Statistical and geostatistical approaches to study spatiotemporal uncertainties in earthquake catalog databases

Abstract

Lack of data in time and location domain is a main problem in statistical seismology. Therefore, several methods have been developed to make synthetic catalogs to compensate these uncertainties. The approaches introduced in this paper try to decrease these uncertainties. A statistical tool has been determined to study the lack of data in time domain and revise a magnitude-frequency relationship in one of the very high-seismic regions in the world, northwest of Iran (44.00 to 48.00 E and 35.60 to 40.00 N). A geostatistical simulation method has also been utilized to reduce the uncertainties in the spatial domain. Variogram tool has been introduced as a spatial tool to assign a spatial regression among data in various directions. A geostatistical simulation produced a representative, synthetic catalog with 10,707 events to reduce spatial uncertainties (the number of data in the earthquake catalogs was 307 events). The synthetic database was classified by a geographical information system (GIS) based on simulated magnitudes to reveal the underlying seismicity patterns. Although some regions with high seismicity correspond to known faults, as far as seismic patterns are concerned, the new method could highlight locations of interest that have not been previously determined. It also suggests some previously unrecognized lineation and clusters in likely future strain release.