Articolo in rivista, 2023, ENG, 10.3390/axioms12030237

Spatiotemporal analysis of the background seismicity identified by different declustering methods in northern Algeria and its vicinity

A. Benali, A. Jalilian, A. Peresan, E. Varini, and S. Idrissou

CRAAG, Algiers, Algeria; Razi University, Kermanshah, Iran OGS, Udine, Italy CNR IMATI, Milano, Italy Université Abderrahmane Mira, Béjaia, Algeria

The main purpose of this paper was to, for the first time, analyse the spatiotemporal features of the background seismicity of Northern Algeria and its vicinity, as identified by different declustering methods (specifically: the Gardner and Knopoff, Gruenthal, Uhrhammer, Reasenberg, Nearest Neighbour, and Stochastic Declustering methods). Each declustering method identifies a different declustered catalogue, namely a different subset of the earthquake catalogue that represents the background seismicity, which is usually expected to be a realisation of a homogeneous Poisson process over time, though not necessarily in space. In this study, a statistical analysis was performed to assess whether the background seismicity identified by each declustering method has the spatiotemporal properties typical of such a Poisson process. The main statistical tools of the analysis were the coefficient of variation, the Allan factor, the Markov-modulated Poisson process (also named switched Poisson process with multiple states), the Morisita index, and the L-function. The results obtained for Northern Algeria showed that, in all cases, temporal correlation and spatial clustering were reduced, but not totally eliminated in the declustered catalogues, especially at long time scales. We found that the Stochastic Declustering and Gruenthal methods were the most successful methods in reducing time correlation. For each declustered catalogue, the switched Poisson process with multiple states outperformed the uniform Poisson model, and it was selected as the best model to describe the background seismicity in time. Moreover, for all declustered catalogues, the spatially inhomogeneous Poisson process did not fit properly the spatial distribution of earthquake epicentres. Hence, the assumption of stationary and homogeneous Poisson process, widely used in seismic hazard assessment, was not met by the investigated catalogue, independently from the adopted declustering method. Accounting for the spatiotemporal features of the background seismicity identified in this study is, therefore, a key element towards effective seismic hazard assessment and earthquake forecasting in Algeria and the surrounding area.

Axioms 12 (3), pp. 237–?

Keywords

Statistical seismology, Earthquake declustering, Markov-modulated Poisson process, Allan factor, Morisita index, L-function

CNR authors

Varini Elisa

CNR institutes

IMATI – Istituto di matematica applicata e tecnologie informatiche "Enrico Magenes"

ID: 478552

Year: 2023

Type: Articolo in rivista

Creation: 2023-02-28 11:44:07.000

Last update: 2023-05-30 14:15:28.000

CNR authors

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:478552

DOI: 10.3390/axioms12030237

ISI Web of Science (WOS): 000957395200001

Scopus: 2-s2.0-85151129177