In this work we describe a study where automated time-lapse electrical resistivity tomography (ALERT) monitoring technology has been installed on a section of Victorian embankment on the Great Central Railway (Nottingham, United Kingdom). Raw datasets collected by the ALERT system have been processed/filtered, and inverted to yield a 3D resistivity distribution which is temperature corrected and converted to gravimetric moisture content using a relationship established by laboratory testing. Electrical resistivity tomography monitoring has been used to characterize the internal structure of the embankment, and image moisture content changes and wetting front development at a high spatial resolution. Monitoring has been undertaken at the test site to determine seasonal temperature changes in the subsurface; these data have been used to correct for temperature effects. We fitted the resistivity data as a function of gravimetric moisture content by modifying the Waxman-Smits model. Using results from laboratory testing, a best fit is computed and used to establish a resistivity, gravimetric moisture content relationship, used to facilitate property translation from temperature corrected resistivity to gravimetric moisture content. These results indicate that ERT has potential to identify structures and processes related to instability at an early stage in their development.


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