Predicting Longitudinal Dispersion Coefficient in Natural Streams Using M5′ Model Tree
Publication: Journal of Hydraulic Engineering
Volume 138, Issue 6
Abstract
The longitudinal dispersion coefficient is a key parameter in determining the distribution of pollution concentration, especially in temporally time-varying source cases after full cross-sectional mixing has occurred. Several studies have been performed to present simple formulas to predict it. However, they may not always result in an accurate prediction because of the complexity of the phenomenon. In this study, a M5′ model tree was used to develop a new model for predicting the longitudinal dispersion coefficient. The main advantages of the model trees are that (1) they provide transparent formulas and offer more insight into the obtained formulas and (2) they are more convenient to develop and employ compared with other soft computing methods. To develop the model tree, extensive field data sets consisting of hydraulic and geometrical characteristics of different rivers were used. By using error measures, the performance of the model was also compared with the performance of other existing equations. Overall, the results showed that the developed model outperforms the existing formulas and can serve as a valuable tool for predicting of the longitudinal dispersion coefficient.
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Acknowledgments
The authors acknowledge the comments of professor Jorg Imberger on the previous version of the manuscript. The authors also thank Meysam Bali, Ebrahim Jafari, Ali Behnood and Amin Asgarian for their help in improving the manuscript.
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Published In
Journal of Hydraulic Engineering
Volume 138 • Issue 6 • June 2012
Pages: 542 - 554
Copyright
© 2012. American Society of Civil Engineers.
History
Received: Feb 16, 2011
Accepted: Dec 14, 2011
Published online: May 15, 2012
Published in print: Jun 1, 2012
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