Timothy D. Scheibe

Processes in microbial transport in the natural subsurface

This is a review of physical, chemical, and biological processes governing microbial transport in the saturated subsurface. We begin with the conceptual models of the biophase that underlie mathematical descriptions of these processes and the physical processes that provide the framework for recent focus on less understood processes. Novel conceptual models of the interactions between cell surface structures and other surfaces are introduced, that are more realistic than the oft-relied upon DLVO theory of colloid stability. Biological processes reviewed include active adhesion/detachment (cell partitioning between aqueous and solid phase initiated by cell metabolism) and chemotaxis (motility in response to chemical gradients). We also discuss mathematical issues involved in upscaling results from the cell scale to the Darcy and field scales. Finally, recent studies at the Oyster, Virginia field site are discussed in terms of relating laboratory results to field scale problems of bioremediation and pathogen transport in the natural subsurface.

Simulations of reactive transport and precipitation with smoothed particle hydrodynamics

A numerical model based on smoothed particle hydrodynamics (SPH) was developed for reactive transport and mineral precipitation in fractured and porous materials. Because of its Lagrangian particle nature, SPH has several advantages for modeling Navier-Stokes flow and reactive transport including: (1) in a Lagrangian framework there is no non-linear term in the momentum conservation equation, so that accurate solutions can be obtained for momentum dominated flows and; (2) complicated physical and chemical processes such as surface growth due to precipitation/dissolution and chemical reactions are easy to implement. In addition, SPH simulations explicitly conserve mass and linear momentum. The SPH solution of the diffusion equation with fixed and moving reactive solid-fluid boundaries was compared with analytical solutions, Lattice Boltzmann [Q. Kang, D. Zhang, P. Lichtner, I. Tsimpanogiannis, Lattice Boltzmann model for crystal growth from supersaturated solution, Geophysical Research Letters, 31 (2004) L21604] simulations and diffusion limited aggregation (DLA) [P. Meakin, Fractals, scaling and far from equilibrium. Cambridge University Press, Cambridge, UK, 1998] model simulations. To illustrate the capabilities of the model, coupled three-dimensional flow, reactive transport and precipitation in a fracture aperture with a complex geometry were simulated.

Multiphysics simulations: Challenges and opportunities

We consider multiphysics applications from algorithmic and architectural perspectives, where “algorithmic” includes both mathematical analysis and computational complexity, and “architectural” includes both software and hardware environments. Many diverse multiphysics applications can be reduced, en route to their computational simulation, to a common algebraic coupling paradigm. Mathematical analysis of multiphysics coupling in this form is not always practical for realistic applications, but model problems representative of applications discussed herein can provide insight. A variety of software frameworks for multiphysics applications have been constructed and refined within disciplinary communities and executed on leading-edge computer systems. We examine several of these, expose some commonalities among them, and attempt to extrapolate best practices to future systems. From our study, we summarize challenges and forecast opportunities.

Use of sedimentological information for geometric simulation of natural porous media structure

A geometric simulation method was used to develop a three-dimensional, highly detailed synthetic representation of point bar sediments in the Wabash River system. Geometric simulation methods, in comparison to well-known second-order stochastic methods, offer the advantage of being more closely related to depositional processes, which are often similarly conceptualized (i.e., described in terms of shapes of discrete bed forms, trends in grain size, and spatial relationships of defined geologic facies). Multiple scales of geometric variation were defined within a sedimentologically prescribed framework, and shapes of discrete geometric elements were established at each scale. The selected shapes were based on published field studies including sedimentological bed form studies and trench studies in active point bar sediments. The parameterization of the shapes allowed for random variability of the shape descriptors; discrete shapes were then generated and assimilated by computer. Hydraulic conductivity values were assigned to the discrete elements based on reports of observed variations in grain size and field measurements of hydraulic conductivity. The synthetic model, referred to as a numerical aquifer, is being used as the basis for extensive numerical experimentation to study the relationship between natural spatial structure and subsurface flow and transport.

