Exploiting electrical resistivity tomography for hydraulic tomography: Sandbox experiments

Abstract

Hydraulic tomography (HT) has been proven effective for characterizing aquifer hydraulic heterogeneity for decades. Many have also proposed using electrical resistivity tomography (ERT) to gain prior information about large-scale layer structures to improve the HT estimates, when the number of pumping tests and drawdown measurements is limited. This study investigates the merits of such proposals via numerical and physical experiments using an actual sandbox.

The numerical experiments show that ERT can detect the sandbox's layer structure under fully saturated conditions. Surprisingly, the physical sandbox experiments yielded different results: ERT could not detect the layer structures under saturated conditions. Nevertheless, the surveys in the physical experiments under drained conditions facilitated mapping structures, revealing that electrical conductivity show a stronger correlation with moisture content than porosity. We then used the detected layer structure under unsaturated conditions from the ERT without a definitive resistivity/hydraulic conductivity relationship as the HT prior information to improve HT's saturated hydraulic conductivity (K) estimates. The results of independent pumping and tracer tests in the numerical sandbox experiments demonstrated and validated improvements in K estimation. These findings are significant, questioning the need for accurate local-scale resistivity/hydraulic conductivity relationships. It is a new insight into hydrogeophysics.