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Landslide characterization through seismic noise investigation

ZOPPÃ , GIULIANA
•
COSTA, GIOVANNI
•
G. Marcato
2013
  • conference object

Abstract
The purpose of this study is to evaluate the capabilities of seismic noise data for detection of landslide sliding surfaces using the H/V spectral ratio (Nakamura method). The case study is Passo della Morte landslide, located in the Nord East of Italy (Carnic Alps) along the left side of the Tagliamento River. Its surface is approximately 530 thousand m2 and movements are up to 5 cm/year of on most active zones. The risk associated with this phenomenon is the interference with a National Road (N.R. 52) and two road tunnels. Moreover, Tagliamento River flowing at the landslide toe, a possible damming has to be taken into account. Several studies have been carried out to characterize the landslide behavior, via multiple displacement measuring techniques (laser scanner, GPS, extensimeter, inclinometer, TDR), micro-seismic monitoring systems (seismometer and acoustic emission sensor) and seismic survey (GPR and seismic refraction). The main objectives of this investigation are: determine the depth of landslide sliding surface in various sites and reconstruct its geometry by applying the law [f0=Vs/4H] to the resonance frequencies found with Nakamura method. Measurements sites have been set 200m apart on a regular grid covering all the surface to be monitored. Seismic noise has been recorded using a Lennartz seismometer (LE-3D/5s) connected to a Quanterra Q330 (Kinemetrics) acquisition system. Results have been validated by means of several boreholes performed in the examined area. On the other hand, the H/V spectral ratios in the horizontal plane as a function of the azimuth have been analyzed in order to investigate the directivity in seismic site response on the landslide. The results obtained with this work will be presented.
Archivio
http://hdl.handle.net/11368/2756556
Diritti
metadata only access
Soggetti
  • Seismic noise

  • Passo della Morte

  • Landslide

  • Nakamura method

Visualizzazioni
2
Data di acquisizione
Apr 19, 2024
Vedi dettagli
google-scholar
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