Informed electrical resistivity imaging for monitoring infiltration dynamics in the near surface
Abstract/Contents
- Abstract
- Determining the spatial distribution of subsurface properties is critical to developing efficient groundwater management strategies. Though hydrologic methods can accurately measure these properties, they often have sparse spatial coverage and cannot capture the spatial variation. Integrating geophysical and standard methods can provide more comprehensive measures of spatial and temporal variation in hydrologic properties. Electrical resistivity imaging (ERI) provides continuous maps of the subsurface electrical conductivity, which is related to water content in the vadose zone, making it particularly useful for groundwater applications. However, differences in measurement scales and the challenge of obtaining accurate images of electrical conductivity can limit the ability to integrate ERI with existing hydrologic data. To address these issues I present a framework for informed imaging, the incorporation of all available information into the acquisition, inversion and interpretation of electrical resistivity data. This framework includes methods for informed experimental design, time-lapse inversion, and integration of different data types into a consistent hydrogeologic model. I present an application of informed imaging to monitoring flow beneath an artificial recharge pond, which is part of an aquifer storage and recovery project for managing coastal groundwater resources. As a first step in informed imaging, I create a hydrostratigraphic model, which incorporates hydrologic, geologic, and geophysical data into a systematic framework. I use this model with the proposed experimental design method to select acquisition arrays for ERI experiments. Monitoring data acquired at the pond are inverted using an implementation of the extended Kalman filter, which incorporates all previously acquired information into the inversion of data at each time-step. This is the first application of this method to surface-ERI data collected in the field. Furthermore, I present an analysis of the impact of measurement support on the estimated correlation structure of properties in anisotropic systems, which must be accounted for when integrating processed geophysical data into hydrologic models. The successful application of these methodologies to monitoring flow at an artificial recharge pond leads me to conclude that using an informed imaging approach can enhance the use of geophysical methods to developing groundwater management strategies.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2010 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Mitchell, Vanessa Renae |
|---|---|
| Associated with | Stanford University, Department of Geophysics |
| Primary advisor | Knight, Rosemary (Rosemary Jane), 1953- |
| Thesis advisor | Knight, Rosemary (Rosemary Jane), 1953- |
| Thesis advisor | Beroza, Gregory C. (Gregory Christian) |
| Thesis advisor | Harris, Jerry M |
| Thesis advisor | Kitanidis, P. K. (Peter K.) |
| Thesis advisor | Pidlisecky, Adam |
| Advisor | Beroza, Gregory C. (Gregory Christian) |
| Advisor | Harris, Jerry M |
| Advisor | Kitanidis, P. K. (Peter K.) |
| Advisor | Pidlisecky, Adam |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Vanessa Renae Mitchell. |
|---|---|
| Note | Submitted to the Department of Geophysics. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2010. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2010 by Vanessa Renae Mitchell
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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