Spatiotemporal Analysis of the Background Seismicity Identified by Different Declustering Methods in Northern Algeria and Its Vicinity

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