GNGTS 2017 - 36° Convegno Nazionale

GNGTS 2017 S essione 2.1 295 (Gardner and Knopoff, 1974; Uhrhammer, 1986), are considered for this purpose. In particular, a statistical method for detection of earthquake clusters, based on “nearest-neighbor distances” of events in space-time-energy domain, is applied (Baiesi and Paczuski 2004; Zaliapin et al. , 2008). The method allows for a robust data-driven identification of seismic clusters, and permits to disclose possible complex features in the internal structure of the identified clusters (Zaliapin and Ben-Zion, 2013). The application of the nearest-neighbor technique requires preliminary computation of the scaling parameters that characterize seismicity, specifically the b-value of the Gutenberg-Richter law (Gutenberg and Richter, 1954) and the fractal dimension of epicenters distribution (e.g. Grassberger, 1983). For this purpose we consider average robust estimates of the parameters the Unified Scaling Law for Earthquakes (USLE) in the study regions (Nekrasova et al. , 2011, 2016). Accordingly, a formal selection and comparative analysis of earthquake clusters is carried out for the most relevant earthquakes in Northeastern Italy, as reported in the bulletins compiled at the National Institute of Oceanography and Experimental Geophysics since 1977 (Peresan and Gentili, 2016; Gentili et al. , 2011). The analysis is then extended to consider earthquake sequences occurred in areas characterized by a different seismotectonic setting, such as the area struck by the recent Central Italy earthquakes. For this purpose we consider two databases of Italian seismicity: the historical catalog CPTI15 (Rovida et al. , 2016) and the instrumental catalog, composed by the catalog of Lolli and Gasperini (2006) and updated since 2005 using the data from the Italian Seismological Instrumental and parametric Data-basE (http://iside. rm.ingv.it/iside/) . The similarities and basic differences, between the clusters identified by the nearest-neighbor method and using other approaches, are investigated for the selected sequences, with special emphasis on seismicity of north-eastern Italy. Results from clusters identification turn out quite robust with respect to the time span and completeness level of the input catalog. Moreover, the study shows that the data-driven approach, based on the nearest-neighbor distances, can be satisfactorily applied to decompose the seismic catalog into background seismicity and individual sequences of earthquake clusters, also in areas characterized by moderate seismic activity. With these results acquired, some statistical features of seismic clusters are explored by different techniques, including quantitative measures of the complex interdependence of events forming clusters, with the aim to capture possible spatial patterns of earthquakes occurrence in Northeastern Italy. Acknowledgments We are grateful to I. Zaliapin for providing the code for nearest-neighbor analysis. The research presented in this paper benefited from funding provided by Protezione Civile della Regione Autonoma Friuli-Venezia Giulia. References Baiesi, M and M. Paczuski (2004). Scale-free networks of earthquakes and aftershocks. Phys. Rev. E, 69, 066106. Gardner, J. K., and L. Knopoff (1974), Is the sequence of earthquakes in Southern California, with aftershocks removed, Poissonian?, Bull. Seis. Soc. Am., 64(5), 1363–1367. Gentili, S., M. Sugan, L. Peruzza, D. Schorlemmer (2011). ������������� ������������ ���������� �� ��� ���� �� ����� Probabilistic completeness assessment of the past 30 years of seismic monitoring in northeastern Italy, Physics of the Earth and Planetary Interiors, V 186, Issues 1–2, Pages 81–96. Gentili S., Di Giovambattista R., Peresan A. (2017). Seismic quiescence preceding the 2016 central Italy earthquakes. Physics of the Earth and Planetary Interiors 272 (2017) 27–33 Grassberger P. (1983). Generalized dimensions of strange attractors. Phys Lett 97A: 227-230. Gutenberg B. and C.F. Richter (1954). Seismicity of the Earth, 2nd edn., (Princeton University Press, 1954, Princeton). Lolli, B., Gasperini, P. (2006). Comparing different models of aftershocks rate decay: The role of catalog incompleteness in the first times after main shock. Tectonophysics, 423, 43–59. Nekrasova A., V. Kossobokov, A. Peresan, A. Aoudia, G.F. Panza (2011). A Multiscale Application of the Unified Scaling Law for Earthquakes in the Central Mediterranean area and Alpine region. Pure and Applied Geophysics, Special Issue on “Advanced seismic hazard assessments”. Vol. 168 (1-2). DOI 10.1007/s00024-010-0163-4.