APPLICATION OF THE HBMO APPROACH TO PREDICT THE TOTAL SEDIMENT DISCHARGE

Abstract

River sediment discharge estimation is a very important process for the water resourcemanagement. Sediment discharge is usually calculated either from the direct measurements ofsediment concentration or sediment transport empirical equations. Due to several difficulties inapplying empirical equations and direct measurements, in this study a general equation isdeveloped to estimate the total sediment load with a good accuracy. An artificial intelligent modelbased on Honey Bee Mating Optimization (HBMO) is used to estimate the parameters of theproposed equation. The set of variables in the model is based on evaluating some of the existingempirical equations and also the prior researches to find the dominant parameters in the sedimenttransport 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 ofthe 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 andpowers of the general equation. Three data sets of different rivers have been chosen to demonstratethe 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 twocommon 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 modelefficiency.