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Technical Note

D-InSAR-Based Analysis of Slip Distribution and Coulomb Stress Implications from the 2024 Mw 7.01 Wushi Earthquake

by
Yurong Ding
,
Xin Liu
*,
Xiaofeng Dai
,
Gaoying Yin
,
Yang Yang
and
Jinyun Guo
College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(22), 4319; https://doi.org/10.3390/rs16224319
Submission received: 29 October 2024 / Revised: 17 November 2024 / Accepted: 17 November 2024 / Published: 19 November 2024
(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Third Edition))
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Abstract

:
On 23 January 2024, an Mw 7.01 earthquake struck the Wushi County, Xinjiang Uygur Autonomous Region, China. The occurrence of this earthquake provides an opportunity to gain a deeper understanding of the rupture behavior and tectonic activity of the fault system in the Tianshan seismic belt. The coseismic deformation field of the Wushi earthquake was derived from Sentinel-1A ascending and descending track data using Differential Interferometric Synthetic Aperture Radar (D-InSAR) technology. The findings reveal a maximum line-of-sight (LOS) displacement of 81.1 cm in the uplift direction and 16 cm in subsidence. Source parameters were determined using an elastic half-space dislocation model. The slip distribution on the fault plane for the Mw 7.01 Wushi earthquake was further refined through a coseismic slip model, and Coulomb stress changes on nearby faults were calculated to evaluate seismic hazards in surrounding areas. Results indicate that the coseismic rupture in the Mw 7.01 Wushi earthquake sequence was mainly characterized by left-lateral strike-slip motion. The peak fault slip was 3.2 m, with a strike of 228.34° and a dip of 61.80°, concentrated primarily at depths between 5 and 25 km. The focal depth is 13 km. This is consistent with findings reported by organizations like the United States Geological Survey (USGS). The fault rupture extended to the surface, consistent with field investigations by the Xinjiang Uygur Autonomous Region Earthquake Bureau. Coulomb stress results suggest that several fault zones, including the Kuokesale, Dashixia, Piqiang North, Karaitike, southeastern sections of the Wensu, northwestern sections of the Tuoergan, and the Maidan-Sayram Fault Zone, are within regions of stress loading. These areas show an increased risk of future seismic activity and warrant close monitoring.

