Regional groundwater prediction model using automatic parameter calibration SCE method for a coastal plain of Seto Inland Sea

Operational groundwater prediction models vary in complexity, but most of them have parameters for which values must be estimated. In the present study, the proposed regional groundwater prediction model was based on a nonlinear water balance model, which is very easy to be used once its parameters were determined. The traditional procedure of the model calibration was done manually using a trial and error process of parameter adjustments. In this case, the goodness-of-fit of the calibrated model is based on a visual judgment by comparing the simulated and the observed data. It requires considerable training or experience and is also typically laborious and time consuming. Thus, this paper proposed an approach, which considered the possibilities of using a nonlinear optimization technique -- the Shuffled Complex Evolution (SCE) method to calibrate the groundwater model. The applicability of this technique was demonstrated with a case study for a coastal plain in Japan. The performance of the groundwater model with SCE method was evaluated by comparing the measured and predicted data.