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Abstract

Assessing subsurface characteristics and imaging geologic features (e.g., faults, cavities, low-velocity layers, etc.) are typical problems in near-surface geophysics. These questions often have adverse geotechnical engineering implications, and can be especially acute when associated with high-hazard structures such as large earthen flood-control dams. Dam-related issues are becoming more frequent in the United States, because a large part of this major infrastructure was designed and constructed in the early- to mid-twentieth century; these dams are thus passing into the latter stages of their design life, where minute flaws that were overlooked or thought to be insignificant in design/construction are now proving problematic. The high-hydraulic heads associated with these structures can quicken degradation of weak areas and compromise long-term integrity. Addressing dam-related problems solely with traditional invasive drilling techniques is often inadequate (i.e., lack of lateral resolution) and/or economically exorbitant at this scale. However, strategic geotechnical drilling integrated with the broad utility of near-surface geophysics, particularly the horizontally polarized shear-wave (SH-mode) seismic-reflection technique for imaging the internal structural detail and geological foundation conditions of earthfill embankment dams can cost-effectively improve the overall subsurface definition needed for remedial engineering. Demonstrative evidence for this supposition is provided in the form of SH-wave seismic-reflection imaging of in situ and engineered as-built components of flood-control embankment dams at two example sites in the central United States.

Document Type

Article

Publication Date

10-2018

Notes/Citation Information

Published in Engineering, v. 4, issue 5, p. 694-701.

© 2018 The Author. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Digital Object Identifier (DOI)

https://doi.org/10.1016/j.eng.2018.08.009

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