1. Introduction

At 2:09 AM on 23 January 2024, a Mw 7.01 earthquake struck Wushi County, Xinjiang Uygur Autonomous Region. The China Earthquake Networks Center confirmed that the epicenter is located at (41.26°N, 78.63°E) with a focal depth of 22 km. The maximum intensity reached IX, primarily impacting Wushi County in the Aksu Prefecture and Aheqi County in the Kizilsu Kirghiz Autonomous Prefecture. By 28 January 2024, over 4000 aftershocks had been recorded, which is considered a mainshock-aftershock sequence with the maximum magnitude 5.7. The earthquake resulted in three fatalities and five injuries, with no major casualties or significant property damage reported [1].
The earthquake occurred in the Tianshan seismic belt [2], near the Maidan-Sayram Fault Zone (M-SF). After the earthquake, various agencies released focal mechanism solutions [3,4,5,6]. Considering the seismogenic environment of the affected area, initial assessments indicate that the 2024 Mw 7.01 Wushi earthquake involved thrusting with a left-lateral strike-slip component. Historical earthquake records show that in the past 50 years, there have been 131 earthquakes with a magnitude of 5.0 or above in the region [7]. Analyzing the structural geometry and slip behavior of the seismogenic fault from this earthquake is highly valuable for understanding tectonic dynamics within the Tianshan seismic belt fault system.
This earthquake was influenced by compressional forces resulting from the collision of the Indian plate. The area contains numerous northeast-trending thrust and left-lateral strike-slip faults. Additionally, a series of ongoing aftershocks have been recorded (see Figure 1). Recent geological investigations indicate that the Mw 7.01 Wushi earthquake in Xinjiang occurred at the convergence of the Southern Tianshan and Wushi Basin, where the Tarim block shifts southward and the Southern Tianshan block moves northward [2]. The Tianshan region is well-known for its irregular and frequent seismic events. Since 1900, 11 earthquakes with magnitudes of 7.0 or above have been documented in this region [8], the most significant being the Mw 8.0 earthquake that struck Atushi on 22 August 1902 [9].
The M-SF within the Tianshan seismic belt initiated the 2024 Mw 7.01 Wushi earthquake, driven by marked north-south compression and shear dynamics [10,11,12]. The fault has been active since the Holocene. Recent studies indicate that the M-SF has experienced both left-lateral strike-slip and thrust movement since the Late Quaternary [13,14]. Geological data indicate that the fault has an east-northeast (E-N-E) orientation, accommodating compressive shortening to the south of the Tianshan and showing a pronounced dip to the west [14]. The geological shortening rate during the Late Quaternary is estimated at approximately 1.19 ± 0.25 mm/year [13], consistent with the geodetic measurements that indicate an annual rate between 1.15 and 2.10 mm [14,15]. Moving westward, the shortening rate gradually decreases, estimated at 0.20 to 0.30 mm/year [12,14]. Numerical simulations recently suggest a steady rise in Coulomb stress on the M-SF, indicating that stress buildup has elevated the seismic risk in the region. Moreover, tectonic stress accumulation on the fault is viewed as a factor contributing to the heightened risk [16]. Analysis of earlier geological data has shown a considerable interseismic slip shortfall, which may have the potential to initiate an earthquake exceeding magnitude 7 on the M-SF [17].
Currently, Interferometric Synthetic Aperture Radar (InSAR) technology provides essential ground deformation data and technical support for advancements in seismic geodesy. The Differential Interferometric Synthetic Aperture Radar (D-InSAR) extracts deformation information by repeatedly observing the same area, offering advantages such as extensive coverage, strong continuity, and robust reliability in fault geometry parameter inversion and slip distribution results [18,19,20,21,22,23,24]. To precisely characterize the deformation features of this earthquake and its associated structures, this study employed D-InSAR measurement techniques. The Sentinel-1A data were used to derive the coseismic deformation field, which then served to constrain a nonlinear inversion based on the Okada elastic half-space dislocation model, allowing for the calculation of fault geometry parameters and rupture parameters. The coseismic slip distribution is determined using the non-negative least squares method, followed by calculations of Coulomb stress changes at various depths to assess regional seismic hazards.

2. Coseismic Deformation Analysis

2.1. D-InSAR Data Processing

The ascending and descending Sentinel-1A data covering the seismogenic zone of the 2024 Mw 7.01 Wushi earthquake were selected (Table 1) (website: https://browser.dataspace.copernicus.eu/, accessed on 23 May 2024), with the coverage area displayed in Figure 2. The D-InSAR technique was applied using SARscape® 5.7.0 software in ENVI to derive the coseismic deformation field [25]. During data processing, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) data, with a spatial resolution of 30 m × 30 m provided by NASA, were used to mitigate the influence of topographic phase [26,27]. Single-look complex SAR images were subjected to multi-looking with a range-to-azimuth ratio of 4:1 to suppress noise and enhance the signal-to-noise ratio. The Goldstein adaptive filtering algorithm was applied to the coseismic interferometric phase for noise reduction [28]. Tropospheric delay corrections were made using the Generic Atmospheric Correction Online Service (GACOS) model [29,30]. Phase unwrapping of the interferogram was conducted using the Minimum Cost Flow (MCF) algorithm [31], with a coherence threshold of 0.3. Finally, deformation data were geocoded using DEM data [32], converting the radar satellite data coordinate system to the WGS84 coordinate system.

2.2. Coseismic Deformation Field

Figure 3 illustrates surface deformation fields along the line-of-sight (LOS) from InSAR data. The positive values indicate displacement toward the satellite, whereas negative values represent displacement in the opposite direction. The coseismic deformation fields across all three tracks exhibit consistent deformation characteristics. The LOS deformation for all tracks shows the same sign, indicating uniform relative vertical motion, suggesting that thrust faulting primarily triggered the earthquake. Track 56 results indicate a peak displacement of 81.1 cm toward the satellite and 16 cm in the opposite direction. For track 34, the maximum displacement is 50.3 cm toward and 11.9 cm away from the satellite, while track 136 shows approximately 65.7 cm toward and 21.1 cm away. These variations are attributed mainly to differences in observation geometry. The deformation is more pronounced on the northwest side compared to the southeast side [33]. Notably, the D-InSAR results show that the image coherence is still relatively high, which suggests that only a small portion of the fault may have ruptured to the bottom surface. The coseismic deformation field primarily shows uplift, with a deformation pattern consistent with thrust fault earthquake characteristics.

