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In this paper we describe the performance of the ShakeMap software package (Wald et al., 1999; Worden and Wald, 2016) obtained from the fully automatic procedure to estimate ground motions, based on manually revised location and magnitude, during the main event of the Amatrice sequence with special emphasis to the M6 main shock, that struck central Italy on the 24th August 2016 at 1:36:32 UTC. Our results show that the ShakeMap procedure we developed in the last years, with real-time data exchange among those institutions acquiring strong motion data, produces a reliable and useful description of the ground motion experienced throughout a large region in and around the epicentral area. The prompt availability of the rupture fault model, within three hours after the earthquake occurrence, provided a better description of the level of strong ground motion throughout the affected area. Progressive addition of station data and manual verification of the data insures improvements in the description of the experienced ground motions. In particular, comparison between the MCS (Mercalli-Cancani-Sieberg) intensity shakemaps and preliminary field macroseismic reports show overall agreement within the limitations imposed by the station geometry. Finally the overall spatial pattern of the ground motion of the main shock is consistent with reported rupture directivity toward NW and reduced levels of ground shaking toward SW probably linked to the peculiar source effects of the earthquake.
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ANNALS OF GEOPHYSICS, 59, FAST TRACK 5, 2016; DOI: 10.4401/ag-7238
The ShakeMaps
of the Amatrice, M6, earthquake
LICIA FAENZA*, VALENTINO LAUCIANI, ALBERTO MICHELINI
Istituto Nazionale di Geofisica e Vulcanologia,
Centro Nazionale Terremoti, Italy
* licia.faenza@ingv.it
Abstract
In this paper we describe the performance of the ShakeMap software package (Wald et al., 1999; Worden
and Wald, 2016) obtained from the fully automatic procedure to estimate ground motions, based on
manually revised location and magnitude, during the main event of the Amatrice sequence with special
emphasis to the M6 main shock, that struck central Italy on the 24th August 2016 at 1:36:32 UTC.
Our results show that the ShakeMap procedure we developed in the last years, with real-time data ex-
change among those institutions acquiring strong motion data, produces a reliable and useful description
of the ground motion experienced throughout a large region in and around the epicentral area.
The prompt availability of the rupture fault model, within three hours after the earthquake occurrence,
provided a better description of the level of strong ground motion throughout the affected area. Progressive
addition of station data and manual verification of the data insures improvements in the description of the
experienced ground motions. In particular, comparison between the MCS (Mercalli-Cancani-Sieberg) in-
tensity shakemaps and preliminary field macroseismic reports show overall agreement within the limita-
tions imposed by the station geometry. Finally the overall spatial pattern of the ground motion of the main
shock is consistent with reported rupture directivity toward NW and reduced levels of ground shaking
toward SW probably linked to the peculiar source effects of the earthquake.
I. INTRODUCTION
hakeMap is a software package [Wald et
al. 1999a; Worden et al. 2010, Worden and
Wald, 2016] that can be used to generate
maps of ground shaking for various peak
ground motion (PGM) parameters, including
the peak ground acceleration (PGA), peak
ground velocity (PGV), and spectral accelera-
tion response (PSA) at 0.3 s, 1.0 s and 3.0 s, and
instrumentally derived intensities.
The primarily aim of the implementation of
the ShakeMap code [Michelini et al., 2008] at
the Istituto Nazionale di Geofisica e Vulcanologia
(INGV; National Institute of Geophysics and
Volcanology) is to support the Dipartimento
della Protezione Civile (DPC; Civil Protection
Department) providing a first order assess-
ment of the experienced ground shaking to
better direct the rescue teams and planning the
emergency responses in the first few hours fol-
lowing a damaging earthquakes.
At its core, ShakeMap is a seismologically based
interpolation algorithm that exploits the avail-
able data of the observed ground motions and
the available seismological knowledge to
pro-
duce maps of ground motion at local and re-
gional scales. Of particular importance when cal-
culating
the maps is the availability of
observed
data to accurately reproduce the ground
shaking
experienced, especially in the near source.
Thus, in addition to data that are essential to
derive realistic and accurate results, the fun-
damental ingredients for obtaining accurate
maps are: the ground-motion prediction equa-
tion (GMPE), as a function of distance at dif-
ferent periods, and for different magnitudes;
and realistic descriptions of the amplifications
S
ANNALS OF GEOPHYSICS, 59, FAST TRACK 5, 2016; DOI: 10.4401/ag-7238
that the local site geology induces on the in-
coming seismic wavefield; i.e., the site effects.
In its current version, ShakeMap relies on re-
gional attenuation laws and local site amplifi-
cations based on the S-wave velocities in the
uppermost 30 m (VS30) to generate its PGM
maps [Michelini et al., 2008].
In this report, we start with a chronicle of the
generation of the shakemaps for two main
events of the sequence that struck Central Italy
the 24 August 2016 between the towns of Ama-
trice and Norcia [Scognamiglio et al., this is-
sue; Michele et al., this issue] and we conclude
with a comment on the procedure we adopted.
