broadband seismic network of iran and increasing quality of seismic recordings

Broadband Seismic Network of Iran andIncreasing Quality of Seismic Recordingsby Anooshiravan Ansari and Kambod Amini Hosseini

INTRODUCTION

In the last decade, the number of seismic stations has increasedsignificantly, and new denser regional networks with advancedtechnology have been installed worldwide. Moreover, the recentimprovements in the quality of seismological instruments haveresulted in the application of modern broadband seismometerswith high dynamic range digitizers for most seismological stud-ies. Among various seismic data, broadband networks providevaluable data for seismological research. Broadband systems arebeing widely used in many research areas, such as seismic sourcestudies and frequency-dependent attenuation in the Earth, par-ticularly from body waves and moment tensor solutions (Mar-shall et al., 1972; Douglas, 2001).

Tectonically, the Iranian plateau is located in the centralpart of the Alpine–Himalayan orogenic belt, which is knownas one of the most active seismic regions of the world. Manymajor and strong earthquakes have occurred in Iran during itshistory (Berberian and Yeats, 1999). The 1962 Boen-ZahraM s 7.2, 1978 Tabas Mw 7.4, 1990 Manjil Mw 7.4, and2003 Bam Mw 6.4 earthquakes are among the deadliest earth-quakes in the world. Installation of broadband networks greatlyhelps to monitor the seismicity of the country, obtain accuratecrustal velocity models, and study source characteristics.

In Iran, major activities related to monitoring of earth-quakes are carrying out by the seismography networks of theGeophysical Institute of Tehran University (IGTU) and thebroadband seismic network of the International Institute ofEarthquake Engineering and Seismology (IIEES). The mainpurpose of the IGTU network is the determination and an-nouncement of location and magnitude of earthquakes aroundthe country; the IIEES network is mainly used forresearch purposes. Local networks also have been installed insome provinces and cities, including the seismic network ofKhorasan (operated by Mashhad University) and an affiliatednetwork of seismic monitoring of the Tehran Disaster Mitiga-tion and Management Organization.

Real-time earthquake processing systems rely on high-quality seismic data to compute accurate earthquake locationsand magnitudes, moment tensor solutions, finite-fault models,and shaking intensity. High-quality broadband data is requiredto characterize a wide range of Earth science subjects, such asimaging the interior of the Earth or determining the size andrupture of large earthquakes. Therefore, it is important tohave monitoring and quality control strategies to improve the

accuracy of seismic recordings within the broadband seismicnetworks. As part of the standard quality control procedure ofthe raw seismic data, the background noise power spectral den-sity (PSD) is systematically estimated for all broadband stationsof IIEES using the procedure of McNamara and Buland(2004). These PSDs are statistically analyzed to compute prob-ability density functions (PDFs), which provide a useful tool formonitoring the network performance. The PDFs help to iden-tify the stations that have anomalous noise levels, as well as toinvestigate the major sources of noise at different frequencybands. They also enable the researchers to study the dailyand seasonal variations of background noise.

In this paper, we first introduce the broadband seismicnetwork of Iran then present an overall and brief descriptionof the seismicity and seismotectonic of the country. In order toimprove the quality of recordings, a new method for the con-struction of sensor vaults is introduced, and the results of anexperiment are discussed to evaluate the influence of differentenvironmental parameters on background noise level in differ-ent period ranges. The ranks of different stations are alsodetermined based on the level of background noise.

BROADBAND SEISMIC NETWORK OF IRAN

The Iran plateau is compressed between two blocks of Arabiaand Eurasia. The active deformation is not uniformly distrib-uted in this plateau, and different active faults throughout thecountry accommodate the plate convergence (Berberian,1976). Figure 1 shows the seismicity that is mainly concen-trated along the Zagros in the southwest, the Kopeh Daghin the northeast, the Alborz thrust belt in the north, the centralIran zone (Berberian and Yeats, 1999), and in the Makran sub-duction zone (Byrne et al., 1992). This figure also representsactive faults of Iran, with the corresponding mechanism of eachfault (Hessami et al., 2003). Most large earthquakes have shal-low depth (less than 30 km). The seismotectonic provinces ofIran, as proposed by Mirzaei et al. (1998), are also presented inthis figure.

