The Experts below are selected from a list of 303 Experts worldwide ranked by ideXlab platform
Alicia García - One of the best experts on this subject based on the ideXlab platform.
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The Seismic Noise at Las Cañadas volcanic caldera, Tenerife, Spain: Persistence characterization, and possible relationship with regional tectonic events
Journal of Volcanology and Geothermal Research, 2008Co-Authors: Roberto Carniel, Marta Tárraga, Olivier Jaquet, Ramon Ortiz, Alicia GarcíaAbstract:Abstract The origin of the continuous Seismic Noise recorded during the last few years in the volcanic island of Tenerife (Canary Islands, Spain) is under debate, due to the important implications in terms of hazard. The Seismic Noise is strongly affected by anthropogenic contamination but previous work has shown that nevertheless a significant fraction of this Noise has a natural origin, an origin that appears to be related to the generation of local tectonic events within or close to the island. In this paper, the variogram tool is used to characterize the so called “persistence” of the Seismic Noise. This analysis can quantify how much memory the Seismic Noise has of its recent past. This has important implications in terms of how informative the recorded Noise can be about its future evolution, and this in turn puts important constraints on how likely it is for the Seismic Noise to be the source of potential precursors highlighting variations in the volcanic activity that is supposed to generate (part of) this Seismic Noise. In particular, the memory characterization can help to distinguish the naturally generated Seismic Noise from the anthropogenic contamination. Although only a few clear examples have been observed until now, the possibility that this memory can be affected by the occurrence of local tectonic events is also discussed.
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Possible interaction between tectonic events and Seismic Noise at Las Cañadas Volcanic Caldera, Tenerife, Spain
Bulletin of Volcanology, 2008Co-Authors: Roberto Carniel, Marta Tárraga, F. Barazza, Alicia GarcíaAbstract:Continuous Seismic Noise is recorded in the volcanic island of Tenerife (Canary Islands, Spain). The origin of this Noise, strongly augmented by anthropogenic contamination, is still under debate. In this paper, we discuss the relationship between this Noise and the occurrence of local tectonic events in the same area. In particular, transitions are sought in the time evolution of dynamic parameters computed on the Seismic Noise, and examples are shown where abrupt transitions may be associated with the occurrence of tectonic events. These transitions provide further evidence of the existence of a natural origin for at least part of the Seismic Noise, which is strongly contaminated—if not dominated—by anthropogenic sources.
Roberto Carniel - One of the best experts on this subject based on the ideXlab platform.
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The Seismic Noise at Las Cañadas volcanic caldera, Tenerife, Spain: Persistence characterization, and possible relationship with regional tectonic events
Journal of Volcanology and Geothermal Research, 2008Co-Authors: Roberto Carniel, Marta Tárraga, Olivier Jaquet, Ramon Ortiz, Alicia GarcíaAbstract:Abstract The origin of the continuous Seismic Noise recorded during the last few years in the volcanic island of Tenerife (Canary Islands, Spain) is under debate, due to the important implications in terms of hazard. The Seismic Noise is strongly affected by anthropogenic contamination but previous work has shown that nevertheless a significant fraction of this Noise has a natural origin, an origin that appears to be related to the generation of local tectonic events within or close to the island. In this paper, the variogram tool is used to characterize the so called “persistence” of the Seismic Noise. This analysis can quantify how much memory the Seismic Noise has of its recent past. This has important implications in terms of how informative the recorded Noise can be about its future evolution, and this in turn puts important constraints on how likely it is for the Seismic Noise to be the source of potential precursors highlighting variations in the volcanic activity that is supposed to generate (part of) this Seismic Noise. In particular, the memory characterization can help to distinguish the naturally generated Seismic Noise from the anthropogenic contamination. Although only a few clear examples have been observed until now, the possibility that this memory can be affected by the occurrence of local tectonic events is also discussed.
