ABSTRACT

There are different models for the estimation, prediction, and control toward better operation and management of water resources planning and maintenance. In the past, such goals were achieved through crisp mathematical statements and the use of digital computers for the interim calculations. Classical applications did not enhance the hydrologist with philosophical thinking and useful background logical deductions but mechanical application of ready formulations without attention to the underlying set of assumptions, approximations, idealizations, simplications, and logical foundations. Perhaps this is one of the main reasons for the signicant differences in opinion between operators, engineers, and academicians who cannot agree on scientic issues because each one has a different approach or interpretation of the same problem. For instance, most academicians have a formula addiction, operators prefer rule-of-thumb solutions dependent on many years of experience, and engineers prefer rather simple and readily applicable formulations. However, without any career distinction, those interested in the hydrological sciences may have the same common basis in terms of rationality and logical thinking problem solving although they may differ in their philosophical approach. They can ultimately agree on common logical conclusions linguistically. In this context, FL is a problem-solving methodology that lends itself to implementation in systems ranging from simple, small, embedded micro-scale controllers and predictors to large, networked, multichannel personal computer-or workstation-based data acquisition

and control systems. It can be implemented in hardware, software, or a combination of the two. Fuzzy systems provide a simple way to arrive at a denite conclusion based on vague, ambiguous, imprecise, noisy, or missing input information.