Hydrobiogeochemical Modeling of Field-Scale Uranium Bioremediation

Seminar
Steve Yabusaki
Thursday, March 5, 2015 · 2:30 pm to · 6:30 am
ESB 5104
Hosted by
Uli Mayer

Uranium contaminated groundwater can be found in a wide variety of settings as a result of the defense production mission, milling and processing operations, and mining activities. In many cases, uranium plumes persist despite natural groundwater flushing that should have cleaned up these sites according to earlier models. In 2002, a long-term field research study at a former uranium mill tailings site in western Colorado was begun to better understand the processes, properties, and conditions controlling uranium mobility and the potential for engineered bioremediation of uranium contaminated groundwater. A key component of the research was the development of a mathematical model that couples three-dimensional variably saturated flow through physically and chemically heterogeneous sediments with multicomponent biogeochemical reactive transport. We present the modeling of a field experiment, in which acetate groundwater amendment was used to stimulate indigenous metal-reducing bacteria to catalyze the transformation of aqueous U(VI) to immobile U(IV) mineral.

In the model, the geochemical conditions are impacted directly by the terminal electron accepting process (TEAP) reactions and indirectly by subsidiary reactions induced by the biologically-mediated reaction products. The modeling also addresses site-specific issues such as the continuous influx of U(VI) into the treatment zone, seasonal water table variation, spatially variable physical (hydraulic conductivity, porosity) and geochemical (reactive surface area) material properties, and competition for the acetate electron donor by sulfate reducing bacteria. Genomic, transcriptomic, and proteomic data from groundwater samples was crucial to the refinement of the biogeochemical reaction network. Advanced computing was necessary to provide the high performance and large memory to simulate the comprehensively detailed processes, including a genome-scale “in silico” metabolic model for Geobacter metallireducens.