Geophysical Journal International

Transcription

1 Geophysical Journal International Geophys. J. Int. () 84, doi:./j x x Characterization of earthquake-induced ground motion from the L Aquila seismic sequence of 9, Italy Luca Malagnini, Aybige Akinci, Kevin Mayeda,,3 Irene Munafo, Robert B. Herrmann 4 and Alessia Mercuri Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy. luca.malagnini@ingv.it Weston Geophysical Corporation, Lexington, MA, USA 3 Berkeley Seismological Observatory, University of California, Berkeley, CA, USA 4 Department of Earth and Atmospheric Sciences of Saint Louis University, St. Louis, MO, USA Accepted October. Received August 3; in original form May SUMMARY Based only on weak-motion data, we carried out a combined study on region-specific source scaling and crustal attenuation in the Central Apennines (Italy). Our goal was to obtain a reappraisal of the existing predictive relationships for the ground motion, and to test them against the strong-motion data [peak ground acceleration (PGA), peak ground velocity (PGV) and spectral acceleration (SA)] gathered during the M w 6.5 L Aquila earthquake (9 April 6, :3 UTC). The L Aquila main shock was not part of the predictive study, and the validation test was an extrapolation to one magnitude unit above the largest earthquake of the calibration data set. The regional attenuation was determined through a set of regressions on a data set of 777 high-quality, high-gain waveforms with excellent S/N ratios (459 vertical and 858 horizontal time histories). Seismograms were selected from the recordings of 7 foreshocks and aftershocks of the sequence (the complete set of all earthquakes with M L 3., from 8 October to May ). All waveforms were downloaded from the ISIDe web page ( a web site maintained by the Istituto Nazionale di Geofisica e Vulcanologia (INGV). Weak-motion data were used to obtain a moment tensor solution, as well as a coda-based moment-rate source spectrum, for each one of the 7 events of the L Aquila sequence (.8 M w 6.5). Source spectra were used to verify the good agreement with the source scaling of the Colfiorito seismic sequence of recently described by Malagnini et al. (8). Finally, results on source excitation and crustal attenuation were used to produce the absolute site terms for the 3 stations located within 8 km of the epicentral area. The complete set of spectral corrections (crustal attenuation and absolute site effects) was used to implement a fast and accurate tool for the automatic computation of moment magnitudes in the Central Apennines. Key words: Earthquake ground motions; Body waves; Coda waves; Site effects; Wave propagation. GJI Seismology INTRODUCTION A number of recent papers have recognized the importance of weakmotion-based investigations of regional wave propagation and complex source scaling, pointing out the large regional variability of the first (e.g. Drouet et al. ), and the case-by-case variations of the second (e.g. Malagnini et al. a). In spite of these and other observations, such as supershear rupture and slow earthquakes, a large segment of the seismological community holds onto the belief that earthquake sources are self-similar and that regional variations in wave propagation are not significant in strong ground motion and related studies. As a result, we tend to use only ground motion predictive relationships that are obtained using global data sets of strong ground motion records. In this study, we aim to address the long-standing question, namely: How to properly predict future ground motion of large earthquakes if we only have a weak-motion database?. Specifically, we want to address the following: (i) Do regional differences in the excitation/attenuation of seismic waves matter in ground motion predictive equations (GMPE)? (ii) Do we need to limit ourselves to strong-motion accelerograms when we try to predict the ground motion induced by moderate-to-large earthquakes? (iii) Are earthquakes self-similar? (iv) Can we improve the accuracy of GM- PEs by using region-specific data sets, even if they do not contain C The Authors 35 Geophysical Journal International C RAS Downloaded from on 5 July 8

2 36 L. Malagnini et al. strong-motion recordings? The latter question is especially useful for real-time applications like ShakeMap R, for which accuracy is the key, not conservatism, but also for engineering applications. We believe that the L Aquila seismic sequence of 9 is quite adequate to find better answers to these questions, since a large amount of weak- and strong-motion data were recorded for the main shock and the entire aftershock sequence. As we show in the following sections, this complete data set permits us to use several recently developed approaches, and compare our results with others in the study region. Moreover, extreme hazard was estimated in the region before the earthquake (Pace et al. 6; Akinci et al. 9), and the seismological community believes the regional hazard is still very high. Elevated hazard in the region, its accurate estimation (Akinci et al. a), and possible repercussions on the city of Rome from large earthquakes in the Apennines (Olsen et al. 6), make this paper particularly valuable for both the periodic reappraisals of the national hazard map that INGV is asked to perform by the Italian Civil Protection Department (DPC), the evaluation of scenarios, and the correct implementation of ShakeMap R (Michelini et al. 8). With regard to the unresolved issues, the question of regional variations in attenuation (question i) has remained without having a concrete answer for many years. Very high quality digital data, in terms of sizes of the data sets and densities of the monitoring networks, have been available for well over two decades. On the contrary, notwithstanding the dramatic technological evolution of strong-motion networks that took place in the last yr, regional accelerometric data sets of strong ground motions are still woefully underrepresented relative to weak-motion data sets, simply due to the infrequent occurrence of large events. Weak-motion studies performed on very large sets of broadband recordings did show significant regional