To monitor the seismicity of Iran and collect the requireddata for seismological studies, IIEES established the broadbandseismic network of Iran. The main objectives of creating thisnetwork are (1) to provide an online monitoring system forseismic activities in the Iranian plateau and (2) to create anaccessible earthquake information database. This system can

878 Seismological Research Letters Volume 85, Number 4 July/August 2014 doi: 10.1785/0220130153

be further used for research purposes in the fields of seismol-ogy, earthquake engineering, and disaster management.

The broadband seismic network of Iran began operationin 1998, with the installation of the Ashtian (ASAO) station,followed by construction of Zahedan (ZHSF), Nain (NASN),and Kavosh (THKV) stations. By the end of 2004, 10 broad-band stations were installed, which were operated as an offlinenetwork. The real-time operation of the network started byimplication of very small aperture terminal (VSAT) communi-cation technology in 2004. Sixteen other stations were installedby the end of 2011. To date, the network consists of 26 stations

(Fig. 2). All stations are located on hard rock. Table 1 shows thegeographic coordinates of these stations, along with their cor-responding codes. As depicted in Figure 2, most active stationsare along Alborz mountain ranges in the north and Zagrosmountain ranges in the west. This distribution is based on thetectonic setting of Iran and higher seismicity of these regions(see Fig. 1). For better monitoring seismicity around theTehran metropolitan area, three stations (CHTH, DAMV,and THKV) were installed close to each other around the city.However, the number of active stations is not adequate tomonitor the seismicity of other parts of the country in the

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▴ Figure 1. Seismicity of Iran from 1900 to 2011 and main active faults (Shahvar et al., 2013). Shading of events is proportional to depth(km). The inset maps shows the seismotectonic provinces of Iran and nearby regions (Mirzaei et al., 1998).

Seismological Research Letters Volume 85, Number 4 July/August 2014 879

northwest, northeast, and southeast. Figure 3 provides a mapof magnitude of completeness for earthquakes recorded by thenetwork. Magnitude of completeness is a quantitative measureto study the coverage of the network in different parts ofthe country and is calculated using the method of maximumcurvature (Woessner and Wiemer, 2005). The magnitude ofcompleteness is less than 2.7 for central parts of Iran, whereasthis value is more than 3.1 for the northwest, northeast, andsoutheast.

All the broadband seismic stations are equipped withGüralp CMG-3T sensors (which are sensitive to ground shak-ing in the frequency range of 0.008–50 Hz), 24-bit CMG-DM24 digitizers, Global Positioning System receivers, VSATtransceivers, and local storage systems. VSAT communication

system is applied to transmit waveform data in real time. Thisfacilitates installation of broadband stations in different geo-graphical regions and remote locations. All 26 current seismicstations are powered by the 220 V national electrical network.The new seismic stations will be powered by a 320 W solararray to reduce the electrical power demand. The continuousseismic data are digitized in three channels (Z, N, and E) withsampling rates of 50 and 100 Hz for satellite transmission andlocal storage, respectively.

All earthquake seismic waveforms with magnitude greaterthan 4.5 can be obtained from the website of the network (www.iiees.ac.ir/english/, last accessed May 2014). Local bulletinsand a catalog of earthquakes can be retrieved from this websiteas well.

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▴ Figure 2. Active stations in the broadband seismic network of Iran by the end of 2012. (See Table 1 for details.)

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The main objective of the development of the broadbandnetwork of Iran is to locate every earthquake with a magnitudegreater than 2.0 in the network. Therefore, the seismic networkshould be dense enough to record all earthquake groundmotions and maintain its operation during large events. Thenumber of required stations depends on the overall backgroundnoise of the stations, relative signal strength, seismometry, re-cording equipment, processing techniques, and analysis proce-dures. All these influencing factors are reflected implicitly inthe previous performance of the network. Therefore, the directmethod is used to determine the threshold magnitude of thenetwork. For each magnitude increment, the average maxi-mum station distance is determined based on the analysis ofthe previous seismic bulletin of the network (Ringdal, 1975;VonSeggern and Blandford, 1976). Figure 4 shows the averagedistance from the farthest station that was used to locate pastearthquakes in the broadband seismic network of Iran plottedagainst the local magnitude scale. All seismic P-phase arrivals ofearthquakes from 2004 to 2011 were analyzed, and the averagevalue of maximum distance for each 0.1 magnitude bin wascalculated. For local magnitudes ranging from 2.0 to 6.5, thefarthermost station that detects the event signal is located more

