Research Topic 6 (RT6): A South American Strong Motion Database and Selection of ground motion prediction equations (GMPEs) for seismic hazard analysis in South America

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• Luisa Fernanda Castillo - Colombian Geological Survey, Bogotá, Colombia
• Cristina Dimaté – Universidad Nacional de Colombia, Bogotá, Colombia
• Stéphane Drouet – Observatório Nacional, Rio de Janeiro, Brazil (Coordinator)
• Gonzalo Antonio Fernandez Marañon – Observatorio San Calixto, La Paz, Bolivia
• Gonzalo Montalva – Universidad de Concepción, Concepción, Chile
• Nicolas Bastias – Universidad de Concepción, Concepción, Chile
• Cecilio Morales – Fundación Venezolana de Investigaciones Sismológicas-Funvisis, Caracas, Venezuela
• Marlon Pirchiner, IAG/USP, São Paulo, Brazil
• Juan Carlos Singaucho Armas – Instituto Geofísico/EPN, Quito, Ecuador
• Graeme Weatherill GEM Hazard Team, GEM Foundation, Pavia, Italy

Strong motion recording networks are in operation across South America and the data they record can provide fundamental insight into the earthquake process and the associated attenuation of strong shaking. Unfortunately the data are highly fragmented with records processed using different standards and techniques, critical metadata regarding the station, sensors and events often missing, and access to the waveforms themselves frequently restricted. Faced with this challenge, a consortium of scientists from Brazil, Bolivia, Chile, Colombia, Ecuador and Venezuela constructed the first continental-scale South American strong motion database [see figures below].

About 350 events recorded since 1985 have been selected to feed the database: 64 are crustal events, 76 are inslab events (associated with the Bennioff zones of subducted plates), 142 are related to the interface between the oceanic and continental plates (subduction of the Nazca or Caribbean plates), 69 are located in the stable craton. Earthquake magnitudes range between 2.0 and 8.8. Most of them are Mw but some are Ml or MD. About 45% of the earthquakes included in the database have Mw magnitudes greater than 5 and more than 40% are in the range between 4 and 5 Mw. Events with magnitude lower than 4 are located mainly in the Brazilian craton region. The attributes describing the characteristics of the strong motion record (earthquake, site and record itself) are collected and organized following the data model shown below (Weatherhill, 2014). The model departs from the PEER NGA-East Database (Goulet et al. 2014) scheme and it has been adapted to local databases conditions.

Earthquakes in the Strong Motion Database. Colours indicate the tectonic context of the event location.	Seismological or accelerographic stations providing data to the Strong Motion Database

About 2100 horizontal and vertical component records were collected and processed. The adopted processing scheme is based on advice from S. Akkar (Bogazici University, Istanbul, Turkey) following the Boore et al. (2012) procedure and was modified through a series of technical workshops to debate issues in strong motion recording in the region.

The purpose of our time series treatment procedure is to remove noise, to correct for instrument response and to select reliable time and frequency windows. We expect that they will be representative of the true ground motion and will provide the most basic information required for selection of ground motion prediction equations. Processing of the records is performed in two phases. In the first phase, we correct the waveforms for instrument response, identify trigger and spurious spikes and cut the P, S and noise windows.

In the second phase, we remove the mean, tape the ends of the signal window with a time length of 5% of the total signal duration and pad with zeroes -up to the next power of 2- the extremes of the record. We then apply a Fourier transform on the noise and S-wave windows and compute the signal-to-noise ratio. Frequencies with a signal-to-noise ratio greater than 3 define the usable frequency band. To remove frequencies out of this band we apply a second order Butterworth, acausal bandpass filter. The processing is applied in the same way to both velocimetric and accelerometric records. Finally we compute acceleration, velocity and displacement by numerical integration and derivation of velocity, or by double integration of acceleration.

Iquique (2014-Chile) earthquake. Mw=8.1, Station TO3A, hypocentral distance = 109 km

The harmonized database of earthquake recordings (see Figure above), created within this topic, which covers the major tectonic regions found in South America (subduction interface, subduction in-slab, active shallow crustal and stable continental) was used for the selection of suitable ground motion prediction equations for application in the different tectonic regions of South America, from the OpenQuake-engine’s extensive library of GMPEs (see table below).
*Ground Motion Prediction Equations included within version 1.0.0 of the SARA hazard model*

The database will, in future, provide the opportunity for scientists in the region to refine future seismic hazard models for the region by calibrating the ground motion models to local tectonic conditions in South America. The information being revealed within this work can provide an important basis for strong motion modelling in South America, allowing the possibility of creating locally calibrated GMPEs in future.

• Abrahamson N., N. Gregor and K. Addo (2015). BC Hydro Ground Motion Prediction Equations For Subduction Earthquakes Earthquake Spectra, in press.
• Akkar S., M. A. Sandikkaya, and J. J. Bommer (2014). Empirical Ground-Motion Models for Point- and Extended- Source Crustal Earthquake Scenarios in Europe and the Middle East, Bulletin of Earthquake Engineering (2014), 12(1): 359 - 387
• Atkinson Gail M. and David M. Boore (2006). Earthquake Ground-Motion Prediction Equations for Eastern North America; Bulletin of the Seismological Society of America, Volume 96, No. 6, pages 2181-2205
• Bindi D., M. Massa, L.Luzi, G. Ameri, F. Pacor, R.Puglia and P. Augliera (2014). Pan-European ground motion prediction equations for the average horizontal component of PGA, PGV and 5 %-damped PSA at spectral periods of up to 3.0 s using the RESORCE dataset, Bulletin of Earthquake Engineering, 12(1), 391 - 340
• Boore David M., Jonathan P. Stewart, Emel Seyhan and Gail Atkinson (2014). NGA-West2 Equations for Predicting PGA, PGV, nd 5 % Damped PGA for Shallow Crustal Earthquakes; Earthquake Spectra, Volume 30, No. 3, pages 1057 - 1085.
• Boore, D.M., Azari Sisi, A. and Akkar, S. (2012). Using Pad-Stripped Acausally Filtered Strong-Motion Data, BSSA 102(2), 751-760.
• Drouet S. (2015). Unpublished for Brazil based on the method described in Douet & Cotton (2015)
• Drouet, S., Cotton, F. (2015): Regional Stochastic GMPEs in Low‐Seismicity Areas: Scaling and Aleatory Variability Analysis—Application to the French Alps. - Bulletin of the Seismological Society of America, 105, 4, pp. 1883—1902. DOI: http://doi.org/10.1785/0120140240
• Goulet, C.A., Kishida, T., Ancheta, T.D., et al.(2014). PEER 2014/17 - PEER NGA-East Database Report.
• Montalva et al. (2015). Unpublished, adaptation of the Abrahamson et al. (2015) BC Hydro GMPE, calibrated to Chilean strong motion data.
• Tavakoli B. and S. Pezeshk in 2005 and published as “Empirical-Stochastic Ground-Motion Prediction for Eastern North America” (2005, Bull. Seism. Soc. Am., Volume 95, No. 6, pages 2283-2296).
• Weatherill, G. A. (2014) OpenQuake Ground Motion Toolkit - User Guide. Global EarthquakeModel (GEM). Technical Report
• Zhao, J. X., Zhang, J., Asano, A., Ohno, Y., Oouchi, T., Takahashi, T., Ogawa, H., Irikura, K., Thio, H. K., Somerville, P. G., Fukushima, Y., & Fukushima, Y. (2006). Attenuation relations of strong ground motion in Japan using site classification based on predominant period. Bulletin of the Seismological Society of America, 96(3), 898–913.

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