GNGTS 2013
Sessione 1.1
The 2012 Emilia sequence: application of an automatic procedure to
determine moment magnitude
A. Gallo1,2, G. Costa2, P. Suhadolc2
AREA Science Park – Trieste, Italy
Seismological Research and Monitoring Group, Department of Mathematics and Geosciences, University of Trieste, Italy
1
2
On May 2012 a seismic sequence took place in the Emilia Romagna region, northern
Italy. The two main-shocks on May 20 and May 29 with ML=5.9 and ML=5.8, respectively,
were followed by several relevant aftershocks with ML>4. Using a procedure implemented
by the SeisRaM group of the Department of Mathematics and Geosciences of the University
of Trieste, the seismic moment is estimated, as well as the moment magnitude and the corner
frequency of the events recorded by strong motion instruments. The goals of this procedure
are: the rapid determination of earthquake parameters and an interface to obtain a fast and
reliable communication of the parameters related to the seismic events to the Civil Defense. We
analyze a strong-motion dataset consisting of high-quality records (among which the two main
events and several aftershocks with magnitudes ranging from 3 to 5) obtained by the National
Strong Motion Network (RAN).
The RAN is distributed on the Italian territory to record earthquakes of medium and high
intensity. It is managed by the Seismic Monitoring Service of the Territory within the Seismic
and Volcanic Risks Office of the Civil Protection Department (DPC) in Rome (Gorini et al.,
2010; Zambonelli et al., 2011). RAN has more than 500 digital stations equipped with a GSM
modem or GPRS, connected to the RAN data capture Centre of Rome (last update: 20 May
2011). The Antelope® software (BRTT, Boulder) that collects and archives data, and the SeisRaM
procedure to determine moment magnitude and all seismic source parameters in near real-time
(Gallo et al., 2013), is now installed also at DPC for managing and analyzing recorded data.
The SeisRaM procedure is extensively described in Gallo et al. (2013), but we recall here
only the main aspects. Using spectral analysis, the seismic source parameters are calculated
following Andrews (1986). The source model used is a simple ω2 model proposed by Brune
(1970, 1971). For the attenuation we use the Q frequency-depend attenuation factor (Console
and Rovelli, 1981) and we assume a body-waves theory for the geometrical spreading. From
the corrected amplitude spectra the corner frequency also the Brune low-frequency spectrum amplitude and the seismic moment are computed. Finally, the moment magnitude is
determined according to the Kanamori (1979) formula. The procedure starts by taking the
event location, Richter magnitude (Richter, 1935), P and S phases, signals and instrumental
response from Antelope databases. We remove the average, trend, spike and instrumental response. We limit ourselves to events with epicentral distances up to the maximum of 70 km,
in order to respect the assumption of the spherical geometrical decay. It is essential to determine the frequency range over which the observed spectral levels are significantly higher
than noise. We select band pass corner frequencies using SNR. The minimum frequency
corresponding to the first value for which SNR > 2.5, the maximum frequency the last value
for which SNR > 5. Following Ottemoller and Havskov (2003), in the selected frequency
window the SNR average must be everywhere larger than 1.5. This additional requirement
that the average ratio between signal and noise spectral amplitude in the selected frequency
range be above a threshold value, allows to choose the final frequency window and to avoid
processing only noise. We apply a Butterworth band pass filter, and then we obtain accelerations, velocities and displacements from the derivative or the integral of the signal. We
apply the Fast Fourier Transform (FFT) to obtain the signal spectra. Then we correct them
for geometrical spreading and intrinsic attenuation to retrieve the source spectra. At the end
we calculate seismic moment and moment magnitude and strong motion parameters like as
PGA, PGV Arial and Housner intensity, and store these results in a database table. A report
is also generated within 10 min from the event.
59
Sessione 1.1
GNGTS 2013
The Emilia 2012 seismic sequence was a great opportunity to validate our procedure. In
Tab. 1 we report the results of the events with ML>5 in which the location, the local magnitude
ML (Richter, 1935) calculated by Antelope® software, the moment magnitude, the seismic
moment, the corner frequency estimation are reported. The error on our moment magnitude
estimation represents the variance and is linked to the number of stations selected by the procedure inside the range of distance defined a priori (0-70 km).
