Prediction of response spectra via real-time earthquake measurements

The development and implementation of an earthquake early warning system (EEWS), both in regional or on-site configurations can
help to mitigate the losses due to the occurrence of moderate-to-large earthquakes in densely populated and/or industrialized areas. The
capability of an EEWS to provide real-time estimates of source parameters (location and magnitude) can be used to take some
countermeasures during the earthquake occurrence and before the arriving of the most destructive waves at the site of interest. However,
some critical issues are peculiar of EEWS and need further investigation: (1) the uncertainties on earthquake magnitude and location
estimates based on the measurements of some observed quantities in the very early portion of the recorded signals; (2) the selection of the
most appropriate parameter to be used to predict the ground motion amplitude both in near-and far-source ranges; (3) the use of the
estimates provided by the EEWS for structural engineering and risk mitigation applications.
In the present study, the issues above are discussed using the Campania–Lucania region (Southern Apennines) in Italy, as test-site
area. In this region a prototype system for earthquake early warning, and more generally for seismic alert management, is under
development. The system is based on a dense, wide dynamic accelerometric network deployed in the area where the moderate-to-large
earthquake causative fault systems are located.
The uncertainty analysis is performed through a real-time probabilistic seismic hazard analysis by using two different approaches. The
first is the Bayesian approach that implicitly integrate both the time evolving estimate of earthquake parameters, the probability density
functions and the variability of ground motion propagation providing the most complete information. The second is a classical point
estimate approach which does not account for the probability density function of the magnitude and only uses the average of the
estimates performed at each seismic station.
Both the approaches are applied to two main towns located in the area of interest, Napoli and Avellino, for which a missed and false
alarm analysis is presented by means of a scenario earthquake: an M 7.0 seismic event located at the centre of the seismic network.
Concerning the ground motion prediction, attention is focused on the response spectra as the most appropriate function to
characterize the ground motion for earthquake engineering applications of EEWS.

[1] Heaton TH. A model for a seismic computerized alert network.
Science 1985;228:987–90.
[2] Kanamori H. Real-time seismology and earthquake damage mitiga-
tion. Annu Rev Earth Planet Sci 2004;33:5.1–5.20.
[3] Allen RM, Kanamori H. The potential for earthquake early warning
in Southern California. Science 2003;300:786–9.
[4] Wu YM, Zhao L. Magnitude estimation using the first three seconds
p-wave amplitude in earthquake early warning. Geophys Res Lett
2006;33:L16312.
[5] Zollo A, Lancieri M, Nielsen S. Earthquake magnitude estimation
from peak amplitudes of very early seismic signals on strong motion
records. Geophys Res Lett 2006;33:L23312.
[6] Horiuchi S, Negishi H, Abe K, Kanimura A, Fujinawa Y. An
automatic processing system for broadcasting earthquake alarms.
Bull Seism Soc Am 2005;95:708–18.
[7] Rydelek P, Pujol J. Real-time seismic warning with a 2-station
subarray. Bull Seism Soc Am 2004;94:1546–50.
[8] Satriano C, Lomax A, Zollo A. Real-time evolutionary location for
seismic early warning. Bull Seism Soc Am 2006 Submitted for
publication.
[9] Wald DJ, Quitoriano V, Heaton TH, Kanamori H, Scrivner CW,
Worden CB. TriNet ShakeMaps: rapid generation of instrumental
ground motion and intensity maps for earthquakes in southern
California. Earthquake Spectra 1999;15:537–55.
[10] Allen RM. The ElarmS earthquake warning methodology and
application across California. In: Pecce M, Manfredi G, Zollo A,
editors. In the many facets of seismic risk. Proceedings of the
workshop on multidisciplinary approach to seismic risk problem,
Sant’Angelo dei Lombardi, September 22, 2003. Universita` degli
Studi di Napoli ‘‘Federico II’’–CRdC-AMRA, 2004.
[11] Dreger D, Kaverina A. Seismic remote sensing for the earthquake
source process and near-source strong shaking: a case study of the
October 16, 1999 Hector mine earthquake. Geophys Res Lett
2000;27:1941–4.
[12] Iervolino I, Convertito V, Giorgio M, Manfredi G, Zollo A. Real-
time risk analysis in hybrid early warning systems. J Earthquake Eng
2006;10(6):867–85.
[13] Iervolino I, Giorgio M, Manfredi G. Expected loss-based alarm
threshold set for earthquake early warning system. Earthquake Eng
Struct Dyn 2007;36(9):1151–68.
[14] Cornell CA. Engineering seismic risk analysis. Bull Seism Soc Am
1968;58:1583–606.
[15] Weber E, Iannaccone G, Zollo A, Bobbio A, Cantore L, Corciulo M,
et al. Development and testing of an advanced monitoring
infrastructure (ISNet) for seismic early-warning applications in the
Campania region of southern Italy. In: Gasparini et al., editors.
Earthquake early warning systems. Berlin: Springer; 2007
[16] Reiter L. Earthquake hazard analysis—issues and insights. New
York: Columbia University Press; 1990. 254pp.
[17] Akkar S, Bommer JJ. Prediction of elastic displacement response
spectra in Europe and the Middle East. Earthquake Eng Struct Dyn
2007;36(10):1275–301.
[18] Ambraseys NN, Douglas J, Sarma SK, Smit P. Equations for the
estimation of strong ground motions from shallow crustal earth-
quakes using data from Europe and the Middle East: horizontal peak
ground acceleration and spectral acceleration. Bull Earthquake Eng
2005;3(1):1–53.
[19] Sabetta F, Pugliese A. Estimation of response spectra and simulation
of nonstationarity earthquake ground motion. Bull Seism Soc Am
1996;86:337–52.
[20] Pate` -Cornell ME. Warning systems in risk management. Risk
Manage 1986;6:223–34.
[21] CEN, European Committee for Standardisation TC250/SC8/ [2003]
Eurocode 8: design provisions for earthquake resistance of structures,
Part 1.1: general rules, seismic actions and rules for buildings,
PrEN1998-1.
[22] Calvi GM, Stucchi M, Mappe interattive della pericolosita` sismica.
Distributed through the Internet 2006: URL: /http://esse1.mi.ingv.itS.
[23] Wessel P, Smith WHF. Free software helps map and display data.
EOS Trans Am Geophys Union 1991;72(441):445–6.