variations in the crustal wave propagation and their anelastic attenuation (Drouet et al. ). Furthermore, there are several published papers that were carried out in different regions of the world, although nobody ever undertook the effort of a comprehensive comparative study [examples of such regions are: the Apennines, Malagnini et al. (a, 8); Malagnini & Herrmann (), the San Francisco Bay Area, Malagnini et al. (7), the Northeastern Alps, Malagnini et al. (), the Kachchh Basin, India, Bodin et al. (4), the Erzincan and Marmara regions of Turkey, Akinci et al. (, 6), the Northwestern Alps, Morasca et al. (6), Eastern Sicily, Scognamiglio et al. (5), Switzerland, Bay et al. (3), Central Europe, Malagnini et al. (b), Southern California, Raoof et al. (999) and Israel, Meirova et al. (8)]. Results from previous studies on the Apennines, the western Alps and eastern Sicily were used for the computation of the national hazard map of Italy (Akinci et al. 4; Gruppo di Lavoro MPS4 4; Montaldo et al. 5). The idea behind the use of regional, weak-motion-based predictive relationships for the ground motion in the Italian hazard map of 4 was that they would contribute only to the hazard calculation at moment magnitudes M w 5.5. Strong-motion-based predictive relationships would be used only for the integration of the larger events, beyond the M w 5.5 threshold. One subsequent study (Malagnini et al. 7), clearly demonstrated that the weak-motion-based relationships could successfully predict the ground motions induced by the Loma Prieta earthquake (M w 7.), after an ad hoc calibration of the sole source term at the large magnitude level of the main shock. This successful prediction was carried out using a calibration data set that was roughly magnitude units smaller than the main shock. Later in this study we show that at moderate magnitudes and local distances (e.g. R 5 6 km and M w = 6.5), strong motion predictions calibrated on different regions may not differ too much between each other, whereas large variations do occur at smaller magnitudes (i.e. M w ). To answer the second question on whether only strong motion data should be used (question ii), we will address the validity of the following statement: Given a large number of digital weakmotion recordings for a study of the regional wave propagation, and broadband seismograms recorded at regional distances for the investigation of the aprioridetails of source scaling, then accurate predictions of strong ground motion can be made for the region under investigation. With regard to source scaling (question iii), there is no clear consensus within the community. Groups with very different viewpoints gave conflicting answers to the question of source scaling (poll results of the 5 Chapman Conference on Radiated Energy and the Physics of Earthquake Faulting: As a result, it is still debated whether earthquakes are always strictly self-similar, as advocated by Ide & Beroza () and many others, or whether the source scaling is more complex and region-dependent (e.g. Mayeda & Malagnini ). The problem with addressing source scaling (question iii) lies in the inaccuracy of the available measurements of radiated energy or apparent stress. Recently developed new techniques, which reduces the error bars of energy measurements, favoured the need for a change in the physics of friction and faulting at some critical moment magnitude, say M w 5.5 (Mayeda & Walter 996; Morasca et al. 5; Mayeda et al. 7; Malagnini & Mayeda 8; Malagnini et al. 8, a; Mayeda & Malagnini 9, ). New results on the Parkfield earthquake of 4 (Mayeda & Malagnini, in preparation) show that, within the error bars, selfsimilar sequences do (infrequently) occur. Finally, the answer to the question of accurate GMPE s (question iv) sounds like common sense, once we understand wave propagation, and can accurately predict the source spectra within a specified range of magnitudes. In this study, by using high-quality, weak-motion data from the L Aquila (Italy) seismic sequence (.8 M w 5.4), we recalculate a functional form describing the regional wave propagation in the Central Apennines. We then couple the attenuation results with the source scaling discussed in Malagnini et al. (8) for the Colfiorito seismic sequence of , and predict the peak motions [peak ground acceleration (PGA), peak ground velocity (PGV) and spectral acceleration (SA)]. Horizontal peak accelerations and velocities from processed data of the L Aquila earthquake are compared with other ground motion prediction equations (GMPEs) developed on the basis of both strong- and weak-motion data. The technique described in Malagnini et al. (4, 6, 7) is applied to the weak-motion data set, and the absolute site terms for 3 stations of the INGV national seismic network are obtained. A spectral correction for the effects induced by the regional attenuation and the shallow geology is successfully implemented in an automatic algorithm for the accurate computation of moment magnitudes in the Central Apennines. CHARACTERIZATION OF THE DATA SET The L Aquila seismic sequence started, with respect to our data set of events with M L 3., on 8 October. During the entire sequence, a large number of high-quality, three-component, weak-motion time histories were recorded by the National C The Authors, GJI, 84, Geophysical Journal International C RAS Downloaded from on 5 July 8

3 Earthquake-induced GM in the Apennines 37 Digital Seismic Network run by the Istituto Nazionale di Geofisica e Vulcanologia (INGV), whereas strong-motion accelerograms were gathered by the Italian Strong Motion Network (RAN, which stands for Rete Accelerometrica Nazionale). Weak-motion data on the one hand, are freely available in quasi-real time at INGV, where seismograms can be downloaded from the ISIDe (Italian Seismological and Instrumental and parametric DatabasE) web site ( On the other hand, reviewed strong-motion accelerograms may be downloaded, after a substantial delay, from the ITACA (ITalian ACcelerometric Archive) web site ( Moment tensor solutions of all the events with M L 3. were computed in quasi-real time (right after the waveforms were downloaded from ISIDe), based on a regional velocity model obtained from the inversion of Love- and Rayleigh-wave group velocities (Herrmann & Malagnini 9). Solutions may be reached on the following web site ( The described effort allowed the storage of an excellent data set of 7 events with.8 M w 6.5. After visually inspecting each single waveform, we selected 777 time histories (459 vertical, and 858 horizontal seismograms) with excellent S/N ratios. P- and S-wave arrivals were manually picked, and waveforms were visually checked for glitches and drop-outs. Fig. shows a map of the region where are represented the 7 moment tensor solutions, whereas Fig. shows a map of the stations of the regional network that were used in the first part of the study: a reappraisal of the regional attenuation of the Central Apennines. HIGH-FREQUENCY WAVE PROPAGATION: GEOMETRICAL SPREADING AND ANELASTIC ATTENUATION IN THE CENTRAL APENNINES In the first part of this study on the regional wave propagation, we used all the INGV stations indicated in Fig. (a) (single and double triangles of different colours, open and solid). Stations indicated by solid blue triangles are those for which the number of recordings allowed the calculation of the absolute site terms for all the three components of the ground motion. The events of Fig. are also indicated with red stars. The study on the regional wave propagation is completely decoupled from that on the quantification of the source characteristics. Moreover, recordings of the main shock were excluded from the quantification of the characteristics of regional wave propagation and anelastic attenuation that are presented in this paper. On the contrary, data from the main shock (only weak-motion recordings, however) were only used to analyse the source scaling for the largest events of the sequence, but not for the reappraisal of the groundmotion predictive relationships (see later). At a specific central frequency, f c, a narrow bandpass filter is made of a high-pass filter with corner at (/ )f c, followed by a low-pass filter with corner at f c. For purposes of graphical representation of the regional attenuation (see Fig. 3), each filtered amplitude is normalized, at the sampling frequencies used in this study, to the rms-value of the bandpass-filtered time history at a fixed elapsed time in the seismic coda. Such procedure would eliminate source and site contributions from the observed filtered amplitudes. In the L -norm sense, coda-normalized amplitudes are forced to have their piece-wise linear median trend (not shown) to go though the null value at an arbitrary reference distance r REF = 4 km (for details on the entire technique, see Malagnini et al. a). A set of regressions was run independently on the peak values of all the filtered time histories. For each data point, we used the following scheme: [ A ij ( f c, r ij ) = log aij ( f c, r ij ) ] = SRC j ( f c, r REF ) + D ( ) r ij, r REF, f c + SITEi ( f c ), () where r ij is the hypocentral distance between the jth source [the corresponding term in the regressions would be SRC j ( f c, r REF )], and the ith site term [SITE i ( f c ) would be the corresponding term in the regressions]; D(r ij, r REF, f c ) is the regional attenuation term, which include geometrical spreading and anelastic attenuation effects. Eq. () (i.e. the convolution theorem, which holds true for the Fourier amplitudes of the recorded ground motions) may also be applied to the peak values of the bandpass-filtered time histories. A non-rigorous proof of the latter statement can be obtained by applying the mathematical tool of Random Vibration Theory (RVT, Cartwright & Longuet-Higgins 956) to a narrow bandpass-filtered waveform, together with the Parseval s equality. Because the logarithm of the path term is normalized to zero at the arbitrary reference distance r = r REF, the path term in Central Apennines, D(r, r REF, f c ), may be modelled as follows: D (r, r REF, f c ) = log [d(r, r REF, f c )] ) exp = log [( g(r) g(r REF ) ( π f c (r r REF ) β Q ( f c ) )], () where r REF = 4 km, and r. r r = km ( ). ( ). r g(r) = r r r < r r = 3 km ( ). ( ). ( ).7 r r r r r r > r Each component of the ground motion (N S, E W and U D) is independently inverted, and a zero-average constraint is forced only on the horizontal site terms during the regressions. The constraints of null average for the site terms, and of null path term at r = r REF [D(r = r REF, f c ) = ], allow the effective decoupling of the three logarithmic terms on the right-hand side of eq. (). Moreover, they grant a precise physical meaning to the three logarithmic terms on eq. (): the SRC j ( f c, r REF ) terms represent the excitation that would be recorded during the jth earthquake at the reference distance, r REF, by the log-averaged horizontal network site, /N[ N i= SITE i( f c )]. An independent site term is referred to each and every specific component of the ground motion, for all stations. Results are given, for each sampling frequency, in Fig. 4. The empirical terms of Fig. 4 were modelled using the attenuation model for the crust in Central Apennines obtained by eqs () (4) (black lines in the background of Fig. 4) Q( f ) = 4 f.5. (4) Eqs (3) and (4) are obtained after a trial-and-error modelling procedure. Fits are shown in Fig. 4. The geometrical spreading used in (3) at short distances (r < km) is slightly faster than /r, inagreement with the numerical results of an unpublished experiment run by Herrmann and Malagnini) on synthetic ground motions induced by a set of 45 -dipping, dip-slip faults. Given the trial-and-error method used to obtain the model described in eqs (3) and (4), no uncertainties could be provided. For comparison, Malagnini et al. (8) found the following functional forms: g(r) = (3) r r = 3 km )( ).5 (5) r r r r > r r. ( C The Authors, GJI, 84, Geophysical Journal International C RAS Downloaded from on 5 July 8

4 38 L. Malagnini et al. Figure. Map of the region surrounding L Aquila, with the focal solutions for the events of the sequence, as they have been obtained by Herrmann & Malagnini (9). The minimum magnitude for which it was possible to obtain a reliable moment tensor solution was M w.8. Colour scale indicates the depths of the events that minimize the misfit. The black square indicates the centre of the city of L Aquila. The main shock of the sequence (M w 6.5) can be recognized because the curves of its focal mechanism have been thickened. Locations used for the plot are those available on the ISIDe web site. and Q( f ) = f.4 (6) All the details about the regressions can be found in the ground motion-related papers by Malagnini et al. that are cited in the introductory section, together with the details about the trial-and-error procedures that allowed the definition of the regional attenuation model described by eqs () (4). The misfit between the old attenuation model (eqs, 5 and 6), and the new regressions (Fig. 4, lines in colour) is very similar to that obtained using the new model (the one shown in Fig. 4), although of a lesser quality. Yet, given the minute error bars of Fig. 4, the misfit reduction obtained with the new model is statistically significant. Duration of the ground motion at the various sampling frequency was also regressed, although it is not shown here, and actually completes the model shown with black lines in Fig. 4. In fact, normalized peak values shown in Fig. 4 with the black lines in the background are computed through RVT, using a spectral model and an estimate of duration as a function of distance and frequency. The duration function regressed at.5 Hz was used for the computation of the PGA and PGV shown later, and also in those included in the Electronic Supplement. The Spectral Accelerations in the Electronic Supplement were computed using durations at the specific frequencies (.33 Hz,., 3. and. Hz). The main difference between this study and that by Malagnini et al. (8) stands entirely in the characteristics of the data sets. Whereas the data set of this study is made of high-quality, broadband seismograms from a dense regional network, recorded entirely during an important seismic sequence, the one used by Malagnini et al. (8) was made of short-period seismograms recorded during a time window of background seismicity. The quality of the C The Authors, GJI, 84, Geophysical Journal International C RAS Downloaded from on 5 July 8

5 Earthquake-induced GM in the Apennines 39 Figure. (a) Broad-band stations of the INGV national network that were used in this study (triangles). Open triangles indicate stations that only entered in the study of wave propagation in the Central Apennines. Solid blue triangles indicate the stations located within 8 km of epicentral distance from L Aquila, for which the quality of the recorded data allowed the calculation of the absolute site term at all the three components of the ground motion. Red stars indicate the locations of the 7 evens of the sequence that provided the data set. Green solid triangles indicate the stations used to study the source scaling. If the same station was to be marked with both solid blue and solid green symbols, two triangles are used, the green one being rotated upside-down. (b) The events of the Colfiorito seismic sequence of are shown with the white star (main shock) and with the black dots included into the region enclosed in the drawed oval (aftershocks M w 4+, used by Malagnini et al. 8, who used the MedNet stations AQU and CII for the quantification of the source scaling. From Malagnini et al. 8, modified). digital data is extremely high in the first case, and all the events had a moment tensor solution of high standard that allowed the absolute calibration of an excitation model based on a single parameter, the Brune stress drop (Brune 97, 97), with the special meaning defined by Malagnini et al. (a). Moreover, most of the events of the L Aquila sequence were recorded by most, if not all, of the seismic stations highlighted in blue in Fig. (a). The sampling geometry of this study is thoroughly described by Figs and (a). The quality of the digital data used in the study of 8, on the contrary, is that of a high-quality regional network of a previous generation, whose digital recorders were equipped with short-period seismometers. Many small events in the old data set C The Authors, GJI, 84, Geophysical Journal International C RAS Downloaded from on 5 July 8

6 33 L. Malagnini et al. Regional Attenuation (log[d(r,f)]) 5.5 Hz Hz Hz 7.5 Hz Hz 5.5 Hz Hz 5.85 Hz 5 5. Hz 5 7. Hz Hz 5.4 Hz 5.5 Hz Hz Hypocentral Dist. (km) Figure 3. Horizontal and vertical coda-normalized attenuation data (see Malagnini et al. a) were obtained by normalizing the peak values of narrow bandpass-filtered waveforms with their rms-average values at 4 s into the coda. Piecewise linear trends of all distributions were forced to pass through the null value at an arbitrary reference distance of At a specific central frequency, f c, bandpass filters were 4 km. Central frequencies are indicated in each frame. made of a high-pass filter with corner at (/ )fc, followed by a low-pass filter with corner at f c. All the plotted data points passed specific S/N criteria. Data distributions show clear attenuation trends that will be better quantified in Fig. 4, after a set of regressions will be carried out over the original peak values. The most crowded frames contain about data points. were recorded by only a few stations, generally at local distances. With respect to the sampling geometry of the new data set, all the sources were concentrated on a single, small fault system, with the stations evenly distributed, with respect to azimuth and hypocentral distance, around the epicentral area of the 9 L Aquila earthquake. The old data set, on the contrary, represents the low-level background seismicity of the region (M wmax = 4.), with a crisscrossing geometry of the source receiver paths that allowed excellent crustal sampling. Both studies, old and new, had strengths; what makes the present one particularly valuable is the availability of a large number of events, each one with tens of recordings from high-quality digital stations equipped with broad-band sensors that could also be used for the determination of the moment tensor solution. We stress the fact that the main point of this work is not the reappraisal of the seismic excitation/attenuation in the Central Apennines. What is important to us is to demonstrate that the two different sequences of Colfiorito ( ) and L Aquila (9) shared very similar scaling characteristics (see the following section), and to justify the use of the source scaling available for Colfiorito to successfully predict the strong ground motions induced by the L Aquila main shock. However, given the availability of an excellent new set of broadband waveforms, a very limited effort was sufficient to re-evaluate the crustal attenuation in the region, and to obtain a complete reappraisal of the predictive relationships for the Central Apennines. S O U RC E S C A L I N G O F T H E L AQ U I L A SEQUENCE Above the magnitude range sampled by our data set, a necessary ingredient for the prediction of the strong ground motions is the quantification of the source scaling, in the hypothesis that the latter is the same throughout a tectonically homogeneous region like the Central Apennines. In what follows, the source term is modelled with a simple Brune source spectrum. We can summarize our previous findings by saying that the stress parameter (i.e. the Brune stress drop) that we needed to describe the Colfiorito sequence was MPa at M w 6., and strongly decreased with decreasing moment magnitude, down to about 5 MPa at M w 4.. Malagnini et al. (8) envisioned a saturation of the stress parameter describing the source scaling at magnitudes beyond a threshold M w 5.5. If the L Aquila and Colfiorito seismic sequences share the same behaviour, as might be expected since they share the same tectonic setting, then accurate ground motion predictions can be made using the crustal attenuation obtained in this study, coupled with the source scaling observed for Colfiorito by Malagnini et al. (8). C The Authors, GJI, 84, C RAS Geophysical Journal International Downloaded from on 5 July 8

7 Earthquake-induced GM in the Apennines 33 log(r/4)+d(r) Aquila9 H Comp Band Pass D(r) for f n f n (Hz) HYPOCENTRAL DISTANCE (km) Figure 4. Empirical regional attenuation experienced by the narrowbandfiltered amplitudes of the ground motion, at the central frequencies indicated. Filtering is obtained using a high-pass filter with a corner at (/ )f c, followed by a low-pass filter with corner at f c. Lines in colour indicate the results obtained from the regressions at the different frequencies (formal error bars are also indicated). Black lines in the background are obtained with the attenuation model described by eqs () (4). All lines are normalized by a /r decay (the horizontal dashed line represents the /r decay). Results displayed in Fig. 5 (seismic moment, M, versus corner frequency, f ) demonstrate that the physics of faulting in the two areas should be similar. Malagnini et al. (8, a) hypothesized that a progressive dynamic weakening took place during the Colfiorito seismic sequence, due to thermal pressurization of pore fluids. One should notice that the main difference between the two sequences, for what concerns Fig. 5, is the presence in Colfiorito of multiple main shocks with 5. M w 6., whereas the L Aquila sequence had a single main shock. STRONG-MOTION PREDICTIONS We verified the close similarity of the Colfiorito sequence source scaling with that of L Aquila sequence, and used it to predict the strong ground motion induced by the L Aquila main shock, together with the crustal attenuation developed in this study. The observed PGA and PGV for the L Aquila main shock (M wcoda = 6.5, see later) are shown in Figs 6(a) and (b), respectively. The figures show the theoretical predictions based on the results of this study for the Generic Rock Site (Boore & Joyner 997), and from the strongmotion relationships by Sabetta & Pugliese (996). Predictions are given in terms of medians values ±σ. Predictions by Akinci et al. (b), computed using the ground motion model developed by Malagnini et al. (8), are only slightly different from the ones obtained in this study, and fit quite well the recorded strong motion data up to a distance of km. Figs 7(a) (d) show the spectral accelerations (SAs) observed during the main shock at the three frequency bands that are used into the ShakeMap R package, and for the extra frequency of. Hz. The excellent agreement between data and predictions from our model shown in Figs 6(a) and (b) and Figs 7(a) (d), allows a comprehensive evaluation of the performance of our ground motion model, in a much broader frequency band than that relative only to peak accelerations and velocities. We point out that ShakeMap R uses also the parts of the predictive relationships, given in the Electronic Supplement, about PGAs and PGVs. Due to the broadband character of the response of the damped single-degree-of-freedom oscillator, the spectral accelerations at the extra frequency of. Hz that has been investigated in Fig. 7(d) are not very different from the ones at 3. Hz. Nevertheless, the predicted spectral accelerations at. Hz (5 per cent damping) show, again, an excellent agreement with the observations. It is worth repeating that the quality of our ground motion model at high-frequency is exceptionally high, as it must be clear by looking at the lines in colour of Fig. 4 (a series of almost perfect fits up to Hz). We strongly stress the role of RVT in defining our ground motion model. Due to the application of RVT, the attenuation model shown in Fig. 4 contains (embedded in the black lines of Fig. 4, and in the numbers provided with the Electronic Supplement) not only the spectral attenuation model described by eqs () (4), but also the Figure 5. Left-hand panel: M versus f plot for some of the events of the L Aquila seismic sequence (this study). Oblique lines represent constant Brune stress drops (i.e. self-similar distributions). The main shock of the sequence clearly deviate from the self-similar trend of its aftershocks. Measurements relative to four foreshocks of the sequence are indicated with black symbols. Right-hand panel: similar plot for the Colfiorito sequence (modified from Malagnini et al. 8). C The Authors, GJI, 84, Geophysical Journal International C RAS Downloaded from on 5 July 8

