Estimation of Longitudinal Dispersion Coefficient of Rivers by Using Meta-Heuristic Algorithms

Across the world, rivers are the main supply arches for drinking, industry and agriculture. Hence, in recent years, the identification and study of the processes of transport of pollution in rivers has become very important. Longitudinal dispersion coefficient is the most important parameter in the transport equation, and various methods for its estimating and calculating have been presented so far. Considering the nature of the problem, Meta-Heuristic Optimization methods are the important approaches for estimating the longitudinal dispersion coefficient. In this research, the ability of five Meta-Heuristic Algorithms to estimate the parameter was evaluated and compared. The equation of calculating the longitudinal dispersion coefficient using each of the algorithms was presented and the results were compared with the observational data. According to the results, the genetic optimization algorithm has the best accuracy and speed compared to the other algorithms under the same iteration conditions. Then statistical parameters including the mean of the absolute error, root mean squared error and correlation coefficient were used to check the accuracy of the algorithms. These values for the genetic algorithm were 0.4354, 0.1052 and 0.8288, respectively. As a result, it can be safely introduced the equation derived from this algorithm effective in calculating the longitudinal dispersion coefficient.