Investigating fault characteristics is necessary for seismic hazard evaluation and can provide useful insights for municipalities to optimize their investments in safer buildings and more resilient infrastructure. The location and the geometry of the faults, especially their relationship with sedimentary layer thickness, and the amount of stress drop are critical components when evaluating strong ground motions caused by earthquakes. Interferometric Synthetic Aperture Radar (InSAR) is a powerful tool for accurately determining fault parameters of shallow inland earthquakes and investigating their characteristics in terms of seismic hazards. In this study, based on our earlier results from InSAR data inversions conducted on five Iranian shallow blind reverse-fault earthquakes, we particularly exploited the resolving power of InSAR to investigate fault characteristics and discussed their implications for seismic hazard evaluation in Iran. For all studied Iranian earthquakes, the InSAR-derived fault was deeper than the sedimentary layer. This may indicate that these earthquakes did not rupture the entire seismogenic layer, likely leaving a significant seismic potential. Moreover, the average stress drop of the Iranian earthquakes was relatively large (13.4 MPa), which might be related to their immature blind reverse faults, leading to a possibility of generating stronger short-period ground motions, which should receive greater consideration in future seismic hazard analyses. As InSAR data can be easily accessed, this study presents a cost-effective method to provide fault parameters that can be used for the evaluation of strong ground motions caused by earthquakes, even in countries where observation networks of strong ground motions are not well developed.
Research Article
InSAR-Derived Source Characteristics of Iranian Blind Reverse-Fault Earthquakes and Their Implications for Seismic Hazard Evaluation
https://doi.org/10.21203/rs.3.rs-1407313/v1
This work is licensed under a CC BY 4.0 License
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InSAR
Seismic hazards
Iran
Blind reverse-fault earthquakes
Sedimentary layer
Stress drop
Fundamental components of ground motion evaluation at the sites of interest are the location and geometry of the source, level of seismicity, and structural models (e.g., Parvez et al. 2003). Investigating the fault characteristics in terms of seismic hazards using accurate source models can provide useful insights for municipalities to optimize their investments in safer buildings and more resilient infrastructure. Hence, the seismic risk of a given area, such as property losses and damages to buildings, can be accurately assessed with an accurate estimate of seismic hazard, which can be used for various purposes, including building codes for standard buildings, designing larger buildings and infrastructure projects, land use planning, and determining insurance rates.
The Arabian plate is moving in a N13°E direction at a rate of approximately 31 mm yr-1 relative to the Eurasian plate at a longitude of 52°E (Vernant et al. 2004). As a result of the convergent geodynamics in the region, Iran is one of the most seismically active countries in the world and has suffered many deaths and losses of livelihood throughout human history due to catastrophic earthquakes. From 1900 to the present day, the United States Geological Survey (USGS) database has recorded more than 100 earthquakes with M ≥ 6 in Iran and adjacent areas (Fig. 1). Raeesi et al. (2017) noted that since 2000 BC, more than 50 major earthquakes with M ≥ 7 have struck the Iranian plateau and these events along with large and moderate earthquakes have caused more than 1,936,000 fatalities the country. Notably, for some recent earthquakes in Iran, earthquake hazard assessments have failed to correctly predict actual ground motions and intensities (Zare 2017). These facts highlight the importance of improving the seismic hazard evaluation system in the country.
In many countries, presence of sedimentary layer prevents accurate seismic hazard evaluation. There are several reasons for the difficulty in evaluating seismic hazards in Iran. Firstly, due to sparse seismic stations in Iran, the characterization of faulting using seismic data cannot be precisely performed. Secondly, reverse faults dominate the tectonic of Iran (Berberian and Yeats 1999), which are usually overlaid by sediment layer and have not been well studied. Lastly, reverse faults have a low probability of surface rupturing because rock and overlying sediments can sustain compression more than tension (Ambraseys and Jackson 1998; Moss and Ross 2011).
