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Improvement on the Existing Equations for Predicting Longitudinal Dispersion Coefficient

Author

Listed:
  • Mohamad Javad Alizadeh

    (K.N. Toosi University of Technology)

  • Davoud Ahmadyar

    (K.N. Toosi University of Technology)

  • Ali Afghantoloee

    (Universite Laval)

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.

Suggested Citation

  • Mohamad Javad Alizadeh & Davoud Ahmadyar & Ali Afghantoloee, 2017. "Improvement on the Existing Equations for Predicting Longitudinal Dispersion Coefficient," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(6), pages 1777-1794, April.
    • Handle: RePEc:spr:waterr:v:31:y:2017:i:6:d:10.1007_s11269-017-1611-z
    DOI: 10.1007/s11269-017-1611-z
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    References listed on IDEAS

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    1. Liu, Bo & Wang, Ling & Jin, Yi-Hui & Tang, Fang & Huang, De-Xian, 2005. "Improved particle swarm optimization combined with chaos," Chaos, Solitons & Fractals, Elsevier, vol. 25(5), pages 1261-1271.
    2. Xiangtao Li & Huawen Liu & Minghao Yin, 2013. "Differential Evolution for Prediction of Longitudinal Dispersion Coefficients in Natural Streams," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5245-5260, December.
    3. Hazi Azamathulla & Aminuddin Ghani, 2011. "Genetic Programming for Predicting Longitudinal Dispersion Coefficients in Streams," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(6), pages 1537-1544, April.
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