Effects of different empirical ground motion models on seismic hazard maps for North Iceland

• Published in: Soil Dynamics and Earthquake Engineering
• Main Authors: Kowsari, Milad, Halldorsson, Benedikt, Snæbjörnsson, Jónas, Jonsson, Sigurjon
• Other Authors: Crustal Deformation and InSAR Group, Earth Science and Engineering Program, Physical Science and Engineering (PSE) Division, Faculty of Civil and Environmental Engineering, School of Engineering and Natural Sciences & Earthquake Engineering Research Centre, University of Iceland, Reykjavik, Iceland, Division of Processing and Research, Icelandic Meteorological Office, Reykjavik, Iceland, School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Elsevier BV 2021
• Subjects: Iceland
• Online Access: http://hdl.handle.net/10754/669723; https://doi.org/10.1016/j.soildyn.2020.106513

This study builds on previous site-specific hazard studies for North Iceland, specifically regarding delineation of seismic sources and seismicity parameters. Using a Monte Carlo approach to generate synthetic earthquake catalogues for North Iceland, and multiple ground motion models (GMMs) that have been proposed and used for probabilistic seismic hazard analysis (PSHA) in Iceland in the past, the variability of the resulting hazard estimates is presented in a map-form. The variability in the hazard estimates is quite large, which is a direct result of the inconsistency in the GMMs used in previous studies. We show how this is caused by the inability of these models to capture the characteristic amplitude attenuation of Icelandic earthquake ground motion with distance, thus casting doubt on the validity of the resulting PSHA of past studies. In contrast, we re-evaluated the variability of PSHA for North Iceland based on new empirical Bayesian GMMs that not only satisfy all the conditions required for use in PSHA, but also fully capture the characteristics of the existing Icelandic ground motion dataset and in addition contain elements that account for the saturation of near-fault peak ground motions at large magnitudes. The results quantify how the variability in the GMMs, contribute to the range of spatial distribution of PSHA amplitudes and uncertainties. The results show that the confidence in the PSHA values is significantly increased using the new models vs. the older ones. The confidence of the PSHA values is quantified through the coefficient of variation. The confidence is shown to be largest over distance ranges where data is most abundant. On the other hand, the confidence decreases considerably at near-fault and far-field distances, primarily because of lack of data for those distances. The findings highlight the importance of using appropriate GMMs for PSHA in Iceland and give a spatial sense of the relative levels of confidence of hazard estimates. They moreover highlight the need for a revision of ...