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Scale appropriate modelling of diffuse microbial pollution from agriculture

Centre for Sustainable Water Management, Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK, d.m.oliver{at}lancaster.ac.uk

A. Louise Heathwaite

Centre for Sustainable Water Management, Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK

Rob D. Fish

Centre for Sustainable Water Management, Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK, Centre for Rural Policy Research, Department of Politics, University of Exeter, Amory Building, Exeter EX4 6RJ, UK

Dave R. Chadwick

North Wyke Research, Okehampton EX20 2SB, UK

Chris J. Hodgson

North Wyke Research, Okehampton EX20 2SB, UK

Michael Winter

Centre for Rural Policy Research, Department of Politics, University of Exeter, Amory Building, Exeter EX4 6RJ, UK

Allan J. Butler

Centre for Rural Policy Research, Department of Politics, University of Exeter, Amory Building, Exeter EX4 6RJ, UK

The prediction of microbial concentrations and loads in receiving waters is a key requirement for informing policy decisions in order to safeguard human health. However, modelling the fate and transfer dynamics of faecally derived microorganisms at different spatial scales poses a considerable challenge to the research and policy community. The objective of this paper is to critically evaluate the complexities and associated uncertainties attributed to the development of models for assessing agriculturally derived microbial pollution of watercourses. A series of key issues with respect to scale appropriate modelling of diffuse microbial pollution from agriculture is presented, and these include: (1) appreciating inadequacies in baseline sampling to underpin model development; (2) uncertainty in the magnitudes of microbial pollutants attributed to different faecal sources; (3) continued development of the empirical evidence base in line with other agricultural pollutants; (4) acknowledging the value of interdisciplinary working; and (5) beginning to account for economics in model development. It is argued that uncertainty in model predictions produces a space for meaningful scrutiny of the nature of evidence and assumptions underpinning model applications around which pathways towards more effective model development may ultimately emerge.

Key Words: diffuse pollution • end-user • faecal indicator organism • modelling • pathogen • scale • stakeholder • uncertainty.

This version was published on June 1, 2009

Progress in Physical Geography, Vol. 33, No. 3, 358-377 (2009)
DOI: 10.1177/0309133309342647


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