In this work, a computationally efficient Bayesian framework for the reduction and characterization of parametric uncertainty in computationally demanding environmental 3‐D numerical models has been developed. The framework is based on the combined application of the Stochastic Response Surface Method (SRSM, which generates accurate and computationally efficient statistically equivalent reduced models) and the Markov chain Monte Carlo method. The application selected to demonstrate this framework involves steady state groundwater flow at the U.S. Department of Energy Savannah River Site General Separations Area, modeled using the Subsurface Flow And Contaminant Transport (FACT) code. Input parameter uncertainty, based initially on expert opinion, was found to decrease in all variables of the posterior distribution. The joint posterior distribution obtained was then further used for the final uncertainty analysis of the stream base flows and well location hydraulic head values.
The groundwater flow model supporting Performance Assessments (PAs) and Composite Analyses (CAs) at the Savannah River Site was significantly revised in 2016 and 2017 using new hydrostratigraphic surfaces, updated well water level calibration targets, and semi-automated model calibration with the PEST optimization code. This model is referred to as "GSA_2016". This report documents further refinement of the GSA_2016 model in 2018 to incorporate updates to model calibration targets, closure of the H-Area Ash Basin, construction of E-Area Slit Trench operational covers, and plume information from the Mixed Waste Management Facility and Low-Level Radioactive Waste Disposal Facility. Another objective was to lower hydraulic head residuals by adding another calibration zone. The resulting model is referred to as "GSA_2018".
This data package provides recommendations for waste form physical and chemical properties to support the initial analysis of Solid Secondary Waste (SSW) disposals in the 2017 Integrated Disposal Facility (IDF) Performance Assessment (PA). At this time, specific formulations have not been identified for cementitious materials that will be used to encapsulate or solidify SSW, and no IDF-specific experiments were conducted to obtain data for the PA. Thus recommended property values are provided for a range of candidate materials, and based on a review of existing literature. Four key SSW streams were identified for emphasis due to expected inventories for contaminants of potential concern (COPC): HEPA filters, ion exchange resins, carbon adsorber beds and Ag-mordenite. Based on current disposal plans, compacted HEPA filters were considered as an encapsulated waste form and the other three key waste streams were assumed to be blended and solidified in a cementitious matrix. Considerations for alternative disposal methods were also addressed. The IDF PA team identified specific COPCs expected to be the key contributors for the PA calculations: Tc-99, I-129, Cs-137, Sr-90, uranium isotopes (and total uranium), chromium, mercury and nitrate. These species are the focus of this data package.
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