Developing a predictive understanding of subsurface contaminant plume evolution and natural attenuation capacity is hindered by the inability to tractably characterize controlling reactive transport properties over field-relevant scales. Here we explore a concept of reactive facies, which is based on the hypothesis that subsurface units exist that have unique distributions of properties that influence reactive transport. We further hypothesize that geophysical methods can be used to identify and spatially distribute reactive facies and their associated parameters. We test the reactive facies concept at a U.S. Department of Energy uranium-contaminated groundwater site, where we have analyzed the relationships between laboratory and field (including radar and seismic tomographic) data sets. Our analysis suggests that there are two reactive facies that have unique distributions of mineralogy, texture, hydraulic conductivity, and geophysical attributes. We use these correlations within a Bayesian framework to integrate the dense geophysical data sets with the sparse core-based measurements. This yields high-resolution (0.25 m × 0.25 m) estimates of reactive facies and their associated properties and uncertainties along the 2-D tomographic transects. Comparison with colocated samples shows that the estimated properties fall within 95% uncertainty bounds. To illustrate the value of reactive facies characterization approach, we used the geophysically estimated properties to parameterize reactive transport models, which were then used to simulate migration of an acidic-U plume through the domain. Modeling results suggest that each identified reactive facies exerts a unique control on plume evolution, highlighting the usefulness of the reactive facies concept for spatially distributing properties that control reactive transport over field-relevant scales.