Quick clay avalanche is one of the most devastating landslide types worldwide. Hence, an early warning system is in demand to mitigate the fatal consequences caused by such events. To address this, distributed acoustic sensing data are collected in an area containing quick clay deposits between July 2021 and February 2022 in Rissa, Norway, while a new road is constructed on the quick clay. Road construction can induce unwanted changes to the mass balance in the clay, and previous landslides have been triggered by such changes. For this purpose, passive and active data are collected to test and compare various analysis methods. Using extracted Rayleigh wave dispersion from active sledgehammer shots, shear-wave velocity depth profiles covering the first 15 m could be estimated and compared using a linearized and a nonlinear surface wave inversion method. Furthermore, ambient noise crosscorrelation is used to obtain the dispersion from the ambient noise and associated shear-wave velocity profiles, providing two possible data collection methods for the early warning system. The obtained dispersion curves and the estimated shear-wave velocity profiles show small time-laps variation during the acquisition period (up to approximately 23 m/s), where the variation is within one standard deviation. Such a small variation suggests that the construction work and the extra load added to the quick clay do not alter the quick clay’s properties. Nevertheless, the obtained results capture the nonrepeatability effects within the acquisition period and provide reference curves for the study area at undisturbed conditions and valuable information for future comparisons to refer to potential failure scenarios. This is the first step in exploring an early warning system for quick clay landslides using fiber-optic cables. Further work will investigate the possibility of automatizing the system and improving the accuracy of the sensing system.
Climate change is impacting the Arctic faster than anywhere else in the world. As a response, ecosystems are rapidly changing. As a result, we can expect rapid shifts in whale migration and habitat use concurrent with changes in human patterns. In this context, responsible management and conservation requires improved monitoring of whale presence and movement over large ranges, at fine scales and in near-real-time compared to legacy tools. We demonstrate that this could be enabled by Distributed Acoustic Sensing (DAS). DAS converts an existing fiber optic telecommunication cable into a widespread, densely sampled acoustic sensing array capable of recording low-frequency whale vocalizations. This work proposes and compares two independent methods to estimate whale positions and tracks; a brute-force grid search and a Bayesian filter. The methods are applied to data from two 260 km long, nearly parallel telecommunication cables offshore Svalbard, Norway. First, our two methods are validated using a dedicated active air gun experiment, from which we deduce that the localization errors of both methods are 100 m. Then, using fin whale songs, we demonstrate the methods' capability to estimate the positions and tracks of eight fin whales over a period of five hours along a cable section between 40 and 95 km from the interrogator unit, constrained by increasing noise with range, variability in the coupling of the cable to the sea floor and water depths. The methods produce similar and consistent tracks, where the main difference arises from the Bayesian filter incorporating knowledge of previously estimated locations, inferring information on speed, and heading. This work demonstrates the simultaneous localization of several whales over a 800 km area, with a relatively low infrastructural investment. This approach could promptly inform management and stakeholders of whale presence and movement and be used to mitigate negative human-whale interaction.
<p>Distributed Acoustic Sensing (DAS) is becoming increasingly popular due to its high spatial and temporal resolution. DAS holds great potential for geohazard applications as, in principle, anything affecting the strain on a fibre optic cable section can be measured. Examples are passing seismic surface waves and ambient temperature changes.&#160; This presentation demonstrates the feasibility of DAS for quick clay monitoring, and presents data from a field trial in Rissa, Norway.</p><p>In Norway, almost all landslides in clays that have serious consequences are caused by the instability of quick clay. Examples include the landslides Tr&#246;gstad (1967), Rissa (1978), and recently Gjerdrum (2020).</p><p>A research field site was established at Rissa by the Centre for Geophysical Forecasting (CGF). Long term monitoring with DAS over several months is carried out to monitor changes in the geophysical parameters of the soil before and after road construction work.</p><p>Due to the close relation between elastic parameters controlling seismic wave propagation and the petrophysical properties of the sediment, which determine the strength, DAS measurements from seismic waves, mainly Rayleigh waves, can be used to investigate the soil stability.</p><p>The Rayleigh waves of interest travel with a velocity that is approximately 0.9 times the shear wave velocity (Vs) and may have wavelengths of only a few meters. The shear modulus, which is the main geomechanical parameter controlling the stability and shear strength, can be approximately inferred from Vs. Therefore, observation of changes in Vs can be used to detect changes in shear strength of clay formations.</p><p>One of the main challenges for this application lies in the detection of seismic surface waves of shorter wavelengths. Commonly used methods for quick clay monitoring suffer either from lower spatial resolution or limited area coverage, and we also seek to address these challenges.</p><p>Alcatel Submarine Network Norway developed an interrogation technology (OptoDAS) enabling long-range measurement over 100km. Spatial sampling intervals as small as 1m can be chosen. It is, however, the gauge length and the spatial sampling that determines the spatial resolution. The gauge length varies from 40m to 2m, and is analogous to receiver (group or node) separation in conventional seismic methods.&#160;</p><p>Due to the inherent properties of DAS interrogation the SNR is lower for very small gauge lengths. Although the data quality is adequate, we strive to improve the SNR further to make DAS well suited for the analysis of seismic waves with wavelengths even shorter than 4m.</p><p>A cost-effective solution for increasing the data quality could be found by introducing fibre loops into the acquisition design. The gain of these optimization will be presented, and it will be demonstrated that data quality can be improved by stacking over multiple similar fibre optic pathways.</p><p>Results will be presented for seismic signals from passive sources &#8211; such as passing cars on the nearby road, and from an active source, a seismic hammer and plate shot.</p><p>The pros and cons of using long-range high-resolution DAS technology for soil monitoring will be discussed along with potential areas for future advances.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.