relative seismic shaking vulnerability microzonation

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Relative seismic shaking vulnerability microzonationusing an adaptation of the Nakamura horizontal

to vertical spectral ratio method

Mic h a e l L Tu r n b u l l

Central Queensland University, Faculty of Business and Informatics, Bundaberg DC, Queensland, Australia.

e-mail: M.Turnbull.cqu.edu.au

An alternative seismic shaking vulnerability survey method to computational intensive theoreticalmodelling of site response to earthquake, and time consuming test versus reference site horizon-tal ratio methods, is described. The methodology is suitable for small to large scale engineeringinvestigations. Relative seismic shaking vulnerability microzonation using an adaptation of theNakamura horizontal to vertical spectral ratio method provides many advantages over alternativemethods including: low cost; rapid field phase (100 km2 can easily be covered by a single operatorin 5 days); low and flexible instrumentation requirements (a single seismometer and data logger ofalmost any type is required); field data can be collected at any time during the day or night (the

results are insensitive to ambient social noise); no basement rock reference site is required (thuseliminating trigger synchronisation between reference and multiple test site seismographs); rapidsoftware aided analysis; insensitivity to ground-shaking resonance peaks; ability to compare resultsobtained from non-contiguous survey fields. The methodology is described in detail, and a practi-cal case study is provided, including mapped results. The resulting microzonation maps indicatethe relative seismic shaking vulnerability for built structures of different height categories withinadjacent zones, with a resolution of approximately 1 km.

1. Introduction

There are two broad categories of methods used incharacterising the horizontal response of a parti-cular surface site to incident seismic energy theo-retical modelling and empirical measurement.

In theoretical modelling basic physical theoryand knowledge of the site conditions (e.g., geology,topography and boundary conditions) are usedto create a mathematical model of the site. Thesolution(s) to these mathematical models requireextensive computational capability and expertknowledge of computer program and numerical

methods. Models of one, two and three dimen-sions have been produced (c.f., Coutel and Mora1998). Theoretical modelling depends on detailedphysical knowledge of the site of interest. Such

detailed knowledge is rarely available in practice.

Assumptions have to be made which reduce con-fidence in the modelled results. The formulationand solution of the model is time consuming andexpensive.

The empirical measurement category of siteresponse characterisation relies on direct mea-surement of horizontal ground movement ampli-fication within the area of interest. The groundmovement at a matrix of sites within the areais measured and the results are used to pro-duce a static map depicting the relative seismicshaking vulnerability present at adjacent sites.

Two methods that fit into this category are thetest/reference site spectral ratio method andthe single site horizontal/vertical spectral rationmethod.

Keywords. Microzonation; earthquake hazard; Nakamura; ground motion; geophysics; seismology; natural hazards.

J. Earth Syst. Sci. 117, S2, November 2008, pp. 879895 Printed in India. 879


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880 Michael L Turnbull

In contrast with the theoretical modellingmethod, the empirical measurement methods donot rely on extensive computing power. Althoughthe data collection and some of the analysis requirevery modest computing facilities, much of theresult presentation can be done manually if neces-sary. This makes the method particularly suited for

developing countries and small institutions.

1.1 Two site spectral ratio method

This method relies on the presence, within the areaof interest, of a reference site that has the responsecharacteristics of basement bedrock. Such a refer-ence site may be obtained by boring a hole downto the bedrock and installing an instrument at thebottom of the hole; or, preferably, by locating aninstrument on a nearby outcrop of solid basementrock. The quality of results obtained using thismethod is dependent on the characteristics of thereference site and considerable care must be takenin choosing a suitable reference site (Steidl et al1996).

During the measurement period two instru-ments are deployed, one at the site of interestand one at the reference site. The instrumentsare triggered simultaneously, or within an overlap-ping time period, to measure ground movementat both sites stimulated by a common seismicenergy source. The horizontal time series data from

each site is converted by Fourier transform tech-niques to an amplitude or power spectrum and theratio of the site spectrum to the reference spec-trum is produced. The site to reference ratio is adirect measure of the horizontal ground movementamplification at the site of interest.

If the reference site is the actual basementbedrock under the measurement site then the ratiois equivalent to the basement to surface layer,frequency dependent horizontal transfer functionTBS(f); defined as follows, where HS(f) is the hori-zontal spectrum at the surface layer, and HB(f) isthe horizontal spectrum at the basement layer:

TBS(f) =HS(f)

HB(f). (1)

This method has been employed using various seis-mic energy sources including: earthquake S waves(c.f., Chavez-Garca et al 1997; Coutel and Mora1998; Wen et al1995a, b); P waves (c.f., Lachet et al1996); earthquake coda (c.f., Field 1996); ambi-

ent seismic noise (c.f., Seht and Wohlenberg 1999;Konno and Ohmachi 1998; Coutel and Mora 1998;Lachet et al1996; Chavez-Garca et al1996; McCueand Boreham 1996; Field 1996; Ferritto 1996;Seekins et al 1996; Clithero and Taber 1995; Field

and Jacob 1995; Somerville et al1993; Kagami et al1986); and high explosive blasts (c.f., Malagniniet al 1996).

