Reactive chemical transport plays a key role in geological media across scales, from pore scale to aquifer scale. Systems can be altered by changes in solution chemistry and a wide variety of chemical transformations, including precipitation/dissolution reactions that cause feedbacks that directly affect the flow and transport regime. The combination of these processes with advective‐dispersive‐diffusive transport in heterogeneous media leads to a rich spectrum of complex dynamics. The principal challenge in modeling reactive transport is to account for the subtle effects of fluctuations in the flow field and species concentrations; spatial or temporal averaging generally suppresses these effects. Moreover, it is critical to ground model conceptualizations and test model outputs against laboratory experiments and field measurements. This review emphasizes the integration of these aspects, considering carefully designed and controlled experiments at both laboratory and field scales, in the context of development and solution of reactive transport models based on continuum‐scale and particle tracking approaches. We first discuss laboratory experiments and field measurements that define the scope of the phenomena and provide data for model comparison. We continue by surveying models involving advection‐dispersion‐reaction equation and continuous time random walk formulations. The integration of measurements and models is then examined, considering a series of case studies in different frameworks. We delineate the underlying assumptions, and strengths and weaknesses, of these analyses, and the role of probabilistic effects. We also show the key importance of quantifying the spreading and mixing of reactive species, recognizing the role of small‐scale physical and chemical fluctuations that control the initiation of reactions.

Rivers are a vital part of global ecosystems due to their major role in sediment distribution and cycling of nutrients and carbon (Cole et al., 2007;Tiegs et al., 2019). This is accomplished largely through the interactions between the flow in the stream and the underlying sediment bed. Interactions such as bed motion and water exchange between the stream and the subsurface are influenced by numerous physical properties including stream flow, streambed slope, particle size distribution of the bed, and so on. Biogeochemical processes in streams particularly depend on delivery of nutrients and substrates to microbes that are mostly found in the streambed (

No abstract

Path reversibility and radial symmetry are often assumed in push‐pull tracer test analysis. In reality, heterogeneous flow fields mean that both assumptions are idealizations. To understand their impact, we perform a parametric study which quantifies the scattering effects of ambient flow, local‐scale dispersion, and velocity field heterogeneity on push‐pull breakthrough curves and compares them to the effects of mobile‐immobile mass transfer (MIMT) processes including sorption and diffusion into secondary porosity. We identify specific circumstances in which MIMT overwhelmingly determines the breakthrough curve, which may then be considered uninformative about drift and local‐scale dispersion. Assuming path reversibility, we develop a continuous‐time‐random‐walk‐based interpretation framework which is flow‐field‐agnostic and well suited to quantifying MIMT. Adopting this perspective, we show that the radial flow assumption is often harmless: to the extent that solute paths are reversible, the breakthrough curve is uninformative about velocity field heterogeneity. Our interpretation method determines a mapping function (i.e., subordinator) from travel time in the absence of MIMT to travel time in its presence. A mathematical theory allowing this function to be directly “plugged into” an existing Laplace‐domain transport model to incorporate MIMT is presented and demonstrated. Algorithms implementing the calibration are presented and applied to interpretation of data from a push‐pull test performed in a heterogeneous environment. A successful four‐parameter fit is obtained, of comparable fidelity to one obtained using a million‐node 3‐D numerical model. Finally, we demonstrate analytically and numerically how push‐pull tests quantifying MIMT are sensitive to remobilization, but not immobilization, kinetics.