The main shock caused severe damage in the
small towns in Central Italy, including Ama-
trice and Accumuli and in dozens of villages
located along the river Tronto and almost 300
casualties [Azzaro et al, this issue]. The shak-
ing was felt throughout central Italy.
In the recent past, moderate seismic events
struck this area (Gubbio 1984, Mw 5.6; Colfio-
rito 1997, Mw 6.0; Norcia 1979, Mw 5.9;
L’Aquila 2009, Mw 6.1), all with focal mecha-
nisms consistent within the regional NE–SW
extension of the stress field. The main shock of
the Amatrice sequence occurred along a fault
alignment which extends from Mt. Vettore to
Mt. Gorzano, which is external (to the E) of the
tectonic alignment that develops from Gubbio
to Colfiorito and, to the south, extends to the
area struck by the 2009 L’Aquila sequence.
As of October 6, 2016, shakemaps have been
determined for a total of 74 earthquakes with
M>=3.5.
II. THE AUGUST 24, 2016 ML 6.0
EARTHQUAKE
In this section, we present a concise de-
scription of the evolution of the ShakeMap
de-
termination for the August 24, 2016, Ml 6.0 earth-
quake.
i) The automatic final earthquake location
(origin time, 01:36:32 UTC; latitude, 42.69 N; lon-
gitude, 13.2 E; depth, 4 km) was available within
5 minutes of the origin time (01:41:37 UTC).
ii) The manually revised location became
available 17 minutes (1:53 UTC) after the ori-
gin time, with a similar location (42.71 N, 13.22
E), and depth (4 km).
iii) For the magnitude estimation, the first
automatic determination, which became avail-
able within about 5 min from the origin time,
was ML 6.0 The manual revision, which was
available after 12 min, confirmed the same value.
The first moment magnitude was available 1.5
h later, as Mw 6.0 [Scognamiglio et al., 2009;
Scognamiglio et al., this issue].
iv) The first shakemap based on the auto-
matic location and magnitude became avail-
able at 1:43:16 UTC. This map included only
the first data available and lacks of near epi-
center stations.
v) The first map that included the available
RAN (“Rete Accelerometrica Nazionale” man-
aged by the Department of Civil Protection,
DPC) strong motion data and the more distant
broadband data of the Italian seismic network
(RSN) including the local networks of the Uni-
versities of Genova and Trieste, OGS, AMRA,
among others became available at 02:27 UTC,
~46 minutes after the automatic location and
~33 minutes after the revised location (version
3, figure 1). The spatial coverage of the epicen-
tral area is somewhat denser though the near
finite source area is still only partly covered
(only NRC and RQT station PGM data became
available).
vi) Based on the time domain moment
ten-
sor solution [Scognamiglio et al., this issue], the
scaling laws [Wells and Coppersmith, 1994],
and
the geology, with the analysis of the active tec-
tonic structures in the area and their orienta-
tion, the first maps with the fault
included (ver-
sion 5) were published at 04:39 UTC,
about 3
hours after the earthquake occurrence (figure
2). This map better constrains the shaking in
the epicentral area by taking into account the
fault finiteness. Insertion of the fault is based,
however, on a manual procedure which re-
quires the availability of the manually revised
moment tensor and rapid selection of one of
the rupture planes.
ANNALS OF GEOPHYSICS, 59, FAST TRACK 5, 2016; DOI: 10.4401/ag-7238
Figure 1. The Shakemaps of the main shock using automatic processing for the INGV PGM data and the PGM data
provided by DPC. Left: MCS derived instrumental intensity; Center: PGA; Right: PGV.
Figure 2. The Shakemaps of the main shock as in Figure 1 after inserting the fault. Left: MCS derived instrumental in-
tensity; Center: PGA; Right: PGV.
In the following days, the maps were updated
with more close-in and distant stations and the
Mercalli Intensity instrumentally derived scale
of Wald et al. [1999] was replaced by the MCS
[Mercalli-Cancani-Sieberg; Sieberg, 1930] in-
tensity scale calibrated for Italy (Faenza and
Michelini, 2010, 2011). This second change was
adopted because MCS intensities have been
found more informative to non-expert audi-
ences unfamiliar with instrumental ground
motion parameters. More specifically, in the
INGV ShakeMap implementation [Michelini et
al., 2008], the instrumentally derived intensity
values are derived from the conversion of
PGM into intensity values as proposed by
Wald et al. [1999b]. This regression, however,
is based on the Mercalli Modified scale cali-
brated using intensity and PGM data collected
in California. In Italy, the analysis of historical
seismicity through the use of the macroseismic
intensity data has a long tradition and the
MCS intensity scale has been long adopted. To
attain homogeneity between the instrumen-
tally derived intensity maps and the observed
Italian macroseismic intensities, new regres-
sion
relations between PGM and MCS intensity
ANNALS OF GEOPHYSICS, 59, FAST TRACK 5, 2016; DOI: 10.4401/ag-7238
Figure 3. The Shakemaps of the main shock using the revised data obtained from the engineering strong motion DB
(http://esm.mi.ingv.it). Left: MCS derived instrumental intensity; Center: PGA; Right: PGV.
data were proposed by Faenza and Michelini
[2010, 2011] but never implemented into the
ShakeMap procedure at INGV since it was
sought to maintain consistency with similar
instrumental values elsewhere worldwide.
These new relations for MCS were inserted in
ShakeMap starting with the mainshock of this
sequence to better support local needs in Italy.
The shakemaps are by their nature determined
very rapidly right after an earthquake using
automatic procedures. In the following days,
however, new PGM data became available de-
termined from manually revised waveforms.
At INGV the strong motion data are verified
and archived in the Engineering Strong
Mo-
tion DB (ESM; http://esm.mi.ingv.it) to-
gether
with the associated PGM parameters.
Therefore on September 22, 2016, once the re-
vised data became available we replaced the
PGM readings and re-determined the maps
(figure 3).
Overall, this procedure allows a progressive
improvement in the quality of the shakemaps
as additional data become available and man-
ual intervention is performed.
In figure 4 we have summarised the improve-
ments obtained by calculating the differences
(for PGA) between the final shakemaps shown
in figure 3 and the maps obtained with the
automatic processing (figures 2 and 1). In sum-
mary, we note that i) the addition of the AMT
station data condition strongly the values of PGA
at the southern end of the rupture plane and ii)
including the fault is important to improve
and extend the pattern of ground motion near
and above the fault.
The shakemaps shown in figures 1-3 show the
maps of the main shock as they result at the
end of the steps outlined above. The largest
values of the ground motion occur next or
above the fault plane as resulting from the
largest values of acceleration recorded by the
three closest stations (AMT, RQT and NRC)
that all recorded values around 40%g. This
whole area featured values of PGV on the
horizontal components larger than 20 cm/s
(intensity level VIII). One important feature of
the PGA and PGV maps is that relatively large
accelerations have been recorded from NW to
NE of the earthquake epicenter (see the 7%g
contour line) when compared to those re-
corded SE and especially to the SW. This pat-
tern is likely dependent on the source directiv-
ity observed for the main shock both from the
raw data [INGV-ReLUIS Working Group,
2016] and from the preliminary finite fault in-
version results using strong motion data [Tinti
et al, 2016].
ANNALS OF GEOPHYSICS, 59, FAST TRACK 5, 2016; DOI: 10.4401/ag-7238
Figure 4. Differences between the different PGA shakemaps. Left: final shakemap with revised data and fault map com-
pared with automatically processed data and no fault; center: final shakemap with revised data and fault map compared
with automatically processed data and fault inserted; right: shakemap with fault and automatically processed data com-
pared with the same data but no fault.
III. DISCUSSION
In August 2016, a seismic sequence struck the
Apennine in Central Italy, an area that has a
long history of destructive earthquakes, as
known from historical and macroseismic anal-
ysis [Locati et al, 2015]. In this study, we have
described the determination and the pro-
gressive updating of the shakemaps of the
main shock as additional and more accurate
information became available.
In our experience, the inclusion of observed
data is of fundamental importance for the cal-
culation of shakemaps. Indeed, the quantifica-
tion of the shaking near the epicentre using
only the PGM prediction equations comple-
mented with site-effect corrections is difficult
and prone to macroscopic errors and bias
[Faenza et al. 2011; Lauciani et al, 2012].
Moreover, for larger earthquakes that saturate
the recordings of the velocimeters at and near
the epicenter, the accuracy of the shakemaps
depends also on the prompt availability of
strong-motion data, which, for the Amatrice
main shock, become available shortly after its
occurrence. We have found that the area
stricken by the sequence has in general a dense
enough station coverage to produce reasona-
bly accurate maps of the strong ground shak-
ing. The installation of the temporary stations
in the epicentral area improved, however, the
coverage for the subsequent events.
Comparing figures 1 and 3, it is possible to see
the improvement in the quantification of the
ground shaking with the inclusion of the
source model and new review data (see figure
4 for the differences in terms of PGA). The first
preliminary shakemap (figure 1) remained on-
line for only 3 hours. Figure 2 shows a differ-
ent pattern in the near-source shaking because
of the adoption of the Joyner-Boore distance
measure from the fault location, leading to an
underestimation of the PGM values in the near
source. We note also that this time, we have
not encountered the time delay experienced
previously in the strong motion data exchange
since both the RAN data and the INGV data
were readily available.
Since the intensity scale in our maps adopts the
relations obtained from the regression between
PGM parameters and the MCS intensity values of
Faenza and Michelini (2010, 2011), we have com-
pared the final shakemaps with the preliminary
macroseismic maps available at the time of writ-
ing this work. In figure 5 we show the two maps
represented using the same color scale. We note
ANNALS OF GEOPHYSICS, 59, FAST TRACK 5, 2016; DOI: 10.4401/ag-7238
Figure 5. Comparison between the reported macroseismic intensities and the estimated intensities obtained using
Shakemap represented using the same color palette.. Left: preliminary macroseismic map compiled by the field macro-
seismic teams (from “Rapporto sugli effetti macrosismici del terremoto del 24 Agosto 2016 di Amatrice in scala MCS” a
cura di P. Galli e E. Peronace, Coordinamento del rilievo macrosismico MCS a cura di P. Galli e A. Tertulliani, 2016).
Right: MCS intensity values obtained with the final shakemap updated with the manually revised data.
that the MCS intensity shakemap although
much blurred since it relies on essentially three
main data points in the near fault region (AMT,
NRC, and RQT) can nevertheless provide a
very first information on the ground shaking
in the near fault region. For example, and by
simply determining the population within e.g.
the level VIII MCS, it is possible to obtain very
rapidly an initial estimate of the population
exposed to that intensity level as has been pro-
vided by the USGS that publishes the PAGER
estimates (Earle et al., 2009). For the Amatrice
earthquake we found that by using the MCS
VIII contour as polygonal line within which to
extract the population from the LandScan
popu-
lation DB
(http://web.ornl.gov/sci/landscan/),
it would have
resulted almost immediately that
~10,000 people would have been exposed to
strong ground shaking. Similar estimates can
be done for lower intensity levels.
IV. CONCLUSIONS
Our analysis has shown that for the M6
Ama-
trice earthquake of August 24, 2016, the shake-
maps
produced by INGV
i) became available within a few minutes of
the main shock and they already had an amount
of data that insured a relatively good assess-
ment of the ground shaking experienced in the
Amatrice and nearby villages and towns;
ANNALS OF GEOPHYSICS, 59, FAST TRACK 5, 2016; DOI: 10.4401/ag-7238
ii) inclusion of the finite fault within ~3
hours of the main shock contributed to improve
the accuracy of the maps;
iii) inclusion of additional data as they be-
come progressively available is important to
improve the quality of the maps;
iv) inclusion of thoroughly reviewed data is
equally important to avoid that the maps could
be possibly contaminated by processing errors
always present in automatic procedures;
v) comparison between the MCS intensity
shakemaps and a preliminary map of the mac-
roseismic report compiled by the teams that
have evaluated the macroseismic intensity in
the field indicates a remarkable similarity be-
tween estimated and reported intensities.
vi) the pattern of spatial ground motion ob-
tained is consistent with the preliminary reports
that indicate rupture directivity toward NW
and relatively reduced levels of ground motion
toward SW from the earthquake source.
REFERENCES
[Azzaro et al., 2016] Azzaro R., A. Tertulliani,
F. Bernardini, R. Camassi, S. Del Mese, E. Erco-
lani, L. Graziani, M. Locati, A. Maramai, V.
Pessina, A. Rossi, A. Rovida, P. Albini, L.
Arco-
raci, M. Berardi, C. Bignami, B. Briquela, C.
Ca-
stellano, V. Castelli, S. D’Amico, V. D’Amico,
A.
Fodarella, I. Leschiutta, A. Piscini, M. Sbarra.
The Amatrice 2016 earthquake: macroseismic
survey in the damage area and preliminary
EMS intensity assessment, Annals of Geophys-
ics, 59, Fast Track 5, doi:10.4401/ag-7203.
[Earle et al., 2009] Earle, P.S., Wald, D.J.,
Jaiswal, K.S., Allen, T.I., Marano, K.D., Ho-
tovec, A.J., Hearne, M.G., and Fee, J.M (2009).
Prompt Assessment of Global Earthquakes for
Response (PAGER): A system for rapidly de-
termining the impact of global earthquakes
worldwide. U.S. Geological Survey Open-File
Report 2009-1131.
[Faenza and Michelini, 2010] Faenza L. and A.
Michelini, Regression analysis of MCS inten-
sity and ground motion parameters in Italy
and its application in ShakeMap, Geophys. J.
Int, 180(3), 1138-1152, doi:10.1111/j.1365-
246X.2009.04467.x.
[Faenza et al., 2011] Faenza, L., V. Lauciani and
A. Michelini (2011). Rapid determination of the
shake maps for the L'Aquila main shock: a
critical analysis, B. Geofis. Teor. Appl., 52, 407-
425.
[Faenza and Michelini, 2011] Faenza, L., and A.
Michelini (2011), Regression analysis of MCS
intensity and ground motion spectral accelera-
tions (SAs) in Italy, Geophys. J. Int, 1-16,
doi:10.1111/j.1365-246X.2011.05125.x.
[INGV-ReLUIS Working Group, 2016] INGV-
ReLUIS Working Group (2016), Preliminary
study of Rieti earthquake ground
motion data
V5, 1-87, doi:10.13140/RG.2.2.2
7933.92641/1.
[Available at http://www. reluis. it].
[Lauciani et al., 2012] Lauciani V., L. Faenza
and A. Michelini (2012), SchakeMap during
the Emilia sequence, Annals of Geophysics, 55,
4, 2012; doi: 10.4401/ag-6160.
[Locati et al, 2015] Locati M., Camassi R., Ro-
vida A., Ercolani E., Bernardini F., Castelli V.,
Caracciolo C.H., Tertulliani A., Rossi A., Azza-
ro R., D’Amico S., Conte S., Rocchetti E.
(2016).
DBMI15, the 2015 version of the Italian Macrosei-
smic Database. Istituto Nazionale
di
Geofisica e
Vulcanologia; doi:http://doi.org/10.6092/INGV.
IT-DBMI15.
[Michele et al., 2016] Michele M., Di Stefano
R.,
Chiaraluce L., Cattaneo M., De Gori P.,
Monachesi G., Latorre D., Marzorati S., Valor-
oso L., Ladina C., Chiarabba C., Lauciani V. and
M. Fares. The Amatrice 2016 seismic sequence:
a preliminary look to the mainshock and after-
ANNALS OF GEOPHYSICS, 59, FAST TRACK 5, 2016; DOI: 10.4401/ag-7238
shocks distribution, Annals of Geophysics, 59,
Fast Track 5, doi:10.4401/ag-7277.
[Michelini et al., 2008] Michelini A., L. Faenza,
V. Lauciani and L. Malagnini (2008). Shake-
Maps implementation in Italy, Seismol. Res.
Lett., 79, 688-697.
[Scognamiglio et al., 2009] Scognamiglio, L., E.
Tinti, and A. Michelini (2009), Real-Time De-
termination of Seismic Moment Tensor for the
Italian Region, Bull. Seismol. Soc. Am., 99 (4),
2223-2242.
[Scognamiglio et al., this issue] Scognamiglio
L, E. Tinti, M. Quintiliani, The 2016 Amatrice
seismic sequence: Fast determination of the
time domain moment tensors and finite fault
model analysis of the ML 5.4 aftershock, This
issue.
[Sieberg, 1930] Sieberg A. (1930), Geologie der
Erbbeben, Handbuch der Geophysik, 2, 4, 552-
555.
[Tinti et al, 2016] Tinti, E., L. Scognamiglio, A.
Michelini, and M. Cocco (2016), Slip heteroge-
neity and directivity of the M L6.0, 2016, Ama-
trice earthquake estimated with rapid finite-
fault inversion, Geophys. Res. Lett, 1-8,
doi:10.1002/2016GL071263.
[Wald et al., 1999a] Wald, D.J., Quitoriano, V.,
Heaton, T.H., and Kanamori, H., (1999a), Rela-
tionship between Peak Ground Acceleration,
Peak Ground Velocity, and Modified Mercalli
Intensity in California, Earthquake Spectra, 15
(3), p. 557-564.
[Wald et al., 1999b] Wald, D.J., Quitoriano,
V.,
Heaton, T.H., Kanamori H, Scrivner, C.W.
and
Worden C.B. (1999n). Trinet ‘ShakeMaps’:
rapid generation of peak ground motion and
intensity maps for earthquakes in southern
California, Earthq. Spectra, 15, 537.
[Wells and Coppersmith, 1994]. Wells D.L.,
and K.J. Coppersmith (1994). New empirical
relationships among magnitude, rupture length,
rupture width, rupture area, and surface dis-
placement, B. Seismol. Soc. Am, 84, 974-1002.
[Worden et al., 2010 ] Worden, C.B., Wald, D.J.,
Allen, T.I., Lin, K., Garcia, D. and Cua G. (2010).
A revised ground-motion and intensity inter-
polation scheme for ShakeMap. B. Seismol.
Soc. Am. 100, 3083-3096.
[Worden and Wald, 2016] Worden, C. B., and
D. J. Wald (2016), ShakeMap Manual, version
2.0, 1-113.
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... However, the ShakeAlert system for EEW in the western US has been recently upgraded to include the determination of ground motion using the same region-specific ground-motion prediction equations that are used by ShakeMap implementations in California, Oregon, and Washington (Given et al., 2018). In general, the time required to produce the first shakemaps depends on several factors such as data availability, and transmission and processing latencies, and the map accuracy depends on the density of the stations and on the quality of the data available (e.g., for the 2016 Central Italy M=6 August 24 mainshock, the first ShakeMaps were provided 6 minutes after origin time; Faenza et al., 2016). ...
Preprint
This study describes a deep convolutional neural network (CNN) based technique for the prediction of intensity measurements (IMs) of ground shaking. The input data to the CNN model consists of multistation 3C broadband and accelerometric waveforms recorded during the 2016 Central Italy earthquake sequence for M $\ge$ 3.0. We find that the CNN is capable of predicting accurately the IMs at stations far from the epicenter and that have not yet recorded the maximum ground shaking when using a 10 s window starting at the earthquake origin time. The CNN IM predictions do not require previous knowledge of the earthquake source (location and magnitude). Comparison between the CNN model predictions and the predictions obtained with Bindi et al. (2011) GMPE (which require location and magnitude) has shown that the CNN model features similar error variance but smaller bias. Although the technique is not strictly designed for earthquake early warning, we found that it can provide useful estimates of ground motions within 15-20 sec after earthquake origin time depending on various setup elements (e.g., times for data transmission, computation, latencies). The technique has been tested on raw data without any initial data pre-selection in order to closely replicate real-time data streaming. When noise examples were included with the earthquake data, the CNN was found to be stable predicting accurately the ground shaking intensity corresponding to the noise amplitude.