Table 1Station List of Broadband Seismic Network of Iran

Number Name Code Latitude (°) Longitude (°) Elevation (m) Start Time (Year)1 Ashtian ASAO 34.548 50.025 2217 19982 Naein NASN 32.799 52.808 2379 19983 Zahedan ZHSF 29.611 60.775 1575 19994 Tehran THKV 35.916 50.879 1795 19995 Germi GRMI 38.810 47.894 1300 20006 Ghir-Karzin GHIR 28.286 52.987 1200 20007 Damavand DAMV 35.630 51.971 2520 20028 Persian Gulf BNDS 27.399 56.171 1500 20029 Sanandaj SNGE 35.093 47.347 1940 200210 Maku MAKU 39.355 44.683 1730 200411 Shooshtar SHGR 32.108 48.801 150 200512 Charan-Tehran CHTH 35.908 51.126 2350 200513 Kerman KRBR 29.982 56.761 2576 200514 Maravetape MRVT 37.659 56.089 870 200615 Zanjan ZNJK 36.670 48.685 2200 200716 Ghom GHVR 34.480 51.295 927 200717 Ramhormoz RMKL 30.982 49.809 176 200818 Shahrakht SHRT 33.646 60.291 837 200819 Tabas TABS 33.649 57.119 1106 200820 Bojnurd BJRD 37.700 57.408 1337 200821 Khomeyn KHMZ 33.739 49.964 1985 200922 Chabahar CHBR 25.595 60.482 125 200923 Shahrood SHRO 36.008 56.013 1264 200924 Ahram AHBO 28.865 51.297 80 201025 Basiran BSRN 31.996 59.118 1416 201226 Yazd YAZD 32.390 54.591 2210 2012

▴ Figure 3. Magnitude of completeness for earthquakes re-corded by the International Institute of Earthquake Engineeringand Seismology (IIEES) broadband network by the end of 2012.


than 200 km from the epicenter of the event (Fig. 4). There-fore, in cases for which all seismic events are detected by morethan three stations within 200 km distance from the epicenter,the threshold magnitude will be less than 2.0. This is the designtarget of the network: all seismic events with local magnitudesgreater than 2.0 can be detected.

To determine the minimum number of stations requiredto cover the entire country, it is divided into 0:2° × 0:2° grids,assuming that an earthquake can occur in the center of eachcell. The number of stations in 150 and 200 km radii of eachhypothetical event and corresponding azimuthal gap are quan-titative measures of spacial coverage of the network (Havskovand Alguacil, 2006). Using the configuration shown inFigure 5, all earthquakes in Iran will be recorded by more thanfive stations with a distance less than 200 km. The maximumazimutal gap of this configuration will be 150°, whichcorresponds to border regions and central parts of the countrywith very low seismicity. Therefore, the configuration shown inFigure 5, which covers all parts of the country with 100 broad-band stations, is considered as the development plan of thenetwork.

QUALITY OF SEISMIC RECORDS

The standard quality control procedure provides a useful toolfor monitoring network performance, allowing identificationof potential anomalous noise levels. It also helps to investigatethe major sources of noise at different frequency bands andvariations of background seismic noise with weather, season,and time of day. Moreover, it provides a quantitative measureto rank seismic stations according to quality of the raw data atdifferent frequency ranges.

McNamara and Buland (2004) provided a standardprocedure for the calculation of the smoothed PSD of hourlybackground noise. Indeed, PDFs provide a statistical measure to

study the variations of background noise in the course of time.In this study, the PSDs and PDFs of continuous data for allstations of the broadband seismic network of Iran are calcu-lated. The mode and mean curves obtained by the processingof thousands of hourly data are considered as characteristicfunctions of each station. Abnormal data (resulting from eithera new noise source near the station or malfunctioning of theseismic sensors) can be detected by comparing the PSD func-tion of new data with these characteristic curves.

