Geostatistical analysis of centimeter‐scale hydraulic conductivity variations at the MADE site

Abstract

[1] Spatial variations in hydraulic conductivity (K) provide critical controls on solute transport in the subsurface. Recently, new direct-push tools were developed for highresolution characterization of K variations in unconsolidated settings. These tools were applied to obtain 58 profiles (vertical resolution of 1.5 cm) from the heavily studied macrodispersion experiment (MADE) site. We compare the data from these 58 profiles with those from the 67 flowmeter profiles that have served as the primary basis for characterizing the heterogeneous aquifer at the site. Overall, the patterns of variation displayed by the two data sets are quite similar, in terms of both large-scale structure and autocorrelation characteristics. The direct-push K values are, on average, roughly a factor of 5 lower than the flowmeter values. This discrepancy appears to be attributable, at least in part, to opposite biases between the two methods, with the current versions of the direct-push tools underestimating K in the highly permeable upper portions of the aquifer and the flowmeter overestimating K in the less permeable lower portions. The vertically averaged K values from a series of direct-push profiles in the vicinity of two pumping tests at the site are consistent with the K estimates from those tests, providing evidence that the direct-push estimates are of a reasonable magnitude. The results of this field demonstration show that direct-push profiling has the potential to characterize highly heterogeneous aquifers with a speed and resolution that has not previously been possible.

Rapid field application of hydraulic tomography for resolving aquifer heterogeneity in unconsolidated sediments

“…The variant is called ''high-resolution K probe'' (HRK) and it facilitates sampling of a 10 m profile with a vertical resolution of 0.015 m in less than 30 min. Bohling et al [2012] applied these hydraulic DP tools to obtain several profiles from the heavily studied MAcro Dispersion Experiment (MADE) site to characterize detailed K-variations at the site. The data are compared with those from the flowmeter profiles that have served as the primary basis for characterizing the heterogeneous aquifer at the site [Rehfeldt et al, 1992].…”

Influence of conceptual model uncertainty on contaminant transport forecasting in braided river aquifers

“…Globally, considering the assumption of field information scarcity, the predicted plumes are within reasonable orders of magnitude in terms of concentration and travel time. In this specific case, though the conductivity mean l lnðKÞ ' À9:1 and variance r 2 lnðKÞ ' 3:1 values computed from analogue data (Jussel et al, 1994) are different from the conductivity mean l lnðKÞ ' À11:6 and variance r 2 lnðKÞ ' 6:6 measured on the MADE site, as reported by Bohling et al (2012), the K distribution with a smaller variance and higher conductivity mean is still overlapping with the DPIL measured K distribution. Thus combined with various different geological structure might allow reproducing comparable plume speed or dispersion.…”

“…The mean is porosity l n ¼ 0:20. These values are of course different from a mean lnðKÞ of À11.6 and variance of 6.6 obtained by direct-push injection logger measures (Bohling et al, 2012) and from a mean porosity of 0.31 as reported by Boggs and Adams (1992). These differences are the consequence of the data paucity assumption and they do not prevent pursuing the aims of the papers.…”

“…It has been followed by two tracer experiments under forced hydraulic gradient at smaller scales (MADE IV and V). More recently, geophysical campaigns including Ground Penetrating Radar (GPR), Direct Push (DP) and Direct Current (DC) resistivity measurements have been conducted to complete the characterization of the site (Bowling et al, 2005;Dogan et al, 2011;Bohling et al, 2012).…”

Proposta metodológica para projeto de redes hidrométricas: parte II - exclusão, rearranjo e inclusão de estações

“…A técnica de geoestatística vem sendo aplicada em várias áreas do conhecimento científico, podendo-se citar: geologia (Mouslopoulou & Hristopulos, 2011); propriedades físicas dos solos (Motomiya et al, 2011;Bohling et al, 2012;Santos et al, 2012); recursos minerais (Abichequer et al, 2012); climatologia (Fouquet et al, 2011;Ramos et al, 2011;Wanderley et al, 2012;) e hidrologia (Ávila et al, 2009;Castro et al, 2010). Nour et al (2006) utilizando a técnica geoestatística consideraram as implicações que o projeto de uma rede de monitoramento pluviométrico pode acarretar no mapeamento de precipitações e concluíram que, a partir da krigagem ordinária, a análise geoestatística forneceu bons resultados na identificação de locais para instalação de estações pluviométricas, possibilitando a redução dos erros de estimativa espaciais.…”