Environmental Modelling at Nottingham
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Methods for the Development of Parsimonious Models Models of complex environmental processes and systems are widely used as tools to assist the development of research, and to support decision making at a number of levels (e.g. international, national government, corporate). Many models become unwieldy, over-parameterised and difficult to test as they seek to capture the temporal and spatial dynamics of relevant processes. The performance of most models is usually assessed through some kind of 'test' against observed data. However this testing is commonly a simple comparison between a given model and a given set of observed data. Invariably there are many plausible model representations of particular processes and the influence of these alternatives on model performance is rarely investigated. We believe that models should be parsimonious, i.e. as simple as possible, but no simpler.
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Although this view is often expressed, the tendency, has been for the development of complex models, rarely with any investigation of simpler, potentially equally reliable, models. Our aim in this work is to develop an approach for systematic model reduction to achieve improved model parsimony.
Outputs Our first paper from this project is now in print. G.M. Cox, J.M. Gibbons, A.T.A. Wood, J. Craigon, S.J. Ramsden and N.M.J. Crout (2006). Towards the systematic simplification of mechanistic models. Ecological Modelling 198:240-246. [click here] for a pre-print version
Participants Glen Cox, James Gibbons, Neil Crout, Jim Craigon, Stephen Ramsden: Division of Agricultural & Environmental Sciences Andy Wood, Department of Mathematical Sciences |