Assessing seismic hazard and uncertainty in Büyükçekmece using ground motion simulations

Süleyman, Hakan; Çaktı, Eser

doi:10.1007/s10518-024-01953-6

Assessing seismic hazard and uncertainty in Büyükçekmece using ground motion simulations

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Published: 24 June 2024

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Abstract

This study presents a comprehensive seismic hazard assessment for Büyükçekmece, a district in Istanbul, Turkey, situated near the seismically active North Anatolian Fault (NAF). The study utilizes stochastic ground motion simulations with the validated EXSIM algorithm to understand the potential impact of medium to large-magnitude earthquakes (ranging from M_W 6.3 to 7.42) on this vulnerable community. The research employs a site-specific approach, considering unique amplification factors for each location. By conducting 50 scenario-based simulations, the study assesses the seismic hazard, highlighting the importance of comprehending variations in ground motion, even when they are small, for a more precise hazard assessment. Furthermore, this study addresses the critical issue of uncertainty, particularly concerning stress parameters and hypocenter locations. The researchers demonstrate that variability in these factors can introduce substantial uncertainty in ground motion predictions. The study provides insights into the range of potential ground motion outcomes through probabilistic assessments involving multiple scenarios and stress drop values. Notably, the results indicate that ground motion levels vary with earthquake magnitudes and underscore the significance of accounting for this variability. This research emphasizes the seismic vulnerability of Büyükçekmece and the importance of accurate ground motion simulations, offering valuable insights for earthquake preparedness and mitigation efforts in the region.

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1 Introduction

The report explores the potential impact of major earthquakes on the Büyükçekmece district in Istanbul, Turkey, by utilizing stochastic ground motion simulations. The region is situated near the North Anatolian Fault (NAF), which is one of the most seismically active regions globally, making it susceptible to earthquake damage. Due to these characteristics of the area, researchers worldwide have always been drawn to studying the seismicity of the region and assessing earthquake hazard through various methods (including but not limited to Pulido et al. 2004; Sørensen et al. 2007; Tanırcan 2012; Zengin and Çaktı 2012; Paolucci et al. 2018; Infantino et al. 2020; Stupazzini et al. 2020).

Unlike previous studies, this report concentrates on assessing earthquake hazard in a specific district of Istanbul, which is the final in a series of few studies. These studies are developed in collaboration with multiple academic institutions, Büyükçekmece Municipality and Istanbul Metropolitan Municipality. The findings from these studies are anticipated to inform future city-wide planning initiatives.

Initially, we carefully selected five earthquakes that occurred on NAF to validate the EXSIM simulation algorithm and we successfully validated the accuracy of this algorithm by simulating these earthquakes for the wider metropolitan region of Istanbul (Süleyman and Çaktı 2020, 2021, 2022) using data from the Istanbul Early Warning and Rapid Response System (IEWRRS).

To obtain a better insight into the potential impact of a major earthquake, we extensively analyzed the site response of this district in a recent study (Süleyman et al. 2023). We utilized the seismic ambient vibrations recorded in this region to calculate the depth-to-bedrock values, which were used to compute quarter-wavelength amplification factors in this study. These amplification factors were utilized in stochastic ground motion simulations, enabling us to prepare our estimations with expected improved accuracy.

In this study, we aimed to gain a better understanding of the impact of earthquakes with magnitudes ranging from 6.3 to 6.7 and 7.2 to 7.42 on the district. In the first stage, we conducted a total of 50 scenario events of these magnitudes, with a particular focus on the Büyükçekmece district. We thoroughly discussed these simulated scenario events, focusing on the impacts of different magnitude events and various period spectral accelerations on the district. In the study's second stage, we aimed to gain a deeper understanding of the uncertainty stemming from variations in stress parameter and hypocenter location. To achieve this, we significantly increased the number of scenarios examined compared to the first stage. As a result, our analysis shifted towards probabilistic investigations to better investigate the impact of these two key source parameters on the outcomes.

This study highlights the potential for earthquake hazards in this district in the event of medium to large earthquakes. The study emphasizes the importance of understanding the potential impact of earthquakes in Büyükçekmece and taking measures to minimize the impact.