There has been considerable interest in using thismethod employing ambient seismic noise as thesource. This technique has the obvious advantagethat the instrumentation does not need to be put

in place over long periods to observe actual earth-quake events. It also has the distinct advantageof not requiring invasive drilling and blasting. Allthat is needed is for the reference instrument tobe deployed and the site instrument to be thentransported from station to station in order to col-lect matching pairs of ambient noise recordings. Ifnumerous sites are to be occupied, however, there isstill considerable time involved. There is also thelogistic difficulty of simultaneous triggering of theinstruments to be considered.

The two site spectral ratio method has beenused in a limited capacity for microzonation whererelatively few sites have been used (c.f., Lachetet al 1996; McCue and Boreham 1996; Clitheroand Taber 1995; Sommerville et al 1993; Darraghand Shakal 1991). It has had restricted applica-tion in large-scale high-resolution microzonationexcept for one notable exception in Perth, westernAustralia (Gaull et al 1995). In this latter studysix instruments were used simultaneously; five atbasin stations, and one at the reference site. Thefive basin stations were deployed to take late night

simultaneous readings over two nights. Over 100sites were occupied using 3 km grid spacing, imply-ing that the data collection would have taken morethan 40 days.

The method has the disadvantage that the pres-ence of noise generated by localised social move-ment (cars, trucks, trains, pedestrians, etc.), whichdoes not equally affect the site and referenceinstrument, tends to produce results which are notcharacteristic of the site of interest, but are charac-teristic of the energy source. Consequently the peri-ods during which the technique can be employedare limited to those times of the night whensocial noise is at a minimum (usually in the hoursbetween midnight and dawn). It also has the dis-advantage that it cannot be employed in areaswhere a suitable reference site is not available.

1.2 Single site spectral ratio method

If it can be shown that the vertical ground motionat a site of interest is characteristic of the basementbedrock motion at that site, then the horizontal to

vertical ground motion ratio will correspond to thesite to reference ratio measure of horizontal groundmotion amplification. The single site spectral ratiomethod of characterising site response relies onthis condition being approximated. In this method,


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Relative seismic shaking vulnerability microzonation 881

the simultaneous horizontal and vertical groundmotion is measured using a single multi-axis instru-ment. The amplitude or power spectrum of thehorizontal and the vertical data are determinedusing standard Fourier transform techniques, andthe ratio of the horizontal to vertical spectra isproduced. This method is generally referred to as

the Horizontal to Vertical Spectrum Ratio (HVSR)method.

1.3 The Nakamura method

In 1989, Yutaka Nakamura used the single siteHVSR method to study responses at socially noisysites, using ambient seismic noise sources, andfound that the results resembled the transfer func-tions for horizontal motion in the surface layers.Nakamura showed that, for a relatively wide fre-quency range, localised noise sources consisting of

mainly Rayleigh waves were cancelled out duringthe horizontal to vertical ratio process. His reason-ing was as follows.

Nakamura noted in the basement to surfacelayer, frequency dependent horizontal transferfunction TBS(f) (see equation 1) that HS(f) isreadily affected by locally generated social noise,which mainly consists of Rayleigh waves. Naka-mura also noted that the vertical spectrum at thesurface layer VS(f) should include the local Raleighwave contribution, but the basement verticalspectrum VB(f) should not.

Assuming that the surface layer does not amplifythe vertical ground motion, the effect of thelocal Rayleigh waves on the incident microtremormotion within the surface layer can be representedas:

S(f) =VS(f)

VB(f), (2)

where there is a Rayleigh wave contribution, S(f)will be greater than unity and this will converge

to unity as the contribution of the local Rayleighwave decreases; therefore S(f) is greater than orequal to unity at all frequencies.

Assuming that the effect of the local Rayleighwave on the horizontal and vertical incident motionis equal (i.e., its ellipticity is unity), a modifiedsurface layer horizontal transfer function TBSM(f)may be defined as:

TBSM(f) =TBS(f)

S(f). (3)

We also define the following ratios:

RS(f) =HS(f)

VS(f), (4)

RB(f) =HB(f)

VB(f), (5)

which allows TBSM(f) to be expressed as:

TBSM(f) =RS(f)

RB(f). (6)

Nakamura was able to show that the 24 h aver-aged horizontal to vertical basement ratio RB(f),for three different measurement sites, was approxi-mately unity over a frequency range from 0.1 to20 Hz.

Under the condition that RB(f) 1 (i.e., theellipticity of the incident waves in the basementmaterial is approximately unity), equation (6)reduces to

RN(f) = TBSM(f) RS(f) = HS(f)

VS(f), (7)

where RN(f) is referred to as the Nakamuraspectral ratio.

