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Het OWA, het open archief van het Waterbouwkundig Laboratorium heeft tot doel alle vrij toegankelijke onderzoeksresultaten van dit instituut in digitale vorm aan te bieden. Op die manier wil het de zichtbaarheid, verspreiding en gebruik van deze onderzoeksresultaten, alsook de wetenschappelijke communicatie maximaal bevorderen.

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Dealing with uncertainty in water quality models of the North Sea Sonneveldt, H.L.A.; Baretta, J.W.; Laane, R.W.P.M. (2002). Dealing with uncertainty in water quality models of the North Sea, in: Anderson, E.D. (Ed.) 100 Years of Science under ICES: Papers from a Symposium held in Helsinki, 1-4 August 2000. ICES Marine Science Symposia, 215: pp. 172-178 In: Anderson, E.D. (Ed.) (2002). 100 Years of Science under ICES: Papers from a Symposium held in Helsinki, 1-4 August 2000. ICES Marine Science Symposia, 215. ICES: Copenhagen. V, 610 pp., meer In: ICES Marine Science Symposia. ICES/Reitzel: Copenhagen. ISSN 0906-060X, meer

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Beschikbaar in	Auteurs
VLIZ: Non-open access 305771 [ aanvragen ]

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Trefwoorden

Analysis > Water analysis Models Water quality ANE, Noordzee [Marine Regions] Marien/Kust

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Sonneveldt, H.L.A. Baretta, J.W. Laane, R.W.P.M., meer

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Abstract

During the last 20 years, several chemical water quality models of the North Sea have been constructed. In general, the available processes, knowledge, data, and parameters have been integrated to describe the distribution, cycling, and fate of metals and organic compounds. Thus, it is possible, from a scientific point of view, to evaluate and identify gaps in knowledge. In some countries, these models have also been used to verify whether emission reduction measures were sufficient to attain water quality objectives. Intercomparisons have demonstrated that various models still show considerable differences in the simulated concentrations of substances. There is still a need for appropriate validation data. The question arises whether further development of North Sea water quality models could benefit from a more systematic approach to uncertainty analysis and from establishing unambiguous quality criteria for evaluating model results. International cooperation is important, to improve both field knowledge as weIl as models. Better "tuning" of the data necessary for monitoring purposes and model parameterization, initialization, and validation still needs attention. ICES could intensify its coordinating role, using its organizational network and data holdings.

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