To calculate PSDs and PDFs for the broadband stations inIran, the procedure of McNamara and Buland (2004) is imple-mented. For this purpose, all available data should be considered;there is no removal of earthquakes, system transients, ordata glitches. The instrument transfer function is deconvolvedfrom each time segment, yielding ground acceleration for directcomparison to the new low-noisemodel (NLNM) andnewhigh-noise model (NHNM) of Peterson (1993). Each time series seg-ment is divided into 13 subsegments overlapping by 75%. ThePSD of each hourly data is calculated after removing the meanand long-period trend, tapering using a 10% cosine function andtransforming using the fast Fourier transform algorithm (referto McNamara and Boaz [2005] for details). In the next step,PSDs are gathered by binning periods and power in 1=8 octaveand 1 dB intervals, respectively. To compute the PDF, eachperiod–power bin is normalized by the total number of contrib-uting segments. The mode value in each frequency level corre-sponds to the power value of the noise with maximumprobability value. This makes it possible to construct the modecurve of background noise for each station. To study the varia-tions of noise level in each period, the 10th and the 90th per-centile of the PSD distribution are also calculated for eachstation.

▴ Figure 4. Average distance from the farthest station, whichis used to locate past earthquakes in seismic broadband networkof Iran.

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▴ Figure 5. Optimum configuration of stations of the broadbandseismic network of Iran.


To improve the quality of seismic recordings, the sourcesof background noise should be identified in each station. How-ever, the characteristics and nature of background seismic noiseare different in various frequency ranges. At periods less than1 s, sources of noise are mainly human activities and windeffects (McNamara and Buland, 2004). At periods above 2 s,noise sources are oceanic and large-scale meteorological condi-tions. However, at long-period ranges of more than 20 s, hori-zontal components of noise differ more from NLNM ofPeterson (1993) than do the vertical components. This isattributed to the sensitivity of surface-mounted broadbandseismometers to local, dynamic tilting caused by thermal- andbarometric-induced surface displacements. In this period range,which is of great importance in seismic source studies, back-ground noise is sensitive to diurnal and seasonal variationsof the temperature.

Figure 6 shows the mode curves of background noise forall the broadband stations of IIEES, from the starting date ofoperation of each station to the end of 2012. It is possible to

categorize characteristics of background noise in three differentperiod ranges. In the short-period range of 0.1–1.0 s, noise lev-els are high, which is mainly due to local cultural noise sources.Large diurnal variation of background noise in this period rangeindicates that human activities have great influence on noise levelin most stations. An example is presented in Figure 7, in whichdiurnal variation of background noise in SHRTstation is shown.The 15 dB difference between day and night hours in this figureis an indication of cultural noise in this station. As will be dis-cussed later, locating seismic stations far from sources of culturalnoise is the most effective method to decrease such noise. How-ever, wind turbulence around topographical irregularities willgenerate high-frequency noise signals as well (McNamara andBuland, 2004). It will be shown that installation of sensors insideshallow vaults may decrease seismic noise due to wind load inthis period range.

In the period range of microseisms between 2 and 25 s, thescatter of mode curves of all stations is low (Fig. 6). Moreover,mode curves obey NLNM with approximately 5 dB difference

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▴ Figure 7. Diurnal variations of background noise PDFs in SHRT station.


for the vertical component. Because most stations of the net-work are located a large distance from ocean coastlines, thesecondary microseism peak is slightly shifted to longer periodsaround 6 s (McNamara et al., 2009). In the long-period range(between 20 and 100 s), horizontal components have generallyhigher noise levels than vertical components. This is mainlydue to thermal instabilities and wind-induced tilt in the surfacevaults. Installation of sensors inside shallow vaults with thermalinsulation have positive influence on increasing the quality ofseismic recording in this period range.

STATION CONSTRUCTION AND INCREASINGQUALITY OF SEISMIC RECORDINGS

The background noise in the period range of less than 1.0 s isusually reduced by careful selection of station locations in thebroadband seismic network of Iran. To verify the quality ofseismic data in this period range, the level of background noiseis checked by recording seismic data for at least six hoursduring day time. The level of cultural noise is usually higherin day time; therefore, the maximum level of background noiseis obtained in this period range by recording background noisein this time interval.

Thermal instabilities and barometric changes have themost influence on long-period noise with periods more than20 s. Therefore, thermal insulation is an important step in theinstallation of a broadband seismometer. The objective is toachieve a thermal time constant of sufficient length to signifi-cantly attenuate the diurnal thermal signature (Uhrhammerand Karavas, 1997). Figure 8 depicts the prepared plan of seis-mic vaults used for the installation of broadband sensors. Eachvault consists of a prefabricated steel cylinder with 1.5 m indiameter and 4.5 m in depth, which is entirely buried in theground and fixed using a soil–cement mixture. The cylinderhas a removable lid to allow easy access to the instrumentation.The seismometer is installed on a concrete pier with maximumheight of 10 cm attached to bedrock at the bottom of the vault.The concrete mixture of the pier is composed from fine grainaggregates without any steel wire or reinforcement to make auniform material with an approximately constant coefficient ofthermal expansion. In addition, the sensor pier is thermally in-sulated from ambient temperature using three layers of poly-urethane foam.

