Traditional approaches to the management of an artificial reservoir involve the use of linear, dynamic, nonlinear or stochastic programming. Hence a purely model-based approach would be extremely difficult and thus, recently, a large number of papers devoted to the solution of reservoir management problems based on fuzzy logic approaches have appeared. In this work, two management problems of a reservoir are addressed with fuzzy logic: the definition of the water flow to supply to the user, a typical decision problem; and the regulation of the dam gate, which is a typical control problem. Both problems have been integrated in an Automated Fuzzy Decision and Control System (AFDCS) that is able to identify the ordinary and drought operating conditions. Fuzzy rules are developed from a database derived from the traditional experience of operators and they have been optimized with a genetic algorithm. Two cost functionals are used, able to weight user's desiderata (water demand) with water waste (water spills and evaporation). Three strategies are developed for a case study and are validated in different scenarios, using Monte Carlo simulations and worst case situations. Results show a good performance of AFDCS to alleviate the consequences of drought and to control of the dam gate.