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Automatic Shifting Method for the Identification of Generalized Radial Flow Parameters by Water Cycle Optimization

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  • A. Ufuk Şahin

    (Hacettepe University)

Abstract

The general radial flow (GRF) could successfully analyze the groundwater flow in a fractured medium which has generally a more complex mechanism due to the scale-dependent heterogeneity and dynamic processes for both individual fracture and fracture networks. A new optimization scheme, referred to as the automatic shifting method (ASM), was established in order to eradicate the subjectivity and some definite difficulties in classical graphical curve matching (GCM) for the determination flow parameters of GRF from in-situ pumping test data. The logic behind the ASM is similar to GCM but it simplifies and enhances the estimation process by optimizing newly introduced parameters (the horizontal and vertical shifts) together with the flow dimension parameter via Water Cycle Algorithm (WCA). The proposed ASM was tested with several hypothetical pumping test scenarios as well as a number of real field data. In addition, the capability of WCA was thoroughly compared with other competitive derivative-free, nature inspired population-based optimization algorithms by implementing a multi decision criteria analysis. The proposed ASM with WCA could achieve the outstanding estimation performance for the implemented analyses. In conclusion, ASM has a great potential to be modified for interpreting test data obtained from different groundwater models.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:15:d:10.1007_s11269-021-02995-0
    DOI: 10.1007/s11269-021-02995-0
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    References listed on IDEAS

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    1. Abbas Afshar & Fariborz Masoumi & Sam Solis, 2015. "Reliability Based Optimum Reservoir Design by Hybrid ACO-LP Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 2045-2058, April.
    2. Wenzhuo Wang & Benyou Jia & Slobodan P. Simonovic & Shiqiang Wu & Ziwu Fan & Li Ren, 2021. "Comparison of Representative Heuristic Algorithms for Multi-Objective Reservoir Optimal Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(9), pages 2741-2762, July.
    3. 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.
    4. Hamid Reza Yavari & Amir Robati, 2021. "Developing Water Cycle Algorithm for Optimal Operation in Multi-reservoirs Hydrologic System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(8), pages 2281-2303, June.
    5. Q. Ma & M. Abily & M. Du & P. Gourbesville & Oliver Fouché, 2020. "Integrated Groundwater Resources Management: Spatially-Nested Modelling Approach for Water Cycle Simulation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(4), pages 1319-1333, March.
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