Geophysics provides a multidimensional suite of investigative methods that are transforming our ability to see into the very fabric of the subsurface environment, and monitor the dynamics of its fluids and the biogeochemical reactions that occur within it. Here we document how geophysical methods have emerged as valuable tools for investigating shallow subsurface processes over the past two decades and offer a vision for future developments relevant to hydrology and also ecosystem science. The field of “hydrogeophysics” arose in the late 1990s, prompted, in part, by the wealth of studies on stochastic subsurface hydrology that argued for better field‐based investigative techniques. These new hydrogeophysical approaches benefited from the emergence of practical and robust data inversion techniques, in many cases with a view to quantify shallow subsurface heterogeneity and the associated dynamics of subsurface fluids. Furthermore, the need for quantitative characterization stimulated a wealth of new investigations into petrophysical relationships that link hydrologically relevant properties to measurable geophysical parameters. Development of time‐lapse approaches provided a new suite of tools for hydrological investigation, enhanced further with the realization that some geophysical properties may be sensitive to biogeochemical transformations in the subsurface environment, thus opening up the new field of “biogeophysics.” Early hydrogeophysical studies often concentrated on relatively small “plot‐scale” experiments. More recently, however, the translation to larger‐scale characterization has been the focus of a number of studies. Geophysical technologies continue to develop, driven, in part, by the increasing need to understand and quantify key processes controlling sustainable water resources and ecosystem services.

[1] There is growing interest in the use of geophysical methods for hydrological model parameterization. Empirical induced polarization (IP)-hydraulic conductivity (K) relationships have been developed, but these are only applicable to sediments in which the IP response shows limited variation with electrical current frequency. Here we examine the spectral IP response of samples taken from a UK sandstone aquifer and compare measured parameters with physical and hydraulic properties. We demonstrate the limited value of existing IP-K models due to the inherent IP frequency dependence of these samples. Our results show how the mean relaxation time, t, is a more appropriate measure of IP response for these sediments. A significant inverse correlation between the surface area to pore volume ratio and t is observed, suggesting that t is a measure of a characteristic hydraulic length scale. This is supported by a measured strong positive correlation between log t and log K. Our measurements also reveal evidence of a relationship between t and a dominant pore throat size, which leads to postulations about the parallelism between the spectral IP behavior and unsaturated hydraulic characteristics. Additional experiments show how the relaxation time is affected by degree of fluid saturation, indicating that saturation levels must be accounted for if our empirical relationships are applied to vadose zone studies. Our results show clear evidence of the potential value of frequency-based IP measurements for parameterization of groundwater flow models.

[1] We use complex conductivity measurements to predict the hydraulic conductivity (K) of unconsolidated materials. The samples include natural sediments and artificial sand/clay mixtures. We apply the Börner et al. [1996] model, which is based on the Kozeny-Carman equation and incorporates electrical estimates of formation factor (F) and specific surface area per unit volume-to-porosity ratio (S por ), from the real (s 0 ) and imaginary (s 00 ) conductivity components respectively. We find that K correlates with s 00 but shows no correlation with F, which we attribute to the wide range in grain size for these materials. The Börner model appears primarily dependent on the K -s 00 relation. The relationship between s 00 and S por is nonlinear and appears to depend upon material type. Further examination shows that s 00 is well correlated with effective grain size (d 10 ) and is relatively independent of the material type. We propose a simple Hazen-type equation in which the effective grain size is estimated from s 00 . This simple model provides order of magnitude estimates of K for a range of unconsolidated sediments.

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