Determination of Discharge Distribution in Meandering Compound Channels Using Machine Learning Techniques
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Volume 148, Issue 1
Abstract
Accurate flow rate prediction is essential to analyze flood control, sediment transport, riverbank protection, and so forth. The flow rate distribution becomes even more complicated in compound channels due to the momentum transfer between different subsections across the width of the channel. Conventional channel division methods estimate flow distribution at the main channel and floodplains by assuming a division line with zero apparent shear stress. The article attempts to develop a model to calculate the percentage of discharge in the main channel using techniques such as Group Method of Data Handling—Neural Network (GMDH-NN) and gene-expression programming (GEP) by incorporating the effects of various geometric and hydraulic parameters. The paper proposes a modified channel division method with a variable-inclined interface, with zero apparent shear force distribution at the channel subsections according to the statistical indices employed to assess these models’ performance in predicting . This variable-inclined interface changes its slope according to the channel parameters. The model’s effectiveness is verified by validating with experimental observations by conventional analytical methods.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article. In detail, data can be found from the relevant literatures.
Acknowledgments
The authors acknowledge the support from the Department of Civil Engineering, National Institute of Technology Rourkela, India, to conduct the experiments.
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Journal of Irrigation and Drainage Engineering
Volume 148 • Issue 1 • January 2022
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© 2021 American Society of Civil Engineers.
History
Received: Apr 21, 2021
Accepted: Sep 22, 2021
Published online: Oct 28, 2021
Published in print: Jan 1, 2022
Discussion open until: Mar 28, 2022
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