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EN
In a recent study, Papadakis et al. (Physica A 456: 135–144, 2016) investigate seismicity in Greece, using the non-extensive statistical physics formalism. Moreover, these authors examine the spatial distribution of the non-extensive parameter qM and show that for shallow seismicity, increase of qM coincides with strong events. However, their study also reveals low qM values along the North Aegean Trough, despite the presence of strong events during 1976–2009. Consequently, the present study further examines the temporal behaviour of parameters qM and A, to reveal their relation with the evolution of the earthquake sequence. Through temporal examination of these parameters, we aim to show that the seismogenic system of the North Aegean Trough presents high degree of interactions after strong earthquakes during the studied period. Our findings indicate that increase of qM signifies the existence of long-range correlations. If its value does not significantly decrease after a strong earthquake (i.e. M ≥ 5) then the studied area has not reached the state of equilibrium.
2
Content available remote More statistical tools for maximum possible earthquake magnitude estimation
EN
In this paper, we introduce additional statistical tools for estimating the maximum regional earthquake magnitude, mmax, as complement to those already introduced by Kijko and Singh (Acta Geophys. 59(4):674– 700, 2011). Four new methods are introduced and investigated, with regard to their applicability and performance. We present an example of application and a comparison that includes the methods introduced earlier by the previous authors. A condition for the existence of the Tate– Pisarenko estimate and a proof of the asymptotic equivalence of the Tate–Pisarenko and Kijko–Sellevoll estimates are presented in the two appendices
EN
The Iranian Plateau does not appear to be a single crustal block, but an assemblage of zones comprising the Alborz–Azerbaijan, Zagros, Kopeh–Dagh, Makran, and Central and East Iran. The Gumbel’s III asymptotic distribution method (GIII) and maximum magnitude expected by Kijko–Sellevoll method is applied in order to check the potentiality of the each seismogenic zone in the Iranian Plateau for the future occurrence of maximum magnitude (Mmax). For this purpose, a homogeneous and complete seismicity database of the instrumental period during 1900- 2012 is used in 29 seismogenic zones of the examined region. The spatial mapping of hazard parameters (upper bound magnitude (ω), most probable earthquake magnitude in next 100 years (M100) and maximum magnitude expected by maximum magnitude estimated by Kijko–Sellevoll method ( max K S M − ) reveals that Central and East Iran, Alborz and Azerbaijan, Kopeh–Dagh and SE Zagros are a dangerous place for the next occurrence of a large earthquake.
4
Content available remote Statistical tools for maximum possible earthquake magnitude estimation
EN
Several procedures for the statistical estimation of the regioncharacteristic maximum possible earthquake magnitude, mmax , are currently available. This paper aims to introduce and compare the 12 existing procedures. For each of the procedures given, there are notes on its origin, assumptions made in its derivation, condition for validity, weak and strong points, etc. The applicability of each particular procedure is determined by the assumptions of the model and/or the available information on seismicity of the area.
EN
The variations of spring water radon concentration and meteorological parameters were analysed in relation to the seismic activities in Garhwal Himalaya, India. The radon anomalies were classified on the basis of statistical treatment of the daily observations. The precise measurements of water discharge rate from the spring have been made along with radon measurements for earthquake precursory study. The earthquakes with epicentral distances less than 150 km were considered by an empirical relationship. Pre-, co-, and post-seismic changes in the radon concentration were taken carefully into account in the empirical relationship to establish this behaviour as a potential earthquake precursor. The empirical relationship has been validated by the radon data recorded from the spring waters. The magnitudes of the earthquakes were estimated by using the empirical relationship by introducing computed correlation coefficient of radon and meteorological parameters. The calculated magnitude of some local earthquakes matches exactly with the magnitude recorded by the laboratory seismograph. The possible mechanisms that may cause a radon anomaly are also discussed.
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