Browse by author
Lookup NU author(s): Dr Paul Quinn
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
Laboratory and small-scale field observations have yielded fundamental insights into the causes of nitrate pollution. Detection of downstream, off-site impacts of nitrate pollution reveals its effects. However, there is a gulf in our knowledge and practice that prevents the expertise gained at the small-scale from contributing to a sound scientific basis for planning at the catchment scale. Many modellers may thus rely on simple empirical models when simulating nitrate pollution at the catchment scale as these models can reflect their judgments and uncertainties. Other modellers struggle to apply physically-based, distributed models within complex, three-dimensional heterogeneous landscapes, inducing equifinality and predictive uncertainty problems. One way for planners and scientists to advance is to create scale appropriate modelling techniques, which can call upon a range of model types [including complex physically-based, quasi-physical, semi-distributed models and lumped Minimum Information Requirement (MIR) models]. This paper argues that the modeller must use the appropriate model type, at the appropriate scale, in order to best understand nitrate losses observed at that scale. When simulating at the catchment scale, the modeller must accept that there are processes that are not fully understood and cannot be modelled with accuracy, yet the modeller must still produce decision support tools that are capable of solving real world problems, despite inherent model uncertainty. Thus, this paper will show, through a fully worked example, how hydrological flow paths and nitrate pollution sources can be simulated at the catchment scale by first, reflecting our understanding of the physical world and second paying full respect to catchment scale issues and uncertainty problems. The River Great Ouse (1400 km2) case study is a typical intense arable region of the UK, where the available data sources are by no means perfect, but where nitrate policy must still be implemented. Thus, physically-based model simulations, simple MIR models, GIS data sources and 'expert' knowledge are brought together to create a simple, applied modelling toolkit to simulate nitrate pollution and support catchment policies that reduce the loss of nitrate to rivers. © 2004 Elsevier B.V. All rights reserved.
Author(s): Quinn PF
Publication type: Article
Publication status: Published
Journal: Journal of Hydrology
Year: 2004
Volume: 291
Issue: 3-4
Pages: 197-217
ISSN (print): 0022-1694
ISSN (electronic):
Publisher: Elsevier BV
URL: http://dx.doi.org/10.1016/j.jhydrol.2003.12.040
DOI: 10.1016/j.jhydrol.2003.12.040
Altmetrics provided by Altmetric
