J Zhejiang Univ Sci A 15(11):914–924Įmiroglu ME, Baylar AHMET (2003) An investigation of effect of stepped chutes with end sill on aeration performance. KSCE J Civ Eng 20(2):943–950Įbtehaj I, Bonakdari H, Sharifi A (2014) Design criteria for sediment transport in sewers based on self-cleansing concept. ISBN 9789058093523-CAT# RU41258ĭursun OF (2016) An experimental investigation of the aeration performance of Parshall flume and venturi flumes. ISBN 0-08-041918-6Ĭhanson H (2002) Hydraulics of stepped chutes and spillways. KSCE J Civ Eng 15(8):1329–1334Ĭhanson H (1995) Hydraulic design of stepped cascades, channels, weirs and spillways. Water Qual Res J 38(4):753–767īaylar A, Unsal M, Ozkan F (2011) The effect of flow patterns and energy dissipation over stepped chutes on aeration efficiency. J Hydraul Div 104(11):1521–1540īaylar A (2003) An investigation on the use of venturi weirs as an aerator. Generalized structure-group method of data handling GCV:Īvery ST, Novak P (1978) Oxygen transfer at hydraulic structures. Multivariate adaptive regression splines GMDH: Oxygen aeration efficiency of tape water for any room temperature E 20Īdaptive neuro fuzzy inference system MARS: Total number of observations for soft computing techniques E Predicted values from soft computing techniques m Observed values for soft computing techniques k i Number of BFs derived from MARS method w iĬoefficient of transfer function x i and x j Linked with the volume over which oxygen transfer occurs Vĭependent parameter which is predicted using function f( x) a 0Ĭomplexity penalty that increases by number of BFs D Saturation concentration of oxygen in water C 0Ĭoncentration of oxygen in water at time t = 0 C tĬoncentration of oxygen in water at time t in seconds A Volumetric oxygen transfer coefficient or absorption coefficient C s Overall comparison among conventional and advance soft computing models suggests that advance soft computing models perform better than conventional models. MARS model with input combination of ratio of throat width to throat length (W/L), ratio of sill height to throat length (S/L) and Froude number is performing better than that of all other input combinations used for models and found to be more suitable for predicting the E 20. Agreement plot of GS-GMDH and MARS models showed that the MARS model has the maximum exactness in predicting E 20 values at Parshall flumes and its modified forms with the lowest RMSE = 0.0020, MAE = 0.0015. The performance of the models was assessed using four evaluating metrics coefficient of determination ( R 2), mean absolute error (MAE), root mean square error (RMSE) and Nash Sutcliffe model efficacy. In the study, advance soft computing models Multivariate Adaptive Regression Splines (MARS) and Generalized Structure- Group Method of Data Handling (GS-GMDH) have used to predict aeration efficiency ( E 20) values at Parshall flumes and its modified forms and also compared with existing conventional models. Exchange of oxygen between water and air is termed as aeration. It is an economical due to its construction and installation and an accurate in discharge measurement in open channel and non-full pipe. A Parshall flume is a versatile device due to its diverse applications in irrigation canals, mine discharge, dam seepage, sewage treatment plants and many more.