Prediction of Flow Discharge in Compound Open Channels Using Group Method of Data Handling

Document Type : Research Article


1 Ph.D. Candidate of Hydro-Structure Engineering, Water Engineering Department, Lorestan University, Khorramabad, Iran.

2 Ph.D. Candidate of Hydro-Structure Engineering, Water Engineering Department, Gorgan University, Golestan, Iran.

3 Associate professor in Water Engineering, Gorgan University of Agricultural Sciences and Natural, Golestan, Iran.


Prediction of flow through the compound open channel is one of the main problems in the field of hydraulic engineering. One of the main parameter related to the flow properties in the compound open channel is shear stress. The shear stress occurs because of difference of velocities between the main channel and floodplains. The shear stress is the main causes of turbulence and vortex creation on the border of main channel and floodplains. The difference between the roughness of main channel and floodplains intensifies the shear stress in the border zone and also decreases total flow discharge. In this paper, the flow discharge in compound open channels was predicted using group method of data handling technique. To do this, related dataset was collected from literature. Involved parameters in modeling are relative hydraulic depth (Hr ), relative hydraulic radius (Rr ), relative roughness (fr ) and relative area (Ar ). To compare the performance of GMDH with other types of soft computing methods, the MLPNN as most well[1]known soft computing technique was developed as well. Results indicated that the GMDH model with coefficient of determination 0.91 and root means square error 0.057 was more accurate than the MLPNN. Reviewing the structure of developed GMDH model showed that and are the most effective parameters on prediction of flow discharge in compound open channels.


