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Symposium on the Application of Geophysics to Engineering and Environmental Problems 2010 2010
DOI: 10.4133/1.3445424
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A Case Study of Self‐Potential Detection of Seepage at the Junction of Two Embankment Dams

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“…By measuring these voltage variations, researchers can gain valuable information about the hydraulic regime within the dam, which is crucial for detecting and characterizing seepage. Studies by [17][18][19] have demonstrated the effectiveness of the SP method in identifying and characterizing seepage in embankment dams. The electrical resistivity tomography (ERT) method measures the electrical resistivity/conductivity of the subsurface by galvanic coupling, allowing researchers to visualize variations in the dam's composition and identify potential anomalies such as weak zones, cracks, or excessive moisture.…”
Section: Introductionmentioning
confidence: 99%
“…By measuring these voltage variations, researchers can gain valuable information about the hydraulic regime within the dam, which is crucial for detecting and characterizing seepage. Studies by [17][18][19] have demonstrated the effectiveness of the SP method in identifying and characterizing seepage in embankment dams. The electrical resistivity tomography (ERT) method measures the electrical resistivity/conductivity of the subsurface by galvanic coupling, allowing researchers to visualize variations in the dam's composition and identify potential anomalies such as weak zones, cracks, or excessive moisture.…”
Section: Introductionmentioning
confidence: 99%
“…This electrical potential anomaly can be sampled at the ground surface with a pair of non-polarizing electrodes (one used as a reference) and high input-impedance voltmeter. This method has been broadly used for the detection of seepages in embankments (e.g., Nzumotcha-Tchoumkam et al, 2010). However other sources of current exist in the subsurface (e.g., associated with the corrosion of metallic bars and ores, Mendonça, 2008) and can make the interpretation of selfpotential signals more difficult (Revil et al, 2012).…”
Section: Introductionmentioning
confidence: 99%