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## Earth Sciences Research Journal

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*Print version* ISSN 1794-6190

### Earth Sci. Res. J. vol.10 no.2 Bogotá July/Dec. 2006

** **

**SEISMIC HAZARD MAP FOR THE ITALIAN TERRITORY USING MACROSEISMIC DATA**

**Augusto A. Gómez C. **

Istituto Nazionale di Geofisica e Vulcanologia, sezione MilanoVia Bassini 15, 20133, Milano, Italy

gomez@mi.ingv.it

**Abstract**

A seismic hazard map, in terms of macroseismic intensity, is proposed for the Italian continental territory and Sicily, which has a 10% probability of exceedance in 50 years. The methodology used here was first proposed by Cornell (1968), which requires information about the location and seismicity rates within each of the defined seismogenic zones, as well as an attenuation model. In particular, it is proposed an original macroseismic intensity attenuation model derived from the Italian macroseismic database DBMI04. The seismic hazard map, obtained in terms of intensity, was subsequently transformed into PGA by means of a linear relation between intensity and PGA, in order to compare it with the national seismic hazard map MPS04.

**Key words:** Probabilistic seismic hazard, macroseismic data, seismogenic zonation, intensity attenuation, Italy

**Resumen**

Se propone un mapa de amenaza sísmica, en términos de intensidad macrosísmica con un 10% de probabilidad de excedencia en 50 años, para Italia continental y Sicilia. La metodología usada fue propuesta originalmente por Cornell (1968), la cual requiere información acerca de la localización y tasas de sismicidad dentro de cada una de las zonas sismogénicas definidas, como también del modelo de atenuación. En particular se propone un modelo nuevo de atenuación de la intensidad macrosísmica desarrollado a partir de la base de datos macrosísmica italiana DBMI04. El mapa de amenaza sísmica obtenido fue transformado en PGA usando relaciones lineales entre la intensidad y PGA para luego compararlo con el mapa nacional de amenaza sísmica MPS04.

**Palabras clave:** Riesgo sísmico probabilístico, datos macrosísmicos, zonación simogénica, atenuación de intensidad, Italia.

**1. Introduction**

Seismic hazard is generally assessed in terms of peak ground acceleration (PGA) for deriving engineering design parameters for new buildings. However, the short time interval covered by the instrumental records can be a problem in regions where the earthquake cycle is rather slow and seismicity not very frequent. In terms of seismic hazard assessment, this can affect the evaluation of seismicity rates in the data sample, because they may not be representative of seismogenic processes. The low density of recording stations determines, in some parts of the world, a limited availability of the strong motion data needed to study the attenuation. It is clear that in these cases the macroseismic data are very important as they may represent the only available data.

Macroseismic intensity is defined by Grünthal (1998) as a classification of the severity of the ground shaking on the basis of observed effects in a limited area. As a consequence of this definition, the macroseismic intensity is a parameter that could be used to evaluate expected ground shaking.

In Italy, as in other countries, most of the earthquake catalogue data are derived mainly from macroseismic studies (Gruppo di Lavoro CPTI, 2004). The historical research has contributed to the knowledge of the historical seismicity dating back 1000 years (Stucchi et al., 1991; Albini et al., 2004); the earthquakes occurred before the 20th century and many consecutive events are only qualified with macroseismic intensity data. In the last years in Italy, a number of macroseismic databases have been proposed (Monachesi and Stucchi, 1997; Boschi et al., 2000; Gruppo di Lavoro DBMI, 2005). This wealth of data permits to assess the seismic hazard in terms of macroseismic intensity.

A seismic hazard assessment, based on historical earthquakes concerning the local history of seismic effects (site approach), has been proposed by Albarello et al. (2002), Albarello and Mucciarelli (2002), Mucciarelli et al. (2000), Kijko et al. (2001, 2003); Monachesi et al. (1994), Gaull and Kelsey (1999) and Basili et al. (1990).

Slejko et al. (1998) elaborated a map of seismic hazard of Italy, in terms of macroseismic intensity, using the standard probabilistic approach (Cornell, 1968), the NT 4.1 earthquake catalogue (Camasi and Stucchi, 1996), the seismogenic zonation published by Scandone (1997), and two intensity attenuation models (Grandori et al., 1987; Berardi et al., 1993) without introducing the standard deviation.

