IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v32y2018i2d10.1007_s11269-017-1837-9.html
   My bibliography  Save this article

A Particle Swarm Optimization Assessment for the Determination of Non-Darcian Flow Parameters in a Confined Aquifer

Author

Listed:
  • A.Ufuk Şahin

    (Hacettepe University)

Abstract

Being one of the preliminary in-situ testing methods, aquifer pumping tests would provide significant insights which form a basis for the aquifer characterization. The use of Darcian based flow models to describe the groundwater flow would be ineffective for the aquifer pumping tests under certain circumstances. Non-Darcian flow models could therefore construct more accurate portrayal of physical reality for the assessment of aquifer testing. The interpretation of flow parameters obtained from non-Darcian flows via classical curve matching methods seems extremely difficult to acquire a unique match since the well-defined type curves have not been developed. In this study, an evolutionary optimization based algorithm, called as Particle Swarm Optimization (PSO), was established to determine the flow parameters namely power index, storativity and the turbulent factor which serves as an apparent hydraulic conductivity. The proposed PSO based parameter estimation scheme was implemented for a number of numerical test cases and the estimation performance was evaluated by comparing with available population based algorithms. The results reveal that the PSO based estimation approach is successfully able to identify the flow parameters in an accurate and fast manner. A number of sensitivity analyses were also conducted to draw the limitations of the introduced PSO based technique. The positive findings from this study pointed the potential capability of using PSO as a viable algorithm to process the complex relations in the flow.

Suggested Citation

  • A.Ufuk Şahin, 2018. "A Particle Swarm Optimization Assessment for the Determination of Non-Darcian Flow Parameters in a Confined Aquifer," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(2), pages 751-767, January.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:2:d:10.1007_s11269-017-1837-9
    DOI: 10.1007/s11269-017-1837-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-017-1837-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-017-1837-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Plischke, Elmar, 2012. "An adaptive correlation ratio method using the cumulative sum of the reordered output," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 149-156.
    2. Bolado-Lavin, R. & Castaings, W. & Tarantola, S., 2009. "Contribution to the sample mean plot for graphical and numerical sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(6), pages 1041-1049.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Payam Sarkhosh & Amgad Salama & Yee-Chung Jin, 2021. "Implicit Finite-Volume Scheme to Solve Coupled Saint-Venant and Darcy–Forchheimer Equations for Modeling Flow Through Porous Structures," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4495-4517, October.
    2. A. Ufuk Şahin, 2021. "Automatic Shifting Method for the Identification of Generalized Radial Flow Parameters by Water Cycle Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(15), pages 5205-5223, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    2. Yeratapally, Saikumar R. & Glavicic, Michael G. & Argyrakis, Christos & Sangid, Michael D., 2017. "Bayesian uncertainty quantification and propagation for validation of a microstructure sensitive model for prediction of fatigue crack initiation," Reliability Engineering and System Safety, Elsevier, vol. 164(C), pages 110-123.
    3. Zhai, Qingqing & Yang, Jun & Zhao, Yu, 2014. "Space-partition method for the variance-based sensitivity analysis: Optimal partition scheme and comparative study," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 66-82.
    4. Soha Saad & Florence Ossart & Jean Bigeon & Etienne Sourdille & Harold Gance, 2021. "Global Sensitivity Analysis Applied to Train Traffic Rescheduling: A Comparative Study," Energies, MDPI, vol. 14(19), pages 1-29, October.
    5. Tarantola, S. & Kopustinskas, V. & Bolado-Lavin, R. & Kaliatka, A. & Ušpuras, E. & Vaišnoras, M., 2012. "Sensitivity analysis using contribution to sample variance plot: Application to a water hammer model," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 62-73.
    6. Xing Liu & Enrico Zio & Emanuele Borgonovo & Elmar Plischke, 2024. "A Systematic Approach of Global Sensitivity Analysis and Its Application to a Model for the Quantification of Resilience of Interconnected Critical Infrastructures," Energies, MDPI, vol. 17(8), pages 1-24, April.
    7. Kucherenko, S. & Klymenko, O.V. & Shah, N., 2017. "Sobol' indices for problems defined in non-rectangular domains," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 218-231.
    8. Spiessl, S.M. & Becker, D.-A. & Rübel, A., 2012. "EFAST analysis applied to a PA model for a generic HLW repository in clay," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 190-204.
    9. Wei, Pengfei & Lu, Zhenzhou & Ruan, Wenbin & Song, Jingwen, 2014. "Regional sensitivity analysis using revised mean and variance ratio functions," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 121-135.
    10. Cheng, Lei & Lu, Zhenzhou & Zhang, Leigang, 2015. "Application of Rejection Sampling based methodology to variance based parametric sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 9-18.
    11. Mirko Ginocchi & Ferdinanda Ponci & Antonello Monti, 2021. "Sensitivity Analysis and Power Systems: Can We Bridge the Gap? A Review and a Guide to Getting Started," Energies, MDPI, vol. 14(24), pages 1-59, December.
    12. Kucherenko, Sergei & Song, Shufang & Wang, Lu, 2019. "Quantile based global sensitivity measures," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 35-48.
    13. Plischke, Elmar & Borgonovo, Emanuele, 2019. "Copula theory and probabilistic sensitivity analysis: Is there a connection?," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1046-1059.
    14. Matieyendou Lamboni, 2020. "Uncertainty quantification: a minimum variance unbiased (joint) estimator of the non-normalized Sobol’ indices," Statistical Papers, Springer, vol. 61(5), pages 1939-1970, October.
    15. Spiessl, Sabine M. & Becker, Dirk-A., 2015. "Sensitivity analysis of a final repository model with quasi-discrete behaviour using quasi-random sampling and a metamodel approach in comparison to other variance-based techniques," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 287-296.
    16. Kucherenko, S. & Song, S., 2017. "Different numerical estimators for main effect global sensitivity indices," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 222-238.
    17. Matieyendou Lamboni, 2018. "Global sensitivity analysis: a generalized, unbiased and optimal estimator of total-effect variance," Statistical Papers, Springer, vol. 59(1), pages 361-386, March.
    18. Wei, Pengfei & Lu, Zhenzhou & Song, Jingwen, 2015. "Variable importance analysis: A comprehensive review," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 399-432.
    19. Di Maio, Francesco & Bandini, Alessandro & Zio, Enrico & Alberola, Sofia Carlos & Sanchez-Saez, Francisco & Martorell, Sebastián, 2016. "Bootstrapped-ensemble-based Sensitivity Analysis of a trace thermal-hydraulic model based on a limited number of PWR large break loca simulations," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 122-134.
    20. Plischke, Elmar & Borgonovo, Emanuele & Smith, Curtis L., 2013. "Global sensitivity measures from given data," European Journal of Operational Research, Elsevier, vol. 226(3), pages 536-550.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:32:y:2018:i:2:d:10.1007_s11269-017-1837-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.