2 Seismotectonics of the Marmara region

The NAF is a significant right-lateral strike-slip fault that stretches over approximately 1500 km and runs along the transform boundary between the Eurasian plate and the Aegean-Anatolian plate. The Marmara fault segments of NAF are located in a seismic gap, and their total length is approximately 100 km (Bohnhoff 2013; Ergintav et al. 2014). According to Ambraseys (2002), the recurrence interval for a major earthquake in this area is between 150 and 400 years, with the last event occurring in 1766. Drab et al. (2015) highlighted the importance of the Çınarcık segment, also known as Princes' Islands segment, which acts as a permanent seismic barrier. The authors identified four earthquake sequences in the Marmara Sea between C.E. 740 and 1999, with only one large earthquake propagating within a single event through the bend between the Çınarcık and the western portion of the İzmit segment.

Although major earthquakes occurred sequentially from east to west along the NAF in the twentieth century, culminating with the 1999 earthquakes, the seismic rupture has not yet broken the Marmara Sea segment. According to Ergintav et al. (2014), Diao et al. (Full size image

The results of this study provide valuable insights into the site-specific parameters of Büyükçekmece district. The estimated site amplification and depth-to-bedrock values can be utilized to improve the accuracy of seismic hazard assessments for the region. More detailed information on the methodology and results of this study can be found in Süleyman et al. (2023).

4.2 Validation of the ground motion simulation algorithm for Büyükçekmece

Ground motion simulations play an essential role in assessing seismic hazard and risk for a given region. In this study, we used the open-source algorithm EXSIM (Motazedian and Atkinson 2005; Boore 2009; EXSIM 2018), which has been validated in previous studies, to generate ground motion scenarios for Büyükçekmece, a region located in the western part of Istanbul, Turkey. The EXSIM algorithm accounts for finite-fault source models and stochastic simulation approaches, critical for accurately simulating realistic earthquake scenarios.

4.2.1 Source and path parameters used in the validation study

The validation exercise for the EXSIM algorithm, by utilizing five selected earthquakes was conducted in Süleyman and Çaktı (2021) and updated in later stages (Süleyman and Çaktı 2022). These five earthquakes considered in the validation process ranged in magnitude from M_W 4.0–5.8 and occurred in the Marmara Sea region (Fig. 2). The selection of these events aimed to capture the diversity of the seismic sources in the region–such as, the diversity in epicentral locations, magnitudes, recording locations, and observed ground motion levels were a few of the selection criteria (Süleyman and Çaktı 2020).

For the largest earthquake (M_W 5.8), a finite-fault source model developed by Karabulut et al. (2021) was used, while for the smaller events, point sources were utilized due to their relatively small rupture sizes. The validated set of parameters used in this study is similar to the ones used in Yenihayat et al. (2023) to validate the stochastic simulation algorithm for the region of Istanbul. Similarly, Infantino et al. 2020 used the same earthquake recordings to validate their 3D velocity model.

Table 1 summarizes the path, site, and source effect parameters used in the validation exercise. These parameters were globally and regionally developed, with particular attention paid to the Istanbul and Marmara region. The bottom lines of Table 1 relate to the source parameters of the five earthquakes included in the validation study.

Table 1 Summary of the parameters used in the validation exercise

Full size table

In order to accurately model the ground motion in the Büyükçekmece region, a site-specific approach was adopted, which involved the use of amplification factors generated for each of the 42 observation locations. In previous studies, a generic amplification model based on site classes had been used (Süleyman and Çaktı 2022). However, in this updated set of validated parameters, the Square-Root-Impedance (SRI) technique developed by Joyner et al. (1981) is employed for the amplification calculations. Further information on the application of this model can be found in the subsequent section.

Attenuation at high frequencies was measured based on the approach of Anderson and Hough (1984) in a previous study by Süleyman and Çaktı (2018). However, in the current study, to account for frequency-dependent anelastic attenuation, the model proposed by Horasan et al. (1998) was used. This model observes the spectral decay of S-waves at selected central frequencies over Fourier amplitude spectra. To describe geometrical spreading, the model of Akinci et al. (2013) was used. The duration of the simulated ground motions was scaled according to the model suggested by Boore and Thompson (2014). This validated model was then used to conduct scenario ground motion simulations for the metropolitan region of Istanbul in Süleyman and Çaktı (2022).

4.2.2 Ground motion simulation development using site-specific SRI method

The SRI method, commonly referred to as the Quarter-Wavelength Approximation, is a widely recognized technique used for estimating approximate linear site amplifications in simulations of ground motions and for comparing seismic velocity estimates at a single site (Boore and Joyner 1997; Boore 2003; Brown et al. 2002; Stephenson et al. 2005).

The SRI method offers distinct advantages over alternative approaches for calculating site amplifications. Notably, it is characterized by its efficiency, relying solely on a simple velocity model of the site. It assigns an amplification frequency to each depth and effectively smoothens multiple peaks. However, the SRI approach consistently provides lower estimates for the peaks observed in resonant systems and for gradient models lacking significant impedance differences, across a broad spectrum of frequencies. In the case of two gradient models commonly utilized in stochastic ground-motion simulations to derive crustal amplifications, this underestimation is limited to a maximum of approximately 30%. This margin is comparable to the uncertainties associated with several parameters utilized in simulations, and significantly smaller than the typical uncertainties in observed ground motions. Furthermore, Thompson et al. (2011) and Boore (2013) demonstrated that site responses computed using the SRI method exhibit closer alignment with observed site responses compared to results from the “full-resonant” method. Additionally, this study advocates for the adoption of the SRI method in constructing site response functions for average velocity profiles.

The method's core methodology entails estimating average seismic parameters, with a specific emphasis on the quarter-wavelength velocity (V_s^QWL), up to a depth denoted as z(f), equivalent to one-quarter of the wavelength associated with the frequency (f) of interest. Amplification factors for a given frequency are then computed by deriving the square root of the impedance ratio between the average depth and a reference point. To calculate the quarter-wavelength velocity corresponding to a particular frequency, a process of travel-time averaging across the input profile is employed by minimizing the expression as presented in Eq. 1 and 2.

$$\begin{array}{*{20}c} {\arg \min } \\ {z\left( f \right)} \\ \end{array} \left\|z\left( f \right) - \frac{{V_{s}^{QWL} \left( {z\left( f \right)} \right)}}{4f}\right\|$$

(1)

given that:

$$V_{s}^{QWL} \left( {z\left( f \right)} \right) = z\left( f \right)\left( {\mathop \int \limits_{0}^{z\left( f \right)} \frac{1}{{V_{s} \left( {z\left( f \right)} \right)}}dz\left( f \right)} \right)^{ - 1}$$

(2)

The depth-to-bedrock values and assigned shear-wave velocities were used in conjunction with the 1-D crustal shear-wave velocity model utilized by Karabulut et al. (2021) to generate unique amplification curves for each location. By adopting a site-specific approach and incorporating validated models for amplification, attenuation, and spreading, the simulations presented in this study are expected to offer a more precise representation of ground motion in the Büyükçekmece region.

For comparison, amplification factors computed for amplitudes exceeding 5 Hz at a site with a V_S,30 value approximating 260 m/s equate to 4.32, whereas for a site with a V_S,30 value approximating 340 m/s, the corresponding factor is calculated as 3.74. While it might be tempting to employ generic amplifications for each site class, this approach could introduce significant disparities in amplification factors, potentially resulting in overestimation or underestimation of stochastically simulated motions. Consequently, this study employs site-specific amplification factors to ensure a closer alignment between the simulated motions and the actual seismicity.

4.3 Scenario ground motion simulation development

As previously indicated, the authors of this study have emphasized seismic gaps along the North Anatolian Fault (NAF), specifically by develo** earthquake scenarios for the eastern portion of the central Marmara segment (Source #1) and the Princes' Islands segment (Source #2) of the NAF. Source #1 and Source #2 have the potential for ruptures spanning approximately 100 km and 35 km, respectively. It is noteworthy that ruptures in either of these sources may trigger ruptures in the other, given that these segments intersect.

