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.

Effect of dissolved CO2 on a shallow groundwater system: a controlled release field experiment.

Capturing carbon dioxide (CO(2)) emissions from industrial sources and injecting the emissions deep underground in geologic formations is one method being considered to control CO(2) concentrations in the atmosphere. Sequestering CO(2) underground has its own set of environmental risks, including the potential migration of CO(2) out of the storage reservoir and resulting acidification and release of trace constituents in shallow groundwater. A field study involving the controlled release of groundwater containing dissolved CO(2) was initiated to investigate potential groundwater impacts. Dissolution of CO(2) in the groundwater resulted in a sustained and easily detected decrease of ~3 pH units. Several trace constituents, including As and Pb, remained below their respective detections limits and/or at background levels. Other constituents (Ba, Ca, Cr, Sr, Mg, Mn, and Fe) displayed a pulse response, consisting of an initial increase in concentration followed by either a return to background levels or slightly greater than background. This suggests a fast-release mechanism (desorption, exchange, and/or fast dissolution of small finite amounts of metals) concomitant in some cases with a slower release potentially involving different solid phases or mechanisms. Inorganic constituents regulated by the U.S. Environmental Protection Agency remained below their respective maximum contaminant levels throughout the experiment.

Influence of heavy metals on microbial growth kinetics including lag time: mathematical modeling and experimental verification.

Heavy metals can significantly affect the kinetics of substrate biodegradation and microbial growth, including lag times and specific growth rates. A model to describe microbial metabolic lag as a function of the history of substrate concentration has been previously described by Wood et al. (Water Resour Res 31:553-563) and Ginn (Water Resour Res 35:1395-1408). In the present study, this model is extended by including the effect of heavy metals on metabolic lag by developing an inhibitor-dependent functional to account for the metabolic state of the microorganisms. The concentration of the inhibiting metal is explicitly incorporated into the functional. The validity of the model is tested against experimental data on the effects of zinc on Pseudomonas species isolated from Lake Coeur d'Alene sediments, Idaho, U.S.A., as well as the effects of nickel or cobalt on a mixed microbial culture collected from the aeration tank of a wastewater treatment plant in Athens, Greece. The simulations demonstrate the ability to incorporate the effect of metals on metabolism through lag, yield coefficient, and specific growth rates. The model includes growth limitation due to insufficient transfer of oxygen into the growth medium.

Comparison of Electrostatic and Non-Electrostatic Models for U(VI) Sorption on Aquifer Sediments.

A non-electrostatic generalized composite surface complexation model (SCM) was developed for U(VI) sorption on contaminated F-Area sediments from the U.S. Department of Energy Savannah River Site, South Carolina. The objective of this study was to test if a simpler, semi-empirical, non-electrostatic U(VI) sorption model (NEM) could achieve the same predictive performance as a SCM with electrostatic correction terms in describing U(VI) plume evolution and long-term mobility. One-dimensional reactive transport simulations considering key hydrodynamic processes, Al and Fe minerals, as well as H+ and U surface complexation, with and without electrostatic correction terms, were conducted. The NEM was first calibrated with laboratory batch H+ and U(VI) sorption data on F-Area sediments, and then the surface area of the NEM was adjusted to match field observations of dissolved U(VI). Modeling results indicate that the calibrated NEM was able to perform as well as the previously developed electrostatic model in predicting the long-term evolution of H+ and U(VI) at the site, given the variability of field-site data. The electrostatic and NEM models yield somewhat different results for the time period when basin discharge was active; however, it is not clear which modeling approach may be better to model this early time period because groundwater quality data during this period were not available. A key finding of this study is that the applicability of NEM (and thus robustness of its predictions) to the field system evolves with time and is strongly dependent on the pH range that was used to develop the model.