A regionally-adaptable ground-motion model for shallow crustal earthquakes in Europe

Abstract

Abstract To complement the new European Strong-Motion dataset and the ongoing efforts to update the seismic hazard and risk assessment of Europe and Mediterranean regions, we propose a new regionally adaptable ground-motion model (GMM). We present here the GMM capable of predicting the 5% damped RotD 50 of PGA , PGV , and $$ SA\left( {T = 0.01 - 8\,{\text{s}}} \right) $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>S</mml:mi><mml:mi>A</mml:mi><mml:mfenced><mml:mrow><mml:mi>T</mml:mi><mml:mo>=</mml:mo><mml:mn>0.01</mml:mn><mml:mo>-</mml:mo><mml:mn>8</mml:mn><mml:mspace/><mml:mtext>s</mml:mtext></mml:mrow></mml:mfenced></mml:mrow></mml:math> from shallow crustal earthquakes of $$ 3 \le M_{W} \le 7.4 $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>3</mml:mn><mml:mo>≤</mml:mo><mml:msub><mml:mi>M</mml:mi><mml:mi>W</mml:mi></mml:msub><mml:mo>≤</mml:mo><mml:mn>7.4</mml:mn></mml:mrow></mml:math> occurring $$ 0 &lt; R_{JB} \le 545\,{\text{km}} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>0</mml:mn><mml:mo>&lt;</mml:mo><mml:msub><mml:mi>R</mml:mi><mml:mrow><mml:mi>JB</mml:mi></mml:mrow></mml:msub><mml:mo>≤</mml:mo><mml:mn>545</mml:mn><mml:mspace/><mml:mtext>km</mml:mtext></mml:mrow></mml:math> away from sites with $$ 90 \le V_{s30} \le 3000\,{\text{m}}\,{\text{s}}^{ - 1} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>90</mml:mn><mml:mo>≤</mml:mo><mml:msub><mml:mi>V</mml:mi><mml:mrow><mml:mi>s</mml:mi><mml:mn>30</mml:mn></mml:mrow></mml:msub><mml:mo>≤</mml:mo><mml:mn>3000</mml:mn><mml:mspace/><mml:mtext>m</mml:mtext><mml:mspace/><mml:msup><mml:mrow><mml:mtext>s</mml:mtext></mml:mrow><mml:mrow><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math> or $$ 0.001 \le slope \le 1\,{\text{m}}\,{\text{m}}^{ - 1} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>0.001</mml:mn><mml:mo>≤</mml:mo><mml:mi>s</mml:mi><mml:mi>l</mml:mi><mml:mi>o</mml:mi><mml:mi>p</mml:mi><mml:mi>e</mml:mi><mml:mo>≤</mml:mo><mml:mn>1</mml:mn><mml:mspace/><mml:mtext>m</mml:mtext><mml:mspace/><mml:msup><mml:mrow><mml:mtext>m</mml:mtext></mml:mrow><mml:mrow><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math> . The extended applicability derived from thousands of new recordings, however, comes with an apparent increase in the aleatory variability ( σ ). Firstly, anticipating contaminations and peculiarities in the dataset, we employed robust mixed-effect regressions to down weigh only, and not eliminate entirely, the influence of outliers on the GMM median and σ . Secondly, we regionalised the attenuating path and localised the earthquake sources using the most recent models, to quantify region-specific anelastic attenuation and locality-specific earthquake characteristics as random-effects, respectively. Thirdly, using the mixed-effect variance–covariance structure, the GMM can be adapted to new regions, localities, and sites with specific datasets. Consequently, the σ is curtailed to a 7% increase at T &lt; 0.3 s, and a substantial 15% decrease at T ≥ 0.3 s, compared to the RESORCE based partially non-ergodic GMM. We provide the 46 attenuating region-, 56 earthquake localities-, and 1829 site-specific adjustments, demonstrate their usage, and present their robustness through a 10-fold cross-validation exercise.

Topics & Concepts