Date of Award
Master of Science (MS)
Murdoch , Lawrence
Khan , Taufiquar
Integrated data fusion (IDF), also known as coupled inversion, is becoming a more widely used method for estimating hydrologic parameters from geophysical data. IDF is being used in this research as an approach to inversion that couples mathematical models of groundwater flow, solute transport, and electrical resistivity for the direct estimation of hydraulic conductivity, porosity, and dispersivity from transient resistivity data collected during a tracer test. In this work, synthetic field resistivity data are generated using only a single current electrode pair and many potential electrodes. This data is then used within the IDF framework to a) estimate hydraulic conductivity with a gradient-based optimization algorithm, b) analyze trends in hydraulic conductivity estimates related to changes in environmental and survey conditions, c) analyze model sensitivity to changes in hydraulic conductivity, porosity, and dispersivity, and d) determine if the limited resistivity data utilized are enough to infer that the initial conceptual model was incorrect. The results of the simulations indicate that hydraulic conductivity and porosity can be constrained quite well if Archie's Law is known, but dispersivity may remain non-unique due to trade-offs with velocity and the spatial distribution of the plume. In addition, there may not be enough information contained within current/potential pair data to definitively rule out the possibility that the system is homogeneous; therefore the addition of more current pairs may be necessary.
Fowler, Dylan, "A synthetic analysis of integrated data fusion: Combining hydrologic and geophysical data collected during a tracer test to estimate aquifer flow and transport parameters" (2010). All Theses. 997.