Milling activities at a former uranium mill site near Riverton, Wyoming, USA, contaminated the shallow groundwater beneath and downgradient of the site. Although the mill operated for \6 years (1958)(1959)(1960)(1961)(1962)(1963), its impact remains an environmental liability. Groundwater modeling predicted that natural flushing would achieve compliance with applicable groundwater protection standards by the year 2098. A decade of groundwater monitoring indicated that contaminant concentrations were declining steadily, which confirmed the conceptual site model (CSM). However, local flooding in 2010 mobilized contaminants that migrated downgradient from the Riverton site and resulted in a dramatic increase in groundwater contaminant concentrations. This observation indicated that the original CSM was inadequate to explain site conditions and needed to be refined. In response to the new observations after the flood, a collaborative investigation to better understand site conditions and processes commenced. This investigation included installing 103 boreholes to collect soil and groundwater samples, sampling and analysis of evaporite minerals along the bank of the Little Wind River, an analysis of evapotranspiration in the shallow aquifer, and sampling naturally organic-rich sediments near groundwater discharge areas. The enhanced characterization revealed that the existing CSM did not account for high uranium concentrations in groundwater remaining on the former mill site and groundwater plume stagnation near the Little Wind River. Observations from the flood and subsequent investigations indicate that additional characterization is still needed to continue refining the CSM and determine the viability of the natural flushing compliance strategy. Additional sampling, analysis, and testing of soil and groundwater are necessary to investigate secondary contaminant sources, mobilization of contaminants during floods, geochemical processes, contaminant plume stagnation, distribution of evaporite minerals and organic-rich sediments, and mechanisms and rates of contaminant transfer from soil to groundwater. Future data collection will be used to continually revise the CSM and evaluate the compliance strategy at the site.
This study investigates the potential impact of climate change on residual contaminants in vadose zones and groundwater. We assume that the effect of climate changes can be represented by perturbations in the natural recharge through the aquifer system. We perform numerical modeling of unsaturated/saturated flow and transport and consider different performance metrics: contaminant concentrations at observation wells and contaminant export at the site's boundary. We evaluate the effect of increasing and decreasing recharge as well as the impact of potential failure of surface capping structures employed to immobilize vadose zone contaminants. Our approach is demonstrated in a real case study by simulating transport of non-reactive radioactive tritium at the U.S. Department of Energy's Savannah River Site. Results show that recharge changes significantly affect well concentrations: after an initial slight dilution we identify a significant concentration increase at different observation wells some years after t he recharge increase and/or the cap failure, as a consequence of contaminants' mobilization. This effect is generally emphasized and occurs earlier as the recharge increases. Under decreased aquifers' recharge the concentration could slightly increase for some years, due to a decrease of dilution, depending on the magnitude of the negative recharge shift. We identify trigger levels of recharge above which the concentration/export breakthrough curves and the time of exceedance of the Maximum Contaminant Level for tritium are remarkably affected. Moreover, we observe that the contaminant export at the control plane, identified as the risk pathway to the downgradient
This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the :. United States Government or any agency thereof. The views and opinions of t authors expressed herein do not necessarily state or reflect those of the United-States'Government or any agency thereof. ,This repon has been reproduced directly from the best available copy. .-Available to DOE and DOE contractors from the Office of Scientific and Technical Information, P. O. Box 62, Oak Ridge, TN 37831; prices available from (615) 576-8401.
This study presents a Kalman filter-based framework to establish a real-time in situ monitoring system for groundwater contamination based on in situ measurable water quality variables, such as specific conductance (SC) and pH. First, this framework uses principal component analysis (PCA) to identify correlations between the contaminant concentrations of interest and in situ measurable variables. It then applies the Kalman filter to estimate contaminant concentrations continuously and in real-time by coupling data-driven concentration-decay models with the previously identified data correlations. We demonstrate our approach with historical groundwater data from the Savannah River Site F-Area: We use SC and pH data to estimate tritium and uranium concentrations over time. Results show that the developed method can estimate these contaminant concentrations based on in situ measurable variables. The estimates remain reliable with less frequent or no direct measurements of the contaminant concentrations, while capturing the dynamics of short- and long-term contaminant concentration changes. In addition, we show that data mining, such as PCA, is useful to understand correlations in groundwater data and to design long-term monitoring systems. The developed in situ monitoring methodology is expected to improve long-term groundwater monitoring by continuously confirming the contaminant plume's stability and by providing an early warning system for unexpected changes in the plume's migration.
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