions in FIO concentrations in the harbour after the sewerage schemes, which was reflected by better compliance with the E. coli and enterococci limits for "excellent" of the Bathing Waters Directive. Mean concentrations of E. coli in shellfish reduced ≤0.5log₁₀ and compliance of commercial shellfish beds with the limits of Regulation (EC) No 854/2004 either maintained or upgraded to class B status during the 11-year period. However, compliance with the guideline E. coli standard of the Shellfish Water Protected Areas Directions was not consistently achieved. We suggest that better harmonisation of monitoring practices used in the various statutory programmes would help in understanding if the observed discrepancy in FIO compliance between waters and shellfish is due to actual pollution levels at compliance sites or other factors. Nevertheless, this study demonstrates that fortnightly sampling can provide data to evidence long-term water quality improvements following sewerage schemes.

Microbial Water Quality Conditions Associated with Livestock Grazing, Recreation, and Rural Residences in Mixed-Use Landscapes

Contamination of surface waters with microbial pollutants from fecal sources is a significant human health issue. Identification of relative fecal inputs from the mosaic of potential sources common in rural watersheds is essential to effectively develop and deploy mitigation strategies. We conducted a cross-sectional longitudinal survey of fecal indicator bacteria (FIB) concentrations associated with extensive livestock grazing, recreation, and rural residences in three rural, mountainous watersheds in California, USA during critical summer flow conditions. Overall, we found that 86% to 87% of 77 stream sample sites across the study area were below contemporary Escherichia coli-based microbial water quality standards. FIB concentrations were lowest at recreation sites, followed closely by extensive livestock grazing sites. Elevated concentrations and exceedance of water quality standards were highest at sites associated with rural residences, and at intermittently flowing stream sites. Compared to national and state recommended E. coli-based water quality standards, antiquated rural regional policies based on fecal coliform concentrations overestimated potential fecal contamination by as much as four orders of magnitude in this landscape, hindering the identification of the most likely fecal sources and thus the efficient targeting of mitigation practices to address them.

A generic approach for the development of short-term predictions of Escherichia coli and biotoxins in shellfish

Microbiological contamination or elevated marine biotoxin concentrations within shellfish can result in temporary closure of shellfish aquaculture harvesting, leading to financial loss for the aquaculture business and a potential reduction in consumer confidence in shellfish products. We present a method for predicting short-term variations in shellfish concentrations of Escherichia coli and biotoxin (okadaic acid and its derivates dinophysistoxins and pectenotoxins). The approach was evaluated for 2 contrasting shellfish harvesting areas. Through a meta-data analysis and using environmental data (in situ, satellite observations and meteorological nowcasts and forecasts), key environmental drivers were identified and used to develop models to predict E. coli and biotoxin concentrations within shellfish. Models were trained and evaluated using independent datasets, and the best models were identified based on the model exhibiting the lowest root mean square error. The best biotoxin model was able to provide 1 wk forecasts with an accuracy of 86%, a 0% false positive rate and a 0% false discovery rate (n = 78 observations) when used to predict the closure of shellfish beds due to biotoxin. The best E. coli models were used to predict the European hygiene classification of the shellfish beds to an accuracy of 99% (n = 107 observations) and 98% (n = 63 observations) for a bay (St Austell Bay) and an estuary (Turnaware Bar), respectively. This generic approach enables high accuracy short-term farm-specific forecasts, based on readily accessible environmental data and observations.

A catchment-scale model to predict spatial and temporal burden of E. coli on pasture from grazing livestock

