Abstract
AbstractIn order to model complex environmental systems, one needs to find a balance between the model complexity and the quality of the data available needed to run and validate the model. This paper describes a method to find this balance. Four models of different complexity were applied to describe the transfer of nitrogen and phosphorus from pollution sources to river outlets in two large European river basins (Rhine and Elbe). A comparison of the predictive capability of these four models tells us something about the added value of the added model complexity. We also quantified the errors in the data that were used to run and validate the models and analysed to what extent the model validation errors could be attributed to data errors, and to what extent to shortcomings of the model. We conclude that although the addition of more process description is interesting from a theoretical point of view, it does not necessarily improve the predictive capability. Although our analysis is based on an extensive pollutionâsourcesâriverâload database it appeared that the information content of this database was sufficient only to support models of a limited complexity. Our analysis also illustrates that for a proper justification of a model's degree of complexity one should compare the model to simplified versions of the model. Copyright © 2001 John Wiley & Sons, Ltd.
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