Source parameters estimation of 2003 Bam earthquake Mw 6.5 using empirical Green’s function method, based on an evolutionary approach

• Published in: Journal of Earth System Science 2010-06, Vol.119 (3), p.383-396
• Main Authors: Nicknam, Ahmad, Abbasnia, Reza, Eslamian, Yasser, Bozorgnasab, Mohsen, Mosabbeb, Ehsan Adeli
• Format: Article
• Language: English
• Subjects: Algorithms; Depth perception; Earth and Environmental Science; Earth Sciences; Earth, ocean, space; Earthquake damage; Earthquakes; Empirical analysis; Exact sciences and technology; Genetic algorithms; Green's function; Green's functions; Ground motion; Ground stations; Historic buildings & sites; Historical buildings; Mathematical models; P waves; Parameter estimation; Parameter sensitivity; Parameters; Response spectra; Retrofitting; Seismic activity; Seismic wave velocities; Seismograms; Seismology; Sensitivity analysis; Shaking; Simulation; Space Exploration and Astronautics; Space Sciences (including Extraterrestrial Physics; Wave velocity
• ISSN: 0253-4126; 2347-4327; 0973-774X
• DOI: 10.1007/s12040-010-0018-5

We determine the source parameters for 2003 (Mw 6.5) Bam, Iran, earthquake using an empirical Green’s function summation approach to model ground motions recorded by two strong motion stations at approximately 45 km epicentral distance. We introduce a genetic algorithm technique to optimize the fit to observed elastic response spectra. The proposed genetic algorithm technique allows us to explore the sensitivity of the results to multiple source parameters, including hypocenter location, focal mechanism (Strike and Dip), P-wave velocity in depth, fault dimension and rupture and healing velocities. We simulated the three components of seismogram at a far station, Mohammad-Abad station, by means of an inversion solution technique and predicted seismograms at another far station, Abaragh, incorporating the estimated model parameters. More agreement of our synthesized seismograms with those of the observed data in comparison with the results of other investigators confirms the reliability of estimated seismological parameters and the applicability of our technique. A series of sensitivity analysis are performed for demonstrating the influence of individual model parameter variation on defined error value. Using the empirical Green’s function summation method, our inferred source parameters provide the basis for predicting main shock shaking and guiding retrofitting efforts at sites, for example, the historical buildings in Arge-Bam site which were damaged during the 2003 Bam earthquake and strong motion data is unavailable.