... Shake-maps describe the main ground motion parameters, giving a quantitative evaluation of the seismic action. These are provided by INGV (National Institute of Geophysics and Volcanology), starting from the data recorded in its seismic stations, and are defined according to the correlations provided by Michelini et al. (2008), Faenza and Michelini (2010) and Faenza et al. (2016). The maps already account for the soil types determined by the V s30 value, estimated on the 1:100,000 geological map of Italy, but they do not account for local site effects. ...
Article
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The paper presents a detailed report on a large sample of masonry churches damaged by the 2016–2017 Central Italy seismic sequence. The first part of the work analyses the seismic sequence to give an overview of the occurred events in terms of both ground motion parameters and macro-seismic intensities. The surveyed data are organized into a database made, to date, of 990 cases, which represent almost one-fourth of the whole surveys performed during the emergency phase. Such a significant statistical sample was used to carry out a regional scale typological analysis in order to identify the most recurrent typologies of churches present in Central Italy. The analysis of the observed damage and usability outcomes allowed drawing some conclusions on the behaviour of the inspected churches under the 2016–2017 seismic sequence. The collected data were used to create damage probability matrixes for homogeneous classes of churches at different damage levels and, successively, to implement the corresponding fragility curves in terms of PGA.
... The great advantage of distributed sensors arrays is to map earthquake energy throughout the territory, thus limiting spatial aliasing and detecting local response effects. In our application example, the increased number of receivers along the Umbria Valley allows defining a more detailed shake map than the one obtainable only with the very limited number of classical strong-motion stations (Faenza et al., 2016). The shake maps based on the few available HQ sensors present a general moderate instrumental intensity for the entire Umbria Valley. ...
Article
Modern seismic ground-motion sensors reached excellent response quality in terms of dynamic and bandwidth resolution. The weakest point in the recording of the strong-motion wavefield is the spatial sampling and resolution, due to the limited number of installed sensors, often at large distances. A significant improvement in spatial resolution can be achieved by the use of low-cost distributed sensors arrays, capable of recording seismic events with a dense sensors network. In this perspective, microelectro mechanical system (MEMS) sensors could efficiently integrate the use of standard accelerometers for moderate-to-strong seismic events. In this article, we present data from the 2016 Central Italy earthquakes, recorded by a spatially dense prototype MEMS array installed in the neighborhood of the epicenter area. MEMS records are compared against the national strong-motion network data, suggesting that these very low-cost sensors could be an effective choice for increasing the spatial density of stations to provide strong-motion peak parameters.
... In this sense, seismic design codes have usually been improved after each earthquake disaster, but old constructions have remained unprotected by new techniques. Nevertheless, poor behavior has also been observed in those buildings designed with recent seismic regulations [1][2][3]. ...
Article
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Featured Application: Geographic Information System (GIS) estimation of ante-earthquake scenarios through a more functional and standardized method of seismic vulnerability evaluation of reinforced concrete buildings in urban areas. Abstract: In spite of the enhancements related to building construction, many regions still present a major level of seismic risk as a consequence of the high vulnerability of the urban configuration of their cities. An improved method to assess the seismic vulnerability of buildings in urban areas is proposed in this contribution in order to advance the management of seismic emergency scenarios. The methodology, mainly based on the cadastral database, allows for a more standardized implementation as a function on the typological, structural, and urban parameters of the buildings, reducing the level of uncertainties linked to these methodologies and giving continuity to the different RISK-UE published works. The generalization of the method to any urban area has also been improved by means of removing the parameters whose calibration is associated with a specific area. The methodology has been put into practice in the urban area of the city of Lorca (SE Spain), in the aftermath of the earthquake of 11 May 2011, due to the availability of well-documented data reported from this seismic event. The proposal, when it is combined with Geographic Information System (GIS) techniques, provides valuable information for the planning and management of post-earthquake emergency situations.
Chapter
This chapter highlights the primary goal, as well as the problem that is solved through the implementation of this framework. This was accomplished by developing an improved version of the original vulnerability index technique, which utilizes the application of non-linear parametric analysis to quantify the physical structural characteristics that are the most effective overall. Because it takes into account the standard precautions that need to be matched with the availability of observable damage aspects, the analytical framework is quickly becoming the new preferred way for modeling. In order to accomplish this, designers can model and construct parameters that significantly affect the behavior of the structure, as well as create a framework by inventing an analytical Seismic Vulnerability Index.
