Pore‐Scale Hydrodynamics in a Progressively Bioclogged Three‐Dimensional Porous Medium: 3‐D Particle Tracking Experiments and Stochastic Transport Modeling

Abstract

Biofilms are ubiquitous bacterial communities that grow in various porous media including soils, trickling, and sand filters. In these environments, they play a central role in services ranging from degradation of pollutants to water purification. Biofilms dynamically change the pore structure of the medium through selective clogging of pores, a process known as bioclogging. This affects how solutes are transported and spread through the porous matrix, but the temporal changes to transport behavior during bioclogging are not well understood. To address this uncertainty, we experimentally study the hydrodynamic changes of a transparent 3‐D porous medium as it experiences progressive bioclogging. Statistical analyses of the system's hydrodynamics at four time points of bioclogging (0, 24, 36, and 48 h in the exponential growth phase) reveal exponential increases in both average and variance of the flow velocity, as well as its correlation length. Measurements for spreading, as mean‐squared displacements, are found to be non‐Fickian and more intensely superdiffusive with progressive bioclogging, indicating the formation of preferential flow pathways and stagnation zones. A gamma distribution describes well the Lagrangian velocity distributions and provides parameters that quantify changes to the flow, which evolves from a parallel pore arrangement under unclogged conditions, toward a more serial arrangement with increasing clogging. Exponentially evolving hydrodynamic metrics agree with an exponential bacterial growth phase and are used to parameterize a correlated continuous time random walk model with a stochastic velocity relaxation. The model accurately reproduces transport observations and can be used to resolve transport behavior at intermediate time points within the exponential growth phase considered.

Formation Criteria for Hyporheic Anoxic Microzones: Assessing Interactions of Hydraulics, Nutrients, and Biofilms

“…These findings are in opposition to our original hypothesis that bioclogging would enhance microzone formation. It is also different from recent porous media studies (Carrel, Morales, Beltran, et al, 2018;Carrel, Morales, Dentz, et al, 2018) that indicate that progressive bioclogging may enhance non-Fickian and intensify superdiffusive flow, which should mean that bioclogging creates preferential flow pathways and stagnation zones where microzones could develop. However, the addition of nutrient resource constraints on biofilm dynamics, including different biomass growth and decay rates in our model, resulted in these preferential flow paths and stagnation zones becoming ephemeral features of the model domain as discussed in detail below (section 3.1.2).…”

“…The microbial metabolic activity that likely plays a key role in the development of these microzones and biogeochemical transformations of the hyporheic zone can also lead to the expansion of microbial biomass in the sediment matrix over time (e.g., Molz et al, 1986;Widdowson et al, 1988). This gradual accumulation of biomass primarily appears as the formation of biofilms attached to sediment particles and may alter the hydraulic flux through the sediment (e.g., Carrel, Morales, Beltran, et al, 2018;Carrel, Morales, Dentz, et al, 2018). This biomass accumulation can lead to a phenomenon known as bioclogging, which causes a reduction in overall hydraulic conductivity and pore connectivity (e.g., Thullner, 2010;Thullner et al, 2002Thullner et al, , 2004.…”

Stochastic Dynamics of Lagrangian Pore‐Scale Velocities in Three‐Dimensional Porous Media

“…The models proposed by these authors are similar to time‐domain and continuous time random walk approaches (Delay et al, ; Berkowitz et al, ; Noetinger et al, ; Painter & Cvetkovic, ) in that they consider particle motion through transitions over the characteristic pore lengths characterized by random time increments that depend on the distribution of pore‐scale velocities. Recent experimental and numerical studies have shown that the occurrence of non‐Fickian particle dispersion due to long advective residence times is directly linked to intermittency in the Lagrangian velocity time series (Carrel et al, ; De Anna et al, ; Holzner et al, ; Kang et al, ; Morales et al, ). Thus, the understanding of these phenomena requires a sound characterization and understanding of the dynamics of Lagrangian and Eulerian pore‐scale velocities, which have been the subject of a series of recent studies (De Anna et al, ; Gjetvaj et al, ; Holzner et al, ; Jin et al, ; Meyer & Bijeljic, ; Morales et al, ; Matyka et al, ; Siena et al, ).…”

Identification of Channeling in Pore‐Scale Flows

“…Channeling may occur under diverse conditions and on a wide range of spatial scales and is always characterized by two major features: (i) high velocity values persisting over long distances and (ii) flow focused within a few regions (principal paths) of the pore space (Hyman et al, 2012;Le Goc et al, 2010). Time evolution of the statistics of experimental observations of Lagrangian velocities in three-dimensional porous samples is analyzed in Carrel et al (2018) to evaluate the effect of progressive biofilm growth on flow channeling. While some indication about the level of channeling at the Darcy scale can be gained by the correlation length of permeabilities, this is not the case at the pore scale.…”

“…Characterization of channeling for two-dimensional geometries is presented in Alim et al (2017) relying on the pore network method and in Nissan and Berkowitz (2018) solving Navier-Stokes equations for given pore geometries. Time evolution of the statistics of experimental observations of Lagrangian velocities in three-dimensional porous samples is analyzed in Carrel et al (2018) to evaluate the effect of progressive biofilm growth on flow channeling.…”