Numerical Modeling of Time‐lapse Electrical Resistivity Data for Improved Imaging of Managed Aquifer Recharge
Date
2014-01-29
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Abstract
Time‐lapse electrical resistivity tomography (ERT) is becoming more useful for
identifying spatial and temporal variability in unsaturated flow and transport
processes. This research is focused on the numerical forward modeling of synthetic
time‐lapse ERT data to simulate the response of a Managed Aquifer Recharge (MAR)
pond in the Pajaro Valley, California.
One of the issues identified at this site is that during the operation of the pond
there is a time‐varying water layer, which has a large effect on the ERT data. We
illustrate through forward modeling scenarios that small positional errors in either
pond stage or topography will create large misfits between observed and calculated
ERT data resulting in inversion artifacts.
We develop a method to improve the accuracy of the pond stage or topographic
positions by 1) estimating the time of electrode wetting for a subset of time‐lapse
ERT data and, 2) applying a correction to the model by adjusting the stage height or
electrode positions accordingly. Although the developed framework has some
limitations, it has potential to improve MAR imaging capabilities at this site.
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Geophysics
Citation
Ferguson, C. M. (2014). Numerical Modeling of Time‐lapse Electrical Resistivity Data for Improved Imaging of Managed Aquifer Recharge (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/27143