Integrating Model Abstraction into Subsurface Monitoring Strategies (NUREG/CR-7221)

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Publication Information

Manuscript Completed: December 2012
Date Published: March 2017

Prepared by:
Y. Pachepsky¹, A. Guber¹, A. Yakirevich²,
F. Pan¹, T. Gish¹, M. Kouznetsov²,
M. Van Genuchten³, R. Cady⁴, T. Nicholson⁴

¹United States Department of Agriculture
Agricultural Research Service
Environmental Microbial and Food Safety Laboratory
Hydrology and Remote Sensing Laboratory
Beltsville, MD 20705

²Department of Environmental Hydrology & Microbiology
Zuckerberg Institute for Water Research
Blaustein Institutes for Desert Research
Ben-Gurion University of the Negev
Sede Boqer Campus, 84990, Israel

³Department of Mechanical Engineering, COPPE/LTTC
Federal University of Rio de Janeiro, UFRJ
Rio de Janeiro, RJ CEP 21945-970, Brazil

⁴Division of Risk Analysis
Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington, DC 20555

T.J. Nicholson, NRC Project Manager

NRC Job Code N6730

Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington DC 20555-0001

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Abstract

NUREG/CR-7221 reports on integrating modeling abstraction techniques into subsurface monitoring strategies. This research is the culmination of many field and modeling studies conducted by the USDA/Agricultural Research Service (ARS) at their Beltsville Area Research Center. The research design was to identify and examine near-surface water flow pathways by monitoring performance indicators within the unsaturated zone and local water-table system. The peak tracer concentration and the time to peak concentration at several monitoring locations served as the performance indicators. The objective was to apply model abstraction techniques in designing monitoring networks such as those used at nuclear waste and decommissioned facilities. The level of spatial and temporal detail in characterizing soil properties (e.g. water contents and hydraulic conductivities) is based upon the model abstraction considerations. Simplifications may omit significant processes and conditions that control the water and contaminant migration. The ARS field studies provided detailed databases for modeling water and chemical tracer movement in 2- and 3- dimensions to facilitate understanding of what processes and properties could be simplified (abstracted). Model abstractions included using pedotransfer functions for hydraulic conductivity, soil profile homogenization, and unsaturated zone omission. This latter abstraction proved to be the most accurate in generating a monitoring network that reflected the calibrated model. A comprehensive sensitivity analysis was performed to identify possible directions of model simplification in the model abstraction process. The integration of model abstraction into monitoring strategies based upon the ARS field and modeling findings was documented and reviewed by international soil scientists. The studies were jointly funded by NRC and USDA/ARS.