Investigation of Possible Landslide Precursor Activity in a Small-Scale Laboratory Experiment

Investigation of Possible Landslide Precursor Activity in a Small-Scale Laboratory Experiment

Spiridon G. Krokidis (Department of Informatics, Ionian University, Corfu, Greece), Konstantinos Marmarokopos (Department of Informatics, Ionian University, Corfu, Greece) and Markos Avlonitis (Department of Informatics, Ionian University, Corfu, Greece)
Copyright: © 2018 |Pages: 13
DOI: 10.4018/IJAGR.2018100105

Abstract

The aim of this article is to elucidate the identification and investigation of micro-crack evolution as a landslide precursor activity. For this purpose, the construction of a model test was considered appropriate by simulating a soil landslide in a small scale. There is a direct correlation between slope steepness and the occurrence of landslides. When inclination increases, a few seconds before failure, micro-cracks appear, initiating the slide. The whole procedure was recorded by an accelerometer, intending to record micro cracks imprint. The second step upon primary data acquisition was signal analysis in order to locate and examine micro-crack frequency range either a slide occurred and not. Finally, the signal analysis results indicated that there is a specific time period, a few seconds before failure, which, according to its frequency and energy content, can be defined as a landslide precursor activity. Comparing frequency content between precursor activity time period and no activity one greatly can identify the offset difference.
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Introduction

Landslides are a common natural hazard which causes great losses to life and properties every year. Along with earthquakes, tsunamis, volcanic eruptions, cyclones, wildfires and floods, landslides are among the greatest natural disasters and one of the major causes of loss of life. In many countries of the world, landslides are the most important catastrophic phenomena in terms of damage (Papathoma, Zischg, Fuchs, Glade, & Keiler, 2015) (Glade, Stark, & Dikau, 2005) (Mertens et al., 2016) (Glass, 2013) (Colkesen, Sahin, & Kavzoglu, 2016) (Highland & Bobrowsky, 2008). Slope movements do not need to be large to be destructive and as a phenomenon can occur almost everywhere in the world (Romer & Ferentinou, 2016) (Guo, Sun, Lai, Lu, & Li, 2016) (Peruccacci, et al., 2017) (Xu, Coop, Maosheng, & Genlong, 2017) (Persichillo, Bordoni, Cavalli, Crema, & Meisina, 2018) (Peng, et al., 2017) (Lv, Liu, & Yang, 2017), both in natural and artificial slopes and this is primarily due to the different mechanisms of landslide triggering and activation (Highland & Bobrowsky, 2008) (Hunt, 2007) (Landslide Types and Processes, 2004) (Varnes, 1978) (Lee & Evangelista, 2006) (Gariano & Guzzetti, 2016). Considering that although a material in an old landslide moved and balanced in a new position, it is still sensitive and can easily slide again onto the same slip surface (Dewitte & Demoulin, 2005), it is imperative one comprehend and emphasize on the research stage of monitoring active landslides, (Bozzano, Cipriani, Mazzanti, & Prestininzi, 2014) as the development of landslide early warning systems decreases social impacts, financial and environmental cost (Nicu, 2017) (Poonam, et al., 2017) (Uhlemann, et al., 2015). According to the aforementioned, current paper presents a study on micro-crack behavior in a landslide simulation by using a physical model. Physical models are an effective way to comprehend the triggering mechanisms, failure potentials as well as the behavior of soil slope stability influenced by the increase of slope angle in a small scale (Li, et al., 2016). Aiming at mitigating the destructiveness of future landslides, small scale landslide experiments have been used by various researchers (Eckersley, 1990) (Guymer & Spence, 1997) (Wang & Sassa, 2001) (Wang & Shibata, 2007) (Take, Bolton, Wong, & Yeung JF, 2004) (Deangeli, 2008) (Roche, Attali, Mangeney, & Lucas, 2011). What is presented in the current study is an initial approach including the recognition of micro-crack imprint, at a simulation level, as precursor activity, in order to draw some initial conclusions about their frequency and energy content that will help in further stages of research.

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