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 |
| 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. |
|