Effective management of diffuse microbial water pollution from agriculture requires a fundamental understanding of how spatial patterns of microbial pollutants, e.g. E. coli, vary over time at the landscape scale. The aim of this study was to apply the Visualising Pathogen &Environmental Risk (ViPER) model, developed to predict E. coli burden on agricultural land, in a spatially distributed manner to two contrasting catchments in order to map and understand changes in E. coli burden contributed to land from grazing livestock. The model was applied to the River Ayr and Lunan Water catchments, with significant correlations observed between area of improved grassland and the maximum total E. coli per 1km² grid cell (Ayr: r=0.57; p<0.001, Lunan: r=0.32; p<0.001). There was a significant difference in the predicted maximum E. coli burden between seasons in both catchments, with summer and autumn predicted to accrue higher E. coli contributions relative to spring and winter (P<0.001), driven largely by livestock presence. The ViPER model thus describes, at the landscape scale, spatial nuances in the vulnerability of E. coli loading to land as driven by stocking density and livestock grazing regimes. Resulting risk maps therefore provide the underpinning evidence to inform spatially-targeted decision-making with respect to managing sources of E. coli in agricultural environments.

Using spatial-stream-network models and long-term data to understand and predict dynamics of faecal contamination in a mixed land-use catchment

An 11year dataset of concentrations of E. coli at 10 spatially-distributed sites in a mixed land-use catchment in NE Scotland (52km²) revealed that concentrations were not clearly associated with flow or season. The lack of a clear flow-concentration relationship may have been due to greater water fluxes from less-contaminated headwaters during high flows diluting downstream concentrations, the importance of persistent point sources of E. coli both anthropogenic and agricultural, and possibly the temporal resolution of the dataset. Point sources and year-round grazing of livestock probably obscured clear seasonality in concentrations. Multiple linear regression models identified potential for contamination by anthropogenic point sources as a significant predictor of long-term spatial patterns of low, average and high concentrations of E. coli. Neither arable nor pasture land was significant, even when accounting for hydrological connectivity with a topographic-index method. However, this may have reflected coarse-scale land-cover data inadequately representing "point sources" of agricultural contamination (e.g. direct defecation of livestock into the stream) and temporal changes in availability of E. coli from diffuse sources. Spatial-stream-network models (SSNMs) were applied in a novel context, and had value in making more robust catchment-scale predictions of concentrations of E. coli with estimates of uncertainty, and in enabling identification of potential "hot spots" of faecal contamination. Successfully managing faecal contamination of surface waters is vital for safeguarding public health. Our finding that concentrations of E. coli could not clearly be associated with flow or season may suggest that management strategies should not necessarily target only high flow events or summer when faecal contamination risk is often assumed to be greatest. Furthermore, we identified SSNMs as valuable tools for identifying possible "hot spots" of contamination which could be targeted for management, and for highlighting areas where additional monitoring could help better constrain predictions relating to faecal contamination.

Predicting diffuse microbial pollution risk across catchments: The performance of SCIMAP and recommendations for future development

Microbial pollution of surface waters in agricultural catchments can be a consequence of poor farm management practices, such as excessive stocking of livestock on vulnerable land or inappropriate handling of manures and slurries. Catchment interventions such as fencing of watercourses, streamside buffer strips and constructed wetlands have the potential to reduce faecal pollution of watercourses. However these interventions are expensive and occupy valuable productive land. There is, therefore, a requirement for tools to assist in the spatial targeting of such interventions to areas where they will have the biggest impact on water quality improvements whist occupying the minimal amount of productive land. SCIMAP is a risk-based model that has been developed for this purpose but with a focus on diffuse sediment and nutrient pollution. In this study we investigated the performance of SCIMAP in predicting microbial pollution of watercourses and assessed modelled outputs of E. coli, a common faecal indicator organism (FIO), against observed water quality information. SCIMAP was applied to two river catchments in the UK. SCIMAP uses land cover risk weightings, which are routed through the landscape based on hydrological connectivity to generate catchment scale maps of relative in-stream pollution risk. Assessment of the model's performance and derivation of optimum land cover risk weightings was achieved using a Monte-Carlo sampling approach. Performance of the SCIMAP framework for informing on FIO risk was variable with better performance in the Yealm catchment (r_s=0.88; p<0.01) than the Wyre (r_s=-0.36; p>0.05). Across both catchments much uncertainty was associated with the application of optimum risk weightings attributed to different land use classes. Overall, SCIMAP showed potential as a useful tool in the spatial targeting of FIO diffuse pollution management strategies; however, improvements are required to transition the existing SCIMAP framework to a robust FIO risk-mapping tool.

