Modeling biofilm dynamics and hydraulic properties in variably saturated soils using a channel network model

Abstract

Biofilm effects on water flow in unsaturated environments have largely been ignored in the past. However, intensive engineered systems that involve elevated organic loads such as wastewater irrigation, effluent recharge, and bioremediation processes make understanding how biofilms affect flow highly important. In the current work, we present a channel-network model that incorporates water flow, substrate transport, and biofilm dynamics to simulate the alteration of soil hydraulic properties, namely water retention and conductivity. The change in hydraulic properties due to biofilm growth is not trivial and depends highly on the spatial distribution of the biofilm development. Our results indicate that the substrate mass transfer coefficient across the water-biofilm interface dominates the spatiotemporal distribution of biofilm. High mass transfer coefficients lead to uncontrolled biofilm growth close to the substrate source, resulting in preferential clogging of the soil. Low mass transfer coefficients, on the other hand, lead to a more uniform biofilm distribution. The first scenario leads to a dramatic reduction of the hydraulic conductivity with almost no change in water retention, whereas the second scenario has a smaller effect on conductivity but a larger influence on retention. The current modeling approach identifies key factors that still need to be studied and opens the way for simulation and optimization of processes involving significant biological activity in unsaturated soils.

Influence of Hydrological Perturbations and Riverbed Sediment Characteristics on Hyporheic Zone Respiration of CO2 and N2

“…Physical characteristics can vary dynamically with time as a function of microbial growth and infiltration within riverbed sediments representing an internal control on AR and DN (Newcomer et al, ). As microbial populations increase (Rosenzweig et al, ; Thullner, ; Yarwood et al, ), biofilms and cellular matter associated with their growth fill sediment pore spaces, reducing riverbed porosity (Φ) and riverbed hydraulic conductivity ( K c ) (Brovelli et al, ; Thullner, Mauclaire, et al, ; Thullner et al, ; Thullner, Zeyer, & Kinzelbach, ) and thereby also infiltration and the rate of substrate provision and associated residence time distributions (Aubeneau et al, ; Caruso et al, ). This dynamic dependence of porosity upon biomass and of biomass growth rates on porosity generates a complex, self‐limiting bottom‐up feedback effect whereby microbial biomass limits the flow that initially supported its growth.…”

Modeling Microbial Communities: A Call for Collaboration between Experimentalists and Theorists

“…Although growth remains the primary focus of many biofilm models, other factors such as quorum sensing [35,40] and biofilm mechanics [35,41] have also been represented. To elucidate the features of a microbial biofilm model, the 3D simulation of a biofilm on porous media [42][43][44] or in unsaturated soil [45] has been considered. In both cases, the focus is on the effect that biofilms have on the hydraulic properties of soil.…”

“…Graf von der Schulenburg et al [42] modeled the velocity, pressure, nutrient concentration, and biomass distribution of a biofilm using a biofilm IBM previously established for a 2D model [46], complemented by parameters for fluid velocity, pressure, and solute concentration. Complementary to this work, Rosenzweig et al [45] developed a channel-network model to describe the effect that biofilm spatial distribution has on soil hydraulic properties. Essential parameters that have been considered are time-dependent flow, substrate transport, and biofilm growth under various soil saturation conditions [45].…”

“…Complementary to this work, Rosenzweig et al [45] developed a channel-network model to describe the effect that biofilm spatial distribution has on soil hydraulic properties. Essential parameters that have been considered are time-dependent flow, substrate transport, and biofilm growth under various soil saturation conditions [45]. Simpler models of spatial structure have also been used to capture how the organization of cells influences range expansion [47,48], intercellular interactions [49,50], or access to environmental resources [51,52].…”

Modeling microbial growth and dynamics

“…Similarly, but in a very different context, Cogan et al (2013) utilized spatial constraints in a multiphase xylem model to limit the growth in different fluid phases (free bacteria, bacteria in biofilm, extracellular polymeric substances (EPS), and sap) in a system where bacterial EPS production disrupts water transport from the plant root and causes symptoms of leaf wilting. This system again shares conceptual similarities with bioclogging, a process of enhancing growth of EPS-producing bacteria in soil targeted at reducing soil permeability in order to redirect water flow around contaminated sites or for enhanced oil recovery (Bozorg et al 2011;Surasani et al 2013;Rosenzweig et al 2014). Bacteria are also used to enhance recovery of other natural resources such as in copper bioleaching, where specialized copper-oxidizing species such as Acidithiobacillus ferrooxidans mobilize copper ions into a recoverable solute.…”