Auto-Calibration of Aquifer Parameters Using Aquifer Distributed Mathematical Models and Direct Searching Algorithm

Document Type : Research Paper


Faculty of Science, Chamran University


Simulation of behavior of aquifers into determining groundwater exploitation rate and planning for sustainable use of groundwater is very important. In this regard, groundwater models using hydraulic, hydrological and hydro-geological parameters were developed to predict the quality and quantity of aquifer parameters. Good knowledge of these parameters can be increase the accuracy of aquifer simulation. For this purpose, a structure based on advance optimization methods for calibration of parameters with low accuracy (coefficient of hydrodynamic, aquifer recharge and withdrawal rates) were developed. In the proposed model, minimizing the sum of the square differences between simulated and observed groundwater level was considered as the objective function. Allowable range of calibration parameters has been considered as constraints. The governing flow equations of the aquifer used to determine the groundwater level in each cells. These equations were solved by the finite difference method. by runing the proposed model, the optimal values of parameters were determined in each cell. The comparison between simulated and observed groundwater level shows the capability of the proposed approach in accuratey estimation of the aquifer parameters.


Main Subjects

1. Carrera, J., Medina, A., Heredia, J., Vives, L., Ward, J., and Walters, G. (1989). “Parameter estimation in groundwater modelling: From theory to application.” Hydrogeo Chem, Inc., Tucson, Arizona, USA.
2. Thiery, D. (1994). “Calibration of groundwater models by optimization of parameters in homogeneous geological zones.” Stochastic and Statistical Methods in Hydrology and Environmental EngineeringWater Science and Technology Library, 10(4), 69-82.
3. Fallah-Mehdipour, E., Bozorg Haddad, O., and Mariño, M.A. (2013). “Developing reservoir operational decision rule by genetic programming.” J. of Hydroinformatics, 15(1), 103-119.
4. Bozorg Haddad, O., Afshar, A., and Mariño, M.A. (2008a). “Honey-bee mating optimization (HBMO) algorithm in deriving optimal operation rules for reservoirs.” J. of Hydroinformatics, 10(3), 257-264.
5. Bozorg Haddad, O., Afshar, A., and Mariño, M.A. (2008b). “Design-operation of multi-hydropower reservoirs: HBMO approach.” Water Resources Management, 22(12), 1709-1722.
6. He, H., Takase, K., and Wang, Y. (2007). “Regional groundwater prediction model using automatic parameter calibration SCE method for a coastal plain of Seto Inland Sea.” Water Resources Management, 21(6), 947-959.
7. Bastani, M., Kholghi, M., and Rakhshandehroo, G.R. (2010). “Inverse modeling of variable-density groundwater flow in a semi-arid area in Iran using a genetic algorithm.” Hydrogeology Journal, 18(5), 1191-1203.
8. Samuel, M.P., and Jha, M.K. (2003). “Estimation of aquifer parameters from pumping test data by genetic algorithm optimization technique.” J. of Irrigation and Drainage Engineering, 5(1), 348-359.
9. Schoups, G., Addams, C.L., and Gorelick, S.M. (2005). “Multi-objective calibration of a surface water-groundwater flow model in an irrigated agricultural region: Yaqui Valley, Sonora, Mexico.” Hydrology and Earth System Sciences, 9(5), 549-568.
10. Bekele, E.G., and Nicklow, J.W. (2007). “Multi-objective automatic calibration of SWAT using NSGA-II.” J. of Hydrology, 341(3-4), 165-176.
11. Afshar, A., Kazemi, H., and Saadatpour, M. (2011). “Particle swarm optimization for automatic calibration of large scale water quality model (CE-QUAL-W2): Application to Karkheh reservoir, Iran.” Water Resources Management, 25(10), 2613-2632.
12. Dakhlaoui, H., Bargaoui, Z., and Bardossy, A. (2012). “Toward a more efficient calibration schema for HBV rainfall–runoff model.” J. of Hydrology, 445-446(11), 161-179.
13. Sun, A.Y., Green, R., Swenson, S., and Rodell, M. (2012). “Toward calibration of regional groundwater models using GRACE data.” J. of Hydrology, 422-423(23), 1-9.
14. Bakker, M., Maas, K., and Von Asmuth, J. R. (2008). “Calibration of transient groundwater models using time series analysis and moment matching.” Water Resources Research, 44(4), doi:10.1029/2007WR006239.
15. Todd, D.K., and Mays, L.W. (2005). Groundwater hydrology, John Wiley & Sons, Inc., N.Y, USA.
16. Karahan, H., and Ayvaz, M.T. (2005). “Transient groundwater modeling using spreadsheets.” Advances in Engineering Software, 36(6), 374-384.
17. Mohammad Rezapour Tabari, M. (2009). “Uncertainty based conjunctive use modeling in regional scale.” Ph.D. Dissertation, Civil and Environmental Engineering Department, AmirKabir University of Technology, Tehran. (In Persian)