An INCA model for pathogens in rivers and catchments: Model structure, sensitivity analysis and application to the River Thames catchment, UK

Pathogens are an ongoing issue for catchment water management and quantifying their transport, loss and potential impacts at key locations, such as water abstractions for public supply and bathing sites, is an important aspect of catchment and coastal management. The Integrated Catchment Model (INCA) has been adapted to model the sources and sinks of pathogens and to capture the dominant dynamics and processes controlling pathogens in catchments. The model simulates the stores of pathogens in soils, sediments, rivers and groundwaters and can account for diffuse inputs of pathogens from agriculture, urban areas or atmospheric deposition. The model also allows for point source discharges from intensive livestock units or from sewage treatment works or any industrial input to river systems. Model equations are presented and the new pathogens model has been applied to the River Thames in order to assess total coliform (TC) responses under current and projected future land use. A Monte Carlo sensitivity analysis indicates that the input coliform estimates from agricultural sources and decay rates are the crucial parameters controlling pathogen behaviour. Whilst there are a number of uncertainties associated with the model that should be accounted for, INCA-Pathogens potentially provides a useful tool to inform policy decisions and manage pathogen loading in river systems.

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.

Risk factors for norovirus contamination of shellfish water catchments in England and Wales

This study examines the relationships between concentrations of human noroviruses (NoV) genogroups I (GI) and II (GII) and Escherichia coli monitored in oysters from 31 commercial harvesting areas on the coast of England and Wales from May 2009 to April 2011 and demographic, hydrometric, climatic and pollution source characteristics of upstream river catchments using multiple regression techniques. The predictive environmental factors for E. coli contamination in the oysters were rainfall (cumulative 7days before sampling) while the predictive factors for NoV (GI+GII) were water temperature, catchment area and the combined volume of continuous sewage discharges in the catchment. Oysters from cold waters (<5°C) had significantly higher NoV content than those from warmer waters (>10°C). The association with water temperature may be consequential on the seasonal prevalence of the virus in the community or linked with oyster metabolic function. In a group of 10 study sites, mean concentrations of NoV increased as the number of stormwater spills at those sites also increased. The results of this study could be used to evaluate the likely impact of sewerage infrastructure improvements in catchments at risk of NoV contamination and to help identify sites suitable for shellfish farming.

Post-industrial river water quality-Fit for bathing again?

For the Ruhr River, bathing has been prohibited for decades. However, along with significant improvements of the hygienic water quality, there is an increasing demand of using the river for recreational purposes, in particular for bathing. In the "Safe Ruhr" interdisciplinary research project, demands, options and chances for lifting the bathing ban for the Ruhr River were investigated. As being the prominent reason for persisting recreational restrictions, microbiological water quality was in the focus of interest. Not only the faecal indicator organisms (FIOs) as required by the European Bathing Water Directive were considered, but also pathogens such as Salmonella, Pseudomonas aeruginosa, Legionella pneumophila, Campylobacter, Leptospira, enteroviruses and protozoan parasites. In this introductory paper, we firstly relate current recreational desires to historical experiences of river bathing. After recapitulating relevant microbial river contamination sources (predominantly sewage treatment plants, combined sewer overflows, and surface runoffs), we review existing knowledge about the relationships of FIOs and pathogens in rivers designated for recreational purposes, and then trace the evolution, rationale and validity of recreational freshwater quality criteria which are, despite obvious uncertainties, mostly relying on the FIO paradigm. In particular, the representativeness of FIOs is critically discussed. The working programme of Safe Ruhr, aiming at initiating and facilitating a process towards legalisation of Ruhr River bathing, is outlined. Sources of contamination can be technically handled which leaves the actual measures to political decisions. As contaminations are transient, only occasionally exceeding legal limits, a flexible bathing site management, warning bathers of non-safe situations, may amend technical interventions and offer innovative solutions. As a result, a situation-adapted system for lifting of the bathing ban for Ruhr River appears realistic.

Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments

The application of models to predict concentrations of faecal indicator organisms (FIOs) in environmental systems plays an important role for guiding decision-making associated with the management of microbial water quality. In recent years there has been an increasing demand by policy-makers for models to help inform FIO dynamics in order to prioritise efforts for environmental and human-health protection. However, given the limited evidence-base on which FIO models are built relative to other agricultural pollutants (e.g. nutrients) it is imperative that the end-user expectations of FIO models are appropriately managed. In response, this commentary highlights four over-arching questions associated with: (i) model purpose; (ii) modelling approach; (iii) data availability; and (iv) model application, that must be considered as part of good practice prior to the deployment of any modelling approach to predict FIO behaviour in catchment systems. A series of short and longer-term research priorities are proposed in response to these questions in order to promote better model deployment in the field of catchment microbial dynamics.

Using microbiological tracers to assess the impact of winter land use restrictions on the quality of stream headwaters in a small catchment

Diverse land use activities can elevate risk of microbiological contamination entering stream headwaters. Spatially distributed water quality monitoring carried out across a 17 km(2) agricultural catchment aimed to characterize microbiological contamination reaching surface water and investigate whether winter agricultural land use restrictions proved effective in addressing water quality degradation. Combined flow and concentration data revealed no significant difference in fecal indicator organism (FIO) fluxes in base flow samples collected during the open and prohibited periods for spreading organic fertilizer, while relative concentrations of Escherichia coli, fecal streptococci and sulfite reducing bacteria indicated consistently fresh fecal pollution reached aquatic receptors during both periods. Microbial source tracking, employing Bacteroides 16S rRNA gene markers, demonstrated a dominance of bovine fecal waste in river water samples upstream of a wastewater treatment plant discharge during open periods. This contrasted with responses during prohibited periods where human-derived signatures dominated. Differences in microbiological signature, when viewed with hydrological data, suggested that increasing groundwater levels restricted vertical infiltration of effluent from on-site wastewater treatment systems and diverted it to drains and surface water. Study results reflect seasonality of contaminant inputs, while suggesting winter land use restrictions can be effective in limiting impacts of agricultural wastes to base flow water quality.

Predicting fecal indicator organism contamination in Oregon coastal streams

In this study, we used publicly available GIS layers and statistical tree-based modeling (CART and Random Forest) to predict pathogen indicator counts at a regional scale using 88 spatially explicit landscape predictors and 6657 samples from non-estuarine streams in the Oregon Coast Range. A total of 532 frequently sampled sites were parsed down to 93 pathogen sampling sites to control for spatial and temporal biases. This model's 56.5% explanation of variance, was comparable to other regional models, while still including a large number of variables. Analysis showed the most important predictors on bacteria counts to be: forest and natural riparian zones, cattle related activities, and urban land uses. This research confirmed linkages to anthropogenic activities, with the research prediction mapping showing increased bacteria counts in agricultural and urban land use areas and lower counts with more natural riparian conditions.

Resolving conflicts in public health protection and ecosystem service provision at designated bathing waters

Understanding and quantifying the trade-off between the requirement for clean safe bathing water and beaches and their wider ecosystem services is central to the aims of the European Union (EU) Marine Strategy Framework Directive (MSFD), and vital for the sustainability and economic viability of designated bathing waters. Uncertainty surrounding the impacts of ensuing bathing water policy transitions, e.g. the EU revised Bathing Waters Directive (rBWD), puts new urgency on our need to understand the importance of natural beach assets for human recreation, wildlife habitat and for protection from flooding and erosion. However, managing coastal zones solely in terms of public health could have potentially negative consequences on a range of other social and cultural ecosystem services, e.g. recreation. Improving our knowledge of how bathing waters, surrounding beach environments and local economies might respond to shifts in management decisions is critical in order to inform reliable decision-making, and to evaluate future implications for human health. In this paper we explore the conflicts and trade-offs that emerge at public beach environments, and propose the development of an evaluative framework of viable alternatives in environmental management whereby bathing waters are managed for their greatest utility, driven by identifying the optimal ecosystem service provision at any particular site.

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.

