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Understanding the effects of subsidence on unconfined aquifer parameters by integration of Lattice Boltzmann Method (LBM) and Genetic Algorithm (GA)

Author

Listed:
  • Roghayeh Yousefi

    (Shiraz University)

  • Nasser Talebbeydokhti

    (Shiraz University)

  • Seyyed Hosein Afzali

    (Shiraz University)

  • Maryam Dehghani

    (Shiraz University)

  • Ali Akbar Hekmatzadeh

    (Shiraz University of Technology)

Abstract

Excessive exploitation of groundwater has hitherto led to a significant land subsidence in a considerable number of plains in Iran. The compaction of aquifer layers ends up with changes in aquifer parameters, including hydraulic conductivity (Kx), specific yield (Sy), and compressibility (α). Accordingly, a precise estimation of aquifer parameters, Kx, Sy, and α seems essential for future water resources planning and management. In this study, an innovative inversion solution based on the combination of lattice Boltzmann method (LBM) and genetic algorithm (GA) was developed to determine the aquifer parameters, Kx, Sy, and α in Darab plain (in Fars province, Iran), which is highly subject to land subsidence. Herein, a newly developed LBM for unconfined groundwater flow was employed by incorporating the amount of subsidence measured by synthetic aperture radar interferometry (InSAR) spanning from 2010 to 2016. In order to optimize the aquifer parameters, the whole process of inverse modeling is replicated on the annual basis from 2010 to 2016 which leads to the temporal estimation of the aquifer parameters. Due to the compaction occurring in the aquifer system, a declining temporal trend is observed in the aquifer parameters in most parts of the plain. By fitting a function to time-dependent aquifer parameters, Kx, Sy, and α, their corresponding values and consequently the amount of subsidence in the near future, i.e., 2017, are predicted. The small average relative error (~ 3.5%) between the predicted land subsidence and the InSAR measurements demonstrates the high performance of the proposed inverse modeling approach. Graphical abstract

Suggested Citation

  • Roghayeh Yousefi & Nasser Talebbeydokhti & Seyyed Hosein Afzali & Maryam Dehghani & Ali Akbar Hekmatzadeh, 2023. "Understanding the effects of subsidence on unconfined aquifer parameters by integration of Lattice Boltzmann Method (LBM) and Genetic Algorithm (GA)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(2), pages 1571-1600, January.
    • Handle: RePEc:spr:nathaz:v:115:y:2023:i:2:d:10.1007_s11069-022-05607-1
    DOI: 10.1007/s11069-022-05607-1
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    References listed on IDEAS

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    1. Chan, Timothy C.Y. & Kaw, Neal, 2020. "Inverse optimization for the recovery of constraint parameters," European Journal of Operational Research, Elsevier, vol. 282(2), pages 415-427.
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