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Possible interaction between tectonic events and Seismic Noise at Las Cañadas Volcanic Caldera, Tenerife, Spain
Bulletin of Volcanology, 2008Co-Authors: Roberto Carniel, Marta Tárraga, F. Barazza, Alicia GarcíaAbstract:Continuous Seismic Noise is recorded in the volcanic island of Tenerife (Canary Islands, Spain). The origin of this Noise, strongly augmented by anthropogenic contamination, is still under debate. In this paper, we discuss the relationship between this Noise and the occurrence of local tectonic events in the same area. In particular, transitions are sought in the time evolution of dynamic parameters computed on the Seismic Noise, and examples are shown where abrupt transitions may be associated with the occurrence of tectonic events. These transitions provide further evidence of the existence of a natural origin for at least part of the Seismic Noise, which is strongly contaminated—if not dominated—by anthropogenic sources.
Joachim R. R. Ritter - One of the best experts on this subject based on the ideXlab platform.
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Seismic Noise: A challenge and opportunity for seismological monitoring in densely populated areas
2010Co-Authors: Jörn Christoffer Groos, Joachim R. R. RitterAbstract:Several of the new techniques using the deep underground, such as geothermal power plants or CO2 sequestration, have to be installed in densely populated areas to be economically successful. Geothermal power plants need access to the district heating network to efficiently use the low-temperature heat remaining after power production. Therefore, even weak and non-destructive induced earthquakes became a serious problem for operators of geothermal power plants as such events are felt by many residents. This provokes a loss of acceptance for the new technologies in the local population. The potential application of CO2 sequestration struggles with similar problems as large coal power plants are also installed in densely populated areas. A transparent and comprehensive (seismological) monitoring of new interventions in the underground is crucial to get and keep the public acceptance. Seismological monitoring in cities and densely-populated areas is a challenging task due to the complexity of the man-made Seismic Noise wave field. Especially the important identification of the small events which are unnoticeable for humans is made difficult by numerous other man-made sources of Seismic energy such as traffic and industry. Man-made Seismic signals are the dominant source of Seismic energy in the frequency range of interest above 1 Hz. A good knowledge and understanding of the Seismic Noise wave field in densely populated areas is important for the successful planning and operation of seismological monitoring networks. Especially the identification of suitable measuring sites is important as the installation of entire networks in boreholes is hardly possible for economic or practical reasons. Furthermore, the reliable identification of small earthquakes requires a good knowledge of the local Seismic Noise wave field besides other parameters (e.g. velocity structure, etc.). We present a statistical classification scheme in the time domain to quantify and characterise automatically the Seismic Noise wave field. The character of Seismic Noise (e.g. Gaussian distributed or dominated by single transient signals) is represented by only six Noise classes. This approach allows us to easily visualise the Seismic Noise properties (amplitude and statistical properties). Furthermore, it provides a reduced dataset from broadband Seismic waveforms to analyse temporal and spatial changes of Seismic Noise conditions. We use this new classification scheme in combination with a spectral time-frequency analysis to demonstrate the most important properties of the urban Seismic Noise wave field especially in the frequency range important for seismological monitoring. We select representative seismological measurements in the city of Bucharest, Romania, and in the vicinity of geothermal power plants in south-western Germany for our discussion of the Seismic Noise wave field in large cities and densely populated areas.
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Time Domain Classification and Quantification of Seismic Noise
2009Co-Authors: Jörn Christoffer Groos, Joachim R. R. RitterAbstract:Currently several efforts are undertaken in seismology to retrieve information about the underground from ambient Seismic Noise (e.g. Curtis et al. 2006; Shapiro et al. 2005; Sens-Schonfelder & Wegler 2006). Such studies are especially interesting in areas where traditional Seismic methods are complicated such as remote areas with poor access and cities. E.g. a large number of passive Seismic measurements in urban environments are undertaken with the aim to provide the required underground information for Seismic hazard assessment. Seismological research must significantly improve the understanding of (urban) Seismic Noise to successfully and reliably apply these new methods in urban environments (Bonnefoy-Claudet et al. 2006; Campillo 2006). A good knowledge of the Seismic Noise conditions and contributing Noise sources are crucial to select adequate time windows of available long-term data or to design short-term measurements. We present a statistical classification scheme in the time domain to quantify and characterise Seismic Noise. The character of Seismic Noise (e.g. Gaussian distributed or dominated by single signals) is represented by only six Noise classes. This approach allows us to easily visualise the Seismic Noise properties (amplitude and statistical properties). Furthermore, it provides a reduced dataset from broadband Seismic waveforms to analyse temporal and spatial changes of Seismic Noise conditions.