Impact of low intensity summer rainfall on E. coli-discharge event dynamics with reference to sample acquisition and storage

Understanding the role of different rainfall scenarios on faecal indicator organism (FIO) dynamics under variable field conditions is important to strengthen the evidence base on which regulators and land managers can base informed decisions regarding diffuse microbial pollution risks. We sought to investigate the impact of low intensity summer rainfall on Escherichia coli-discharge (Q) patterns at the headwater catchment scale in order to provide new empirical data on FIO concentrations observed during baseflow conditions. In addition, we evaluated the potential impact of using automatic samplers to collect and store freshwater samples for subsequent microbial analysis during summer storm sampling campaigns. The temporal variation of E. coli concentrations with Q was captured during six events throughout a relatively dry summer in central Scotland. The relationship between E. coli concentration and Q was complex with no discernible patterns of cell emergence with Q that were repeated across all events. On several occasions, an order of magnitude increase in E. coli concentrations occurred even with slight increases in Q, but responses were not consistent and highlighted the challenges of attempting to characterise temporal responses of E. coli concentrations relative to Q during low intensity rainfall. Cross-comparison of E. coli concentrations determined in water samples using simultaneous manual grab and automated sample collection was undertaken with no difference in concentrations observed between methods. However, the duration of sample storage within the autosampler unit was found to be more problematic in terms of impacting on the representativeness of microbial water quality, with unrefrigerated autosamplers exhibiting significantly different concentrations of E. coli relative to initial samples after 12-h storage. The findings from this study provide important empirical contributions to the growing evidence base in the field of catchment microbial dynamics.

Application of a linear regression model to assess the influence of urbanised areas and grazing pastures on the microbiological quality of rural streams

Faecal coliform (FC) bacteria were used as a proxy of faecal indicator organisms (FIOs) to assess the microbiological pollution risk for eight mesoscale catchments with increasing lowland influence across north-east Scotland. This study sought to assess the impact of urban areas on microbial contaminant fluxes. Fluxes were lowest in upland catchments where populations are relatively low. By contrast, lowland catchments with larger settlements and a greater number of grazing populations have more elevated FC concentrations throughout the year. Peak FC counts occurred during the summer months (April-September) when biological activity is at its highest. Lowland catchments experience high FC concentrations throughout the year whereas upland catchments exhibit more seasonal variations with elevated summer conditions and reduced winter concentrations. A simple linear regression model based on catchment characteristics provided scope to predict FC fluxes. Percentage of improved grazing pasture and human population explained 90 and 62 % of the variation in mean annual FC concentrations. This approach provides scope for an initial screening tool to predict the impact of urban space and agricultural practice on FC concentrations at the catchment scale and can aid in pragmatic planning and water quality improvement decisions. However, greater understanding of the short-term dynamics is still required which would benefit from higher resolution sampling than the approach undertaken here.

Seaweeds and plastic debris can influence the survival of faecal indicator organisms in beach environments

The revised Bathing Water Directive (rBWD) introduces more stringent standards for microbial water quality and promotes more pro-active management of the beach environment through the production of a bathing water profile (BWP). The aim of this study was to determine whether living seaweeds in the littoral zone are colonised by faecal indicator organisms (FIOs), and to quantify the survival dynamics of waterborne Escherichia coli in microcosms containing senescing seaweeds. Living seaweed (Fucus spiralis) was not associated with FIO colonisation, although could be providing a protected environment in the underlying sand. Senescing seaweeds enhanced waterborne E. coli survival compared to plastic debris, with the brown seaweed Laminaria saccharina facilitating greater E. coli persistence than either Chondrus crispus or Ulva lactuca. This has important implications for FIO survival on bathing beaches as the majority of beach-cast biomass is composed of brown seaweeds, which could support significant levels of FIOs.