A total of 50 simulations were conducted on the two seismic sources mentioned above–as separate rupture locations and jointly. Each of these scenarios represents a unique scenario with different combinations of magnitude, rupture, and hypocenter locations. “Appendix B” summarizes all the source parameters used in these simulations.

Simulations from scenario number 26 to 40 were conducted at Source #1 (Fig. 3), with magnitudes ranging from M_W 7.2 to 7.4. Simulations from scenario number 1 to 25 took place at Source #2, (Fig. 3) involving M_W 6.3 to M_W 6.7 events. The simulations from number 41 to 45 involved combinations of M_W 7.4 and M_W 6.4 events, and the final five simulations involved combinations of M_W 7.4 and M_W 6.7 events with—the larger event triggering the latter one, forming larger magnitude events of M_W 7.41 and M_W 7.42, all taking place at two source locations consecutively. In all these scenarios, the hypocenter location was randomly assigned.

At all the ruptures considered slip weights are randomly generated at each sub-source of each simulation. The simulations only involved rectangular rupture plane scenarios due to the limitations of the EXSIM tool, which does not allow for rupture models with irregular shapes. The dip angles for all events were set at 90 degrees, given the predominantly horizontal nature of the faulting in the NAF. Stress values were set at 100 or 130 bars, as previously investigated in Süleyman and Çaktı (2022). The hypocenter depths of the simulated earthquakes range from 5.3 to 17 km, despite their expected shallow depths.

The simulations in this study were conducted for the 0.05–5 s (0.2–20 Hz) range. The simulated mean horizontal S-wave motions for each observation location considered in the Süleyman et al. (2023) study are presented as a result.

4.4 Accounting for variability in hypocenter location and stress drop values

The hypocenter location and stress drop values are recognized as two of the most uncertain parameters in the context of modeling ground motions. However, these parameters can significantly influence the ground motion values observed at near-source locations. The quantification of this uncertainty holds paramount importance in comprehending the range of ground motion levels, thereby enhancing the meaningfulness of outcomes produced through ground motion simulations. Despite the incorporation of diverse scenarios involving varying magnitudes and multiple hypocenter locations within this study, the researchers also undertook a probabilistic assessment of the aforementioned variability in hypocenter and stress drop.

In order to characterize the variability of ground motion at each observation point, a wide range of stress drop values was defined for each of the considered magnitudes. Consequently, for each of the selected stress drop values a hundred randomized scenarios were generated, each involving randomized hypocenter locations. This approach facilitated the quantitative analysis of this variability, leading to a more precise representation of the ground motion models.

5 Results

For each simulation, we obtained peak ground acceleration (PGA), peak ground velocity (PGV), and spectral accelerations (SA) at various periods, in addition to the mean horizontal S-wave motions. We compared our estimations with two ground motion prediction equations (GMPEs) that involve adjustment factors for Turkey, BSSA14 (Boore et al. 2014) and ASK14 (Abrahamson et al. 2014). The PGA and PGV estimations were compared against the GMPE curves derived for these simulated values, as presented in Fig. 4.

