Fault Kinematics of the 2022 Delingha Mw 5.6 and Mw 5.7 Earthquakes Revealed by InSAR Observations

Abstract

Between January and April 2022, three moderate earthquakes (Mw 5.6 on 23 January, Mw 5.7 on 25 March, and Mw 5.1 on 15 April) struck the Hala Lake area of Delingha, Qinghai, China. Their seismogenic faults are poorly mapped, resulting in an unclear understanding of their kinematics and regional seismotectonics. In this study, we employed Interferometric Synthetic Aperture Radar (InSAR) observations to reconstruct the coseismic deformation fields of the Mw 5.6 and 5.7 events. We then utilized a Bayesian inversion algorithm to delineate the fault geometries of the two events, and further resolved their coseismic fault slip. Our results reveal that these earthquakes ruptured different fault planes: the fault plane of the Mw 5.6 event dips westward at an angle of 60°, while the Mw 5.7 event ruptured as a nearly vertical fault with a dipping angle of 89°. The finite-fault slip inversions further demonstrate that the coseismic rupture of the Mw 5.6 event was predominantly concentrated between depths of 2 km and 7 km, with a maximum slip of 0.18 m; in contrast, the Mw 5.7 event was mainly concentrated between depths of 2 km and 9 km, with a maximum slip of 0.4 m. We calculated the coseismic Coulomb failure stress change (ΔCFS) induced by these two earthquakes. Integrating the analysis of ΔCFS and the spatial distribution of aftershocks, we argue that the sequence earthquakes were triggered by the proceeding earthquakes.

1. Introduction

On 23 January 2022, a moderate earthquake (moment magnitude [Mw] 5.6) struck Delingha City in Haixi Mongolian and Tibetan Autonomous Prefecture, Qinghai Province. Following the earthquake, a Mw 5.7 earthquake on 25 March and a Mw 5.1 earthquake on 15 April affected the same region. These moderate-magnitude events are referred to as the 2022 Delingha earthquake sequence.

Situated on the northeastern margin of the Tibetan Plateau, this region is significantly influenced by the ongoing collision between the Indian Plate and the Eurasian Plate, leading to active crustal movements and frequent earthquakes along multiple thrust and strike-slip faults (Figure 1). The Qilian–Haiyuan fault system, extending approximately 900 km in a northwest–southeast direction, comprises the thrust-dominant Qilian fault and the left-lateral Haiyuan fault. These faults are located at the intersection of the Qinghai, Alashan, and Ordos blocks. Modern geodetic data, including the Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR), reveal a gradual increase and subsequent decrease in slip rates along this fault system from west to east [1,2]. In the central Qilian Mountains, where elevations exceed 3500 m, thrust deformation is minimal. Additionally, the presence of discontinuities and low-relief terrain around the epicenter suggests that this area may serve as a transitional zone within a complex tectonic environment [3].

The seismic activity in the Qinghai area, which hosts large-scale strike-slip faults, exhibits periodic cycles of activity and quiescence. The region accumulates energy for M~6 earthquakes every two to four years [4,5,6,7] and M~7 earthquakes every ten years [8,9]. Despite a relatively quiet period of seismic activity in recent years, medium–large earthquakes, including the M 6.4 Delingha earthquake on 17 April 2003, the M 5.9 Menyuan earthquake on 21 January 2016, and the M 6.6 Menyuan earthquake on 8 January 2022, have occurred, indicating a possible spatial and temporal correlation. During the period from January to April 2022, three moderate-magnitude right-lateral strike-slip earthquakes occurred in Delingha, with epicenters within the 2022 earthquake hazard area for the Qilian–Sunan region of Qinghai [10], highlighting the region’s high seismic activity rate.

The distribution of seismic risk is not confined to regions of frequent earthquake activity along plate boundaries; areas with tectonic faults but moderate seismic activity may exhibit seismic risk. Studying the Delingha seismic sequence may contribute to refining our understanding of the internal deformation of the northeastern Tibetan Plateau. Research into coseismic surface deformation and its spatial distribution characteristics is crucial for understanding the rupture behavior of crustal faults [10]. It also serves as an essential basis for seismic defense of various important infrastructures in areas of tectonic activity. Additionally, investigating coseismic slip distribution is important for understanding seismic activity, assessing seismic risks, and predicting future events. While previous studies revealed the fault kinematics of the 2022 Delingha earthquake sequence using seismological and geodetic observations [11,12,13], the fault kinematics of these studies, however, are inconsistent. This discrepancy calls for further analysis of the fault kinematics related to these earthquakes.

Here, we use InSAR observations to extract the coseismic displacements of the Mw 5.6 and 5.7 earthquakes. Due to the relatively small magnitude of the Mw 5.1 earthquake, InSAR observation did not capture its surface deformation. Using a nonlinear Bayesian algorithm based on a homogeneous elastic model, we determined the optimal fault geometries of these two earthquakes. To delineate the rupture kinematics in detail, we inverted the InSAR data for finite-fault slips of these two earthquakes. We calculated the coseismic coulomb stress perturbations between different events and, in conjunction with relocated aftershock data, explored possible interconnection between them. Our results show that the Mw 5.6 and Mw 5.7 earthquakes were segmented ruptures, and the preceding event might have triggered the subsequent events.

2. InSAR Data and Processing

We used InSAR Scientific Computing Environment (ISCE) software (Version 2.3) [14] to analyze Sentinel-1 SAR data from tracks 99 (ascending) and 4 (descending), enabling us to extract coseismic deformation from the 2022 Delingha earthquake sequence by integrating LOS measurements from D-InSAR (Table 1). We utilized precise orbit data to correct for orbital errors in the interferograms. The 1 arc-second SRTM DEM was employed to decrease the contribution of the topographic phase in the interferograms. We generated multi-looking algorithms (20 in azimuth and 5 in range) and created a phase adaptive filter for interferograms [15]. We used SNAPHU, a statistical minimum cost-flow approach, for phase unwrapping to remove potential residual orbital ramps [16]. To further improve the coseismic deformation fields, we applied linear regression to detrend a ramp across all interferograms, which helps reduce noise from atmospheric perturbations and orbital inaccuracies [17].

Figure 2b,d depict the InSAR coseismic deformation fields for the Mw 5.6 earthquake in ascending and descending tracks, respectively. The deformation fields exhibit minor but continuous and smooth deformation in the epicentral region, generally trending NNE-SSW. In the ascending track, significant deformation is observed on the northeast side of the fault, predominantly characterized by uplift, whereas the deformation on the southwest side is relatively subdued. The maximum uplift in the ascending track is 2.67 cm, and the maximum subsidence is 1.98 cm. The descending track shows less pronounced overall deformation compared to the ascending track, with a maximum uplift of 1.52 cm and a maximum subsidence of 1.47 cm.

Figure 2f,h illustrate the InSAR coseismic deformation fields for the Mw 5.7 earthquake, with the ascending track showing maximum uplift and subsidence values of 0.64 cm and 2.61 cm, respectively, and the descending track displaying maximum uplift and subsidence values of 1.53 cm and 1.99 cm, respectively. Comparing the ascending and descending track deformation fields reveals: (1) both exhibit continuous and smooth deformation in the epicentral region, trending NNE–SSW, indicating that the seismogenic fault did not reach the surface; (2) the regions of significant subsidence (uplift) along the line of sight in both ascending and descending track deformation fields are spatially opposite, suggesting the primarily strike-slip motion of the fault.

3. Determine Fault Geometric Parameters

Fault geometry is crucial for the initiation, propagation, and termination of earthquake ruptures [18]. However, obtaining fault geometries is difficult for buried earthquakes. Here, we use surface displacements to explore the seismogenic geometry of the 2022 Delingha earthquakes.

We use the Geodetic Bayesian Inversion Software (GBIS, Version 1.1), which employs a Markov chain Monte Carlo algorithm to perform geometric inversion of fault parameters [19,20]. This approach is suited for addressing the probability distributions associated with complex fault geometries, facilitating the estimation of posterior probability distributions for various source parameters. With known prior information and the likelihood function, we can obtain the optimal solution and the posterior probability density distribution of the fault parameters.

Due to the large amount of InSAR data, it is impractical to extract all data for the inversion. Here, the Quadtree sampling is used to downsample the ascending and descending track data. The retained data for both ascending and descending track InSAR coseismic deformation fields are around 2000, with denser data in the epicentral area and fewer data in the far field.

The uniform elastic half-space rectangular model [21,22] is adopted, and the initial fault parameters are set according to the focal mechanism solution parameters (Table 2). For both earthquakes, a Bayesian search is performed with 200,000 iterations, which ensures sufficient samples to obtain the mean values and error intervals of the fault geometric parameters (Figure 3). The dip and strike of the Mw 5.6 earthquake are estimated to be −60° and 350°, respectively, and they are −89° and 179° for the Mw 5.7 earthquake. These results show that the seismogenic faults have different dip angles, ruling out the possibility of two events on the same fault.