Extended tailing of bacteria following breakthrough at the Narrow Channel Focus Area, Oyster, Virginia

Extended tailing of low bacterial concentrations following breakthrough at the Narrow Channel focus area was observed for 4 months. Bacterial attachment and detachment kinetics associated with breakthrough and extended tailing were determined by fitting a one-dimensional transport model to the field breakthrough-tailing data. Spatial variations in attachment rate coefficient (kf) were observed under forced gradient conditions (i.e., k f decreased as travel distance increased), possibly because of decreased bacterial adhesion with increased transport distance. When pore water velocity decreased by an order of magnitude at 9 days following injection, apparent bacterial attachment rate coefficients did not decrease with velocity as expected from filtration theory, but, instead, increased greatly for most of the wells. The coincidence of the increase in apparent attachment rate coefficient with the occurrence of protist blooms suggested that the loss of bacteria from the aqueous phase during the protist blooms was not governed by filtration but rather was governed by predation. Simulations were performed to examine the transport distances achieved with and without detachment, using attachment and detachment rate coefficients similar to those obtained in this field study. Simulations that included detachment showed that transport distances of bacteria may significantly increase because of detachment under the conditions examined.

Scaling of flow and transport behavior in heterogeneous groundwater systems

Three-dimensional numerical simulations using a detailed synthetic hydraulic conductivity field developed from geological considerations provide insight into the scaling of subsurface flow and transport processes. Flow and advective transport in the highly resolved heterogeneous field were modeled using massively parallel computers, providing a realistic baseline for evaluation of the impacts of parameter scaling. Upscaling of hydraulic conductivity was performed at a variety of scales using a flexible power law averaging technique. A series of tests were performed to determine the effects of varying the scaling exponent on a number of metrics of flow and transport behavior. Flow and transport simulation on high-performance computers and three-dimensional scientific visualization combine to form a powerful tool for gaining insight into the behavior of complex heterogeneous systems. Many quantitative groundwater models utilize upscaled hydraulic conductivity parameters, either implicitly or explicitly. These parameters are designed to reproduce the bulk flow characteristics at the grid or field scale while not requiring detailed quantification of local-scale conductivity variations. An example from applied groundwater modeling is the common practice of calibrating grid-scale model hydraulic conductivity or transmissivity parameters so as to approximate observed hydraulic head and boundary flux values. Such parameterizations, perhaps with a bulk dispersivity imposed, are then sometimes used to predict transport of reactive or non-reactive solutes. However, this work demonstrates that those parameters that lead to the best upscaling for hydraulic conductivity and head do not necessarily correspond to the best upscaling for prediction of a variety of transport behaviors. This result reflects the fact that transport is strongly impacted by the existence and connectedness of extreme-valued hydraulic conductivities, in contrast to bulk flow which depends more strongly on mean values. It provides motivation for continued research into upscaling methods for transport that directly address advection in heterogeneous porous media. An electronic version of this article is available online at the journals homepage at http://www.elsevier.nl/locate/advwatres or http://www.elsevier.com/locate/advwatres (see “Special section on vizualization”. The online version contains additional supporting information, graphics, and a 3D animation of simulated particle movement.©1998 Elsevier Science Limited. All rights reserved

Coupling a genome-scale metabolic model with a reactive transport model to describe in situ uranium bioremediation.

The increasing availability of the genome sequences of microorganisms involved in important bioremediation processes makes it feasible to consider developing genome‐scale models that can aid in predicting the likely outcome of potential subsurface bioremediation strategies. Previous studies of the in situ bioremediation of uranium‐contaminated groundwater have demonstrated that Geobacter species are often the dominant members of the groundwater community during active bioremediation and the primary organisms catalysing U(VI) reduction. Therefore, a genome‐scale, constraint‐based model of the metabolism of Geobacter sulfurreducens was coupled with the reactive transport model HYDROGEOCHEM in an attempt to model in situ uranium bioremediation. In order to simplify the modelling, the influence of only three growth factors was considered: acetate, the electron donor added to stimulate U(VI) reduction; Fe(III), the electron acceptor primarily supporting growth of Geobacter; and ammonium, a key nutrient. The constraint‐based model predicted that growth yields of Geobacter varied significantly based on the availability of these three growth factors and that there are minimum thresholds of acetate and Fe(III) below which growth and activity are not possible. This contrasts with typical, empirical microbial models that assume fixed growth yields and the possibility for complete metabolism of the substrates. The coupled genome‐scale and reactive transport model predicted acetate concentrations and U(VI) reduction rates in a field trial of in situ uranium bioremediation that were comparable to the predictions of a calibrated conventional model, but without the need for empirical calibration, other than specifying the initial biomass of Geobacter. These results suggest that coupling genome‐scale metabolic models with reactive transport models may be a good approach to developing models that can be truly predictive, without empirical calibration, for evaluating the probable response of subsurface microorganisms to possible bioremediation approaches prior to implementation.

Hybrid Simulations of Reaction-Diffusion Systems in Porous Media

Hybrid or multiphysics algorithms provide an efficient computational tool for combining micro- and macroscale descriptions of physical phenomena. Their use becomes imperative when microscale descriptions are too computationally expensive to be conducted in the whole domain, while macroscale descriptions fail in a small portion of the computation domain. We present a hybrid algorithm to model a general class of reaction-diffusion processes in granular porous media, which includes mixing-induced mineral precipitation on, or dissolution of, the porous matrix. These processes cannot be accurately described using continuum (Darcy-scale) models. The pore-scale/Darcy-scale hybrid is constructed by coupling solutions of the reaction-diffusion equations (RDE) at the pore scale with continuum Darcy-level solutions of the averaged RDEs. The resulting hybrid formulation is solved numerically by employing a multiresolution meshless discretization based on the smoothed particle hydrodynamics method. This ensures seamless noniterative coupling of the two components of the hybrid model. Computational examples illustrate the accuracy and efficiency of the hybrid algorithm.

Transport and biogeochemical reaction of metals in a physically and chemically heterogeneous aquifer

Biologically mediated reductive dissolution and precipitation of metals and radionuclides play key roles in their subsurface transport. Physical and chemical properties of natural aquifer systems, such as reactive iron-oxide surface area and hydraulic conductivity, are often highly heterogeneous in complex ways that can exert significant control on transport, natural attenuation, and active remediation processes. Typically, however, few data on the detailed distribution of these properties are available for incorporation into predictive models. In this study, we integrate field-scale geophysical, hydrologic, and geochemical data from a well-characterized site with the results of laboratory batch-reaction studies to formulate two-dimensional numerical models of reactive transport in a heterogeneous granular aquifer. The models incorporate several levels of coupling, including effects of ferrous iron sorption onto (and associated reduction of reactive surface area of) ferric iron surfaces, microbial growth and transport dynamics, and cross-correlation between hydraulic conductivity and initial ferric iron surface area. These models are then used to evaluate the impacts of physical and chemical heterogeneity on transport of trace levels of uranium under natural conditions, as well as the effectiveness of uranium reduction and immobilization upon introduction of a soluble electron donor (a potential biostimulation remedial strategy).

NON-GAUSSIAN PARTICLE TRACKING : APPLICATION TO SCALING OF TRANSPORT PROCESSES IN HETEROGENEOUS POROUS MEDIA

Observation of scale-dependent dispersion and non-Gaussian concentration distributions under field-scale transport in heterogeneous media motivates investigation of alternatives to the classical Fickian diffusion model. A numerical model of non-Gaussian transport, employing a particle-tracking approach, is examined here. Non-Gaussian behavior is represented through modeling of the correlation between components of the random dispersive vector applied at each time step in the random walk particle-tracking algorithm. This model is applied to a number of highly detailed, synthetic hydraulic conductivity fields. By simultaneously modeling particle movement at two different scales, the impact of the small-scale heterogeneity on the correlation structure of the dispersive vectors at the larger scale can be observed directly. It is shown that accounting for the correlation structure of the dispersive vectors greatly improves prediction of arrival distributions (breakthrough curves) over the standard Fickian model. This improvement is especially evident when the model scale is not much larger than the correlation length of hydraulic conductivity but persists at relatively large transport distances. In particular, the non-Gaussian model is better able to represent the late arrival tail, which has important implications for the design and implementation of aquifer remediation methods. It is also shown that the apparent scale dependence of field dispersivity results at least in part from neglecting the correlation structure of local velocity perturbations.