Field study of dispersion in a heterogeneous aquifer: 3. Geostatistical analysis of hydraulic conductivity

Abstract

Observations of the spatial variability of hydraulic conductivity at a tracer test site, located atColumbus Air Force Base in Mississippi, are presented. Direct measurements of hydraulic conductivity of the heterogeneous alluvial aquifer at the site were made using borehole flowmeter logging, slug tests, and a laboratory permeameter to test undisturbed soil cores. Indirect methods estimating hydraulic conductivity were also evaluated, including soil grain size analyses, surface geophysical surveys, and mapping of sediment facies. The spatial covariance of the 2187 hydraulic conductivity values obtained with the borehole flowmeter method was examined. The log hydraulic conductivity variance (cr•2n •c) and the horizontal and vertical correlation scales (An and X,) of 4.5, 12.8 m, and 1.6 m, respectively, were estimated assuming second-order stationarity of the conductivity field. The covariance parameters are uncertain with bounding values that are 24-76% above or below the estimate. Covariance parameters estimated with more limited nonfiowmeter data were within the same magnitude as those obtained using the extensive flowmeter data, suggesting that data from a variety of methods may be used to provide approximate values of the autocovariance parameters. Nonstationarity of the In K field was examined by removing three-dimensional polynomial trend surfaces and calculating variograms of the residuals. Significantly lower estimates for cr•2n K, An and A• of 2.7, 4.8 m, and 0.8 m, respectively, were obtained from the third-order log conductivity residuals. After trend removal, the bounding parameter values differ 15-44% from the estimated values. Accounting for unsteady flow and the uncertainty in the covariance parameters of the third-order log conductivity residuals, the calculated longitudinal and horizontal transverse macrodispersivities ranged from 1.5 m to 1.8 m and 0.3 m to 0.6 m, respectively.

Spatial and temporal variability of crop yield and some Rhodic Hapludox properties under no-tillage

“…High CV values were found for hydraulic conductivity in an Ultisol by Abreu et al (2003). Bosch & West (1998) also reported large variations for hydraulic conductivity in two sandy soils, and Rehfeldt et al (1992) observed high variations of hydraulic conductivity in floodplain soil. Note that independent of the soil and management type, measurements of this property seem to be highly variable.…”

Space‐fractional advection‐dispersion equations with variable parameters: Diverse formulas, numerical solutions, and application to the Macrodispersion Experiment site data

“…The MADE site has a variance of log conductivity [ln(K)] as high as 4.5 [Rehfeldt et al, 1992], which is much larger than previous natural gradient experiment sites, including the Borden site (0.29 [see MacKay et al, 1986]), the Cape Cod site (0.26 [see Garabedian, 1987;LeBlanc et al, 1991]), and the Twin Lake site (0.031 [see Killey and Moltyaner, 1988]). However, Fogg [2004] showed that a 4.5 variance of ln(K) is not uncommon, especially for large alluvial aquifer systems.…”

“…However, Fogg [2004] showed that a 4.5 variance of ln(K) is not uncommon, especially for large alluvial aquifer systems. The MADE site aquifer is dominated by unconsolidated sand and gravel, with less clay and silt deposits which might form the relatively immobile, irregular lenses and layers [Rehfeldt et al, 1992]. In typical alluvial depositional systems, the high-K paleochannel sands and gravels tend to be interconnected in space (as long as their volume fraction is sufficiently large) and thus provide multiscale preferential flow paths for water and solute [Fogg et al, 2000].…”

Toward efficiency in heterogeneous multispecies reactive transport modeling: A particle‐tracking solution for first‐order network reactions

“…Even though model predictions can be strongly affected by the spatial variability of both hydraulic and biochemical properties [Rehfeldt et al, 1992;Miralles-Wilhelm and Gelhar, 1996;Miralles-Wilhelm et al, 1997;Cunningham and Fadel, 2007;Maxwell and Kastenberg, 1999;Maxwell et al, 2007], reactive transport codes based on Eulerian methods such as finite-difference or finite elements [e.g., Saaltink et al, 2004;Clement, 1997] still undergo computational burden and numerical problems when modeling strong heterogeneities and complex biochemical systems at high resolution. In this context, Particle Tracking Methods (PTMs) offer a convenient numerical solution particularly efficient in dealing with heterogeneities [e.g., Wen and GomezHernandez, 1996;LaBolle et al, 1996;Salamon et al, 2007;Riva et al, 2008] and a large variety of complex transport processes such as non-Fickian transport [Delay and Bodin, 2001;Cvetkovic and Haggerty, 2002;Berkowitz et al, 2006;Zhang and Benson, 2008;Dentz and Castro, 2009] and multiple porosity systems [Salamon et al, 2006b;Benson and Meerschaert, 2009;Tsang and Tsang, 2001;Huang et al, 2003;Willmann et al, 2013].…”

“…The effect of these different types of heterogeneities should not be considered independently. The joint effect and correlation of the processes underlying these different sources of variability can be equally important to assess the fate and transport of contaminants [Rehfeldt et al, 1992;Cunningham and Fadel, 2007].…”