Bull Earthquake EngDOI 10.1007/s10518-013-9480-1

ORIGINAL RESEARCH PAPER

Seismic microzonation of the central archaeological areaof Rome: results and uncertainties

Alessandro Pagliaroli · Massimiliano Moscatelli ·Giuseppe Raspa · Giuseppe Naso

Received: 11 January 2013 / Accepted: 23 June 2013© Springer Science+Business Media Dordrecht 2013

Abstract The paper summarizes the results of a multidisciplinary study aimed at seismicmicrozonation of the Central Archeological Area of Rome including the Palatine hill, RomanForum and Coliseum. A large amount of subsoil data, available mainly from adjacent subwaylines and from the archaeological superintendence, were collected and used to plan newmultidisciplinary investigations, carried out in 2010–2011. First, the paper describes theintegrated subsoil model aimed at numerical modeling of site effects. The results of equivalentlinear 2D site response analyses carried out on seven representative cross-sections of the areaare then presented and discussed. Ground motion amplification factors defined in termsof Housner Intensity were computed in different ranges of period, covering the differentfundamental vibration periods pertaining to the monuments and structures. The contouringof amplification factor values from all the numerical simulations, based on morphological andgeological constrains, eventually allowed to create microzonation maps. Finally, a sensitivitystudy was carried out to investigate the effects of uncertainties of input parameters and soilheterogeneity on microzonation.

Keywords Seismic microzonation · Site effects · Numerical modeling · Geostatisticalsimulation · Palatine hill

A. Pagliaroli (B) · M. MoscatelliCNR-IGAG, Istituto di Geologia Ambientale e Geoingegneria,Area della Ricerca di Roma 1, Via Salaria km 29300,00015 Monterotondo Stazione, Rome, Italye-mail: alessandro.pagliaroli@igag.cnr.it

G. RaspaDipartimento di Ingegneria Chimica Materiali Ambiente,Sapienza Università di Roma, Via Eudossiana 18, 00185 Rome, Italy

G. NasoDipartimento della Protezione Civile,Via Vitorchiano 2, 00189 Rome, Italy

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1 Introduction

Seismic microzonation (SM) can be defined as the process of mapping the distribution of siteresponse with respect to ground shaking intensity, liquefaction and landslide susceptibility,collating information that can be useful primarily for urban planning and land use manage-ment and also for emergency planning or reconstruction after an earthquake (Ansal et al.2009).

The importance of the issues addressed by SM studies have been recognized for a longtime; however it has been the scientific work conducted over the last 20 years (Fäh et al. 1997;Anastasiadis et al. 2001; Marcellini et al. 2001; Teves-Costa et al. 2002; Finn et al. 2004;Roca et al. 2008; Ansal et al. 2010), that has resulted in significant contributions to develop-ment of guidelines in this discipline (AFPS 1995; CDC 1997, 2008; ISSMGE 1999; DRM2004a,b,c; SMH 2011). In Italy, in order to define methodologies and criteria for produc-tion and use of SM results, the “Guiding Principles and Criteria for Seismic Microzonation”(ICMS 2008) were published in 2008 by the Conference of Italian Regions and AutonomousProvinces and the Italian Civil Protection Department. These criteria are an attempt to cre-ate a national standard for seismic microzonation, based on previous experiences carriedout worldwide and in some Italian Regions, such as Toscana (Regione Toscana 2002) andLombardia (Regione Lombardia 2005). In particular, three levels of SM have been definedby ICMS (2008), depending on the objectives of the work: (i) level 1 is a preparatory levelfor SM studies, generally based on the collection of existing data, which are qualitativelyprocessed to divide the investigated area into zones that are homogeneous in terms of groundshaking intensity, and to identify areas susceptible to ground instability; (ii) level 2 intro-duces simple investigations and a quantitative evaluation generally achieved by simplifiedmethods; (iii) level 3 introduces, on particular issues or areas identified at previous levels,detailed investigation and defines the SM map generally on the basis of the results obtainedfrom numerical analyses aimed to quantify local site effects.

This paper presents the level 3 SM study of the Central Archaeological Area of Rome,which includes Palatine Hill, Roman Forum, and Coliseum, carried out according to ICMS(2008). The study was performed in the framework of a larger research project, sponsoredby the Italian Department of Civil Protection, aimed at geohazard assessment affecting thearea (Cecchi 2010, 2011). Among the different hazardous earthquake effects, ground motionamplification phenomena due to local geology are addressed, while a qualitative assessment(level 1 zonation) in terms of permanent deformations susceptibility can be found in Manciniet al. (2013).

A large amount of subsoil data was already available in the study area mainly from thearchaeological superintendence and from the surveys for the design of adjacent subwaylines. These data were collected, validated in terms of their quality, and processed to definea preliminary model of the area and to plan a new multidisciplinary survey carried out in2010–2011 including continuous-coring boreholes, in situ and laboratory geotechnical tests,MASW, Cross- and Down-Hole tests, ambient noise measurements, electrical resistivitytomographies, ground penetrating radar surveys. A ground shaking level 1 SM of the areawas preliminary defined essentially on the basis of geological and lithologic information(Mancini et al. 2013); a final subsoil model aimed at site response analyses was thereforebuilt by integrating all the available information (Moscatelli et al. 2012; Pagliaroli et al.2013a).

After a description of the subsoil model, the paper shows the results of equivalent linear2D site response analyses. The main physical phenomena responsible for ground motionchanges, extensively treated in Pagliaroli et al. (2013b), are briefly described.

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The microzonation maps, drawn on the basis of the contouring of amplification factordefined in terms of Housner Intensity, are therefore illustrated. In order to cover the entirerange of fundamental vibration periods pertaining to the different monuments and structures,the maps were drawn in three different ranges of period: 0.1–0.5, 0.5–1.0 and 1.0–2.0 s.Finally, a sensitivity study to investigate the effects of uncertainties of input parameters andsoil heterogeneity on seismic microzonation is presented. In particular, the results of analysescarried out on subsoil models derived from geostatistical conditional simulations of shearwave velocity are compared with those obtained with the deterministic subsoil model usedfor SM maps.

2 Integrated subsoil model

2.1 Morphological and geological setting

The geological bedrock of the Palatine hill and surrounding areas consists of a Pliocenesandy-clayey unit of marine origin, the Monte Vaticano Formation (MVA in Fig. 1), whosetotal thickness is about 900 m (Signorini 1939). The top of this unit is cut by an unconformity,over which was deposited a Quaternary complex formed by the following middle Pleistocenefluvial-palustrine and distal volcanic deposits (Fig. 1), listed from oldest to youngest (afterFuniciello and Giordano 2008): (1) Santa Cecilia Formation (CIL); (2) Valle Giulia Formation(VGU); (3) Palatine Unit (PTI); (4) Prima Porta Unit (PPT); (5) Fosso del Torrino Formation(FTR); (6) Villa Senni Formation (VSN), with the Tufo Lionato (VSN1) and Pozzolanelle(VSN2) members; (7) Aurelia Formation (AEL). These formations have a sub-horizontalmultilayered distribution, except for the Fosso del Torrino Formation (FTR) that fills a fluvialpaleo-valley that deeply cuts into older Quaternary units in the eastern portion of the Palatinehill (see Fig. 1, cross-section #2). Finally, all of these units were carved by local tributaries ofthe Tiber River during the Late Quaternary sea-level fall, giving rise to deep (up to 70–80 m)and narrow alluvial valleys (i.e., the Velabro, Labicano, and Murcia valleys; Fig. 1). Thesevalleys were mainly filled with organic rich clayey sediments in response to the Holocenesea level rise (SFTba3 deposits in Fig. 1). The study area were then almost entirely coveredby anthropogenic deposits that can locally reach 20 m in thickness.

Because almost no direct observation of the geological substratum is possible, due to thethick anthropic cover, research units with capabilities in geology, geotechnical engineering,geophysics, and archaeology were involved to interpret subsoil information, in order to (i)identify the pre-anthropic/anthropic contact (Moscatelli et al. 2013), and (ii) identify andcharacterize the geological formation.

All the different formations recognized in the study area have been interpreted in termsof lithofacies, mainly based on their sedimentological features (Mancini et al. 2013). Inorder to mechanically characterize these materials, the various lithofacies have then beengrouped into lithotypes (listed in Fig. 1) characterized by similar physical properties (e.g.,grain size distribution, void ratio, unit weight, plasticity index) as determined from laboratorygeotechnical tests (Pagliaroli et al. 2013a).

2.2 Identification of seismic bedrock

The overconsolidated clays of the MVA geological bedrock unit have an average shear wavevelocity (VS) lower than 500 m/s in the upper tens of meters, as determined by direct geo-physical tests (Pagliaroli et al. 2013a). This value is quite smaller than the 800 m/s usually

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Fig. 1 Geological map (above) and cross-section #2 (below) of the Palatine hill and surrounding areas;CM = location of the Circus Maximus borehole

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assumed for seismic bedrock during site response analyses. A noise measurements campaignwas undertaken to identify the depth of seismic bedrock (Pagliaroli et al. 2013b). Microtremormeasurements were performed at 10 sites located throughout the study area (see Fig. 1 forlocation) using 5 seconds 3-component Lennartz� velocity transducer (LE3D-5s). All themeasurements showed a clear H/V peak around 0.3–0.35 Hz, thus suggesting the presenceof a several hundred meters deep seismic bedrock.

The seismic bedrock position was therefore identified by considering: (i) a very deepwell located in the Circus Maximus (CM in Fig. 1), crossing the entire 900 m thick MVAFormation and intercepting the passage between the clayey lithotype and the underlyingstiffer sandy-clayey lithotype at about 560 m from the ground surface (Signorini 1939); (ii)the results of 1D parametric site response analyses aimed at reproducing the site fundamentalfrequency at 0.30–0.35 Hz. According to these analyses, the VS-depth profile best matchingthe experimental results shows a VS average value of 550 m/s in the upper 200 m of the MVAFormation, 600 m/s in the subsequent 200 m, and 650 m/s in the lower 100 m of the MVA;the value VS ≥ 800 m/s (i.e. seismic bedrock) occurs below a depth of 500 m from the top ofthe MVA Formation, in substantial agreement with the CM borehole (Pagliaroli et al. 2013b).

2.3 Geophysical and geotechnical characterization

The site response analyses conducted for SM purposes adopt the traditional visco-elasticlinear-equivalent approach (Pagliaroli et al. 2013b). As such, the subsoil numerical modelrequires the characterization of each unit in terms of unit weight (γ), shear wave velocity (VS),compression wave velocity (VP) or, similarly, Poisson ratio (ν); the variation of normalizedshear modulus (G/G0) and damping ratio (D) with shear strain amplitude (γc) is also required.The S-wave velocities were determined for the study area from a total of 17 Cross-Hole (CH)tests, 11 Down-Hole (DH) tests, 3 Seismic Dilatometer (SDMT) tests, and 20 MASW testsavailable from existing studies as well as from the 2010 survey. Each lithotype was thereforecharacterized by averaging VS and VP across the different depth ranges. A constant value ofthe geophysical parameters with depth was therefore assumed with exception of the anthro-pogenic layer (h) and the MVA, for which a VS gradient with depth was defined. For lithotypeh the gradient was derived by interpolating all available measurement points (Pagliaroli etal. 2013a), while for the MVA a VS trend was deduced by reproducing the experimental sitefundamental frequency using 1D analyses, as described in the previous paragraph.

The normalized shear modulus G(γc)/G0 and the damping ratio D(γc) variation withshear strain amplitude were measured from a total of 20 resonant column and 2 cyclic tor-sional shear tests available from previous surveys in the area, as well as from results of 12new cyclic simple shear tests performed in 2010–2011. These latter tests were conductedto characterize all lithotypes; however, particular attention was given to those which hadnot been investigated in previous surveys (mainly organic clays SFTb3 and tuffs PTI-PPT-VSN1a; Pagliaroli et al. 2013a). For gravelly soils (CIL1, FTR1 and SFTba1), for whichundisturbed sampling was not possible, reference was made to literature data obtained onmaterials having a similar granulometric distribution (Hatanaka et al. 1988); the same curveswere used for the anthropogenic layer (h), given the prevalence of coarse material. Wheremultiple laboratory determinations for the same lithotype were available, the average range ofthe G(γc)/G0 and D(γc) curves obtained at in situ confining pressure was used. Only for theMVA marly member, considering its significant thickness (about 500 m), the laboratorycyclic simple shear curves at the highest applicable confining pressure were preferred(Pagliaroli et al. 2013a).

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Table 1 Integrated subsoilmodel for site response analyses

γ = unit weight,VS = shear wave velocity,ν = Poisson ratio. See legend ofFig. 1 for a description of thelithotypesa Gradient with depth

Lithotype γ (kN/m3) VS (m/s) ν

h 18.0 VS = 185z0.31 0.42

hm 19.0 530 0.40

SFTba2,3 18.5 270 0.49

SFTba1 20.0 590 0.46

VSN1a 16.0 600 0.40

PTI-PPT 16.0 650 0.39

FTR2,3-VGU2-VSN1b-CIL2 19.7 340 0.48

VGU1 20.0 390 0.42

FTR1 20.5 680 0.45

CIL1 20.5 620 0.39

MVA 20.5 550–650a 0.48

Seismic bedrock 22.0 800 0.46

Fig. 2 Non-linear behaviour of soils and soft rocks: G(γc)/G0 and D(γc) curves selected for each lithotypeand assumed in the integrated subsoil model for site response analyses

Finally the lithotypes were grouped into sets characterized by similar values for the proper-ties relevant for site response analyses: unit weight γ, VS, ν and G(γc)/G0 and D(γc) curves.The physical and mechanical properties adopted for the subsoil model are summarized inTable 1 and Fig. 2.

3 Selection of input motion

The monumental heritage of Rome has undoubtedly been subjected to earthquake-induceddamage: the macroseismic intensity in Rome has reached VII MCS on at least six differ-ent occasions in the past (Galli and Molin 2013). Rome is affected by earthquakes associ-ated with three different seismogenic districts (Fig. 3a): (1) the seismogenetic structures ofthe Central Apennine mountain chain, located about 90–130 km east of Rome, responsi-ble for events having a magnitude M of up to 6.7–7.0; (2) the Colli Albani volcanic area,located 20 km to the south of the city (M = 5.5); (3) the Rome area itself (inside thebeltway, i.e., the Grande Raccordo Anulare) characterized by rare, shallow, low-magnitudeevents (M < 5).

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Fig. 3 Seismicity affectingRome: black circles represent theepicentres of historical andinstrumental earthquakes from1000 to 2006 A.D. (size-scaled toMw), rectangles show the surfaceprojection of the main activefaults as reported in the Databaseof Individual SeismogenicSources, DISS 3.1.1 (Basili et al.2008), blue polygons representthe seismotectonic zones withinseismic zonation used for thecreation of the national seismichazard map (Meletti et al. 2008)(a); reference spectra selected forthe microzonation of the centralarchaeological area of Rome (b)(from Sabetta 2013)

Sabetta (2013) used both probabilistic and deterministic seismic hazard assessment tech-niques to evaluate the seismic input for site response analyses. Among the different UniformHazard Spectra (UHS) considered for the probabilistic approach, the INGV UHS with areturn period of 475 years and rock site conditions was selected (Fig. 3b). It should be notedthat this spectrum essentially corresponds to the Italian National Building Code spectrum(i.e., the Norme Tecniche per le Costruzioni; NTC-08), which was based on the INGV study.

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The INGV UHS spectrum was then used to simulate a spectrum-compatible time-historyacceleration.

For the deterministic approach (DSHA), three earthquake scenarios were selected accord-ing to the different seismogenic districts (Sabetta 2013): (1) Colli Albani volcanic complex,with Mw = 5.5 and an epicentral distance of R = 20 km; (2) Fucino basin source (Mw =7.0, R = 85 km); (3) local seismicity (Mw = 4.9, R = 5 km). The acceleration responsespectra of these earthquake scenarios were calculated using the Sabetta and Pugliese (1996)ground motion prediction equation with a prescribed fraction of standard deviation (Fig. 3b).Only scenario 1 and 2 were considered because local seismicity gives a spectrum interme-diate between the formers at low periods and much lower at higher values due to the smallmagnitude (Sabetta 2013). Artificial accelerograms (based on magnitude, distance and soilconditions) were then simulated for the two earthquake scenarios to be compatible withthe reference spectra. Moreover, in the deterministic approach, natural accelerograms wereselected from global databases that correspond to the magnitude, distance, and soil condi-tions extracted for the scenario earthquakes 1 and 2, including: (i) that measured at Torre delGreco during the 1980 Irpinia earthquake as representative of scenario associated to district1; and (ii) that registered at Assisi during the 1997 Umbria–Marche earthquake for district2 (Fig. 3b). In total, five acceleration time histories were selected as input motion, threeartificial signals and two natural accelerograms.

In order to assess the sensitivity of amplification factors used for SM to different inputmotions, Pagliaroli et al. (2013b) carried out analyses using all 5 accelerograms selectedabove. The amplification factors associated with the different input motions agree from botha qualitative and quantitative point of view in all the period ranges. Only in limited portions ofthe area differences as high as 30–40 % were observed. The Authors ascribed this behaviourto the moderate nonlinearity experienced by the soils.

The probabilistic approach, using the INGV UHS spectrum, was finally employed for siteresponse analyses aimed at defining the microzonation maps. This is because microzonationis essentially a planning tool focused on preventing damage that could occur due to futureearthquakes having different magnitudes and distances from the site. In this respect, theprobabilistic approach is certainly more suitable (Ansal et al. 2009) as it allows to constructan equi-probable spectrum combining a series of earthquakes that can affect, to differentdegrees, the study site. However, as said before, the INGV UHS input motion leads to resultscomparable with those associated to deterministic approach, ensuring the significance of thestudy for possible future earthquake scenarios. The value of 475 years chosen for the returnperiod of the input motion is a standard adopted for several studies in Italy (Pergalani et al.1999; Lanzo et al. 2011) and worldwide (Ansal et al. 2009).

4 Representative site response analyses

In order to define a level 3 seismic microzonation map of the Palatine hill and surroundings,2D numerical analyses were performed on 7 cross-sections representative of the geologicaland morphological setting of the area: three oriented NW–SE, three SW–NE, and one incorrespondence of the Coliseum (see traces in Fig. 1). The equivalent-linear finite elementcode QUAD4M (Hudson et al. 1994) was used. The main features of the code and details onthe numerical model are summarized in Pagliaroli et al. (2013b).

Numerical 2D results were processed mainly in terms of peak ground acceleration (PGA)and Housner Intensity (HI) (Housner 1952) over the period T1-T2, computed at cross-sectionssurface with reference to the horizontal component. Amplification factors in terms of HI

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Fig. 4 Housner Intensity amplification factors FH (a) and PGA (b) profiles computed for cross-section #2

have been used for a long time in Italy for SM studies, employing both weak motion ornoise recordings (Tento et al. 2001; Strollo et al. 2012) and numerical analyses (Pergalaniet al. 1999; Lanzo et al. 2011), because HI relates better to the structural damage thanPGA. In order to cover the entire range of fundamental vibration period pertaining to thearchaeological remains and monuments, HI was computed for three different period ranges:0.1–0.5, 0.5–1.0, and 1.0–2.0 s. The corresponding amplification factors profiles (FH0.1−0.5s,FH0.5−1.0s and FH1.0−2.0s) were then calculated by taking the ratio between the HI computedat the section surface and the corresponding HI of the input motion. The ground motionparameters were computed on INGV UHS input motion, as stated above.

In the following the results are discussed for cross-section #2, that cuts the Palatine hillthrough its centre in a NW–SE direction, and it is considered as representative of the maingeological and morphological features of the area. The results are then presented in a syntheticway for all cross-sections in the next paragraph.

FH amplification factors and PGA for cross-section #2 are reported in Fig. 4. The PGAprofile shows minor fluctuations on the Palatine hilltop plateau, indicating limited two-dimensional effects. In contrast, 2D effects associated with topography and buried mor-phology give rise to significant spatial variations of the PGA in correspondence with thehill toe (PGA < 0.1 g) and Labicano and Velabro alluvial valleys (PGA reach up to0.16 g). Ground motion amplification in the alluvial valleys is related to the impedance con-trast between the soft layer formed by alluvial clays (SFTba3) plus anthropogenic deposits(h) and the underlying stiff soils (MVA overconsolidated clays and CIL1–FTR1 gravels).The 2D amplification functions computed at the centre of the Velabro Valley and LabicanoValley show a clear amplification peaks around 2 Hz corresponding to the 1D fundamentalfrequency of the entire SFTba2,3-h layer. 2D resonance valley phenomena were also invokedto explain ground motion changes (Pagliaroli et al. 2013b). The PGA deamplification at

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the hill toe can be ascribed to topographic effects, as observed in many experimental andnumerical studies (Pagliaroli et al. 2011).

The three amplification factors (FH0.1−0.5s, FH0.5−1.0s, FH1.0−2.0s) show quite differenttrends from both a qualitative and quantitative point of view, highlighting the “filter effect”that the soft rock and soil deposits exert on seismic motion as a function of their mechanicaland morphological features.

The amplification factor FH0.1−0.5s is almost constant on the Palatine hilltop (1.15 on aver-age); no appreciable differences can be observed between the NW (multilayered deposit) andSE (FTR paleo-valley) sectors. Higher values (1.4–1.6) are observed in correspondence withthe Labicano and Velabro valleys while significant deamplification occurs at the hill toe,especially in the NW sector (Via di San Teodoro). Since this factor quantifies the amplifi-cations that occur primarily in the medium to high frequencies range (2–10 Hz), the causesof ground motion modification can be essentially ascribed to the same physical phenomenaresponsible for changes in the PGA and discussed above.

The amplification factor FH0.5−1.0s (frequency range 1–2 Hz) has a maximum value(1.6–1.7) in correspondence with the FTR paleo-valley essentially due to 1D amplificationphenomena, probably coupled with 2D effects such as interference by direct SV waves andRayleigh waves diffracted at paleo-valley edge (Chávez-García and Faccioli 2000; Pagliaroliet al. 2013b). Lower FH0.5−1.0s values occur in the recent alluvial valleys (Labicano andVelabro) which influence higher frequencies thus increasing factor FH0.1−0.5s, as previouslydescribed.

Finally, the factor FH1.0−2.0s shows minor fluctuations throughout the entire area, withlimited amplification phenomena (1.2) only in the NW portion of the FTR paleo-valley.

5 Seismic microzonation maps

The results in terms of amplification factors FH0.1−0.5s, FH0.5−1.0s and FH1.0−2.0s computedfor all the 7 cross-sections are reported in Fig. 5: the colour changes along the cross-sectionsrepresent FH values distribution; the geologic map of Fig. 1 is also reported for comparison.

Starting from the numerical results, for each period range a microzonation map in terms ofFH amplification factor was produced according to the following methodology: (i) the rangeof FH was divided into windows of 0.2 amplitude; (ii) for each cross-section, points at whichlimiting values of FH windows (0.8–1.0–1.2–1.4 and so on) are reached were identified onsection; (iii) contours of FH limiting values were manually performed taking into account theburied and outcropping geological and morphological features responsible for site effects,i.e., the physical phenomena controlling site response.

Each microzone is therefore defined by FH windows of 0.2 amplitude and identifies anarea with fairly constant FH amplification value and homogeneous stratigraphic, topographicand paleo-morphologic conditions.

The level 3 maps are reported in Figs. 6, 7 and 8 and described in the following withreference to the different period ranges.

5.1 FH0.1−0.5s map (Figs. 5a, 6)

High amplification values (FH > 1.4) are concentrated along Labicano and Velabro valleys,filled by recent clayey alluvia (SFTba3), in the areas characterized by higher shape ratio (i.e.,the ratio between valley maximum thickness and half-width) intersected by cross-sections#2, #3 and #7; in particular, a peak of 1.6–1.8 was computed in the southern portion of

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Fig. 5 Results of all numericalsimulations in terms of HousnerIntensity amplification factorsFH0.1−0.5s (a), FH0.5−1.0s (b)and FH1−0−2.0s (c); thegeological map of Fig. 1 is alsoreported as background

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Fig. 6 Level 3 seismic microzonation map for 0.1–0.5 s period range; A = Horti Farnesiani, B = Aula Regia,C = S. Anastasia church, D = San Teodoro church, E = via dei Fori Imperiali, F = via Nova, G = VignaBarberini, H = Circus Maximus, I = piazza Bocca della Verità; UTM33N WGS84 coordinates in meters arereported on both axes

Coliseum (cross-section 7). As previously observed with reference to cross-section #2, thisamplification can be related to 1D resonance of anthropogenic and alluvial layers superim-posed to 2D resonance of recent alluvial valleys filled by SFTba3. Conversely, where thevalleys are larger (smaller shape ratio), i.e., in the southern portion of Labicano and Velabrovalleys (cross-section #1) and in the Murcia valley (cross-sections #4, #5 and #6), the 2Deffects are less pronounced (Pagliaroli et al. 2013b) and FH < 1.4.

High amplification values, up to 1.7, do also occur in the area of the Roman Forum andVia dei Fori Imperiali (cross-sections #5 and #6). In this area the amplification effects areessentially related to 1D resonance of anthropogenic deposit h and FTR clays (FTR3) overunderlying FTR1 gravels (Pagliaroli et al. 2013b).

Relevant amplification is also found along the western flank of the FTR paleo-valley(Vigna Barberini area, node G in Fig. 6, see also cross-sections #2, #3 and #4), where FH ashigh as 1.4–1.6 is reached. Such amplification can be ascribed to focusing of seismic wavesat the valley edge and/or interaction between the direct waves and diffracted surface waves(Pagliaroli et al. 2013b). Similar amplification values (FH = 1.4–1.6) are also attained in theHorti Farnesiani (A in Fig. 6) and Aula Regia area (B in Fig. 6, cross-sections #5 and #6)probably for the 1D resonance of layer h overlying the stiffer VSN1a lithoid tuff.

Minor ground motion changes (FH values as high as 1.2–1.4) occur in correspondencewith the NE side of the Palatine hill (Via Nova area, F in Fig. 6, cross-sections #3 and #5).

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Fig. 7 Level 3 seismic microzonation map for 0.5–1.0 s period range; A = Horti Farnesiani, B = Aula Regia,C = S. Anastasia church, D = San Teodoro church, E = via dei Fori Imperiali, F = via Nova, G = VignaBarberini, H = Circus Maximus, I = piazza Bocca della Verità. UTM33N WGS84 coordinates in meters arereported on both axes

Finally, ground motion deamplification (FH = 0.8–1.0) can be observed at the toe ofPalatine, Aventino and Celio hills because of topographic effects.

5.2 FH0.5−1.0s map (Figs. 5b, 7)

The maximum amplification factors (FH = 1.6–1.8) for this frequency range do corre-spond to the areas of maximum thickness of FTR paleo-valley and SFTba alluvial valleys.The FH maximum at the NW edge of the FTR paleo-valley (Vigna Barberini area, G inFig. 7) is associated with essentially 1D stratigraphic effects that may be slightly enhancedby 2D valley effects. These latter consist primarily of surface waves generation at the valleyedge interacting with direct waves, whereas 2D resonance can be excluded based on themorphological, geometrical and mechanical properties of the FTR valley (Pagliaroli et al.2013b). Moreover, topographic effects appear to have a minor influence in this area and inthe adjacent multi-layered volcanic area, both located on the NW hillside of the Palatine(Horti Farnesiani area, A in Fig. 7, cross-section #6) (Chávez-García and Faccioli 2000;Pagliaroli et al. 2013b). FH values as high as 1.4–1.6 in Circus Maximus area (H in Fig. 7,cross-sections #4, #5 and #6) are associated to the 1D resonance of the anthropogenic coverand the clays filling the Murcia valley. The same phenomenon is responsible for the peak of

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Fig. 8 Level 3 seismic microzonation map for 1.0–2.0 s period range; A = Horti Farnesiani, B = Aula Regia,C = S. Anastasia church, D = San Teodoro church, E = via dei Fori Imperiali, F = via Nova, G = VignaBarberini, H = Circus Maximus, I = piazza Bocca della Verità. UTM33N WGS84 coordinates in meters arereported on both axes

1.6–1.8 attained at the convergence of Velabro and Murcia valleys close to the Tiber rivermain trunk (Bocca della Verità area, I in Fig. 7, cross-sections #1 and #6).

Ground motion deamplification (FH = 0.8–1.0) is observed in the area comprised betweenthe Roman Forum and S. Anastasia church (western flank of Palatine hill, C and D in Fig. 7),characterized by a small thickness of anthropogenic layer and sub-outcropping stiff gravels.

5.3 FH1.0−2.0s map (Figs. 5c, 8)

In this period range amplification factors are significantly lower than those computed in theother two ranges.

As observed for the previous map (FH0.5−1.0s), amplification zones are associated toessentially 1D seismic response of the deposits constituted by the high-thickness filling ofFTR paleo-valley and SFTba valley and the superimposed anthropogenic unit. FH values ashigh as 1.2–1.3 are computed at NW edge of the FTR paleo-valley (Vigna Barberini area,G in Fig. 8, cross-sections #2 and #4) and close to the Tiber River main trunk (Bocca dellaVerità area, I in Fig. 8, cross-sections #1 and #6).

Deamplification zones (FH = 0.9–1.0) are mainly in the NW portion of the area (betweenRoman Forum and S. Teodoro church, D in Fig. 8).

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6 Effects of uncertainties on the evaluation of site amplification

Even if a large amount of subsoil data are available for the study area, significant uncertaintiesmay persist in input key parameters used for site effects numerical modelling. Among thesefactors the most important are usually: geological model (mainly the buried morphology),VS distribution, non linear soil behaviour properties, position and mechanical characteristicsof seismic bedrock, type and incident angle of input waves.

A sensitivity study was then carried out on cross-section #2 considered as representativeof the main geological and morphological features of the area.

Regarding the geological model, the case history of the Central Archaeological Area ofRome represents a scholarly example of how the assessment of local seismic response requiresa detailed reconstruction of the subsoil, especially when outcrops are scarce because of thehigh thickness of anthropic cover. Incorrect correlation of geological bodies across boreholes,due to poor datasets and unawareness of stratigraphic setting, may be translated into anerroneous subsoil model and misleading for assessing local seismic response. However,evaluation of uncertainty related to the geological model is a very complicated topic and isbeyond the scope of this paper; the reader is referred to Mancini et al. (2013) for a discussionon this subject.

Apart from the uncertainty related to the geological model, it is believed that factors suchas non linear properties and input motion play a minor role on seismic motion distribution.

The non linear behaviour experienced by soils and soft rocks of Palatine and surroundingsis moderate. Pagliaroli et al. (2013b) shows that a maximum shear strain of 0.03–0.04 %occurs in the softer materials (SFTba alluvia and anthropogenic layer), while in the stiffer ones(including older alluvia and soft rocks) the shear strain is less than 0.01 %. The uncertaintiesin non linear characterization play therefore a minor role with respect to those associated toVS profiles.

As stated before in the text, the influence of input motion was investigated by Pagliaroliet al. (2013b) by means of numerical analyses carried out on cross-section #2 using differenttime histories corresponding to probabilistic and deterministic seismic hazard analyses. Evenif the input spectra show significant differences in shape and spectral amplitudes (Fig. 3b)only in limited portions of the area differences as high as 30–40 % were observed. Differencesassociated to different time histories compatible with the same target spectrum can thereforebe regarded as negligible.

Considering that the relevant seismogenic sources are located in the intermediate (ColliAlbani district) and in the far-field (Central Apennine district) areas, the standard assumptionof vertical incidence of S-waves made for numerical analyses can be regarded as realistic.P-waves and angle of incidence can play a significant role on the horizontal ground motiononly in the near-fault region. Also the uncertainties associated to type of waves and angle ofincidence can be therefore neglected.

Among the above mentioned input parameters, we therefore believe that the profiles ofVS in the soft covers and the contrast of impedance between covers and seismic bedrockplay a primary role in influencing the site effects. The impact of VS distribution and seis-mic bedrock stiffness on ground motion amplification was then investigated by means ofparametric numerical analyses. The results are illustrated hereafter.

6.1 Role of bedrock shear wave velocity

As stated before, the position of seismic bedrock was identified by reproducing with para-metric analyses the site fundamental frequency of the whole area measured by a microtremor

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Fig. 9 Housner intensity amplification factors FH profiles (a) computed for cross-section #2 using twodifferent values for the shear wave velocity of bedrock (Vb = 800 and 1,200 m/s); the 1D model employed toobtain the Vb = 1,200 m/s deconvolved input motion is also shown (b)

measurements campaign. The position (about 500 m below the top of MVA formation) isfurther confirmed by direct information from a deep borehole (CM in Fig. 1).

The fundamental frequency allows to constrain the position of seismic bedrock but givesno quantitative estimation of impendence contrast, and therefore of the shear wave velocity ofseismic bedrock, Vb. The standard value of 800 m/s was assumed in the numerical analysesbut sensitivity analyses where carried out by increasing Vb in a realistic range. It should beremembered that an higher impedance contrast could lead to an increase in amplificationfactors and response spectra, especially for long period in this case.

No direct data are available for MVA at such high depths. Based on judgment and expe-rience on similar soils, Caserta et al. (2013) hypothesized a VS gradient for the whole MVAformation in the area of Rome. This model was then employed to compute 1D transfer func-tions at San Paolo and Garbatella stations, in the urban area of Rome, where recordings ofthe M = 6.3 2009 L’Aquila earthquake (Lanzo et al. 2010) were available. A satisfactorilyagreement between experimental and numerical transfer functions was found.

According to the proposed model, at 500 m below the MVA top, a VS = 1,200 m/s isreached. It should be noted that the passage between the clayey lithotype and the sandy-clayey, shown by the deep CM borehole, was not explicitly considered by authors. However,this value (Vb = 1,200 m/s) can be realistically regarded as upper limit for the shear wavevelocity of the seismic bedrock assumed in the present study.

If Vb > 800 m/s, the input motion, which is usually referred to a outcropping rockcharacterized by an equivalent shear wave velocity of 800 m/s, should be deconvolved to thevalue of Vb assumed in the analyses. In the absence of a real outcropping bedrock in thestudied area, a VS profile for the deconvolution analyses was hypothesized (Fig. 9b) on thebasis of VS measurements on outcropping rock formation of similar characteristics, i.e., onthe Miocene sandy marly clays unit in the area of L’Aquila (Working Group Macroarea 92010). The 1D deconvolution analyses were carried out with ProShake (EduPro Civil SystemInc. 1998) assuming a visco-elastic behaviour for the materials.

FH profiles computed at cross-section #2 surface with the Vb = 1,200 m/s bedrockare compared with the corresponding values obtained with the Vb = 800 m/s bedrock inFig. 9a.

Appreciable differences can be observed only for FH0.5−1.0s and FH1.0−2.0s factors whichon average increase of 12 and 15 %, respectively, if Vb increases from 800 to 1,200 m/s.

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The amplification factors increase almost uniformly in space suggesting that the qualitativerelative ranking of the different geological-morphological domains does not change.

6.2 Role of shear wave velocity profiles

The effect of VS heterogeneity on ground motion was highlighted by comparing, for cross-section #2, the results obtained with the adopted subsoil model (i.e., the deterministic modelof Table 1 defined by averaging the VS for each layer) with those obtained from a stochasticmodel performed using the in-hole measurements. In particular, on cross-section #2 twentydifferent Vs distributions were obtained from geostatistical conditional simulations takinginto account the spatial variability of this parameter and honouring its available measure-ments. For each simulation a 2D site response analyses was carried out and FH profiles werecomputed accordingly. After a brief overview of the methodology used for geostatistical sim-ulations, results and comparison between the two approaches (deterministic vs. stochastic)are presented in the following.

6.2.1 Methodology of simulation

The Vs data used for the stochastic simulations were obtained from the 31 in-hole geophysicaltests (DH, CH and SDMT) carried out in the area; the number of measurement points in eachlithotype ranges between 3 and 195 (Pagliaroli et al. 2013a).

Since Vs varies according to the lithotypes, its simulation in the entire cross-section wasperformed as the union of independent simulations made in each of the following lithotypes(in brackets is shown the number of in-hole tests crossing them followed by the number ofavailable measurements): CIL1 (3–22), CIL2 (1–5), PPT (4–18), VGU2 (3–21), VSN1a(3–17), FTR1 (8–61), FTR2 (16–195), FTR3 (7–51), H (16–165), PTI (4–22), SFTba1(4–27), SFTba3-u (9–96), SFTba3-l (9–37), VSN1b (3–21). The MVA lithotype was not con-sidered for the geostatistical simulations because measurements refer only to the upper portion(20 m) of the formation. SFTba3 lithotype was subdivided in an upper part (SFTba3-u) anda lower part (SFTba3-l), that are characterized by a slightly different VS trend with depth.

The first step was to search for stationarity and compute horizontal and vertical var-iograms. Since it has been chosen a Gaussian simulation method, as will be specifiedlater, variograms have been calculated on the Gaussian-transformed data/detrended data.For the first five lithotypes (CIL1, CIL2, PPT, VGU2 and VSN1a) the small number ofdata and/or the behavior of the experimental variograms did not allow to model the spa-tial variability of Vs. In these cases, on behalf of security, variability structure has beenconsidered to be nugget. In the remaining nine lithotypes a vertical trend has been high-lighted in seven cases while in all cases variograms showed a clear vertical correlation ofVs or detrended VS, depending on the existence of the trend. Results of the variabilityanalysis of Vs concerning the nine lithotypes are shown in Table 2 while Fig. 10 shows thehorizontal and vertical variograms that have been computed and modelled. With regardto the horizontal direction, well estimated variograms were obtained only in two cases(lithotypes FTR2 and h, Fig. 10j–k). It is interesting to observe in Fig. 10k, which rep-resents the horizontal variogram of detrended Vs of the anthropic cover h, that the rangecannot be larger than 34 m (i.e., the mean distance of the first point of the variogram).The availability of data does not allow to define the effective range, which however hasto be >0 m, for physical reasons. Nevertheless, a range in the order of some tens ofmeters is consistent both with the heterogeneity observed in the archaeological excava-tions and with the average size of the buried man-made structures. In the other cases,

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Table 2 Summary description of variographic analysis for lithotypes showing spatial correlation of Vs

Lithotype Trend Vertical variogram Horizontal variogram

FTR1 Yes (+) 1. Nugget –

2. Spherical (5.6)

FTR2 Yes (+) 1. Nugget 1. Nugget

2. Spherical (3.5) 2. Spherical isotropic (220)

FTR3 No 1. Nugget –

2. Spherical (4.0)

h Yes (+) 1. Nugget 1. Spherical isotropic (30)

2. Spherical (8.0)

PTI Yes (−) 1. Gaussian (5.4) –

SFTba1 No 1. Spherical (4.5) –

SFTba3-u Yes (−) 1. Nugget –

2. Spherical (2.4)

SFTba3-l Yes (−) 1. Nugget –

2. Spherical (3.4)

VSN1b Yes (+) 1. Spherical (3.5) –

The number in brackets represents the range/practical range of the variograms, in meters; the sign indicatesthe trend with depth (+: VS increases with depth, −: VS decreases with depth). It is important to note thatthe range of the horizontal variogram of h has been chosen not through a fitting, but taking into account theheterogeneity of the anthropic cover and the average size of the buried man-made structures

the number of points with an acceptable number of pairs was not sufficient to understandthe behaviour of the experimental variogram. In these situations, the horizontal structurewas considered as the same of the vertical one but with a larger range (Elkateb et al.2003).

In the second step an allowable spatial variability model, i.e., with at least one three-dimensional structure, for each of the nine lithotypes has been defined.

Since Vs parameter has been considered without spatial correlation, simulation of thefirst five lithotypes was carried by generating independent Vs samples from each distribu-tion (Ripley 1987). For the remaining nine lithotypes simulation was performed using theSequential Gaussian Simulation (SGS). This method is suitable when simulation grid is notregular, as in the present case. The reader is referred to Alabert and Massonnat (1990) andGómez-Hernández and Kassiraga (1994) for a description of the method.

6.2.2 Results and comparisons

Housner Intensity amplification factors FH computed for cross-section #2 assuming deter-ministic and stochastic models for VS distribution are shown in Fig. 11a–c. The FH profilescomputed from stochastic model are represented in terms of 25th, 50th and 75th percentilescomputed from the analyses carried out for the 20 simulations of VS. The 50th percentilesubstantially agrees with the average profile. A representative VS distribution from one ofthe VS simulation is also shown (Fig. 11d) with a detail for the anthropogenic layer.

