Successful prediction of subsurface contaminant plume evolution and assessment of natural attenuation capacity requires the ability to correctly identify controlling reaction and transport properties and to accurately distribute those properties over relevant scales. Properties controlling reactive transport of a contaminant plume include both hydraulic characteristics (such as permeability) and reactive characteristics (such as mineral surface properties, organic matter content, microbial ecology, and dissolved phases). Spatial heterogeneity of these characteristics strongly influences the evolution of a contaminant plume. However, parameterization of this heterogeneity is severely limited by the sparse nature of subsurface sampling using borehole approaches. For example, established hydrological characterization methods (such as pumping, slug and flowmeter tests) are commonly used to measure hydraulic conductivity in the vicinity of the wellbore [e.g., Freeze and Cherry, 1979; Butler, 2005; Molz et al., 1994]; wellbore fluid samples are often used for water quality assessment [e.g., Chapelle, 2001]; and laboratory analysis of retrieved core samples is often used to characterize reactive mineralogy. Unfortunately, data obtained from borehole methods is typically sparse relative to the simulation volume and thus may not capture sufficient information away from the wellbore to describe the key controls on subsurface flow or reactions. The inability to characterize controlling properties at a high enough spatial resolution and over a large enough volume often hinders our ability to accurately simulate subsurface flow and transport processes. To circumvent this common obstacle, we explore if properties that control reactive transport can be associated with a subsurface unit that is discernible with geophysical methods in order to both simplify the task of characterizing heterogeneous systems and to ameliorate the problem of inadequate sampling. Moreover, we explore the potential of geophysical methods for identifying and spatially distributing these reactive facies over field scales, as is needed to improve predictions of subsurface contaminant transport.
 The reactive facies concept is based on the hypotheses that subsurface units can be identified, which have shared properties that influence flow and reactive transport that are distinct from surrounding units. A facies is an assemblage of like characteristics, usually reflecting the origin of a rock unit that serves to differentiate the unit from neighboring or related rock units [Koltermann and Gorelick, 1996]. Some common facies types include lithofacies (defined on the basis of petrographic properties); sedimentary/depositional facies (defined by geologic origins [Reading and Lovell, 1996; Anderton, 1985]), and hydrofacies (sediment units that share distinctive hydraulic properties used for parameterizing hydrology models); [Poeter and Gaylord, 1990; Klingbeil et al., 1999, Heinz et al., 2003; Zappa et al., 2006]. One of the main advantages of facies-based approaches is that they can significantly simplify the task of characterizing complex heterogeneous systems by subdividing the subsurface into a finite number of relatively homogeneous units that can be more easily described and characterized.
 Evidence suggests that facies-based approaches often better represent subsurface property distributions compared to distributions obtained from interpolation of point measurements [Fogg et al., 1998; Falivene et al., 2006; Michael et al., 2010; Zappa et al., 2006]. Hydrofacies-based approaches for characterizing hydrologic properties can often better represent sharp contrasts observed between different deposits and better represent the interconnectivity of conductive bodies relative to traditional interpolation techniques that spatially smooth heterogeneities [e.g.,de Marsily et al., 2005]. Eggleston and Rojstaczar  showed that hydrofacies, identified through wellbore sampling and used as input to flow and transport models, improved the estimated distribution of a contaminant plume compared to other methods used to develop the model domain parameters (such as kriging and polynomial regression).
 The use of facies to characterize contaminant reactivity in highly heterogeneous environments has also shown significant promise. Kleineidam et al. showed that the sorption of hydrophobic organic contaminants in a fluvial aquifer depends on the source, petrographic composition, and depositional processes of the sediment. They observed increased rates of sorption and higher proportions of organic sediment grains in gravel-dominated facies when compared to sand-dominated facies. These variations were traced to differences in source rock (organic rich sedimentary rocks versus silicate dominated igneous and metamorphic rocks) and to differences in sediment maturity (highly transported and weathered sands compared to gravels). The study ofKleineidam et al.  emphasized the importance of not only differences in lithofacies, but also the history and source of the sediments that constitute a facies. van Helvoort et al. studied the reactive potential of different sediments within an unconfined fluvial aquifer and found improved predictive ability when sediment samples were subdivided into sedimentary facies. They showed that accounting for postdepositional facies-based processes (such as facies-selective oxidation or reduction of mineral and organic components) led to improved prediction of groundwater reactivity over models that disregarded postdepositional alterations. These studies suggest that by using a facies based approach along with careful laboratory analysis, reactive behavior can be better characterized.