8 33 L. Malagnini et al. Figure 6. (a) Predictions of peak ground acceleration (PGA) for the L Aquila main shock (M w 6.5) and comparison with the observed data. Solid lines refer to the predictions calculated in this study (median ± σ ), whereas dashed lines refer to Sabetta Pugliese (996, SP96 in the figure). (b) Same as in frame (a) but for peak ground velocity (PGV). The agreement of the ground motion model presented in his study with the observations gathered during the main shock allow an objective judgment of the model s performance. Observed PGAs and PGVs are characterized, when available, by their Eurocode 8 class (symbols in colours). Figure 7. Predictions of spectral acceleration (SA) for the L Aquila main shock, compared with the observations at four different frequencies (.33,., 3. and. Hz). Frames (a), (b) and (c), corresponding to.33,. and 3. Hz, are used in the ShakeMap R software package, whereas frame (d) has been included, both in the picture and in the Supporting Information, in order to provide: (i) a complete proof of the validity of the ground motion predictive relationship and (ii) an extra frequency that may be useful for interpolating predictions. details of the frequency-dependent dispersion of the seismic waves in Central Apennines, which is quantified by using a frequencyand distance-dependent effective duration of the filtered ground motions. The latter has been used in the definition used by Raoof et al. (999): for each filtered recording, the time window starting at 5 per cent of the integrated seismic energy that follows the S-wave arrival, and ending when the 75 per cent level of the integrated seismic energy is reached. C The Authors, GJI, 84, Geophysical Journal International C RAS Downloaded from on 5 July 8

9 Earthquake-induced GM in the Apennines 333 Herrmann & Malagnini (9) emphasized the importance of surface waves in low-frequency ground motions (for frequencies up to. Hz), even at relatively short distances. It follows that scaling relations must reflect the strong contributions of surface wave to low-frequency ground shaking, and not only that delivered by direct S waves. We believe that an important strength of our prediction tool stands in the ability to assign the proper weights at all distances to the main contributors of the ground shaking: surface and direct S waves. Malagnini et al. (8) used 6 selected weak-motion waveforms from 476 small events (M 4.), recorded at distances up to km by three-component digital seismic stations. The source scaling for the Colfiorito sequence was investigated using broadband seismograms recorded at the two MedNet stations AQU and CII, from events with moment magnitudes ranging from M 4to6. Figs 6(a) and (b), and Figs 7(a) (d) demonstrate the following:. Weak-motion based attenuation models, when coupled with information on the source scaling obtained from the analysis of broadband seismograms (again, weak-motion data), may be used to accurately predict the ground motion (weak and/or strong) in the linear regime, at moment magnitudes much larger than the ones of the data set used to characterize source excitation and regional wave propagation. The study on the extended San Francisco Bay Area by Malagnini et al. (7) demonstrated that extrapolations may successfully be attempted up to M w 7. Beyond such a moment magnitude, seismic events usually get very complex, and our pointsource radiation model may be too simplistic for the high-frequency part of the spectrum.. Source scaling of two distinct sequences in the Central Apennines share very similar characteristics. This is not a trivial result. On the contrary, it is likely that for events within homogeneous regions, the case described in this study is of general relevance. Malagnini et al. (a) hypothesized that the seismic source scaling is modulated, through dynamic lubrication, by the pore fluids trapped within the fault core, and provided evidence for an abrupt change in the physics of faulting beyond a magnitude threshold (M w ), where a break in self-similarity seems to affect all seismic sequences (see also Mayeda et al. 7). About the L Aquila main shock, Lucente et al. () described evidence that the M w 6.5 main event of 9 April 6 has been driven by the complex migration of fluids started on 9 March 3 by a M w 4.8 event. A similar fluid migration was observed during the Colfiorito seismic sequence (Miller et al. 4). 3. Despite the similar scaling, the two sequences showed different behaviors: the Colfiorito one was characterized by the presence of multiple main shocks (Amato et al. 998), whereas the L Aquila sequence has a single main shock. Modelling and interpreting such different behaviours, however, is beyond the scope of this study. 4. Some of the high-frequency observations shown between and 8 km in Fig. 6(a) and Figs 7(c) (d) are anomalously low, due to extended-source effects (Akinci et al. b). Such anomalies cannot be taken into account by our isotropic, point-source-based predictive model. The Supporting Information to this paper is given in form of a table of peak values (PGA, PGV and SA at.33,., 3. and. Hz), as a function of hypocentral distance, between and km, and of moment magnitude, between M w. and M w 7.. In such a table, the increments in hypocentral distance and moment magnitude are. km and. M w units, respectively. Such a table can be used directly with ShakeMap R, for earthquakes occurring throughout the Central Apennines (most probably, the presented ground motion model works throughout the entire mountain belt of the peninsular Italy, including the Northern Apennines, and excluding the Calabrian Arc). COMPARISONS BETWEEN GROUND MOTION PREDICTIONS FROM DIFFERENT REGIONS OF THE WORLD Figs 8(a) and (b) show the predicted peak ground motions for four different regions of the world: from very active young crust (the Apennines, this study, and Central Japan, Malagnini et al. b), to a cratonic region like Western India. Intermediate environments may be represented by the Eastern Alps, in which the stable crust of the Africa foreland (the Adria microplate) is overthrusted by the younger Alpine units of northeastern Italy (Amato et al. 99). Ground