Prevalence of diarrhea-associated virulence genes and genetic diversity in Escherichia coli isolates from fecal material of various animal hosts

In order to assess the health risk associated with a given source of fecal contamination using bacterial source tracking (BST), it is important to know the occurrence of potential pathogens as a function of host. Escherichia coli isolates (n=593) from the feces of diverse animals were screened for various virulence genes: stx1 and stx2 (Shiga toxin-producing E. coli [STEC]), eae and EAF (enteropathogenic E. coli [EPEC]), STh, STp, and LT (enterotoxigenic E. coli [ETEC]), and ipaH (enteroinvasive E. coli [EIEC]). Eleven hosts were positive for only the eae (10.11%) gene, representing atypical EPEC, while two hosts were positive for both eae and EAF (1.3%), representing typical EPEC. stx1, stx2, or both stx1 and stx2 were present in 1 (0.1%,) 10 (5.56%), and 2 (1.51%) hosts, respectively, and confirmed as non-O157 by using a E. coli O157 rfb (rfbO157) TaqMan assay. STh and STp were carried by 2 hosts (2.33%) and 1 host (0.33%), respectively, while none of the hosts were positive for LT and ipaH. The repetitive element palindromic PCR (rep-PCR) fingerprint analysis identified 221 unique fingerprints with a Shannon diversity index of 2.67. Multivariate analysis of variance revealed that majority of the isolates clustered according to the year of sampling. The higher prevalence of atypical EPEC and non-O157 STEC observed in different animal hosts indicates that they can be a reservoir of these pathogens with the potential to contaminate surface water and impact human health. Therefore, we suggest that E. coli from these sources must be included while constructing known source fingerprint libraries for tracking purposes. However, the observed genetic diversity and temporal variation need to be considered since these factors can influence the accuracy of BST results.

Trends in the levels of Escherichia coli in commercially harvested bivalve shellfish from England and Wales, 1999-2008

Temporal trends in Escherichia coli concentrations in bivalve shellfish were examined using data collected from 57 production areas around the coast of England and Wales during 1999-2008. Downward trends were detected in annual geometric means of E. coli in shellfish from 12% of the sampling points. The percentage of class B areas (E. coli ≤ 4600/100 g shellfish in 90% of samples) increased from 69% to 86% during the 10-year period. The improvement in the microbial quality of shellfish is associated with sewerage improvement schemes largely implemented during 2000-2005. Upward trends were detected in 9% of the points. The causes of these increases are not known. It is recommended that quantitative sanitary profiling of shellfish waters and cost-benefit appraisal over long-term planning horizons are considered as part of sewerage investment programmes under the Water Framework Directive. This would allow greater scope to secure protection and improvement of shellfish water quality.

Land use and hydroclimatic influences on Faecal Indicator Organisms in two large Scottish catchments: towards land use-based models as screening tools

Faecal Coliform (FC) bacteria were used as Faecal Indicator Organisms (FIOs) for assessment of microbiological pollution risk in two large, mixed land use catchments in Scotland. FC counts varied spatially in relation to land use and human population and resulting trophic status. These were highest in catchments with a high cover of improved pasture (which was assumed to be a proxy for cattle and sheep grazing densities) and significant human populations. FC counts were lowest in oligotrophic upland areas, where domesticated animal populations were low. In both lowland and upland catchments, peak FC counts occurred under periods of elevated flows during summer. However, in lowland agricultural catchments of higher trophic status, contamination appears to be chronic and occurs all year round. In contrast, upland headwater catchments exhibit more episodic peaks in relation to high flow events. Larger scale catchments integrate the inputs from contrasting head water streams. Spatial variations in stream FC concentrations can be predicted to a first approximation using multiple regression based on catchment characteristics. Land cover was the most important factor, with percentage improved pasture being the primary control and human population being of secondary importance. These two factors could explain 78% of the variation in mean annual FC concentrations and 65% of the 95th percentile. This simple linear model provides a screening tool for rapid assessment of pollution risk in unmonitored catchments. However, improved prediction of short-term dynamics and peak values requires higher resolution sampling and process-based models of FC production, survival and transport. A particularly important need is an improved characterisation of the hydrological connectivity which controls the flux from pollutant reservoirs on the landscape into river channel networks.