3. Inversion of Fault Parameters and Slip Distribution

3.1. Uniform Slip Model

The Mw 7.01 Wushi earthquake occurred on the M-SF. Due to the lack of prior fault parameters of the seismogenic fault, a nonlinear method is needed to set the basic search space for inversion. The Geodetic Bayesian Inversion Software Version 1.1 (GBIS), which applies an elastic half-space dislocation model, was used to perform the inversion of the fault parameters [34,35]. Given the spatial continuity of InSAR observations, an excessive data volume would add no further detail but would exponentially increase computational demands, hindering the convergence of inversion results. Therefore, prior to modeling, the range deformation results were downsampled using a quadtree algorithm [36], with the variance threshold set to 0.0082 m. Ultimately, 1886, 988, and 768 deformation points were obtained for tracks T056, T034, and T136, respectively. Based on the parameters published by various institutions and studies (see Table 2), we set the search range for the parameters as follows: the fault strike is set between 200° and 300°, the dip angle is set between 30° and 70°, the fault length is set between 30 km and 40 km, the fault width is set between 10 km and 20 km, and the strike-slip and dip-slip amounts are set between −3 m and 3 m. In this range, the Okada half-space dislocation model was used for inversion, and the Levenberg–Marquardt least-squares optimization algorithm was applied to identify optimal fault geometry parameters [37,38], with iterations set to 106.
Figure 4 displays the posterior probability density functions for the nine fault source parameters. Histograms of the marginal distributions for each parameter are shown in the bottom row, while joint distributions between parameter pairs are illustrated in the other rows. The inversion results show a fault measuring 34.8 km in length, 15.8 km in width, and extending to a depth of 7.9 km (from the surface to the midpoint of its upper boundary). The fault has a strike of 228.34° and a dip of 61.88°. In this study, the reference point is set at (78.67°E, 41.20°N). The posterior probability plots (Figure 4) show significant correlations between the following parameter pairs: dip-slip and width, dip-slip and depth, and depth and width. The source parameters suggest that the causative fault has a reverse faulting mechanism combined with left-lateral strike-slip features. The fault parameters inverted in this study align closely with the focal mechanisms reported by various institutions (see Table 2). The fault slip depth is primarily concentrated around 7.8 to 8 km. The strike-slip and dip-slip measurements are 1.53 m and 1.69 m, respectively. In the uniform slip model inversion, Poisson’s ratio was assigned a value of 0.25 [39]. The estimated earthquake moment is 3.65 × 1019 N·m, corresponding to a moment magnitude of Mw 7.01.
Table 2. Source Parameters of the 2024 Mw 7.01 Wushi Earthquake Released by Different Agencies.
Table 2. Source Parameters of the 2024 Mw 7.01 Wushi Earthquake Released by Different Agencies.
Source of StudyEpicenterStrike (°)Dip (°)Rake (°)Length (km)Width (km)Magnitude
USGS [3]78.64°E, 41.26°N2354542----7.0
GCMT [4]78.57°E, 41.19°N2364847----7.0
IPGP [5]78.59°E, 41.29°N2345051----7.1
CEA [6]78.63°E, 41.22°N2504259----7.0
Nai (2024) [40]78.64°E, 41.23°N230554234.710.57.05
Li (2024) [41]78.65°E, 41.22°N22962.450.4535.47.17.0
Zhao (2024) [42]78.60°E, 41.19°N22867603414.27.0
Guo (2024) [43]--23555------7.03
Yu (2024) [44]--22962.849.8------
Qiu (2024) [33]78.66°E, 41.23°N229.1759.8844.3483.713.177.02
This study78.66°E, 41.22°N228.3461.88--34.815.87.01
Figure 5 displays the observed, modeled, and residual results of the coseismic deformation field obtained from the uniform slip model inversion. There is a strong consistency between the observed results and the forward modeling results of the uniform slip distribution model. The residual results in Figure 5c,f,i show that the overall residuals are not significant. To quantitatively evaluate the fault slip model’s reliability, the mean, standard deviation, and root mean square error (RMSE) of the fitting residuals were calculated for each of the three tracks. It was found that the mean/standard deviation/RMSE for track T056 were 0.54/0.90/1.05 cm, for track T034 were −0.59/1.16/1.31 cm, and for track T136 were 0.55/1.32/1.07 cm (Table S2). These results demonstrate that the fault slip model has high accuracy and reliability.

