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dc.contributor.advisorRevil, André, 1970-
dc.contributor.authorRittgers, Justin Bradley
dc.contributor.committeememberMooney, Michael A.
dc.contributor.committeememberSava, Paul C.
dc.contributor.committeememberSchneider, Jennifer J.
dc.contributor.committeememberSmith, Jessica, 1980-
dc.contributor.committeememberMarkiewicz, Richard
dc.date.accessioned2015-10-21T19:29:11Z
dc.date.available2015-10-21T19:29:11Z
dc.date.issued2015
dc.description2015 Fall.
dc.descriptionIncludes illustrations (some color), color maps.
dc.descriptionIncludes bibliographical references.
dc.description.abstractIn this dissertation, I present research involving the application of active and passive geophysical data collection, data assimilation, and inverse modeling for the purpose of earthen embankment infrastructure assessment. Throughout the dissertation, I identify several data characteristics, and several challenges intrinsic to characterization and imaging of earthen embankments and anomalous seepage phenomena, from both a static and time-lapse geophysical monitoring perspective. I begin with the presentation of a field study conducted on a seeping earthen dam, involving static and independent inversions of active tomography data sets, and self-potential modeling of fluid flow within a confined aquifer. Additionally, I present results of active and passive time-lapse geophysical monitoring conducted during two meso-scale laboratory experiments involving the failure and self-healing of embankment filter materials via induced vertical cracking. Identified data signatures and trends, as well as 4D inversion results, are discussed as an underlying motivation for conducting subsequent research. Next, I present a new 4D acoustic emissions source localization algorithm that is applied to passive seismic monitoring data collected during a full-scale embankment failure test. Acoustic emissions localization results are then used to help spatially constrain 4D inversion of collocated self-potential monitoring data. I then turn to time-lapse joint inversion of active tomographic data sets applied to the characterization and monitoring of earthen embankments. Here, I develop a new technique for applying spatiotemporally varying structural joint inversion constraints. The new technique, referred to as Automatic Joint Constraints (AJC), is first demonstrated on a synthetic 2D joint model space, and is then applied to real geophysical monitoring data sets collected during a full-scale earthen embankment piping-failure test. Finally, I discuss some non-technical issues related to earthen embankment failures from a Science, Technology, Engineering, and Policy (STEP) perspective. Here, I discuss how the proclaimed scientific expertise and shifting of responsibility (Responsibilization) by governing entities tasked with operating and maintaining water storage and conveyance infrastructure throughout the United States tends to create barriers for 1) public voice and participation in relevant technical activities and outcomes, 2) meaningful discussions with the public and media during crisis communication, and 3) public perception of risk and the associated resilience of downhill communities.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierT 7904
dc.identifier.urihttp://hdl.handle.net/11124/20320
dc.languageEnglish
dc.publisherColorado School of Mines. Arthur Lakes Library
dc.relation.ispartof2015 - Mines Theses & Dissertations
dc.rightsCopyright of the original work is retained by the author.
dc.subjectimaging
dc.subjectmodeling
dc.subjectsensing
dc.subjectinversion
dc.subjectembankments
dc.subjectpolicy
dc.titleActive and passive electrical and seismic time-lapse monitoring of earthen embankments
dc.typeText
thesis.degree.disciplineGeophysics
thesis.degree.grantorColorado School of Mines
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)


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