Among existing broadband stations of Iran, YAZD andBSRN stations were constructed using this new method ex-plained. In the YAZD station, a comprehensive experimentwas carried out to study the influence of the new design ofseismic stations on increasing quality of seismic recordings. Forthis purpose, simultaneous measurement of background noiseon the ground surface and inside the vault was performed for90 days (Fig. 9). Wind speed and direction, humidity, and tem-perature inside and outside of the vault were also measured inthis period of time. Figure 10 shows some of these results forthe first 12 days of sensor installation. The humidity and tem-perature inside the vault became stationary after 12 days. Thestep-like shape of vault temperature and humidity in day 2 is

due to opening of the vault door, which was done to study theinfluence of door opening on changing the stationary conditionof the vault. Figure 10a depicts the fluctuations in the windvelocity. The maximum measured wind speed during the 90-day period of experiment was 21:0 m=s. Figure 10b shows thatdominant wind direction in this period is 170° from the east.

Figure 11 shows the mode curves and the 10th and 90thpercentiles of the PSD distribution for the surface and interior-

▴ Figure 8. Design of the seismic vault used for broadband sta-tions in Iran.

▴ Figure 9. A view of YAZD station. The surface sensor is in-stalled under the protective dome.


vault sensors in YAZD station during a 90-day recording. Inthe short-period range, there is a decrease of about 5–10 dB innoise level for both vertical and horizontal components for thesensor located inside the vault. This could be due to the pro-tection of the sensor from surface wind. Decreasing the differ-ence between the 10th and the 90th percentile curves in thisperiod range is an indication of positive influence of the vaultin providing more stable conditions for the sensor. Changes ofthe noise level in this period range could not be referenced tocultural noise because both sensors are located the same dis-tance from the nearby small village. In the period range ofmicroseisms (1–20 s), the mode and the 10th percentile curvesclosely track the NLNM of Peterson (1993). Also, the secon-dary microseism is narrow and peaked at longer periods (6–7 s)relative to the NLNM. A strong primary microseism may alsobe observed in the 90th percentile at approximately 20 s periodfor vertical components.

As indicated in Figure 11 for horizontal components, thedecrease in the noise level of the vault sensor is less than 10 dB,which is more clearly reflected in the 10th percentile curves. Itshould be noted that there are no thermal instabilities for thesensor located inside the vault (Fig. 10d). Sorrells (1971) andSorrells et al. (1971) explained that atmospheric perturbationscan be the cause of long-period noise in the period band of 20–100 s, with different mechanisms for vertical and horizontalcomponents. Local atmospheric pressure changes due to evenlow wind speed produce a static loading of the ground, whichgenerates earth motions. These ground movements can be theprincipal sources of noise on the vertical component. Theirhorizontal amplitudes are small but generate tilts of the groundsurface that produce noise on the horizontal components re-gardless of the rock type. Stutzmann et al. (2000) also men-tioned that installing the station 40–50 m below the surfacedoes not attenuate daily noise variations of the horizontal com-

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ponents of GEOSCOPE stations for periods longer than 20 s.The temperature of the sensor location is certainly constant inthis depth due to the insulating property of the soil. Thus suchdaily variations of seismic noise for long periods could be theresult of the pressure changes on ground surface due to thewind. This is supported by the fact that noise level for longperiods (more than 20 s) is higher in the east–west directionfor the on-ground sensor, as depicted in Figure 11. AsFigure 10b indicates, the predominant wind direction is alsoeast–west. In other words, based on the results of this experi-ment, wind had a dominant effect in generating long-periodnoise for horizontal components in surface vaults. Therefore,site selection of surface broadband stations is of crucial impor-tance. The quality of recording can be increased in the entireperiod range by choosing locations far from cultural sourcesand quiet from winds.

