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Toward reliable calibration of aquifer hydrodynamic parameters: characterizing and optimization of arid groundwater system using swarm intelligence optimization algorithm

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Abstract

Despite advanced development in computational techniques, the issue of how to adequately calibrate and minimize misfit between system properties and corresponding measurements remains a challenging task in groundwater modeling. Two important features of the groundwater regime, hydraulic conductivity (k) and specific yield (S y), that control aquifer dynamic vary spatially within an aquifer system due to geologic heterogeneity. This paper provides the first attempt in using an advanced swarm-intelligence-based optimization algorithm (cuckoo optimization algorithm, COA) coupled with a distributed hydrogeology model (i.e., MODFLOW) to calibrate aquifer hydrodynamic parameters (S y and k) over an arid groundwater system in east Iran. Our optimization approach was posed in a single-objective manner by the trade-off between sum of absolute error and the adherent swarm optimization approach. The COA optimization algorithm further yielded both hydraulic conductivity and specific yield parameters with high performance and the least error. Estimation of depth to water table revealed skillful prediction for a set of cells located at the middle of the aquifer system whereas showed unskillful prediction at the headwater due to frequent water storage changes at the inflow boundary. Groundwater depth reduced from east toward west and southwest parts of the aquifer because of extensive pumping activities that caused a smoothening influence on the shape of the simulated head curve. The results demonstrated a clear need to optimize arid aquifer parameters and to compute groundwater response across an arid region.

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References

  • Bastani M, Kholghi M, Rakhshandehroo GR (2010) Inverse modeling of variable-density groundwater flow in a semi-arid area in Iran using a genetic algorithm. Hydrogeology J 18(5):1191–1203

    Article  Google Scholar 

  • Bekele EG, Nicklow JW (2007) Multi-objective automatic calibration of SWAT using NSGA-II. J of Hydrology 341(3–4):165–176

    Article  Google Scholar 

  • Boussinesq J (1904) Recherches théoriques sur l’écoulement des nappes d’eau infiltrées dans le sol et sur le débit des sources. Journal de mathématiques pures et appliquées 11:363–394

    Google Scholar 

  • Dupuit J (1857) Mouvement de l'eau a travers le terrains permeables. C R Hebd Seances Acad Sci 45:92–96

    Google Scholar 

  • Dupuit J (1863) Estudes Theoriques et Pratiques sur le Mouvement desEaux. Dunod, Paris

    Google Scholar 

  • Emace R, Chodhury A, Anaya R, Way SC (2000) A numerical groundwater flow model of the upper and middle trinity aquifer, Hill Country Area, Texas, Water Development Board. Report number: 00–02

  • Forchheimer P (1886) Über die Ergiebigkeit von Brunnen-Anlagen und Sickerschlitzen. Z Architekt Ing-Ver (Hannover) 32:539–563

    Google Scholar 

  • Hamraz BS, Akbarpour A, Pourreza-Bilondi M (2016) Assessment of parameter uncertainty of MODFLOW model using GLUE method (case study: Birjand plain). Journal of Water and Soil Conservation 22(6):61–79 (In Persian)

    Google Scholar 

  • He H, Takase K, Wang Y (2007) Regional groundwater prediction model using automatic parameter calibration SCE method for a coastal plain of Seto Inland Sea. Water Resour Manag 21(6):947–959

    Article  Google Scholar 

  • Hill MC, Tiedeman CR (2007) Effective calibration of groundwater models, with analysis of data, sensitivities, predictions, and uncertainty. John Wiley and Sons, New York

    Google Scholar 

  • Kersic N (1997) Quantitative solution in hydrology and groundwater modeling. Lewis Publishers

  • Lee SM, Jin YM, Woo SK, Shin DH (2013) Approximate cost estimating model of eco-type trade for river facility construction using case-based reasoning and genetic algorithms. KSCE J Civ Eng 17(2):292–300, 374. doi:10.1007/s12205-013-1638-5

    Article  Google Scholar 

  • Liu Y, Gupta HV (2007) Uncertainty in hydrologic modeling: toward an integrated data assimilation framework

  • Maliki R, Karami GH, Dolati Ardajani F, Hoseini H, Asadian F (2011) Optimization of hydrodynamic coefficients of Shahroud plain by using GMS6.5. Fourth Conference of Water Resources Management, Tehran, Iran, pp. 1–7

