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Lexicographic optimisation for water resources planning: the case of Lake Verbano, Italy

Enrico Weber, Rodolfo Soncini-Sessa, Andrea Castelletti

edited by: Andrea-Emilio Rizzoli, Anthony J. Jakeman

Lake Verbano is a natural lake used as multipurpose reservoir. The lake supplies water for irrigation and hydropower generation to downstream users, while flood controls are applied to protect the lake shores and the downstream populations on the Ticino river, and environmental preservation constraints must be respected. All these objectives are conflicting and they have different priorities, as stated by the Italian regulation on water use. This paper explores a methodology aimed at solving this conflict. The stakeholders involvement in the decision making process is supported by a Multi Objective Decision Support System for the management of water reservoirs. It is designed to be used at the planning level by water agencies to generate management policies and release plans over various time horizons. The DSS also supports the analysis of various scenarios of possible structural modification of the lake outlet and the introduction of a minimum flow rate on the Ticino river. Solving a multi-objective problem, the DSS algorithm generates ”set-valued” policies, providing the decision makers with multiple choices, thus integrating, not substituting, human intelligence. The knowledge of a set of equivalent controls instead of a single value can be advantageous for decision makers since they can choose the control most suitable to a particular situation on the basis of their experience and information. This set-valued policy, obtained solving the primary optimal control problem, can also be exploited for a further lexicographic optimisation. The primary policy, ensuring the performance of a prioritised group of objectives, can be used to define the feasible set of controls for the secondary optimal control problem, defined for a new set of secondary objectives.


In Proceedings of the iEMSs First Biennial Meeting: Integrated Assessment and Decision Support (2002), pp. 235-240 
Key: INRMM:14376771

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