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Soil Dynamics and Earthquake Engineering 29 (2009) 699–709

Contents lists available at ScienceDirect

Soil Dynamics and Earthquake Engineering

0267-72

doi:10.1

� Corr

E-m

journal homepage: www.elsevier.com/locate/soildyn

Loss estimation in Istanbul based on deterministic earthquake scenariosof the Marmara Sea region (Turkey)

A. Ansal a, A. Akinci b,�, G. Cultrera b, M. Erdik a, V. Pessina c, G. Tonuk a, G. Ameri c

a Bogazici University, Kandilli Observatory and Earthquake Research Institute, Istanbul, Turkeyb Istituto Nazionale di Geofisica e Vulcanologia, Via di Vigna Murata, 605, 00143 Roma, Italyc Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Milano-Pavia, via Bassini 15, 20133 Milano, Italy

a r t i c l e i n f o

Article history:

Received 15 April 2008

Received in revised form

8 July 2008

Accepted 16 July 2008

Keywords:

Loss estimation

Deterministic ground shaking scenarios

Istanbul area

Marmara Sea region

61/$ - see front matter & 2008 Elsevier Ltd. A

016/j.soildyn.2008.07.006

esponding author. Tel.: +39 06 518 60 403; fax

ail address: akinci@ingv.it (A. Akinci).

a b s t r a c t

The rapid urban development in Istanbul has lead to an increase in the exposure levels of the urban

vulnerability. Due to the steadily increasing population, with improper land-use planning, inappropriate

construction techniques and inadequate infrastructure systems, associated with an existing high hazard

level, Istanbul is one of the most risky cities in the Mediterranean region. Estimations of casualties and

losses, expected for given earthquake scenarios, are necessary to develop sustainable rehabilitation

programs and for improving preparedness. Deterministic hazard scenarios and time-dependent

probabilistic hazard assessment were used as input to a GIS-based loss estimation model, to evaluate

the earthquake risk for Istanbul.

The deterministic ground shaking scenarios, used for loss estimation in Istanbul, were defined in

terms of acceleration and velocity time series for recognized reference earthquakes caused by different

rupture models along extended sources. The ground motions were calculated for the whole

metropolitan area extending over a grid system of 25�100 km2.

For the case of Istanbul, the representative scenario was selected by comparing the simulated peak

values and response spectra with the empirical ground motion models available for the area. Simulated

values are within one standard deviation of the empirical regressions.

The availability of wide-ranging building inventory data allowed the application of a GIS-based loss

estimation model (KoeriLoss-V2) to evaluate different loss scenarios depending on the ground shaking

input, as well as to consider the implications of mitigation actions. It was found that 30% of the

buildings in the metropolitan area may be in need of either strengthening or demolition to achieve an

adequate degree of life safety.

& 2008 Elsevier Ltd. All rights reserved.

1. Introduction

Istanbul, situated along both sides of the Bosporus Channel andMarmara Sea in Europe and Asia, is the largest city in Turkeyand the area has experienced high levels of earthquake groundmotion. Four earthquakes of M 7.6 (1509, 1719, and 1766)and M 7.0 (1894) situated in the Marmara Sea have generatedintensities up to X–XI in the city (Fig. 1). Recent studies havepointed out that the seismic hazard in Istanbul is mainlyassociated within two active seismogenic areas (Fig. 2): theCentral Marmara Basin (CMB) and the North Boundary Fault (NBF)located about 20–30 km south-west and south of Istanbul,respectively [1,2]. Because of the increasing awareness of earth-quake threat in the Marmara region, the need for seismic hazard

ll rights reserved.

: +39 06 504 1181.

studies has become progressively more important for planningrisk reduction actions [3].

Seismic hazard in Istanbul has been estimated previously usingprobabilistic methods [4,5]. Instead, Pulido et al. [6] modelled thebedrock ground motions due to a finite-earthquake source (M 7.5)in the Marmara Sea using a hybrid broadband simulationtechnique. The magnitude of the scenario earthquake in theirstudy is similar to the one adopted in the present study, but theyused different geometry for the fault. Sørensen et al. [7] evaluatedthe influence of the attenuation parameters and of changing thecritical source on the simulated ground motions.

In this study, the earthquake loss estimation was carried out asrequired in the European Integrated Project LessLoss ‘‘Riskmitigation for earthquakes and landslides’’ [8–10] where theIstanbul case study was chosen because of the very high levels ofearthquake hazard, vulnerability, and exposure factors. Indeed therisk in the city has been increasing steadily due to overcrowding,improper land-use planning, bad construction techniques, inade-quate infrastructures, and environmental degradation.