With reference to the 50th percentile an appreciable difference with the “deterministic”FH profiles can be observed only for the 0.1–0.5 s period range (Fig. 11a). Even if the generaltrend of FH is quite similar for both subsoil models, the 50th stochastic profiles can locally

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Fig. 10 Vertical (a–i) and horizontal (j–k) variograms of Gaussian-transformed Vs/detrended Vs data accord-ing to the description shown in Table 2

exceed of about 50 % the deterministic amplification factors. This increment can reach about90 % if the reference is made to 75th percentile.

This behaviour is coherent with the heterogeneities observed in the anthropic layer(Moscatelli et al. 2013), and is related to the complex 2D effects associated to waves scat-tered by the mechanical heterogeneities present in the stochastic model especially in theupper meters, greatly influencing high frequencies. FH peaks provided by the stochasticmodel indeed roughly match the soft zones surrounded by more rigid materials (i.e., masonryremains) in the anthropogenic cover (see the progressive 300 and 400 m in Fig. 11d).

On the contrary, FH1.0−2.0s is almost insensitive to VS distribution in the natural geologicalunits (Fig. 11c), while slight underestimation of FH0.5−1.0s by the deterministic model, as highas 10 % with respect to 50th percentile stochastic profile, can locally occur (Fig. 11b). Theseresults are not surprising considering that the longer wavelengths associated to FH0.5−1.0sand FH1.0−2.0s are not influenced by short-range VS variability.

7 Conclusions

The results of a multidisciplinary study aimed at seismic microzonation of the Central Archae-ological Area of Rome including Palatine hill, Roman Forum, and Coliseum are presented in

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Fig. 11 Housner Intensity amplification factors FH computed for cross-section #2 in the 0.1–0.5 s (a), 0.5–1.0s (b) and 1.0–2.0 s (c) period ranges assuming deterministic and stochastic models for VS distribution. The FHprofiles computed from stochastic model are represented in terms of 25th, 50th and 75th percentiles computedfrom 20 simulations. A representative VS simulation is also shown (d) with a detail for the anthropogeniclayer

this paper. A large amount of data, collected from previous investigations and derived fromad hoc multidisciplinary survey, allowed to define an integrate subsoil model for site responsenumerical modelling. For the definition of the subsoil model particular efforts were devotedto the identification of deep seismic bedrock, the characterization of the buried morphology(valleys and anthropogenic cover) and the measurements of cyclic properties of soils and softrocks.

A uniform hazard spectrum with return period of 475 years was selected as referencespectrum for input motion. Bi-dimensional numerical analyses were then carried out for

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seven representative cross-sections. The results show that ground motion distribution ismainly controlled by 1D resonance phenomena and 2D effects associated with (i) recentalluvial valleys bordering Palatine hill, and (ii) a large and deep N–S oriented paleo-valley.

The microzonation maps were drawn bounding zones with homogeneous stratigraphicand morphologic features and constant values of amplification factors in terms of Hous-ner Intensity (FH), computed in three different ranges of period, i.e., 0.1–0.5, 0.5–1.0, and1.0–2.0 s. The maps show limited changes in ground motion amplitude (maximum ampli-fication as high as 1.4–1.8 in the range 0.1–1.0 s are expected), which however can besignificant for monumental and archaeological heritage generally characterized by high vul-nerability.

Finally, a sensitivity study was carried out on a representative cross-section to investi-gate the effects of uncertainties of input parameters and soil heterogeneity on microzona-tion results. In particular, the impact of VS spatial variation and seismic bedrock stiff-ness was investigated, as in the present case they play a major role on ground motionamplification. Regarding the VS profiles, S-wave distributions compatible with valuesmeasured at in-hole profiles were first generated from twenty geostatistical simulations.Numerical results obtained using each stochastic simulation were then compared withthose from the deterministic model adopted to create the microzonation maps. Appre-ciable difference can be observed only for the 0.1–0.5 s period range: the general trendof FH is quite similar for both subsoil models but FH from stochastic simulations canlocally exceed of about 50 % on average the deterministic amplification factors. Wavesscattering phenomena due to mechanical heterogeneities in the anthropogenic cover couldexplain the ground motion aggravation. These results are coherent with the heterogeneityobserved in the anthropic layer and affects the SM maps for the lower periods of vibra-tion.

Regarding the influence of bedrock stiffness, not directly investigated by geophysicalsurveys due to the high depth, if the shear wave velocity of the seismic bedrock increasesfrom 800 m/s (adopted for the maps) to 1,200 m/s (expected upper limit for this kind ofbedrock), minor differences can be observed only for FH0.5−1.0s and FH1.0−2.0s factors,which on average increase of 12 and 15 %, respectively. The amplification factors increasealmost uniformly in space suggesting that the qualitative relative ranking of the differentgeological-morphological domains does not change.

Apart from the contribution of the seismic bedrock, the case study presented here showshow the strong heterogeneity of shallow geological bodies can influence the result of theseismic microzonation, at least in the medium to high frequency range. This heterogeneityconditions the geometry and distribution of microzones much more than the mean values ofthe amplification factors, due to the strong lateral variability of FH. Under these conditions,therefore, the results of a seismic microzonation performed with standard methods should beused carefully, for both small-scale planning and support activities to the seismic retrofittingof structures.

Acknowledgments The authors thank Roberto Cecchi (former Government Commissioner) and PiaPetrangeli (first project coordinator, and then Government Commissioner) for funding the geological andgeophysical surveys. The study was carried out within the UrbiSIT Project (2007–2012), financially sup-ported by DPC, the Italian Civil Protection Department (CNR-IGAG project manager: G.P. Cavinato; DPCreferents: L. Cavarra, F. Leone, G. Naso, F. Bramerini). Collaboration of the Special Superintendence for theArchaeological Heritage of Rome was greatly appreciated. The Authors are also grateful to Fabrizio Marconiand Francesco Stigliano (CNR-IGAG) for the precious support in producing the microzonation maps. Finally,the authors thank Landmark for the use of the software LithoTect�.

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