Modeling the Baltic Sea Eutrophication in a Decision Support System

• Published in: Ambio Vol. 36; no. 2; pp. 141 - 148
• Main Authors: Savchuk, Oleg P, Wulff, Fredrik
• Format: Journal Article
• Language: English
• Published: Sweden Royal Swedish Academy of Sciences 01.04.2007; Springer Nature B.V
• Subjects: Animals; Aquaculture - methods; Aquaculture - statistics & numerical data; Baltic States; Basins; Biogeochemistry; Boundary conditions; Brackish; Data assimilation; Decision support systems; Decision Support Techniques; Ecosystem; Ecosystem management; Ecosystem models; Environmental Monitoring - methods; Environmental Monitoring - statistics & numerical data; Eutrophication; Freshwater; Geography; Marine; Marine Biology; Models, Biological; Nitrogen; Nitrogen - metabolism; Nitrogen fixation; Nutrient concentrations; Nutrient Dynamics from Land to Sea; Nutrient transport; Nutrients; Oceans and Seas; Oxygen - metabolism; Phosphorus; Phosphorus - metabolism; Phosphorus cycle; Seas; Sediments; Time Factors; Water Movements; Water Pollutants - metabolism; Water Pollutants - toxicity; Water pollution; Baltic States; Baltic Sea; ANE, Baltic Sea
• ISSN: 0044-7447; 1654-7209
• DOI: 10.1579/0044-7447(2007)36[141:MTBSEI]2.0.CO;2

SANBALTS (Simple As Necessary Baltic Long-Term Large-Scale) is a model of the coupled nitrogen and phosphorus cycles. This model has been developed as an integral part of the decision support system Marine Research on Eutrophication's Nest with the overall aim to evaluate management options for reducing Baltic Sea eutrophication. Simulated nutrient and oxygen concentrations as well as transport flows and major biogeochemical fluxes can be analyzed in many different ways, including construction of detailed nutrient budgets and tracing the fate of nutrient inputs. The large amounts of data that exist for this sea makes it possible to validate model results with observations. Major biogeochemical properties of the Baltic Sea are discussed through an analyses of model sensitivity to external forcing and internal parameterizations. Model results emphasize two features that are especially important for ecosystem management: i) impacts of local measures would always be modified by the long-range transports from other regions and ii) the response to significant changes in loads would only be seen after several decades.