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Performance Evaluation of Improved Symbiotic Organism Search Algorithm for Estimation of Solute Transport in Rivers

Author

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  • Mohamad Reza Madadi

    (University of Jiroft)

  • Saeid Akbarifard

    (Shahid Chamran University of Ahvaz)

  • Kourosh Qaderi

    (Shahid Bahonar University of Kerman)

Abstract

Accurate estimation of solute transport has significant importance in water resources and environmental engineering. Among the various types of mathematical formulation for modeling of solute transport, the transient storage model has been widely applied by different researchers as an appropriate model. In this study, an improved version of symbiotic organism search (SOS) algorithm was used to estimate the parameters of transient storage model. A large set of data from natural rivers of USA was collected from the literature and used for derivation and validation of the algorithm. The performance of the algorithm was evaluated by standard statistical indices. Accordingly, the values of R and RMSE for transient storage model parameters (Kf, T and ε) were obtained 0.922 and 30.62 (for Kf), 0.596 and 5645 (for T) and, 0.643 and 0.019 (for ε) for whole dataset. In addition, the results of this study were compared with those obtained by different reserachers via other models. The results indicate the higher capability of improved SOS algorithim compared to the others in estimating the transient storage model parameters.

Suggested Citation

  • Mohamad Reza Madadi & Saeid Akbarifard & Kourosh Qaderi, 2020. "Performance Evaluation of Improved Symbiotic Organism Search Algorithm for Estimation of Solute Transport in Rivers," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(4), pages 1453-1464, March.
    • Handle: RePEc:spr:waterr:v:34:y:2020:i:4:d:10.1007_s11269-020-02512-9
    DOI: 10.1007/s11269-020-02512-9
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    References listed on IDEAS

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    1. Rajeev Sahay, 2012. "Erratum to: Predicting Transient Storage Model Parameters of Rivers by Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(13), pages 3687-3687, October.
    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. Rajeev Sahay, 2012. "Predicting Transient Storage Model Parameters of Rivers by Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(13), pages 3667-3685, October.
    4. Tae Cheong & Bassam Younis & Il Seo, 2007. "Estimation of key parameters in model for solute transport in rivers and streams," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(7), pages 1165-1186, July.
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    Cited by:

    1. Mohammad Reza Sharifi & Saeid Akbarifard & Kourosh Qaderi & Mohamad Reza Madadi, 2021. "Developing MSA Algorithm by New Fitness-Distance-Balance Selection Method to Optimize Cascade Hydropower Reservoirs Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(1), pages 385-406, January.

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