Radiguet et al. (2009) noted that both a blind fault and an immature fault would strengthen the ground motions. Moreover, it has been well known that the sedimentary layer greatly amplifies ground motions associated with earthquakes (e.g., Aoi et al. 2008). Most regions of Iran are covered by sedimentary layer (Fig. 2b); hence, the relation between the fault depth and sedimentary layer thickness is an important factor for accurately evaluating earthquake ground motions.
One of the key strengths of Interferometric Synthetic Aperture Radar (InSAR) is its detectability and high spatial resolution in the epicentral area of shallow inland earthquakes, which can often provide the ground truth for fault parameters of shallow moderate magnitude earthquakes (Ghayournajarkar and Fukushima 2022). Moreover, InSAR is particularly useful for such purpose in countries with sparse seismic stations, such as Iran, because of the public availability of the InSAR data. In this study, based on our earlier results from InSAR data inversions conducted on five Iranian shallow blind reverse-fault earthquakes (Ghayournajarkar and Fukushima 2022), we exploit the resolving power of InSAR for investigating the fault characteristics and discussed their implications for seismic hazard evaluation in Iran. We specifically focus on the depth of the top of the rupture and on the stress drop, as these are key components for predicting earthquake ground motions.
Table 1 lists the studied earthquakes. These earthquakes, Mw 5.9–7.3 and focal depth 9.0–19.0 km, caused clear InSAR signals, and were all associated with blind reverse faulting. The earthquakes occurred in the north (2017 Sefid Sang), south (2005 Qeshm and 2008 Dargahan), west (2017 Kermanshah), and center (2017 Hojedk) of Iran (Fig. 2).
Table 1 USGS-derived location, depth, and moment magnitude of the studied Iranian earthquakes
|
Earthquake |
Date (yyyymmdd) |
Latitude (°N) |
Longitude (°E) |
Depth (km) |
Magnitude (Mw) |
|
Qeshm |
20051127 |
26.774 |
55.858 |
10.0 |
5.9 |
|
Dargahan |
20080910 |
26.743 |
55.828 |
12.0 |
6.1 |
|
Sefid Sang |
20170405 |
35.776 |
60.436 |
13.0 |
6.1 |
|
Kermanshah |
20171112 |
34.911 |
45.959 |
19.0 |
7.3 |
|
Hojedk |
20171201 |
30.746 |
57.307 |
9.0 |
6.1 |
The 2005 Qeshm earthquake struck Qeshm island, located in the southeastern part of the Zagros fold-and-thrust belt. This is one of the most seismically active belts in the world. This region has been struck by moderate to large magnitude earthquakes with general focal mechanisms of reverse faulting and with focal depths of 10–20 km (Arian 2015). This earthquake destroyed the village of Tonban, located in the central part of the island, and caused 13 deaths and injured approximately 100 people (Nissen et al. 2007). The Global Centroid Moment Tensor (GCMT)-derived focal mechanism of the earthquake suggested that the main shock involved a predominantly reverse fault motion that is consistent with the mechanism of the faults in the region. The 2008 Dargahan earthquake also struck Qeshm island, which caused seven deaths and injured 30 people (Sorbi et al. 2012). The focal mechanism determined by the USGS indicated an oblique reverse faulting.
The 2017 Sefid Sang earthquake struck northeastern Iran, approximately 90 km southeast of Mashhad city with a population of more than three million. This region contains the Kopeh Dagh fold-and-thrust belt, which generates low to moderate magnitude earthquakes with focal mechanisms of dextral strike-slip faulting and thrusting (Arian 2015). The focal mechanism solutions of the 2017 Sefid Sang earthquake showed that the earthquake ruptured an oblique reverse fault (Aflaki et al. 2019; Ghayournajarkar and Fukushima 2020), which is consistent with the regional transpressional stress regime (Shabanian et al. 2010).
The 2017 Kermanshah earthquake struck the Iran-Iraq border with a USGS-derived epicenter located approximately 50 km northeast of Sarpol-e Zahab city. This earthquake occurred in the northern margin of the Zagros fold-and-thrust belt along the northeastern part of the Arabian plate. This region has experienced not only moderate to large magnitude earthquakes of shallow depths but also relatively deep earthquakes (depths exceeding 70 km), which is an indication of the initial stages of thick-skinned tectonics (Arian 2015). The 2017 Kermanshah earthquake was the strongest instrumentally recorded earthquake in the region and caused at least 530 deaths (Feng et al. 2018). The focal mechanism determined by the European Mediterranean Seismological Center (EMSC) indicated an oblique reverse faulting.
The 2017 Hojedk earthquake struck the eastern part of the village of Hojedk, approximately 50 km north of Kerman city. The western part of the Tabas-Minab seismotectonic province, where the earthquakes occurred, has experienced moderate to large magnitude earthquakes exhibiting focal mechanisms of dominantly reverse faulting with dextral strike-slip (Arian 2015). This earthquake did not cause too much destruction because it occurred in a remote region with a sparse population, but its occurrence suggests the presence of an unknown fault, and hence, potential seismic hazards for much larger neighboring settlements, such as Kerman with a population of approximately 800,000 (Savidge et al. 2019). The earthquake exhibited a predominantly reverse fault mechanism.
This study uses the fault models obtained by Ghayournajarkar and Fukushima (2022). The data and method for determining these fault models are summarized in this section.
We used ascending and descending interferograms of the Advanced Land Observing Satellite (ALOS-2), Environmental Satellite (ENVISAT), and Sentinel-1A satellite to map the co-seismic deformation caused by the earthquakes (Table 2).
Table 2 Interferograms used to study the Iranian earthquakes (Ghayournajarkar and Fukushima 2022)
|
Earthquake |
Satellite |
Track*a |
Primary (yyyymmdd) |
Secondary (yyyymmdd) |
B*b (m) |
Incidence Angle |
|
Qeshm 2005 |
ENVISAT |
328A |
20050105 |
20051221 |
-26.3 |
40.6 |
|
|
435D |
20051124 |
20051229 |
-186.8 |
22.1 |
|
|
Dargahan 2008 |
ENVISAT |
328A |
20060125 |
20081001 |
-539.9 |
40.9 |
|
|
435D |
20080417 |
20081009 |
-81.2 |
22.0 |
|
|
Sefid Sang 2017
|
ALOS-2 |
171A |
20170121 |
20170624 |
-1.1 |
36.2 |
|
|
64D |
20170315 |
20170524 |
-376.7 |
32.5 |
|
|
Sentinel-1A |
13A |
20170324 |
20170405 |
-63.0 |
33.8 |
|
|
|
93D |
20170330 |
20170411 |
36.4 |
33.8 |
|
|
Kermanshah 2017
|
ALOS-2 |
179A |
20171012 |
20171123 |
65.9 |
34.3 |
|
|
72D |
20160523 |
20180521 |
147.2 |
40.4 |
|
|
Sentinel-1A |
72A |
20171111 |
20171123 |
-29.3 |
41.5 |
|
|
|
6D |
20171107 |
20171119 |
13.5 |
46.6 |
|
|
|
ALOS-2 |
173A |
20171121 |
20171205 |
-112.5 |
38.5 |
|
Hojedk 2017 |
Sentinel-1A |
57A |
2017112 |
20171204 |
125.0 |
45.7 |
|
|
|
166D |
20171130 |
20171212 |
-27.4 |
33.7 |
a A and D correspond to ascending and descending orbits, respectively. b Perpendicular baseline.
