Abstract

Reactive transport modeling is a powerful tool to evaluate systems with complex geochemical relations. However, parameters are not always directly measurable. This study represents one of the first attempts to obtain hydrologic, transport and geochemical parameters from an experimental dataset involving transient unsaturated water flow and solute transport, using an automatic inverse optimization (or calibration) algorithm. The data come from previously published, controlled laboratory experiments on the transport of major cations (Na, K, Mg, Ca) during water absorption into horizontal soil columns that were terminated at different times. Experimental data consisted of the depth profiles of water contents (θ), Cl concentrations, and total aqueous and sorbed concentrations of major cations. The dataset was used to optimize several parameters using the reactive transport model, HP1 and the generic optimization code, UCODE. Although the soil hydraulic and solute transport parameters were also optimized, the study focused mainly on the geochemical parameters because the soil columns were constructed from disturbed soil. The cation exchange capacity and the cation exchange coefficients for two exchange models (Gapon and Rothmund–Kornfeld) were optimized. The results suggest that both calibrated models satisfactorily described the experimental data, although the Rothmund–Kornfeld model fit was slightly better. However, information content and surface response analyses indicated that parameters of the Gapon model are well identifiable, whereas those of the Rothmund–Kornfeld model were strongly correlated. The calibrated geochemical parameters were validated using an independent dataset. In agreement with the identifiability analysis, the Gapon approach was better than the Rothmund–Kornfeld model at calculating the observed concentrations of major cations in the soil solution and on the exchange sites.

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