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A. Ansal et al. / Soil Dynamics and Earthquake Engineering 29 (2009) 699–709700

The primary objective of this study is to develop earthquakeloss scenarios in terms of buildings damage and casualties.Therefore, the scenario earthquakes were computed by determi-nistic seismic hazard analysis integrated with time-dependentprobabilistic hazard assessments by Erdik et al. [11] and Spence etal. [12]. Strong ground motions have been calculated for differentfault ruptures of the CMB structure for a M7.4 scenario earth-quake. Computed synthetic time series of ground motion fordirect S-wave field due to extended faults were simulated byusing a hybrid stochastic–deterministic approach (determinis-tic–stochastic method (DSM); [13]) valid for high frequencies.

The best envelope NEHRP spectra were determined for theaverage acceleration spectra in NS and EW components of thesimulated acceleration spectra on the rock outcrop. In the secondstep these spectra were modified according to the NEHRP [14] soilamplification coefficients to estimate the spectral accelerations(SA) at short (T ¼ 0.2 s) and long (T ¼ 1 s) periods. The spatialdistribution of the soil classes in Istanbul is essentially based onthe information obtained from the 1/50,000 scale surface geologymap prepared by Istanbul Metropolitan Municipality and allavailable borehole data at the time.

A comprehensive building inventory of every structure in thecity was assembled from a variety of sources [15,16] and it hasbeen used for damage and loss estimations using KoeriLoss-V2

Fig. 1. Location of the modelled fault traces in the Marmara Sea together with

historical strong earthquakes causing intensities up to X–XI in the Marmara region.

Fig. 2. Locations of the rupturing faults (CMB, NBF,) and their respective nucleation poin

ST036 and ST119, are chosen as test sites useful for the discussion of the results. Stars

software [17]. Parametric studies were conducted to evaluate theeffects of retrofit options on the building damage and the numberof casualties.

2. Ground motion simulation methodology

The DSM ([13]) has been adopted for the prediction of strongground motion due to extended faults in the frequency rangef40.5–1 Hz. Ground motions are calculated in terms of accelera-tion and velocity time series for three slip models and threenucleation points (9 scenarios for each fault) on a grid of 180receivers with a resolution of 5�5 km2 approximately (Fig. 2).

The method allows computing synthetic time series for directS-wave field at bedrock sites, and is suitable for generatingshaking scenarios near an extended fault, where the direct S wavefield is generally dominant in amplitude with respect to thereflected and superficial phases. The DSM follows the point-source-stochastic-method (PSSM) procedure of Boore [18] withtwo important modifications regarding to the accelerationenvelope and the theoretical spectrum. First, the envelope of theseismograms does not have a predetermined functional form, butit is calculated deterministically based on a plausible rupturemodel on an extended fault. The rupture scenario is described byspecifying a nucleation point on a rectangular fault plane, fromwhich the rupture propagates radially outward with a prescribedrupture velocity; a slip distribution over the fault can be alsoassigned to complete the kinematical description of the source.Second, the source spectrum is described with an omega-squaredmodel, and some of the spectral parameters such as the cornerfrequency are controlled by the deterministic computation ofthe envelope. In particular, the apparent corner frequency iscomputed from the shaking duration as perceived by receiver,varies from site to site. Consequently, sites located in the directionof the rupture front propagation usually experience shorterduration and higher-amplitude ground motion that is calledforward directivity. The synthetic time series can be easilycalculated in the frequency band of engineering interest (up to20 Hz) and the results are quite independent from the velocityprofile of the propagation medium.

Although this technique is approximate it is suitable forgenerating shaking scenarios near an extended fault usingdifferent source models. The capability of the method was

ts (#1, #2, #3), indicated by stars and 180 receivers (5�5 km resolution). Two sites,

indicate the nucleation points on the fault traces.

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Table 2Spectral parameters used in the ground motion simulations taken from the Akinci

et al. [21,23] study

Q (s�1) 180f0.45

k (s) 0.055

Stress drop 100 bar

A. Ansal et al. / Soil Dynamics and Earthquake Engineering 29 (2009) 699–709 701

demonstrated by modelling the strong ground motions from the1992 Landers (Mw 7.3), California, earthquake and comparingthem with the recorded accelerograms, which were clearlyaffected by directivity effects [13]. Ameri et al. [19] also simulatedthe 1978 Thessaloniki earthquake (M ¼ 6.5) using the sameprocedure.

