Biofilm growth and the related changes in the physical properties of a porous medium: 3. Dispersivity and model verification

Stewart W. Taylor, Peter R. Jaffe

Research output: Contribution to journalArticlepeer-review

103 Scopus citations

Abstract

In the first part of this paper the change in dispersivity resulting from the growth of a biofilm in a porous medium is derived from an existing model of dispersivity and a cut‐and‐random‐rejoin‐type model of the pore geometry. The change in dispersivity due to a biofilm is also estimated from experimental data. Tracer experiments were conducted in biofilm column reactors and dispersion coefficients estimated by solving the inverse solute transport problem by nonlinear, least squares regression. Due to the presence of the biofilm in the porous media, solute flux into the biofilm is an important transport process and is given special attention. Both the dispersivity model and experimentally estimated dispersivities show order of magnitude increases in dispersivity as a result of significant biofilm growth. In the second part of the paper the models for the biofilm‐affected permeability, porosity, and specific surface derived in a companion paper (Taylor et al., this issue) are verified using data from biofilm column reactors. These models are used to parameterize an equation describing the transport of substrate in the experimental columns. Numerical simulations were performed and compared to observed substrate data. Results show that the models for permeability and porosity can be used to make estimates of these parameters, while the model for specific surface appears to be inadequate.

Original languageEnglish (US)
Pages (from-to)2171-2180
Number of pages10
JournalWater Resources Research
Volume26
Issue number9
DOIs
StatePublished - Sep 1990

All Science Journal Classification (ASJC) codes

  • Water Science and Technology

Fingerprint

Dive into the research topics of 'Biofilm growth and the related changes in the physical properties of a porous medium: 3. Dispersivity and model verification'. Together they form a unique fingerprint.

Cite this