Within-day variability in microbial concentrations at a UK designated bathing water: Implications for regulatory monitoring and the application of predictive modelling based on historical compliance data
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 regu...
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Published in: | Water research X Vol. 1; p. 100006 |
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01-12-2018
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Abstract | 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 log
order, with the largest daily variations exceeding 2 log
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. |
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AbstractList | 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 log
order, with the largest daily variations exceeding 2 log
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. 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 log 10 order, with the largest daily variations exceeding 2 log 10 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. Image 1 • Half hourly samples were taken for 60 days in the UK bathing season. • Every day produced highly variable bacterial results covering 1–2.5 log 10 . • The daily variance was independent of antecedent conditions. • Samples taken at different times had different compliance outcomes. 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 |
ArticleNumber | 100006 |
Author | Wyer, Mark D Morgan, Huw Naylor, Sam Kay, David Clark, Simon Francis, Carol Watkins, John Osborn, Hamish Davies, Cheryl M Bennett, Sarah |
AuthorAffiliation | a Department of Geography and Earth Sciences, Llandinam Building, Aberystwyth University, SY23 3DB, UK b Place, Housing and Public Protection Services, Pollution Control, Swansea Council, The Guildhall, Swansea, SA1 4PE, UK c Natural Resources Wales, Area Office, Maes Newydd, Llandarcy, SA10 6JQ, UK |
AuthorAffiliation_xml | – name: c Natural Resources Wales, Area Office, Maes Newydd, Llandarcy, SA10 6JQ, UK – name: a Department of Geography and Earth Sciences, Llandinam Building, Aberystwyth University, SY23 3DB, UK – name: b Place, Housing and Public Protection Services, Pollution Control, Swansea Council, The Guildhall, Swansea, SA1 4PE, UK |
Author_xml | – sequence: 1 givenname: Mark D surname: Wyer fullname: Wyer, Mark D organization: Department of Geography and Earth Sciences, Llandinam Building, Aberystwyth University, SY23 3DB, UK – sequence: 2 givenname: David surname: Kay fullname: Kay, David organization: Department of Geography and Earth Sciences, Llandinam Building, Aberystwyth University, SY23 3DB, UK – sequence: 3 givenname: Huw surname: Morgan fullname: Morgan, Huw organization: Place, Housing and Public Protection Services, Pollution Control, Swansea Council, The Guildhall, Swansea, SA1 4PE, UK – sequence: 4 givenname: Sam surname: Naylor fullname: Naylor, Sam organization: Place, Housing and Public Protection Services, Pollution Control, Swansea Council, The Guildhall, Swansea, SA1 4PE, UK – sequence: 5 givenname: Simon surname: Clark fullname: Clark, Simon organization: Place, Housing and Public Protection Services, Pollution Control, Swansea Council, The Guildhall, Swansea, SA1 4PE, UK – sequence: 6 givenname: John surname: Watkins fullname: Watkins, John organization: Department of Geography and Earth Sciences, Llandinam Building, Aberystwyth University, SY23 3DB, UK – sequence: 7 givenname: Cheryl M surname: Davies fullname: Davies, Cheryl M organization: Department of Geography and Earth Sciences, Llandinam Building, Aberystwyth University, SY23 3DB, UK – sequence: 8 givenname: Carol surname: Francis fullname: Francis, Carol organization: Department of Geography and Earth Sciences, Llandinam Building, Aberystwyth University, SY23 3DB, UK – sequence: 9 givenname: Hamish surname: Osborn fullname: Osborn, Hamish organization: Natural Resources Wales, Area Office, Maes Newydd, Llandarcy, SA10 6JQ, UK – sequence: 10 givenname: Sarah surname: Bennett fullname: Bennett, Sarah organization: Natural Resources Wales, Area Office, Maes Newydd, Llandarcy, SA10 6JQ, UK |
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Title | Within-day variability in microbial concentrations at a UK designated bathing water: Implications for regulatory monitoring and the application of predictive modelling based on historical compliance data |
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