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On 24 August 2016, a Mw 6.0 earthquake started a damaging seismic sequence in central Italy. The historical center of Amatrice village reached the XI degree (MCS scale) but the high vulnerability alone could not explain the heavy damage. Unfortunately, at the time of the earthquake only AMT station, 200 m away from the downtown, recorded the mainshock, whereas tens of temporary stations were installed afterwards. We propose a method to simulate the ground motion affecting Amatrice, using the FFT amplitude recorded at AMT, which has been modified by the standard spectral ratio (SSR) computed at 14 seismic stations in downtown. We tested the procedure by comparing simulations and recordings of two later mainshocks (Mw 5.9 and Mw 6.5), underlining advantages and limits of the technique. The strong motion variability of simulations was related to the proximity of the seismic source, accounted for by the ground motion at AMT, and to the peculiar site effects, described by the transfer function at the sites. The largest amplification characterized the stations close to the NE hill edge and produced simulated values of intensity measures clearly above one standard deviation of the GMM expected for Italy, up to 1.6 g for PGA.
Conference Paper
Latest Italian earthquakes have significantly highlighted that heritage masonry buildings, especially churches, are considerably vulnerable to seismic actions. Though usually made of good quality materials, churches are characterized by highly vulnerable structural morphologies and architectural configurations, such as significant dimensions, wide halls, thin long span vaults, slender towering or projecting parts, slender walls with large openings. On 21 st August 2017, an earthquake struck the Ischia Island causing several damages to both ordinary and heritage buildings. During the emergency phases after the event, many churches were surveyed and the damage evaluation was carried out by filling in the II level survey form (A-DC) in situ. An interesting database made of 27 churches was, thus, created aimed to carry out detailed analysis of the recorded damages and to realize damage probability matrices, useful to implement fragility curves based on an "observational approach". Both global damage index and activation of mechanisms were investigated. Considerations about the correlation between vulnerability index and observed damage level were also presented. Finally, for a homogenous class of churches, a predictive formulation of the mean damage was assessed and compared with other formulations available in the literature and obtained according to a similar approach.
Article
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Three damaging earthquakes occurred in Central Italy between August and October 2016 leaving almost 30,000 homeless. The first event is a Mw 6.0 occurred on August 24th at 01:36 UTC close to Accumoli village; two months later, a Mw 5.9 on October 26th at 19:18 UTC happened 3 km West of Visso and finally a Mw 6.5 on October 30th at 06:40 UTC, 6 km North of Norcia, which is the largest earthquake recorded in Italy since the Mw 6.9 1980 Irpinia event. This paper focuses on the seismicity distribution observed from the beginning of the sequence until the 15th of September 2016, almost six weeks before the occurrence of the largest event. We relocated the aftershocks of the Mw 6.0 Amatrice 2016 main event by inverting, with a non-linear probabilistic location method, P- and S-arrival time readings produced and released in near real-time by the analyst seismologists of INGV on 24H duty in the seismic monitoring room. Earthquake distribution shows the activation of a normal fault system with a main SW-dipping fault extending from Amatrice to NW of Accumoli village for a total length of 40 km. Toward north, in the hanging-wall volume of the main fault, the structure becomes more complex activating an antithetic fault below the Norcia basin. It is worth nothing that below 8-9 km of depth, the whole fault system has an almost continuous sub-horizontal layer interested by an intense seismic activity, about 2 km thick.
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We present the revised Time Domain Moment Tensor (TDMT) catalogue for earthquakes with ML larger than 3.6 of the first month of the ongoing Amatrice seismic sequence (August 24th-September 25th). Most of the retrieved focal mechanisms show NNW-SSE striking normal faults in agreement with the main NE-SW extensional deformation of Central Apennines. We also report a preliminary finite fault model analysis performed on the larger aftershock of this period of the sequence (Mw 5.4) and discuss the obtained results in the framework of aftershocks distribution.
Article
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The 24 August 2016 earthquake very heavily struck the central sector of the Apennines among the Lazio, Umbria, Marche and Abruzzi regions, devastating the town of Amatrice, the nearby villages and other localities along the Tronto valley. In this paper we present the results of the macroseismic field survey carried out using the European Macroseismic Scale (EMS) to take the heterogeneity of the building stock into account. We focused on the epicentral area, where geological conditions may also have contributed to the severity of damage. On the whole, we investigated 143 localities; the maximum intensity 10 EMS has been estimated for Amatrice, Pescara del Tronto and some villages in between. The severely damaged area (8-9 EMS) covers a strip trending broadly N-S and extending 15 km in length and 5 km in width; minor damage occurred over an area up to 35 km northward from the epicenter.
Data
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The latest version of the Italian Macroseismic Database, DBMI15, has been released in July 2016, and replaces the prevision version, called DBMI11 (Locati et al., 2011). DBMI makes available a set of macroseismic intensity data related to Italian earthquakes and covers the time-window 1000-2014. Intensity data derive from studies by authors from various Institutions, both in Italy and bordering countries (France, Austria, Slovenia, and Croatia). Macroseismic Data Points (MDPs) are collected and organized in DBMI for several scopes. The main goal is to create a homogenous set of data for assessing earthquake parameters (epicentral location and magnitude) for compiling the Parametric Catalogue of Italian Earthquakes (CPTI). The data provided by DBMI are also used for compiling the seismic history of thousands of Italian localities (15213 in DBMI15), in other words the list of effects observed in a place through time as a consequence of earthquakes, expressed as macroseismic intensity degrees. As they are closely linked, DBMI and CPTI tend to be published at the same time, and using the same release version (e.g. DBMI04-CPTI04, DBMI11-CPTI11), but in two distinct websites, one for DBMI, and a different one for CPTI. From this release, DBMI and CPTI (Rovida et al., 2016) are made available using a unified website.