This paper presents a new seismic hazard map of Italy mainland and Sicily derived by using updated data, a new derived intensity attenuation model, and the Cornell methodology as implemented in the SeisRisk III code (Bender and Perkins, 1987).

Table 1 describes the input elements used to evaluate the seismic hazard. The first three elements were taken from the national seismic hazard map released in 2004 (Gruppo di Lavoro MPS, 2004); in particular, the CPTI04 earthquake catalogue (Gruppo di Lavoro CPTI, 2004), the ZS9 seismogenic zonation (Figure. 1), and the historical (CO-04.2) and statistical (CO-04.4) completeness time intervals. The other two elements (e.g., seismicity rates in terms of epicentral intensity (I_{0}) and intensity attenuation models) have been computed by Gómez (2006).

This author presents an original macroseismic intensity attenuation model derived from the most recent Italian DBMI04 macroseismic database (Gruppo di Lavoro DBMI, 2005) that includes different relationships, which are developed in section 2.

In section 3, a logic tree approach is used to explore some possible alternatives of epistemic character regarding the catalogue completeness, seismicity rates, and the attenuation models.

In the same section, it is described the modification introduced in SeisRisk III (Bender and Perkins, 1987) to compute hazard in terms of macroseismic intensity. The obtained intensity values have been transformed to PGA by using specific empirical relationships developed for Italy (Margottini et al. 1992; Faccioli and Cauzzi, 2006).

**2. Intensity attenuation models**

**2.1. State-of-the-art**

Macroseismic intensity attenuation is described by Musson and Cecic (2002) as the rate of decay of shaking with distance from the epicentre. The literature provides a number of empirical relationships that model the intensity decay in varied regions of the world as a function of epicentral or hypocentral distance.

The first model was proposed by Kövesligethy (1906) at the beginning of the last century and assumes that the energy of seismic waves declines due to geometrical spreading and absorption of the geophysical media. Mathematically, the attenuation of intensity is written as the difference between epicentral and site intensity. Where (D) is a function of epicentral distance in km, (h) is the focal depth in km, and (α) is a free parameter.

In Blake (1941), the Kövesligethy relationship is simplified eliminating the linear term (absorption coefficient) but letting the coefficient of the logarithm (geometrical coefficient) as a free parameter (b). Following Blake (1941), other authors such as Howell and Schultz (1975), Chandra et al. (1979), Ambraseys (1985), and Dowrick (1992) proposed attenuation intensity models as special cases of the Kövesligethy relationship introducing additional simplifications.

Table 2 illustrates some of the studies proposed in literature; for further references see: Neumann (1954), Ergin (1969), Grandori et al. (1991), Peruzza (2000), Gómez and Salcedo (2002), Castro et al. (2002), ECOS (2002), Fäh et al. (2003), Carletti and Gasperini (2003), Albarello and D'Amico (2005), Azzaro et al. (2006).

**Table 2**

The macroseismic intensity attenuation models proposed in the literature are either logarithmic or non-logarithmic (linear, polynomial).

The logarithmic models are derived assuming empirically that the macroseismic intensity is proportional to the logarithm or to a power of the seismic energy density (Howell and Schultz, 1975). The limitation of these models is that the correlation with macroseismic data is not good. For instance, the Kövesligethy relationship cannot be used to estimate the coefficients of geometric spreading and absorption, and at the same time estimate focal depth (h) (Ambraseys, 1985). In Italy, this type of model has been proposed, among others, by Albarello and D'Amico (2004). Their relation describes the intensity decay as a function of the epicentral intensity and hypocentral distance using four free parameters.

Non-logarithmic models result from a statistical approach that allows finding the best fit of the macroseismic data. Two main studies could be mentioned for Italy: Berardi et al. (1993) and Gasperini (2001). The first proposed a simple attenuation model called the Cubic Root Attenuation Model (CRAM) with two free parameters, and the latter proposed a bilinear attenuation model (Table 2) with three free parameters.

The CRAM functional model (Berardi et al., 1993) has been chosen in the present study to model the attenuation of Italian macroseismic intensity data:

It assumes that the intensity decay, expressed by the difference between epicentral and site intensity, is proportional to the cubic root of the epicentral distance (D), without dependence on the earthquakes focal depth. The CRAM is as fairly simple model as it uses only two free parameters. However, it provides a better fit of the macroseismic data compared to other models such as the logarithmic and square root (Berardi et al., 1993).

**2.2. Macroseismic data set**

The Italian macroseismic database DBMI04 (Gruppo di Lavoro DBMI, 2005) has been considered in the present study. DBMI04 contains about 60,000 intensity data points (IDP), in MCS scale, related to 1042 earthquakes occurred from 217B.C. to 2002.

In order to derive an intensity attenuation to be used in Probabilistic Seismic Hazard Analysis (PSHA), a careful selection of the macroseismic data was carried out considering diverse criteria. Table 3 describes 13 criteria to filter the intensity records not to be used. First, the macroseismic observations of the Etna volcanic zone (ZS936 seismogenic zone of ZS9) are eliminated because the propagation of the seismic energy in this zone is different than other tectonic zones (Del Pezzo et al., 1987; Ciccotti et al., 2000). Other filters are used to remove earthquakes characterised by epicentral intensity I_{0}<7, site intensity I_{s}<3, number of macroseismic observation N_{IDP}<13 and epicentres outside of ZS9.

**Table 3**

The IDP of earthquakes that are not well known have also been disregarded. For instance, the 1456 and 1914 earthquakes are described (Meletti et al., 1988; Meloni et al., 1988) as deep events, which are not easy to use in a statistical study of the macroseismic intensity attenuation because they are distributed over a very large area.Another criterion is based on the distance: for every I_{0}, the local distance for I_{s}=4, called Dist_I_{s4}, is determined using the relationship of Albarello and D'Amico (2004); for every I0, IDP with D≥Dist_I_{s4} are rejected.

After applying the 13 criteria (Table 3), the intensity database is reduced to 20,873 IDP related to 212 earthquakes that occurred from 1279 to 2002. Figure 2 shows the epicentral distribution of the 212 selected earthquakes.The distribution of the selected IDP for each epicentral intensity class and for each site intensity class are shown in tables 4a and 4b respectively. The largest number of IDP belongs to the I0 7MCS class and the Is 5 MCS class.

Figure 3 shows the frequency distribution of the intensities as a function of epicentral distance, which indicates that the majority of IDP are located within 100km from the epicentre.

The IDP of the volcanic areas are divided into two datasets

:• The first corresponds to the ZS921 (Etruria), ZS922 (Colli Albani) and ZS928 (Ischia-Vesuvio) seismogenic zones;

• The second corresponds to the ZS936 (Etna) seismogenic zone.

From these two datasets, a selection of macroseismic data was used considering the criteria described in table 5, resulting in a subset of 716 IDP for Ertruria, Colli Albani and Ischia-Vesuvio and 1328 IDP related to 54 earthquakes for the Etna zone (ZS936).

**2.3. Development of macroseismic intensity attenuation models**

According to Bommer et al. (2003), the combination of seismic source characterisation, including rupture mechanism and ground-motion prediction equations that explicitly account for style-of-faulting, should produce refined estimates of the seismic hazard. The most recent seismic source zone model of Italy, called ZS9 (Gruppo di Lavoro MPS, 2004), includes for each zone an average depth of the seismogenic layer, and an indication of the predominant faulting style (Figure. 1). This information was used to assess the seismic hazard of Italy with regional attenuation relationships, and with the Bommer et al. (2003) style-of-faulting scaling factors.

In analogy with the PGA attenuation relationships, and using the information provided by ZS9, Gómez (2006) derived a set of macroseismic intensity attenuation relationships, called Cub05-Reg., from the 20,873 IDP described in the previous section. The set includes:

1. A valid relationship for the entire Italian territory (CUB05-General);

2. A relationship for areas with predominant normal style-of-faulting (PFM-Normal);

3. A relationship for areas with predominant strike-slip and reverse-style-of-faulting (PFM-Strike-Slip+Reverse);

4. A relationship for the Etna volcanic zone (ZS936).

Table 6 summarizes the values of the parameters of equation 1 obtained for each attenuation relation and their relative standard deviation. The macroseismic data have been fitted by the least squares method using the KaleidaGraph software (Synergy Software, 2005)

Independent attenuation relationships for areas with reverse and strike-slip style faulting respectively were also derived, but they have been disregarded because the data sample is not statistically significant (Gómez, 2006). Similarly, attenuation relations for the ZS921, ZS922 and ZS928 volcanic areas have been rejected because they are not significantly different from CUB05-General.

