Master of Science (MS)
First Committee Member
Second Committee Member
Third Committee Member
Fourth Committee Member
Heat has been effectively used as a groundwater tracer for decades, and high-resolution temperature data can better identify and quantify discrete flow zones. Refinements to the numerical modeling of advective heat transfer in borehole temperature sensing deployments can improve understanding of dynamic hydrogeologic systems. In my thesis, I develop a novel two-dimensional coupled radial groundwater flow and heat transfer numerical model that considers intra-borehole vertical flow. To test the performance of this model, I used finite element analysis to generate synthetic data sets consisting of prescribed variable flow fields and resulting borehole temperatures. I input synthetic temperatures into the two-dimensional model and invert temperatures to optimize for horizontal flux. I compared prescribed synthetic flux and temperature with inverse model computed flux and temperature to determine the errors, limitations, and reliability of this approach. The inverse model predictably approximated the prescribed flow rate within a range of optimized flux (between 1.4e-6 m/s [0.12 m/day] and 1.0e 5 m/s [0.89 m/day]), and the inverse flux was greater than the prescribed flow rate by about a factor of two. I find that model predictions were affected by a systematic error attributed to modeling mechanics that biased inverse flux and, in part, limited the range of reliable flux calculations. The error between inverse and synthetic temperature was low and relatively consistent for all scenarios, except for conduction-dominated (i.e., low flow) cases. My study provides insights into several complexities associated with quantifying groundwater flow using heat transport as well as highlights the importance of vertical flow observations and synthetic data to refine and validate numerical models.
Darcian flow; Distributed temperature sensing; DTS; Heat transfer; Hydrogeology; Numerical modeling
University of Nevada, Las Vegas
Heintz, Kevin, "Hydrogeologic Heterogeneity Identification: Using Inverse Modeling of Synthetic Borehole Temperatures to Predict Groundwater Flux" (2022). UNLV Theses, Dissertations, Professional Papers, and Capstones. 4590.
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