Analysis of hydraulic tomography using temporal moments of drawdown recovery data

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Two‐dimensional characterization of hydraulic heterogeneity by multiple pumping tests (2007, background): “Numerical investigations [Bohling, 1993; Gottlieb and Dietrich, 1995; Vesselinov et al., 2001a, 2001b; Zhu and Yeh, 2006] and sandbox experiments [Yeh and Liu, 2000] have demonstrated that hydraulic tomography may produce a significantly improved description of spatially variable hydraulic…”
Solute transport in low‐heterogeneity sandboxes: The role of correlation length and permeability variance (2014, background): “Characteristics of solute transport in porous media can be represented by key parameters such as first and second temporal moments [Dagan, 1990; Zhu and Yeh, 2006; Zhu et al., 2009].”
Hydraulic tomography using temporal moments of drawdown recovery data: A laboratory sandbox study (2007, methodology): “To ease the computational burden, a HT which utilizes zeroth and first temporal moments of transient drawdown recovery data (HT-m) has been developed by Zhu and Yeh (2006).”
A Bayesian approach for inverse modeling, data assimilation, and conditional simulation of spatial random fields (2010, methodology): “The temporal moments can be related to the hydraulic conductivity using a series of steady state equations forM, and this is much easier to process compared to the time series that would require a transient flow equation for M [Zhu and Yeh, 2006].”