Heterogeneity in hydraulic conductivity and its role on the macroscale transport of a solute plume: From measurements to a practical application of stochastic flow and transport theory

Abstract

[1] The spatial variability of hydraulic conductivity in a shallow unconfined aquifer located at North Bay, Ontario, composed of glacial-lacustrine and glacial-fluvial sands, is examined in exceptional detail and characterized geostatistically. A total of 1878 permeameter measurements were performed at 0.05 m vertical intervals along cores taken from 20 boreholes along two intersecting transect lines. Simultaneous three-dimensional (3-D) fitting of Ln(K) variogram data to an exponential model yielded geostatistical parameters for the estimation of bulk hydraulic conductivity and solute dispersion parameters. The analysis revealed a Ln(K) variance equal to about 2.0 and 3-D anisotropy of the correlation structure of the heterogeneity (l 1 , l 2 , and l 3 equal to 17.19, 7.39, and 1.0 m, respectively). Effective values of the hydraulic conductivity tensor and the value of the longitudinal macrodispersivity were calculated using the theoretical expressions of Gelhar and Axness (1983). The magnitude of the longitudinal macrodispersivity is reasonably consistent with the observed degree of longitudinal dispersion of the landfill plume along the principal path of migration. Variably saturated 3-D flow modeling using the statistically derived effective hydraulic conductivity tensor allowed a reasonably close prediction of the measured water table and the observed heads at various depths in an array of piezometers. Concomitant transport modeling using the calculated longitudinal macrodispersivity reasonably predicted the extent and migration rates of the observed contaminant plume that was monitored using a network of multilevel samplers over a period of about 5 years. It was further demonstrated that the length of the plume is relatively insensitive to the value of the longitudinal macrodispersivity under the conditions of a steady flow in 3-D and constant source strength. This study demonstrates that the use of statistically derived parameters based on stochastic theories results in reliable large-scale 3-D flow and transport models for complex hydrogeological systems. This is in agreement with the conclusions reached by Sudicky (1986) at the site of an elaborate tracer test conducted in the aquifer at the Canadian Forces Base Borden.Citation: Sudicky, E. A., W. A. Illman, I. K. Goltz, J. J. Adams, and R. G. McLaren (2010), Heterogeneity in hydraulic conductivity and its role on the macroscale transport of a solute plume: From measurements to a practical application of stochastic flow and transport theory, Water Resour. Res., 46, W01508,

The impact of medium architecture of alluvial settings on non-Fickian transport

“…The variances of Ln (K) for the hydrofacies models in this study are mostly in the range of 20 to 27 (where K has units of m/d) ( Table 1). Similar variability of Ln (K) has been observed elsewhere [11,44], while smaller values of Ln (K) variance have also been reported in relatively homogeneous aquifers such as in glacial outwash [86] and in datasets of borehole-scale measurements that do not resolve discrete low-K aquitard layers (e.g., [2,9]). Values of Ln (K) greater than 10 may be characteristic of alluvial hydrofacies models that include both aquifer and aquitard units [38,39].…”

“…The variances of Ln (K) in the Monte Carlo simulations in this study are mostly in the range of 20 to 27, which may be typical of hydrofacies models of heterogeneous alluvium [39]. The applicability of the above conclusions in more homogeneous settings [86] remains to be seen.…”

A model-based assessment of the potential use of compound-specific stable isotope analysis in river monitoring of diffuse pesticide pollution

“…Furthermore, it is possible to include interception, transpiration and evaporation processes. Applications of HGS include large watershed modelling (Goderniaux et al, 2009;Li et al, 2008), simulations of aquifer-river interactions in hypothetical model domains (Doble et al, 2012;McCallum et al, 2010), and the analysis of contaminant transport in groundwater (Rivett et al, 2006;Sudicky et al, 2010).…”

How can we be sure fracking will not pollute aquifers? Lessons from a major longwall coal mining analogue (Selby, Yorkshire, UK)

“…In practice, uncertainties in various governing parameters mean that it is more logical to undertake calculations of pollutant inflow rates and concentrations probabilistically (e.g., Sudicky et al 2010). This entails defining both the input and output parameter sets as probability density functions.…”