Geometrical spreading R (km)

R�1 p30

R�0.4 30–60

R�0.6 60–90

R�0.8 90–100

R�0.5 4100

The fault distance R assumed in the simulations is the average distance from sub-

faults that contribute to the maximum released energy perceived by the receiver.

3. Possible scenario earthquakes in the Marmara Sea

The first step in the computation of a deterministic groundmotion scenario is the choice of a ‘‘reference’’ earthquake,identified by the magnitude and location. In the case of urbanloss estimation, it may not be the maximum credible event(usually adopted in the hazard analysis of critical structures), butrather the maximum historical earthquake that affected the city[20], especially if the historical record is sufficiently long. Thesecriteria lead to the identification of the event sources, with thesupport of seismotectonic studies and of probabilistic seismichazard deaggregation analysis.

According to deaggregation results [12,21–23], the majorcontribution to PGA hazard (47%) with 0.10 exceedance prob-ability in 50 years (return period of about 475 years) comesfrom the CMB (Mw ¼ 7.4), while 30% of the total hazard with0.50 exceedance probability in 50 years (return period of about70 years) comes from the NBF (Mw ¼ 6.9; Fig. 2). These results arein agreement with the recent studies in the Marmara Sea [1],indicating that the seismic hazard in Istanbul can be mainlyassociated with these two active seismogenic structures locatedabout 20–30 km south-west and south of central Istanbul,respectively (Fig. 1).

Therefore, the earthquake scenarios for Istanbul were definedconsidering the rupture of these two segments of the NorthAnatolian Fault System. Different fault rupture scenarios weresimulated for each segment (CMB, NBF) using, in both cases, threedifferent locations of the hypocentre and three different slipdistributions (Fig. 2). In this study only the CMB scenarioearthquakes are presented because they are the source of thestrongest shaking level expected for the city of Istanbul for use inloss estimations. Ground shaking scenarios generated by NBFsource have been studied as sources with short return periods [9],but they are not considered in the present study. The sourceparameters of the hypothesized seismogenic source of CMB aresummarized in Table 1.

The slip models have been computed with the k�2 method[24,25], the locations of the asperities in each fault segment beingdefined following the seismicity, the tectonic structure in theMarmara Sea, and the submarine morphology [1,2,26,27,28,36]. Inparticular, the two main existing basins (Central and Kumburgazbasins) were assumed able to change the seismic rupture featuresalong the CMB fault. Considering the previous observations, we

Table 1Fault model parameters of reference earthquake: length, strike and dip of model

fault planes are based on Okay et al. [2]

Fault parameters CMB fault

East end coordinate 40.89N–28.87E

West end coordinate 40.80N–27.59E

Length, L (km) 108

Width, W (km) 20

Rupture area, L�W 106�18 km2

Moment, Mo (dyn cm) 1.7�1027

Magnitude, M�w 7.4

Strike (deg) 81.5

Dip (deg) 90

Focal mechanism Right-lateral strike slip

defined three slip models: slip model #1 where two asperities arelocated within the basins, slip model #2 where one asperity islocated in the seismic gap zone, slip model #3 where the oneasperity is located between Central and Kumburgaz basins. Foreach slip model, three different nucleation points at a depth of10 km were considered in order to observe directivity effects onthe ground motion predictions (Fig. 2): one in the centre of thefault (bilateral rupture), and the other two close to the right andleft ends of the fault (unilateral ruptures towards west or east,respectively). The rupture starts at each nucleation point andpropagates radially with a constant rupture velocity of 2.8 km/s(80% of S-wave velocity), leading to nine different rupture models.

The propagation medium used for the simulations (Table 2) isdefined by the crustal velocity model [29] and the spectralattenuation model, which includes geometrical spreading,frequency-dependent Q, and diminution parameter k [21,23].

4. Simulated ground motions at bedrock in Istanbul

4.1. Variability of ground motion and spatial distribution

The nine rupture models are used to develop shaking scenariosat bedrock. The scenarios are classified as SXY, where X indicatesthe slip model (previously defined), and Y the nucleation pointposition (1 ¼ left, western point 2 ¼ centre, 3 ¼ right, easternpoint): for instance, S11 is the scenario generate for slip model 1and left nucleation point.

The overall variability for the entire Istanbul area is obtainedfrom each scenario and summarized in terms of PGA (Fig. 3).Median values of PGA are generally confined in the range1.0–7.0 m/s2, and the ground motion shows a high variability(more than 1 order of magnitude in the considered area) amongdifferent earthquake scenarios, due to several factors: the verylarge extension of the city, the large size of the event, the faultproximity to the city, and rupture directivity effects. Groundmotion distributions are very sensitive to the position of thenucleation point on the fault plane and unfortunately this isprobably the most uncertain seismological information that canbe forecast. In the case of CMB fault (Fig. 2), the nucleationpoint #3 provides median values that are lower than the othertwo nucleation hypotheses (because of the backward directivityeffects). The bilateral rupture (nucleation point #2) provides, ingeneral, PGA values comparable to the unilateral rupture (nuclea-tion point #1), due to the large extension of the fault.

Fig. 4 shows how the PGA values (mean horizontal component)are distributed inside the Istanbul area considering the slipmodel 1. The maximum PGA inside the city is lower for rupturepropagating from nucleation point #3 (S13, Fig. 4c) than fromnucleation point #1 (S11, Fig. 4a), varying from 4.0 to 6.0 m/s2. Theworst scenario, for slip model 1, is obtained with central

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0.1

1

10

100

S11Scenario code

PGA

(m/s

2 )

S21 S31 S12 S22 S32 S13 S23 S33

Fig. 3. Variability of peak ground accelerations obtained from 9 scenarios computed for CMB fault (vertical bars). Horizontal bar segments represent the average horizontal

component of the PGA distribution. The results are grouped according to their nucleation points and, within each group, three different slip distributions are considered.

A. Ansal et al. / Soil Dynamics and Earthquake Engineering 29 (2009) 699–709702

nucleation point (S12, Fig. 4b), where the PGA reaches up to morethan 10 m/s2 around the islands sited in front of the Asiancoastline. This strong ground shaking is caused by the combinedeffects of the proximity of the nucleation point to the city (closerthan nucleation point #1) and of the directivity of the rupturepropagation toward the city.

Time series simulated using S11 and S13 scenarios at site ST119(Fig. 2) show the typical features of records obtained at a siteexperiencing backward and forward directivity (Fig. 5): theduration of the time series increases up to 45 s when the rupturepropagates away from the site location (S13) and it decreases to10 s when the rupture propagate towards its location (S11),according to the different nucleation point position. Moreover,synthetics show lower amplitudes (around 0.3 m/s2) when S13 isconsidered, while PGA reaches 1.3 m/s2 when rupture propagatestowards the site (S11).

4.2. Comparison with empirical ground motion prediction equations

A comparison between synthetics and empirical groundmotion prediction equations (GMPE) guided the selection of arepresentative deterministic scenario for loss modelling. The peakparameters and spectral accelerations (SA) obtained from9 scenarios were compared with data from some empiricalground motion models valid for the region (AMB05 [30]; Akinci06[21,23]). The comparison in terms of PGA values (Fig. 6) showsgreat variability of ground motions obtained from differentrupture models; the larger differences are more dependent onthe position of the nucleation point than the slip model on thefault (Fig. 6a) and correspond to more than one standard deviationof the considered GMPE. The representative scenario event wasselected from the rupture models producing peak values withinone standard deviation of the empirical model (Fig. 6b). This eventwas defined by a slip model with two asperities and thenucleation point located west to the fault centre (S11) (Fig. 4a).Due to directivity effects, the PGA distribution shows a maximumshaking area located inside the city, with maximum values of PGAaround 6 m/s2 (Fig. 4a).

The advanced simulations were preferred to the GMEP in thedeterministic hazard assessment. The deterministic scenariocomputes the whole time series instead of a few ground motionparameters and account for specific source effects, such as theextension and geometry of the fault and the rupture propagationphenomena. In this way it is also possible to quantify theazimuthal variability of the ground shaking that is not accounted

by the empirical GMP models. Fig. 7 shows the comparisonbetween synthetics and empirical acceleration response spectra ofAMB05 and Akinci06 for the S11 CMB scenario at sites S036 andS119. It is noteworthy that the good agreement between thepredicted and the 71 standard deviation of empirical accelerationresponse spectra confirms the choice of S11 rupture model asrepresentative scenario to be used for loss estimation in Istanbul.

In general, the adopted fault and rupture models cause higherdirectivity effects in the city than the worst-case scenarioperformed by Pulido et al. [6], which produced the largest PGAvalue around 3.34 m/s2 and PGV value of 0.71 m/s, in the Istanbulregion.

5. Site-specific ground motion

Istanbul metropolitan area is composed of 32 towns and41 districts with total population of 10,018,735, according to the2000 census. The total area was divided with a grid system of0.0051�0.0051 (approximately 400 m�600 m) into 8131 geo-cells. For each cell, the spatial variation of geotechnical siteconditions was assessed following the 1/50,000 scale surfacegeology map prepared by Istanbul Metropolitan Municipality,supplemented with available boring data. Both types of data wereused to obtain the ‘‘Soil Classification Map of Istanbul’’ in terms ofNEHRP [14] site classes as shown in Fig. 8.

The acceleration ground motions simulated for the 9 scenarioswere used to compute acceleration response spectra (SA) on therock outcrop. An algorithm was developed to calculate NEHRPUniform hazard response spectra that envelope the averageacceleration response spectra. These best-fit NEHRP spectra werefirst of all used to define the spectral accelerations for T ¼ 0.2 and1.0 s on the rock outcrop, and then modified according to theNEHRP site-amplification coefficients which depend on the soiltype and the input motion level. The site-specific spectralaccelerations shown in Fig. 9 were then used for vulnerabilityanalysis in the assessment of building damages and lossestimation.

6. Losses estimation: building damage and casualties

6.1. Building inventory for Istanbul metropolitan area

Building inventory data compiled based on different types ofinformation (i.e. Aerial photos, State Statistical Institute Building

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Fig. 4. PGA distribution in the study area for 3 scenarios, (a) S11 (slip 1 and

nucleation point #1), (b) S12 (slip 1 and nucleation point #2) and (c) S13 (slip 1

and nucleation point #3). Dashed line represents the CMB fault trace. Dots show

the 180 receivers where the simulations are realized. The white triangles indicate

sites ST036 and ST119.

A. Ansal et al. / Soil Dynamics and Earthquake Engineering 29 (2009) 699–709 703

Inventories, Turkish Telecommunications Company maps) isavailable with respect to relatively coarse cell size of (400 m�600 m) for the entire city. The total number of buildings in theinventory is 737,653; among these, 76.3% are reinforced concrete(RC) frame buildings and 23.5% are masonry [12,15,16]. Allbuildings were classified according to the typology, the numberof stories and the construction year (Bijk parameter, illustrated inTable 3). Due to the recent urbanization, the largest number ofbuildings belongs to type B112 and B122 (RC, post–1980, low andmid-rise) [37].

6.2. Damage and casualty estimates for existing city

The analytical computation of the vulnerability relationship isbased on the spectral capacity method that estimates theresponse of a structure from spectrum demand and spectralcapacity curves [31]. The spectrum demand curve represents theground motion on spectral acceleration vs. spectral displacementaxes [16]. The spectral capacity curve represents the ability of thestructure to deform at various degrees of resistance, usuallyapproximated from a ‘‘pushover’’ analysis with the deformationsplotted against the load in the spectral displacement and spectralacceleration coordinates. The basic idea of the spectral capacitymethod is that the expected median response is determined bythe intersection of the spectral capacity and spectrum demandcurves. The building capacity parameters including the buildingperiod are estimated based on building typology and number ofstories. In spectral displacement-based fragility curves, thehorizontal axis represents the spectral displacement demandand vertical axis refers to the cumulative probability of structuraldamage reaching or exceeding the threshold of a given damagestate (Fig. 10). The analytical expression of each fragility curve isbased on the assumption that earthquake damage distribution canbe represented by a lognormal distribution function [32,33].

The structural damage to buildings is usually classified intofive groups: (1) no damage, (2) slight damage, (3) moderatedamage, (4) extensive damage, and (5) collapsed. Nine earthquakerupture scenarios calculated in this study and a probabilistichazard scenario provided for RP ¼ 475 years by Erdik et al. [11]were used to determine the damage distribution for RC buildingsbased on the calculated spectral accelerations including siteeffects. Damage assessment is limited to RC structures thatrepresent more than 3

4 of the inventory.As shown in Fig. 11, with respect to number of buildings in

different damage levels, three different damage patterns wereobserved in all 10 scenarios. The first group composed ofprobabilistic PR ¼ 475 years input, deterministic scenarios S11and S31 appear to be similar. The second group of deterministicscenarios S13, S23 and S33 yields very low damage levels. Thethird group of deterministic scenarios S12, S21, S22, and S32yields much higher levels of damage.

