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Improvement on the Existing Equations for Predicting Longitudinal Dispersion Coefficient

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Abstract

Accurate prediction of longitudinal dispersion coefficient (K) is a key element in studying of pollutant transport in rivers when the full cross sectional mixing has occurred. In this regard, several research studies have been carried out and different equations have been proposed. The predicted values of K obtained by different equations showed a great amount of uncertainty due to the complexity of the phenomenon. Therefore, there is still a need to make an improvement on the existing predictive models. In this study, a multi-objective particle swarm optimization (PSO) technique was used to derive new equations for predicting longitudinal dispersion coefficient in natural rivers. To do this, extensive field data, including hydraulic and geometrical characteristics of different rivers were applied. The results of this study were compared with those of the previous studies using the statistical error measures. The comparison revealed that the proposed model is superior to the previous ones. According to this study, PSO algorithm can be applied to improve the performance of the predictive equations by finding optimum values of the coefficients. The proposed model can be successfully applied to estimate the longitudinal dispersion coefficient for a wide range of rivers’ characteristics.

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Authors and Affiliations

  1. Faculty of Civil Engineering, K.N. Toosi University of Technology, Tehran, Iran

    Mohamad Javad Alizadeh & Davoud Ahmadyar

  2. Center for Research in Geomatics, Department of Geomatics, Universite Laval, Quebec, Canada

    Ali Afghantoloee

Authors
  1. Mohamad Javad Alizadeh
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  2. Davoud Ahmadyar
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  3. Ali Afghantoloee
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Corresponding author

Correspondence to Mohamad Javad Alizadeh.

Appendix

Appendix

Table 5 * Summary of the Geometric, Hydraulic and Dispersion coefficient datasets employed in this study
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Alizadeh, M.J., Ahmadyar, D. & Afghantoloee, A. Improvement on the Existing Equations for Predicting Longitudinal Dispersion Coefficient. Water Resour Manage 31, 1777–1794 (2017). https://doi.org/10.1007/s11269-017-1611-z

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  • DOI: https://doi.org/10.1007/s11269-017-1611-z

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