Tab. 1 – List of the results regarding the events of the Emilia 2012 sequence. The location is automatically
calculated by Antelope® software; ML represents the Richter magnitude by Antelope® software; M W,M0, f 0 and
eqR are the moment magnitude, the seismic moment, corner frequency and the equivalent radius calculated by
our procedure in near-real time following Andrews (1986); ERR represents the variance linked to the number of
stations used (USTA); STRESS DROP is estimated following Madariaga (1976).
LAT
(°N)
LON DEPTH
DATA
TIME
(°E)
(km) (mm/gg/aa) (hh:mm)
ML
Mw ERR
Mo
(Nm)
fo
(Hz)
eqR
(km)
usta
STRESS
DROP
(MPa)
44.92 11.23
8
5/20/2012
2:03
6.1
6.1
0.2
2.84E+18
0.3
4.5
13
1.65
44.90
11.14
11
5/20/2012
3:02
5.3
5.3
0.2
1.46E+17
0.5
2.7
12
0.42
44.83 11.46
8
5/20/2012
13:18
5.3
5.3
0.1
1.16E+17
0.5
2.7
11
0.29
44.92
11.10
4
5/29/2012
7:00
5.8
5.9
0.2
1.37E+18
0.3
4.2
25
1.16
44.92 10.99
5
5/29/2012
10:55
5.5
5.5
0.3
4.42E+17
0.4
3.5
23
0.70
44.92 11.00
8
6/03/2012
19:20
5.0
5.2
0.2
1.07E+17
0.6
2.4
25
0.58
Fig. 1 – Comparison between the local magnitude as estimated by
Antelope and the moment magnitude estimated by our procedure. The
red line shows the bisector, the blue one the regression line.
60
In Fig. 1 we report Richter
local magnitude versus moment magnitude estimates for
all events used in this work. ML
generally underestimates the moment magnitude MW by about 0.5
magnitude units, principally in
the range 3 < ML < 4.5. A possible reason could be the site effect
not yet taken into account by the
procedure. A recent study (Castro et al., 2013) shows important
amplification variability between
the sites located within the Po
Plain. The area under study has
a complex geological structure,
so a more detailed analysis on
the attenuation and spreading of
waves will most probably also
lead to improved estimates of
seismic source parameters.
Fig. 2 shows corner frequency plotted versus seismic
moment (on a log-log scale).
GNGTS 2013
Sessione 1.1
The corner frequency estimation appears quite stable. The
relationship between seismic
moment and corner frequency
. We
is approximately
calculate stress drop using the
following equation (Madariaga,
1976):
The values range between
0.1 and 1.8 MPa (Fig. 3), which
are within the bounds generally found for crustal earthquakes
(104 Pa < Δσ < 108 Pa, e.g. Hanks,
1977; Kanamori, 1994). The obtained values of stress drop are
within the range reported by several authors for the Emilia seismic
sequence (Malagnini et al., 2012;
Castro et al., 2013). We have also
compared, wherever possible, our
magnitude estimation with the
ones obtained by other Authors
(Malagnini et al., 2012; Pondrelli et al. 2012; Saraò et al., 2012;
Scognamilio et al., 2012). The
agreement is quite fair especially
for the major events (MW > 5).
The differences for some values
are due to different initial assumptions to compute moment magnitude, such as, e.g., velocity model,
epicentral distance and frequency
range. The results obtained represent an important validation for
our real-time procedure proving
that it is robust and reliable. This
real-time automatic procedure is
now routinely used at DMG and
at the Department of Civil Defense (DPC) in Rome for a rapid
determination of earthquake parameters.
Fig. 2 – Corner frequency versus seismic moment. The relationship
between seismic moment and corner frequency is approximately
.
Acknowledgements. We would like to
thank the Italian Civil Protection for kindly Fig. 3 – Stress drop values computed following Madariaga (1976).
providing us part of the seismic data used
in this research. Part of his work was financially supported by the S.H.A.R.M. Project of the Area Science Park of Trieste:
“Tomografia crostale per la valutazione e mitigazione del rischio sismico”. This study was partially supported also by
Project S1 of the Instituto Nazionale di Geofisica e Vulcanologia (INGV) (2012-2013): ”Miglioramento delle conoscenze
per la definizione del potenziale sismogenetico”.
61
GNGTS 2013
Sessione 1.1
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