GNGTS 2018 - 37° Convegno Nazionale

138 GNGTS 2018 S essione 1.1 within the seismological services. Moreover, the catalog will be the starting point to investigate lower magnitude seismicity in key regions using template matching algorithms (Ross et al. , 2018). Acknowledgements. AlpArray at ETH Zurich is funded by Swiss National Science Foundation SINERGIAProject CRSII2-154434/1 (Swiss-AlpArray). We thanks L. Scarabello, P. Kästli, R. Racine and S. Heimers (ETH Zurich) for their invaluable work and technical support. References Diehl T., Kissling E., Husen S., Aldersons F.; 2009: Consistent phase picking for regional tomography models: application to the greater Alpine region . Geophysical Journal International, 176 (2): 542-554. Hetényi G., Molinari I., Clinton J., Bokelmann G., Bondár I., Crawford W. C., Dessa J-X., Doubre C., Friederich W., Fuchs F., Giardini D., Gráczer Z., Handy M. R., Herak M., Jia Y., Kissling E., Kopp H., Korn M., Margheriti L., Meier T., Mucciarelli M., Paul A., Pesaresi D., Piromallo C., Plenefisch T., Plomerová J., Ritter J., Rümpker G., Šipka V., Spallarossa D., Thomas C., Tilmann F., Wassermann J., Weber M., Wéber Z., Wesztergom V., Živčić M., AlpArray Seismic Network Team, AlpArray OBS Cruise Crew, AlpArray Working Group; 2018: The AlpArray Seismic Network: a large-scale European experiment to image the Alpine orogeny. Surveys in Geophysics, 1-25 . doi.org/10.1007/s10712-018-9472-4. Kissling E.; 1988: Geotomography with local earthquake data . Rev. Geophys., 26 , 659-698. Ross Z. E., Meier M. A. and Hauksso E.; 2018: P-wave arrival picking and first-motion polarity determination with deep learning. J. Geophys. Res.-Solid Earth, 123 , doi: 10.1029/2017JB015251. MODELING AND DETECTING THE (HIDDEN) EFFECTS OF POROELASTICITY IN INSAR AND GPS DATA, THE CASE OF THE EMILIA ROMAGNA EARTHQUAKES M. Nespoli 1 , M.E. Belardinelli 1 , A. Gualandi 2 , E. Serpelloni 3 , M. Bonafede 1 1 Department of Physics and Astronomy, University of Bologna, Bologna, Italy 2 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA 3 Istituto Nazionale di Geofisica e Vulcanologia, Bologna, Italy Introduction. The two mainshocks occurred in Emilia-Romagna in 2012 were close in time and space (Fig. 1a). We model the influence of fluids and pore-pressure changes on both surface displacements and on the Coulomb failure function (CFF). The poroelastic modeling was performed in a 3D half-space whose elastic and hydraulic parameters are depth dependent, in accordance with the stratified geology of the Emilia-Romagna subsoil. The model provides both the post-seismic poroelastic displacements and the coseismic and postseismic pore- pressure changes induced by the May 20 and May 29 mainshocks. The results are compared with postseismic InSAR and GPS displacement time series. We find that pore-pressure changes have the same magnitude in both the along-strike and along-dip directions. Although we cannot completely rule out that the slow fluid flow occurring at hypocentral depth could have played an active role in carrying on the Emilia-Romagna seismic sequence, we find small postseismic porepressure and CFF changes (~10 kPa), and we think that the triggering of the second mainshock is more due to stress variations related to the tectonic activity than to fluid migration. GPS and InSAR data. We have considered the analysis of ground displacements using data from continuous GPS stations (May 2012–May 2014 time interval). The detrended and filtered displacement time series (GAMIT/GLOBK and QOCAsoftware) are the input of an independent component analysis (ICA) performed adopting a variational Bayesian approach (vbICA, Chan et al. , 2003; Gualandi et al. , 2016). The vbICA performs a spatiotemporal separation of the geodetic data into a limited number of signals, interpreted as physical sources that generated the observed displacements. Each source has a spatial distribution (U) and follows a given temporal evolution not a priori imposed (V) (Fig. 1b and 1c). The original data can be reconstructed