3.2. Coseismic Slip Model

In most cases, fault slip caused by earthquakes is uneven. To better describe the fault slip, a distributed slip inversion is required. Initially, the fault’s geometry is defined using parameters calculated in the previous step. Subsequently, the steepest descent method (SDM) is applied to invert the detailed slip distribution of the source fault [45]. This approach uses non-negative least squares to establish the relationship between fault slip and surface deformation. The objective function for the inversion is
W G s − y 2 + α 2 H s 2 = min
where y denotes the surface deformation; s represents the slip on each fault segment; G is the Green’s function; H refers to the second-order finite difference Laplacian operator; α2 is the smoothing factor; and W is the weight matrix. In this study, the fault plane is divided into meshes, each measuring 2.8 km × 2.8 km.
The trade-off curve shown in Figure 6 illustrates slip model roughness versus data fit. The curve’s inflection point was selected as the optimal smoothing factor [46], and for the Wushi earthquake this factor was determined to be 0.07. The choice of medium model affects the layering of Earth’s materials, which can influence the coseismic deformation field [46]. In this study, parameters for the subsurface medium model were derived from the CRUST 1.0 model (Table 3) [47,48]. These medium model parameters are used to calculate the Green’s function G [49,50,51].
Figure 7 and Figure 8 display the slip distribution model along the fault’s strike, showing a rupture length of 50 km and a maximum slip of 3.2 m centered at 78.60°E, 41.20°N, at a depth of 10.2 km. The calculated seismic moment is 3.69 × 1019 N·m, corresponding to an Mw 7.02 earthquake, consistent with findings from other agencies. Near the surface, the slip is relatively low, measuring 1.45 m. The primary slip zone extends along 10–60 km of the fault’s strike, occurring at depths of 5 to 25 km. Although the slip near the surface is limited, both the slip distribution model results and field observations by the Xinjiang Earthquake Agency indicate that this earthquake ruptured the surface. The RMS between the calculated fault slip model and the slip distribution model published by USGS is 0.02 m. The RMS value of 0.02 m indicates a high degree of consistency between the calculated fault slip model and the slip distribution model reported by the USGS. This low RMS error suggests that the calculated model closely aligns with the primary slip characteristics observed by the USGS. However, it is important to note that the reliability of this approach also depends on the selected inversion parameters. While the small RMS discrepancy indicates a good match between the spatial pattern and slip magnitude of the models, the confidence in the model’s accuracy for interpreting the earthquake’s rupture characteristics is influenced by the choice of parameters used in the inversion process.