Main Subjects

[1] P. Ackers, Flow formulae for straight two-stage channels, Journal of Hydraulic Research, 31(4) (1993) 509-531.
[2]  S. Atabay, D. Knight, 1-D modelling of conveyance, boundary shear and sediment transport in overbank flow, Journal of Hydraulic Research, 44(6) (2006) 739-754.
[3]  H.M. Azamathulla, A.H. Haghiabi, A. Parsaie, Prediction of side weir discharge coefficient by support vector machine technique, Water Science and Technology: Water Supply, 16(4) (2016) 1002-1016.
[4]  H. Bashiri-Atrabi, K. Qaderi, D.E. Rheinheimer, E. Sharifi, Application of harmony search algorithm to reservoir operation optimization, Water Resources Management, 29(15) (2015) 5729-5748.
[5]  D. Bousmar, Y. Zech, Momentum transfer for practical flow computation in compound channels, Journal of hydraulic engineering, 125(7) (1999) 696- 706.
[6]  P. Conway, J.J. O'Sullivan, M.F. Lambert, Stage– discharge prediction in straight compound channels using 3D numerical models, Proceedings of the Institution of Civil Engineers, Water
[7] Management, 166 (1) (2012) 3-15.
[8]  M. Filonovich, R. Azevedo, L. Rojas-Solórzano, J. Leal, Credibility analysis of computational fluid dynamic simulations for compound channel flow, Journal of Hydroinformatics, 15(3) (2013) 926-938.
[9]  F. Huthoff, P.C. Roos, D.C. Augustijn, S.J. Hulscher, Interacting divided channel method for compound channel flow, Journal of hydraulic engineering, 134(8) (2008) 1158-1165.
[10]  S. Ikeda, I.K. McEwan, Flow and sediment transport in compound channels: the experience of Japanese and UK research, CRC Press, 2009.
[11]  A.G. Ivakhnenko, Polynomial theory of complex systems, IEEE transactions on Systems, Man, and Cybernetics, 1(4) (1971) 364-378.
[12]  K. Khatua, K. Patra, P. Mohanty, Stage-discharge prediction for straight and smooth compound channels with wide floodplains, Journal of hydraulic Engineering, 138(1) (2011) 93-99.
[13]  D. Knight, J. Demetriou, M. Hamed, Stage discharge relationships for compound channels, in: Channels and Channel Control Structures, Springer Berlin Heidelberg, (1984) 445-459.
[14]  T. Koftis, P. Prinos, Reynolds stress modelling of flow in compound channels with vegetated floodplains, Journal of Applied Water Engineering and Research, (2016) 1-11.
[15]  H. Kordi, R. Amini, A. Zahiri, E. Kordi, Improved Shiono and Knight method for overflow modeling, Journal of Hydrologic Engineering, 20(12) (2015) 04015041.
[16]  A. Mohanta, K. Khatua, K. Patra, Flow Modeling   in Symmetrically Narrowing Flood Plains, Aquatic Procedia, 4 (2015) 826-833.
[17]  M. Najafzadeh, G.-A. Barani, H.M. Azamathulla, GMDH to predict scour depth around a pier in cohesive soils, Applied ocean research, 40 (2013) 35- 41.
[18]  M. Najafzadeh, M.R. Balf, E. Rashedi, Prediction   of maximum scour depth around piers with debris accumulation using EPR, MT, and GEP models, Journal of Hydroinformatics, 18(5) (2016) 867-884.
[19]  M. Najafzadeh, A.M. Sattar, Neuro-fuzzy GMDH approach to predict longitudinal dispersion in water networks, Water Resources Management, 29(7) (2015) 2205-2219.
[20]  M.  Najafzadeh,  A.  Tafarojnoruz,   Evaluation   of neuro-fuzzy GMDH-based particle swarm optimization to predict longitudinal dispersion coefficient in rivers, Environmental Earth Sciences, 75(2) (2016) 157.
[21]  M. Najafzadeh, A.R. Zahiri, Neuro-fuzzy GMDH- based evolutionary algorithms to predict flow discharge in straight compound channels, 20(12) (2015) 04015035.
[22]  A. Parsaie, A.H. Haghiabi, Predicting the longitudinal dispersion coefficient by radial basis function neural network, Modeling earth systems and environment, 1(4) (2015) 34.
[23]  A. Parsaie, S. Najafian, M.H. Omid, H. Yonesi, Stage discharge prediction in heterogeneous compound open channel roughness, ISH Journal of Hydraulic Engineering, 23(1) (2017) 49-56.
[24]  A. Parsaie, S. Najafian, H. Yonesi, Flow discharge estimation in compound open channel using theoretical approaches, Sustainable Water Resources Management, 2(4) (2016) 359-367.
[25]  A. Parsaie, H. Yonesi, S. Najafian, Prediction of flow discharge in compound open channels using adaptive neuro fuzzy inference system method, Flow Measurement and Instrumentation, 54 (2017) 288- 297.
[26]  A. Parsaie, H.A. Yonesi, S. Najafian, Predictive modeling of discharge in compound open channel by support vector machine technique, Modeling Earth Systems and Environment, 1(1-2) (2015) 1.
[27]  M. Sahu, K. Khatua, S. Mahapatra, A neural network approach for prediction of discharge in straight compound open channel flow, Flow Measurement and Instrumentation, 22(5) (2011) 438-446.
[28]  K. Shiono, D.W. Knight, Turbulent open-channel flows with variable depth across the channel, Journal of Fluid Mechanics, 222 (1991) 617-646.
[29]  G. Seckin, A comparison of one-dimensional methods for estimating discharge capacity of straight compound channels, Canadian Journal of Civil Engineering, 31(4) (2004) 619-631.
[30]  X. Tang, D.W. Knight, Lateral distributions of streamwise velocity in compound channels with partially vegetated floodplains, Science in China Series E: Technological Sciences, 52(11) (2009) 3357- 3362.
[31]  P. Wormleaton, D. Merrett, An improved method of calculation for steady uniform flow in prismatic main channel/flood plain sections, Journal of Hydraulic Research, 28(2) (1990) 157-174.
[32]  H.A. Yonesi,  M.H.  Omid,  S.A.  Ayyoubzadeh, The hydraulics of flow in non-prismatic compound channels, J Civil Eng Urban, 3(6) (2013) 342-356.
[33]  C.L. Yen, D.E. Overton, Shape Effects on Resistance in Flood Plain Channels, Journal of the Hydraulics Division, ASCE, 99 (HY1) (1973) 21 9-238.