Year of Award
2023
Document Type
Thesis
Degree Type
Master of Science (MS)
Degree Name
Geosciences
Department or School/College
Department of Geosciences
Committee Chair
W. Payton Gardner
Commitee Members
Jon Graham, Marco Maneta
Keywords
conceptual model uncertainty, groundwater simulation, environmental tracers
Subject Categories
Environmental Monitoring | Geology | Hydrology | Numerical Analysis and Scientific Computing
Abstract
Environmental tracer concentrations for CFC12, SF6, and tritium are used in groundwater simulations to assess the ability of these tracers to reduce conceptual model uncertainty due to uncertainty of a site’s geologic and recharge characterization. The resulting groundwater simulations are characterized by site-specific hydrologic and geologic data, and with coordination from a field team with years of knowledge about the site. First-order (conceptual) uncertainty is directly addressed by using a stochastic modeling approach for spatial variability of the proposed subsurface configurations. Simulations of environmental tracer concentrations and water levels are used to assess six alternate conceptual models that are based on three alternate geologic interpretations and two levels of spatial complexity in groundwater recharge. Our results show that water levels and tracers both provide unique information, but tracers enhance our ability to distinguish between models throughout multiple analyses. Tracers CFC12 and tritium show how simulating environmental tracer transport in groundwater is better than using water levels at testing alternate hydrogeologic conceptual models and reducing conceptual uncertainty between them.
Recommended Citation
Nordberg, Andrew; Graham, Jon; and Gardner, W. Payton, "Evaluating the Use of Environmental Tracers to Reduce Conceptual Model Uncertainty of Hydrogeologic Models" (2023). Graduate Student Theses, Dissertations, & Professional Papers. 12138.
https://scholarworks.umt.edu/etd/12138
Included in
Environmental Monitoring Commons, Geology Commons, Hydrology Commons, Numerical Analysis and Scientific Computing Commons
© Copyright 2023 Andrew Nordberg, Jon Graham, and W. Payton Gardner