4. Regional Seismic Risk Assessment

Analyzing variations in Coulomb Failure Stress (CFS) during major earthquakes is essential for evaluating future seismic risks near the epicenter. Fault rupture involves the release and redistribution of stress, where positive CFS changes indicate stress loading and negative changes indicate stress unloading on the fault. These variations impact earthquake occurrence. Using Coulomb 3.3 software, the static Coulomb stress changes (ΔCFS) induced by the coseismic rupture in adjacent areas were quickly assessed to support future seismic hazard evaluations [52]. In the calculation process, a slip distribution model was applied for the source fault, while the receiver fault parameters were set to a strike of 228.34°, a dip of 61.88°, and a rake of 42°. With the earthquake’s centroid depth and main fault slip range from 8 to 18 km, the static Coulomb stress was calculated at depths of 10 km, 15 km, and 20 km, using a Poisson’s ratio of 0.25. The equation is as follows:
Δ σ f = Δ τ + μ ′ Δ σ n
where ∆ σ f represents the Coulomb stress change on the fault; Δ τ represents the change in shear stress along the fault slip direction, derived from the stress change tensor; ∆ σ n indicates the alteration in normal stress; and μ′ is the effective friction coefficient, typically set to 0.4 [53].
The results indicate positive Coulomb failure stress changes at both ends of the seismogenic fault, suggesting that the earthquake transferred stress along the fault’s strike, reaching both the northwest and southeast regions (Figure 9). The 2024 Mw 7.01 Wushi earthquake significantly released accumulated stress on the seismogenic fault, especially in the blue-shaded area at a 10 km depth. Additionally, the near north-south orientation of the fault rupture zone has caused a large stress shadow over a wide area. This indicates that the fault in this region has experienced a decrease in stress, thereby inhibiting fault slip within this area. An in-depth analysis of Coulomb failure stress across three depths reveals that the KKSF, DSXF, Piqiang North Fault Zone (PNF), KTF, sections of the NWSF southeast of the epicenter, parts of the TSF northwest, and portions of the M-SF west of the epicenter are all experiencing stress accumulation. In the northwest section of the seismogenic fault, maximum Coulomb failure stress values are approximately 1.2, 1.0, and 0.7 bar at 10 km, 15 km, and 20 km depths, respectively. In the northeast, stress levels reach around 1.1, 2.1, and 2.8 bar at the same depths. For the southeast, peak values are about 0.6, 0.6, and 0.1 bar at depths of 10 km, 15 km, and 20 km, respectively.

5. Discussion

5.1. Seismogenic Structure of the Mw 7.1 Wushi Earthquake

The mismatch between the fault mapping and the surface deformation reported by InSAR (Figure 3 and Figure 5) warrants further discussion. The boundary between the uplift and subsidence blocks exhibits a rupture geometry with a NE-SW trend, while the mapped fault shows a predominantly ENE-WSW strike. This discrepancy may arise from several factors. First, the fault mapping is based on seismic data, which provide information about the subsurface geometry, whereas the InSAR results are sensitive to surface displacements and may be influenced by near-surface heterogeneities or complex fault zone structures that are not well-resolved at greater depths. Additionally, the difference in strike orientations could be due to variations in the fault slip distribution or local structural complexities that are not fully captured by the mapping process. These factors highlight the need for further refinement of the fault model and the importance of integrating multiple data sources, such as InSAR, seismic, and geological observations, to improve the accuracy of fault geometry interpretations.

5.2. The Triggering Relationship of Aftershock

In Figure 8, it can be observed that aftershocks are mainly concentrated at the edges and adjacent areas of the slip region, while there are fewer aftershocks in the peak slip areas (red zones). This aligns with the general rule that the peak slip areas of the fault during the mainshock release the most stress, significantly reducing the stress in those regions. In contrast, stress redistribution around the edges makes these areas more likely to trigger aftershocks. Aftershocks are primarily concentrated in regions with high slip gradients, where the variation in slip is more pronounced. This may be due to significant local stress redistribution in these areas, resulting in stress concentration and a higher likelihood of rupture.
From the figure, it can be observed that the distribution of aftershocks is not uniform along depth, but rather concentrated at intermediate depths (approximately 10–20 km). This suggests that stronger stress loading or higher residual stress may exist on the fault plane at these depths. In regions with low or negligible slip (dark blue areas), there are still scattered aftershocks. This may be related to the initial stress state or the characteristics of Coulomb stress changes in these areas. Despite low slip, dynamic stress changes induced by the mainshock or fault complexity may still trigger rupture in these regions. The distribution of aftershocks shows a noticeable tilt, consistent with the fault geometry of the mainshock slip. This indicates that aftershocks are primarily controlled by the fault plane of the mainshock and the redistribution of its stress field.
To further understand how stress redistribution affects the distribution of aftershocks, Coulomb stress changes were calculated at depths of 5 km, 10 km, 15 km, 20 km, 25 km, and 30 km, as shown in Figure 10. It can be seen that aftershocks (white dots) are mostly located in the red zones, corresponding to Coulomb stress increase areas. At depths of 5 km, 10 km, 15 km, 20 km, 25 km, and 30 km, the proportions of aftershocks within stress-loading zones are 64%, 71%, 89%, 92%, 96%, and 33%, respectively. This indicates that the stress redistribution caused by the mainshock has triggered fault activity in these areas. A small number of aftershocks are located in the blue zones (stress unloading areas), possibly due to high initial stress in these regions or the complexity of the stress field caused by crustal heterogeneity. The spatial distribution of Coulomb stress changes is closely related to fault geometry, with regions near fault intersections and branches showing larger stress gradients, which are also areas of high aftershock occurrence. In summary, the triggering mechanisms of aftershocks are mainly consistent with Coulomb stress-loading zones, while depth and fault geometry significantly influence their distribution.

