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Sci Total Environ. 2016 Dec 1;572:1601-1610. doi: 10.1016/j.scitotenv.2016.01.128. Epub 2016 Feb 11.

An INCA model for pathogens in rivers and catchments: Model structure, sensitivity analysis and application to the River Thames catchment, UK.

Author information

1
School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, UK. Electronic address: paul.whitehead@ouce.ox.ac.uk.
2
School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, UK.
3
SYKE, P.O. Box 140, FIN-00251 Helsinki, Finland.
4
Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, SE-75007, Uppsala, Sweden.

Abstract

Pathogens are an ongoing issue for catchment water management and quantifying their transport, loss and potential impacts at key locations, such as water abstractions for public supply and bathing sites, is an important aspect of catchment and coastal management. The Integrated Catchment Model (INCA) has been adapted to model the sources and sinks of pathogens and to capture the dominant dynamics and processes controlling pathogens in catchments. The model simulates the stores of pathogens in soils, sediments, rivers and groundwaters and can account for diffuse inputs of pathogens from agriculture, urban areas or atmospheric deposition. The model also allows for point source discharges from intensive livestock units or from sewage treatment works or any industrial input to river systems. Model equations are presented and the new pathogens model has been applied to the River Thames in order to assess total coliform (TC) responses under current and projected future land use. A Monte Carlo sensitivity analysis indicates that the input coliform estimates from agricultural sources and decay rates are the crucial parameters controlling pathogen behaviour. Whilst there are a number of uncertainties associated with the model that should be accounted for, INCA-Pathogens potentially provides a useful tool to inform policy decisions and manage pathogen loading in river systems.

KEYWORDS:

E. coli; Land use change; Modelling; Pathogens; River Thames; Water quality

PMID:
26875602
DOI:
10.1016/j.scitotenv.2016.01.128
[Indexed for MEDLINE]

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