Each graph in Fig. 4 includes two mean GMPE curves derived for two sets of magnitudes: one for scenarios with magnitudes M_W 7.2–7.42 and the other for scenarios with magnitudes M_W 6.3–6.7. The V_S,30 value used to generate these curves was selected as 300 m/s due to the close proximity of the observed V_S,30 values at all sites used for these simulations (“Appendix A”). The Joyner-Boore distances of the M_W 7.2–7.42 events range from 17 to 19 km, while for the magnitude 6.3–6.7 events, it ranges from 31 to 36 km. It is noteworthy to mention that the PGA and PGV values for the M_W 7.2–7.42 events are higher than the mean curve, whereas those for the M_W 6.3–6.7 events are lower than the mean curve generated for these events. Moreover, most of these values fall within ± 1 standard deviation of the means of the used GMPEs. The high decay of ground motion values for the lower magnitude range can be attributed to the high attenuation of seismic waves, as observed and discussed in the recent study by Malcioglu et al. (2022), particularly focusing on the M_W 5.8 Silivri earthquake. However, as mentioned earlier, the area is predominantly characterized by soft soil conditions, consisting of thick layers of unconsolidated sediments. These sediments act as traps, intensifying seismic waves and significantly amplifying ground shaking during earthquakes. The depth of the bedrock also plays a crucial role, with shallower bedrock resulting in greater amplification. Overall, the PGA levels for the M_W 7.2–7.42 and M_W 6.3–6.7 scenario events range between 313–490 cm/s² and 55–93 cm/s², respectively, while the PGV levels range between 29–50 cm/s and 4–8 cm/s. In comparison, Infantino et al. (2020) provided PGV estimations via PBSs for M_W 7.2 and M_W 7.4 at a V_S,30 of 650 m/s, which closely align with the PGV estimations in our study for equivalent distances. However, our region's V_S,30 stands around 300 m/s. Notably, within our study area, Infantino et al.'s (2020) PBS approach notably overestimates PGVs in contrast to those estimated by Cauzzi et al. (2015). Stupazzini et al. (2020) present comprehensive maps delineating 975 years of return period PGV values for their footprint and GAF estimations across much of Istanbul. Remarkably, their estimations for this region are in strong concordance with ours for the M_W 7.2–7.42 range. Zengin and Çaktı (2012) employ stochastic simulations for Istanbul, offering estimations for V_S,30 of 270 m/s for the M_W 7.4 case. Surprisingly, both their PGA and PGV estimations are lower than ours. Despite employing a rupture scenario akin to our M_W 7.4 case, their set of input parameters diverges substantially from ours. Notably, a key factor contributing to this variance is likely the disparity in stress drop values; they utilize 100 bars, whereas our study incorporates a stress drop of 130 bars for the M_W 7.2–7.4 range. This parameter holds significant sway over the ground motion values derived through the EXSIM algorithm.

Figure 5 discusses whether any geographical dependencies exist in the study area within PGA and within the SA value distributions on the map, considering the magnitude 7.4 simulation (scenario number 36 in “Appendix B”). Therefore, no significant trend is observed. This figure also depicts the inter-period acceleration change. It is evident from the figure that at 0.2 s SA values exceed 1.2, whereas SA values decrease substantially at 2 s.

Specifically, we computed SA values for 49 logarithmically spaced periods for 50 simulations for each location. To facilitate meaningful comparisons, the computed SA values were plotted using 3D bar charts. An illustration of the SA spectra (0.5–5 s) for all the realized simulations at location #17 (“Appendix B”) is depicted in Fig. 6. The results indicate a systematic variation in the SA spectra as the magnitudes of the simulations decrease. As expected, the highest SA values were observed for M_W 7.42 event simulations, while M_W 7.3 and M_W 7.2 scenario events also showed significantly high values. Our analysis revealed that the periods between the 0.06–0.9 s range are likely to exhibit the highest expected SA values.

The study conducted by Beauval et al. (2009) aims to develop a hybrid methodology for computing probabilistic seismic hazard, by employing an empirical Green’s function (EGF) simulation technique. The researchers analyze ground-motion variability at various stations, with a particular emphasis on understanding the sigma values. The researchers generated a large number of acceleration time histories based on the EGF method. By comparing these simulations with observed spectra and predictions from ground-motion models, the study highlights discrepancies and underscores the importance of sigma in hazard assessment. As the results of our study point out a significant uncertainty around ground motion values, we attempted to model this uncertainty by kee** the variability of stress parameter and the hypocenter location in the center of our attention. To deepen our analyses, we followed an approach similar to that of Beauval et al. (2009). We decided to increase the number of simulations drastically at this stage of the study. Such as, for the simulation scenario number 36 of M_W 7.4 in “Appendix B”, we defined a wide stress drop range from 100 to 160 bars, with a 5-bar increment. For each of these increasing stress values a hundred simulations were realized to parametrize the uncertainty, in total yielding 1300 simulations for this exact location and magnitude. In each of these simulations, the hypocenter location was randomly generated within the defined rupture plane. This process was repeated for all the other scenarios and observation locations.

Figure 7 shows the PGA and PGV occurrence frequency distribution amongst 1300 realized simulations and their corresponding probability density (PDF) overlaid on the frequency distribution histogram. The PGA and PGV frequency distributions clearly show normal distribution observed in most of the other locations and scenarios, as well as in the case demonstrated in Fig. 7. Therefore, the PDF is modeled to observe the probability of occurrence of ground motion parameters for a pre-defined moment magnitude and rupture location, while stress drop and hypocenter location are the variables. It is also important to mention that sigma levels cover relatively wide PGA and PGV ranges, even when a single magnitude and the same observation location is considered. The phenomenon of a wider range of ground motions is caused due to high uncertainty of the stress value and hypocenter location, especially when such relatively large ruptures are considered.

For this particular case shown in Fig. 7, the PDF shows a mean value of 422 cm/s² for PGA and 44 cm/s for PGV. Stupazzini et al. (2020), follow a similar approach to check the ground motion distributions through histograms and lognormal distributions. As a comparison, for the M_W 7.4 case, they develop 20 PBS scenarios. For the location of Hagia Sophia of Istanbul at 20 km distance from the NAF and V_S,30 of 650 m/s, they observe mean PGA and PGV values of 309 m/s² and 46 m/s, respectively through the PBS approach. As their mean estimation for PGA is lower than our estimation, the PGV estimation is nearly the same.

6 Conclusions

The NAF is an area with a high potential for seismic activity, and Büyükçekmece, a densely populated district in Istanbul, is particularly vulnerable to earthquake damage. This study aimed to use the EXSIM stochastic ground motion simulation approach to model potential earthquakes in the region and gain a better understanding of the impact that medium to large magnitude earthquakes could have on the district. The accuracy of the EXSIM algorithm was validated by simulating five past earthquakes in the region in a preceding study.

By using scenario ground motion simulations, we identified the potential earthquake hazard in an approximately 6 km² area in Büyükçekmece. The site-specific approach adopted in this study provided unique amplification curves for each location, which were used to carefully model the ground motion in Büyükçekmece. The use of finite-fault source models and site-specific parameters allowed for the precise simulation of realistic earthquake scenarios. Our investigations revealed that the site-response in this part of Büyükçekmece is relatively similar, which resulted in similar estimations of ground motion levels at all locations. However, it is worth understanding the variations in ground motions, even though they are small, for a more accurate hazard assessment.

In this study, we presented practical ways to observe (1) the effect of magnitudes mostly for the magnitude increments of 0.1 and 0.01 on ground motion levels along a wide range of periods (0.05–5 s); (2) the importance of modeling the uncertainty caused by the stress parameter and hypocenter location. Involving scenarios differing in magnitudes, stress parameters and hypocenters allowed us to observe that the ground motions may significantly vary when different scenarios are applied. Moreover, difficulties in predicting the hypocenter location and stress values cause a significant range of uncertainty that the researchers of this study suggest to be carefully considered in such studies.

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Funding

Open access funding provided by the Scientific and Technological Research Council of Türkiye (TÜBİTAK). This work has been supported by UKRI-GCRF in the framework of project “Tomorrow’s Cities”.

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Authors and Affiliations

Department of Earthquake Engineering, Kandilli Observatory and Earthquake Research Institute, Boğaziçi University, 34684, Istanbul, Çengelköy, Turkey
Hakan Süleyman & Eser Çaktı

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Hakan Süleyman
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Eser Çaktı
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Correspondence to Hakan Süleyman.

