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SMOES: a simulation model for the Oosterschelde ecosystem. Part I: Description and uncertainty analysis
Klepper, O.; van der Tol, M.W.M.; Scholten, H.; Herman, P.M.J. (1994). SMOES: a simulation model for the Oosterschelde ecosystem. Part I: Description and uncertainty analysis, in: Nienhuis, P.H. et al. The Oosterschelde Estuary (The Netherlands): A case-study of a changing ecosystem. Developments in Hydrobiology, 97: pp. 437-451. https://dx.doi.org/10.1007/978-94-011-1174-4_32
In: Nienhuis, P.H.; Smaal, A.C. (Ed.) (1994). The Oosterschelde Estuary (The Netherlands): A case-study of a changing ecosystem. Developments in Hydrobiology, 97. Springer Science+Business Media: Dordrecht. ISBN 978-94-010-4512-4; e-ISBN 978-94-011-1174-4. XXIV, 597 pp. https://dx.doi.org/10.1007/978-94-011-1174-4, more
In: Dumont, H.J. (Ed.) Developments in Hydrobiology. Kluwer Academic/Springer: The Hague; London; Boston; Dordrecht. ISSN 0167-8418, more
Related to:
Klepper, O.; van der Tol, M.W.M.; Scholten, H.; Herman, P.M.J. (1994). SMOES: a simulation model for the Oosterschelde ecosystem. Part I: Description and uncertainty analysis. Hydrobiologia 282: 437-451. https://dx.doi.org/10.1007/BF00024647, more

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Keywords
    Aquatic communities > Plankton > Phytoplankton
    Aquatic communities > Plankton > Zooplankton
    Dimensions > Size
    Population functions > Growth
    Sea
    ANE, Netherlands, Oosterschelde [Marine Regions]
    Marine/Coastal; Brackish water
Author keywords
    Ecosystem; Simulation model; Sw netherlands; Estuary; Estuarium

Authors  Top 
  • Klepper, O.
  • van der Tol, M.W.M.
  • Scholten, H.
  • Herman, P.M.J., more

Abstract
    The model SMOES integrates the results of the ecological research program conducted in the Oosterschelde estuary before and during the construction of a storm surge barrier. Its aim is to provide a quantitative summary of the research findings and to provide a tool for analysis and prediction of the ecosystem in response to human manipulations. This chapter describes model background and formulations. An uncertainty analysis is used to analyze the effect of uncertainties in model parameters on model outcome. The results of the sensitivity analysis are classified by distinguishing groups of model parameters with a qualitatively different effect on model results. Within these groups, a quantitative ranking of the parameters is possible. It appears that the most sensitive parameters represent processes that are relatively little studied in the Oosterschelde, which may provide guidelines for further research.

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