The variation of all types of collapsed reinforced framebuildings for the deterministic scenario S11 is shown in Fig. 12for Istanbul metropolitan area. The calculated numbers ofdamaged buildings for different damage levels are also sum-marised in the same figure.

The casualty estimation proceeds from the building damageassessment because the casualty number is mainly due to the rateof people trapped in collapsed or heavy damaged structures. Thereare several procedures proposing the use of casualty rates withrespect to the type of building damage (i.e. HAZUS99); however,the casualty rates are often derived for different regions and arenot directly applicable to Turkey as observed by past experiencewhere higher fatalities have been recorded in total collapsedmulti-story RC buildings (pancake type). Erdik et al. [16] proposedan earthquake casualty model by applying the existing meth-odologies revising the casualty rates with the help of existing dataon Turkish earthquakes. According to this approach, casualty forany given structure type, building damage level, and injuryseverity level can be calculated as

K ¼ population per buildingnnumber of damaged building

ncasualty rate:

The casualties are computed for four injury severity levelsas defined in HAZUS99: injuries can require basic medical aid(severity 1), medical care and hospitalization (severity 2);

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Fig. 5. Acceleration and velocity time series (NS component) obtained at site ST119 for scenarios S11and S13 showing backward and forward directivity effects, respectively.

Fig. 6. (a) Median PGA (logarithmic average) of all scenarios7standard deviation (vertical lines) computed for CMB and compared with different ground motion predictive

relationships; AMB05 [30], BJF97 [38] and Akinci06 [21,23], (b) PGA values from simulated scenarios with slip model 1 and three nucleation points (S11, S12, S13).

A. Ansal et al. / Soil Dynamics and Earthquake Engineering 29 (2009) 699–709704

adequate treatment because of immediate life threatening condi-tion (severity 3) or they are mortally injured (severity 4). Thesame damage classification was used for both the damageassessment of the buildings and to calculate the casualties.However, based on past experience, the collapsed buildings weredivided into two subcategories as ‘‘partial collapse’’ (90%) and‘‘total collapse’’ (10%) with significantly different casualty rates asobserved in 1999 in Turkey [34].

An average population number of three persons per unit (unitsare dwellings) were calculated as the ratio of district populationsand number of units in the districts based on 2000 buildingcensus [16] and it was adopted for calculating the casualties fordifferent building types. The results are calibrated for thepopulation density determined based on the 2000 population

census results, thus they represent the condition of night-timepopulation.

Different shaking scenarios produce big differences in buildingdamage distribution (Fig. 11), but these significant variations inthe number of damaged buildings are even more important in thecalculated fatalities that indeed vary in a very large range.Fatalities calculated for RC buildings for the time-dependentprobabilistic hazard scenario for RP ¼ 475 years were in the orderof 31,500 while in the case of representative deterministicscenarios S11 the number of fatalities are in the order of 71,322.The number of fatalities strongly depends on the number ofcollapsed buildings and in the case of S11 the number of collapsedbuildings was approximately twice compared to the probabilisticscenario that amplified the casualty distribution.

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Fig. 7. Response spectra for 5% damping at sites 036 and 119 for S11 scenario (slip model 1 with left nucleation point). Synthetic spectral accelerations are compared with

the empirical predictions of AMB05 and BJF97 at sites 036 and 119 for the selected CMB scenario.

BLACK SEA

MARMARA SEAISTANBULSoil Classification Map

NEHARP (1997)Classification

A-B boundaryBCDE-F

0 10 20

kilometers

Fig. 8. NEHRP Soil Classification Map of Istanbul and the grid of geocells [16].

A. Ansal et al. / Soil Dynamics and Earthquake Engineering 29 (2009) 699–709 705

7. Retrofit actions and new results

The effect of retrofit on the damage assessments is difficult toestimate due to the irregular nature of the structural types anddistribution of the building stock. The existing practice on typicalmid-rise RC buildings have proven that the most appropriate andcost-effective retrofit systems are structural wall addition andcolumn jacketing. In order to achieve collapse prevention,preliminary studies on typical mid-rise buildings have indicatedthat the proposed retrofit schemes result in a decrease in thepredominant periods of such buildings to approximately two-third of those of the original buildings on average. In addition,these retrofit schemes are estimated to result in approximately a2.5-fold increase in the lateral load capacities of those buildings[35]. Thus, building property data were modified to obtain the

