TY - JOUR
T1 - Within-day variability in microbial concentrations at a UK designated bathing water
T2 - Implications for regulatory monitoring and the application of predictive modelling based on historical compliance data
AU - Wyer, Mark
AU - Kay, David
AU - Morgan, Huw
AU - Naylor, Sam
AU - Clark, Simon
AU - Watkins, John
AU - Davies, Cheryl
AU - Francis, Carol
AU - Osborn, Hamish
AU - Bennett, Sarah
N1 - Funding Information:
This work, under the project titled 'Smart Costs Sustainable Communities', was funded by the European Union, Ireland-Wales Interreg programme with additional inputs from the Swansea Council, Natural Resources Wales, Dŵr-Cymru/Welsh Water and Aberystwyth University. Parallel research was conducted under the same grant by University College Dublin. We are grateful to all our partner organisations and particularly to the staff of the Welsh European Funding Office managing the Ireland-Wales Programme and their desk officer Mr Patrick Lilley, who gave generously of his time and advice throughout. Related work has been awarded further funding in the 2014–2020 EU Interreg programme entitled 'Acclimatize'. We are grateful to Professor Stephen Tooth who offered useful comment and suggestions on an early draft of this paper. We are grateful to the three reviewers who made perceptive and detailed points which have significantly enhanced the clarity of this paper.
Publisher Copyright:
© 2018 The Author(s)
PY - 2018/12/1
Y1 - 2018/12/1
N2 - 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.
AB - 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.
KW - Bathing water variability faecal indicators
UR - http://www.scopus.com/inward/record.url?scp=85061043373&partnerID=8YFLogxK
U2 - 10.1016/j.wroa.2018.10.003
DO - 10.1016/j.wroa.2018.10.003
M3 - Article
SN - 2589-9147
VL - 1
SP - 1
EP - 12
JO - Water Research X
JF - Water Research X
M1 - 100006
ER -
