Suspended sediment concentration estimation by Honey-Bees Mating Optimization (HBMO) algorithm

So far, various models have been developed to identify the relation between discharge and suspended sediment load. Empirical relations such as sediment rating curves are often applied to determine the average relationship between discharge and suspended sediment load. This type of model generally underestimate when sediment load are estimated from water discharge using least squares regression of log-transformed variables. To avoid that drawback, it is proposed to employ HBMO algorithm as a new tool for optimization of this relation. Results of this model are compared with two different sediment rating curves (SRC). The daily streamflow and suspended sediment concentration data from Mad River Catchment near Arcata, USA are used as a case study. Statistics and graphs present that the HBMO algorithm performs better than the other models in estimation of suspended sediment concentration in the particular data sets used in this study.