Geophysical monitoring of moisture‐induced landslides: a review

Whiteley, J.S.; Chambers, J.E.; Uhlemann, S.; Wilkinson, P.B.; Kendall, J.M.. 2019 Geophysical monitoring of moisture‐induced landslides: a review. Reviews of Geophysics, 57 (1). 106-145. https://doi.org/10.1029/2018RG000603

Before downloading, please read NORA policies.

Preview

Text (Open Access Paper)
Whiteley_et_al-2019-Reviews_of_Geophysics.pdf - Published Version
Available under License Creative Commons Attribution 4.0.
Download (5MB) | Preview

Official URL: http://dx.doi.org/10.1029/2018RG000603

Abstract/Summary

Geophysical monitoring of landslides can provide insights into spatial and temporal variations of subsurface properties associated with slope failure. Recent improvements in equipment, data analysis, and field operations have led to a significant increase in the use of such techniques in monitoring. Geophysical methods complement intrusive approaches, which sample only a very small proportion of the subsurface, and walk-over or remotely sensed data, which principally provide information only at the ground surface. In particular, recent studies show that advances in geophysical instrumentation, data processing, modeling, and interpretation in the context of landslide monitoring are significantly improving the characterization of hillslope hydrology and soil and rock hydrology and strength and their dynamics over time. This review appraises the state of the art of geophysical monitoring, as applied to moisture-induced landslides. Here we focus on technical and practical uses of time-lapse methods in geophysics applied to monitoring moisture-induced landslide. The case studies identified in this review show that several geophysical techniques are currently used in the monitoring of subsurface landslide processes. These geophysical contributions to monitoring and predicting the evolution of landslide processes are currently underrealized. Hence, the further integration of multiple-parametric and geotechnically coupled geophysical monitoring systems has considerable potential. The complementary nature of certain methods to map the distribution of subsurface moisture and elastic moduli will greatly increase the predictive and monitoring capacity of early warning systems in moisture-induced landslide settings.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1029/2018RG000603
ISSN:	8755-1209
Date made live:	17 Apr 2019 08:10 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/522877

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1029/2018RG000603

ISSN:

8755-1209

Date made live:

17 Apr 2019 08:10 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/522877