motion predictions obtained from weak-motion data in the four tectonic regions just described are compared against each other Peak Ground Acceleration (g) M 5. W M 6.5 W India (Bodin et al., 4) N-E Alps (Malagnini & al., ) Japan (Malagnini et al., b) Central Apennines (present study) Bommer & al. (7) Sabetta & Pugliese (996) Joyner and Boore distance (km) Peak Ground Velocity (m/sec) M 5. W M 6.5 India (Bodin et al., 4) N-E Alps (Malagnini & al., ) Japan (Malagnini et al., b) Central Apennines (present study) Akkar & Bommer (7a) Sabetta & Pugliese (996) Joyner and Boore distance (km) W Figure 8. Predictions of peak ground accelerations (PGA, g) and peak ground velocities (PGV, m s ) for different regions of the world: India (red lines, Bodin et al. 4); N E Alps (blue lines, Malagnini et al. ); Japan (Malagnini et al. b) and black (Central Apennines, this study). Predictions obtained using Bommer et al. (7), Akkar & Bommer (7) and Sabetta & Pugliese (996) are also shown. See main text for more details. Similar comparisons can be made for spectral accelerations (SA) using the results presented in this study, and comparing them against predictive relationships like (among many) those by Akkar & Bommer (7). C The Authors, GJI, 84, Geophysical Journal International C RAS Downloaded from on 5 July 8

10 334 L. Malagnini et al. in Figs 8(a) and (b). The figures include predictive relationships developed on the European and the Middle East strong motion data sets (Akkar & Bommer 7; Bommer et al. 7), as well as a predictive relationship obtained by regressing an Italian data set of strong-motion waveforms (Sabetta & Pugliese 996). Weak-motion-based ground motion predictions of Figs 8(a) and (b) were obtained for two moment magnitudes (M w 5. and 6.5) using the generic rock sites by Boore & Joyner (997), coupled with a high-frequency filter exp( πκ f ), with κ =.35 sec. The same two magnitudes are used to obtain similar predictions from the strong-motion-based equations. The choice of these magnitudes allows the discussion of two features of the ground motion that may be of general importance. The lower magnitude limit (M w 5.) sets the initiation of substantial structural damage for old buildings made with traditional construction techniques in Mediterranean countries like Italy. The higher magnitude limit (M w 6.5), most probably, marks the transition to large seismic events that are likely to show complex behaviour, and thus should be handled with predictive relationships calibrated on large earthquakes. However, Malagnini et al. (7) showed that successful predictions obtained with our methods could be extented to M w 7.. The differences observed in the ground motion levels at short Joyner-Boore distances, R jb, are due to the stress parameter. At M w 5., the decay of the predicted peak amplitudes (for increasing distances from the source) is always stronger (i.e. steeper curves) than that observed at M w 6.5. In fact, the peak values of the ground motions induced by larger magnitudes are carried by lower dominant frequencies, and for this reason are less sensitive than peak motions from small earthquakes to a given anelastic attenuation structure. Due to the spectral characteristics of source excitation and crustal path attenuation, peak values predicted at M w 6.5 are much closer to one another than their counterparts at M w 5.. This is because a region-specific spectral scaling characterizes each data set shown in Figs 8(a) and (b). Each source scaling shows a saturation level for the Brune stress drop at large moment magnitudes (roughly between and5mpaabovem w 5.5), as might be expected to avoid unrealistic values for this parameter. Again, at larger magnitudes, the induced ground motions are carried by lower dominant frequencies, and are not very sensitive to differences in the anelastic attenuation. Different steepnesses may also be due to differences in the crustal structure, i.e. in the effective attenuations due to the combination of geometrical spreading and anelastic attenuation. ABSOLUTE SITE TERMS The complete calibration of the regional seismic network cannot be accomplished without the accurate quantification of the frequencydependent spectral distortion induced by the shallow geology at the recording sites (i.e. shallow impedance layering, especially in sediment-filled valleys, lateral heterogeneities of the subsurface structures, anelastic attenuation, topography, etc.). To achieve such a goal, we used the technique implemented and applied by Malagnini et al. (4, 6, 7). It is necessary to emphasize that our absolute site terms are strictly for linear motions, and may not be valid to describe the large shaking expected near the source during large earthquakes. Akinci et al. (b) used a different approach for the computation of the absolute site terms of the accelerometric network that recorded the L Aquila main shock. They did not observe obvious non-linearities in the local response of the shallow geology, even at the sites located in the epicentral area. Possible exceptions were AQV and AQK: two stations located within the L Aquila urban area, on the hanging wall of the fault, where hints of nonlinear behaviour could be found. Results are shown in Fig. 9, where we plot the individual components of the inverted absolute site terms. The latter are defined as the spectral distortion experienced by the observed ground motions, in excess to the regional attenuation of Figs 3 and 4 (eqs 4). Vertical site terms are indicated by green colour, in blue are north south site terms, and curves in red are relative to east west site terms. Black lines indicate the Boore & Joyner (997) generic rock site, multiplied by a factor of to take into account the free-surface effect that is embedded into the empirical terms. We show the effects of two different high-frequency filters to the generic rock site, whose parameters are: κ =. s (upper line), and κ =.35 s (lower line). Since no specific studies are available at the stations of the INGV National Seismic Network to check our measurements against (e.g. shear wave velocity profiles), we indirectly check the validity of our results by checking the observed