6 - Application of fuzzy theory to snowmelt runoff

Summary

ABSTRACT Fuzzy theory (logic) is introduced to reduce uncertainty in the prediction of snowmelt runoff. It has been used to control plants, traffic junctions, subway systems, etc. The tanks model of Sugawara seems to be the most reliable method enabling computation of the snowmelt runoff in Japanese conditions. However, it is difficult to identify the parameters of this model and much data are needed for calibration. Fuzzy logic is the tool that gives the best prediction while it does not require the optimal parameters of the prediction model (tanks model). If the fuzzy logic is employed, the deviation between the observed values and the predicted ones is automatically minimized step by step. The prediction by the fuzzy logic is based on the value of the membership functions used. The effect of different membership functions on the prediction is tested by changing coefficients in time. As a result, despite the complexity of the phenomenon of snowmelt runoff, the prediction is in a good agreement with observation.

INTRODUCTION

A fuzzy set theory developed by Zadeh (1965) is presently being applied in many fields. For example, Mamdani (1974, 1981) used a fuzzy algorithm to control a plant (laboratorybuilt steam engine). Further, Pappis & Mamdani (1977) used the fuzzy logic for a traffic-junction control. Recent use of fuzzy methods can be found in the field of complex industrial processes (Tong, 1977) and feedback analysis (Cumani, 1982, Tanaka et al., 1982, and Tong, 1980). Fujita (1985) predicted runoff from rainfall by adopting a fuzzy logic.