Closed‐flow column experiments: A numerical sensitivity analysis of reactive transport and parameter uncertainty

Abstract The identification of transport parameters by inverse modeling often suffers from equifinality or parameter correlation when models are fitted to measurements of the solute breakthrough in column outflow experiments. This parameter uncertainty can be approached by performing multiple experiments with different sets of boundary conditions, each provoking observations that are uniquely attributable to the respective transport processes. A promising approach to further increase the information potential of the experimental outcome is the closed‐flow column design. It is characterized by the recirculation of the column effluent into the solution supply vessel that feeds the inflow, which results in a damped sinusoidal oscillation in the breakthrough curve. In order to reveal the potential application of closed‐flow experiments, we present a comprehensive sensitivity analysis using common models for adsorption and degradation. We show that the sensitivity of inverse parameter determination with respect to the apparent dispersion can be controlled by the experimenter. For optimal settings, a decrease in parameter uncertainty as compared to classical experiments by an order of magnitude is achieved. In addition, we show a reduced equifinality between rate‐limited interactions and apparent dispersion. Furthermore, we illustrate the expected breakthrough curve for equilibrium and nonequilibrium adsorption, the latter showing strong similarities to the behavior found for completely mixed batch reactor experiments. Finally, breakthrough data from a reactive tracer experiment is evaluated using the proposed framework with excellent agreement of model and experimental results.