 Although attempts have been made to link subsurface units with hydrogeological or reactive properties, only a few studies have explored the link of facies with both of these properties together. Scheibe et al.  conducted numerical studies to explore the impact of coupled physiochemical properties (including clay content, hydraulic conductivity, and iron sediment geochemistry) on the efficacy of uranium bioremediation. In their synthetic study, they used subsurface hydraulic conductivity and geophysically obtained Fe(III) estimates from the U.S. Department of Energy (DOE) South Oyster Bacterial Transport Site [Hubbard et al., 2001; Chen et al., 2004] and assumed a negative correlation between the hydrological and sediment geochemical properties. Li et al. also performed numerical studies to explore the impact of coupled physiochemical properties on uranium transport associated with the DOE Integrated Field Research Center in Rifle, CO. They found that linked hydraulic conductivity and Fe(III) distributions resulted in localized larger accumulation of remediation-induced biomass and precipitates relative to homogeneous or independent heterogeneities, which led to a greater possibility of pore clogging.Allen-King et al.  categorized relatively homogeneous core samples on the basis of sediment facies in the Borden Aquifer and found good correlations between hydraulic conductivity (K) and adsorption coefficient (Kd) when the data were subdivided by facies [Allen-King et al., 1998]. Together, these studies suggest that a reactive facies based approach may provide a simple, yet effective, framework for describing coupled physiochemical properties that govern subsurface flow and transport.
 Herein, we explore if reactive facies can be identified, distributed over field scales using geophysical data, and used to parameterize reactive transport models. In the last decade, geophysical methods have been used extensively for shallow subsurface mapping, parameter estimation, and process monitoring [e.g., Rubin and Hubbard, 2005; Vereecken et al., 2006]. The main advantage of using geophysical data to complement conventional measurements is that geophysical methods can provide spatially extensive information about the subsurface in a minimally invasive manner at a comparatively high resolution. The greatest disadvantage is that the geophysical methods only provide indirect proxy information about subsurface properties or processes: petrophysical models and integration methods are commonly used to extract quantitative estimates of subsurface flow and transport properties from the geophysical data [e.g., Hubbard and Linde, 2010; Slater, 2007].
 Petrophysical relationships are often developed through comparison of geophysical attributes at wellbore locations with measurements made in the wellbore or using wellbore-derived core. The comparison of geophysical and single “point” measurements suffers from two main drawbacks. The first complication stems from the differences in measurement support volume of geophysical measurements and the direct measurements [e.g.,Ferré et al., 2005; Moysey et al., 2005; Day-Lewis et al., 2005]. The support scale of geophysical measurements is related to the resolution of the method (which in turn is governed by factors such as acquisition method, geometry, and material properties); it is generally much larger than the support scale of direct measurements. In addition to scale-matching problems, wellbore drilling and laboratory analysis of individual core samples (which are used to assess permeability, porosity, sorting, and mineralogy) often disturb the material, rendering the measurements less representative of the in situ conditions that are sampled by the geophysical signals. Statistical development of petrophysical relationships between physiochemical properties and geophysical attributes requires a large number of analyzed samples. Because reactive facies are likely to be larger than the geophysical measurement support scale, a reactive facies based characterization approach has the potential to minimize the scale-matching problem and increase the statistical significance of the petrophysical relationship.
 Many geophysical attributes have the potential to be sensitive to facies-based architecture and associated parameter suites. Indeed, the juxtaposition of different facies and the resulting seismic signature of the interface led to the development of a concept called seismic facies [Sangree and Widmier, 1979], which has been widely used to delineate stratigraphic architecture for the exploration of hydrocarbons. The concept of using geophysical methods to delineate the architecture of sedimentary units has been adopted for the shallower subsurface using many different geophysical methods, including seismic, electrical [Gerilynn et al., 1995], and ground-penetrating radar (GPR) [Neal, 2004; van Overmeeren, 1998].