QUALITY CONTROL OF SEISMIC DATA ANDRANKING OF THE STATIONS

All active stations in the network can be sorted according toabsolute difference of the mode curve from NLNM of Peterson(1993) in different period ranges. Figure 12 depicts the rankingof stations, sorted according to average mode values of threecomponents in three period ranges: 0.1–1.0, 1.0–10.0, and10.0–100.0 s. It should mentioned that in the 0.1–10.0 s

period, the quality of all three components of noise are approx-imately at the same level; whereas, in the long-period range(10.0–100.0 s), the quality of vertical component is generallymuch better than the horizontal motions. This is due to the factthat horizontal sensors are more susceptible to ground tilt causedby atmosphere–solid Earth interactions (Fukao et al., 2002).

As shown in Figure 12, there is more than 35 dB differencebetween the noise levels of the best and the worst stations ofthe network in the 0.1–1.0 and 10.0–100.0 s period ranges,respectively. In these ranges, BSRN records the best qualitydata among other stations of the network. This can also beobserved in Figure 13. However, such difference is not clearin the 1.0–10.0 s period range.

Ranking of stations at different period ranges can be usedto establish the priority for rehabilitation of each station. Themost effective solution for those stations with a high level ofcultural noise is to change the location of the station. However,for stations where noise is mainly induced by wind, the sensorshould be installed inside a buried vault to decrease the noiselevel for short periods.

CONCLUSION

The broadband seismic network of Iran was designed and con-structed to gather high-quality waveform data from the entirecountry. The network is used for monitoring and studying the

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▴ Figure 11. Mode curve (dashed gray line), 10th percentile (thick dark gray line), and 90th percentile (thick light gray line) of the powerspectral density (PSD) distribution for on-ground (top row) and inside-vault (bottom row) sensors in YAZD station. Black lines show theNHNM and NLNM (Peterson, 1993).


seismic signals at different frequency bands. The quality of seis-mic signals is of primary interest, which requires special atten-tion for the selection of proper location and constructionof high-quality stations in the network. For this purpose, anew design for making sensor vaults was prepared and con-structed in the YAZD station. An experiment was performedin this station to identify the influence of effective parametersin background noise of broadband stations. Fluctuation ofenvironmental parameters such as temperature, humidity, windvelocity, and direction was measured in a period of 90 days fortwo sensors, one installed on the ground surface and one insidethe vault. The results of this experiment reveal that installationof broadband sensors inside a buried vault will increase thequality of recording in short periods, especially due to protec-

tion of the sensor against wind. For long periods, thermalinstabilities around sensors and fluctuation of air pressuredue to local winds will increase background noise, especiallyin horizontal components. Both of these factors will createsignificant tilt noise on long-period horizontal seismographslocated at or near the surface. To study the relative influenceof thermal instabilities and pressure fluctuations on long-period noise, a complete thermal insulation was applied in sen-sor vault. Accurate measurements showed that temperature isconstant inside the vault with. However, there is no consider-able difference between noise level at long periods for signalsrecorded by the on-ground and vault sensors. Based on the re-sults of this experiment, the dominant source of long-periodnoise of horizontal component is fluctuation of air pressurecaused by local winds.

To provide a quantitative measure of signal quality in dif-ferent stations of the broadband network of Iran, the quality ofseismic signals were checked for signals recorded by the end of2012, and ranking of seismic stations in different frequencybands was performed accordingly. The results can be used todetermine the priority and method of rehabilitation for eachstation. It also provides a guideline for development of newstations.

ACKNOWLEDGMENTS

The authors appreciate the assistance of Holdermine company(Musa Hohjat and his colleagues) for providing design detailsof the sensor vaults. The information provided by Farzam Ya-mini Fard is also highly appreciated. The constructive com-ments of Sasan Iranpour had great influence on improvingthe manuscript. Special thanks are also due to the two anony-mous reviewers for their constructive criticism and their effortsto improve this work. This study was supported by theInternational Institute of Earthquake Engineering and Seis-mology (IIEES) Project Number 8-659.

10−1

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PS

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. (10

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4 /Hz)

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NLNMBSRNNASNYZKH

▴ Figure 13. Mode curves of BSRN, NASN, and YZKH stations (Zcomponent).

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▴ Figure 12. Ranking of the broadband seismic stations of Iran indifferent period ranges.


REFERENCES

Berberian, M. (1976). Contribution to the seismotectonics of Iran (partII), Geol. Surv. Iran Tech. Rept. 39.

