Relationship Between Dual-Domain Parameters and Practical Characterization Data

Dual-domain solute transport models produce significantly improved agreement to observations compared to single-domain (advection-dispersion) models when used in an a posteriori data fitting mode. However, the use of dual-domain models in a general predictive manner has been a difficult and persistent challenge, particularly at field-scale where characterization of permeability and flow is inherently limited. Numerical experiments were conducted in this study to better understand how single-rate mass transfer parameters vary with aquifer attributes and contaminant exposure. High-resolution reference simulations considered 30 different scenarios involving variations in permeability distribution, flow field, mass transfer timescale, and contaminant exposure time. Optimal dual-domain transport parameters were empirically determined by matching to breakthrough curves from the high-resolution simulations. Numerical results show that mobile porosity increases with lower permeability contrast/variance, smaller spatial correlation length, lower connectivity of high-permeability zones, and flow transverse to strata. A nonzero non-participating porosity improves empirical fitting, and becomes larger for flow aligned with strata, smaller diffusion coefficient, and larger spatial correlation length. The non-dimensional mass transfer coefficient or Damkohler number tends to be close to 1.0 and decrease with contaminant exposure time, in agreement with prior studies. The best empirical fit is generally achieved with a combination of macrodispersion and first-order mass transfer. Quantitative prediction of ensemble-average dual-domain parameters as a function of measurable aquifer attributes proved only marginally successful.