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Time domain classification and quantification of Seismic Noise in an urban environment
Geophysical Journal International, 2009Co-Authors: Jörn Christoffer Groos, Joachim R. R. RitterAbstract:SUMMARY Broad-band urban Seismic Noise (USN) must be considered as a temporally and spatially non-stationary random process. Due to the high variability of USN a single measure like the standard deviation of a Seismic Noise time-series or the power spectral density at a given frequency is not enough to characterize a sample (time-series) of USN comprehensively. Therefore, we use long-term spectrograms and propose an automated statistical classification in the time domain to quantify and characterize USN. Long-term spectrograms of up to 28 d duration are calculated from a broad-band Seismic data set recorded in the metropolitan area of Bucharest, Romania, to identify the frequency-dependent behaviour of the timevariable processes contributing to USN. Based on the spectral analysis eight frequency ranges between 8 mHz and 45 Hz are selected for our proposed time domain classification. The classification scheme identifies deviations from the Gaussian distribution of 4-hr-long timeseries of USN. Our classification is capable to identify Gaussian distributed Seismic Noise timeseries as well as time-series dominated by transient or periodic signals using six Noise classes. Four additional Noise classes are introduced to identify corrupt time-series. The performance of the method is tested with a synthetic data set. We also apply the statistical classification for the data set from Bucharest in three time windows (0–4, 8–12 and 13–17 EET) at 11 d in the eight frequency ranges. Only 40 per cent of the analysed time-series are observed to be Gaussian distributed. Most common deviations from the Gaussian distribution (∼47 per cent) are due to the influence of large-amplitude transient signals. In all frequency ranges between 0.04 and 45 Hz significant variations of the statistical properties of USN are observed with daytime, indicating the broad-band human influence on USN. We observe the human activity as a dominant influence on the USN above and below the frequency band of ocean-generated microseism between 0.04 and 0.6 Hz. Our time domain classification and quantification is furthermore capable to resolve the influence of wind on Seismic Noise and a known site effect variation in the metropolitan area of Bucharest. The information about Noise amplitudes and statistical properties derived automatically from broad-band Seismic data can be used to select time windows containing adequate data for Seismic Noise utilization like H/V-studies or ambient Noise tomography.
Arnaud Burtin - One of the best experts on this subject based on the ideXlab platform.
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Spatiotemporal sequence of Himalayan debris flow from analysis of high-frequency Seismic Noise
Journal of Geophysical Research, 2009Co-Authors: Arnaud Burtin, R. Cattin, L. Bollinger, J. Vergne, John L. NabelekAbstract:During the 2003 summer monsoon, the Hi-CLIMB seismological stations deployed across the Himalayan Range detected bursts of high-frequency Seismic Noise that lasted several hours to days. On the basis of the cross correlation of Seismic envelopes recorded at 11 stations, we show that the largest transient event on 15 August was located nearby a village partially destroyed on that day by a devastating debris flow. This consistency in both space and time suggests that high-frequency Seismic Noise analysis can be used to monitor debris flow generation as well as the evacuation of the sediment. A systematic study of one year of Seismic Noise, focusing on the detection of similar events, provides information on the spatial and temporal occurrence of mass movements at the front of the Himalayas. With a 50% probability of occurrence of a daily event, a total of 46 debris flows are Seismically detected. Most of them were generated in regions of steep slopes, large gullies, and loose soils during the 2003 summer monsoon storms. These events are compared to local meteorological data to determine rainfall thresholds for slope failures, including the cumulative rainfall needed to bring the soil moisture content to failure capacity. The inferred thresholds are consistent with previous estimates deduced from soil studies as well as sediment supply investigations in the area. These results point out the potential of using Seismic Noise as a dedicated tool for monitoring the spatiotemporal occurrence of landslides and debris flows on a regional scale.
