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Prediction of bathing water quality is recommended by the World Health Organization (WHO), the European Union (EU) and the United States Environmental Protection Agency (USEPA) and is an established element in bathing water management designed to protect public health. Most commonly, historical regulatory compliance data are used for model calibration and provide the dependent variable for modelling. Independent (or predictor) variables (e.g. rainfall, river flow and received irradiance) measured over some antecedent period are used to deliver prediction of the faecal indicator concentration measured on the day of the regulatory sample collection. The implied linked assumptions of this approach are, therefore, that; (i) the independent variables accurately predict the bathing-day water quality; which is (ii) accurately characterized by the single regulatory sample. Assumption (ii) will not be the case where significant within-day variability in water quality is evident. This study built a detailed record of water quality change through 60 days at a UK coastal bathing water in 2011 using half-hourly samples each subjected to triplicate filtration designed to enhance enumeration precision. On average, the mean daily variation in FIO concentrations exceeded 1 log10 order, with the largest daily variations exceeding 2 log10 orders. Significant diurnality was observed at this bathing water, which would determine its EU Directive compliance category if the regulatory samples were collected at the same time each day. A sampling programme of this intensity has not been reported elsewhere to date and, if this pattern is proven to be characteristic of other bathing waters world-wide, it has significance for: (a) the design of regulatory sampling programmes; (b) the use of historical data to assess compliance, which often comprises a single sample taken at the compliance point on a regular, often weekly, basis; and (c) the use of regulatory compliance data to build predictive models of water quality. Keywords: Bathing water variability faecal indicators

To meet European Water Framework Directive requirements, data are needed on faecal indicator organism (FIO) concentrations in rivers to enable the more heavily polluted to be targeted for remedial action. Due to the paucity of FIO data for the UK, especially under high-flow hydrograph event conditions, there is an urgent need by the policy community for generic models that can accurately predict FIO concentrations, thus informing integrated catchment management programmes. This paper reports the development of regression models to predict base- and high-flow faecal coliform (FC) and enterococci (EN) concentrations for 153 monitoring points across 14 UK catchments, using land cover, population (human and livestock density) and other variables that may affect FIO source strength, transport and die-off. Statistically significant models were developed for both FC and EN, with greater explained variance achieved in the high-flow models. Both land cover and, in particular, population variables are significant predictors of FIO concentrations, with r2 maxima for EN of 0.571 and 0.624, respectively. It is argued that the resulting models can be applied, with confidence, to other UK catchments, both to predict FIO concentrations in unmonitored watercourses and evaluate the likely impact of different land use/stocking level and human population change scenarios.

As the requirements of the Water Framework Directive (WFD) and the US Clean Water Act (USCWA) for the maintenance of microbiological water quality in ‘protected areas’ highlight, there is a growing recognition that integrated management of point and diffuse sources of microbial pollution is essential. New information on catchment microbial dynamics and, in particular, the sources of faecal indicator bacteria found in bathing and shellfish harvesting waters is a pre-requisite for the design of any ‘programme of measures’ at the drainage basin scale to secure and maintain compliance with existing and new health-based microbiological standards. This paper reports on a catchment-scale microbial source tracking (MST) study in the Leven Estuary drainage basin, northwest England, an area for which quantitative faecal indicator source apportionment empirical data and land use information were also collected. Since previous MST studies have been based on laboratory trials using ‘manufactured’ samples or analyses of spot environmental samples without the contextual microbial flux data (under high and low flow conditions) and source information, such background data are needed to evaluate the utility of MST in USCWA total maximum daily load (TMDL) assessments or WFD ‘Programmes of Measures’. Thus, the operational utility of MST remains in some doubt. The results of this investigation, using genotyping of Bacteroidetes using polymerase chain reaction (PCR) and male-specific ribonucleic acid coliphage (F + RNA coliphage) using hybridisation, suggest some discrimination is possible between livestock- and human-derived faecal indicator concentrations but, in inter-grade areas, the degree to which the tracer picture reflected the land use pattern and probable faecal indicator loading were less distinct. Interestingly, the MST data was more reliable on high flow samples when much of the faecal indicator flux from catchment systems occurs. Whilst a useful supplementary tool, the MST information did not provide quantitative source apportionment for the study catchment. Thus, it could not replace detailed empirical measurement of microbial flux at key catchment outlets to underpin faecal indicator source apportionment. Therefore, the MST techniques reported herein currently may not meet the standards required to be a useful forensic tool, although continued development of the methods and further catchment scale studies could increase confidence in such methods for future application. [ABSTRACT FROM AUTHOR]