Automatic calibration of the groundwater simulation model with high parameter dimensionality using sequential uncertainty fitting approach

Abstract

Abstract Calibration of the groundwater simulation model is one of the main challenges in the modeling process. In addition, hydrogeological complexities and the lack of field data in terms of time and space lead to uncertainty in the model. Therefore, the present study linked the groundwater simulation model (MODFLOW) and sequential uncertainty fitting approach (SUFI-2) to the uncertainty-based automatic calibration of the Ardabil groundwater model located in northwestern Iran. Hydraulic conductivity, specific yield, recharge rate, the hydraulic conductivity of the riverbed material, and the boundary conductance of the aquifer were considered as the uncertain parameters. Furthermore, the Newton solution method for the unconfined aquifer was used for solving the groundwater flow equation. A Normalized Total Uncertainty Index was defined to evaluate the performance of the SUFI-2 algorithm. According to the MODFLOW-SUFI-2 calibration findings, 60% of observational data was bracketed by a 95% confidence interval, on average. The Ardabil groundwater model was also calibrated with the PSO algorithm. In comparison with SUFI-2, although this method resulted in good coverage of the solution, it obtained irrational values for most parameters since they only aimed to match observational and computational values. Eventually, SUFI-2 showed a small number of simulation runs compared with the PSO algorithm.