HR: 0800h
AN: H11A-0289 INVITED     [Abstracts]
TI: Modeling of Bioclogging in Porous Media - Approaches and Uncertainties
AU: * Thullner, M
EM: m.thullner@geo.uu.nl
AF: Department of Earth Sciences - Geochemistry, Utrecht University, P.O. Box 80021, Utrecht, 3508 TA Netherlands
AB: The ability of microorganisms to reduce the hydraulic conductivity of porous media is known as biological clogging or bioclogging. Bioclogging has been observed in many environmental and engineered systems and has been the subject of numerous laboratory experiments. Results of these experiments show that the buildup of biomass due to microbial growth within the pores can reduce the hydraulic conductivity of a porous medium by several orders of magnitude. Thus, models simulating the movement of water and chemical species in a medium affected by bioclogging have to address this issue appropriately. For this reason, a number of modeling approaches have been developed, which couple the reduction of hydraulic conductivity with a reduction of porosity caused by microbial biomass growth. These approaches differ in terms of assumptions made on biomass composition, configuration, and distribution within the porous media. As a result, the predictions of these models regarding the clogging efficiency of biomass differ, too. Here, an evaluation of several of bioclogging models is presented. Model predictions are compared with experimental data and the sensitivity of model output towards internal parameters is tested. Results show that the clogging models can be described by a limited number physical parameters, of which values might be derived from experimental observations (e.g., residual hydraulic conductivities of clogged media). In contrast, the in-situ measurement of several properties of the clogging biomass is still a challenge, limiting accurate predictions of bioclogging. Biomass properties (e.g., the biomass density, the flow resistance of the biomass and the biomass distribution at the pore scale) hardly determined in clogging experiments, so far, have a major impact on model simulations.
DE: 3210 Modeling
DE: 1829 Groundwater hydrology
DE: 1832 Groundwater transport
DE: 0400 Biogeosciences
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting