Seismic Hazard Evaluation and Strain Dynamics in the Simav Fault Zone: A Comprehensive Analysis of Earthquake Recurrence and Energy Release Patterns

Abstract

This study aims to determine the earthquake hazard of the Simav Fault Zone (SFZ), one of the key tectonic features of Western Anatolia—a region that serves as a natural laboratory for geoscientists due to its complex tectonic structure and swarm-type seismic activity generated by multiple active graben systems. For this purpose, the a (6.33) and b (0.92) seismic parameters based on the Gutenberg–Richter magnitude–frequency relationship were first calculated using M ≥ 3 earthquakes that occurred between 1900 and 2024 along the SFZ. Moreover, the recurrence periods of events with magnitudes between M = 5 and M = 7.1 were determined (ranging 32 and 982 years), and the seismic hazard levels in the region were identified. The spatial density of the earthquakes and the regional distribution of the energy they released were analyzed, and the variations in seismic activity along the fault and energy flow in the region were investigated. For the evaluation of past earthquakes with the current strain field of the region, using geodetic velocity data, the strain rates of each segment of SFZ were calculated (reaching 90 ns/year) and findings related to stress accumulation processes were obtained. The findings, along with previous events, indicate that the region is susceptible to seismic hazards and that even moderate earthquakes pose a significant threat to both infrastructure and the population. This study, which seeks to enhance the understanding of seismic hazards and regional strain accumulation in the SFZ, is expected to serve as a valuable tool in seismic hazard assessments and local disaster management strategies, and to provide a critical reference for decision-makers in effective earthquake risk management.

1. Introduction

Earthquakes, which lead to the collapse of engineering structures, infrastructure systems, and homes, causing casualties and widespread destruction, are among the most significant natural hazard phenomena worldwide. They have profound socio-economic consequences and pose a serious threat to the sustainability of the human life cycle [1]. Throughout human history, earthquakes, being the most devastating natural disasters, have caused significant loss of life and economic challenges in many densely populated, seismically active regions worldwide over the past few years [2,3,4]. Today, although the timing, location, and magnitude of earthquakes cannot be precisely predicted, studies conducted across various disciplines have enabled the estimation of key seismic parameters. Through earthquake catalogues specific to the region of interest, it is possible to derive critical data such as recurrence periods, seismic intensity, fault maps, and ground motion characteristics from past seismic events [5]. Through the application of these data, seismic hazard analyses can be performed to predict the potential hazards, damages, and indirect socio-economic impacts of future earthquakes within the focus area. These analyses enable the development of strategies to mitigate such effects, thereby enhancing resilience and reducing vulnerability. The primary objective of seismic hazard analysis, which is used to predict future ground shaking caused by earthquakes in one or more regions, is to systematically integrate existing data from past seismic events with seismological, geological, and statistical information. This integration enables the determination of probable values for seismic ground motion parameters—such as, velocity, peak ground acceleration (pga), and dislocations—that the region of interest may experience in the future [6].

From past to present, two distinct approaches have been employed in the assessment and modeling of seismic hazard: Deterministic Seismic Hazard Analysis (DSHA) and Probabilistic Seismic Hazard Analysis (PSHA). The DSHA method, being a simple and rapid approach, is particularly used to identify the worst-case scenario in the hazard analysis of massive engineering structures. However, it considers only a single earthquake scenario at a specific location and magnitude, disregarding uncertainties related to the magnitude, location, and timing of the event [7,8]. The probabilistic approach, initially developed in the late 1960s by Cornell [9], is preferred over the deterministic approach today due to its ability to quantitatively calculate for the uncertainties in seismic hazard analysis [10]. The aim of Probabilistic Seismic Hazard Analysis (PSHA) is to calculate the exceedance probabilities of different ground motion levels at specific locations or regions over a given time period, which may lead to damage and loss of life [11,12]. PSHA provides a detailed and comprehensive perspective on seismic hazard by not only accounting for uncertainties in the magnitude, location, and recurrence frequency of earthquakes, but also by defining and logically integrating uncertainties related to the changes in ground motion properties in relation to earthquake magnitude and epicentral location [10,13,14]. Conventionally, seismic hazard analyses rely on earthquake catalogs and empirical equations to evaluate seismic hazard, utilizing data from past earthquakes. As stated by Reid [15], during the pre-seismic period, potential energy accumulates in seismic sources, leading to an increase in stress, a phenomenon referred to as the elastic rebound theory [16]. The rising stress leads to different deformations in the Earth’s crust, and these alterations can be detected through geodetic methods. Advancements in technology, especially in space geodesy during the latter part of the 20th century, have led to the widespread adoption of GNSS for detecting tectonic plate movements using geodetic techniques. The geodetic perspective, a powerful tool for better understanding earthquake potential in seismic hazard analyses, is frequently used to identify high seismic hazard regions by aiding in the determination of stress levels on faults within the strain fields of seismic sources [17,18,19,20,21,22,23,24,25,26]. Seismic hazard analysis is a critical process for evaluating the safety of structures in earthquake-prone areas and mitigating potential damage through the development of seismic-resistant structures. The methods and data used in seismic hazard analysis have been applied by various researchers around the world, depending on the seismic sources and scale of the study in the region, in Finland [27], Mexico [28], the Arabian Peninsula [29], India [30,31], and Europe [32].

The Anatolian Plate, situated between the Eurasian Plate to the north and the African and Arabian Plates—which are moving approximately toward it from the south—is one of the most active tectonic deformation zones in the Alp-Himalayan belt in terms of seismic activity due to its unique geological setting [33]. As a result of the motion induced by the southern plates, the Anatolian Plate has experienced extensive faulting, and these faults have generated numerous earthquakes of magnitude greater than M > 7 that have historically caused significant casualties and property damage (1939—Erzincan Mw: 7.9; 1976—Van Mw: 7.5; 1999—Gölcük Mw: 7.8; 2011—Van Mw: 7.2; 2023—Kahramanmaraş Mw: 7.6) [34]. Following the collision between the Eurasian and Arabian Plates and the ongoing convergence, four distinct neotectonic regions have developed within the Anatolian Plate: the Eastern Anatolian compressional zone, the Northern Anatolian region, the Central Anatolian plain, and the Western Anatolian extensional zone [35,36,37] (Figure 1). The Western Anatolian Extensional System, one of these neotectonic regions, is among the primary seismic source areas within the Anatolian Plate, following the North Anatolian Fault Zone (NAFZ) and the East Anatolian Fault Zone (EAFZ). At an annual deformation rate of 25–30 mm, the Western Anatolian horst–graben system—comprising the Edremit, Bakırçay, Kütahya, Simav, Gediz, Küçük Menderes, Büyük Menderes, and Gökova grabens—is among the fastest deforming continental regions globally; within this system, the Simav Fault Zone (SFZ), a crucial tectonic structure located on the northeastern margin of the Aegean extensional province, is predominantly characterized by normal faulting [38,39,40,41].

The Simav Fault Zone (SFZ), approximately 205 km in length, is one of the most significant source zones in Western Anatolia due to its length and segmental structure. Also, it has the potential to generate destructive earthquakes with magnitudes ranging from 6.7 to 7.1 Mw [42,43]. The energy released by earthquakes of this magnitude (Mw > 6), which could generate surface rupture, is 11.2 to 44.7 times greater [44]. This increased risk, combined with the presence of approximately 4 million people within a 100 km radius, raises the potential for significant loss of life and property. Furthermore, due to its role in the country’s socio-economic environment, conducting a seismic hazard analysis for this region is a crucial need.

The SFZ and its surrounding region exhibit significant seismic activity, which profoundly affects the area’s tectonics and geodynamics, leading to broad environmental and social consequences. The ongoing seismic activity and earthquake hazard in the Simav Fault Zone (SFZ) and its surrounding region pose a threat to the local population as well as the relatively vulnerable building stock and infrastructure. Therefore, in this study, in addition to all the critical issues discussed in detail above, a comprehensive seismic hazard analysis was conducted for the SFZ and its vicinity. This analysis was motivated by the continuation of destructive earthquakes in the instrumental period, following those that occurred during the historical period, as well as the fault zone’s potential to generate large-magnitude earthquakes in the future. For this purpose, the most extensive earthquake catalog for the SFZ and its vicinity were first obtained from the KOERI database; to ensure homogeneity in the dataset, all earthquakes with M ≥ 3 listed in the catalog were converted to moment magnitude (Mw). Subsequently, to derive a detailed assessment of the region’s seismic hazard, the a and b parameters of the Gutenberg–Richter law were estimated and earthquake recurrence periods were calculated. Finally, the strain rates of SFZ segments were derived from geodetic data, providing insights into the current stress state of each segment. In this study, the instrumental earthquake records of the SFZ were analyzed in terms of temporal, spatial, and energy patterns, and a comprehensive seismic hazard analysis was conducted for the SFZ in light of the current geodetic strain rates. The results, when analyzed in conjunction with historical earthquake data, offer a comprehensive understanding of the region’s dynamics at the spatial scale. They quantitatively reveal fault behavior while simultaneously incorporating future risks into projections. This study offers valuable quantitative and qualitative data-driven guidance for earthquake risk management and disaster policies. In this respect, this study provides valuable data-driven guidance, offering both scientific and practical insights for earthquake risk management and disaster policies.

2. Tectonic Settings

Under the influence of the Hellenic-Cyprus subduction zone, Western Anatolia has undergone extensional deformation, resulting in the formation of horst–graben structures bounded by parallel normal or oblique faults. These structures, including the Edremit, Bakırçay, Simav, Gediz, Küçük Menderes, Büyük Menderes, and Gökova Gulf grabens, define the Western Anatolian Extensional Province (WAEP) [45,46]. In addition to its morphotectonic characteristics and ongoing macroseismic activity, the oblique, dip-slip normal fault segments within the fault system promote the development of numerous horst and graben structures parallel to the overall trend of the system. The ASFS has been the focus of numerous studies by researchers over time due to its unique natural geomorphological characteristics [47,48,49,50,51,52,53,54,55,56,57,58,59,60,61]. The SFZ forms the northwestern extension of the Akşehir-Simav Fault System (ASFS), one of the major seismogenic zones within the WAEP, extending approximately 500 km from Konya in the east to Balıkesir in the west [62].

As a vital component of the extensional tectonic regime affecting Western Anatolia, the Simav Fault Zone (SFZ) is an active fault system extending approximately 205 km in a NW–SE direction between Sındırgı (Balıkesir) and Afyon. To the west, it is bounded by the NE-trending Gelenbe Fault Zone (GFZ) [40,63,64,65]. The SFZ consists of seven segments, named from west to east as follows: (i) Sındırgı Segment (35 km long, trend: 267–306°), (ii) Çaysimav Segment (54 km long, trend: 277–308°), (iii) Şaphane Segment (23 km long, trend: 286–312°), (iv) Abide Segment (33 km long, trend: 287–308°), (v) Banaz Segment (24 km long, trend: 3–359°), (vi) Elvanpaşa Segment (27 km long, trend: 270–298°), and (vii) Sinanpaşa Segment (18 km long, trend: 303–323°) [43,48,56,62,66] (

Table 1. Fault parameters and potential earthquake magnitudes for SFZ and GFZ [39,48,67,68].

Fault				Trend (RHR)		Dip Angle (C°)		Depth (km)		Magnitude
	Segment	Type	Length (km)	Min	Max	Min	Max	Focal d.	Literature	Estim. Mw
Simav Fault Zone	Sındırgı	RL	35	267	306	87	90	18	16	6.89
	Çaysimav	RL	54	277	308					7.10
	Şaphane	RL	23	286	312					6.69
	Abide	RL	33	287	308					6.86
	Banaz	RL	24	3	359					6.71
	Elvanpaşa	RL	27	270	298					6.76
	Sinanpaşa	RL	18	303	323					6.57
Gelenbe FZ	East	RL	35	3	50					6.89
	West	RL	36	6	40					6.90

).

Considering its length and multi-segmented structure, the SFZ is one of the key source zones in Western Anatolia. It has been thoroughly investigated by many researchers, who have proposed different interpretations regarding its fault characteristics [57,64,66,69,70,71,72,73,74]. As stated by Koçyiğit and Deveci [54], Bekler et al. [65], Kartal and Kadirioğlu [57], and Gündoğdu et al. [74], the SFZ exhibits an oblique-slip character, with normal faulting being the dominant mechanism. Additionally, Gündoğdu et al. [58] and Gündoğdu et al. [66] highlight that the region was initially dominated by compressional tectonics during the Early Miocene, followed by extensional tectonics in the Quaternary. They also indicate that the Simav Fault initially functioned as a strike-slip normal fault and later evolved into a dip-slip normal fault, remaining active to this day. Yolsal-Çevikbilen et al. [75] further state that the earthquake source parameters exhibit a normal faulting mechanism with a strike-slip component. Opposing views to these suggestions emphasized that the SFZ should be considered as an important seismogenic zone with a strike-slip mechanism within the current tectonics of Western Anatolia and stated that the SFZ is a strike-slip active fault system [64]. Unlike these two views, Duman et al. [72] pointed out that different faulting mechanisms were observed in different segments of the fault as a result of paleoseismological studies. In addition to these inferences, all segments of the SFZ were defined as right-lateral in the MTA Active Fault Database [43]. In geodetic studies conducted in the region using GNSS data, Aktuğ et al. [39] emphasize that the Simav Fault Zone (SFZ) exhibits a strike-slip structure with a normal faulting component. However, according to the most recent study in the region by Solak et al. [76], in contrast to previous findings, the fault is characterized by predominantly normal faulting behavior.

During the instrumental period, approximately 450 earthquakes with M ≥ 4 and 79 earthquakes with M ≥ 5 have occurred in SFZ and its surrounding regions (Figure 2). In addition to these seismic events, geological studies conducted in the area, combined with the instrumental records, indicate that multiple faults within the zone have been active at different times. The seismic activity of the SFZ is evidenced by numerous historical and instrumental period earthquakes, which have caused severe damage and human casualties in the surrounding regions (94, 1766, 1873, 1876 ve 1896 Historical, 1928 (Emet M: 6.2), 1944 (Şaphane M: 6.2), 1946 (Abide M: 6), 1969 (Demirci M: 5.9), 1970 (Gediz M: 7.2), and 1979 (Çavdarhisar M: 5.9) [34,54,70,73] (

Table 2. Historical and instrumental period earthquakes that occurred on and around the SFZ [34,77,78,79].

Historical Period (AC)				Instrumental Period (1900–)				Focal Mech.
Date	Lat.	Lon.	Mag.	Date	Lat.	Lon.	Mag.
94	38.75	30.5	VIII	1905	38.81	28.52	6.1	-
1595	38.99	29.39	VII	1924	39.51	28.4	5.5	-
1611	38.74	28.68	V	1942	39.27	28.19	5.5	-
1728	39.09	28.97	V	1942	39.1	27.8	6.1	-
1860	39.3	29.05	VIII	1944	38.79	29.31	5.9	-
1862	38.8	30.5	VIII	1969	39.14	28.48	7
1873	38.76	30.55	VI	1969	39.25	28.44	6
1887	38.73	29.75	VIII	1970	39.21	29.51	7.2
1896	39.3	29.2	VII	1970	39.03	29.76	5.8
1897	38.93	28.2	VI	1971	39.05	29.71	6
1899	39.4	28.13	VII	2011	39.13	29.08	5.9

)). Following the 1970 Gediz earthquake (Mw: 7.2), which is regarded as one of the most devastating earthquakes in the history of Turkiye and produced a total surface rupture of 45 km, the most recent major earthquake in the vicinity of the SFZ occurred in Simav in 2011 (Mw: 5.8). This event, characterized by surface ruptures at various locations and a shallow focal depth, significantly amplified the extent of damage, particularly in rural areas due to deficient construction standards. Approximately one month after the main shock, a second earthquake with a local magnitude of Ml = 5.0 occurred in the same region. This was followed by nearly 7000 aftershocks and a third earthquake with a local magnitude of Ml = 5.4 on 3 May 2012, which was strongly felt in the surrounding provinces. Since then, the SFZ and surrounding areas have not experienced any destructive earthquakes [34,57] (Figure 3).

According to the Earthquake Hazard Map prepared in 2019 by the Disaster and Emergency Management Presidency (AFAD) based on the Peak Ground Acceleration (PGA) methodology, Turkiye is divided into five seismic zones based on hazard levels. The region where the SFZ is located is represented by values of 0.47–0.54 g, classifying it as one of the highest-risk zones [80]. Furthermore, in the study conducted by Karasözen et al. [81] after the 1970 Gediz earthquake, they pointed out the existence of a significant seismic gap in the middle section of the SFZ concerning large instrumental period earthquakes, highlighting that this situation presents a potential hazard for the SFZ and its surrounding areas. In addition to that, in a study conducted by Durmuş [82], Coulomb stress change analyses revealed that the energy accumulation caused by the 1970 Gediz earthquake (Mw: 7.2) on the SFZ was not fully released by the 2011 Simav earthquake (Mw: 5.8). The study further highlighted that a significant portion of the SFZ, particularly the Şaphane Segment (>1 bar) located in the eastern part of the fault zone, is still subjected to significant stress accumulation. Additionally, in the models proposed by Aktuğ et al. [39] and Solak et al. [76], the eastern part of the SFZ, which represents a block boundary and thus experiences significant deformation, has also experienced destructive earthquakes. Historical and instrumental period earthquake records indicate the occurrence of numerous earthquakes within the ASFS that have generated surface ruptures. The 1921 Doğanhisar-Ilgın (M: 5.4), 1946 Ilgın-Argıthanlı (M: 5.5), 2000 Sultandağı (M: 6), and 2002 Çay earthquakes (M: 6.5 and 6.2) that occurred within the ASFS are considered part of a northwestward earthquake migration along the fault system [50]. The possibility of this earthquake migration continuing westward is of significant relevance to the SFZ.

3. Methodology and Implementation

3.1. Creating Dataset

There are three different earthquake catalogs that document the seismic events occurring in the study region: The Kandilli Observatory and Earthquake Research Institute (KOERI), the U.S. Geological Survey (USGS), and the Disaster and Emergency Management Authority (AFAD). These catalogs contain information such as magnitudes, epicenter coordinates, depths, and locations of the earthquakes. While the data in the AFAD and USGS catalogs are scarce, the most comprehensive data for the SFZ are available in the KOERI earthquake catalog. Therefore, the earthquake data from the KOERI catalog were utilized for the analyses conducted within the scope of this study. Since earthquake catalogs primarily contain instrumental period data regarding the seismic activity of faults, the number of damaging earthquakes recorded in these catalogs is quite limited. This situation further highlights the importance of statistical and geodetic studies for seismic hazard analysis. To reduce noise in the catalog containing events recorded in the study region, a Goodness-of-Fit Test [83] was performed, yielding a completeness magnitude (Mc) threshold of 3. Based on this analysis, earthquakes with Mw < 3 were excluded from the catalog. Furthermore, aftershocks following major earthquakes were also removed from the dataset. For this purpose, earthquakes located within a 25 km radius of the mainshock, occurring up to 6 months after Mw: 5 earthquakes, and taking place within 1 year after Mw: 6 earthquakes were classified as aftershocks. The histogram of the final dataset of more than 4500 earthquakes obtained after this filtering process is presented in Figure 4.

Different types of earthquake magnitudes (e.g., Md, Ml, Mw) can lead to inconsistencies in seismological studies. Therefore, for seismic hazard analyses, earthquake data must be converted to a common magnitude scale to generate a homogeneous catalog. For magnitude conversion, various quantitative relationships have been developed by researchers and are widely accepted in the literature [84,85,86]. However, since these relationships may reflect local characteristics, conversion coefficients specific to the study area were determined to enhance the reliability of the analysis. The moment magnitude (Mw) was chosen as the common magnitude scale, and Orthogonal Regression was employed to compute the conversion coefficients. The values obtained from the regression analysis are presented in

Table 3. The coefficients obtained for magnitude scaling along with standard deviations, correlation percentages, and data counts.

Mag. Type	Const		Magnitude		Relationship (%)	Data Count
	Coef	Std Err.	Coef	Std Err.
Md	0.2061	±0.069	0.9980	±0.015	98	88
Ml	−0.1554	±0.047	1.0483	±0.012	95	411
Ms	1.3900	±0.063	0.7521	±0.013	97	92
Mb	−0.3018	±0.080	1.1007	±0.017	98	93

.

3.2. Gutenberg–Richter Law

3.2.1. Seismic Hazard Parameters

In seismology, the Gutenberg–Richter law, the most well-known empirical relationship used for evaluating earthquake magnitudes and seismic hazard, is a method based on establishing a linear magnitude–frequency relationship between the number of past earthquakes in a region and their magnitudes to estimate the potential magnitudes of future events [87,88]. One of the key relationships used to reflect the seismic activity of a relevant region, the G-R law method, defines the relationship between earthquake magnitudes and their frequencies of occurrence through the equation provided in Equation (1):

log N(M) = a − b.M

(1)

Here, N(M) represents the number of earthquake events in the study area during a specific time period with magnitudes equal to or greater than M, while the values of a and b refer to the regression coefficients assumed to be constant for the region. While the a parameter is a value that depends on the seismic activity level of the study area, which may vary significantly from different regions, the b parameter is accepted as a parameter representing the tectonic features of the region [89,90,91,92]. The a parameter, which represents the annual average seismic activity, can vary depending on the time period under study, the area size, and the earthquake frequency. The b parameter, which is inversely proportional to the stress in the crust and is related to the physics of earthquake occurrence, is crucial for earthquake occurrence probability evaluation. It is also associated with or reflects the stress conditions in the region [93,94]. While the a-value represents the overall earthquake rate, the b-value indicates the ratio between small and large earthquakes. A higher b-value suggests that smaller magnitude earthquakes occur more frequently than larger ones, whereas a lower b-value indicates that larger magnitude earthquakes are more common, reflecting a region with higher stress [8,95,96,97].

In the early studies conducted on seismic hazard analysis, it was assumed that the b-value was the same across all regions. However, subsequent studies have shown that the b parameter can vary between regions, as demonstrated in several studies, examples of which are provided below [98]. In a seismically active region, the b parameter is generally assumed to be very close to 1, but changes in this value can be observed depending on the estimation method, the catalogue used, and the magnitude range of the selected earthquakes, and the slightest difference in the b parameter notably affects the results [99]. Gutenberg and Richter [100] presented b = 0.90 ± 0.02 for shallow earthquakes in the M = 6 to 6.5 range and b = 1.2 ± 0.2 for intermediate and deep earthquakes. They also suggested that the b parameter varies between 0.45 and 1.5 for other regions. Miyamura [101] proposed that the b-value ranges between 0.4 and 1.8 for different tectonic regions, suggesting that it is related to the geological age of the tectonic region. Mogi [102], on the other hand, stated that the b-value varies between 1.0 and 1.6. Tsapanos [103] stated that in a study conducted across 11 different seismic regions worldwide, including the Americas, Alaska, New Zealand, and Japan, the b-values ranged between 0.75 and 0.85. Additionally, various suggestions containing different values based on the a and b parameters have been made for different continents, regions, time intervals, and specific seismic sources [104,105,106,107,108,109,110].

Traditionally, parameters of the G-R calculated using the maximum likelihood (ML) estimation method based on past earthquakes with a certain sample size. Unlike the maximum likelihood method, which requires large datasets for accurate parameter estimation, hazard parameters can also be estimated using linear or nonlinear least squares regression (LSR). Generally, these two methods are the most commonly used for parameter estimation [111,112]. In LSR, which is essentially a curve fitting technique, the b-value is typically estimated by applying linear regression to the logarithm of the histogram. This method performs effectively in various situations, such as assessing the likelihood of large-magnitude earthquakes [113,114]. Therefore, in this study, the estimation of a and b parameters according to the G-R law was carried out using the nonlinear least squares method.

Gutenberg–Richter frequency–magnitude relation is applied in the sources on and around SFZ, which were identified from recent seismotectonic understanding of the region. In this study, earthquakes without moment magnitudes were converted into moment magnitudes using the coefficients obtained from orthogonal regression, and the a and b parameters were estimated using a catalog from over 4500 earthquakes with M ≥ 3 (Figure 5). The obtained results for the a- and b-values are 6.33 and 0.92, respectively. These results indicate high seismic activity in the region based on the a-value, while the b-value suggests that moderate to large earthquakes occur regularly.

3.2.2. Earthquake Recurrence Periods

One of the most essential parameters for seismic hazard analysis is the earthquake recurrence period of active faults. The earthquake recurrence period refers to the frequency at which earthquakes occur on a fault or fault zone. These periods are particularly necessary for seismic risk analysis studies to be conducted in the areas affected by faults that have reached their recurrence period. The earthquake recurrence period can be determined through paleoseismological studies, fault parameters, and statistical methods. One of the methods used to calculate this period is the Gutenberg–Richter law. By using the a- and b-values estimated with the relation provided in Equation (1), the periods can be calculated using the relation in Equation (2). Here, T represents the recurrence period and N(M) refers to the annual average number of earthquakes with magnitude M or greater in this equation.

$$T={\displaystyle \frac{1}{N\left(M\right)}}$$

(2)

As mentioned above, after calculating the a- and b-values using the Gutenberg–Richter law, the recurrence periods of earthquakes between M = 5 and M = 7.1 with intervals of 0.1 were computed for the study area using Equation (2) (Figure 6). There are several reasons for calculating the recurrence periods of earthquakes with an incremental 0.1 magnitude. Although it is stated in the literature that M > 6 earthquakes are generally capable of generating surface ruptures [63], the destructiveness of an earthquake is not entirely limited to its magnitude. The depth of the earthquake, underlying soil properties, proximity to populated areas, and the durability of structures (such as buildings, bridges, etc.) in the region also play a significant role in determining the destructive impact. The fact that the study area covers a large region and contains old settlements (such as buildings, houses, barns, schools, etc.) also increases the significance of the analysis conducted in this study [115]. There are also notable differences in the potential energy released by the earthquakes with magnitudes determined at incremental 0.1 magnitude steps. The results indicate that the recurrence periods of earthquakes with magnitudes between M = 5 and M = 7.1 in the region range from 32 years to 982 years.

3.3. Spatiotemporal Distribution of Earthquake Energy

Identifying areas where earthquakes are concentrated is important for seismic hazard analysis and subsequent risk management in a region. Determining regions with frequent earthquake occurrences allows for the examination of active faults/zones and their associated seismic hazards, and through comprehensive interpretation of the results, potential epicenters and impacted areas of future earthquakes can be forecasted. For this reason, there are studies in the literature where spatial density analyses have been conducted using earthquake catalogs [116,117].

Through the obtained dataset, a spatial density analysis was conducted for the SFZ and its surrounding area (Figure 7). Kernel Density Estimation (KDE) has been used for the density analysis. KDE is a statistical method used to estimate the probability density function for a dataset. This method defines a kernel function (Gaussian) around each data point and then sums the effects of these kernels to smoothly represent the density of the data. The results of the spatial density analysis conducted in this study indicate intense seismic activity to the northwest of the Gelenbe Fault Zone (GFZ) and approximately to the north of the Simav segment.

The spatial density analysis highlights the areas where events are concentrated in terms of frequency. These densities are obtained by applying a kernel with a specific bandwidth around each point, calculating the increase in density in the region where the point is located. The bandwidth controls the degree of spread of the kernels, with a smaller bandwidth creating a more detailed density pattern, while a larger bandwidth results in a more general density pattern. The bandwidth factor was determined according to Silverman’s Rule of Thumb, as proposed by Silverman [118], and was obtained as 0.64643 in this study. Although spatial density analyses provide valuable insights into areas with concentrated events, one disadvantage of spatial density analysis is the assumption that all events used for the analysis are considered equally significant. In other words, the impact of two earthquakes, one with a magnitude of M = 6 and the other with a magnitude of M = 3, is considered equal in the spatial density analysis. However, the magnitudes of actual or potential earthquakes are critically important for seismic hazard analyses as they play a distinctive role in assessing the risk. The energy released during earthquakes, which is closely linked to their destructive potential, increases logarithmically.

$$E={10}^{1.5 x M+4.8}$$

(3)

For the reasons mentioned above, it is necessary to weight the earthquakes according to their magnitudes in seismic hazard analysis spatial density maps. The most appropriate method for weighting the occurred earthquakes is to use the energy released as a result of the earthquakes. Therefore, the earthquakes in the dataset have been converted into energy using the formula in Equation (3). In this equation, E represents the energy released by the earthquake (Joule) and M (Mw) denotes the magnitude of the earthquake (Figure 8). The results show that the energy released by the earthquakes that occurred and were recorded during the instrumental period was mostly concentrated at the intersection of the Sındırgı and Simav segments. Additionally, high energy was also released to the north of the Abide segment.

Figure 8. Spatial energy density results of earthquakes in the study area (the black dashed line represents the main zone examined in this study, the SFZ, while the red lines indicate other active faults in the region). Examining the temporal density of earthquakes for seismic hazard analysis provides valuable understanding into determining the frequency of seismic activity over time. The way earthquakes concentrate over time, changes in their magnitudes, and particularly variations in the recurrence intervals of large earthquakes offer significant insights into the accumulated energy in the region. Similar to spatial density analysis, temporal density analysis that focuses solely on the number of earthquakes provides information about the timing of increases and decreases in seismic activity but does not provide sufficient insight into the destructiveness of earthquakes. However, the temporal analysis of the cumulative energy released by these earthquakes is more closely related to their destructiveness. With this goal in mind, the temporal densities of the earthquakes in the dataset have been analyzed both in terms of the number of events and the energy released (Figure 9). The results show that during the instrumental period, the energy density was primarily around the GFZ located to the west of SFZ, but after 1960, it was concentrated around the EF located to the north of the Simav segment of SFZ. The findings indicate that in the study area, particularly before 1970, earthquakes releasing high energy predominantly occurred at the intersection of the GFZ and SFZ. However, after this period, seismic activity shifted towards the central segments of the SFZ and its intersection with the EF located to the north, possibly driven by the 1970 Gediz earthquake (Mw: 7.2). Between the 1980s and the end of 2025, the significant energy release from the Gediz earthquake, combined with the occurrence of the 2011 Mw: 5.8 and 2012 Ml = 5.4 Simav earthquakes in the approximately same region, has resulted in an intensified release of seismic energy in the central segment of the SFZ.

Figure 8. Spatial energy density results of earthquakes in the study area (the black dashed line represents the main zone examined in this study, the SFZ, while the red lines indicate other active faults in the region). Examining the temporal density of earthquakes for seismic hazard analysis provides valuable understanding into determining the frequency of seismic activity over time. The way earthquakes concentrate over time, changes in their magnitudes, and particularly variations in the recurrence intervals of large earthquakes offer significant insights into the accumulated energy in the region. Similar to spatial density analysis, temporal density analysis that focuses solely on the number of earthquakes provides information about the timing of increases and decreases in seismic activity but does not provide sufficient insight into the destructiveness of earthquakes. However, the temporal analysis of the cumulative energy released by these earthquakes is more closely related to their destructiveness. With this goal in mind, the temporal densities of the earthquakes in the dataset have been analyzed both in terms of the number of events and the energy released (Figure 9). The results show that during the instrumental period, the energy density was primarily around the GFZ located to the west of SFZ, but after 1960, it was concentrated around the EF located to the north of the Simav segment of SFZ. The findings indicate that in the study area, particularly before 1970, earthquakes releasing high energy predominantly occurred at the intersection of the GFZ and SFZ. However, after this period, seismic activity shifted towards the central segments of the SFZ and its intersection with the EF located to the north, possibly driven by the 1970 Gediz earthquake (Mw: 7.2). Between the 1980s and the end of 2025, the significant energy release from the Gediz earthquake, combined with the occurrence of the 2011 Mw: 5.8 and 2012 Ml = 5.4 Simav earthquakes in the approximately same region, has resulted in an intensified release of seismic energy in the central segment of the SFZ.

Figure 9. Temporal energy density results of earthquakes in the study area from 1900 to 2030, shown in 10-year intervals (red lines represent active faults in the study area).

Figure 9. Temporal energy density results of earthquakes in the study area from 1900 to 2030, shown in 10-year intervals (red lines represent active faults in the study area).

3.4. Geodetic Strain Rate Analysis of the SFZ

Seismic hazard analyses conducted using earthquake catalogs provide predictions about future hazards based on the past activities of faults. Nevertheless, these data have limited capacity to fully reflect the current seismic hazard potential of the faults. Therefore, the use of high-precision GNSS velocity data is crucial for understanding the current deformation state of faults. The reason for this is that strain accumulation on faults during the pre-seismic or inter-seismic period can be calculated using GNSS velocities. These strain rates directly reflect the energy accumulation processes on faults and their dynamic characteristics. Therefore, for a more comprehensive seismic hazard analysis that includes the present accumulation state of faults, it is essential to consider the faults’ current strain build-up. This geodetic approach offers the opportunity to make valuable and more accurate assessments of future seismic hazards, in addition to analyses that are mostly limited to historical catalog data.

In the study area, instrumental earthquake records highlight the high seismic activity, suggesting the possibility of stress accumulation. Furthermore, considering past earthquakes in the region, it is evident that the fault has the potential to cause significant damage to nearby settlements. Therefore, if the faults in the region have the potential to generate a destructive earthquake in the coming years, it is crucial to assess this risk not only theoretically but also based on geodetic data obtained from field observations. Such an approach is of great importance in mitigating potential losses in all terms. For this purpose, the GNSS velocity field consisting of 836 sites on the Anatolian Plate, developed by Kurt et al. [119], was used to calculate the accumulated strain rates on the segments forming the SFZ (Figure 10). The average RMS values for the GNSS sites used in this study are 0.18 mm/yr and 0.20 mm/yr for V_east and V_north, respectively.

The velocity field used contains the most comprehensive velocity data currently available for the Anatolian Plate. Strain rates on the segments were calculated at approximately ~10 km distances using GNSS velocities from 20 sites covering the study area. The results indicate that the strain rates reach their maximum at the western boundary where the zone intersects with the GFZ and are non-negligible at the eastern boundary of the zone.

4. Discussion and Findings

To evaluate the strain accumulation along the SFZ—one of the key tectonic features in Western Anatolia—and analyze the region’s seismic hazard, seismic parameter values were estimated firstly in this study. For this purpose, all recorded earthquakes that occurred in the SFZ and its surrounding regions between 1900 and 2024 were first converted to a common moment magnitude (Mw). Using a comprehensive catalog (>4500 events), the a and b parameters of the Gutenberg–Richter (G-R) law were estimated through the nonlinear least squares method and earthquake recurrence intervals were calculated.

4.1. Strain Accumulation and Evaluation of a and b Parameters

The a and b parameters, which are associated with the physics of earthquake occurrence, the tectonics of the region, and the total seismic activity, were determined specifically for the SFZ as a = 6.33 and b = 0.92 (Figure 5). The a-value, which characterizes the degree of seismic activity or indicates the total seismic activity level of the studied region, was classified by Scholz [120] as low seismic activity if it is less than six. However, subsequent studies have shown that the a-value is directly related to the size of the region under investigation, the time period considered, and the catalog used. It has also been emphasized that the a-value may reflect different seismic activity levels for each region. In general, a value between three and four indicates low seismic activity in the region, a value between four and six suggests moderate seismic activity, and a value greater than six indicates high seismic activity. In various studies conducted for different regions of the world, a-values have been estimated using different methods. On a global scale, the a-value has been calculated as 5.65 to 7.23 in oceanic subduction zones, 6.83 to 8.37 in mid-ocean ridges, 6.11 for the San Andreas Fault, and 6.37 for the Bitlis–Zagros collision zone [89]. In another study focusing on the EAFZ, another significant tectonic feature of the Anatolian Plate, the a-values for the Palu-Hazar Lake segment were estimated to range between 6.5 and 7.0. This suggests that the region is seismically more active than other segments of the EAFZ [94]. In a separate study examining the East African Rift System, a different continental plate, the study area was divided into seven regions, and the a-values were found to vary between 3.78 and 8.4. An a-value of 5.75 was calculated for the Afar Triple Junction, which the authors identified as a highly seismically active region [121]. The a-value obtained in this study indicates that the SFZ and its surrounding area have an active seismic structure and indicate intense earthquake activity. Additionally, a significant number of small-to-moderate magnitude earthquakes that occurred in the region during the studied time period further validate the high a-value obtained (Figure 2).

According to Wiemer and Wyss [122], regions with low crustal heterogeneity and stress are associated with b-values greater than 1.0, while values less than 1.0 are related to high differential stresses. A high b-value indicates that small earthquakes dominate in the studied region, while a low b-value suggests that larger earthquakes suppress smaller events in that area. In addition, it has been stated by many researchers that the b-value is related to the Earth’s crustal stress. Regions or faults with high stress rates and large deformation velocities tend to have lower b-values, while areas with low stress accumulation exhibit higher b-values [94,104,120,123,124,125]. The results obtained from this study, which present findings related to the region’s strain rates, have been compared with conducted studies in the literature. In studies where Western Anatolia is generally considered as a whole, with no specific focus on the SFZ, Alptekin [126], Erdik et al. [127], and Kayabali [128] found the a-values to range between 4.4 and 5.4, and the b-values to range between 0.52 and 0.88, within a source zone that includes some part of the SFZ. Papazachos and Kiratzi [129] calculated the a parameter as 3.82 and b parameter as 0.8, Orhan et al. [7] estimated an a-value of 6.82 and b-value of 1.0 in a study that focused on mostly Eskişehir, while Kalyoncuoglu [114] found a-values varying between 5.5 and 6.3 and b-values between 0.8 and 0.9. Also, Polat et al. [130] found the same b-values around SFZ. Bayrak et al. [131] and Öztürk [132] estimated the b-value around 1.02 for the region including the Kütahya, Simav, and Zeytindağ–Bergama faults (KSZBF) together; for the same fault zones, Öztürk et al. [133] found a b-value of 0.65. Similarly, Sayıl and Osmansahin [134] calculated b-values between 0.52 and 0.66 and a-values between 3.85 and 4.78 for two separate sub-region containing different sections of the SFZ. In another study, where Western Anatolia was divided into 15 sub-regions, Bayrak and Bayrak [135] and Bayrak et al. [136] calculated the a-value as 5.7 and the b-value as 0.94 for the region containing the Simav and Gediz-Dumlupınar Faults. In addition to b-values, some studies suggest that modal values (a/b) are compatible with tectonic environments and also reflect seismic activity in the region of interest better than a- and b-values alone. In this study, the modal value was calculated as 6.9, and this value points out that it is both in agreement with b-values and the general seismicity of the study area [90,95,108,137,138]. As a result of this study, when compared with previous studies conducted in the region, most of the studies are in concordance with our seismic parameters, except for those where the b-value was estimated to be considerably low. Most of the studies where the b-value was estimated to be low are those that examine Western Anatolia partially or completely, particularly without focusing on a specific fault zone. Therefore, it is believed that the low b-values obtained do not reflect the general tectonic regime of Western Anatolia, which releases energy through a large number of low-magnitude earthquakes. When considering the high a-value and low-average b-value obtained specifically for the SFZ in this study, these values suggest that the SFZ generally produces numerous low-to-moderate magnitude earthquakes. However, due to the associated subduction tectonics, it is capable of accumulating stress that could potentially generate large earthquakes, such as the Gediz earthquake (Mw = 7.2), despite being less frequent. A similar calculation was made by Öztürk [132], who interpreted the low b-values obtained for the SFZ and its surroundings as an indication of relatively uniform structural characteristics and significant stress accumulation due to subduction tectonics. This, in turn, could lead to stress buildup over time, which is released by earthquakes that, although less frequent, are great in magnitude [139]. Also, the main location of the İzmit earthquake in 1999 (Mw = 7.4) is situated in a region characterized by a higher a-value and an average b-value [130,140,141].

4.2. Earthquake Recurrence Intervals and Seismic Risk

Earthquake recurrence describes the interval between the consecutive events occurring on a fault zone or a specific segment, representing the duration of the seismic sequence, and plays a crucial role in seismic hazard analysis. Determining the earthquake recurrence period provides important information for assessing the seismic potential of a region and evaluating seismic risks. This period helps predict the time of future earthquakes in seismic hazard analyses and provide guiding inputs for the safe design of infrastructure and settlements in the stage of local and regional planning. Recurrence periods, which model the temporal distribution of earthquake hazard, also serve as a significant indicator for understanding fault dynamics and stress accumulation, contributing to the identification of increasing seismic risk in regions where no major earthquakes have occurred for an extended period. This study estimates the recurrence periods of earthquakes for the SFZ as 32 years for M = 5, 165 years for M = 6, and 982 years for M = 7.1 (Figure 6). Considering that the relatively short recurrence periods obtained are related to the presence of moderate-sized earthquakes (low b-values) and partly to the high seismicity rate (high a-value), it is thought that the a and b parameters obtained from the study align with the stress distribution of the seismic environment in the study area [140]. Although these periods, derived from empirical relationships and past earthquakes, are considered predictions based on the analysis, it can be argued that the risk in those areas rises if no earthquake occurs beyond the expected time frame. The earthquakes that occurred in the historical and instrumental periods in and around the SFZ (Table 2) indicate significant seismic activity in the region. Additionally, the series of Simav earthquakes in 2011 (19 May 2011, Mw: 5.8; 27 June 2011, M: 5.0; 3 May 2012, Ml: 5.4) clearly highlight the seismic activity of the SFZ, underscoring the earthquake risk in the region. The results indicate that while moderate-sized earthquakes occur frequently in the Simav and surrounding settlements, a longer period of stress accumulation is required for larger earthquakes to occur. Evaluations made after the 2011 Simav earthquake, one of the region’s most recent destructive earthquakes, revealed that the region is easily affected by moderate-sized earthquakes. The damage caused by this earthquake had significant effects on the settlements and infrastructure. Although the earthquake was classified as moderate, it was strongly felt over a wide area and caused significant damage to concrete structures, leading to the collapse of more than 300 buildings and rendering thousands of others severely impaired and unsafe for use. The massive damage caused by this moderate earthquake in the region is largely due to the alluvial fan covering the underlying soil of Simav and its surroundings, which amplified the earthquake’s intensity [116,142]. Considering the short recurrence intervals of moderate earthquakes obtained in this study, it is believed that the densely populated areas and surrounding regions, situated on Quaternary-aged alluvium transported by nearby lakes and rivers, face significant risk due to unconsolidated soil characteristics and the existing building stock in the area.

4.3. Spatiotemporal Energy Release Patterns and Geodetic Strain Analysis

The spatial distribution of earthquakes occurring in and around the SFZ indicates that the highest seismic activity is concentrated near the western branch of the GFZ, which interacts with the Sındırgı segment (Figure 7). This concentration north of the GFZ initially appears with low bandwidths and gradually spreads across the region, predominantly towards the south. Another area where the spatial concentration of earthquakes increases is the northern part of the Simav segment, which generated the Mw 5.8 Simav earthquake in 2011. The intense seismic activity in this region spreads across the area with high bandwidth ranges. Apart from a small cluster at the eastern end of the SFZ, the overall seismic activity in the rest of the study area remains low.

In contrast to the spatial density map, the distributions of intensity in the energy map of earthquakes occurring in and around the SFZ are different from each other. The primary reason for this difference is that spatial density maps are generated based only on the number of earthquakes, regardless of their magnitude. However, the energy released by these earthquakes increases logarithmically. When examining the energy density map, an energy corridor extending from the northeastern part of the SFZ toward the GFZ is observed (Figure 8). These findings align with the M ≥ 5 earthquakes occurring in the northern part of the region, and the area where energy intensifies along the corridor is the junction of the Sındırgı and Simav segments. In this area, four M ≥ 5 earthquakes occurred in 1969 and 1970. Similarly, energy released from earthquakes is concentrated in the northern part of the Simav segment, as well as around the EF and its surrounding areas. In this region, there is destructive seismic activity during the instrumental period (Figure 2; Table 2) and three historical earthquake records: an intensity V earthquake in 1728, an intensity VIII earthquake in 1860, and an intensity VII earthquake in 1896.

In this study, a temporal energy density analysis of earthquakes was conducted at 10-year periods between 1900 and 2025 to examine the movement of energy flow along the SFZ, for providing essential insights into the dynamics of seismic activity in the region (Figure 9). In the early periods (1900–1940), the regional distribution of energy density appears to be limited to the western part of SFZ only. The temporal and spatial distributions of energy density have shown a distinct geographical shift, particularly after 1960. Before 1960, the intensity of energy density around the GFZ (Gelenbe Fault Zone) indicates that large-magnitude earthquakes occurred further to the west during this period. However, the post-1960 migration of energy accumulation towards the Simav segment and the vicinity of the northern EF (Erdoğmuş Fault) may be linked to the redistribution of regional tectonic stress accumulation, or it could indicate a dynamic shift in the regional tectonic regime, which might be ultimately leading to the 1970 Gediz earthquake. These shifts can be interpreted as a result of interactions between fault systems or long-term seismic release processes. Temporal trends reveal that, following the 1980s, the substantial energy release from the Gediz earthquake dominated the energy density distribution of the SFZ, resulting in its concentration within the central segments. In addition, the 2011 Mw: 5.8 and 2012 Ml = 5.4 Simav earthquakes, which occurred in close proximity to the south of the Gediz earthquake, are also thought to have contributed to the concentration of energy density in this region during the 2000s. This situation suggests that the SFZ (Simav Fault Zone) released its energy through small-to-moderate magnitude earthquakes occurring in its central segments during the 2010s. However, the 2011–2012 earthquakes highlight that the region has not completely lost its potential for producing moderate-to-large magnitude earthquakes and seismic risk continues. Moreover, during a 50-year period extending to the late 1950s, the intersection of the SFZ and GFZ exhibited the highest and most intense energy density. However, the notably lower energy density observed from the 1970s to the end of 2025, compared to earlier periods, may indicate the possibility of energy accumulation in this region. These findings highlight that the spatial and temporal distribution of energy density should be used as a fundamental parameter in seismic hazard analysis to determine whether it follows a pattern. It is believed that detailed fault segmentation studies and current stress measurements in critical areas, such as the intersections of GFZ-SFZ and SFZ-EF, where energy distribution is concentrated, will provide valuable information for preventing potential hazards in the coming years.

The spatial density and energy maps of earthquakes occurring in a region reflect the past activities of faults. While these data provide valuable insights into the future behavior of the faults, obtaining current energy accumulation data of the fault is crucial for seismic hazard analysis. When examining the current strain rates in the study area, it is notable that the strain rates are particularly high at the eastern and western ends of the SFZ (Figure 10). There is a relationship between the Sındırgı Segment of the SFZ, which is defined as a tectonic block boundary in the literature, and the GFZ, which is characterized by high strain rates. The strain rates in this region increase from east to west, particularly in the eastern part of the Sındırgı segment, reaching approximately ~90 ns/yr in the west. In this segment, the extensional regime is dominant, although significant compressional regimes are also observed. This notable difference in strain rates between the Sındırgı segment and the other segments of SFZ is evidence of the relationship between the two zones. No earthquake records directly associated with this rotational relationship between SFZ and GFZ are present in the instrumental period earthquake catalogs. Also, no paleoseismological studies have been conducted on the past activities of these faults yet. However, when examining historical earthquake catalogs, two historical earthquake records can be identified that might be associated with the relationship between the two zones (AFAD Historical Earthquake Catalogue). These earthquakes are located approximately 20–25 km north of GFZ, within the borders of Bigadiç (Balıkesir). The earthquake, located 25 km to the north, occurred in 1826 and had a magnitude of VIII. Another earthquake, located 20 km near the Sındırgı segment, occurred in 1891, but there is no information available regarding its magnitude. In the Simav segment, located to the east of the Sındırgı segment and characterized by a dominant extensional regime, the strain rates in the area where the 2011 Simav earthquake (Mw: 5.8) occurred are lower compared to the west of the segment. In the western part, the strain rates are approximately 70 ns/yr, while in the eastern part, they are around 50 ns/year. In the easternmost part of the zone, at the Sinanpaşa segment, the dominant regime is extensional in the NE-SW direction, with strain rates around 60 ns/yr. In the Şaphane, Abide, and Banaz segments of the zone, the strain rates are around 50 ns/yr. These strain values do not fully support Karasözen et al. [81]’s suggestion of a seismic gap in the central section of the SFZ. However, although this situation can be explained by the low slip rates of the relevant segments and, thus, their slower accumulation of energy, there is no strong evidence to support this. Moreover, although Dönmez and Tiryakioğlu [143] suggest an accumulation of approximately 4 mm on the right-lateral fault identified as the Simav Fault Zone and associated with the surface rupture of the 1970 Gediz earthquake, the accuracy of the GNSS station velocities does not allow for confirmation of the certainty of these data. In the Elvanpaşa segment, located to the east of this region, the strain rates are observed at minimal levels. The low strain rates in the Elvanpaşa segment are considered to be related to the density and distribution of the GNSS sites in the region.

4.4. Comprehensive Evaluation of Seismic Hazard Components

When all findings are evaluated together within this study, the obtained high a-value, low b-value, and calculated recurrence periods collectively demonstrate that the current tectonic stress in the region is gradually released through energy distribution via small-scale earthquakes; however, the potential for generating large-magnitude seismic events and the persistence of regional seismic risk remain significant. Spatiotemporal energy density analyses reveal that the energy distribution, which was predominantly concentrated around the GFZ in the early 1900s, shifted toward the Simav segment and the EF to the north during the earlier 1970s. Although energy density has been predominantly concentrated in the central segment of the SFZ from 1970 to 2025, following the 1970 Gediz earthquake and the 2010s Simav earthquakes, the seismic silence at the intersection of the GFZ and SFZ, in light of earlier seismic activity and the strain rates obtained from this study, raises significant concerns. The current strain rates—reaching values as high as approximately 90 ns/yr in the western Sındırgı segment—especially at the eastern and western ends of the Simav Fault Zone (SFZ), along with the westward shift of seismic activity from the eastern Afyon-Akşehir Graben (AAG) and a history of destructive earthquakes in the area, collectively suggest that future major seismic events in this zone are most likely to occur in its eastern and western segments. Even with the limited catalog used in this study and the strain values derived from the non-uniformly distributed GNSS network around the Simav Fault Zone (SFZ), the findings suggest that the eastern and western segments of the SFZ exhibit a high level of seismic hazard potential. However, given the relatively sparse distribution of 20 GNSS stations across a 205 km-long fault zone and the limitations of a 120-year earthquake catalog, it is concluded that detailed monitoring studies specific to the Simav Fault Zone (SFZ) should be conducted. In addition to seismic hazard assessments, comprehensive seismic risk analyses are also deemed necessary.

5. Conclusions

In this study, the a and b parameters were first determined using the Gutenberg–Richter magnitude–frequency relationship to assess the seismic hazard of the SFZ and its surrounding area. Also, the earthquake recurrence periods, spatial density of the earthquakes and released energy amount, and strain rates for each segment of the SFZ are estimated for the purpose of reflecting the current seismic hazard potential of the region. In a broad sense, calculated a and b parameters using the nonlinear regression approach seem compatible with the tectonic structures and seismic activity of the region. Earthquake recurrence periods, which provide critical insights into the stress release cycle along the fault, were calculated starting from M = 5 to M = 6.2 with increments of 0.1 magnitude. In addition to the earthquake recurrence periods, the spatial distribution of seismic events, the temporal and spatial evolution of the energy corridor, strain rates are calculated to evaluate seismic risk more accurately. The calculated strain rates reaching their maximum values at the junction of the Sindırgı segment and the GFZ, the western end of the Simav Fault Zone (SFZ), as well as along the extension of the ASFS at the eastern end of the SFZ, are significant findings in this study. This indicates that the SFZ, intersecting with other fault zones to the west and east, is interacting with neighboring tectonic structures and actively accumulating strain. The low strain values observed in the segments located in the central part of the SFZ are believed to result from these segments having released a substantial amount of energy during past major earthquakes. These findings, along with the region’s historical seismic activity, suggest that the area is likely to be vulnerable to seismic hazards, warranting a cautious outlook toward future seismic events. Besides, the past events, the existing building stock, and particularly the fact that Simav and its surroundings are situated on alluvial soil indicate that the region is vulnerable even to moderate earthquakes.

While large-scale studies provide a general perspective on the region, the influence of numerous small events generated by the graben systems across Western Anatolia on hazard parameters, such as b-values, can lead to the potential misinterpretation of faults that have produced major earthquakes in the past. This, in turn, may result in the underestimation of seismic hazards and hinder accurate seismic risk assessments. Consequently, this study, which specifically focuses on the SFZ—a region that has experienced destructive earthquakes in the past and impacts millions of people—produces findings that are regarded as both unique and significant, distinguishing it from broader-scale research conducted across Western Anatolia. This study is expected to contribute to a more accurate understanding of seismic hazards at both local and regional levels, serving as a crucial reference for decision-makers in the development of earthquake risk management and mitigation strategies. The findings are expected to play a pivotal role in the formulation of disaster management and preparedness plans aimed at reducing the potential loss of life and property. The earthquake-generating potential of the segments that make up the SFZ, according to the model of a single segment rupture, significantly exceeds the minimum earthquake magnitude threshold (Mw > 6) required to generate surface rupture [43]. The multiple segment ruptures that occurred during the Kahramanmaraş earthquakes in 2023 (Mw: 7.8 and Mw: 7.6) showed a significant increase in both earthquake magnitude and, consequently, the level of destructiveness [144,145]. In high-risk areas such as the SFZ, it is believed that such studies can significantly enhance resilience to seismic events. However, the GNSS network used in this study was not specifically established for the SFZ or for tectonic purposes, and the lack of homogeneous distribution of observation points across its segments is considered one of the study’s limitations. It is anticipated that future research, utilizing a comprehensive seismo-geodetic network specifically designed for the SFZ—as well as for the ASFS located to its east and especially the GFZ in the western region—will enable a more accurate and detailed assessment of the area’s seismic hazard.