Generic Modelling of Faecal Indicator Organism Concentrations in the UK

Water

John Crowther³  Danyel I. Hampson²  Ian J. Bateman²  David Kay¹  Paulette E. Posen²  Carl M. Stapleton¹ 

[1] Catchment and Coastal Research Centre, River Basin Dynamics and Hydrology Research Group, IGES, Aberystwyth University, Aberystwyth, Ceredigion, SY23 3DB, UK; E-Mails:;School of Environmental Sciences, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK; E-Mails:;Centre for Research into Environment and Health, University of Wales, Trinity Saint David, Lampeter, Ceredigion, SA48 7ED, UK; E-Mail:

关键词: faecal indicator organisms;    Water Framework Directive;    bathing waters;    water quality modelling;    land cover;    population;    stocking density;    microbial source apportionment;   

DOI  :  10.3390/w3020682

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.