We perform an analysis to understand what information may be hidden in partial, limited earthquake catalogues only containing mid-size and a few large seismic events (or even no one) about the largest possible ones using clustering properties of recorded events. We consider the local and global coefficients of variation, the scaling exponent of the Gutenberg–Richter law, the fractal dimension of epicentral series Df, the seismic rate and the number of events. We find that the largest earthquakes occur in locally Poissonian systems (local coefficient of variation of interevents LV ~1) with globally clustered dynamics (global coefficient of variation CV\ >\ 1). While local clustering in time is strongly dependent on the size of the catalogue, so that longer databases tend to be less regular and more Poissonian than shorter ones, the global coefficient seems to be a reliable parameter even in cases of rather limited available information, e.g., few thousand events (Zaccagnino et al., 2023a). We analyse regional seismicity in different tectonic settings getting analogous results, e.g., Southern California, Cascadia (Zaccagnino et al., 2022), Italian Apennines, New Zealand (Zaccagnino et al., 2023a), and Turkey (Zaccagnino et al., 2023b). The fractal dimension of spatial series is positively correlated with the seismic rate, CV and the maximum listed magnitude. Conversely, the b-value does not show any correlation with the principal observables except for the number of earthquakes. We explain this phenomenon considering the different sizes of mainshocks in various tectonic settings. We propose that the predictive power of clustering properties stems from the self-similar nature of slow dynamics producing the emergence of slips in complex systems such as the brittle crust. Prospectively, this approach can be of great interest, once tuned, to extrapolate the features of extreme, still unobserved events given a limited database. References Zaccagnino, D., Telesca, L., & Doglioni, C. (2022). Variable seismic responsiveness to stress perturbations along the shallow section of subduction zones: the role of different slip modes and implications for the stability of fault segments. Frontiers in Earth Science, 10, 989697. Zaccagnino, D., Telesca, L., & Doglioni, C. (2023). Global versus local clustering of seismicity: Implications with earthquake prediction. Chaos, Solitons & Fractals, 170, 113419. Zaccagnino, D., Telesca, L., Tan, O., & Doglioni, C. (2023). Clustering analysis of seismicity in the Anatolian region with implications for seismic hazard. Entropy, 25(6), 835.

Possible applications of self-similarity in earthquake clustering to seismic hazard / Zaccagnino, Davide; Telesca, Luciano; Doglioni, Carlo. - (2024). (Intervento presentato al convegno GNGTS 2024 tenutosi a Ferrara).

Possible applications of self-similarity in earthquake clustering to seismic hazard

Davide Zaccagnino
Primo
;
Carlo Doglioni
Ultimo
2024

Abstract

We perform an analysis to understand what information may be hidden in partial, limited earthquake catalogues only containing mid-size and a few large seismic events (or even no one) about the largest possible ones using clustering properties of recorded events. We consider the local and global coefficients of variation, the scaling exponent of the Gutenberg–Richter law, the fractal dimension of epicentral series Df, the seismic rate and the number of events. We find that the largest earthquakes occur in locally Poissonian systems (local coefficient of variation of interevents LV ~1) with globally clustered dynamics (global coefficient of variation CV\ >\ 1). While local clustering in time is strongly dependent on the size of the catalogue, so that longer databases tend to be less regular and more Poissonian than shorter ones, the global coefficient seems to be a reliable parameter even in cases of rather limited available information, e.g., few thousand events (Zaccagnino et al., 2023a). We analyse regional seismicity in different tectonic settings getting analogous results, e.g., Southern California, Cascadia (Zaccagnino et al., 2022), Italian Apennines, New Zealand (Zaccagnino et al., 2023a), and Turkey (Zaccagnino et al., 2023b). The fractal dimension of spatial series is positively correlated with the seismic rate, CV and the maximum listed magnitude. Conversely, the b-value does not show any correlation with the principal observables except for the number of earthquakes. We explain this phenomenon considering the different sizes of mainshocks in various tectonic settings. We propose that the predictive power of clustering properties stems from the self-similar nature of slow dynamics producing the emergence of slips in complex systems such as the brittle crust. Prospectively, this approach can be of great interest, once tuned, to extrapolate the features of extreme, still unobserved events given a limited database. References Zaccagnino, D., Telesca, L., & Doglioni, C. (2022). Variable seismic responsiveness to stress perturbations along the shallow section of subduction zones: the role of different slip modes and implications for the stability of fault segments. Frontiers in Earth Science, 10, 989697. Zaccagnino, D., Telesca, L., & Doglioni, C. (2023). Global versus local clustering of seismicity: Implications with earthquake prediction. Chaos, Solitons & Fractals, 170, 113419. Zaccagnino, D., Telesca, L., Tan, O., & Doglioni, C. (2023). Clustering analysis of seismicity in the Anatolian region with implications for seismic hazard. Entropy, 25(6), 835.
2024
GNGTS 2024
04 Pubblicazione in atti di convegno::04d Abstract in atti di convegno
Possible applications of self-similarity in earthquake clustering to seismic hazard / Zaccagnino, Davide; Telesca, Luciano; Doglioni, Carlo. - (2024). (Intervento presentato al convegno GNGTS 2024 tenutosi a Ferrara).
File allegati a questo prodotto
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1701172
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact