From regional- to local-scale seismic hazard assessment...

Bull Earthquake Eng (2010) 8:1547–1567DOI 10.1007/s10518-010-9191-9

ORIGINAL RESEARCH PAPER

From regional- to local-scale seismic hazard assessment:examples from Southern Spain

Jorge M. Gaspar-Escribano · Manuel Navarro ·Belén Benito · Antonio García-Jerez · Francisco Vidal

Received: 6 November 2009 / Accepted: 27 April 2010 / Published online: 3 June 2010© Springer Science+Business Media B.V. 2010

Abstract An approach that relates results from a regional seismic hazard assessment studywith local-scale site-effect characterizations in an area of low-to-moderate seismic activitysuch as Andalusia (southern Spain), is presented. Results of a previous probabilistic seismichazard analysis of Andalusia on rock conditions are disaggregated to infer hazard controllingearthquakes for different target motions. A collection of controlling magnitude-distance pairsand the corresponding site-specific response spectra at main capital cities of the region areobtained. These spectra are first-order approximations to expected seismic actions requiredin local earthquake risk assessments. In addition, results of independent, local-scale studiesdeveloped in Almeria City (SE Andalusia) are used to derive an updated seismic zonation ofthe city. These include predominant soil period estimates and shear-wave velocity profiles atdifferent locations. If a local seismic risk assessment study or an earthquake-resistant struc-tural design is to be developed, it may be recommended the use of different seismic actionson sites characterized by distinct response to seismic shaking (as derived from the seismiczonation). The seismic action related to worst-case scenarios may be modeled through a

J. M. Gaspar-Escribano (B) · B. BenitoETSI Topografía, Geodesia y Cartografía, Universidad Politécnica de Madrid, Madrid, Spaine-mail: [email protected]

B. Benitoe-mail: [email protected]

M. Navarro · A. García-JerezEscuela Politécnica Superior, Universidad de Almería, Almería, Spain

M. Navarroe-mail: [email protected]

A. García-Jereze-mail: [email protected]

F. VidalInstituto Andaluz de Geofísica y Prevención de Desastres Sísmicos, Universidad de Granada,Granada, Spaine-mail: [email protected]

123

1548 Bull Earthquake Eng (2010) 8:1547–1567

hazard-consistent response spectrum, obtained by hazard disaggregation at the spectral accel-eration with period matching the prevailing resonant period of the target site or structure.

Keywords Seismic hazard · Seismic risk · Site effects · Spain

1 Introduction, motivation and objective

During the last years, a process of revision and update of seismic risk analyses in Spainis under development. This process comprises three geographical levels: national, regionaland local (Gaspar-Escribano and Benito 2008). The national level is completed and sets thebasis for the development of the other two levels. The regional-level assessment (completedpartially) should conclude with a regional emergency planning and should establish whichmunicipalities must carry out an urban seismic risk assessment. And finally, the local levelassessment must contain a detailed emergency plan at a proper scale.

Most regions in Spain have completed or are about to complete the regional level andare facing the development of local seismic risk assessment studies. However, this is nota straightforward step to take due to natural and social limiting factors. The developmentof local-scale seismic risk analyses requires counting with highly detailed information thatconsumes many resources (human, economic and time) and it is often unavailable and/orhard to obtain. Additionally, in areas subjected to relatively low seismic activity (such asSpain), the social perception of earthquake risk is low (or at least, much lower than of othernatural or anthropogenic risks) and hence, it is regarded as a “lower-urgency” issue. Overall,the step from regional- to local-scale risk analyses is not always fully accomplished in suchareas.

The present work is a follow-up of the regional-scale seismic risk assessment of Andalusiaand constitutes a first development in taking such step (Fig. 1). The focus is given to seismichazard assessment and therefore, results and conclusions from this study may be used notonly for risk analyses but also for earthquake-resistant design of structures.

Seismic hazard may be defined as the seismic ground motion level that can be expectedat a given site. It comprises two factors: the expected ground motion on rock conditions andthe assessment of site amplification. The first factor is basically determined by the actualseismological environment of the study area and its description strongly relies on the avail-ability on sufficiently detailed seismic and geological data. As data on seismogenic faultgeometries, fault activity rates and maximum likely magnitudes in areas of low-to-moder-ate seismic activity are usually lacking or flawed by large uncertainties, their inclusion onsite-specific seismic hazard analyses introduces strong epistemic uncertainties that may behandled through a logic tree.

There are a number of methods to obtain seismic hazard estimates for use in local-scaleapplications, including probabilistic and deterministic methods. In areas of low-to-moderateseismicity, where strong events are not frequent, the use of a deterministic earthquake scenariorelated to the strongest event ever felt (or reported) is associated to a seismic action that is notlikely to occur in the short term. Consequently, using the seismic action related to such a deter-ministic earthquake scenario is not recommended in applications requiring a standard levelof conservatism, typically represented by a return period of 475 years. These include earth-quake-resistant design of normal-importance structures and seismic risk applications that donot involve any critical scenario. Probabilistic seismic hazard estimates may be adapted toany level of conservatism by the choice of return period considered (Bommer and Scherbaum2008). They do not provide a specific earthquake scenario directly defining the seismic input

123

Bull Earthquake Eng (2010) 8:1547–1567 1549

Fig. 1 a Location of Andalusia and main geological units. b original zoning models that where combinedfor the seismic hazard assessment study of Andalusia, top left NCSE-02 (NCSE-02 2002); similar to GSHAPmodel for continental Europe (Jiménez et al. 1999); top right LC-95 (López Casado et al. 1995), bottom leftHAM-98 (Hamdache 1998); bottom right AOU-00 (Aoudia et al. 2000)

for practical applications. In this case, hazard estimates need to be reprocessed by means ofhazard disaggregation, a technique that yields a distribution of magnitude-distance-epsilonbins that provides hazard-consistent earthquake scenarios (Bazzurro and Cornell 1999). Arecursive analysis benefiting from probabilistic and deterministic methods may be followedto get an insightful hazard assessment at a given site (McGuire 2001). With the basis ofregional-scale seismic hazard estimates informing about the most hazardous scenarios for atarget site, seismic hazard may be then further developed by redefining seismic source geom-etries adapted to that specific site (Musson and Henni 2001). Results of such an approachshould yield earthquake scenarios coherent with the hazard-consistent scenarios obtained bydisaggregation of regional-scale hazard estimates.

123


The incorporation of site effects to the standard seismic hazard assessment on rock condi-tions may imply notably large lateral variations in expected ground motions (even in distancesshorter than 100 m). Site effects are assessed, on regional-scale, by a single multiplicativeamplification factor which is mainly determined from surface geology, specifically by thesoftness and the structural configuration of subsurface rocks. Since the NEHRP (US NationalEarthquake Hazard Reduction Program) soil classification in 1994, a representative value ofshear wave velocity for the shallowest 30 m (V30

S ) is adopted as a characteristic site effectparameter in several seismic codes (Eq. 2; Dobry et al. 2000; BSSC 2004), such as the Span-ish NCSE-02 (NCSE-02 2002), the European Eurocode 8 (CEN 2004) and the InternationalBuilding Code IBC 2006 (ICC 2006). This criterion is appropriate and widely used in regionalsoil classifications adopted in seismic site effect evaluations (Alcalá-García et al. 2002; Ismetet al. 2006; Navarro et al. 2008).

More refined (local-scale) site effect classifications can be derived through several seis-mic exploration techniques with passive or controlled source that are effective and eco-nomic. These include conventional seismic refraction surveys and arrays measurements ofmicrotremors. The relation between surface wave dispersion curves and elastic parametersof the ground is extensively used in geophysical prospecting, using earthquakes or controlledsources for derivation of 1-D layered ground models (e.g. Nazarian 1984; Navarro et al. 1997;Tokimatsu 1997; Park et al. 1999). Additionally, passive array methods based on microtremor(e.g.: the spatial autocorrelation (SPAC) method by Aki 1957) prove to be innovative andconvenient techniques for empirical estimation of such dispersion curves (e.g. Parolai et al.2005; García-Jerez et al. 2007).

Below, an approach that combines regional-scale hazard estimates on rock conditions andlocal-scale estimates of site effects is presented and applied to Almeria City. This is one of theSpanish cities with the highest seismic risk. Hazard-consistent response spectra for specificsites and target motions are obtained through hazard disaggregation and are the seismic inputon rock conditions. Additionally, earlier work on seismic zonation of Almeria (Navarro et al.2001), which was based on microtremor measurements and shallow geotechnical boreholes,is completed, extended and updated with more microtremor data and new VS columns (downto 30-m deep) derived by conventional travel-time analysis and inversion of Rg-wave dis-persion curves. The interpretation of these data results in an improved microzonation forAlmeria City in terms of shear-wave velocity.

2 Regional-scale ground-motion characterization: seismic hazard analysisof Andalusia

2.1 Regional seismic hazard analysis of Andalusia

Following recent Spanish regulations, the Civil Defense agency of Andalusia promoted anupdated version of the seismic risk assessment study of the region (SISMOSAN Project) inorder to identify high-hazard areas requiring specific, local-scale emergency plans againstseismic disasters. The main characteristics of the related probabilistic seismic hazard assess-ment (PSHA) study, which concludes with the presentation of hazard maps on rock and soilconditions, are explained in Benito et al. (2010) and summarized below.

The seismic hazard assessment study is conceived at a regional scale. Expected groundmotions for a 0.9 probability of non-exceedance in 50 years (475-year return period) arecalculated for rock conditions. The first part of the hazard study is the review of the seis-mic catalogue. Special attention is paid to reassess the location and size of historical events

123


located in southern Spain and of significant events located along the neighboring Azores-Gibraltar plate contact. To obtain a catalogue with uniform size parameter, conversions fromthe respective national magnitude scales to magnitude Mw are carried out. A standard proba-bilistic method, assuming that seismicity is described by a Poissonian model and it is distrib-uted over zones of uniform seismic characteristics following a Gutenberg-Richter model ofmagnitude distribution, is used. The variability of results related to different zoning models(the model used to develop the hazard map included in the Spanish Seismic Code NCSE-022002; Jiménez et al. 1999; López Casado et al. 1995 for Spain combined with Hamdache1998 and Aoudia et al. 2000 for Northern Africa; Fig. 1) and to different ground-motion pre-diction models (which include composite models that distinguish between areas of distinctattenuation patterns; Ambraseys et al. 1996; Sabetta and Pugliese 1996; and Berge-Thierryet al. 2003 for all areas except for the Atlantic Ocean, where Tavakoli and Pezeshk 2005 andKanno et al. 2006 were used) is considered through a logic tree.

Subsequently, a shaking amplification map of Andalusia is composed by combining theinformation collected from the geological map of Andalusia and geotechnical data acquiredat different locations of the region. In this map, the territory is divided in different areas infunction of their potential to enhance seismic ground-motions according to the prevailingsoil conditions. Six soil classes are defined in the SISMOSAN Project, ranging from classI, the hardest, to class VI, the softest. For each soil class identified, an amplification factorconsistent with current seismic codes (NCSE-02, Eurocode 8 and IBC 2006) is used. Finally,expected ground motion values on rock conditions are combined with these soil amplifica-tion factors in order to obtain expected ground motions including site effects (for the sameprobability level).

Results of the seismic hazard study for a 475-year return period on rock conditions showthat maximum ground motions are expected in the southeastern part of the region (aroundthe Granada Basin and parts of the provinces of Almeria and Malaga). If soil conditionsare considered, areas presenting the largest expected ground motions are more localized insedimentary basins, either along the southern coast (Malaga and Almeria provinces), eitherin inland areas (parts of the Granada, Huercal-Overa and Baza-Guadix Tertiary basins).

2.2 Seismic hazard in capital cities

Results of the seismic hazard study described above are further processed in the eight capitalcities of Andalusia (Fig. 1), where hazard curves and uniform hazard spectra (UHS) areobtained. Uniform hazard spectra on rock conditions for the 475-year return period presentthe largest accelerations in the low-period range (around 0.1 s, grey lines on Fig. 2). Granada,Almeria and Malaga are the cities presenting larger hazard, and Huelva and Cordoba, thecities with lower seismic hazard (on rock conditions).

Site effects are incorporated by multiplying ground motions on rock conditions withamplification factors corresponding to representative soil conditions at the given sites. Soilcategories and period- and amplitude-dependent amplification factors for Andalusian capitalcities are shown in Table 1 and Fig. 2 (Benito et al. 2010). NCSE-02, Eurocode 8 and NEHRPsoil classes are included in this table to facilitate the interpretation of the SISMOSAN soilclassification. Note that according to this regional classification, Almeria is the Andalusiancapital city with the hardest soil class. Uniform hazard spectra including site effects are alsoshown in Fig. 2 (black lines). Note that Granada is clearly the city presenting the largestexpected motions for the 475-year return period due to the combination of large expectedaccelerations on rock conditions and the significant expected site amplification. Other cit-ies with soft soil, where high amplifications may be expected (e. g., Seville) do not show

123


0 0.5 1 1.5 2

Period (s)

0

0.1

0.2

0.3

0.4

0.5S

A (

g)

ALMERIASoil III

0 0.5 1 1.5 2

Period (s)

0

0.1

0.2

0.3

0.4

SA

(g

)

CADIZSoil IV

0 0.5 1 1.5 2

Period (s)

0

0.1

0.2

0.3

0.4

SA

(g

)

CORDOBASoil IV

0 0.5 1 1.5 2

Period (s)

0

0.2

0.4

0.6

0.8

1

1.2

SA

(g

)

GRANADASoil V

0 0.5 1 1.5 2

Period (s)

0

0.1

0.2

0.3S

A (

g)

HUELVASoil IV

0 0.5 1 1.5 2

Period (s)

0

0.1

0.2

0.3

0.4

0.5

SA

(g

)

JAENSoil IV

0 0.5 1 1.5 2

Period (s)

0

0.1

0.2

0.3

0.4

0.5

SA

(g

)

MALAGASoil IV

0 0.5 1 1.5 2

Period (s)

0

0.1

0.2

0.3

0.4

0.5

SA

(g

)

SEVILLESoil V

0 0.5 1 1.5 2 2.5

Period (s)

1

2

3A

mp

lif. f

act

or

Other CapitalsSe

ville

Gra

nada

Almeria

Fig. 2 Uniform hazard spectra for the 475-year return period at capital cities of Andalusia on rock conditions(grey lines) and including site-effects (black lines). Amplification factors are plotted on the lower right panel

such elevated ground motion levels because the input ground motions on rock conditions arerelatively small.

3 From regional- to local-scale ground-motion characterization

The response spectra including soil effects presented in the previous section represent themost complete seismic hazard characterization of a given site that can be obtained from aregular seismic hazard assessment study in a regional scale. More detailed seismic hazardcharacterizations may be obtained by (1) further elaborating seismic hazard results throughhazard disaggregation; and by (2) developing a local-scale seismic zonation to constrain theexpected site amplification with more detail. Whereas the first action implies a limited modi-fication of hazard results restricted to a specific scenario, the second constitutes a qualitativeimprovement of the seismic hazard assessment study.

The local-scale ground motion characterization is carried out in the city of Almeria becauseit is one of the Spanish cities with highest seismic risk and there are new data available regard-ing site effects (Sect. 3.2).

123


Table 1 SISMOSAN soil classification. Geological and geotechnical descriptions and equivalences withNCSE-02, Eurocode 8 and NEHRP soil categories are included

Geological description Geotechnical description Equivalences

SISMOSAN soil class I Igneous (granite, gabbros,basalt, andesite),metamorphic (quartzite,marble, gneiss) andsedimentary (limestoneand dolomites) rocks ofProterozoic, Paleozoicand Mesozoic age

Hard and very hard rocks,slightly fractured

NCSE-02: soil class IEurocode 8: soil class ANEHRP: soil class A

SISMOSAN soil class II Sedimentary (dolomites,limestone, greywacke)and metamorphic(schist, micaschist,slate) rocks of Paleozoicand Mesozoic age

Hard and very hard,fractured rocks

NCSE-02: soil class IEurocode 8: soil class ANEHRP: soil class B

SISMOSAN soil class III Paleozoic filites andmetapelites, Keuperunits (clay, gypsum,sandstone, limestone)and Mesozoic-Cenozoicsandstone, clay,limestone, marl, etc

Medium-hard rocks,highly fractured andeventually withabundant intercalationsof soft rocks. Soft rockswith expansive clays

NCSE-02: soil class IIEurocode 8: soil class BNEHRP: soil class C

SISMOSAN soil class IV Quaternary sedimentsfrom river source,colluvial and foot ofmount: sand, silt,conglomerates. Tertiaryand Quaternary age

Little or no cohesive soilspromptly cemented

NCSE-02: soil class IIIEurocode 8: soil class CNEHRP: soil class D

SISMOSAN soil class V Quaternary sedimentsfrom river, coluvial andwind origin: gravel,sand, silt and clay.Quaternary age

Cohesive soft and loosenot cohesive soils

NCSE-02: soil class IVEurocode 8: soil class DNEHRP: soil class E

SISMOSAN soil class VI Beach deposit, wetlandsand river channels:mud, sand dunes, plasticclay and siltorganic.(Quaternary)

Very soft soils, includingpotentially liquefiablesoils, sensitive clays,organic soils, soft clays

NCSE-02: soil class IVEurocode 8: soil class DNEHRP: soil class F

3.1 Hazard disaggregation and controlling earthquakes

Seismic hazard disaggregation is a technique that allows finding hazard controlling earth-quakes, defined as those earthquakes that present the largest hazard contribution to a particulartarget ground motion level (e. g. Kramer 1996). Controlling earthquakes may present differ-ent characteristics at the same site depending on the target motion considered, even if theycorrespond to the same probability level. For instance, the controlling earthquake associatedto the peak ground acceleration expected for the 475-year return period at a given site isusually smaller and closer (i. e., of lower magnitude and shorter source-to-site distance) thanthe controlling earthquake that corresponds to the long-period spectral acceleration for thesame return period at the same site. Therefore, the location of the study site with regard to

123


the seismic source zones used in the direct PSHA has a major influence on the resultingcontrolling parameters.

Seismic hazard estimates on rock conditions for the 475-year return period are disag-gregated in the eight Andalusian capital cities. Specifically, peak ground accelerations andspectral accelerations of 0.2, 0.5 and 1.0 s are used as target motions. Table 2 shows theresulting controlling magnitudes, source-to-site distances and epsilon values (i. e., a mea-sure of the extent to which the ground motion variability—sigma—contributes to a particularground motion estimate). Most controlling earthquakes present short source-to-site distances,demonstrating the prime influence of local sources on seismic hazard (for the 475-year returnperiod). For short period accelerations (including PGA), low magnitudes control seismic haz-ard. As vibration period increases, controlling magnitudes generally increase as well. Theremarkable case of Huelva, where very large controlling source-to-site distances and mag-nitudes are obtained for long vibration periods, may be explained by the contribution of theGorringe Bank seismic zone. This is one of the most active zones affecting Andalusia, asevidenced by numerous events felt in SW Iberia, including the 1755 Lisbon earthquake.

The controlling earthquake parameters for a given target motion can be used todefine seismic scenarios with a probabilistic basis. The associated hazard-consistent groundmotions can be derived in a number of ways. In earthquake-resistant design of structuresrequiring dynamic analyses, it is common to utilize recorded acceleration time series cor-responding to actual events matching the controlling parameters. In seismic risk analyses,a characteristic response spectrum is adopted. Choices for such a spectrum include seis-mic code response spectra, uniform hazard spectra and specific response spectra (SRS)evaluated with the magnitude and distance (and eventually epsilon) values correspondingto the controlling earthquakes for a given target motion (Gaspar-Escribano et al. 2008)(if a ground motion model is composed by several ground motion relations included ina logic tree framework, the final composite SRS is the result of the weighted sum ofthe individual SRSs obtained by substituting the controlling parameters in each individualrelation).

Focusing the analysis in Almeria, four SRS are computed for a given site, corresponding tofour different target motions: expected values of peak ground acceleration PGA and spectralaccelerations of 0.2, 0.5 and 1 s (denoted as SA(0.2s), SA(0.5s) and SA(1s), respectively) forthe 475-year return period. These SRS can be interpreted as more detailed hazard representa-tions than the UHS around the vibration period of interest in the sense that they are linked to aspecific, traceable scenario. They are calculated by multiplying the hazard-consistent targetmotions on rock conditions (Table 2) by the corresponding amplification factors (Fig. 2).The SRS resulting for Almeria (soil class III) are plotted in Fig. 3, together with the UHSfor the 475-year return period. To match the SRS for a given target motion with the UHSaround the period equaling the period defining the target motion (as marked by open circlesin Fig. 3), the controlling epsilon value is modified discretionally (following Bazzurro andCornell 1999). For short-period target motions, the respective SRS provide smaller spectralaccelerations (about 60%) than the UHS in the long-period range. By contrast, for long-periodtarget motions, the SRS provide larger spectral accelerations (about 30%) than the UHS inthe short-period range. Figure 3 clearly illustrates the significant variability of SRS shapesat the same site depending on the target motion definition adopted, and more specificallyon the spectral period related to the ground motion definition. The suitability of using oneanother spectrum (UHS or any SRS) will be discussed below.

123


Table 2 Target motions for PGA, SA(0.2s), SA(0.5s) and SA(1.0s) corresponding to the 475-year returnperiod on rock conditions (in cm/s2) and controlling source-to-site distances (in km), magnitudes and epsilonintervals for the eight Andalusian capital cities

CITY TARGET MOTION Distance Magnitude Epsilon

ALMERIA PGA = 127 5–10 4.5–5.0 1.0–1.5

SA(0.2s) = 323 5–10 4.5–5.0 1.0–1.5

SA(0.5s) = 160 5–10 5.0–5.5 0.5–1.0

SA(1.0s) = 72 5–10 5.5–6.0 0.0–0.5

CADIZ PGA = 91 5–10 4.5–5.0 1.0–1.5

SA(0.2s) = 231 5–10 4.5–5.0 1.5–2.0

SA(0.5s) = 112 5–10 5.0–5.5 0.0–0.5

SA(1.0s) = 60 5–10 5.5–6.0 −0.5–0.0

CORDOBA PGA = 69 5–10 4.5–5.0 0.5–1.0

SA(0.2s) = 177 5–10 4.5–5.0 1.0–1.5

SA(0.5s) = 90 5–10 5.0–5.5 0.5–1.0

SA(1.0s) = 47 15–20 5.5–6.0 0.0–0.5

GRANADA PGA = 201 0–5 5.0–5.5 −0.5–0.0

SA(0.2s) = 506 0–5 4.0–4.5 2.0–2.5

SA(0.5s) = 260 5–10 5.5–6.0 0.5–1.0

SA(1.0s) = 112 5–10 5.0–5.5 1.5–2.0

HUELVA PGA = 70 5–10 4.0–4.5 0.5–1.0

SA(0.2s) = 176 5–10 4.0–4.5 1.0–1.5

SA(0.5s) = 87 5–10 5.0–5.5 −0.5–0.0

SA(1.0s) = 54 310–315 7.5–8.0 −0.5–0.0

JAEN PGA = 97 5–10 4.5–5.0 0.5–1.0

SA(0.2s) = 247 5–10 4.5–5.0 0.5–1.0

SA(0.5s) = 127 5–10 4.5–5.0 1.0–1.5

SA(1.0s) = 60 5–10 5.5–6.0 −0.5–0.0

MALAGA PGA = 113 5–10 4.5–5.0 0.5–1.0

SA(0.2s) = 287 5–10 4.5–5.0 1.0–1.5

SA(0.5s) = 146 5–10 5.0–5.5 0.5–1.0

SA(1.0s) = 68 30–35 6.0–6.5 0.0–0.5

SEVILLE PGA = 71 5–10 4.5–5.0 0.5–1.0

SA(0.2s) = 180 5–10 4.5–5.0 1.0–1.5

SA(0.5s) = 69 5–10 5.0–5.5 −0.5–0.0

SA(1.0s) = 50 25–30 6.0–6.5 −0.5–0.0

3.2 Seismic zonation of Almeria

A seismic zonation of Almeria City is presented below. It is an update of an earlier workin which the shallow subsoil structure of the city was assessed based on geologic and topo-graphic maps, aerial photographs, four shallow shear-wave refraction profiles (maximumdepth reached smaller than 10 m), 80 shallow borehole data and 173 fundamental periodmicrotremor measurements all over the city (Navarro et al. 2001). The new seismic zonation

123


0

0.1

0.2

0.3

0.4

0.5

SA

(g

)

0 0.5 1 1.5 2

Period (s)

Soil III UHSSRS (PGA475)SRS (SA475(0.2s))SRS (SA475(0.5s))SRS (SA475(1s))

Fig. 3 Hazard-consistent response spectra for Almeria City. UHS for the 475-year return period and SRS fortarget motions coinciding with the expected values of PGA, SA(0.2s), SA(0.5s) and SA(1s) are represented.Open circles represent values in which UHS and SRS coincide

extends the data collection and measurements. The amount of shear-wave refraction surveysincreases up to 15 sites, and adds new Rg-wave dispersion analyses based on nine arraymeasurements of ambient noise. New measurements concentrate in 23 open spaces of thesoutheastern part of Almeria (more than 50% of the built areas of the city), an area where newurban developments are taking place and where the soil conditions are the softest of the city,overall contributing to enhance the expected seismic risk. Two main outcomes are achievedfrom these analyses, namely the update of ambient noise maps for Almeria in areas whichremained not urbanized in former campaigns and that are subjected to relatively high seismicrisk, and the prolongation of the VS profiles attained in the earlier work from less than 10 m todepths of 30 m and deeper. Hereby, the average V 30

S values obtained in the new zonation arederived from actual measurements and not extrapolated from shallow data (surface geology,four 10-m-deep VS profiles and borehole data), as in earlier studies.

Shear-wave velocity profiles are obtained by two methods, depending on the type of mea-surement carried out: For shear-wave refraction surveys, conventional travel-time analysesare applied. For array analyses of ambient noise, inversion from the Rg-wave dispersioncurves is carried out.

A total of 15 shear-wave refraction surveys are conducted. SH-waves are generated byplank hammering. The total length of seismic refraction lines is 45 or 50 m, depending on thesignal-to-noise ratio and the characteristic dimensions at each site. The resulting VS profilesreach depths of around 15 m. Descriptions of all the sites, including shear-wave velocities oftop and bottom layers, are listed in Table 3.

In the case of microtremor prospecting, vertical components of soil motion excited byambient noise, are recorded by using circular-shaped arrays. Five high-sensitivity VSE-15Dsensors surrounding a sixth central sensor and connected to a SPC-35 digitizer are used. Sev-eral arrays, with radii R ranging from 2 to 94 m, were deployed at each site. The maximumsize depends on the available spatial dimensions. Recording time was 30 min, and the signalwas sampled at a rate of 100 and 200 samples per second. All records are analyzed using animplementation of the spatial autocorrelation (SPAC) method (Aki 1957). They are dividedinto 20 s time windows with an overlapping of 80%. To obtain the SPAC coefficient ρ(f, R),cross correlations between the records obtained in the circumference and the central site arecalculated in the frequency domain, normalized by the power spectrum at the central stationand azimuthally averaged. Finally, Rg-wave phase velocities cR(f) are calculated for each

123


Table 3 Summary table of the 15 sites where seismic refraction surveys were carried out, including shear-wavevelocities obtained for top (at surface level) and bottom (at about 15 m below the surface) layers

Profile Landform unit,geologicalformation

Materials ofsurface deposits

Materials lyingunder surfacedeposits

Shear-wavevelocity (m/s)top–bottom

1 Coastal lowland Sand, clay and silt Upper Pleistoceneor Holocenedeposits

360–526

2 Holocene alluvial fan I Gravel and sand Upper Pleistoceneor Holocenedeposits

305–748

3 Flood plain Clay and silt Upper Pleistoceneor Holocenedeposits

298–494


297–578


359–531

6 Mountain Pre-Pliocene rocks – 1689

7 Hill with steep slope Mio-Pleistocene deposits – 348–760

8 Holocene alluvial fan II Silt, gravel and sand Upper Pleistoceneor Holocenedeposits

211–417


303–429


217–569


233–554


235–590


221–466

14 Mountain Pre-Pliocene rocks – 1840


237–358

Sites locations are presented in Fig. 7. Holocene alluvial fan II presents much higher liquefaction potentialand lower SPT N -values than Holocene alluvial fan I

frequency from an smoothed version of ρ(f, R) by using Eq. (1).

ρ(f, R) = J0

(2π f

cR(f)R

)(1)

In this equation, J0 is the zero-order Bessel function. Rg-wave dispersion curves are invertedto obtain shear-wave velocities. The inversion method requires building up a proper initialEarth model, which in our work results from the interpretation of seismic profiles available

123


Fig. 4 Example of the analyses carried out using seismic arrays at a given site: a SPAC coefficients for cir-cular array of radius 20 m (mean, mean-plus-one-sigma and mean-minus-one-sigma curves are represented);b Rg-wave phase velocities measured for different radii R (circles: R = 20m; squares: R = 10 m; triangles:R = 5 m; stars: R = 2.5 m); c Shear-wave velocity model. Solid black line represents the final model, dashedgrey line represents the initial model and horizontal dashed lines mark the theoretical interval where theset of arrays provides good accuracy; d Comparison between Rg dispersion curve of initial model (dashedgrey line), experimental dispersion curve (solid grey line) and theoretical dispersion curve obtained fromShear-wave velocity model (black line). All figures correspond to site A2

in the study area. Due to differences in the dispersion curves both in frequency and phasevelocities, the model of plane-horizontal, homogeneous layers overlying a half-space is notthe same for all sampled sites. The number of layers and their thicknesses are different foreach site and are determined from a priori geological data. Details on the nine arrays deployedand their characteristics are given in Table 4.

Figure 4 shows an example of the analyses carried out with this technique at site A2.Figure 4a shows the variation of the SPAC coefficient with frequency, which typically rangesbetween −1 and 1. Figure 4b represents the variation of phase velocity with frequency. Asthe radius of the array increases, lower frequencies and higher velocities may be sampled.Figure 4c shows the shear-wave velocity model. Note the small variation between the initialand the final model for the shallowest layers. Finally, the comparison between measured, the-oretical (as derived from the velocity model) and initial Rg dispersion curves is presented inFig. 4d. Note the good fit between theoretical and measured curves, validating the shear-wavevelocity model.

123


Tabl

e4

Cha

ract

eris

tics

ofar

ray

ambi

ent

nois

em

easu

rem

ents

:fr

eque

ncy

inte

rval

ssa

mpl

ed(�

f),p

hase

velo

city

rang

e(�

c R),

dept

hin

terv

al(�

z),s

hear

-wav

eve

loci

tyra

nge

(�V

S)

and

V30 S

for

each

site

(see

loca

tions

inFi

g.7)

Site

Nam

eL

andf

orm

Rad

ii(m

)�

f(H

z)�

c R(m

/s)

�z(

m)

�V

S(m

/s)

V30 S

(m/s

)

A1

Veg

ade

Acá

Floo

dpl

ain

5,10

,20,

404.

8–17

.021

5–41

20–

50.0

176–

625

293

A2

Nic

olás

Salm

erón

Floo

dpl

ain

2.5,

5,10

,20

3.0–

21.8

191–

419

0–37

.518

5–47

431

7

A3

Raf

aelA

lber

tiFl

ood

plai

n5,

10,2

03.

0–13

.931

2–55

40–

46.0

283–

665

359

A4

Ade

laD

íaz

Hol

ocen

eal

luvi

alfa

nI

2.5,

5,10

,20

6.4–

29.8

471–

674

0–37

.537

8–74

859

5

A5

Com

pañí

ade

Mar

íaH

oloc

ene

allu

vial

fan

I2.

5,5,

10,1

87.

0–20

.028

8–70

10–

37.5

214–

824

490

A6

Des

alad

ora

Hol

ocen

eal

luvi

alfa

nII

6,12

,25,

50,9

42.

5–27

.026

5–81

60–

107

279–

998

345

A7

Gob

iern

oM

ilita

rH

oloc

ene

allu

vial

fan

I1.

5,3,

5,10

10.5

–30.

039

7–77

50–

37.5

345–

997

596

A8

Col

egio

Goy

aH

illw

ithge

ntle

slop

e2,

4,7.

5,15

10.0

–25.

036

2–88

20–

37.5

290–

1711

513

A9

Hos

pita

lTor

reca

rden

asH

illw

ithst

eep

slop

e3,

6,12

,25

10.0

–19.

949

5–70

70–

44.6

415

–13

7456

4

123


Fig. 5 Examples of Rg-wave phase velocities dispersion curves measured at different sites. Experimentalphase-velocity dispersion curve (grey) and theoretical phase-velocity dispersion curve (black). Note the greatcoincidence between both curves. a Site A1 (Desaladora, Holocene alluvial fan II); b Site A2 (Vega de Acá,Flood plain); c Site A7 (Gobierno Militar, Holocene alluvial fan I); d Site A8 (Goya High School, Hill withgentle slope)

Examples of Rg-wave phase velocities dispersion curves measured at different sites areshown in Fig. 5 and the respective shear-wave velocity profiles obtained are shown in Fig. 6for depths from 0 to 30 m.

Finally, the average shear-wave velocity of the upper 30 m (V30S ) is computed for each site

using the following expression:

V30S = 30∑n

i=1hi

VSi

(2)

where hi and VSi denote the thickness (in meters) and shear-wave velocity (in m/s) of thei-th layer of a total of n layers existing in the top 30 m. The calculated V30

S values are shownin Table 4.

These ambient noise measurements, which allow constraining the VS profile at least fordepths down to 30 m, may be successfully correlated with the shear-wave velocities in theshallowest soil layer (upper 10 m) obtained from refraction surveys and with soil predominantperiods that appear as response to weak motions. A summary of V30

S results, indicating thesoil categories established in seismic codes, is provided in Table 5. The resulting V30

S valuesare representative for soil classes I, III and IV according to the SISMOSAN classification.Class I comprises rocks with high or very high hardness, eventually slightly fractured; classIII includes intermediate-hardness rocks (highly fractured and occasionally with abundantintercalations of soft materials) or soft rocks with expansive clays; finally, class IV representssoils with little or null cohesion or soils barely cemented. Although large parts of the city are

123


Fig. 6 Some examples of Shear-wave velocity models derived from inversion of phase velocities. a Site A1(Desaladora, Holocene alluvial fan II); b Site A2 (Vega de Acá, Flood plain); c Site A7 (Gobierno Militar,Holocene alluvial fan I); d Site A8 (Goya High School, Hill with gentle slope)

Table 5 Calculated V30S values for seismic site effect evaluation in Almeria City

Seismo-geotechnical unit,Geological Formation

V30S (m/s) SISMOSAN

soil classNCSE-02 soilclass

Eurocode 8soil class

NEHRP soilclass

Mountain 1765 I I A A

Pleistocene alluvial fan 554 III II B C

Holocene alluvial fan I 547 III II B C

Holocene alluvial fan II 293 IV III C D

Flood plain 317 IV III C D

Coastal lowland 359* IV III C D

The corresponding soil class of different (model) seismic codes are also shown.∗ Extrapolated from 15 m depth

123


Fig. 7 Seismic zonation of Almeria (modified and updated from Navarro et al. 2001). Sites for seismic refrac-tion surveys (S1 to S15) and for array measurements (A1 to A9) are indicated. 1: Mountain; 2: Steep-slopehill; 3: Gentle-slope hill; 4: Pleistocene alluvial fan; 5: Holocene alluvial fan I; 6: Holocene alluvial fan II; 7:Valley flat I; 8: Valley flat II; 9: Flood Plain; 10: Coastal lowland; 11: Reclaimed land. Holocene alluvial fanI and Valley flat I present higher SPT N-values than Holocene alluvial fan II and Valley flat II, respectively

covered by relatively young alluvial deposits and coastal sediments, according to our resultsthe softest soil classes (in terms of V30

S values) are not present in Almeria City.The final zonation of Almeria is shown in Fig. 7. The integrated interpretation of the new

measurements and results presented in this work (including quantitative estimates of V30S )

with earlier data constitutes an empirical validation of the qualitative seismo-geotechnicaldistribution anticipated by Navarro et al. (2001).

3.3 Local-scale seismic hazard in Almeria

The local-scale seismic hazard estimates in Almeria city presented in Fig. 3 were obtainedby combining the specific response spectra on rock conditions derived in this work withthe period-dependent site amplification factor representative for the city extracted from theSISMOSAN project. The regional-scale SISMOSAN Project sets a soil class III as represen-tative for the entire city, which actually corresponds to the historical city centre. This grossestimate of the site effect may be refined using the zonation proposed in Fig. 7. Accordingly,the expected seismic action may be further adapted to each zone of the city, where differentsets of site-specific hazard-consistent response spectra may be considered for each zone.

123


Period (s)

0

0.1

0.2

0.3

0.4S

A (

g)

SRSSoil I

0

0.1

0.2

0.3

0.4

0.5

SA

(g

)Period (s)

SRSSoil III

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

SA

(g

)

0 0.5 1 1.5 2 0 0.5 1 1.5 2 0 0.5 1 1.5 2

Period (s)

SRSSoil IV

UHS (RP=475 yr) Soil UHS at period T0 = SRS(SA(T=T0))SRS(SA(T=1s))SRS(SA(T=0.5s))

SRS(SA(T=0.2s))SRS(PGA)

Fig. 8 Hazard-consistent response spectra for Almeria City for the 475-year return period: UHS and SRS forsoils classes derived in Fig. 4

Figure 8 shows these seismic actions for the three types of zones found in Almeria City(soil classes I, III and IV). In each graph, the shaded band represents the range of spectralaccelerations that may be expected according to the SRS obtained in Fig. 3 (for all hazardconsistent target motions and the associated controlling earthquakes contained in Table 2)and the dotted line represents the corresponding UHS. Depending on the period of the targetspectral acceleration considered, the adopted SRS could be further adjusted if required. Thisaspect is discussed in the following section.

4 Discussion

Figure 8 shows that a set of SRS, corresponding to different hazard-consistent target motions,could be integrated in a band of expected spectral accelerations at a given site. The question iswhether this spectral band could be narrowed on the base of some extra criteria. The answerdepends on the actual application of the study, and can be affirmative provided the avail-ability of additional data constraints. The basic idea is the following: if it can be reasonablyexpected that resonant effects may appear in a given spectral interval under some particularcircumstances, then it may be recommended the use of the SRS defined for the target motionof the period representing that interval. Two of such particular circumstances are related tonatural modes of vibration of soils and of structures.

For instance, the concurrence of seismic ground-motions with a significant energy contentfor a given period interval in an area where the predominant periods of the (sub-)soil overlapthat given period may lead to undesired resonant effects (e. g. Hasancebia and Ulusay 2006).Then, if a map of predominant soil periods is available, the seismic action for local-scaleseismic risk analysis should be defined as the SRS corresponding to the target motion of theperiod coinciding with the predominant period of the soil at each location. This means thatthe spectral band could be narrowed to that single SRS. This situation is illustrated in Fig. 9,where three sites (A, B, and C) located in the same zone of Almeria (flood plain in Fig. 7),and hence represented by the same spectral band, are considered. Sites A, B and C are char-acterised by different soil predominant periods (TA, TB, and TC), comprised in the intervals0.1 s < TA < 0.4 s, 0.4 s < TB < 0.7 s and 0.7 s < TC < 1 s, respectively. (Although

123


UHS at period T0 = SRS(SA(T=T0))

Band of hazard-consistent SRS for Soil IV sites in Almeria

Other SRS (Fig. 3) Preferred choice considering soil predominant period

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

SA

(g

)

Period (s)

Site C: Soil IV0.7<TC<1s

SRS(SA(1s))

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

SA

(g

)Period (s)

Site B: Soil IV0.4<TB<0.7s

SRS(SA(0.5s))

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7S

A (

g)

0 0.5 1 1.5 20 0.5 1 1.5 20 0.5 1 1.5 2

Period (s)

Site A: Soil IV0.1<TA<0.2s

SRS(SA(0.2s))

Fig. 9 Specific response spectra for three sites of the same zone of Almeria (soil class IV) characterized bydifferent predominant soil periods

these values were obtained from microtremor measurements, it is assumed for simplicitythat they can be extrapolated to any seismic input intensity, associated with small-magnitudeevents, such as the hazard-controlling earthquakes for short period target motions included inTable 2). According to our approach, the seismic action at each site can be represented by theSRS associated to the target spectral acceleration of the period that matches the soil predom-inant period, (noted as SRS(SA(T0), where T0 is the period in seconds). Specifically, it maybe suggested to use SRS(SA(0.2s)) as seismic action for site A, and similarly, SRS(SA(0.5s))and SRS(SA(1s)) for sites B and C, respectively.

Another scenario where resonant effects may be expected occurs when the fundamentalvibration period of a structure coincides with the period of a peak of seismic energy. In thecase in which the fundamental vibration period of a given building or structure is known,the seismic action for earthquake-resistant design could be defined as the SRS of the targetmotion consistent with that period. Inexpensive, straightforward methods based on weak-motion measurements may be very helpful to determine the fundamental vibration period ofexisting buildings and to find a correlation between number of storeys (value that is usuallyavailable in cadastral databases) and fundamental period (e. g., Navarro et al. 2007). Appli-cations of this approach to local-scale risk assessment studies would contribute to improvethe quality of the final results.

Combining the factors cited above, a worst-case scenario can be anticipated where res-onant effects are likely to converge on a given site. Actually, the concurrence of peaks ofspectral accelerations for certain periods, with fundamental vibration periods of one- andtwo-level buildings and with soft soil layers (with a high amplification response) is supposedto have played a significant role in recent damaging earthquake events occurred in Spain,where amplification of ground motions have exerted a major control on damage localisation(Navarro et al. 2007; Gaspar-Escribano and Benito 2007). Therefore, if a local-scale seismicrisk assessment study is carried out for the definition of emergency plans, it is recommendedto investigate the most adverse scenarios combining these factors. This investigation ought toconsider necessarily the SRS linked to the period that coincides either with the fundamentalvibration period of buildings, either with the predominant period of the underlying soil, or ifrequired, with both.

123


A pending question refers to the situations in which the proposed site-specific SRS pre-sented above may be used instead of the UHS. Although the final decision must be reasonedby the structural designer or risk analyst, for those cases in which seismic design may berestricted to a narrow spectral interval (i. e., structures chiefly behaving as a single-degree-of-freedom system), the use of site-specific SRS for target motions consistent with that intervalare recommended. In turn, if a uniform level of conservatism is required, the use of the stan-dard UHS may be preferred. The fact that the UHS is not an envelope for the associated SRSfor the same return period, as it could be expected intuitively, remains an issue for furtherresearch.

5 Conclusions

The definition of the expected seismic action for local-scale applications, such as in seis-mic risk assessment analyses or in earthquake-resistant design of structures, may be refinedby obtaining hazard-consistent specific response spectra through hazard disaggregation andimproving the characterization of site effects with on-site measurements informing about theshear-wave velocity structure of the subsoil down to (at least) 30 m deep (Fig. 8). Seismichazard on rock conditions could be further developed by redefining source geometries toincorporate particular features of active faults (only available for a few fault segments) andmaking heavy use of the associated (large) epistemic uncertainties. However, this process(especially the acquisition of data characterizing fault activity) is not easily achievable in arelatively short time period. By contrast, site conditions and site amplification factors maybe better constrained by gathering more data and sampling more locations, which can bedone at relatively low economic and time costs. An example of this hybrid approach thatcombines regional-scale seismic hazard estimates on rock conditions and local-scale sitecharacterizations is presented in this work.

For earthquake-resistant design of structures, the UHS is an adequate hazard-consistentground-motion characterization as long as an uniform level of conservatism is required forthe entire spectrum. In turn, the SRS is a ground-motion characterization that covers a morerestricted period interval, consistent with a specific target motion, for which the site (thestructure, etc.) need to be prepared against. For instance, the seismic demand of structureswith responses basically represented by the fundamental mode of vibration can be roughlyconstrained by the spectral acceleration at the fundamental vibration period (Luco and Cornell2001). In the case that the structure presents a significant response in more vibration modes,a more complex intensity measure should be considered.

For emergency planning or urban management applications where the seismic action isnot uniquely linked to a given structure, a similar approach may be adopted. However, asis not practicable to ascertain the fundamental mode of vibration of each single structure ofthe entire building stock of a city, alternative methods to generalise the expected response ofbuildings are implemented. Inexpensive methods based on microtremor measurements maybe implemented to estimate fundamental periods of buildings and preclude or counteractadverse situations (Navarro et al. 2007).

Acknowledgments This work is partly financed by Junta de Andalucía through the SISMOSAN Projectand by CICYT coordinate project CGL2007-66745-C02-01-02/BTE. The paper greatly benefited from therevisions of Dario Slejko and an anonymous reviewer. Comments and contributions by J. A. Pastor and byA. Rivas-Medina are acknowledged.

123


References

Aki K (1957) Space and time spectra of stationary stochastic waves, with special reference to microtremors.Bull Earthq Res Inst 35:415–457

Alcalá-García FJ, Espinosa J, Navarro M, Sánchez FJ (2002) Propuesta de división geológica regional dela localidad de Adra (provincia de Almería). Aplicación a la zonación sísmica. Rev Soc Geol España15:55–66

Ambraseys NN, Simpson KA, Bommer JJ (1996) Prediction of horizontal response spectra in Europe. EarthqEng Struct Dyn 25:371–400

Aoudia A, Vaccari F, Suhadolc P, Meghraoui M (2000) Seismogenic potential and earthquake hazard assess-ment in the tell atlas of Algeria. J Seismol 4:79–98

Bazzurro P, Cornell CA (1999) Disaggregation of seismic hazard. Bull Seismol Soc Am 89:501–520Benito B, Navarro M, Vidal F, Gaspar-Escribano JM, García MJ, Martínez-Solares JM (2010) A new seis-

mic hazard assessment in the region of Andalusia (Southern Spain). Bull Earthq Eng. doi:10-1007/s10518-010-9175-9

Berge-Thierry C, Cotton F, Scotti O, Griot-Pommera D-A, Fukushima Y (2003) New empirical responsespectral attenuation laws for moderate European earthquakes. J Earthq Eng 7:193–222

Bommer JJ, Scherbaum F (2008) The use and misuse of logic trees in probabilistic seismic hazard analysis.Earthq Spectra 24:997–1009

Building Seismic Safety Council (BSSC) (2004) The 2003 NEHRP recommended provisions for new buildingsand other structures Part 1: Provisions (FEMA 450), Washington, DC

Comité Européen de Normalisation (CEN) (2004) Eurocode 8: design of structures for earthquake resistance.Part 1: general rules, seismic actions and rules for buildings. EN 1998-1, Brussels

Dobry R, Borcherdt RD, Crouse CB, Idriss IM, Joyner WB, Martin GR, Power MS, Rinne EE, SeedRB (2000) New site coefficients and site classification system used in recent building seismic codeprovisions. Earthq Spectra 16:41–68

García-Jerez A, Navarro M, Alcalá FJ, Luzón F, Pérez-Ruíz JA, Enomoto T, Vidal F, Ocaña E (2007) Shallowvelocity structure using joint inversion of array and H/V spectral ratio of ambient noise: the case of MulaTown (SE Spain). Soil Dyn Earthq Eng 27:907–919

García-Jerez A, Luzón F, Navarro M (2008) Determination of the elastic properties and the depth of shallowsedimentary deposits applying a spatial autocorrelation method. Geomorphology 93:74–88

Gaspar-Escribano JM, Benito B (2007) Ground motion characterisation of low-to-moderate seismicity zonesand implications for seismic design: lessons from recent, Mw ∼ 4.8, damaging earthquakes in SE Spain.Bull Seismol Soc Am 97:531–544

Gaspar-Escribano JM, Benito B (2008) Overview of recent seismic risk analyses in Spain. In: 14 WorldConference on Earthquake Engineering. Beiijng, 12–19 October 2008. 10pp

Gaspar-Escribano JM, Benito B, García-Mayordomo J (2008) Hazard-consistent ground motions in the Regionof Murcia (SE Spain). Bull Earthq Eng 6:179–196

Hamdache M (1998) Seismic hazard assessment for the main seismogenic zones in North Algeria. Pure ApplGeophys 152:281–314

Hasancebia N, Ulusay R (2006) Evaluation of site amplification and site period using different methods foran earthquake-prone settlement in Western Turkey. Eng Geol 87:85–104

International Code Council, Inc. (ICC) (2006) International Building Code 2006. 679 pIsmet A, Tildy P, Prónay Z, Pinar A, Hermann L (2006) VS30 mapping and soil classification for seismic site

effect evaluation in Dinar region, SW Turkey. Geophys J Int 165:223–235Jiménez MJ, García-Fernández M and GSHAP Ibero-Maghreb Working Group (Chadi M, El Fou D,

Izquierdo A, Martinez-Solares JM, Sousa-Oliveira C, Tadili BA) (1999). Seismic hazard assessmentin the Ibero-Maghreb Region. Annali Geofis 42:1057–1066

Kanno T, Narita A, Morikawa N, Fujiwara H, Fukushima Y (2006) A new attenuation relation for strongground motion in Japan based on recorded data. Bull Seismol Soc Am 96:879–897

Kramer SL (1996) Geotechnical earthquake engineering. Prentice Hall, Upper Saddle River NJ, 653 ppLópez Casado C, Sanz de Galdeano C, Delgado J, Peinado MA (1995) The parameter b in the Betic Cordillera,

the Rif and neighbouring areas. Its relations with the tectonics of the region. Tectonophysics 248:277–292Luco N, Cornell CA (2001) Structure-specific scalar intensity measures for near-source and ordinary earth-

quake ground motions. Earthq Spectra 23:357–392McGuire RK (2001) Deterministic vs. probabilistic earthquake hazards and risks. Soil Dyn Earthq Eng 21:

377–384Musson RMW, Henni PHO (2001) Methodological considerations of probabilistic seismic hazard mapping.

Soil Dyn Earthq Eng 21:385–403

123

http://dx.doi.org/10-1007/s10518-010-9175-9

http://dx.doi.org/10-1007/s10518-010-9175-9


Navarro M, Corchete V, Badal JI, Pujades L, Canas JA, Vidal F (1997) Inversion of Rg waveforms in SouthernSpain. Bull Seismol Soc Am 87:847–865

Navarro M, Enomoto T, Sanchez FJ, Matsuda I, Iwatate T, Posadas AM, Luzón F, Vidal F, Seo K (2001) Sur-face soil effects study using short-period microtremor observations in Almeria City, Southern Spain.Pure Appl Geophys 158:2481–2497

Navarro M, Vidal F, Enomoto T, Alcalá FJ, Sánchez FJ, Abeki N (2007) Analysis of site effects weightinesson RC building seismic response. The Adra (SE Spain) example. Earthq Eng Struct Dyn 36:1363–1383

Navarro M, García-Jerez JA, Alcalá FJ, Vidal F, Enomoto T, Luzón F, Creus C (2008) Vs30 Structure of Lorcatown (SE Spain) from Ambient Noise Array Observations. Proc. of the 31st General Assembly of theEuropean Seismological Commission ESC 2008, Hersonissos, Crete, Greece, 7–12 September 2008

Nazarian S (1984) In situ determination of elastic moduli of soil deposits and pavement systems by spectralanalysis of surface waves method. Ph.D. dissertation, University of Texas, Austin

Normativa de Construcción Sismorresistente Española NCSE-02 (2002) Real Decreto 997/2002. Boletín Ofi-cial del Estado 244:11 October, Spain

Park CB, Miller RD, Xia J (1999) Multichannel analysis of surface waves. Geophysics 64:800–808Parolai S, Picozzi M, Richwalski SM, Milkereit C (2005) Joint inversion of phase dispersion and H/V ratio

curves from seismic noise recordings using a genetic algorithm. Geophys Res Lett 32:L01303Sabetta F, Pugliese A (1996) Estimation of response spectra and simulation of nonstationary earthquake ground

motions. Bull Seismol Soc Am 86:337–352Tavakoli B, Pezeshk S (2005) Empirical-stochastic ground-motion prediction for Eastern North America. Bull

Seismol Soc Am 95:2283–2296Tokimatsu K (1997) Geotechnical site characterization using surface waves. In: Ishihara K (ed) Earthquake

geotechnical engineering. Balkema, Rotterdam pp 1333–1368

123

From regional- to local-scale seismic hazard assessment...

Documents

Transcript of From regional- to local-scale seismic hazard assessment...