An effective parameterization to quantify multiple solute flux breakthrough curves

Abstract. To understand soil and groundwater contamination we study the temporal and spatial aspects of solute transport in the unsaturated zone. One monitoring instrument that captures both aspects is the multi-compartment sampler (MCS). With the MCS developed by Bloem et al. (2010) we are able to measure the downward solute fluxes in 100 compartments at the depth of installation of the MCS, with a minimal disturbance of the flow field. Over time this dataset results in 100 individual solute flux breakthrough curves (BTCs) (temporal aspect). Sorting the BTCs in descending order of solute mass gives the spatial solute distribution curve (spatial aspect).

We present a method to quantitatively characterize datasets gathered with MCS (or single samplers installed at multiple locations in a field at the same depth). The method approximates the full set of breakthrough curves using only a single function with four to eight parameters, which combines both temporal and spatial effects of solute transport in soils. This is achieved by modeling the scaled solute flux density breakthrough curves (BTC_F) for each compartment as the solution of a conventional one-dimensional equilibrium convection disperion equation (CDE), without modifications. We detect and parameterize any relationships between the resulting transport velocities and dispersion coefficients of the individual BTC_Fs. Finally the spatial aspect is parameterized using the Beta distribution.

This method is based on the flux density BTCs directly, which for transport phenomena is preferred over solute concentrations. In three experiments on undisturbed soils, the resulting approximation matched the data well.