@article{DiGiulioSavvaidisOhrnbergeretal.2012,
  author    = {Di Giulio, Giuseppe and Savvaidis, Alexandros and Ohrnberger, Matthias and Wathelet, Marc and Cornou, Cecile and Knapmeyer-Endrun, Brigitte and Renalier, Florence and Theodoulidis, Nikos and Bard, Pierre-Yves},
  title     = {Exploring the model space and ranking a best class of models in surface-wave dispersion inversion application at European strong-motion sites},
  series = {Geophysics},
  volume    = {77},
  journal   = {Geophysics},
  number    = {3},
  publisher = {Society of Exploration Geophysicists},
  address   = {Tulsa},
  issn      = {0016-8033},
  doi       = {10.1190/GEO2011-0116.1},
  pages     = {B147 -- B166},
  year      = {2012},
  abstract  = {The inversion of surface-wave dispersion curve to derive shear-wave velocity profile is a very delicate process dealing with a nonunique problem, which is strongly dependent on the model space parameterization. When independent and reliable information is not available, the selection of most representative models within the ensemble produced. by the inversion is often difficult. We implemented a strategy in the inversion of dispersion curves able to investigate the influence of the parameterization of the model space and to select a "best" class of models. We analyzed surface-wave dispersion curves measured at 14 European strong..-motion sites within the NERIES EC-Project. We focused on the inversion task exploring the model space by means of four distinct pararneterization classes composed of layers progressively added over a half-space. The classes differ in the definition of the shear-wave velocity profile; we considered models with uniform velocity as well as models with increasing velocity with depth. At each site and for each model parameterization, we performed an extensive surface-wave inversion (200,100 models for five seeds) using the conditional neighborhood algorithm. We addressed the model evaluation following the corrected Akaike's information criterion (AlCc) that combines the concept of misfit to the number of degrees of freedom of the system. The misfit was computed as least-squares estimation between theoretical and observed dispersion curve. The model complexity was accounted in a penalty term by AlCc. By applying such inversion strategy on 14 strong-motion sites, we found that the best parameterization of the model space is mostly three to four layers over a half-space: where the shear-wave velocity of the uppermost layers can follow uniform or power-law dependence with depth. The shear-wave velocity profiles derived by inversion agree with shear-wave velocity profiles provided by borehole surveys at approximately 80\% of the sites.},
  language  = {en}
}
@article{DelavaudCottonAkkaretal.2012,
  author    = {Delavaud, Elise and Cotton, Fabrice and Akkar, Sinan and Scherbaum, Frank and Danciu, Laurentiu and Beauval, Celine and Drouet, Stephane and Douglas, John and Basili, Roberto and Sandikkaya, M. Abdullah and Segou, Margaret and Faccioli, Ezio and Theodoulidis, Nikos},
  title     = {Toward a ground-motion logic tree for probabilistic seismic hazard assessment in Europe},
  series = {Journal of seismology},
  volume    = {16},
  journal   = {Journal of seismology},
  number    = {3},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {1383-4649},
  doi       = {10.1007/s10950-012-9281-z},
  pages     = {451 -- 473},
  year      = {2012},
  abstract  = {The Seismic Hazard Harmonization in Europe (SHARE) project, which began in June 2009, aims at establishing new standards for probabilistic seismic hazard assessment in the Euro-Mediterranean region. In this context, a logic tree for ground-motion prediction in Europe has been constructed. Ground-motion prediction equations (GMPEs) and weights have been determined so that the logic tree captures epistemic uncertainty in ground-motion prediction for six different tectonic regimes in Europe. Here we present the strategy that we adopted to build such a logic tree. This strategy has the particularity of combining two complementary and independent approaches: expert judgment and data testing. A set of six experts was asked to weight pre-selected GMPEs while the ability of these GMPEs to predict available data was evaluated with the method of Scherbaum et al. (Bull Seismol Soc Am 99:3234-3247, 2009). Results of both approaches were taken into account to commonly select the smallest set of GMPEs to capture the uncertainty in ground-motion prediction in Europe. For stable continental regions, two models, both from eastern North America, have been selected for shields, and three GMPEs from active shallow crustal regions have been added for continental crust. For subduction zones, four models, all non-European, have been chosen. Finally, for active shallow crustal regions, we selected four models, each of them from a different host region but only two of them were kept for long periods. In most cases, a common agreement has been also reached for the weights. In case of divergence, a sensitivity analysis of the weights on the seismic hazard has been conducted, showing that once the GMPEs have been selected, the associated set of weights has a smaller influence on the hazard.},
  language  = {en}
}