Abstract
Scour in the downstream of hydraulic structures is a phenomenon which usually occurs due to exceeding the velocity or shear stress from a critical level. In this paper by using the laboratory data by Borman- Jouline and De-Agostino research, it was tried to get more accurate equations in order to calculate the maximum depth of scour in the downstream of the water level regulation structures. Comparing these equations with the results of the other researchers showed that these equations are much more accurate. After that Artificial neural networks (ANNs) with learning algorithm of error back propagation (BP) were used to estimate maximum water scour depth, and the model which has seven neurons in its hidden layer was produced as the most appropriate model. Finally by using statistical parameters, the ANN model was compared with optimized equations. The results of this study showed high correlation between artificial neural network and proposed equation.
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