We assumed a layered-structure model containing sediment and crystalline crust layers obtained from the CRUST1.0 model (Laske et al. 2013). The CRUST1.0 model is a database of crustal thickness obtained from the compilation of multiple studies defined on a one-degree grid. In each one-degree cell, the boundary depth, compressional and shear-wave velocities, and density are given. To calculate the crustal deformation using the layered-structure model, we used the EDGRN/EDCMP software (Wang et al. 2003). The layered-structure velocity model used in the fault slip inversions was obtained from the CRUST1.0 model (Fig. S1 and S2). We inverted the unwrapped interferograms to solve for the fault parameters, consisting of the horizontal location of the top side of the fault, length, width, depth of the top side of the fault, dip angle, strike angle, rake angle, and slip. The model parameters were solved using Particle Swarm Optimization (PSO) (Kennedy and Eberhart 1995). As the focal mechanism solutions of the earthquakes indicated two candidates of fault planes with different dipping directions, a set of two inversions was conducted for each earthquake by assuming each of the two possible fault dipping directions. Basically, by investigating on the data fit, we selected our preferred fault model for the studied Iranian blind reverse-fault earthquakes. We further confirmed that the selection of the model did not affect the conclusion of our study.
The method used to achieve the purpose of the present study, that is, revealing the characteristics related to the seismic hazard of the studied Iranian blind reverse-fault earthquakes, consists of two investigation approaches as follows:
(1) As the seismic hazard in the immediate vicinity of an earthquake strongly depends on the rupture extent in the seismogenic layer, we compared the depth of the bottom of the sediment layer obtained from the CRUST1.0 model and previous local studies with the InSAR-derived depth of the top of the rupture.
(2) A larger stress drop leads to the radiation of strong short-period ground motions. The stress drop is a key parameter for the estimation of strong ground motions caused by earthquake ruptures (e.g., Miyakoshi et al. 2020; Soghrat et al. 2012). We compared the stress drops of the studied Iranian earthquakes with those of the Japanese earthquakes obtained from our earlier study (Ghayournajarkar and Fukushima 2022) and other studies.
Tables S1 and S2 list the fault parameters of the preferred models derived from the inversions of InSAR data for the studied Iranian and Japanese earthquakes (Ghayournajarkar and Fukushima 2022). The InSAR-derived depths of the upper limit of the fault ruptures ranged between 4.5 and 14.8 km. The comparison between the InSAR-derived depth of the top of the rupture and the depth of the bottom of the sedimentary layer shows that there is a systematic gap between the depth of the top of the rupture and that of the bottom of the sedimentary layer for all the studied Iranian earthquakes (Table 3 and Fig. 3).
Table 3 Comparison of the InSAR-derived depth of the top of the rupture of the preferred fault model and the thickness of the sedimentary layer for the studied Iranian earthquakes
|
Earthquake |
This study
Top Fault |
CRUST1.0
Sediments |
Previous local studies
Sediments |
|
|
Depth (km) |
Thickness (km) |
Thickness (km) |
Type of the study |
|
|
Qeshm 2005 |
6.0 |
5.0 |
3.0
|
Rayleigh wave dispersion (Shirzad and Yaminifard 2020) |
|
Dargahan 2008 |
5.7 |
5.0 |
3.0
|
Rayleigh wave dispersion (Shirzad and Yaminifard 2020) |
|
Sefid Sang 2017 |
5.4 |
0.9 |
1.2
|
Stratigraphy (Poursoltani 2017) |
|
Kermanshah 2017 |
14.8 |
0.5 |
8.0
|
Stratigraphy (Nissen et al. 2019) |
|
Hojedk 2017 |
4.5 |
2.0 |
1.0
|
Stratigraphy (Poole and Ataabadi 2005) |
The uncertainties in the InSAR-derived depth of the top of the rupture range between 0.2-1.0 km, which is smaller than the gap for most cases. Although the uncertainties in the sedimentary layer thickness from previous studies vary and are not necessarily estimated, the consistent gap exists for results derived from both the CRUST1.0 model and previous local studies, supporting the actual presence of the gaps.
