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The U.S. Geological Survey and cooperators are studying chlorinated solvents in a fractured sedimentary rock aquifer underlying the former Naval Air Warfare Center (NAWC), West Trenton, New Jersey. Fractured-rock aquifers are common in many parts of the United States and are highly susceptible to contamination, particularly at industrial sites. Compared to ‘unconsolidated‘ aquifers, there can be much more uncertainty about the direction and rate of contaminant migration and about the processes and factors that control chemical and microbial transformations of contaminants. Research at the NAWC is improving understanding of the transport and fate of chlorinated solvents in fractured-rock aquifers and will compare...
Categories: Publication; Types: Citation
We simulate three types of forced-gradient tracer tests (converging radial flow, unequal strength two well, and equal strength two well) and natural-gradient tracer tests in multiple realizations of heterogeneous two-dimensional aquifers with a hydraulic conductivity distribution characterized by a spherical variogram. We determine longitudinal dispersivities (αL) by analysis of forced-gradient test breakthrough curves at the pumped well and by spatial moment analysis of tracer concentrations during the natural-gradient tests. Results show that among the forced-gradient tests, a converging radial-flow test tends to yield the smallest αL, an equal strength two-well test tends to yield the largest αL, and an unequal...
The U.S. Geological Survey and cooperators are studying chlorinated solvents in a fractured sedimentary rock aquifer underlying the former Naval Air Warfare Center (NAWC), West Trenton, New Jersey. Fractured-rock aquifers are common in many parts of the United States and are highly susceptible to contamination, particularly at industrial sites. Compared to ‘unconsolidated‘ aquifers, there can be much more uncertainty about the direction and rate of contaminant migration and about the processes and factors that control chemical and microbial transformations of contaminants. Research at the NAWC is improving understanding of the transport and fate of chlorinated solvents in fractured-rock aquifers and will compare...
Categories: Publication; Types: Citation
We develop a new observation-prediction (OPR) statistic for evaluating the importance of system state observations to model predictions. The OPR statistic measures the change in prediction uncertainty produced when an observation is added to or removed from an existing monitoring network, and it can be used to guide refinement and enhancement of the network. Prediction uncertainty is approximated using a first-order second-moment method. We apply the OPR statistic to a model of the Death Valley regional groundwater flow system (DVRFS) to evaluate the importance of existing and potential hydraulic head observations to predicted advective transport paths in the saturated zone underlying Yucca Mountain and underground...
We develop a new observation-prediction (OPR) statistic for evaluating the importance of system state observations to model predictions. The OPR statistic measures the change in prediction uncertainty produced when an observation is added to or removed from an existing monitoring network, and it can be used to guide refinement and enhancement of the network. Prediction uncertainty is approximated using a first-order second-moment method. We apply the OPR statistic to a model of the Death Valley regional groundwater flow system (DVRFS) to evaluate the importance of existing and potential hydraulic head observations to predicted advective transport paths in the saturated zone underlying Yucca Mountain and underground...
Calibrated models of groundwater systems can provide substantial information for guiding data collection. This work considers using such models to guide hydrogeologic data collection for improving model predictions by identifying model parameters that are most important to the predictions. Identification of these important parameters can help guide collection of field data about parameter values and associated flow system features and can lead to improved predictions. Methods for identifying parameters important to predictions include prediction scaled sensitivities (PSS), which account for uncertainty on individual parameters as well as prediction sensitivity to parameters, and a new “value of improved information”...
In the spring of 2004, the U.S. Geological Survey (USGS) Menlo Park Center Council commissioned an interdisciplinary working group to develop a forward-looking science strategy for the USGS Menlo Park Science Center in California (here¬after also referred to as “the Center”). The Center has been the flagship research center for the USGS in the western United States for more than 50 years, and the Council recognizes that science priorities must be the primary consideration guiding critical decisions made about the future evolution of the Center. In developing this strategy, the working group consulted widely within the USGS and with external clients and collaborators, so that most stakeholders had an opportunity...
Categories: Publication; Types: Citation
In the spring of 2004, the U.S. Geological Survey (USGS) Menlo Park Center Council commissioned an interdisciplinary working group to develop a forward-looking science strategy for the USGS Menlo Park Science Center in California (here¬after also referred to as “the Center”). The Center has been the flagship research center for the USGS in the western United States for more than 50 years, and the Council recognizes that science priorities must be the primary consideration guiding critical decisions made about the future evolution of the Center. In developing this strategy, the working group consulted widely within the USGS and with external clients and collaborators, so that most stakeholders had an opportunity...
Categories: Publication; Types: Citation
Calibrated models of groundwater systems can provide substantial information for guiding data collection. This work considers using such models to guide hydrogeologic data collection for improving model predictions by identifying model parameters that are most important to the predictions. Identification of these important parameters can help guide collection of field data about parameter values and associated flow system features and can lead to improved predictions. Methods for identifying parameters important to predictions include prediction scaled sensitivities (PSS), which account for uncertainty on individual parameters as well as prediction sensitivity to parameters, and a new “value of improved information”...
A new method was developed for conducting aquifer tests in fractured-rock flow systems that have a pump-and-treat (P&T) operation for containing and removing groundwater contaminants. The method involves temporary shutdown of individual pumps in wells of the P&T system. Conducting aquifer tests in this manner has several advantages, including (1) no additional contaminated water is withdrawn, and (2) hydraulic containment of contaminants remains largely intact because pumping continues at most wells. The well-shutdown test method was applied at the former Naval Air Warfare Center (NAWC), West Trenton, New Jersey, where a P&T operation is designed to contain and remove trichloroethene and its daughter products in...
Categories: Publication; Types: Citation
The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular...
Categories: Publication; Types: Citation
The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular...
Categories: Publication; Types: Citation