Water Table Dynamics and Biogeochemical Cycling in a Shallow, Variably-Saturated Floodplain.

Three-dimensional variably saturated flow and multicomponent biogeochemical reactive transport modeling, based on published and newly generated data, is used to better understand the interplay of hydrology, geochemistry, and biology controlling the cycling of carbon, nitrogen, oxygen, iron, sulfur, and uranium in a shallow floodplain. In this system, aerobic respiration generally maintains anoxic groundwater below an oxic vadose zone until seasonal snowmelt-driven water table peaking transports dissolved oxygen (DO) and nitrate from the vadose zone into the alluvial aquifer. The response to this perturbation is localized due to distinct physico-biogeochemical environments and relatively long time scales for transport through the floodplain aquifer and vadose zone. Naturally reduced zones (NRZs) containing sediments higher in organic matter, iron sulfides, and non-crystalline U(IV) rapidly consume DO and nitrate to maintain anoxic conditions, yielding Fe(II) from FeS oxidative dissolution, nitrite from denitrification, and U(VI) from nitrite-promoted U(IV) oxidation. Redox cycling is a key factor for sustaining the observed aquifer behaviors despite continuous oxygen influx and the annual hydrologically induced oxidation event. Depth-dependent activity of fermenters, aerobes, nitrate reducers, sulfate reducers, and chemolithoautotrophs (e.g., oxidizing Fe(II), S compounds, and ammonium) is linked to the presence of DO, which has higher concentrations near the water table.

Identifying the potential loss of monitoring wells using an uncertainty analysis.

From the mid-1940s through the 1980s, large volumes of waste water were discharged at the Hanford Site in southeastern Washington State, causing a large-scale rise (>20 m) in the water table. When waste water discharges ceased in 1988, ground water mounds began to dissipate. This caused a large number of wells to go dry and has made it difficult to monitor contaminant plume migration. To identify monitoring wells that will need replacement, a methodology has been developed using a first-order uncertainty analysis with UCODE, a nonlinear parameter estimation code. Using a three-dimensional, finite-element ground water flow code, key parameters were identified by calibrating to historical hydraulic head data. Results from the calibration period were then used to check model predictions by comparing monitoring wells' wet/dry status with field data. This status was analyzed using a methodology that incorporated the 0.3 cumulative probability derived from the confidence and prediction intervals. For comparison, a nonphysically based trend model was also used as a predictor of wells' wet/dry status. Although the numerical model outperformed the trend model, for both models, the central value of the intervals was a better predictor of a wet well status. The prediction interval, however, was more successful at identifying dry wells. Predictions made through the year 2048 indicated that 46% of the wells in the monitoring well network are likely to go dry in areas near the river and where the ground water mound is dissipating.

Variably saturated flow and multicomponent biogeochemical reactive transport modeling of a uranium bioremediation field experiment.

Three-dimensional, coupled variably saturated flow and biogeochemical reactive transport modeling of a 2008 in situ uranium bioremediation field experiment is used to better understand the interplay of transport and biogeochemical reactions controlling uranium behavior under pulsed acetate amendment, seasonal water table variation, spatially variable physical (hydraulic conductivity, porosity) and geochemical (reactive surface area) material properties. While the simulation of the 2008 Big Rusty acetate biostimulation field experiment in Rifle, Colorado was generally consistent with behaviors identified in previous field experiments at the Rifle IFRC site, the additional process and property detail provided several new insights. A principal conclusion from this work is that uranium bioreduction is most effective when acetate, in excess of the sulfate-reducing bacteria demand, is available to the metal-reducing bacteria. The inclusion of an initially small population of slow growing sulfate-reducing bacteria identified in proteomic analyses led to an additional source of Fe(II) from the dissolution of Fe(III) minerals promoted by biogenic sulfide. The falling water table during the experiment significantly reduced the saturated thickness of the aquifer and resulted in reactants and products, as well as unmitigated uranium, in the newly unsaturated vadose zone. High permeability sandy gravel structures resulted in locally high flow rates in the vicinity of injection wells that increased acetate dilution. In downgradient locations, these structures created preferential flow paths for acetate delivery that enhanced local zones of TEAP reactivity and subsidiary reactions. Conversely, smaller transport rates associated with the lower permeability lithofacies (e.g., fine) and vadose zone were shown to limit acetate access and reaction. Once accessed by acetate, however, these same zones limited subsequent acetate dilution and provided longer residence times that resulted in higher concentrations of TEAP reaction products when terminal electron donors and acceptors were not limiting. Finally, facies-based porosity and reactive surface area variations were shown to affect aqueous uranium concentration distributions with localized effects of the fine lithofacies having the largest impact on U(VI) surface complexation. The ability to model the comprehensive biogeochemical reaction network, and spatially and temporally variable processes, properties, and conditions controlling uranium behavior during engineered bioremediation in the naturally complex Rifle IFRC subsurface system required a subsurface simulator that could use the large memory and computational performance of a massively parallel computer. In this case, the eSTOMP simulator, operating on 128 processor cores for 12h, was used to simulate the 110-day field experiment and 50 days of post-biostimulation behavior.