Stage discharge prediction in heterogeneous compound open channel roughness

Abstract Prediction of flow discharge in the rivers performs important role in flood management. Using the compound open channel concept, the real condition in natural streams can be accurately estimated. A compound open channel includes a main channel and floodplains that usually floodplains are rougher than the main channel. Several empirical approaches have been proposed for estimating the discharge of flow in the compound open channels. In this study, the accuracy of the empirical approaches including Single Channel Method, Divided Channel Method (DCM), and Coherence Method were assessed to estimate the discharge of flow in heterogeneous compound channel roughness. To this purpose series of experiments were programmed and performed at the hydraulic laboratory of Tehran University. To compare the obtained results with previous studies, 396 data related to discharges of flow in the compound open channel were collected and used for evaluating the performance of applied methods. Results showed that DCM with assuming the virtual perpendicular line as boundry line between sub-sections (main channel and floodplains) with coefficient of determination more than the 0.90 has suitable performance through the empirical approaches and can be used for practical works.

[1]  P. Ackers Flow formulae for straight two-stage channels , 1993 .

[2]  Mohammad Najafzadeh,et al.  Application of improved neuro-fuzzy GMDH to predict scour depth at sluice gates , 2015, Earth Science Informatics.

[3]  Subhasish Dey M.Ish GENERALIZED GEOMETRIC ELEMENTS OF ARTIFICIAL CHANNELS: A NOTE , 1998 .

[4]  Y. Zech,et al.  Momentum transfer for practical flow computation in compound channels , 1999 .

[5]  Kejun Yang,et al.  Stage-Discharge Prediction in Compound Channels , 2014 .

[6]  Amir H. Haghiabi,et al.  Hydraulic characteristics of circular crested weir based on Dressler theory , 2012 .

[7]  H. Md. Azamathulla,et al.  Flow discharge prediction in compound channels using linear genetic programming , 2012 .

[8]  Mohammad Najafzadeh,et al.  Prediction of maximum scour depth around piers with debris accumulation using EPR, MT, and GEP models , 2016 .

[9]  Mohammad Najafzadeh,et al.  Evaluation of neuro-fuzzy GMDH-based particle swarm optimization to predict longitudinal dispersion coefficient in rivers , 2016, Environmental Earth Sciences.

[10]  W. T. Barlow,et al.  Stage-Discharge Models for Concrete Orifices: Impact on Estimating Detention Basin Drawdown Time , 2015 .

[11]  Galip Seckin,et al.  A comparison of one-dimensional methods for estimating discharge capacity of straight compound channels , 2004 .

[12]  Computational Approach to Improving the Efficiency of River Discharge Measurement , 2016 .

[13]  Mohammad Najafzadeh,et al.  Scour prediction in long contractions using ANFIS and SVM , 2016 .

[14]  Subhash C. Jain,et al.  Open-Channel Flow , 2000 .

[15]  Abbas Parsaie,et al.  Predictive modeling the side weir discharge coefficient using neural network , 2016, Modeling Earth Systems and Environment.

[16]  Mohammad Najafzadeh,et al.  Neuro-fuzzy GMDH systems based evolutionary algorithms to predict scour pile groups in clear water conditions , 2015 .

[17]  Abbas Parsaie,et al.  Predictive modeling of discharge in compound open channel by support vector machine technique , 2015, Modeling Earth Systems and Environment.

[18]  Abbas Parsaie,et al.  "SAR" Qualities parameter persistence by a compound method of geostatic and artificial neural network (Case study of Jiroft plain) , 2013 .

[19]  W. R. Myers,et al.  Velocity and Discharge in Compound Channels , 1987 .

[20]  S. Mahapatra,et al.  A neural network approach for prediction of discharge in straight compound open channel flow , 2011 .

[21]  Mohammad Najafzadeh,et al.  Neuro-fuzzy GMDH based particle swarm optimization for prediction of scour depth at downstream of grade control structures , 2015 .

[22]  Mohammad Najafzadeh,et al.  Application of a Neuro-Fuzzy GMDH Model for Predicting the Velocity at Limit of Deposition in Storm Sewers , 2017 .

[23]  D. Knight,et al.  Flood Plain and Main Channel Flow Interaction , 1983 .

[24]  Mohammad Najafzadeh,et al.  Estimation of Pipeline Scour due to Waves by GMDH , 2014 .

[25]  D. Knight,et al.  Variable parameter Muskingum-Cunge method for flood routing in a compound channel , 1999 .

[26]  Abbas Parsaie,et al.  The Effect of Predicting Discharge Coefficient by Neural Network on Increasing the Numerical Modeling Accuracy of Flow Over Side Weir , 2015, Water Resources Management.

[27]  D. Knight,et al.  Stage Discharge Relationships for Compound Channels , 1984 .

[28]  M. Muller,et al.  Integrated Water Resources Management in Practice: Better Water Management for Development , 2012 .

[29]  A. Keshavarzi,et al.  Evaluation of 1-D and 2-D models for discharge prediction in straight compound channels with smooth and rough floodplain , 2016 .

[30]  Mohamad Basel Al Sawaf,et al.  Application of shallow-water acoustic tomography to measure flow direction and river discharge , 2016 .

[31]  Abbas Parsaie,et al.  Prediction of discharge coefficient of side weir using adaptive neuro-fuzzy inference system , 2016, Sustainable Water Resources Management.

[32]  Mohammad Najafzadeh,et al.  Group method of data handling to predict scour depth around vertical piles under regular waves , 2013 .

[33]  Stage Discharge Prediction in a Prismatic Compound Channel , 2013 .

[34]  Abbas Parsaie,et al.  Analyzing the distribution of momentum and energy coefficients in compound open channel , 2016, Modeling Earth Systems and Environment.

[35]  H. Md. Azamathulla,et al.  Comparison between linear genetic programming and M5 tree models to predict flow discharge in compound channels , 2012, Neural Computing and Applications.

[36]  Mohammad Najafzadeh,et al.  Comparison of group method of data handling based genetic programming and back propagation systems to predict scour depth around bridge piers , 2011 .

[37]  Abbas Parsaie,et al.  Computational  Modeling of Pollution Transmission in Rivers , 2017, Applied Water Science.

[38]  Mohammad Najafzadeh,et al.  GMDH based back propagation algorithm to predict abutment scour in cohesive soils , 2013 .

[39]  Abbas Parsaie,et al.  Predicting the longitudinal dispersion coefficient by radial basis function neural network , 2015, Modeling Earth Systems and Environment.

[40]  Mohammad Najafzadeh,et al.  Group Method of Data Handling to Predict Scour at Downstream of a Ski-Jump Bucket Spillway , 2014, Earth Science Informatics.

[41]  Mohammad Najafzadeh Neurofuzzy-Based GMDH-PSO to Predict Maximum Scour Depth at Equilibrium at Culvert Outlets , 2016 .

[42]  Iehisa Nezu,et al.  Calculation of Compound‐Open‐Channel Flow , 1993 .

[43]  Issam Khatib,et al.  Validation of Regression Analysis in the Prediction of Discharge in Asymmetric Compound Channels , 2013 .

[44]  Galip Seckin,et al.  Comparison of an ANN approach with 1-D and 2-D methods for estimating discharge capacity of straight compound channels , 2010, Adv. Eng. Softw..

[45]  I. Al-Khatib,et al.  Evaluation of separate channel methods for discharge computation in asymmetric compound channels , 2012 .

[46]  P. K. Mohanty,et al.  Estimation of discharge and its distribution in compound channels , 2014 .

[47]  Abbas Parsaie,et al.  CFD modeling of flow pattern in spillway’s approach channel , 2015, Sustainable Water Resources Management.

[48]  Abbas Parsaie,et al.  Prediction of energy dissipation on the stepped spillway using the multivariate adaptive regression splines , 2016 .

[49]  D. Knight,et al.  Analytic Stage-Discharge Formulas for Flow in Straight Prismatic Channels , 2007 .

[50]  A. Keshavarzi,et al.  Kinetic energy and momentum correction coefficients in straight compound channels with vegetated floodplain , 2016 .

[51]  Abbas Parsaie,et al.  Prediction of side weir discharge coefficient by support vector machine technique , 2016 .

[52]  Mohammad Najafzadeh,et al.  Neuro-Fuzzy GMDH to Predict the Scour Pile Groups due to Waves , 2015, J. Comput. Civ. Eng..

[53]  Abbas Parsaie,et al.  Predicting the side weir discharge coefficient using the optimized neural network by genetic algorithm , 2014 .

[54]  Peter R. Wormleaton,et al.  Flow Distribution in Compound Channels , 1985 .

[55]  Oscar Castro-Orgaz,et al.  Application of potential flow to circular-crested weir , 2008 .

[56]  Mohammad Najafzadeh,et al.  Prediction of pipeline scour depth in clear-water and live-bed conditions using group method of data handling , 2012, Neural Computing and Applications.

[57]  A. Parsaie,et al.  Prediction of flow discharge in compound open channels using adaptive neuro fuzzy inference system method , 2017 .

[58]  P. R. Wormleaton,et al.  An improved method of calculation for steady uniform flow in prismatic main channel/flood plain sections , 1990 .

[59]  Mohammad Najafzadeh,et al.  Evaluation of GMDH networks for prediction of local scour depth at bridge abutments in coarse sediments with thinly armored beds , 2015 .

[60]  Abbas Parsaie,et al.  Numerical modeling of flow pattern in dam spillway’s guide wall. Case study: Balaroud dam, Iran , 2016 .

[61]  Ali R. Vatankhah Flow measurement using circular sharp-crested weirs , 2010 .

[62]  Abbas Parsaie,et al.  Predictive modeling of discharge of flow in compound open channel using radial basis neural network , 2016, Modeling Earth Systems and Environment.

[63]  K. C. Patra,et al.  Stage-Discharge Prediction for Straight and Smooth Compound Channels with Wide Floodplains , 2012 .

[64]  F. Huthoff,et al.  Interacting divided channel method for compound channel flow , 2008 .

[65]  Serter Atabay,et al.  1-D modelling of conveyance, boundary shear and sediment transport in overbank flow , 2006 .

[66]  A. Zahiri,et al.  Neuro-Fuzzy GMDH-Based Evolutionary Algorithms to Predict Flow Discharge in Straight Compound Channels , 2015 .