Abstract
This chapter addresses some results concerning the development of a Decision Support System (DSS) for the management of Southern European lagoons, and is particularly focused on the application of the proposed DSS to the management of clam farming in the Sacca di Goro lagoon (Italy). After having established a reference framework for the study and management of coastal lagoons, a general model-based decision support structure is introduced. The development of this tool, obtained within the EU project DITTY, was motivated by the need for a common and flexible framework to ease the integration of the outputs of different models and analyses, as well as to deal with the diversity of socio-economic and environmental characteristics of several application sites. The proposed structure helps integrate and manage in a clear and structured fashion the information provided by different kinds of mathematical and analytical models of a lagoon ecosystem, such as biogeochemical, hydrodynamic, ecological and socio-economic models. Data and information obtained from the models can be used to accomplish the decision task by application of multicriteria analysis. Finally, robustness of the decision with respect to external factors beyond the control of the decision maker is considered in the proposed DSS.
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Notes
- 1.
Web site: http://www.dittyproject.org/
- 2.
Web site: http://www2.nilu.no/eloise/
- 3.
The thermodynamic definition of exergy is the amount of work that a system can perform by being brought into equilibrium with its environment.
- 4.
We distinguish the system, i.e. the part of the real world (environment, people, activities, etc.) that is the object of the decision maker's interests and actions, and the decision support system, i.e. the tool for supporting the decisions.
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Mocenni, C., Casini, M., Paoletti, S., Giordani, G., Viaroli, P., Comenges, JM.Z. (2009). A Decision Support System for the Management of the Sacca di Goro (Italy). In: Marcomini, A., Suter II, G., Critto, A. (eds) Decision Support Systems for Risk-Based Management of Contaminated Sites. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09722-0_19
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