Longitudinal Dispersion Coefficient Modeling in Natural Channels using Fuzzy Logic

Abstract

AbstractResearchers have long used differential equations to investigate longitudinal dispersion processes, which can be derived under certain assumptions and include a longitudinal dispersion coefficient (D1). In practice, most empirical equations are developed only for D1. Unfortunately, many critical assumptions in the derivation of these equations are not considered, and consequently, these equations can only be used with precautions and reservations. The goal of this study is to develop a fuzzy model to predict D1 in natural channels. The model depends on 65 data sets extracted from the literature. The variables are the depth, width and mean cross‐sectional velocity of the flow, shear velocity and D1. The data is divided for training and testing phases. The model is compared with measured data and seven existing equations. The comparison depends on seven statistical characteristics, four different error modes, and a contour map. It is observed that the fuzzy model yields results that are more reliable than existing methods and it can be used more easily and efficiently.