It can be seen that the Nakamura spectral ratiois the basement to surface layer, frequency depen-dent horizontal transfer function TBS(f), modifiedto allow for the possible presence of a Rayleighwave generated locally within the surface layer.Under the assumption that the ellipticity of the

local Rayleigh wave is unity, the effect of the localRayleigh wave is cancelled out of the modifiedhorizontal transfer function.

In reality ideal cancellation does not occur andthe modified horizontal transfer function does notreproduce the original horizontal transfer functionfaithfully. Spectra produced using the Nakamuraratio are similar to, but demonstrably differentfrom, those produced using the horizontal transferfunction. This may be due to several factors someof which are suggested below.

The locally generated noise may not be purelyRayleigh waves.

The ellipticity of the local noise waves in thesurface layer may not be unity.

The ellipticity of the incident waves in the base-ment layer may not be (indeed probably wouldnot be) unity.

The ellipticity of the local noise and the incidentwaves may vary over time and space dependingon the nature of the local noise and the incidentwaves.

The Nakamura method is a special application ofthe HVSR method. It has the particular advantageof providing an efficient and cheap means of collect-ing data from numerous sites, within a short space


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of time, at any time during the day. Support forthe assumption that RB(f) 1, or at least that theaverage over the frequency range of interest isapproximately unity, has been reported by laterresearchers (c.f., Somerville et al 1993; Lermo andChavez-Garca 1993, 1994; Schlindwein and Koch2003).

Over the past decade the Nakamura method hasbeen used in numerous site response characterisa-tion and microzonation studies (c.f., Clithero andTaber 1995; Lachet et al 1996; Milana et al 1996;Seekins et al1996; Field 1996; Konno and Ohmachi1998; Jones et al 1998; Cuthbertson et al 1998;Michael-Leiba and Jensen 1999; Schlindwein andKoch 2003; Bragato and Slejko 2005; Drouet et al2005; Ferretti et al 2007). A summary of micro-zonation surveys carried out within Australia upto the end of 1999 is provided by Jensen (2000).

Several studies have been carried out to comparethe results of the Nakamura method with thoseobtained by other methods, including the generalHVSR and reference site methods. Some studieshave reported adverse findings (c.f., Malagnini et al1996), while numerous others indicate that theNakamura method is valid within certain con-straints (c.f., Lermo and Chavez-Garca 1993, 1994;Clithero and Taber 1995; Field and Jacob 1995;Chavez-Garca et al 1996, 1997; Dravinski et al1996; Field 1996; Lachet et al 1996; Theodulidiset al 1996; Seekins et al 1996; Coutel and Mora

1998; Dimitriu et al 1998; Schlindwein and Koch2003; Bragato and Slejko 2005; Drouet et al 2005;Ferretti et al 2007).

It is now generally recognised (Chavez-Garcaet al 2007) that the Nakamura method adequatelyidentifies the fundamental resonance peak of a sitewithin reasonable error bounds, but is incapableof identifying higher orders of resonance. Similarly,whilst this paper demonstrates that the spectraproduced using the method can be used to quan-tify relative hazard between adjacent sites, they areincapable of indicating the absolute ground motionamplification of a given site.

2. A methodology for deriving Nakamura

spectra from microseismograms

2.1 Length of data collection

Although Nakamura (1989) continuously moni-tored each site for up to 30 hours, only datasets of2048 points, or about 20 seconds of data were used

for analysis purposes. Kagami et al (1986) moni-tored each site for 15 minutes, but only sections of1024 datum points were used for analysis. In car-rying out their microtremor study of Newcastle,Somerville et al (1993) took six series of 33-second

readings at 125 samples per second at each site.From these recordings subsets of 2000 data wereused for analysis.

For data collection at test sites the author choseto record for 2 to 2.5 minutes at a sampling rate of100 samples per second (Turnbull 2001). This pro-vided a total of from 12,000 to 15,000 data points

from each site for analysis purposes.

2.2 Size and conditioning of analysis dataset

The size and numbers of the datasets used by pastinvestigators vary considerably. Similarly, the con-ditioning techniques sometimes applied to the timeseries data prior to performing the Fourier trans-form on it varied considerably.

Michael Winter (Pers. Com. 1999), while a post-graduate student studying at the Queensland Uni-versity Advanced Centre for Earthquake Studies(QUAKES) used numerous analysis routines overan approximate three-year period to perform sin-gle and double site spectral analysis of field datacollected for microzonation within the greater Bris-bane metropolitan area. He employed a variety oftime series data conditioning techniques including:

cosine tapering, linear tapering, overlapping of data windows, demeaning and detrending, high and low pass filtering, and zero filling of incomplete datasets.

From comments included in his software sourcecode, and from personal conversations the authorhad with him, Winter was of the opinion that pre-conditioning of the time series data has little orno effect on the appearance of the resulting spec-tral ratios. This has also been the authors per-sonal experience. As long as the size of the datasetis sufficient, preconditioning the time series databy means of any of the above techniques producesno appreciable difference to the resultant spectral

ratios.

2.2.1 Multiple windowing

Figures 1 and 2 each show comparisons of threeground motion spectra calculated from single win-dow time series datasets obtained from the samesites at different times. Figure 1 shows spectraobtained from the site designated AAB001 duringthree separate data collection episodes, designatedBBGA, BBGC and BBGD. Figure 2 shows spectra

obtained from a different site designated ABA001during three separate data collection episodes,designated BBGB, BBGC and BBGD.

Inspection of the spectra figures 1 and 2 revealsthat, whilst the various spectra obtained for the


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Figure 1. Spectra for site AAB001 derived from time-displaced datasets.

Figure 2. Spectra for site ABA001 derived from time-displaced datasets.

same site at different times are similar, they

contain an obvious degree of difference, due tothe natural variability of the microtremor seismicenergy sources over time. As a consequence of thevariability in the individual spectra it would beundesirable to use any one spectrum for microzona-tion purposes. The results of that process would,in general, be irreproducible by analysis of datacollected at future times and could not be used tomonitor for possible changes in the microzonationresults over time.

A more statistically valid method would be tocombine several spectra obtained at different times

by averaging the data points and calculating thestandard deviation. This could be done either bycollecting time series data by means of several fieldtrips over an extended period of time, or by collect-ing a single time series reading of sufficient lengthto provide a number of mutually exclusive contigu-ous datasets (data windows) of size 1024.

Both of the above methods are equivalent. Theonly difference is the time lag between the sequen-tial windows of contiguous data. In the former casethe time difference may be days or months. In the

latter case the time difference is seconds or frac-tions of a second.The use of multiple windows from the one

time series dataset allows the calculation of themean and standard deviation for further analysis

Figure 3. Spectrum derived from multiple data windows.

purposes and ensures the statistical reproducibilityof the data. A suitable minimum size for the timeseries dataset is considered to be 1024. It wouldseem that, for microzonation purposes, a singleraw data window of sufficient size may be suitable;however, it must be pointed out that the results

obtained from a single data window will not bereproducible, and the use of multiple time serieswindows is a superior method.

Figure 3 depicts a Nakamura spectrum derivedby using 10 data windows each consisting of about100 contiguous data points, extracted from a sin-gle seismogram of about 1024 data points in total.The original dataset used to derive the spectrum infigure 3 is the same dataset used to derive the spec-trum labelled BBGB in figure 2. However, whilstthe individual spectra in figure 2 are in general irre-

producible from data obtained at different times,the spectrum in figure 3 can be reproduced, withinthe calculated statistical bounds, from time seriesdata collected at the site at any time.

2.2.2 Combining the horizontal datasets

There are a number of different ways that the hori-zontal datasets can be combined. They can be com-bined in the time domain or the frequency domain,and in either case a number of combinational algo-rithms can be used. The data could be averaged,

either by simple arithmetic average, by geometricaverage, by using the square root of the mean ofthe squared values (i.e., the RMS or Root MeanSquared value) or by some other more obscuremethod.

Figures 4, 5, 6 and 7 show ground amplificationspectra obtained from the same time series dataset,and with the horizontal components combined byvarious methods.

Inspection of figure 4, and comparison with fig-ures 5, 6 and 7, reveals that geometric combination

of the horizontal components in the time domainproduces a spectrum that is substantially differentfrom the other three methods. This is because, inthe time domain, the geometric averaging processis equivalent to vector addition. The horizontal


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Figure 4. Horizontal combined in time domain by Geomet-ric mean.

Figure 5. Horizontal combined in time domain by Arith-metic mean.

Figure 6. Horizontal combined in frequency domain byGeometric mean.

Figure 7. Horizontal combined in frequency domain byArithmetic mean.

time series datasets are derived from orthogonalorientated sensors. If the motion was being stimu-lated by a point energy source, then the horizontal

signals could be regarded as vector signals and usedto determine the azimuth of the source. However,the microtremor sources that produce the groundmotion are diffused and variable tending to berandom in nature. Therefore, the horizontal sig-nals cannot be interpreted as a primary indicationof the vector direction from which the motional

force is coming. Consequently, geometric averag-ing is inappropriate for combining the horizontalcomponents.

Inspection of figures 5, 6 and 7 shows them to bevery similar in appearance. Whilst there are somesubtle differences between figure 5 and the othertwo, those differences are fairly minor. Figure 6 isidentical in form to figure 7 except for a vertical dis-placement of the trace. This is because the geome-tric average is accentuating the horizontal motionin comparison to the arithmetic average.

