uncertainty of complexity

One of the factors that lead to uncertainty in the mathematical model of groundwater flow is the uncertainty due to the complexity of the conceptual model that results from the increase of model parameters. Considering complexity in groundwater modeling can aid in selecting an optimal model, and can avoidmodel uncertainty and misleading conclusions. The purpose of this study is to investigate the uncertainty of the complexity of the mathematical model of the Najafabad aquifer. In this regard, six conceptual models with five different degrees of complexity with the number of calibrated model parameters (4, 16, 20, 22, 26, and 26 parameters) with the same observational data in Najafabad aquifer located in Isfahan province in a steady-state and for the year 2018-2019 were developed and model selection criteria (AIC, AICC, BIC, and KIC) were used to evaluate the probability of models. The results showed that model#1 with four parameters, which is the simplest model, was selected as the best model and has the least uncertainty. But models 5 and 6, which are the most complex models, have the most uncertainty and the least level of confidence. Therefore, it can be said that in defining the conceptual model of an aquifer, determining the optimal number of parameters will decrease the uncertainty of the mathematical model.