Capturing aquifer heterogeneity: Comparison of approaches through controlled sandbox experiments

Abstract

[1] Groundwater modeling has become a vital component to water supply and contaminant transport investigations. These models require representative hydraulic conductivity (K) and specific storage (S s ) estimates, or a set of estimates representing subsurface heterogeneity. Currently, there are a number of approaches for characterizing and modeling K and S s heterogeneity in varying degrees of detail, but there is a lack of consensus for an approach that results in the most robust groundwater models with the best predictive ability. The main goal of this study is to compare different heterogeneity modeling approaches (e.g., effective parameters, geostatistics, geological models, and hydraulic tomography) when input into a forward groundwater model and used to predict 16 independent cross-hole pumping tests. We first characterize a sandbox aquifer through single-and cross-hole pumping tests, and then use these data to construct forward groundwater models of various complexities (both homogeneous and heterogeneous distributions). Two effective parameter models are constructed: (1) by taking the geometric mean of single-hole test K and S s estimates and (2) calibrating effective K and S s estimates by simultaneously matching the response at all ports during a cross-hole test. Heterogeneous models consist of spatially variable K and S s fields obtained via (1) kriging single-hole data; (2) calibrating a geological model; and (3) conducting transient hydraulic tomography . The performance of these parameter fields are then tested through the simulation of 16 independent cross-hole pumping tests. Our results convincingly show that transient hydraulic tomography produces the smallest discrepancy between observed and simulated drawdowns.

Improved predictions of saturated and unsaturated zone drawdowns in a heterogeneous unconfined aquifer via transient hydraulic tomography: Laboratory sandbox experiments

“…This material was packed to match a heterogeneity pattern drawn on the glass side of the sandbox. The sand was slowly added to the sandbox through a tube to create thin layers (approximately 0.5-1 cm thick) and packed between each addition to achieve uniform compaction (e.g., Illman et al, 2007Illman et al, , 2010Berg and Illman, 2011).…”

Joint interpretation of sequential pumping tests in unconfined aquifers

“…They include numerical studies [e.g., Gottlieb and Dietrich, 1995;Yeh and Liu, 2000;Bohling et al, 2002;Yeh, 2005, 2006;Fienen et al, 2008;Ni and Yeh, 2008;Castagna and Bellin, 2009;Xiang et al, 2009;Liu and Kitanidis, 2011], followed by laboratory sandbox studies [e.g., Liu et al, 2002;Brauchler et al, 2003;Illman et al, 2007;Liu et al, 2007;Illman et al, 2008;Yin and Illman, 2009;Illman et al, 2010;Berg and Illman, 2011a;Illman et al, 2012] and then experimental field studies [e.g. Bohling et al, 2007;Li et al, 2007;Straface et al, 2007;Cardiff et al, 2009;Illman et al, 2009;Berg and Illman, 2011b;Brauchler et al, 2011;Huang et al, 2011].…”

Image-guided inversion in steady-state hydraulic tomography

“…Over the past two decades, several numerical and field studies have demonstrated how steadystate hydraulic tests can be used to image hydraulic conductivity or transmissivity (e.g., [12,21,40,59]). Transient pumping tests can also be used to estimate both of the specific storage and hydraulic conductivity fields (e.g., [3,27,64]). Hydraulic conductivity tomography can also be combined with the temporal moments method to reconstruct the hydraulic parameters heterogeneities (e.g.…”

“…The SLE approach has proven to be an efficient tool in hydraulic tomography. Its success has been demonstrated in saturated flow synthetic tests [59,64]; [60,58]; [51], in variably-saturated flow synthetic tests [42], in pneumatic tomography [44], in sandbox experiments [3,32,40,41], and in field experiments [4,6,30,31,49].…”