For the purposes of microzonation analysisdemonstrated out in this paper it was decidedto combine the horizontal data in the frequencydomain using an arithmetic average.

2.3 A methodology for using Nakamuraspectra to conduct seismic shaking

vulnerability microzonation

2.3.1 Seismic shaking vulnerabilitymicrozonation for engineering purposes

Within an area that is subject to a commonambient earthquake hazard, it is known that, ingeneral, zones of differing vulnerability exist. Thismeans that, on a microzonal scale, earthquakevulnerability (from the same earthquake hazard)is, in general, different from place to place. The aimof a microzonation survey is to quantify the rela-tive vulnerability of a small zone of interest withina larger regional area.

The relative vulnerability of different classes ofbuildings, due to their construction techniques andmaterials, their shape and size, is acknowledged in

the building codes (e.g., Australian building codeAS1170.41993). The Australian building code alsoallocates earthquake site loading factors (S) basedon soil types at the site of interest. Apart from theconstruction attributes of a building (which can beoptimised by engineering design) it is the degree towhich the shaking of the ground is transferred tothe buildings that determines the relative vulnera-bility between adjacent sites. It is almost a trivialobservation that a building that is more likely tobe shaken during an earthquake is at more risk to

damage than one that is not. What is not so trivialis devising engineering survey techniques that willquantify the predisposition of a building of a cer-tain class to shake in response to ground movementcaused by an earthquake.


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Table 1. Shaking frequency ranges for building classes.

Range of number Calculated Frequency rangeBuilding class of storeys frequency range used for analysis

Low-rise 13 103.3 Hz 2.9 Hz 10Medium-rise 49 2.51.1 Hz 1.1 Hz < 2.9High-rise 10+ 1.0 Hz 0.5 Hz < 1.1

Any method of seismic shaking vulnerabilitymicrozonation should provide an indication of thedegree to which seismic energy is transferred fromthe foundations of a building to the building struc-ture. The Australian building code (SAA 1993(a)and 1993(b)) AS1170.41993 quantifies this degreeof energy transfer by specifying a range of site load-ing factors (S) varying from 0.67 for rock foun-dations to 2.0 for the deepest, softest soils. Thisscale of site factors recognises the propensity for

deeper, softer soils to exhibit greater ground move-ment than shallower, denser materials when sub-

jected to seismic shaking. However, the Australianbuilding code, as is common in building codes inmany countries, makes no allowance for resonantground movement amplification observed in someareas.

By using actual site seismic shaking amplifica-tion spectra for the sites of interest this deficiencycan be addressed.

2.3.2 Microzonation using generalised naturalshaking frequency of a built structure

All building structures have a natural shaking fre-quency. If a building is subjected to seismic shakingwhich corresponds with its natural shaking fre-quency then it will absorb more energy, and willshake more violently than if the seismic energy wasconcentrated at some other frequency.

For the purposes of microzonation in this paperit is assumed that the generalised natural shaking

frequency (fN

), of a building with N stories, isapproximated by equation (8) (c.f., Michael-Leibaand Jensen 1999):

fN[Hz] 10

N. (8)

Three classes of building will be considered inthis study; low-rise (1 to 3 storeys), medium-rise(4 to 9 storeys), and high-rise (10 or more storeys).Table 1 lists the range of shaking frequencies rele-

vant to the proposed building classes.Analysis of a sites seismic response spectrumcan provide an indication of the relative distribu-tion of seismic energy within the ranges of fre-quency indicated in table 1. The lower frequency

range for high-rise buildings was set at 0.5 Hzbecause that corresponds to a 20-storey building,which was considered sufficient for the purposes ofthis study. Figure 8 displays a typical site responsespectrum and the associated frequency ranges ofinterest. In figure 8, the frequency axis has beendisplayed in logarithmic form to accentuate thelower frequency ranges which on a linear scalewould be much narrower in display width.

In determining the relative energy content in

any particular frequency range, from one siteresponse spectrum to the next, it is sufficientto use the average amplitude of the measure ofground movement amplification (the pseudo gain).Within any given set of site response spectra, thepseudo gain for each frequency range will varyacross the range that includes the natural shak-ing frequency of structures built on that site. Thesite that exhibits the largest average pseudo gainwithin a particular frequency range will present thegreatest seismic shaking vulnerability to buildings

of the associated class within the data collectionarea.Depending on the intended use of the microzona-

tion results the relative vulnerabilities may be pre-sented as numerical values over an arbitrary range,or by qualitative descriptions.

In conformity with the AS1170.41993 site fac-tor allocations (S), following analysis of the siteresponse spectra for each building category, theauthor has devised an empirical formula for allo-cation of arbitrary (but consistent) microzonationsite factors (SM), based on a partitioning of the

pseudo gain (G) at each site in relation to the maxi-mum pseudo gain (GMax) of all sites within themicrozonation area. The microzonation site fac-tors (SM) determined by this method are listed intable 2.