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p>ShakeMap is a software package that can be used to generate maps of ground shaking for various peak ground motion (PGM) parameters, including peak ground acceleration (PGA), peak ground velocity, and spectral acceleration response at 0.3 s, 1.0 s and 3.0 s, and instrumentally derived intensities. ShakeMap has been implemented in Italy at the Istituto Nazionale di Geofisica e Vulcanologia (INGV; National Institute of Geophysics and Volcanology) since 2006 (http://shakemap.rm.ingv.it), with the primary aim being to help the Dipartimento della Protezione Civile (DPC; Civil Protection Department) civil defense agency in the definition of rapid and accurate information on where earthquake damage is located, to correctly direct rescue teams and to organize emergency responses. Based on the ShakeMap software package [Wald et al. 1999, Worden et al. 2010], which was developed by the U.S. Geological Survey (USGS), the INGV is constructing shake maps for Ml ≥3.0, with the adoption of a fully automatic procedure based on manually revised locations and magnitudes [Michelini et al. 2008]. The focus of this study is the description of the progressive generation of these shake maps for the sequence that struck the Emilia-Romagna Region in May 2012. […] <br /
Article
Italy is a seismically active country which has been site of several large and extremely damaging earthquakes causing hundreds to tens of thousands of casualties since historical times. In recent years, the "Dipartimento per la Protezione Civile" (DPC; Italian Civil Protection - an office dependent directly from the prime minister) has supported the project S4 driven specifically toward fast assessment of ground motion shaking in Italy in order to organize the emergency and direct the rescue teams. The Istituto Nazionale di Geofisica e Vulcanologia (INGV) has implemented the software package USGS-ShakeMap® to obtain maps of the peak ground motion parameters (PGM), and of the instrumentally derived intensities. The calculation of shakemaps at INGV relies mainly on broadband and strong motion data acquired by the Italian seismic network. Shakemap PGM data feeding relies on two concurrent seismic acquisition systems and maps are be determined as quickly as 5 minutes from origin time automatically or within 30 minutes using manually revised locations for earthquakes occurring on the national territory. In Italy, attenuation has been found to vary between different regions. For the smaller events (up to M 5.5) we have implemented a six-areas regionalized model (three separate sets of equations) following the relations of Malagnini and co-workers (Malagnini, et al., 2000; Malagnini, et al., 2002; Morasca, et al., 2006), the same used by the National Seismic Hazard Working Group (2004) for the compilation of the national hazard map; for larger earthquakes, the strong-motion-based equations by Ambraseys et al. (1996) are used. For the site corrections, we have implemented a classification based on the 1:100,000 geology map of Italy compiled and published by the "Servizio Geologico Nazionale". In this case, the geologic units have been gathered into five different classes A, B, C, D and E according to the EuroCode8 provisions, EC8, after Draft 6 of January 2003 on the base of the ground acceleration response. This site classification is compared to that that can be obtained from the analysis of the topographic relief (Allen and Wald, 2007). Examples of shakemaps for both recent M4 size earthquakes and for large, instrumentally recorded 20th century earthquakes that have occurred in Italy will be shown.
Article
Rapid (3-5 minutes) generation of maps of instrumental ground-motion and shaking intensity is accomplished through advances in real-time seismographic data acquisition combined with newly developed relationships between recorded ground-motion parameters and expected shaking intensity values. Estimation of shaking over the entire regional extent of southern California is obtained by the spatial interpolation of the measured ground motions with geologically based frequency and amplitude-dependent site corrections. Production of the maps is automatic, triggered by any significant earthquake in southern California. Maps are now made available within several minutes of the earthquake for public and scientific consumption via the World Wide Web; they will be made available with dedicated communications for emergency response agencies and critical users.
Article
In Italy, the Mercalli–Cancani–Sieberg (MCS) is the intensity scale in use to describe the level of earthquake ground shaking, and its subsequent effects on communities and on the built environment. This scale differs to some extent from the Mercalli Modified scale in use in other countries and adopted as standard within the USGS-ShakeMap procedure to predict intensities from observed instrumental data. We have assembled a new PGM/MCS-intensity data set from the Italian database of macroseismic information, DBMI04, and the Italian accelerometric database, ITACA. We have determined new regression relations between intensities and PGM parameters (acceleration and velocity). Since both PGM parameters and intensities suffer of consistent uncertainties we have used the orthogonal distance regression technique. The new relations are and Tests designed to assess the robustness of the estimated coefficients have shown that single-line parametrizations for the regression are sufficient to model the data within the model uncertainties. The relations have been inserted in the Italian implementation of the USGS-ShakeMap to determine intensity maps from instrumental data and to determine PGM maps from the sole intensity values. Comparisons carried out for earthquakes where both kinds of data are available have shown the general effectiveness of the relations.