 Related to the facies concept, many studies have illustrated the value of geophysical methods for characterizing aquifer zonation, and in turn, for improving the understanding of subsurface flow and transport. Hyndman and Gorelick  used seismic tomographic travel time data in conjunction with slug and tracer data to identify zones within an aquifer that had similar hydraulic properties. Tronicke et al.  utilized both GPR travel time and attenuation tomography to delineate aquifer zones using multivariate statistics. Paasche et al.  utilized a clustering technique to define aquifer zones based on the response of multiple geophysical techniques and hydrological measurements. Linde et al. developed a methodology for inverting tracer test data using zonation information obtained from two-dimensional radar tomograms to improve the (typically overly smooth) hydraulic conductivity fields obtained from conventional inversion of tracer test data. The method simultaneously yielded two-dimensional estimates of hydraulic conductivity as well as petrophysical relationships that relate hydraulic conductivity to radar velocity for each key zone.Chen et al.  utilized a Bayesian methodology and observed correlations between mud content and GPR attenuation to quantify the distribution of lithofacies in a shallow, unconfined aquifer. Hubbard et al. used cross-hole radar and seismic measurements with wellbore flowmeter data and a statistical approach to identify hydraulic zonation within a Cr(VI) contaminated aquifer at the DOE Hanford Site in Washington. They found that the hydrological zonation greatly controlled the distribution of amendments that were injected into the subsurface to stimulate bioremediation as well as the location of the induced biogeochemical transformations.Chen et al. jointly inverted surface seismic refraction travel time and wellbore-based lithological information to delineate subsurface zonation at the contaminated Oak Ridge National Laboratory. They used the results to identify the presence of a narrow and laterally extensive subsurface feature that was interpreted to control plume transport.
 A common hypothesis for many of these studies is that the geophysical attribute (such as electrical conductivity, GPR attenuation, or seismic velocity) is sensitive to the bulk or effective soil properties (such as composition, texture, grain size, or sorting) associated with facies. A secondary hypothesis, explored by Chen et al. , is that the sensitivity of geophysical attributes to lithofacies could also be used to quantify sediment geochemistry through exploiting the mutual dependence of geophysical attributes and sediment geochemistry on lithology. Using cross-hole tomographic GPR data collected in conjunction with wellbore core sediment extract data,Chen et al.  developed and exploited a petrophysical relationship between mud content, iron mineralogy, and GPR attenuation to estimate the spatial distribution of Fe(II) and Fe(III) within a shallow aquifer. Together, these studies suggest that geophysical methods hold significant potential for identifying subsurface units that have distinct distributions of hydrological and geochemical properties.
1.2. Reactive Facies Approach
 Previous studies have suggested the value of a facies concept and the potential of geophysical methods to identify facies. Our approach builds on these previous studies to first define the key controls over reactive transport at a particular site, determine if reactive facies exists, and then to determine if geophysical methods can be used to identify and spatially distribute reactive facies and associated properties over field scales as is needed to parameterize reactive transport models. Our approach is schematically indicated in Figure 1. Laboratory-scale analysis is performed to identify the key controls on contaminant reactivity (such as sorption, ion exchange and oxidation) and to determine if these controls are dependent on properties such as mineralogy and texture that may define a reactive facies. In parallel, geophysical analysis and data mining are performed to determine if sediment packages have unique and linked distributions of reactive transport properties, and whether geophysical attributes are able to distinguish the identified reactive facies. If both lines of investigations are successful, then estimation approaches can be used with geophysical data sets to spatially distribute the reactive facies at the field scale.
 We develop and test the concept at an acidic, radionuclide-contaminated aquifer located under seepage basins at the F-Area of the U.S. Department of Energy Savannah River Site (SRS), South Carolina. Developing a predictive understanding of long-term plume mobility in the presence of significant pH gradients is important for ascertaining the long-term natural attenuation capacity at this site [Denham and Vangelas, 2009; Dong et al., 2012; Spycher et al., 2011]. Advanced laboratory exploration of facies-based surface complexation models, as well as reactive transport model sensitivity analysis studies, associated with this site are ongoing.
 Our study is organized as follows. Section 2 provides a description of the study site and the geochemical, geophysical, geological, and hydrological data sets collected at the site. The methodology used to integrate these various data in the identification and estimation of reactive facies is described in section 3. Results and conclusions are provided in section 4.