It should be noted that the microzonationsite factors (SM) are not intended to override theAS1170.41993 site factors (S). A conservativeapproach should be maintained in using the micro-zonation site factors to supplement a building code.The microzonation information should always be

used in conjunction with the building code, and notin isolation. In all instances the higher of the sitefactors obtained from the joint application of thebuilding code and the microzonation results shouldbe used.


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Figure 8. Shaking frequency ranges for building classes.

Table 2. Microzonation site factor allocations.

Relationship of the pseudo gain (G) within the frequency range Microzonationof interest at a particular site, to the maximum pseudo gain site factor(GMax) within the same frequency range at all sites (SM)

G < 1.0 0.671.0 G < (GMax 0.25) 1.00(GMax 0.25) G < (GMax 0.50) 1.25(GMax 0.50) G < (GMax 0.75) 1.50(GMax 0.75) G GMax 2.00

2.4 Microzonation of Bundaberg city usingNakamura spectra A case study

2.4.1 The seismic setting of Bundaberg city

Bundaberg is situated on the Burnett River, about20 to 30km from its mouth, in sedimentary

deposits confined in a basin bounded by outcropp-ing of bedrock consisting chiefly of coal measures.The basin is filled primarily with Tertiary flu-vial deposits. The unconsolidated deposits range indepth from 15 to 70 m within the microzonationsurvey area.

The current Australian earthquake loading code,AS1170.41993, places all of Bundaberg city withinthe highest earthquake hazard region of Queens-land. Research into the earthquake hazard existingin the Bundaberg area (Turnbull 2001) suggests

that the crustal stress gradient is such as to resultin a relatively high risk, within the Australiancontext, of the recurrence of potentially damagingearthquakes, of relatively large magnitude; and,whilst it is probably true that all of Bundaberg is

subject to the same regional hazard from earth-quake occurrence, it can be demonstrated thatsimilar structures in different parts of the city arenot subject to the same relative risk to damagefrom the same earthquake event.

Macroseismic data collected subsequent to earth-quakes that occurred within 120 km of Bunda-

berg in 1918 and in 1997 indicates that thesurface foundation, on which Bundaberg is sited,has a tendency to amplify ground movementto varying degrees (Rynn 1985; Turnbull 2001).This variability of ground motion amplificationcan be attributed to differences in the natureand structure of the surface foundation layers.High amplification is associated with deep soilsand unconsolidated materials. Amplification is alsoaffected by the nature and structure of base-ment materials. Material interfaces that present

a sharp gradient in shear wave propagation velo-city can, depending on the interface geometry,reflect a considerable proportion of seismic energy(Field 1996; Dravinski et al 1996). Under condi-tions where the basement geometry is suitable,


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Figure 9. BBGA data collection sites.

considerable seismic energy resulting from reflectedbasin-edge-induced waves could conceivably beconfined within a basin for extended time, after theinitial waves have passed (Field 1996).

Given the relatively high earthquake hazard pre-sented to Bundaberg city, and the observed vul-

nerability of the city to earthquake shaking, itwas considered to be a suitable area in whichto trial the relative seismic shaking vulnerabil-ity microzonation using the authors adaptationof the Nakamura horizontal to vertical spectralratio method. The method was used to conducta study into the distribution of horizontal groundmovement pseudo-amplification in the Bundabergcity area. The results of this study have providedmicrozonation data that can be used to supple-ment Australian earthquake loading codes, such asAS1170.41993, providing refinement of the codes

within Bundaberg.

2.4.2 Data collection sites

The field measurements were conducted in twoseparate episodes.

In the first episode, designated BBGA, 112 siteswere occupied in the residential zone south of theBundaberg TAFE College. Viable data was col-lected from 95 of the sites. The remaining sites werenot viable due to operation abnormalities, such as

non-levelling of the sensor or failing to realise thatthe recorder memory was full. The sites were cho-sen on street intersections or about 100 m apart.Figure 9 is a map depicting the viable sites occu-pied during the BBGA data collection episode.

Subsequent to the collection of the BBGA fielddata it was realized that coverage of the whole ofthe Bundaberg area at that resolution was imprac-tical. Previous investigators (c.f., Gaul et al 1995)have indicated that grid spacing in the order of3 km was sufficient for the purposes of microzona-

tion. Other investigators (McCue and Love 1997)have demonstrated that irregular spacings of 1 kmor less are sufficient to produce microzonation bymeans of mapped relative risk contours. As it wasthe intention of this current investigation to pro-duce contoured risk maps of the area under investi-gation, it was decided to use a grid spacing of 1 km.

