The main purpose of this study was to analyze and predict scour depth and hydraulic performance of piers using soft computing methods and to estimate scour depths using artificial neural networks and ANFIS methods. In the present study, three situations were studied: a rectangular pier without a cable (type I), a rectangular pier with a cable that has a diameter equal to 10% of the pier diameter, and a cable twist angle of 15 degrees (type II), and a rectangular pier with a cable 15% of the pier diameter and an angle of twist of 12 degrees (type III). Tests were carried out with different flow-approach angles: zero, 5, 10, and 15 degrees. Dimensional analysis based on the π Buckingham method was performed. Then, the effect of different parameters, and their importance for estimating scour depth was investigated. Piers with an angle of 15 degrees with respect to the direction of flow had the greatest depth of scouring. Cables can reduce scour depths at this angle; for the second and third classes of piers, the scouring is 10 and 22% compared to the first pier classification. For the second type of pier, angles of 5, 10, and 15 degrees led to increases in scouring depths of 3, 21, and 37% compared to the zero-angle situation.
