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

Oliver, D.M. and Porter, K.D.H. and Pachepsky, Y.A. and Muirhead, R.W. and Reaney, S.M. and Coffey, R. and Kay, D. and Milledge, D.M. and Hong, E. and Anthony, S.G. and Page, T. and Bloodworth, J.W. and Mellander, P-E. and Carbonneau, P. and McGrane, S.J. and Quilliam, R.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.

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:Article
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Available under License - Creative Commons Attribution.
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Status:Peer-reviewed
Publisher Web site:http://dx.doi.org/10.1016/j.scitotenv.2015.11.086
Publisher statement:© 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/).
Date accepted:17 November 2015
Date deposited:05 August 2016
Date of first online publication:03 December 2015
Date first made open access:No date available

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