In the second episode, designated BBGB, 88viable sites were occupied, covering most of theBundaberg city local government area. The siteswere chosen as near as possible to the intersec-tion of the 1000 m grid lines on the Hema Bund-

aberg street map (Hema 1997). Those potentialsites already occupied during the BBGA episodewere not reoccupied. Figure 10 is a map depict-ing the viable sites occupied during the BBGBdata collection episode, and includes those BBGAsites that were suitable for inclusion in the BBGBdataset.

2.4.3 Instrumentation

All data collection was done using a combination

of Kelunji classic seismograph and SprengnetherS6000 tri-axial seismometer. The analogue dataprocessing boards in the Kelunji instruments usedfor data collection employ direct current couplingand are capable of recording signals in the range


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Figure 10. BBGB data collection sites.

from 0 Hz up to 25 Hz, with a dynamic range inexcess of 90 dB (Pers. Com. Adam Pascale, SeismicResearch Centre, 26 March 2001; Appendix 1).

The output characteristic specification sheet forthe S6000 (Appendix 2) indicates that this sen-sor provides a usable signal of 5 volts per ms1

at 0.4 Hz. This represents a reduction of 13.8 dB

of voltage below the nominal level; well within thedynamic ranges of the Kelunji Classic analogue todigital features. Since a spectral ratio is employedfor analysis the low frequency roll-off does notpresent a technical difficulty. The seismograph pro-vides adequate signal down to at least 0.4 Hz, thusthe lower frequency of 0.5 Hz indicated in figure 8is accurately achieved using this instrumentation.

During data collection the instrumentation wasconveyed in the back of a vehicle. The vehiclesbattery was used to power all instrumentation.A Garmin GPS 12XL was used to determine the

geographical location of each site in terms of itslongitude and latitude. A Suunto MC-1 compass,corrected for 10 easterly deviation of magneticnorth from true north, was used to orientate thesensor at each site. The Springnether S6000 tri-axial seismic sensor is designed with an orientationarrow moulded into the housing. The manufactur-ers recommend that the instrument be installedwith the arrow pointing due west, so as to ensurecorrect polarity of the horizontal sensors. At eachsite the arrow of the sensor was orientated to the

west, except in cases where leveling of the sensorcould not be achieved. Since the results of themicrozonation were not dependent on the correctpolarity of the horizontal sensors, in those rareinstances the arrow was orientated to the east.

The data from the Kelunji Classic seismographwas downloaded to a Toshiba 220CDS laptop run-ning the Microsoft Windows95 V4.00.950 Boperating system, using Telix V3.51 communica-tions software for DOS V3.1 or higher.

2.4.4 Data analysis

The micro-seismograms recorded at each of thedata collection sites were analyzed in accordancewith the microzonation methodology explainedin section 2.3. This resulted in allocating eachsite with three microzonation earthquake loadingsite factors (SM), for low-rise, medium-rise andhigh-rise buildings, depending on the relative hor-izontal ground movement amplification exhibitedat that site.

The ESRI ArcMapTM 2D Spacial Analyst com-puter application was used to convert the SM value

determined for each site to contoured earthquakeshaking vulnerability zones by interpolation, anddisplayed on maps of the Bundaberg city area(see figures 11, 12 and 13). Manual analysis pro-duces almost identical results but is more timeconsuming.

2.4.5 Qualitative descriptions

The boundaries between adjacent vulnerabilityzones depicted in figures 11, 12 and 13 areapproximate only, and may vary from the actual

positions depicted. For explanatory purposes thequalitative descriptions listed in table 3 may beused.

In using these descriptions (and also the arbi-trary SM values) it must be kept in mind that,


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Figure 11. Bundaberg earthquake loading site factors for low-rise buildings.

whilst the relative vulnerability zones depicted inthe microzonation maps are internally consistentwithin the source dataset (i.e., they are applicablewithin the Bundaberg city area), they cannot beused to compare the Bundaberg vulnerability zoneswith vulnerability zones derived for other areas,using a different spectral dataset.

2.4.6 Commentary on common features of the maps

The maps contained in figures 11, 12 and 13 dis-

play colour coded earthquake zone vulnerabilityfactors SM. The colours blue, green, yellow, orangeand red correspond to SM = 0.67, 1.0, 1.25, 1.5 and2.0 respectively. Commentary will be presented inqualitative terms.

All three maps display well-defined vulnerabilityzones superimposed on a background of moderatevulnerability. In the centre of the low-rise and high-rise maps is a large moderately low to moderatezone extending east to west from Kepnock to Mill-bank, and north to south from north Bundaberg to

Thabeban. This central zone is intersected NNE toSSW by a central corridor of higher value. The cen-tral zone is recognizable in the medium-rise map astwo moderately low to moderate zones in the Kep-nock and Millbank areas, with a wide separation

of moderate vulnerability between them. The NNEto SSW central corridor of high values has appar-ent extensions in the areas of the Airport and theeastern part of north Bundaberg. These extensionsappear on all three maps. There are five high valuezones at the boundaries of the measurement area tothe north, west and south that have counterpartsidentifiable on all three maps: Avoca/Sharon; theAirport; south Thabeban; east Bundaberg; and theeast section of north Bundaberg.

