Integrating Historical Operating Decisions and Expert Criteria into a DSS for the Management of a Multireservoir System

Abstract

This paper presents a collaborative framework to couple historical records with expert knowledge and criteria to define a decision support system (DSS) that supports the seasonal operation of the reservoirs of the Jucar River system. The framework relies on the codevelopment of a DSS tool that is able to explicitly reproduce the decision-making processes and criteria considered by the system operators. Fuzzy logic is used to derive the implicit operating rules followed by the managers, and is based on historical decisions and expert knowledge obtained in the codevelopment process, combining both sources of information. Fuzzy regression is used to forecast future inflows based on the meteorological and hydrological variables considered by the system operators in their decisions on reservoir operation. The DSS was validated against historical records. The developed framework and tools offer the system operators a way to predefine a set of feasible ex ante management decisions, and to explore the consequences associated with any single choice. In contrast with other approaches, the fuzzy-based method used in this study is able to embed inflow uncertainty and its effects in the definition of the decisions on the system operation. Furthermore, the method is flexible enough to be applied to other water resource systems.