Journal article
An INCA model for pathogens in rivers and catchments: Model structure, sensitivity analysis and application to the River Thames catchment, UK
- 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 1.1MB, Terms of use)
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- Publisher copy:
- 10.1016/j.scitotenv.2016.01.128
Authors
+ Academy of Finland
More from this funder
- Grant:
- Sustainable Governance of Aquatic Resources: CONPAT Project
- Publisher:
- Elsevier
- Journal:
- Science of the Total Environment More from this journal
- Volume:
- 572
- Pages:
- 1601-1610
- Publication date:
- 2016-02-11
- DOI:
- EISSN:
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1879-1026
- ISSN:
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0048-9697
- Keywords:
- Pubs id:
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pubs:602495
- UUID:
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uuid:d0a2bab4-049d-4a37-bdb2-5b380c7937c4
- Local pid:
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pubs:602495
- Source identifiers:
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602495
- Deposit date:
-
2016-02-15
- ARK identifier:
Terms of use
- Copyright holder:
- Elsevier
- Copyright date:
- 2016
- Notes:
- © 2016 Published by Elsevier B. V. This is the accepted manuscript version of the article. The final version is available online from Elsevier at: [10.1016/j.scitotenv.2016.01.128]
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