6. Conclusions

The Sentinel-1A data are utilized to derive the coseismic surface displacement field. The coseismic slip model of this earthquake is calculated using the coseismic displacement field. Additionally, Coulomb stress changes on faults surrounding the epicenter resulting from this earthquake are calculated, and the regional seismic hazard is assessed. The results of the study are as follows
(1)
The Sentinel-1A coseismic deformation fields for this earthquake, obtained from both ascending and descending tracks, display a nearly elliptical surface uplift pattern. The maximum line-of-sight displacement is approximately 81.1 cm for the ascending track (T056) and 65.7 cm for the descending track (T136).
(2)
The results from the uniform slip model indicate that the fault associated with the 2024 Mw 7.01 Wushi earthquake has a strike angle of 228.34° and a dip of 61.88°. The fault slip distribution results indicate that the primary slip is concentrated between 5 and 25 km depths, reaching a maximum of 3.2 m at 10.2 km. This coseismic slip produced a seismic moment of 3.69 × 101⁹ N·m, equating to a moment magnitude of Mw 7.01. The fault movement combined thrust and left-lateral strike-slip components, suggesting that the seismogenic fault is a secondary structure within the M-SF.
(3)
Based on the analysis of static Coulomb failure stress changes, the 2024 Mw 7.01 Wushi earthquake has increased the future seismic risk in several areas, including the KKSF, DSXF, PNF, KTF, parts of the NWSF southeast of the epicenter, parts of the TSF northwest of the epicenter, and parts of the M-SF west of the epicenter. These active faults require ongoing monitoring for seismic hazards.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/rs16224319/s1, Table S1: Statistics of earthquakes with a magnitude of >6 in the Tianshan area from 1900 to today; Table S2: Difference statistics between surface observations and model forward simulations.

Author Contributions

Conceptualization, Y.D. and X.L.; methodology, Y.D. and J.G.; software, X.D. and G.Y.; validation, Y.Y., G.Y. and X.L.; formal analysis, Y.D.; investigation, X.D. and Y.D.; data curation, Y.D.; writing—original draft preparation, Y.D.; writing—review and editing, Y.D., X.D., X.L. and J.G.; visualization, Y.D. and Y.Y.; supervision, J.G. and G.Y.; project administration, X.L.; funding acquisition, X.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China under Grants 42274006 and 42430101.

Data Availability Statement

The Sentinel-1 SAR images were provided by the European Space Agency (https://browser.dataspace.copernicus.eu/, accessed on 25 March 2024). The fault data come from the National Earthquake Science Data Center (https://data.earthquake.cn/, accessed on 25 March 2024). The SRTM DEM data are obtained from the 30 m resolution shuttle radar topography mission (SRTM) digital elevation model (DEM) provided by the National Aeronautics and Space Administration(NASA) (https://www.earthdata.nasa.gov/about/competitive-programs/measures/new-nasa-digital-elevation-model, accessed on 25 March 2024). ENVI SARscape Software Package: for InSAR processing and deformation analysis. GMT 5.4.5: for map plotting and visualization. GBIS (Geodetic Bayesian Inversion Software): for fault parameter inversion. Coulomb 3.3: for Coulomb stress change calculations. SDM: for coseismic slip distribution inversion.

Acknowledgments

We acknowledge the European Space Agency (ESA) for freely making available the Sentinel-1A data. Most of the figures were plotted with the Generic Mapping Tool (GMT 5.4.5) software provided by Wessel and Smith (1998).