Next, we calculated the stress drops of our analyzed Iranian and Japanese earthquakes, according to the following relation (Kanamori and Anderson 1975):
where M0 is the seismic moment in Nm, calculated assuming a shear modulus of 30 GPa, and S is the rupture area in M2. Strictly speaking, the factor 
is used for circular faults. For rectangular faults, such factors depend on the aspect ratio and have only been numerically calculated for some specific aspect ratios. Hence, we opted for Equation (1) in this study. According to Noda et al. (2013), the factors for rectangular faults are slightly larger than the factor for circular faults, and consequently our estimates of stress drop when using Equation (1) are expected to be slightly smaller.
Table 4 lists the parameters derived from the fault models of the studied Iranian earthquakes (Ghayournajarkar and Fukushima 2022), including their seismic moment, rupture area, stress drop, and moment magnitude. The calculated stress drops range from 9.6 to 17.1 MPa.
Table 4 Parameters derived from the fault models of the Iranian earthquakes
|
Iranian Earthquakes |
Seismic moment (Nm) |
Rupture area |
Stress drop (MPa) |
Magnitude |
|
Qeshm 2005 |
1.22E+18 |
34.5 |
14.6 |
5.99 |
|
Dargahan 2008 |
1.28E+18 |
47.1 |
9.6 |
6.00 |
|
Sefid Sang 2017 |
1.21E+18 |
36.4 |
13.5 |
5.99 |
|
Kermanshah 2017 |
7.79E+19 |
629.1 |
12.0 |
7.19 |
|
Hojedk 2017 |
1.17E+18 |
30.3 |
17.1 |
5.98 |
5.1 Systematic gap between depth of the top of the rupture and that of the bottom of the sedimentary layer
Seismic hazards in the immediate vicinity of an earthquake are usually assumed to have been reduced after the rupture of a continental fault. However, this is only realized if the entire seismogenic layer ruptures during the event (Elliott et al. 2011). The systematic gap between the depth of the top of the rupture and that of the bottom of the sedimentary layer for the studied earthquakes indicates either of the following. 1) The earthquakes did not rupture the entire seismogenic layer, 2) the sedimentary layer thickness results were not accurate enough, and 3) the layer immediately beneath the sedimentary layer (the gap) was not seismogenic. The third possibility cannot be excluded, but the consistency of the presence of the systematic gap in results derived from both the CRUST1.0 model and previous local studies indicates that the effect of the uncertainty in the estimation of the sedimentary layer is limited.
It has been known that reverse-fault earthquakes even with moderate magnitude have seismogenic potential to rupture the sedimentary layer and reach the ground surface. Ritz et al. (2020) pointed out that the 2019 Le Teil reverse-fault earthquake ( 4.9) in France ruptured shallow depths in the Mesozoic sediments up to the ground surface. Furthermore, although the sense of rupture was normal faulting, the 2011 and 2016 events in Japan provide another intriguing case where a significant portion of rupture occurred shallower than 5 km above the upper limit depth of the aftershocks (Fukushima et al. 2018). These earthquakes could have spontaneously ruptured the uppermost part of the seismogenic layer and passively ruptured the sedimentary layer above it simultaneously. Thus, we anticipate such surface-breaking ruptures above the studied Iranian blind reverse-fault earthquakes. It would be important in future studies to clarify whether the shallow zones are seismic or aseismic by investigating slip deficit.
5.2 High stress drops of the Iranian earthquakes
A larger stress drop leads to radiation of strong short-period ground motions; therefore, stress drop is commonly a key parameter in estimating these ground motions (e.g., Soghrat et al. 2012). Knowledge regarding the general characteristics of the stress drop is therefore important for understanding the seismic hazards in the region.
Ghayournajarkar and Fukushima (2022), conducted fault slip inversions on Japanese earthquakes as well using the identical method applied to the studied Iranian earthquakes described in section 3. Here, we calculated the stress drops of these earthquakes using Equation (1), ranging from 3.7 to 5.8 MPa (Table 5).
