Data Decision Analysis: Project Shoal Page: 4 of 74
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The purpose of this study was to determine the most appropriate field activities in terms of
reducing the uncertainty in the groundwater flow and transport model at the Project Shoal area. The
data decision analysis relied on well-known tools of statistics and uncertainty analysis. This
procedure identified nine parameters that were deemed uncertain. These included effective porosity,
hydraulic head, surface recharge, hydraulic conductivity, fracture correlation scale, fracture
orientation, dip angle, dissolution rate of radionuclides from the puddle glass, and the retardation
coefficient, which describes the sorption characteristics. The parameter uncertainty was described
by assigning prior distributions for each of these parameters. Next, the various field activities were
identified that would provide additional information on these parameters. Each of the field activities
was evaluated by an expert panel to estimate posterior distribution of the parameters assuming a field
activity was performed. The posterior distributions describe the ability of the field activity to
estimate the true value of the nine parameters. Monte Carlo techniques were used to determine the
current uncertainty, the reduction of uncertainty if a single parameter was known with certainty, and
the reduction of uncertainty expected from each field activity on the model predictions. The mean
breakthrough time to the downgradient land withdrawal boundary and the peak concentration at the
control boundary were used to evaluate the uncertainty reduction. The radionuclide 137Cs was used
as the reference solute, as its migration is dependent on all of the parameters. The results indicate
that the current uncertainty of the model yields a 95 percent confidence interval between 42 and
1,412 years for the mean breakthrough time and an 18 order-of-magnitude range in peak
The uncertainty in effective porosity and recharge dominates the uncertainty in the model
predictions, while the other parameters are less important. A two-stage process was used to evaluate
the optimal field activities. For all of the field activities combined there were five activities that were
found to be "optimal" in terms of uncertainty reduction per unit cost: two-well, natural-gradient,
energy budget, and single-well tracer tests, and the vadose zone modeling. A subset of the field
activities was chosen such that there would be no duplication in parameter characterization. Of this
subset, the vadose zone model, barometric test, energy budget, and the two-well tracer test were
found to be optimal for the peak breakthrough time metric, while the single-well tracer test and the
hydraulic head measurements are also considered optimal for the peak concentration metric. The
environmental tracer activity was not found to be optimal, yet this activity may provide additional
information on the transport system. Care must be taken in using this analysis to design a field
characterization plan, as many assumptions were required in the analysis. First, many subjective
assumptions were required to assess the reliability of the field activities in terms of their ability to
reduce the uncertainty in the mean parameters. Actual field characterization may not result in the
same reduction in model output uncertainty as estimated by this analysis. Second, this analysis
focused on the reduction in model uncertainty due to the reduction in the uncertainty in the mean
parameters. If the uncertainty in the mean parameters is reduced to zero, there still exists uncertainty
in the natural heterogeneity that can never be reduced to zero. Therefore, this analysis should be used
in combination with expert judgement when designing a field characterization strategy.
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Forsgren, Frank; Pohll, Greg & Tracy, John. Data Decision Analysis: Project Shoal, report, January 1, 1999; United States. (digital.library.unt.edu/ark:/67531/metadc678340/m1/4/: accessed November 17, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.