Estimation, optimization, and value of information in groundwater remediation
Abstract/Contents
- Abstract
- Solving groundwater problems involves a system of methods in characterization and optimization. However, no matter how theoretically sound a method may be, when it is applied in the field, uncertainty is always an important factor that cannot be neglected. Indeed, a good theory or method has to be validated in field applications, and uncertainty propagates from one stage (e.g. characterization) of the application to the next (e.g. remediation optimization). Thus, it is essential for such methods not only to include uncertainty but also to quantify uncertainty in a practical sense. This dissertation covers three important topics in groundwater remediation: site characterization, remediation optimization, and value of information. First, groundwater contamination site characterization with Monte Carlo methods, specifically, Markov chain Monte Carlo (MCMC) methods, is introduced. Then, another subsurface characterization method, stochastic inverse modeling, is covered with an emphasis on solving large-scale characterization problems, meaning resolving the subsurface heterogeneity with a high-resolution. Both methods provide estimation of the site and uncertainty about the estimation. When these characterization results are used for site management such as remediation management, effects of uncertainty on optimization need to be quantified under the specific context of the remediation problem, and traditional measures of uncertainty such as variance and correlation coefficients cannot handle this job well because they do not necessarily depict the severity of uncertainty. In this dissertation, value of information (VOI), defined as the expected cost with the present state of uncertainty minus the expected cost if uncertainty were fully or partially removed, is proposed as a context-specific measure of uncertainty, i.e., it is dependent on site conditions and remediation strategies as well as specific remediation objectives and unit costs. Several laboratory and numerical applications on hydraulic tomography and DNAPL contamination remediation are included in this dissertation to show the efficacy of the methods proposed.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2011 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Liu, Xiaoyi |
|---|---|
| Associated with | Stanford University, Civil & Environmental Engineering Department |
| Primary advisor | Kitanidis, P. K. (Peter K.) |
| Thesis advisor | Kitanidis, P. K. (Peter K.) |
| Thesis advisor | Caers, Jef |
| Thesis advisor | Gorelick, Steven |
| Advisor | Caers, Jef |
| Advisor | Gorelick, Steven |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Xiaoyi Liu. |
|---|---|
| Note | Submitted to the Department of Civil and Environmental Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2011. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2011 by Xiaoyi Liu
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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