S-wave Fourier amplitude spectra, once they are corrected for the effects of: (i) crustal propagation (eqs 4) and (ii) absolute site distortion (Fig. 9). An important parameter that can be obtained from the corrected source spectra, averaged over all the recording stations, is that on the amplitude of the spectral plateau of the displacement spectrum (i.e. the moment magnitude of the event). Because we do not have detailed information on the recording sites to compare against the results plotted in Fig. 9 (see, for example, Malagnini et al. 997), we are not going to give interpretations of the individual absolute site terms. The scope of our study is the determination of these objects, to be used for accurate spectral corrections of the observed spectra of direct S waves. AUTOMATIC, FAST AND ACCURATE COMPUTATION OF MOMENT MAGNITUDES We recently developed an automatic procedure, coded as a SAC macro, to go through the attenuation data sets, and to compute displacement spectra corrected for the regional attenuation. In 7, the algorithm was integrated with the spectral correction relative to the absolute site terms (see Malagnini et al. 7), making the automatic estimates of moment magnitude much more accurate. The data set studied in this paper allows more accurate estimates of the spectral plateaus, and Fig. shows the comparison of our S-wave-based moment magnitudes (M w S) against our reference, coda-based moment magnitudes (M wcoda ). The three oblique lines in Fig. indicate the correspondence, and the two offsets of ±. magnitude units. Due to the characteristics of the observed S- wave spectra, corrected only for the instrument response, and not for the effects of regional wave propagation (for example, the variable S/N ratios at low frequencies, especially in a fairly broad frequency band centred around 8 s, may be dominated by the microseismic noise), such an extremely stable and accurate set of automatic M w estimates indicate that we completely understand the attenuation of S waves in their crustal paths, as well as the site-specific spectral distortions. Moreover, the fact that the accuracy of our moment magnitudes is about the same throughout the entire range available in our data set tells us that the spectral corrections must be well defined in a wide range of frequencies (say, roughly, between.5 and Hz). C The Authors, GJI, 84, Geophysical Journal International C RAS Downloaded from on 5 July 8

11 Earthquake-induced GM in the Apennines AQU - ASSB - CAFR - - CAMP CESI - CESX log (Amplitude) FAGN - FDMO - FIAM - GUAR - GUMA - INTR LNSS - LPEL - MNS - - MTCE NRCA - OFFI POFI RMP TERO TRTR VVLD Z N E *BJ97GR k=. k= Frequency (Hz) - Figure 9. Absolute site terms for the three components of the ground motion of the stations indicated with solid blue triangles in Fig.. Green curves represent vertical site terms; blue and red ones represent, respectively, the site terms affecting the N S and E W components of the ground motion. Black curves represent the Boore & Joyner (997) generic rock site, coupled with the high-frequency filter: exp( πκ f ). Two values for the parameter κ are used:. s (upper black line) and.35 s (lower black line). Station AQU is from MedNet (the MEDiterranean NETwork maintained by INGV). CONCLUSIONS We present a reappraisal of the characteristics of wave propagation in the Central Apennines. The study was performed through a set of regressions, carried out on a data set of 777 single-component waveforms (459 vertical and 858 horizontal recordings), selected from the database generated by the INGV National Seismic Network during the L Aquila seismic sequence of 9. By using some of the gathered seismograms, and a simple spectral ratio technique for the investigation of the regional source scaling, we found strong similarities with the Colfiorito seismic sequence of We showed that, within the error bars, the L Aquila sequence strongly departs from self-similarity. Given such information, we used the new regional attenuation model calculated in this study, coupled it with the absolute source scaling obtained by Malagnini et al. (8), and successfully predicted the strong ground motions that were observed during the main shock of 9 April 6. Based on the described results, it looks as if the weak-motion studies may be of great significance for the accurate prediction of strong ground motions. A requirement for the extrapolation of results to larger moment magnitudes is that self-similarity is abandoned as an aprioricondition for the regional seismicity, at least for the L Aquila (9) and for the Colfiorito ( ) seismic sequences. Departure from self-similarity has generally been observed on the sequences studied by our research group, although self-similar sequences are infrequently observed. For example, the sequence triggered by the 4 Parkfield event (Mayeda and Malagnini, in preparation) was practically self-similar. We stress that it is our ability to reduce the uncertainties on the scaling parameters (Malagnini et al. a) to allow the discrimination between self-similar and non self-similar cases. For a complete calibration of the seismic network in the region, we calculated the absolute site terms for 3 stations of the INGV national network in Central Apennines. Using the calculated crustal attenuation, and the absolute site terms at the cited subset of recording sites, an automatic code accurately computed moment magnitudes for all the events in the data set. Comparison of the automatic magnitudes against independently obtained coda-based moment magnitudes, demonstrates that our regional attenuation model allows accurate spectral corrections. The described automatic tool could be easily implemented at INGV for routine activities, and we strongly suggest the planning of similar studies to be performed on dense national networks. Finally, weak-motion-based predictions of peak ground motions in different regions were compared against each other at M w 5. and 6.5. Results showed significant regional differences, both in terms of source scaling and of attenuation of the seismic waves. C The Authors, GJI, 84, Geophysical Journal International C RAS Downloaded from on 5 July 8