Estimating the Discharge Coefficient of the Type B Piano-Key Side Weir at a 120° Curve using RBF and ANFIS Models in Comparison with Artificial Neural Networks

Side weirs are used to control the water level, flow deviations and drain the excess discharge in irrigation networks, sewer systems, and flood control systems. Considering that it is not possible to increase the length of side weirs to increase their capacity, other types of weirs may be used to overcome this problem. Therefore, incorporating weirs that are associated with a higher length of the same width can be helpful. Accordingly, non-linear piano-key weirs may be used side weirs. Numerical methods can be used to estimate the discharge coefficient of piano-key weirs. Bilhan et al. (2011) used an ANN to estimate the discharge coefficient in a curved canal with a labyrinth weir. Ebtehaj et al. (2015) used the GEP model to estimate the coefficient of discharge in a straight canal. Parsaei (2016) studied the accuracy of the ANN in estimating the coefficient of discharge in a sharp-crested rectangular ogee weir and found the ANN to offer an acceptable accuracy. None of the previous studies have addressed the efficiency of intelligent models in estimating the discharge coefficient of ogee-shaped piano-key weirs. Therefore, this study aims to obtain the discharge coefficient of the piano-key weirs using RBF, ANFIS, and ANN models.