Predicting microbial water quality with models:over-arching questions for managing risk in agricultural catchments

Oliver, David Michael and Porter, Kenneth D. H. and Pachepsky, Yakov A. and Muirhead, Richard W. and Reaney, Sim M. and Coffey, Rory and Kay, David and Milledge, David Graham and Hong, Eunmi and Anthony, Steven G. and Page, Trevor John Charles and Bloodworth, Jack W. and Mellander, Per-Erik and Carbonneau, Patrice E. and McGrane, Scott J. and Quilliam, Richard S. (2016) Predicting microbial water quality with models:over-arching questions for managing risk in agricultural catchments. Science of the Total Environment, 544. pp. 39-47. ISSN 0048-9697

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Abstract

The application of models to predict concentrations of faecal indicator organisms (FIOs) in environmental systems plays an important role for guiding decision-making associated with the management of microbial water quality. In recent years there has been an increasing demand by policy-makers for models to help inform FIO dynamics in order to prioritise efforts for environmental and human-health protection. However, given the limited evidence-base on which FIO models are built relative to other agricultural pollutants (e.g. nutrients) it is imperative that the end-user expectations of FIO models are appropriately managed. In response, this commentary highlights four over-arching questions associated with: (i) model purpose; (ii) modelling approach; (iii) data availability; and (iv) model application, that must be considered as part of good practice prior to the deployment of any modelling approach to predict FIO behaviour in catchment systems. A series of short and longer-term research priorities are proposed in response to these questions in order to promote better model deployment in the field of catchment microbial dynamics.

Item Type:
Journal Article
Journal or Publication Title:
Science of the Total Environment
Additional Information:
© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2300/2311
Subjects:
ID Code:
78619
Deposited By:
Deposited On:
17 Jun 2016 13:32
Refereed?:
Yes
Published?:
Published
Last Modified:
18 Sep 2020 02:45