A spatial cross‐correlation model of spectral accelerations at multiple periods

SUMMARY Many seismic loss problems (such as disruption of distributed infrastructure and losses to portfolios of structures) are dependent upon the regional distribution of ground-motion intensity, rather than intensity at only a single site. Quantifying ground-motion over a spatially-distributed region therefore requires information on the correlation between the ground-motion intensities at different sites during a single event. The focus of the present study is to assess the spatial correlation between ground-motion spectral accelerations at different periods. Ground motions from eight well-recorded earthquakes were used to study the spatial correlations. On the basis of obtained empirical correlation estimates, we propose a geostatistics-based method to formulate a predictive model that is suitable for simulation of spectral accelerations at multiple sites and multiple periods, in the case of crustal earthquakes in active seismic regions. While the calibration of this model and investigation of its implications were somewhat complex, the model itself is very simple to use for making correlation predictions. A user only needs to evaluate a simple equation relying on three sets of coefficients provided here to compute a correlation coefficient for spectral values at two periods and at a specified separation distance. These results may then be used in evaluating the seismic risk of portfolios of structures with differing fundamental periods. Copyright © 2012 John Wiley & Sons, Ltd.

[1]  K. Campbell Campbell-Bozorgnia NGA Ground Motion Relations for the Geometric Mean Horizontal Component of Peak and Spectral Ground Motion Parameters , 2007 .

[2]  M. Goulard,et al.  Linear coregionalization model: Tools for estimation and choice of cross-variogram matrix , 1992 .

[3]  Alan E. Gelfand,et al.  Multivariate Spatial Modeling for Geostatistical Data Using Convolved Covariance Functions , 2007 .

[4]  Nicolas Luco,et al.  Effects of different sources of uncertainty and correlation on earthquake-generated losses , 2007 .

[5]  Bradley P. Carlin,et al.  Multivariate spatial modeling , 2003 .

[6]  Benjamin Edwards,et al.  Development of a Response Spectral Ground‐Motion Prediction Equation (GMPE) for Seismic‐Hazard Analysis from Empirical Fourier Spectral and Duration Models , 2015 .

[7]  Andre G. Journel,et al.  Markov Models for Cross-Covariances , 1999 .

[8]  J. Baker,et al.  Correlation of Spectral Acceleration Values from NGA Ground Motion Models , 2008 .

[9]  Roxane Foulser-Piggott,et al.  A predictive model for Arias intensity at multiple sites and consideration of spatial correlations , 2012 .

[10]  N. Abrahamson,et al.  Summary of the Abrahamson & Silva NGA Ground-Motion Relations , 2008 .

[11]  Katsuichiro Goda,et al.  Interevent Variability of Spatial Correlation of Peak Ground Motions and Response Spectra , 2011 .

[12]  David M. Boore,et al.  Estimated Ground Motion From the 1994 Northridge, California, Earthquake at the Site of the Interstate 10 and La Cienega Boulevard Bridge Collapse, West Los Angeles, California , 2003 .

[13]  Dale O. Stahl,et al.  Rule Learning in Symmetric Normal-Form Games: Theory and Evidence , 2000, Games Econ. Behav..

[14]  Simona Esposito,et al.  PGA and PGV Spatial Correlation Models Based on European Multievent Datasets , 2011 .

[15]  BrianS-J. Chiou,et al.  An NGA Model for the Average Horizontal Component of Peak Ground Motion and Response Spectra , 2008 .

[16]  J. Baker,et al.  Statistical Tests of the Joint Distribution of Spectral Acceleration Values , 2008 .

[17]  Hans Wackernagel,et al.  Multivariate Geostatistics: An Introduction with Applications , 1996 .

[18]  H. Hong,et al.  Spatial correlation of peak ground motions and response spectra , 2008 .

[19]  G. Atkinson,et al.  Ground-Motion Prediction Equations for the Average Horizontal Component of PGA, PGV, and 5%-Damped PSA at Spectral Periods between 0.01 s and 10.0 s , 2008 .

[20]  J. Baker,et al.  Correlation model for spatially distributed ground‐motion intensities , 2009 .

[21]  R. Olea Geostatistics for Natural Resources Evaluation By Pierre Goovaerts, Oxford University Press, Applied Geostatistics Series, 1997, 483 p., hardcover, $65 (U.S.), ISBN 0-19-511538-4 , 1999 .

[22]  Tsuyoshi Takada,et al.  Macrospatial Correlation Model of Seismic Ground Motions , 2005 .

[23]  Peter Jaeckel,et al.  Monte Carlo methods in finance , 2002 .