Title | Long-term monitoring of slopes that affect transport infrastructure |
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Author | Holmes, J; Donohue, S; Chambers, J; Wilkinson, P; Meldrum, P; Gunn, D; Swift, R; Dashwood, B; Kirkham, M; Uhlemann, S; Huntley, D ; Bobrowsky, P |
Source | 160830, 2019 p. 1-5, https://doi.org/10.3997/2214-4609.201902554 |
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Year | 2019 |
Alt Series | Natural Resources Canada, Contribution Series 20200462 |
Publisher | European Association of Geoscientists and Engineers, EAGE |
Meeting | 1st Conference on Geophysics for Infrastructure Planning Monitoring and BIM, Held at Near Surface Geoscience Conference and Exhibition 2019, NSG 2019; The Hague; NL; September 8-12, 2019 |
Document | serial |
Lang. | English |
Media | paper; on-line; digital |
File format | pdf |
Subjects | Science and Technology; geophysics; potassium; slope stability; uranium; soil moisture |
Illustrations | diagrams; graphs |
Released | 2019 09 08 |
Abstract | Slope failures on the transport network are a growing issue as populations continue to expand, putting increasing demand on aging infrastructure, much of which is already operating at full capacity.
Monitoring of such slopes is therefore necessary to maintain the serviceability of transport infrastructure, mitigating against the large social, economic and environmental costs that would emerge in the result of slope failure. Near-surface
geophysics is used increasingly for the assessment of the condition of transport infrastructure. Here, the use of Proactive Infrastructure Monitoring and Evaluation (PRIME) Electrical Resistivity Tomography, which allows for continuous, near-real
time monitoring of subsurface moisture conditions, is assessed in terms of its applicability to monitoring both man-made embankments and natural slopes that affect transport infrastructure. Long-term monitoring data is presented for two field sites
(Old Dalby, a railway embankment in Leicestershire, UK, and the Ripley landslide, a natural slope in British Columbia, Canada). Results demonstrate the sensitivity of electrical resistivity to changes in moisture content, which vary seasonally, and
highlight the advantage of resistivity imaging for monitoring slope moisture dynamics over predictions based on rainfall data alone, providing information on the spatial aspects of slope hydrogeological regimes. |
GEOSCAN ID | 327293 |
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