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Appendices

Appendix A

Coordinates and assigned V_S,30 values of the 56 observation locations at the study region

Location number	Latitude	Longitude	V_S,30 (m/s)
1	41.02362	28.50834	263
2	41.02155	28.50827	308
3	41.02155	28.53497	340
4	41.02178	28.53847	339
5	41.01900	28.50844	337
6	41.01940	28.51122	337
7	41.01928	28.51431	337
8	41.01968	28.52284	329
9	41.02009	28.52554	325
10	41.01947	28.52878	322
11	41.02034	28.53191	320
12	41.01988	28.53476	319
13	41.01987	28.53848	307
14	41.01969	28.54156	313
15	41.01954	28.54425	309
16	41.01994	28.54662	314
17	41.01742	28.50927	339
18	41.01701	28.51150	338
19	41.01725	28.51423	337
20	41.01731	28.51730	333
21	41.01729	28.52010	328
22	41.01750	28.52321	323
23	41.01747	28.52626	317
24	41.01740	28.52893	311
25	41.01760	28.53157	307
26	41.01745	28.53472	325
27	41.01779	28.53816	322
28	41.01758	28.54110	295
29	41.01737	28.54392	288
30	41.01751	28.54695	295
31	41.01459	28.50832	323
32	41.01482	28.51135	326
33	41.01495	28.51464	325
34	41.01525	28.51761	323
35	41.01510	28.52027	318
36	41.01502	28.52327	312
37	41.01520	28.52614	308
38	41.01477	28.52928	302
39	41.01534	28.53204	298
40	41.01547	28.53523	320
41	41.01527	28.53762	307
42	41.01576	28.54088	287
43	41.01593	28.54425	287
44	41.01242	28.50847	307
45	41.01254	28.51143	309
46	41.01271	28.51435	310
47	41.01250	28.51720	308
48	41.01279	28.52034	306
49	41.01258	28.52332	302
50	41.01271	28.52632	299
51	41.01287	28.52875	296
52	41.01281	28.53223	293
53	41.01039	28.50840	297
54	41.01021	28.51114	298
55	41.01046	28.51492	300
56	41.00996	28.51788	298

Appendix B

See Table 2.

Table 2 Summary of the source parameters of each realized simulation

Full size table

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Süleyman, H., Çaktı, E. Assessing seismic hazard and uncertainty in Büyükçekmece using ground motion simulations. Bull Earthquake Eng (2024). https://doi.org/10.1007/s10518-024-01953-6

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Received: 25 October 2023
Accepted: 07 June 2024
Published: 24 June 2024
DOI: https://doi.org/10.1007/s10518-024-01953-6

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Assessing seismic hazard and uncertainty in Büyükçekmece using ground motion simulations

Abstract

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Comparison of conventional and Monte Carlo simulation-based probabilistic seismic hazard analyses for Shiraz city, southern Iran

Site Dependent Seismic Hazard Assessment for Bucharest Based on Stochastic Simulations

A probabilistic seismic hazard analysis in SE Iran; case study: Kerman province

1 Introduction

2 Seismotectonics of the Marmara region

4.2 Validation of the ground motion simulation algorithm for Büyükçekmece

4.2.1 Source and path parameters used in the validation study

4.2.2 Ground motion simulation development using site-specific SRI method

4.3 Scenario ground motion simulation development

4.4 Accounting for variability in hypocenter location and stress drop values

5 Results

6 Conclusions

Data availability

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Appendix A

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Assessing seismic hazard and uncertainty in Büyükçekmece using ground motion simulations

Abstract

Similar content being viewed by others

Comparison of conventional and Monte Carlo simulation-based probabilistic seismic hazard analyses for Shiraz city, southern Iran

Site Dependent Seismic Hazard Assessment for Bucharest Based on Stochastic Simulations

A probabilistic seismic hazard analysis in SE Iran; case study: Kerman province

1 Introduction

2 Seismotectonics of the Marmara region

4.2 Validation of the ground motion simulation algorithm for Büyükçekmece

4.2.1 Source and path parameters used in the validation study

4.2.2 Ground motion simulation development using site-specific SRI method

4.3 Scenario ground motion simulation development

4.4 Accounting for variability in hypocenter location and stress drop values

5 Results

6 Conclusions

Data availability

Code availability

References

Funding

Author information

Authors and Affiliations

Corresponding author

Ethics declarations

Conflict of interest

Additional information

Publisher's Note

Appendices

Appendix A

Appendix B

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