Table 5 Parameters derived from the fault models of the Japanese earthquakes
|
Japanese Earthquakes |
Seismic moment (Nm) |
Rupture area |
Stress drop (MPa) |
Magnitude |
|
Iwate-Miyagi 2008 |
3.01E+19 |
729.9 |
3.7 |
6.92 |
|
Nagano 2014 |
4.72E+18 |
157.5 |
5.8 |
6.38 |
|
Tottori 2016 |
2.52E+18 |
117.0 |
4.8 |
6.20 |
|
Ibaraki 2016 |
5.18E+17 |
42.8 |
4.5 |
5.74 |
The average stress drops of the studied Iranian and Japanese earthquakes are 13.4 and 4.7 MPa, respectively (Tables 4 and 5). The larger stress drops of the studied Iranian earthquakes indicate that the strength of their causative faults is larger than that of the studied Japanese faults, and also indicate that the studied Iranian earthquakes can generate strong short-period seismic waves, which should be considered when evaluating the seismic hazards in the region.
Our results are consistent with the scaling law of the seismic moment and the rupture area as proposed by Kanamori and Anderson (1975) (Fig. 4). The stress drops recently obtained by Miyakoshi et al. (2020) are also plotted in Figure 4, again showcasing the systematic tendency of larger stress drops for the Iranian earthquakes, although the values estimated by Miyakoshi et al. (2020) were obtained via seismic waveform inversion analyses, which can lead to different results (which was the case for the 2014 Nagano earthquake). Manighetti et al. (2007) pointed out that the earthquake stress drop has a strong relationship with the structural maturity of the ruptured fault. Similarly, Wen et al. (2014) suggested that the large stress drops of blind reverse-fault earthquakes may be related to their immature faults. Our results suggest that the studied Iranian earthquakes caused rupturing of immature blind faults.
In the future, the stress drops should be assessed for more earthquakes in order to build a database that will enable to derive different scaling laws for different slip senses (strike-slip, reverse, or normal).
We have investigated the fault characteristics of five blind reverse-fault earthquakes that occurred in Iran using InSAR data and discussed their implications for seismic hazard evaluation. The conclusions derived from these investigations are summarized as follows:
(1) For all studied Iranian earthquakes, the InSAR-derived depth of the top of the rupture was systematically deeper than the bottom of the sedimentary layer. This may indicate that the earthquakes did not rupture the entire seismogenic layer, likely leaving a seismogenic potential to rupture the sedimentary layer and reach the ground surface. The risks of such surface-rupturing events and associated hazards should not be ignored.
(2) The causative blind reverse faults of the studied Iranian earthquakes had larger stress drops than the Japanese earthquakes, leading to the possibility of generating strong short-period ground motions. The larger stress drops of these earthquakes might be related to immature blind faults, which should be considered in future earthquake scenarios to mitigate future seismic hazards. Using appropriate values of stress drop and assuming faults not only along the mapped active faults but also in the possible areas surrounding them, provides useful insights for engineers to construct safer buildings and more resilient infrastructure. In the future, the stress drop estimates can be improved with details by analyzing more events and deriving different scaling laws for different slip senses (strike-slip, reverse, or normal).
As InSAR data can be easily accessed, this study presents a cost-effective method to provide fault parameters that can be used for evaluation of strong ground motions caused by earthquakes even in countries where observation networks of strong ground motions are not well developed.
Funding
The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
Competing Interests
The authors have no relevant financial or non-financial interests to disclose.
Author contributions
Figures and tables preparation, data collection, and analysis were performed by Nematollah Ghayournajarkar. The first draft of the manuscript was written by Nematollah Ghayournajarkar and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Availability of data and materials
ENVISAT and Sentinel-1A SAR data are available from the European Space Agency (ESA). The processed results can be shared upon request to the authors.
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