GNGTS 2016 - Atti del 35° Convegno Nazionale

GNGTS 2016 S essione 1.2 201 Gephart J.W. and Forsyth D.W.; 1984:An improved method for determining the regional stress tensor using earthquake focal mechanism data: Application to the San Fernando earthquake sequence. J. Geophys. Res., 89, 9305–9320. Koulakov I.; 2009: LOTOS code for local earthquake tomographic inversion. Benchmarks for testing tomographic algorithms. Bull. Seismol. Soc. Am., 99, 1, 194-214, doi: 10.1785/0120080013. Michael A.J.; 1987: Use of Focal Mechanisms to Determine Stress: A Control Study. J. Geophys. Res., 92, 357-368. Musumeci C., Scarfì L., Palano M. and Patanè D.; 2014: Foreland segmentation along an active convergent margin: New constraints in southeastern Sicily (Italy) from seismic and geodetic observations. Tectonophysics, http:// dx.doi.org/10.1016/j.tecto.2014.05.017. Pondrelli S., Salimbeni S., Ekström G., Morelli A., Gasperini P. and Vannucci G.; 2006: The Italian CMT dataset from 1977 to the present. Phys. Earth Planet. Int., http://dx.doi.org/10.1016/j.pepi.2006.07.008 , 159/3-4, 286–303. Pondrelli S., Salimbeni S., Morelli A., Ekström G., Postpischl L., Vannucci G. and Boschi E.; 2011: European– Mediterranean Regional Centroid Moment Tensor catalog: Solutions for 2005–200., Phys. Earth Planet. Int., doi:10.1016/j.pepi.2011.01.007. Reasenber P.A. and Oppenheimer D.; 1985: Fortran computer programs for calculating and displaying earthquake fault-plane solutions. U.S. Geol. Surv. Open File Rep., 85–379. Wiemer S.; 2001: A software package to analyze seismicity: ZMAP. Seismol. Res. Lett., 72, 373–382. Zhang H., Thurber C. and Bedrosian P.; 2009: Joint inversion for Vp, Vs, and Vp/Vs at SAFOD, Parkfield, California, Geochem. Geophys. Geosyst., 10, Q110032, http://dx.doi.org/10.1029/2009GC002709. A quantitative approach to the loading rate of seismogenic sources in Italy A. Caporali 1 , C. Braitenberg 2 , P. Montone 3 , G. Rossi 4 , G. Valensise 3 , A. Viganò 5 , J. Zurutuza 1 1 Department of Geosciences, University of Padova, Italy 2 Department of Mathematics and Geosciences, University of Trieste, Italy 3 Istituto Nazionale di Geofisica e Vulcanologia, Roma, Italy 4 Istituto Nazionale di Oceanografia e Geofisica Sperimentale, Trieste, Italy 5 Servizio Sismico, Provincia Autonoma di Trento, Italy To investigate the exchange of mechanical energy between a regional stress field and localized faults, the stress rate tensor inferred from a dense velocity field of permanent GPS sites is projected onto selected fault planes of the Database of Italian Individual Seismogenic Sources (DISS 3.2.0). For given Lame and static friction constants, we compute the load rate on each fault in the sense of a rate of Coulomb Failure Function (CFF). By varying the strike, dip and rake angles in a neighborhood of the nominal values listed on the DISS we also estimate optimally oriented fault planes, in the sense of planes oriented for maximal rate of CFF. We show that of 87 Individual Seismogenic Sources (ISS) well covered by GPS data, only 4 are unloading energy and 79 to 82 (depending on the assumed friction coefficient) load energy in the range 0 : 4 kPa/yr. The sources with larger rate of CFF (4 to 6 ± 1 kPa/yr) are ITIS094 (Tocco da Casauria), ITIS052 (San Giuliano di Puglia) and ITIS053 (Ripabottoni), all in the central Apennines and characterized by a significant strike slip component. We also find that 75% of the examined sources have a loading rate less than 1 kPa/yr relative to faults with strike, dip and rake maximizing the rate of CFF, implying that that the majority of the considered faults have orientations close to optimal. This in particular applies to the sources associated to the 1976 Friuli, 1997 Colfiorito, 2009 Aquila, 2012 Emilia and 2016 Amatrice earthquakes, for which the strike of the faults based on seismological data and the geodetically inferred strike differ at most by 30 degrees. Other sources, e.g. in Friuli, exhibit an offset, suggesting that slip takes place on inherited faults. These conclusions are only marginally affected by the choice of the friction coefficient. Computing the loading rate. The knowledge of current deformation rates at the Earth’s surface represents a significant boundary condition for modeling seismogenic processes in