Berberian, M., and R. S. Yeats (1999). Patterns of historical earthquakerupture in the Iranian plateau, Bull. Seismol. Soc. Am. 89, 120–139.

Byrne, D., L. Sykes, and D. Davis (1992). Great thrust earthquakes andaseismic slip along the plate boundary of Makran subduction zone,J. Geophys. Res. 79, 449–478.

Douglas, A. (2001). The UK broadband seismology network. Astron.Geophys. 42, 2.19–2.21.

Fukao, Y., K. Nishida, N. Suda, K. Nawa, and N. Kobayashi (2002). Atheory of the Earth’s background free oscillations, J. Geophys. Res.107, no. B9, 2206, doi: 10.1029/2001JB000153.

Havskov, J., and G. Alguacil (2006). Instrumentation in Earthquake Seis-mology, Modern Approaches in Geophysics, Springer, Reading, Mas-sachusetts, ISBN-10: 140-202-9683, ISBN-13: 978-140-202-9684.

Hessami, F., F. Jamali, and H. Tabassi (2003). Major active faults of Iran,International Institute of Earthquake Engineering and Seismology,Tehran, Iran.

Marshall, P. D., R. F. Burch, and A. Douglas (1972). How, and why torecord broadband seismic signals, Nature 239, no. 5368, 154–155.

McNamara, D. E., and R. Boaz (2005). Seismic noise analysis system us-ing power spectral density probability density functions: A stand-alone software package, U.S. Geol. Surv. Open-File Rept. 2005-1438,Reston, Virginia.

McNamara, D. E., and R. P. Buland (2004). Ambient noise levels incontinental United States, Bull. Seismol. Soc. Am. 94, no. 4,1517–1527.

McNamara, D. E., C. R. Hutt, L. S. Gee, H. M. Benz, and R. P. Buland(2009). A method to establish seismic noise baselines for automatedstation assessment, Seismol. Res. Lett. 80, no. 4, 628–637.

Mirzaei, N., G. Mengtan, and C. Yuntai (1998). Seismic source region-alization for seismic zoning of Iran: Major seismotectonic provinces,J. Earthq. Pred. Res. 79, 465–495.

Peterson, J. (1993). Observations and modeling of background seismicnoise, U.S. Geol. Surv. Open-File Rept. 93-322, Albuquerque,New Mexico.

Ringdal, F. (1975). On the estimation of seismic detection thresholds,Bull. Seismol. Soc. Am. 65, no. 6, 1631–1642.

Shahvar, M. P., M. Zare, and S. Castellaro (2013). A unified seismic cata-log for the Iranian plateau (1900–2011), Seismol. Res. Lett. 84,no. 2, 233–249.

Sorrells, G. G. (1971). A preliminary investigation into the relation-ship between long-period seismic noise and local fluctuations inthe atmospheric pressure field, Geophys. J. Roy. Astron. Soc. 26,71–82.

Sorrells, G. G., J. A. McDonald, Z. A. Der, and E. Herrin (1971). Earthmotion caused by local atmospheric pressure changes, Geophys. J.Roy. Astron. Soc. 26, 83–98.

Stutzmann, E., R. Genevieve, and L. Astiz (2000). GEOSCOPE stationnoise levels, Bull. Seismol. Soc. Am. 90, no. 3, 690–701.

Uhrhammer, B., and B. Karavas (1997). Guidelines for installingbroadband seismic instrumentation; available from http://seismo.berkeley.edu/bdsn/instrumentation/guidelines.html (last accessedMay 2014).

VonSeggern, D., and R. Blandford (1976). Seismic threshold determina-tion, Bull. Seismol. Soc. Am. 66, no. 3, 753–788.

Woessner, J., and S. Wiemer (2005). Assessing the quality of earthquakecatalogues: Estimating the magnitude of completeness and its un-certainty, Bull. Seismol. Soc. Am. 95, no. 2, 684–698.

Anooshiravan AnsariKambod Amini Hosseini

International Institute of Earthquake Engineering andSeismology (IIEES)

21 Arghavan St.North Dibajee Avenue

Tehran, [email protected]@iiees.ac.ir


http://dx.doi.org/10.1029/2001JB000153

http://seismo.berkeley.edu/bdsn/instrumentation/guidelines.html





broadband seismic network of iran and increasing quality of seismic recordings

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