    Google Scholar 

  • Moharram SH, Gad MI, Saafan TA, Allah SK (2012) Optimal groundwater management using genetic algorithm in El-Farafra oasis, western desert, Egypt. Water Resour Manag 26(4):927–948. doi:10.1007/s11269-011-9865-

    Article  Google Scholar 

  • Moore C, Wöhling T, Doherty J (2010) Efficient regularization and uncertainty analysis using a global optimization methodology. Water Resource Research 46:W08527. doi:10.1029/2009WR008627

    Article  Google Scholar 

  • Moriasi DN, Arnold JG, Van Liew MW, Binger RL, Harmel RD, Veith T (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3):885–900

    Article  Google Scholar 

  • Olsthoorn TN (2013) mfLab: environmet for MODFLOW suite groundwater modeling. http://code.google.come/p/mfLab. Accessed 19 Dec

  • Prickett TA (1975) Modeling techniques for groundwater evaluation. Journal of Advances in Hydrosciense 10(1):1–143

    Article  Google Scholar 

  • Rafipour-Langeroudi M, Kerachian R, Bazargan-Lari MR (2014) Developing operating rules for conjunctive use of surface and groundwater considering the water quality issues. KSCE J Civ Eng 18(2):454–461

    Article  Google Scholar 

  • Rajabioun R (2011) Cuckoo optimization algorithm. Appl Soft Comput 11(8):5508–5518

    Article  Google Scholar 

  • Rojas R, Feyen L, Dassargues A (2008) Conceptual model uncertainty in groundwater modeling: combining generalized likelihood uncertainty estimation and Bayesian model averaging. Water Resource Research 44:W12418

    Article  Google Scholar 

  • Sadeghi-Tabas S, Samadi SZ, Akbarpour A, Pourreza-Bilondi M (2016) Sustainable groundwater modeling using single-and multi-objective optimization algorithms. J Hydroinformatics :jh2016006

  • Saltelli A, Ratto M, Andres T, Campolongo F, Cariboni J, Gatelli D, Saisona M, Tarantola S (2008) Global sensitivity analysis, the primer. Wiley and Sons, Chichester, West Sussex, England, p. 292

    Google Scholar 

  • Schoups G, Addams CL, Gorelick SM (2005) Multi-objective calibration of a surface water-groundwater flow model in an irrigated agricultural region: Yaqui Valley, Sonora, Mexico. Hydrol Earth Syst Sci 9(5):549–568

    Article  Google Scholar 

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Acknowledgments

The authors appreciate those persons and agencies that assisted in accessing research data. Special thanks are owed to Professor Theo Olsthoorn from the Delft University of Technology for his fruitful discussions and technical support on groundwater modeling and processes. Particular acknowledgment is given to the cuckoo developer, Dr. Ramin Rajabioun, from University of Tehran, for providing cuckoo MATLAB code.

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Authors and Affiliations

  1. Department of Civil Engineering, Iran University of Science and Technology (IUST), Tehran, Iran

    S. Sadeghi-Tabas

  2. Department of Water Engineering, University of Birjand, Birjand, Iran

    S. Sadeghi-Tabas & M. Pourreza-Bilondi

  3. Department of Civil Engineering, University of Birjand, Birjand, Iran

    A. Akbarpour

  4. Department of Civil and Environmental Engineering, University of South Carolina, Columbia, SC, 29208, USA

    S. Samadi

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  1. S. Sadeghi-Tabas
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  2. A. Akbarpour
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  3. M. Pourreza-Bilondi
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  4. S. Samadi
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Correspondence to S. Sadeghi-Tabas.

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This article is part of the Topical Collection on Water Resources in Arid Areas

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Sadeghi-Tabas, S., Akbarpour, A., Pourreza-Bilondi, M. et al. Toward reliable calibration of aquifer hydrodynamic parameters: characterizing and optimization of arid groundwater system using swarm intelligence optimization algorithm. Arab J Geosci 9, 719 (2016). https://doi.org/10.1007/s12517-016-2751-9

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  • DOI: https://doi.org/10.1007/s12517-016-2751-9

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