Abstract
Rainfall-induced landslides are one of the most widespread slope instability phenomena posing a serious risk to public safety worldwide so that their temporal prediction is of great interest to establish effective warning systems. The objective of this study is to determine the effectiveness of elastic wave velocities in the surface layer of the slope in monitoring, prediction and early warning of landslide. The small-scale fixed and varied, and large-scale slope model tests were conducted. Analysis of the results has established that the elastic wave velocity continuously decreases in response of moisture content and deformation and there was a distinct surge in the decrease rate of wave velocity when failure was initiated. Based on the preliminary results of this analysis, the method using the change in elastic wave velocity proves superior for landslide early warning and suggests that a warning be issued at switch of wave velocity decrease rate.
Highlights
Landslides are one of the major natural disasters in mountainous regions
It is deduced that the slight decrease in elastic wave velocity in early stage was caused by increase in volumetric water content
This study was performed to determine a method for landslide early warning by real-time monitoring of elastic wave velocity in soil
Summary
Landslides are one of the major natural disasters in mountainous regions. Rainfall is commonly known as a major landslide trigger in different geomorphological settings. Monitoring of (1) slope movements and (2) soil moisture variation are limited to a small sensing area of the sensors. Such sensors are point sensors and sensitive only to deformation and moisture changes in their own vicinity. To cover a wide potential landslide area, a large number of such sensors would be required. This could significantly increase the project cost and on the other hand, reducing the number of sensors would decrease efficiency of landslide prediction thereby making the technology itself questionable. A possible drawback of using (3) rainfall record is that the rainfall criterion does not take into account the effects of local geology, topography and human actions in a Sensors 2018, 18, 997; doi:10.3390/s18040997 www.mdpi.com/journal/sensors
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