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19 - Landslide monitoring:

The role of investigative monitoring to improve understanding and early warning of failure

Published online by Cambridge University Press:  05 May 2013

John J. Clague
Affiliation:
Simon Fraser University, British Columbia
Douglas Stead
Affiliation:
Simon Fraser University, British Columbia
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Summary

Abstract

Recent years have seen significant advances in landslide monitoring technologies. Satellite and ground-based radar systems have considerably increased the areal coverage and spatial resolution of surface displacement monitoring data. Nanotechnology has led to the development of smaller, cheaper, more reliable, and more functional borehole sensors that, together with wireless data acquisition and transmission, have significantly increased the temporal resolution of subsurface slope deformation and microseismic monitoring data. These tools provide increased capacity to detect pre-failure indicators and changes in landslide behavior. Yet the interpretation of slope monitoring data for the purpose of early warning still remains largely subjective, as geologic complexity and uncertainty continue to pose major challenges. To be effective, predictive early-warning monitoring must be preceded by investigative monitoring to provide an understanding of slope behavior over time and typical responses to external stimuli such as precipitation. This chapter reviews several recent developments in landslide monitoring technologies. It discusses the role of investigative monitoring in developing slope monitoring programs and providing early-warning alert levels. Examples are provided from several recent experimental studies involving in-situ rockslide laboratories, in which detailed instrumentation systems and numerical modeling have been used to better understand the mechanisms controlling pre-failure deformations over time and their evolution leading to catastrophic failure. These examples demonstrate that by better integrating different datasets, geologic uncertainty can be minimized and better controlled to provide improved interpretation of slope monitoring and early-warning data.

Type
Chapter
Information
Landslides
Types, Mechanisms and Modeling
, pp. 222 - 234
Publisher: Cambridge University Press
Print publication year: 2012

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