Figure 4a shows a plot of the intensity decay (∆I=Io-I) as a function of epicentral distance (blue curve), along with the 20,873 IDP (small grey points) used to obtain this relationship (CUB05-General) with a standard deviation of ±0.94. Figure 4b shows the ∆I-residuals (observed-computed) as a function of the epicentral distance grouped in 5 km classes for the CUB05-General relationship.

The intensity attenuation model for predominant normal faulting (PFM-Normal) obtained from 11,393 IDP is shown in figure 5a, while the distribution of the ∆I-residuals as a function of epicentral distance is shown in figure 5b.

The distribution of ∆I residuals for CUB05-General and PFM-Normal models are very similar (Figure 4b and Figure 5b) and show moderate oscillations from 5 to 150 km, meaning that the computed intensities can be considered as a good estimate of the observed intensities. For epicentral distances greater than 150 km, the attenuation models do not provide a good estimate of the intensity observations. In both attenuation models, the standard error given by the 95 % confidence intervals increases for distances greater than 330 km.

Figure 6a shows the intensity attenuation relation for both reverse and strike-slip faulting (5,020 IDP) while in Figure 6b are plotted the ∆I-residuals. In the distance range of 5 to 80 km, the intensity decay calculated with the attenuation relationships overestimates the observed intensities; after 80 km the model tends to underestimate the intensity value decay.

The attenuation relationship for the Etna seismogenic zone is presented in figure 7a and the distribution of ∆I-residuals in figure 7b, which shows a slight increase of the standard error of 10 km of epicentral distance.

Figure 8 shows that the frequency distributions of the ∆I-residuals (observed-computed) obtained from the four relationships described so far (CUB05-General, PFM-Normal, PFM-Reverse and Strike-Slip, Etna) are Gaussian curves (normal distribution). This follows naturally from the fact that intensity equations are written as f(I)=I and not f(I)=Ln I (Musson, 2005). Each Gaussian curve in figure 8 has a standard deviation (Tab. 6) that can be used to model the uncertainty of the ground shaking in hazard studies.

Figure 9 compares the four attenuation models obtained in this study (Tab. 6). Using this, it could be concluded:

1. the Etna relationship shows the highest intensity attenuation, consistently with its peculiar geologic setting;

2. Within the first 30 km of distance, there is not much difference between CUB05-General and PFM-Normal models. After 30km the PFM-Normal model shows that the attenuation is slightly greater than the CUB05-General model;

3. The PFM-Reverse and Strike-Slip model is very similar to CUB05-General within the first 20km, after this distance the attenuation is slightly lower than the CUB05-General.

At a given epicentral distance, PFM-Normal predicts is lower compared with the CUB05-General, whereas PFM-Strike-Slip and Reverse predicts higher values. This is similar to empirically observed data from strong ground motion. However, the classification adopted, based on style-of-faulting, carries implicitly a regionalization: the normal faulting style is found, in fact, along the Apennines, while the reverse faulting style is found in NE Italy and Southern Italy in the Apulian area.

Recent studies by Malagnini et al. (2000; 2002) show that these areas are characterized by different geometric and anaelastic attenuation that leads to a faster decay of the ground motion in central and southern Apennines compared with North and Eastern Italy. The results in figure 9 can be attributed both to the effect of the regionalization and to the style-of-faulting, but it is impossible at this stage to discriminate between them.

Compared to the models proposed by Albarello and D'Amico (2004), Gasperini (2001) and Berardi et al. (1993), the CUB05-General model decreases less rapidly within the first 90 km of epicentral distance (Figure 10).

For distances greater than 90 km, the attenuation of the CUB05-General is greater than Albarello and D'Amico model, but decreases less rapidly than Gasperini (2001) and Berardi et al. (1993) model. For epicentral distances equal to zero, the value of ∆I in CUB05-General tends asymptotically to zero.

**3. Macroseismic intensity hazard assessment**

**3.1. Methodology**

Most seismic hazard software (Bender and Perkins, 1987; Ordaz et al., 2003) is designed to work with PGA or spectral acceleration such as residuals following a normal logarithmic distribution (Sabetta and Pugliese, 1987; Ambraseys et al., 1996; Boore et al., 1997).

When computing seismic hazard using macroseismic intensity, it is important to remember that the residuals of the intensity attenuation models follow a normal distribution (see section 2.3; Albarello and D'Amico, 2004; Musson, 2005).

In the present study, the program SeisRisk III (Bender and Perkins, 1987) has been modified in order to evaluate the seismic hazard by implementing a normal distribution scatter and a scale factor equal to 12.0 (Gómez and Sudati, 2005).

The seismic hazard map, in terms of macroseismic intensity, has been evaluated using the same methodology used by Gruppo di Lavoro MPS (2004) to compute the national seismic hazard of Italy.

Some alternatives of epistemic character have been explored using a logic tree approach:

a) Earthquake catalogue completeness time-intervals determined using either the historical (CO-04.2) or statistical (CO-04.4) approach (Gruppo di lavoro MPS, 2004);

b) Criteria to assess I0max as the maximum epicentral intensity for each seismogenic zone of ZS9;

c) Criteria to compute the seismic rates: activity rates (AR) and Gutenberg-Richter rates (GR);

d) Two groups of intensity attenuation relationships. The first group uses the relationships obtained in Gómez (2006) (Cub05-Reg.) with standard deviation. The second group uses the relationship proposed by Albarello and D'Amico (2004) for all seismogenic zones of ZS9, except the Etna volcanic zone (ZS936), which uses the relationship proposed by Azzaro et al. (2006); the standard deviation of the attenuation models are respectively 1.25 and 0.82.

Figure 11 shows the logic tree and the weighting scheme:

1) The historical completeness CO-04.2 and the statistical completeness CO-04.4 have assigned weights of 60% and 40% respectively;

2) The set of individual seismicity rates (activity rates, AR) (60%) are weighted more than the Gutenberg-Richter rates (GR-rates) and the set of Iomax2 (40%);

3) The weight of the regional attenuation relationship (Cub05-Reg) is greater (67%) than Albarello and D'Amico (2004), and Azzaro et al. (2006) relationships (33%).

**3.2. Map of Imax (10%/50 years; 475-year return period)**

The values of Imax, with a 10% probability of exceedance within a 50-year exposure time, were computed applying the logic tree methodology (Figure 11). Results are given as:

• Distribution of median (50th percentile) of the 8 branches of the logic tree (Figure 12);

• Distribution of 84th percentile (Figure 13);

• Distribution of 16th percentile (Figure 14).

In figure 12, the maximum intensity value is IX, observed in Central and Southern Italy. The minimum value in the Italian peninsula is equal to 6. The values of the distribution of 84th and 16th percentile are not very different (Figure 13 and Figure 14), as they range between 6 and 9 in the first case, and between 6 and 8/9 in the remaining cases.

The difference between the value of the 84th percentile and the median (e.g., the maximum uncertainty on the seismic hazard assessment) can be as high as 0.5. Such moderate difference between the percentiles can be due to the small number of branches (only 8) used in the logic tree, or it may be related to the discrete nature of the intensity data. In this case, adding more branches to the logic tree may not introduce enough variability to determine an increase (or decrease) of the intensity level at a given site.

**3.3. Comparison between the maps in PGA (MPS 2004) and Imax (10%/50years)**

Empirical relationships between macroseismic intensity and PGA are useful for comparing maps such as the one of figure 12 with seismic hazard assessment in PGA. A few studies deal with the relationships between macroseismic intensity and PGA and the majority has been published for the western USA (Neuman, 1954; Gutenberg and Richter, 1956; Trifunac and Brady, 1975; Murphy and O'Brien, 1977; Wald et al., 1999; Boatwright et al., 2001). In Italy, relationships between the macroseismic data and PGA records have been proposed among others by Margottini et al. (1992), Panza et al. (1997; 1999; 2001) and by Faccioli and Cauzzi (2006). Some relationships published in literature are shown in figure 15 as the mean values of the correlation.

