Stochastic network optimization models for investment planning
Annals of Operations Research
Scenarios and policy aggregation in optimization under uncertainty
Mathematics of Operations Research
Annals of Operations Research
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Decomposition methods in stochastic programming
Mathematical Programming: Series A and B - Special issue: papers from ismp97, the 16th international symposium on mathematical programming, Lausanne EPFL
Generating Scenario Trees for Multistage Decision Problems
Management Science
Environmental Modelling & Software
Reliable water supply system design under uncertainty
Environmental Modelling & Software
Environmental Modelling & Software
A formal framework for scenario development in support of environmental decision-making
Environmental Modelling & Software
Short communication: Modeling climate change uncertainties in water resources management models
Environmental Modelling & Software
Expert Systems with Applications: An International Journal
Using reservoir trophic-state indexes in optimisation modelling of water-resource systems
Environmental Modelling & Software
Environmental Modelling & Software
Seasonal multi-year optimal management of quantities and salinities in regional water supply systems
Environmental Modelling & Software
Comparison of generic simulation models for water resource systems
Environmental Modelling & Software
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In this paper we present a scenario analysis approach for water system planning and management under conditions of climatic and hydrological uncertainty. The scenario analysis approach examines a set of statistically independent hydrological scenarios, and exploits the inner structure of their temporal evolution in order to obtain a ''robust'' decision policy, so that the risk of wrong decisions is minimised. In this approach uncertainty is modelled by a scenario-tree in a multistage environment, which includes different possible configurations of inflows in a wide time-horizon. In this paper we propose a Decision Support System (DSS) that performs scenario analysis by identifying trends and essential features on which to base a robust decision policy. The DSS prevents obsolescence of optimiser codes, exploiting standard data format, and a graphical interface provides easy data-input and results analysis for the user. Results show that scenario analysis could be an alternative approach to stochastic optimisation when no probabilistic rules can be adopted and deterministic models are inadequate to represent uncertainty. Moreover, experimentation for a real water resources system in Sardinia, Italy, shows that practitioners and end-users can adopt the DSS with ease.