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Major Cenozoic faults and tectonic background of the 2024 Mw 7.01 Wushi earthquake in the Tianshan Belt. White arrows represent the GPS horizontal velocity field; black jagged lines indicate faults; yellow stars mark the locations of earthquakes of magnitude 6 or above since 1900 (Table S1) (USGS: https://earthquake.usgs.gov/earthquakes/, accessed on 23 May 2024); the red star represents the epicenter; the beach ball symbol indicates the focal mechanism solution of this earthquake (USGS, accessed on 23 May 2024); the lower left corner shows a broader area, and the red box highlights the specific study area; and orange circles represent aftershocks. Fault abbreviations are as follows: TSF, Tuoergan Fault; KKSF, Kuokesale Fault; MSF, Maidan-Sayram Fault; NWSF, North Wensu Fault; KF, Keping Fault; YF, Yimugantawu Fault; KTF, Karatake Fault; and DSXF, Dashixia Fault. The fault data come from the National Earthquake Science Data Center (https://data.earthquake.cn/, accessed on 23 May 2024) and the topographic data used are the ETOPO1 Global Relief Model (https://www.ncei.noaa.gov/products/etopo-global-relief-model, accessed on 13 August 2024).
Figure 1. Major Cenozoic faults and tectonic background of the 2024 Mw 7.01 Wushi earthquake in the Tianshan Belt. White arrows represent the GPS horizontal velocity field; black jagged lines indicate faults; yellow stars mark the locations of earthquakes of magnitude 6 or above since 1900 (Table S1) (USGS: https://earthquake.usgs.gov/earthquakes/, accessed on 23 May 2024); the red star represents the epicenter; the beach ball symbol indicates the focal mechanism solution of this earthquake (USGS, accessed on 23 May 2024); the lower left corner shows a broader area, and the red box highlights the specific study area; and orange circles represent aftershocks. Fault abbreviations are as follows: TSF, Tuoergan Fault; KKSF, Kuokesale Fault; MSF, Maidan-Sayram Fault; NWSF, North Wensu Fault; KF, Keping Fault; YF, Yimugantawu Fault; KTF, Karatake Fault; and DSXF, Dashixia Fault. The fault data come from the National Earthquake Science Data Center (https://data.earthquake.cn/, accessed on 23 May 2024) and the topographic data used are the ETOPO1 Global Relief Model (https://www.ncei.noaa.gov/products/etopo-global-relief-model, accessed on 13 August 2024).
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Figure 2. Ground area covered by SAR images utilized for the Mw 7.01 Wushi earthquake analysis. The red star is the epicenter of the Mw 7.01 Wushi earthquake; the beach ball represents the focal mechanism solution (USGS, accessed on 23 May 2024); the black lines are faults.
Figure 2. Ground area covered by SAR images utilized for the Mw 7.01 Wushi earthquake analysis. The red star is the epicenter of the Mw 7.01 Wushi earthquake; the beach ball represents the focal mechanism solution (USGS, accessed on 23 May 2024); the black lines are faults.
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Figure 3. The LOS deformation of InSAR observations; (a–c) represent the LOS deformation results of track 56, track 34, and track 136, respectively. The yellow star marks the earthquake’s epicenter, and the beach ball symbol represents the focal mechanism solution. The black lines are faults.
Figure 3. The LOS deformation of InSAR observations; (a–c) represent the LOS deformation results of track 56, track 34, and track 136, respectively. The yellow star marks the earthquake’s epicenter, and the beach ball symbol represents the focal mechanism solution. The black lines are faults.
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Figure 4. The posterior probability distribution of the fault model parameters for the Mw 7.01 Wushi earthquake. The red line represents the maximum posterior probability solution. Scatter plots are contoured according to frequency (cold colors for low frequency, warm colors for high frequency).
Figure 4. The posterior probability distribution of the fault model parameters for the Mw 7.01 Wushi earthquake. The red line represents the maximum posterior probability solution. Scatter plots are contoured according to frequency (cold colors for low frequency, warm colors for high frequency).
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Figure 5. Observed Coseismic Interferograms, Modeled Interferograms of the 2024 Mw 7.01 Wushi Earthquake, and the Residuals After Subtracting the Modeled Deformation from the Observed Interferograms: (a–c) for Track 56, (d–f) for Track 34, and (g–i) for Track 136. The black lines represent faults. The red star indicates the epicenter.