Determining E. coli burden on pasture in a headwater catchment: combined field and modelling approach

Empirical monitoring studies of catchment-scale Escherichia coli burden to land from agriculture are scarce. This is not surprising given the complexity associated with the temporal and spatial heterogeneity in the excretion of livestock faecal deposits and variability in microbial content of faeces. However, such information is needed to appreciate better how land management and landscape features impact on water quality draining agricultural landscapes. The aim of this study was to develop and test a field-based protocol for determining the burden of E. coli in a small headwater catchment in the UK. Predictions of E. coli burden using an empirical model based on previous best estimates of excretion and shedding rates were also evaluated against observed data. The results indicated that an empirical model utilising key parameters was able to satisfactorily predict E. coli burden on pasture most of the time, with 89% of observed values falling within the minimum and maximum range of predicted values. In particular, the overall temporal pattern of E. coli burden on pasture is captured by the model. The observed and predicted values recorded a disagreement of >1 order of magnitude on only one of the nine sampling dates throughout an annual period. While a first approximation of E. coli burden to land, this field-based protocol represents one of the first comprehensive approaches for providing a real estimate of a dynamic microbial reservoir at the headwater catchment scale and highlights the utility of a simple dynamic empirical model for a more economical prediction of catchment-scale E. coli burden.

Microbiological water quality and its relation to nitrogen and phosphorus at the Pareja limno-reservoir (Guadalajara, Spain)

Bordering on the edge of the Entrepeñas reservoir (Guadalajara, Spain), next to the village of Pareja, a small dam that allows a body of water to develop with a constant level has been built. Initiatives like this (which we have termed "limno-reservoirs") are innovative in Spain and around the world. Earlier reservoirs such as this one were constructed to create a habitat for birds, but the Pareja limno-reservoir is the first to promote socio-economic development. In order to study this limno-reservoir, this research group set up an environmental observatory, analyzing, among other variables, microbiological water quality and nutrient content. After a year and a half of research, it was observed that the concentration of microorganisms is lower in the limno-reservoir than in the river that feeds it, possibly due to the nutrient depletion in the lentic ecosystem. In the limno-reservoir, the total coliforms and enterococci concentrations fall within the European Bathing Water Directive limits, but in the river these concentrations are sometimes higher. The nutrient load in the limno-reservoir is low, with nutrient variations influencing native microorganisms, but not for total coliforms and enterococci. However, the development of special conditions in the bottom has been observed in winter, facilitating coliforms and enterococci survival. This research is very interesting since the creation of limno-reservoirs is rising in Spain and no research is being done on their behaviour.

Predicting pathogen risks to aid beach management: the real value of quantitative microbial risk assessment (QMRA)

There has been an ongoing dilemma for agencies that set criteria for safe recreational waters in how to provide for a seasonal assessment of a beach site versus guidance for day-to-day management. Typically an overall 'safe' criterion level is derived from epidemiologic studies of sewage-impacted beaches. The decision criterion is based on a percentile value for a single sample or a moving median of a limited number (e.g. five per month) of routine samples, which are reported at least the day after recreator exposure has occurred. The focus of this paper is how to better undertake day-to-day recreational site monitoring and management. Internationally, good examples exist where predictive empirical regression models (based on rainfall, wind speed/direction, etc.) may provide an estimate of the target faecal indicator density for the day of exposure. However, at recreational swimming sites largely impacted by non-sewage sources of faecal indicators, there is concern that the indicator-illness associations derived from studies at sewage-impacted beaches may be inappropriate. Furthermore, some recent epidemiologic evidence supports the relationship to gastrointestinal (GI) illness with qPCR-derived measures of Bacteroidales/Bacteroides spp. as well as more traditional faecal indicators, but we understand less about the environmental fate of these molecular targets and their relationship to bather risk. Modelling pathogens and indicators within a quantitative microbial risk assessment framework is suggested as a way to explore the large diversity of scenarios for faecal contamination and hydrologic events, such as from waterfowl, agricultural animals, resuspended sediments and from the bathers themselves. Examples are provided that suggest that more site-specific targets derived by QMRA could provide insight, directly translatable to management actions.