Generic Modelling of Faecal Indicator Organism Concentrations in the UK
| Autor: | Paulette Posen, John Crowther, David Kay, Danyel Hampson, Mark D. Wyer, Carl Michael Stapleton, Ian J. Bateman |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
lcsh:Hydraulic engineering
Geography Planning and Development Population 0207 environmental engineering population 02 engineering and technology Land cover 010501 environmental sciences Aquatic Science 01 natural sciences Biochemistry Water Framework Directive lcsh:Water supply for domestic and industrial purposes land cover lcsh:TC1-978 020701 environmental engineering education 0105 earth and related environmental sciences Water Science and Technology Hydrology education.field_of_study lcsh:TD201-500 Land use Integrated catchment management microbial source apportionment stocking density Water quality modelling Regression analysis Explained variation 6. Clean water 13. Climate action faecal indicator organisms Environmental science bathing waters water quality modelling |
| Zdroj: | Water, Vol 3, Iss 2, Pp 682-701 (2011) Water Volume 3 Issue 2 Pages 682-701 |
| ISSN: | 2073-4441 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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