APPLICATION OF THE HBMO APPROACH TO PREDICT THE TOTAL SEDIMENT DISCHARGE

River sediment discharge estimation is a very important process for the water resource management. Sediment discharge is usually calculated either from the direct measurements of sediment concentration or sediment transport empirical equations. Due to several difficulties in applying empirical equations and direct measurements, in this study a general equation is developed to estimate the total sediment load with a good accuracy. An artificial intelligent model based on Honey Bee Mating Optimization (HBMO) is used to estimate the parameters of the proposed equation. The set of variables in the model is based on evaluating some of the existing empirical equations and also the prior researches to find the dominant parameters in the sediment transport formulas. Based on these investigations some parameters such as average flow velocity, water surface slope, average flow depth, median particle diameter, water temperature and width of the rivers are more effective and have been selected as the dominant variables in this research. With consideration of the mentioned variables, this model tries to determine the coefficients and powers of the general equation. Three data sets of different rivers have been chosen to demonstrate the model. The model has been calibrated by 75% of the data and validated by the remaining 25%. To calculate the proposed model efficiency and validity, the results have been compared with two common models. Therefore, the Sediment Rating Curve (SRC) and Non Linear Regression (NLR) models have been applied and the statistical results have been proposed to show the model efficiency.