Field-scale solute transport parameters derived from tracer tests in large undisturbed soil columns
Dirk Mallants
+ Author Affiliations
- Author Affiliations
CSIRO Land and Water, Waite Road - Gate 4, Glen Osmond, SA 5064, Australia. Email: Dirk.Mallants@csiro.au
Soil Research 52(1) 13-26 https://doi.org/10.1071/SR13143
Submitted: 4 May 2013 Accepted: 3 September 2013 Published: 5 February 2014
Abstract
Transport parameters obtained from laboratory tracer experiments were used to evaluate the stochastic form of the equilibrium convection–dispersion equation (CDE) in describing the transition of scale, i.e. from the column or local scale to a larger field scale. Local-scale solute breakthrough curves (BTCs) were measured in 1-m-long and 0.3-m-diameter undisturbed soil columns by means of time-domain reflectometry at six depths for a 79-h input pulse of chloride. The local-scale data were analysed in terms of the equilibrium CDE and the mobile–immobile non-equilibrium transport model (MIM). At the local scale, the MIM transport model better described the observed early breakthrough and the tailing of the BTC than did the CDE. A linear regression analysis indicated that the relationship between the hydrodynamic dispersion D and pore-water velocity v was of the form D = 31vl.92 (correlation ρv,D = 0.74). Averaging of the local-scale BTCs across the field produced a large-scale or field-scale mean BTC; at the greatest observation depth (0.8 m) the field-scale dispersivity <D>/<v> = λ equals 0.656 m. The results further showed that for large values of the mean dispersion coefficient, <D>, local-scale dispersion is an important mechanism for field-scale solute spreading, whereas the standard deviation, σD, and the correlation between v and D, ρvD, have negligible effects on field-scale transport. Stochastic stream tube models supplemented with statistical properties of local-scale transport parameters provide a practical and computationally efficient tool to describe heterogeneous solute transport at large spatial scales.
Additional keywords: convection–dispersion model, mobile–immobile model, stochastic stream tube model, time-domain reflectometry, parameter optimisation, contaminant transport.
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