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Predicting Transient Storage Model Parameters of Rivers by Genetic Algorithm

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  • Rajeev Sahay

Abstract

The presence of transient storage zone modifies the riverine pollutant transport. In the present work, new empirical expressions for three key parameters of transient storage model (TSM), an important method for predicting concentration variation of pollutants in rivers, have been derived employing genetic algorithm on published hydraulic data on river reaches and TSM parameters. The proposed expressions use few hydraulic and geometric characteristics of rivers that are usually available. Based on various performance indices, it can be concluded that the proposed expressions predict TSM parameters more reliably in comparison to the other empirical expressions for predicting TSM parameters. Copyright Springer Science+Business Media B.V. 2012

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:26:y:2012:i:13:p:3667-3685
    DOI: 10.1007/s11269-012-0092-3
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    References listed on IDEAS

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    1. 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. Jianzhong Zhou & Shuo Ouyang & Xuemin Wang & Lei Ye & Hao Wang, 2014. "Multi-Objective Parameter Calibration and Multi-Attribute Decision-Making: An Application to Conceptual Hydrological Model Calibration," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(3), pages 767-783, February.
    2. 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.
    3. Gokmen Tayfur, 2017. "Modern Optimization Methods in Water Resources Planning, Engineering and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3205-3233, August.

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    1. 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.
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