Estimation of Discharge over the Submerged Compound Sharp-Crested Weir using Artificial Neural Networks and Genetic Programming

Truncated sharp crested weirs are used to measure flow rate and control upstream water surface in irrigation canals and laboratory flumes. The main advantages of such weirs are ease of construction and capability of measuring a wide range of flows with sufficient accuracy. Artificial neural networks (ANNs) and genetic programming (GP) have recently been used for estimation of hydraulic data. In this study, they were used as alternative tools to estimate flow discharge over the submerged truncated weirs. The hydraulic parameter of water flow rate, Q was determined as functions of the crest width b, upstream head h, weir height P1, tail water depth t Y , and flume width B. Estimations of the ANN and GP models were in good agreement with the measured data. The ANN model results were compared with those of the GP1, GP2, GP3 and GP4 models and showed that the proposed ANN models are much more accurate than the GP models. In addition, GP2 model has a better performance than GP1, GP3, GP4 models.