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Reconstruction of landslide movements by inversion of 4D electrical resistivity tomography monitoring data

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journal contribution
posted on 2016-03-03, 14:25 authored by Paul Wilkinson, J. Chambers, S. Uhlemann, Philip Meldrum, Alister SmithAlister Smith, Neil Dixon, Meng H. Loke
Reliable tomographic inversion of geoelectrical monitoring data from unstable slopes relies critically on knowing the electrode positions, which may move over time. We develop and present an innovative inverse method to recover movements in both surface directions from geoelectrical measurements made on a grid of monitoring electrodes. For the first time, we demonstrate this method using field data from an active landslide to recover sequences of movement over timescales of days to years. Comparison with GPS measurements demonstrated an accuracy of within 10% of the electrode spacing, sufficient to correct the majority of artifacts that would occur in subsequent image reconstructions if incorrect positions are used. Over short timescales where the corresponding subsurface resistivity changes were smaller, the constraints could be relaxed and an order-of-magnitude better accuracy was achievable. This enabled the onset and acceleration of landslide activity to be detected with a temporal resolution of a few days.

Funding

P.W., J.C., S.U., and P.M. were supported by the Natural Environment Research Council (NERC). A.S. and N.D. were supported by the Engineering and Physical Sciences Research Council.

History

School

  • Architecture, Building and Civil Engineering

Published in

Geophysical Research Letters

Volume

43

Issue

3

Pages

1166-1174

Citation

WILKINSON, P. ... et al., 2016. Reconstruction of landslide movements by inversion of 4D electrical resistivity tomography monitoring data. Geophysical Research Letters, 43 (3), pp. 1166–1174.

Publisher

American Geophysical Union (AGU) ; Wiley © The Authors

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Acceptance date

2016-01-19

Publication date

2016-02-13

Copyright date

2016

Notes

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

ISSN

0094-8276

eISSN

1944-8007

Language

  • en

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