damage estimations for the retrofitted building stock. Thebuilding inventory for Istanbul is in terms of number of buildingsin each group. There is no data to identify which buildings areprone to collapse among all the buildings in a cell. Thus partlyhypothetical and merely parametric study was performed toobserve the effects of the selected retrofit scheme for the Istanbulcase. It seems rational to rehabilitate (strengthening or retrofit) tothe most vulnerable building residential stock in Istanbul. Theobjective of retrofit will be to avoid total collapse with which mostof the deaths are associated (fatality ratio is about 10%). The firstpriority is given to retrofit all RC buildings that are prone tocollapse according to specific earthquake rupture scenarios. Theseresults indicate that there could be significant decrease in thenumber of collapsed buildings if the retrofit can be implementedsuccessfully. On the other hand, the largest number of collapsed

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Fig. 9. Variation of short period spectral accelerations for the deterministic scenario S11.

Table 3Building classification parameters

Typology (i) Number of stories (j) Construction year (k)

1 ¼ Reinforced concrete

frame bldg

1 ¼ Low rise

(1–4 stories)

1p1979

2 ¼Masonry bldg 2 ¼Mid-rise

(5–8 stories)

3 ¼ Reinforced concrete

shear wall

3 ¼ High rise

(48 stories)

241980

4 ¼ Precast bldg (basement included)

A. Ansal et al. / Soil Dynamics and Earthquake Engineering 29 (2009) 699–709706

buildings are in the mid-rise post-1980 group (B122). Thuspriority can be given to these buildings in the beginning of theretrofit process.

Casualties were recalculated after the retrofit for two scenar-ios: a representative deterministic scenario S11 (Fig. 12) and theprobabilistic RP ¼ 475 years one. Significant decreases in casual-ties with respect to fatalities were observed for S11 scenario(Fig. 13). The vertical axis in Fig. 13 is in logarithmic scale to showthe very significant difference among different building typesbefore and after retrofit. For all the RC buildings, the number offatalities after retrofitting is reduced to 6.6% of the fatalitiesexpected before retrofitting.

8. Conclusions and discussion

In the present study, deterministic earthquake hazard scenar-ios based on finite fault rupture models were implemented fordamage assessment and risk analysis in Istanbul Metropolis.

Estimation of damage to buildings and associated casualtiesare developed on the basis of diverse ground shaking scenarios fordifferent hazard levels and it is also carried out by including thepotential mitigation actions. The reliability and accuracy of theearthquake damage scenarios strongly depend on the uncertain-ties in site characterisation surface ground motions, building stockinventory, and vulnerability relationships.

One of the principal results of this analysis is the estimationof the role of ground shaking level in damage assessmentand how risk results are influenced by the multiplicity of plausibleshaking scenarios. The generation of scenarios obtained by thevariation of the source parameters (e.g. hypocentre location);allow identifying the upper and lower limits of the expectedshaking useful in risk mitigation strategies, providing importantindications for decision makers. Among these scenarios, anearthquake rupture scenario (S11) was selected as representative.Loss modelling was evaluated for this scenario and comparedwith that predicted by a time-dependent probabilistic earthquakehazard scenario [5]. Number of RC frame buildings estimatedto collapse in the case of the probabilistic hazard scenario willbe 23,291 (4.1%) and casualties 31,521. In the deterministicscenario, losses are effectively doubled in terms of both thenumber of RC frame buildings and number of caualities.Uncertainties in the hazard scenario arise from uncertainties inthe source locations of future earthquake and in the values ofsource parameters such as stress drop and rupture velocity. Inspite of our efforts to describe the ground motion variability, weare still limited in the prediction of ground motions from futureearthquakes by our limited knowledge of the source parameters.Other uncertainties are also depending on the different approx-imation levels when evaluating the effects of site conditions that

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Cum

ulat

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age

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babi

lity

0 5 10 15 20 25 30 35 40 45 50 0 5 10 15 20 25 30 35 40 45 50 0 5 10 15 20 25 30 35 40 45 50

RC frame type buildings

Low-rise

Mid-rise High-rise

DAMAGE LEVELSlight (Pre-1980)(Post-1980)

(Post-1980)

(Post-1980)

(Post-1980)

Moderate (Pre-1980)

Extensive (Pre-1980)

Complete (Pre-1980)

Fig. 10. Vulnerability relationships for reinforced concrete frame buildings.

KOERI475

0

100000

200000

300000

400000

500000

600000

DIFFERENT EARTHQUAKE SCENARIOS

NO DAMAGE SLIGHT MODERATE EXTENSIVE COLLAPSED

NU

MB

ER

OF

ALL

RC

FR

AM

E B

UIL

DIN

GN

S

S11 S31 S13 S23 S33 S12 S21 S22 S32

Fig. 11. Distribution of damage levels for all reinforced concrete frame buildings in Istanbul with respect to probabilistic (RP ¼ 475) and 9 deterministic earthquake

scenarios.

Fig. 12. Distribution of collapsed reinforced concrete frame buildings for the

deterministic scenario S11.

A. Ansal et al. / Soil Dynamics and Earthquake Engineering 29 (2009) 699–709 707

are generally recognized to cause a significant damage increase inthe urban area. For large areas, as in the case of IstanbulMetropolis, site conditions can be evaluated through a simplifiedstandard procedure (as NEHRP). In the case of smaller areas, whendetailed geotechnical data are available, more detailed analysescan be carried out for site effects estimation (see the Zeytinburnudistrict case in [9]).

The second important findings of our study are the evaluationof the effects of retrofit in decreasing the building damage andcasualties in the city. A parametric study is conducted for differentscenarios to evaluate the damage distributions and effects ofretrofit on damage and casualties. The results of a simulatedmitigation program clearly indicate the importance and theimpact of the retrofitting in decreasing building damage andmore important in mitigating the fatality rates: collapsed RCbuildings, in case of a probabilistic hazard scenario, are reducedfrom 4.1% to 0.26% (1471) and casualties from 31,521 to 2442; incase of a deterministic scenario casualties are reduced from71,322 to 4729.

ARTICLE IN PRESS

5812

5223

2218

7

3180

9

1649

4642

7132

2

355

119

2180

1371

272 43

3

4729

10

100

1000

10000

100000

B111BUILDING TYPE

NU

MB

ER

OF

FATA

LITI

ES

Before RetrofitAfter Retrofit

B112 B121 B122 B131 B132 TOTAL

Fig. 13. The effect of retrofit on fatalities for RC buildings for the representative deterministic scenario S11.

A. Ansal et al. / Soil Dynamics and Earthquake Engineering 29 (2009) 699–709708

The building damage and consequently casualty distributionsare very much affected by the input ground motion characteristicscalculated based on different rupture models. This variability isalso due to the high vulnerability of the building stock.Considering the inaccurate definition of the building stock andthe conservative approach in the utilized vulnerability relation-ships, even minor changes in the ground motion characteristicscan yield significantly different damage levels and patterns.Therefore, one option to achieve more reliable results is toimprove the accuracy of the building stock definition and improvethe vulnerability functions.

The distribution of building types, the average soil conditions,and the vulnerability functions have been approximated for thisstudy, mainly because of the sizeable urban area of Istanbul.Further refinement is necessary in which detailed damagescenarios will be computed based on a quantitative microzonationwith detailed geotechnical data and detailed vulnerability assess-ment of the buildings. For instance, in the case of Zeytinburnudistrict, located south-west of the city well documented buildingvulnerability and soil characterization motivated more detailedanalysis that showed high damage level.

We believe that future research is needed in applyingdeterministic rupture scenarios for damage and loss estimations.Efforts are principally necessary in collecting new data on theelements prone to seismic risk, and vulnerability and fragilitycurves have to be validated with recent observations and properlyimplemented at local scale. Improvements in the shakingscenarios generation are also necessary to correctly take intoaccount the variability of ground motion and to quantify thevariation of source kinematic parameters.

Acknowledgements

This work has been fully supported by the LESSLOSS ‘‘Riskmitigation for earthquakes and landslides’’ European IntegratedProject. Supported by the Sixth Framework Programme, Priority1.1.6.3 Global Change and Ecosystems) Project no.: GOCE-CT-2003-505488). The authors thank the INGV co-workers ofMilan and Rome (F. Pacor, G. Franceschina, A.M. Lombardi, and M.

Cocco) for their collaboration and E. Faccioli and R. Spence(coordinators of the SP11 and SP10 of LESS LOSS project) for theirencouragements and effort supporting our research. We wouldalso thank Liam Finn, Editor-in-Chief, and two anonymousreviewers whose comments and suggestion improved the paper.

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