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Abstract Within Earth's critical zone, weathering processes influence landscape evolution and hillslope hydrology by creating porosity in bedrock, transforming it into saprolite and eventually soil. In situ weathering processes drive much of this transformation while preserving the rock fabric of the parent material. Inherited rock fabric in regolith makes the critical zone anisotropic, affecting its mechanical and hydrological properties. Therefore, quantifying and studying anisotropy is an important part of characterising the critical zone, yet doing so remains challenging. Seismic methods can be used to detect rock fabric and infer mechanical and hydrologic conductivity anisotropy across landscapes. We present a novel way of measuring seismic anisotropy in the critical zone using Rayleigh and Love surface waves. This method leverages multi‐component surface seismic data to create a high‐resolution model of seismic anisotropy, which we compare with a nuclear magnetic resonance log measured in a nearby borehole. The two geophysical data sets show that seismic anisotropy and porosity develop at similar depths in weathered bedrock and both reach their maximum values in saprolite, implying that in situ weathering enhances anisotropy while concurrently generating porosity in the critical zone. We bolster our findings with in situ measurements of seismic and hydrologic conductivity anisotropy made in a 3 m deep soil excavation. Our study offers a fresh perspective on the importance of rock fabric in the development and function of the critical zone and sheds new insights into how weathering processes operate. 

The belowground architecture of the critical zone (CZ) consists of soil and rock in various stages of weathering and wetness that acts as a medium for biological growth, mediates chemical reactions, and controls partitioning of hydrologic fluxes. Hydrogeophysical imaging provides unique insights into the geometries and properties of earth materials that are present in the CZ and beyond the reach of direct observation beside sparse wellbores. An improved understanding of CZ architecture can be achieved by leveraging the geophysical measurements of the subsurface. Creating categorical models of the CZ is valuable for driving hydrologic models and comparing belowground architectures between different sites to interpret weathering processes. The CZ architecture is revealed through a novel comparison of hillslopes by applying facies classification in the elastic-electric domain driven by surface-based hydrogeophysical measurements. Three pairs of hillslopes grouped according to common geologic substrates — granite, volcanic extrusive, and glacially altered — are classified by five different hydrofacies classes to reveal the relative wetness and weathering states. The hydrofacies classifications are robust to the choice of initial mean values used in the classification and noncontemporaneous timing of geophysical data acquisition. These results will lead to improved interdisciplinary models of CZ processes at various scales and to an increased ability to predict the hydrologic timing and partitioning. Beyond the hillslope scale, this enhanced capability to compare CZ architecture can also be exploited at the catchment scale with implications for improved understanding of the link between rock weathering, hydrochemical fluxes, and landscape morphology.