Abstract
This chapter describes a decision support system framework specifically developed to meet the growing demands and pressures on water resources managers. A generic concept is designed to be applicable to a wide variety of specific water resources system configurations, institutional conditions, and management issues. The framework is based on a detailed model of the water resources system being simulated and include scenario planning in combination with state-of-the-art large scale network flow optimization algorithm. Issues from the demand-side such as water use patterns, costs, and water allocation schemes are considered equally well as supply-side issues such as reservoirs, and water transfers. The system applies integrated approach to simulating both natural (e.g., runoff, baseflow) and man-made components (e.g., reservoirs, groundwater pumping) of water systems. This allows the system user access to a more comprehensive view of the broad range of factors that must be considered in managing water resources for present and future use. The framework stresses out the sovereignty of the user, therefore features menu-driven graphics-based interfaces that facilitate user interaction and can be customized for water availability analysis, conjunctive surface and groundwater use, infrastructure planning , assessing irrigation potential and reservoir performance, estimating water supply capacity and to find equitable trade-offs among stakeholders requirements.
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Notes
- 1.
In this book stakeholder include all persons, groups and organizations with an interest or in an issue, either because they will be affected or because they may have some influence on its outcome. This includes individual citizens and companies, economic and public interest groups, government bodies and experts.
- 2.
An operation rule is a law that specifies how a component of a water resources system operates for various purposes (quantity, quality) as a function of system states and parameters [226].
- 3.
For the numerical solution of large scale non-linear programming problems interior point (IP) solvers have become popular during the last years because of their superior behavior for NLPs with many inequality constraints.
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© 2016 Springer-Verlag Berlin Heidelberg
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Karimanzira, D. (2016). Model Based Decision Support Systems. In: Rauschenbach, T. (eds) Modeling, Control and Optimization of Water Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16026-4_5
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DOI: https://doi.org/10.1007/978-3-642-16026-4_5
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Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-642-16026-4
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