Evaluation of Uncertainty in Contaminant Transport Model in Column Experiment

To assess the uncertainty of contaminant transport models in column experiments it is essential to select reliable models for simulating column experiments and estimation of reliable parameters in order to identify the processes governing contaminant transport. So the overall goal of this study is to specify the uncertainty associated with the model development by defining several conceptual models and selecting the most probable model and the best estimate of contaminant transport model parameters and model prediction. For exploring uncertainty in column experiment we considered four models from the literature including the equilibrium and non-equilibrium convection dispersion models i.e. CDE1 and CDE2 convection-dispersion models and MIM1 and MIM2 mobile-immobile models. The model selection criteria were used to evaluate the probabilities of the four models. Using the full covariance matrix that considers residual correlation has caused definitive recommendations on the basis of AIC, AICc, BIC, and KIC statistics and the model probability. The result showed that for the slow flow case due to the satisfaction of the equilibrium assumption the CDE2 and for the high flow case MIM1 were receiving the highest model probability and the least uncertainty. Finally it is concludes that the reliability of the model’s data interpretation can be improved by considering alternative transport processes and quantifying uncertainty in the experiment.