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The Quest for Rock Site Characterization and Reference Site Definition for the National Seismic Network of Greece

Session: Strong-Motion Data Processing and Dissemination: State-of-the-Art and Outlook [Poster]

Type: Poster

Date: 4/23/2021

Presentation Time: 11:30 AM Pacific

Description: 

The broadband seismic network of the National Observatory of Athens covers most mainland and island Greek territory with 50 broadband seismic stations. These are generally considered as rock, though without any in-situ site measurement of shear-wave velocity profiles or empirical seismic response estimation. Now, more than ever, ground-motion databases require more sophisticated, data-derived (rather than inferred by proxies) site metadata. Now, more than ever, the need for broadband sensor data, in addition to accelerometric data, is also becoming apparent, so as to better represent rock recordings – a site condition that is very much missing in international strong-motion databases to date. There are, hence, many good reasons now that render better site characterization of the Greek national seismic network’s stations imperative. Moreover, certain stations that were up to now considered as rock were recently shown by the authors to exhibit significant variability or atypical seismic response with respect to their generic classification. Hence, the question of reference-station investigation becomes crucial, and the fastest and most economic method to attain this is using the recordings themselves. We use the traditional empirical approach known as the horizontal-to-vertical spectral ratio with a novel twist, as well as a more recent approach using ground-motion model residuals, namely the systematic deviation of a site compared to the average class prediction. It is important to investigate how the response within what is classified a priori as rock stations may vary, or even exhibit directional effects. The results can aid in the quest for a more harmonized and data-driven site characterization throughout Greece, which will in turn feed into the national and European data platforms for strong-motion services, assisting with automatic procedures such as data and metadata quality assurance and outlier identification.

Presenting Author: Olga-Joan Ktenidou

Student Presenter: No

Authors