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Spectral analysis of Seismic Noise induced by rivers: A new tool to monitor spatiotemporal changes in stream hydrodynamics
Journal of Geophysical Research, 2008Co-Authors: Arnaud Burtin, R. Cattin, Jérôme Vergne, Laurent Bollinger, John L. NábělekAbstract:to 20 dB (relative to (m/s) 2 /Hz) for all the stations located along a steep 30-km-long narrow and deeply incised channel of the Trisuli River, a major trans-Himalayan river. The early summer increase in high-frequency energy is modulated by a 24-h periodicity where the minimum of Seismic Noise level is reached around noon and the maximum is reached late in the evening. A detailed study of Seismic Noise amplitude reveals a clear correlation with both regional meteorological and hydrological data along the Trisuli River. Seasonal increase in ambient Noise coincides with the strong monsoon rainfall and a period of rapid melting of snow and ice in the high elevations. The observed 24-h cyclicity is consistent with the daily fluctuation of the precipitation and river discharge in the region. River-induced Seismic Noise is partly generated by stream turbulence, but this mechanism fails to explain the observed clockwise hysteresis of Seismic Noise amplitude versus water level. This pattern is better explained if a significant part of the observed Seismic Noise is caused by ground vibrations generated by bed load transport. This points out the potential of using background Seismic Noise to quantify in continuous river bed load and monitor its spatial variations, which remain difficult with classical approaches.
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Spectral analysis of Seismic Noise induced by rivers: A new tool to monitor spatiotemporal changes in stream hydrodynamics
Journal of Geophysical Research: Solid Earth, 2008Co-Authors: Arnaud Burtin, R. Cattin, Jérôme Vergne, Laurent Bollinger, John L. NabelekAbstract:Analysis of continuous Seismic data recorded by a dense passive seismological network (Hi-CLIMB) installed across the Himalayas reveals strong spatial and temporal variations in the ambient Seismic energy produced at high frequencies (>1 Hz). From June to September 2003, the high-frequency Seismic Noise is observed to increase up to 20 dB (relative to (m/s)2/Hz) for all the stations located along a steep 30-km-long narrow and deeply incised channel of the Trisuli River, a major trans-Himalayan river. The early summer increase in high-frequency energy is modulated by a 24-h periodicity where the minimum of Seismic Noise level is reached around noon and the maximum is reached late in the evening. A detailed study of Seismic Noise amplitude reveals a clear correlation with both regional meteorological and hydrological data along the Trisuli River. Seasonal increase in ambient Noise coincides with the strong monsoon rainfall and a period of rapid melting of snow and ice in the high elevations. The observed 24-h cyclicity is consistent with the daily fluctuation of the precipitation and river discharge in the region. River-induced Seismic Noise is partly generated by stream turbulence, but this mechanism fails to explain the observed clockwise hysteresis of Seismic Noise amplitude versus water level. This pattern is better explained if a significant part of the observed Seismic Noise is caused by ground vibrations generated by bed load transport. This points out the potential of using background Seismic Noise to quantify in continuous river bed load and monitor its spatial variations, which remain difficult with classical approaches.
Boualem Youcef Nassimbenabdeloued - One of the best experts on this subject based on the ideXlab platform.
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geophonino w a wireless multichannel Seismic Noise recorder system for array measurements
Sensors, 2019Co-Authors: Juan Luis Solerllorens, Juan Jose Galianamerino, Jose Juan Ginercaturla, S Rosacintas, Boualem Youcef NassimbenabdelouedAbstract:The characterization of soil is essential for the evaluation of Seismic hazard, because soil properties strongly influence the damage caused by earthquakes. Methods based on Seismic Noise are the most commonly used in soil characterization. Concretely, methods based on Seismic Noise array measurements allow for the estimation of Rayleigh wave dispersion curves and, subsequently, shear-wave velocity profiles. The equipment required for the application of this technique is usually very expensive, which could be a significant economic challenge for small research groups. In this work, we have developed a wireless multichannel Seismic Noise recorder system (Geophonino-W), which is suitable for array measurements. Each station includes a microcontroller board (Arduino), a conditioning circuit, an Xbee module, an SD card, and a GPS module. Several laboratory tests were carried out in order to study the performance of the Geophonino-W: A frequency response test (impulse response and Noise); synchronization test; and battery duration test. Comparisons of Geophonino-W with the commercial systems and field measurements were also carried out. The estimated dispersion curves obtained using the proposed system were compared with the ones obtained using other commercial equipment, demonstrating the effectiveness of Geophonino-W for Seismic Noise array measurements. Geophonino-W is an economic open-source and hardware system that is available to any small research group or university.