The seismic hazard map in terms of intensity shown in figure 12, which represents the Imax with probability of exceedance 10% within a 50-year exposure time, has been converted in PGA values using the relationships of Margottini et al. (1992) (local intensity) and Faccioli and Cauzzi (2006).

Figure 17 shows the converted seismic hazard map representing the weighted mean of the two empirical relationships used according to the scheme proposed in figure 16. Faccioli and Cauzzi (2006) receives a higher weight (67%) compared with the 33% of Margottini et al. (1992), because the dataset used in that study is more recent.

The maximum value is equal to 0.34 g for a site located in Southern Italy. Figure 18 shows the seismic hazard map in PGA (10%/50 years) proposed by Gruppo di Lavoro MPS (2004), where the maximum value is equal to 0.28 g.

Figure 19 shows the difference between the maps shown in figures 17 and 18

:• The positive values (red shades) indicate areas where the values of the converted map are greater than those of the seismic hazard map MPS04 (Gruppo di Lavoro MPS, 2004);

• On the contrary, the negative values (blue shades) indicate areas where MPS04 values are greater than those of the seismic hazard map converted in PGA from Imax.

The smaller differences between the two maps are located in the interval -0.010g to 0.010g (white zones).The areas located outside the seismogenic zones of ZS9 (Figure 19) show greater (up to 0.075) PGA values in the "converted map" than in MPS04. It can be observed that for an epicentral distance greater than 100 km, the macroseismic intensity decays less rapidly than PGA, thus providing higher ground motion values.

In Central and Southern Italy, the average PGA values obtained from Imax are 0.025g greater than the values of MPS04. However, the intensity is a measure of ground shaking, independent of site conditions, while the seismic hazard map MPS04 has been derived specifically for hard ground.

Negative values (up to 0.075g) in North-East Italy, Northern Apennines and Eastern Sicily can be related to the use of regional empirical ground-motion attenuation relations in MPS04.

**4. Conclusions **

Macroseismic data has been used in this study to gain a better knowledge of the macroseismic intensity attenuation and seismic hazard of Italy.

New macroseismic intensity attenuation relationships of regional character for the Italian territory are proposed using the most recent Italian DBMI04 macroseismic database. These includes a valid relationship for the whole Italian territory, a set of relations that account the predominant style-of-faulting (normal, reverse and strike-slip), and a relationship for the Etna volcanic zone (these relationships are shown in Table 6, and are called Cub05-Reg).

Eight years after Slejko et al., (1998), a new seismic hazard map, with 10% probability of exceedance in 50 years in terms of macroseismic intensity, is proposed for continental Italy and Sicily (Figure 12). The calculation of the seismic hazard has taken into account uncertainties of epistemic and random character. This is a regular practice in probabilistic seismic hazard assessment in terms of peak ground acceleration. The hazard map has been deduced by applying the Cornell methodology, and updated input elements such as:

• CPTI04 Earthquake catalogue (Gruppo di Lavoro CPTI, 2004);

• ZS9 Seismogenic zonation (Gruppo di Lavoro MPS, 2004);

• Historical and statistical completeness time intervals (Gruppo di Lavoro MPS, 2004);

• Two sets of macroseismic intensity attenuation models: a regional (Cub05-Reg) and a national (Albarello and D'Amico, 2004; Azzaro et al., 2006) were used for the ZS936 seismogenic zone (Etna zone).

• The computer code adopted to calculate the seismic hazard was SeisRisk III (Bender and Perkins, 1987), which has been modified to be used with macroseismic intensity data (e.g., allowing a normal distribution instead of a normal logarithmic distribution of the residuals).The seismic hazard map proposed concurs with the results obtained by Gruppo di Lavoro MPS (2004).

In fact, the differences between the two maps lies within the range of the uncertainties associated to the hazard evaluation.

**Acknowledgements**

I'm grateful with Massimiliano Stucchi, Carlo Meletti and Paola Albini for their thoughtful suggestion and continuous encouragement, and Valentina Montaldo for reviewing the manuscript and making helpful comments.

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