Estimating and comparison of the amount of solid in the river with fuzzy logic and conventional methods

Accurate estimation of the amount of sediment in rivers has an important place in issues such as pollution of the river, determination of the life-span of dams and river transportation. In this study, sediment amount in a stream was estimated using Multiple Linear Regression (MLR), Adaptive Network Based Fuzzy Inference System (ANFIS), Fuzzy Logic-Simple Membership Functions and Fuzzy Rules Generation Technique (SMRGT) and Sediment Rating Curve (KMAE) methods. The Patapsco River near Catonsville, USA was used as the study area. In this study, real-time flow rate-turbidity and sediment matter data from the sediment observation station 01589025 in the Patapsco River between 2015 and 2018 were used. The amount of sediment was tried to be estimated by using flow rate and turbidity as input data. Obtained results were compared with MLR, ANFIS, SMRGT and sediment key curve. It has been seen that the values using with the fuzzy logic models give results consistent with the observation ones.