Figure 5. Observed Coseismic Interferograms, Modeled Interferograms of the 2024 Mw 7.01 Wushi Earthquake, and the Residuals After Subtracting the Modeled Deformation from the Observed Interferograms: (a–c) for Track 56, (d–f) for Track 34, and (g–i) for Track 136. The black lines represent faults. The red star indicates the epicenter.
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Figure 6. Trade-off curve showing the balance between slip model roughness and data fit, with the red dot marking the optimal slip factor.
Figure 6. Trade-off curve showing the balance between slip model roughness and data fit, with the red dot marking the optimal slip factor.
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Figure 7. Coseismic slip distribution for the seismogenic fault of the Mw 7.01 Wushi earthquake. Arrows are slip vectors as obtained from the inversion.
Figure 7. Coseismic slip distribution for the seismogenic fault of the Mw 7.01 Wushi earthquake. Arrows are slip vectors as obtained from the inversion.
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Figure 8. The 3D Coseismic slip distribution for the seismogenic fault of the Mw 7.01 Wushi earthquake. The black dots represent aftershocks.
Figure 8. The 3D Coseismic slip distribution for the seismogenic fault of the Mw 7.01 Wushi earthquake. The black dots represent aftershocks.
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Figure 9. Static ΔCFS in neighboring regions induced by the 2024 Mw 7.01 Wushi earthquake. The black lines are the faults, the red beach ball is the focal mechanism solution, and the yellow five-pointed star is the epicenter.
Figure 9. Static ΔCFS in neighboring regions induced by the 2024 Mw 7.01 Wushi earthquake. The black lines are the faults, the red beach ball is the focal mechanism solution, and the yellow five-pointed star is the epicenter.
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Figure 10. Static ΔCFS and aftershock distribution in neighboring regions induced by the 2024 Mw 7.01 Wushi earthquake. The black lines are the faults, the red beach ball is the focal mechanism solution, and the yellow five-pointed star is the epicenter. White dots are aftershocks.
Figure 10. Static ΔCFS and aftershock distribution in neighboring regions induced by the 2024 Mw 7.01 Wushi earthquake. The black lines are the faults, the red beach ball is the focal mechanism solution, and the yellow five-pointed star is the epicenter. White dots are aftershocks.
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Table 1. Sentinel-1A data parameters.
Table 1. Sentinel-1A data parameters.
OrbitTrackMasterSlaveImaging ModePolarization ModeMaximum Surface Displacement (cm)Angle of Incidence (rad)Azimuth (rad)
AscendT0562024-01-142024-01-26IWVV81.139.7576.35
DescendT1362024-01-202024-02-25IWVV65.740.97283.61
T0342024-01-132024-01-25IWVV50.339.75283.65
Table 3. The CRUST 1.0 subsurface layered medium model parameters.
Table 3. The CRUST 1.0 subsurface layered medium model parameters.
LayerDepth (km)Vp (km·s−1)Vs (km·s−1)Density (kg·m−3)
10.006.103.552740
219.736.303.652780
340.327.003.992950
449.308.084.493330
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Ding, Y.; Liu, X.; Dai, X.; Yin, G.; Yang, Y.; Guo, J. D-InSAR-Based Analysis of Slip Distribution and Coulomb Stress Implications from the 2024 Mw 7.01 Wushi Earthquake. Remote Sens. 2024, 16, 4319. https://doi.org/10.3390/rs16224319

AMA Style

Ding Y, Liu X, Dai X, Yin G, Yang Y, Guo J. D-InSAR-Based Analysis of Slip Distribution and Coulomb Stress Implications from the 2024 Mw 7.01 Wushi Earthquake. Remote Sensing. 2024; 16(22):4319. https://doi.org/10.3390/rs16224319

Chicago/Turabian Style

Ding, Yurong, Xin Liu, Xiaofeng Dai, Gaoying Yin, Yang Yang, and Jinyun Guo. 2024. "D-InSAR-Based Analysis of Slip Distribution and Coulomb Stress Implications from the 2024 Mw 7.01 Wushi Earthquake" Remote Sensing 16, no. 22: 4319. https://doi.org/10.3390/rs16224319

APA Style

Ding, Y., Liu, X., Dai, X., Yin, G., Yang, Y., & Guo, J. (2024). D-InSAR-Based Analysis of Slip Distribution and Coulomb Stress Implications from the 2024 Mw 7.01 Wushi Earthquake. Remote Sensing, 16(22), 4319. https://doi.org/10.3390/rs16224319

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