2.4.7 Commentary on features

of the low-rise map

The map shown in figure 11 displays several well-defined vulnerability zones superimposed on abackground of moderate vulnerability. In the cen-tre is a large moderately low to moderate zoneextending east to west from Kepnock to Mill-bank, and north to south from north Bundabergto Thabeban. This central zone encloses an oblongcentral island of higher values that separates twozones of low to moderately low to the east and west.

The central island contains a moderately high tohigh core centred on the area just south of the cen-tral business district (CBD). The oblong centralisland of high values has apparent extensions in theareas of the Airport and the eastern part of north


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Figure 12. Bundaberg earthquake loading site factors for medium-rise buildings.

Figure 13. Bundaberg earthquake loading site factors for high-rise buildings.


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Table 3. Qualitative description of relative risk.

Seismic microzonation Qualitative descriptionloading factor (SM) of relative seismic risk

0.67 Low to moderately low1.00 Moderately low to moderate1.25 Moderate1.50 Moderate to moderately high

2.00 Moderately high to high

Bundaberg. The central zone is framed by a seriesof high value zones to the north, west and south.The high value zones in the areas of Avoca/Sharon,the Airport, east Bundaberg and the east sectionof north Bundaberg exhibit core values of modera-tely high to high.

2.4.8 Commentary on features

of the medium-rise map

The map shown in figure 12 displays several well-defined vulnerability zones superimposed on abackground of moderate vulnerability. Distinctivefeatures are the two high value zones thrusting intothe central area of the map from the NNE andSSW. In the centre is a broad background area thatseparates one oblong moderately low to moderatezone (from Kepnock through almost to the CBD)in the east from another (from Millbank down toSugarlands) in the west. The perimeter is flankedby a series of high value zones to the north, westand south. The high value zones in the areas of theAirport, south Thabeban, the east section of northBundaberg and north Sharon exhibit core values ofmoderately high to high.

2.4.9 Commentary on featuresof the high-rise map

The map shown in figure 13 displays several well-defined vulnerability zones superimposed on a

background of moderate vulnerability. In the cen-tre are two moderately low to moderate centralzones extending east to west from Kepnock to Mill-bank, and north to south from north Bundaberg toThabeban separated by a background central cor-ridor. The central zones are framed by a series ofhigh value zones to the north, west and south. Thehigh value zones in the areas of the Airport, southThabeban, east Bundaberg and the east section ofnorth Bundaberg exhibit core values of moderatelyhigh to high.

3. Conclusions

The seismic shaking vulnerability survey methodo-logy described in this paper provides an effective

practical alternative to computational intensivetheoretical modelling of site response to earth-quake, and time consuming test versus referencesite horizontal ratio methods. The author con-cedes that alternative methods have advantagesnot exhibited by the method herein described. Forexample, the authors method cannot determine

the absolute horizontal amplification factor at testsites, and it has limited ability to determine theunconsolidated substrate depth at test sites. Rela-tive seismic shaking vulnerability microzonationusing an adaptation of the Nakamura horizontal tovertical spectral ratio method provides the follow-ing advantages over alternative methods.

Low cost. It does not require high speed com-puting facilities.

Non-invasive. It does not require artificial seis-mic energy sources (i.e., explosions). There is no

need to wait for natural seismic events. Low and flexible instrumentation requirements.

A single seismometer and data logger of almostany type is required.

Rapid field data collection phase. 100 km2 caneasily be covered by a single operator in 5 days.

Field data can be collected at any time duringthe day or night because the results are insensi-tive to ambient social noise.

No basement rock reference site is required thuseliminating trigger synchronisation between ref-

erence and multiple test site seismographs. Insensitivity to ground-shaking resonance peaks

thereby eliminating any reliance on resonancepeaks for results interpretation.

Rapid computer aided analysis using standardGIS software.

The results have both intuitive town planningand practical engineering interpretation.

The results can be presented as arbitraryquantitative relative values or as qualitativedescriptions.

The results obtained from non-contiguous survey

fields can be relatively compared.

The resulting microzonation maps produced bythis method indicate the relative seismic shakingrisk for built structures of different height cate-gories within adjacent zones, with a granularity ofless than 1 km.

Acknowledgements

The author acknowledges the assistance of

Professor Bruce Boreham (Central QueenslandUniversity), and Adjunct Professor Kevin McCue(Geoscience Australia and Central QueenslandUniversity) in the development of the ideaspresented in this paper.


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Appendix 1 Kelunji classic specifications


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Appendix2S6000O

utputvs

frequencyrespo

nse


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MS received 29 September 2007; revised 12 March 2008; accepted 26 March 2008

relative seismic shaking vulnerability microzonation

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