4. Finite-Fault Slip Modeling

Under the assumption of a homogeneous elastic medium [20,21], we utilized the the Steepest Descent Method (SDM) [23] to acquire the distributed slip results for the Mw 5.6 and Mw 5.7 earthquakes. The relationship between coseismic inversion surface displacement and fault unit slip is linear [21], and the optimal fault slip inversion results were obtained through a least-squares iteration that minimizes error under preconditions [23]. To achieve more reasonable fault slip inversion results and to avoid an excessive number of singular points in the results, in addition to prior constraints, fault slip inversion typically includes a smoothness constraint on fault slip or stress drop, which represents a trade-off between the degree of data fit and the roughness of fault slip. The smoothing factor is determined based on data misfit and roughness curves [24]. The optimal smoothing factors for the Mw 5.6 and Mw 5.7 earthquakes were determined to be 0.06 and 0.04 (Figure 4), respectively.

We extend the fault length and width according to the geometric parameters obtained above and discretize the faults into 1 km by 1 km patches. Figure 5 shows the InSAR observations, model predictions, and residuals. The fitting between observed and modeled data for the Mw 5.6 and Mw 5.7 earthquakes were 98% and 97%, respectively, suggesting the model could reasonably explain the data.

Figure 6 shows the finite-fault slip distribution of the 2022 Delingha earthquake sequence. Figure 6a shows that the Mw 5.6 earthquake fault rupture was concentrated along the strike between 2–7 km depth, with minimal slip at the 8 km depth along the dip direction. The average slip angle was −174°, with an average slip of 0.05 m, indicating that the coseismic fault was a nearly pure right-lateral strike-slip fault with minor dip movement. The Mw 5.7 earthquake fault rupture was concentrated along the strike between 2–9 km depth (Figure 6b), with an average slip angle of −10°, an average slip of 0.05 m, and a magnitude of Mw 6.0, indicating that the fault was a westward-dipping, nearly vertical strike-slip fault. Our inversions indicate that both earthquakes were right-lateral strike-slip events. Figure 6c reveals that the coseismic slip of the Mw 5.6 earthquake terminates before the junction of the two seismogenic faults, at a depth of approximately 2 km. We propose that the intersection of the seismogenic fault may have prevented the Mw 5.7 earthquake from rupturing at the surface.

5. Discussions

5.1. Complementary Relationship Between Coseismic Fault Slip and Aftershock Distribution

We collected the relocated aftershock data of the 2022 Delingha earthquake sequence processed with the HypoDD method by Li et al. [11]. Using these aftershocks, we first analyze the rationality of the fault geometry and then analyze the complementary relationship between coseismic slip and aftershocks.

Figure 7 illustrates the spatiotemporal evolution of aftershocks within 50 days of the Mw 5.6 earthquake and 80 days after the Mw 5.7 earthquake. We made three cross-fault profiles for each earthquake. Cross-sectional views reveal that the aftershocks of the Mw 5.6 earthquake predominantly exhibit a westward-dipping distribution with a central vertical trend (Figure 7c–e), whereas those of the Mw 5.7 earthquake show a predominantly vertical distribution, interspersed with vertically and westward-dipping aftershocks (Figure 7f–h). These observations supported the results obtained using the Bayesian algorithm: the Mw 5.6 earthquake had a dip and strike of −60° and 350°, respectively; the Mw 5.7 earthquake had a dip and strike of −89° and 179°, respectively.

Figure 8 shows the distribution of coseismic slip with aftershocks. It is evident that most of the aftershocks are distributed along the edges of the coseismic rupture zone [25,26], suggesting a complementary relationship, which aligns with previous research. Moreover, we note that both epicenters were located on the edge of the main slip, suggesting possible unilateral ruptures of these two earthquakes. However, given that uncertainties may exist for epicenter location and the limited rupture regions of these two earthquakes, more observational evidence is needed to investigate this inference.

5.2. Stress Triggering Among the Earthquake Sequence

The release of stress due to earthquakes can influence the calculation of slip budget and may potentially trigger large earthquakes [27,28] or halt the rupture process [29]. The coseismic slip can alter the stress state of surrounding faults or adjacent areas, leading to changes in Coulomb stress [30]. Therefore, analyzing the coseismic stress is crucial for investigating the potential triggering relationship between strong earthquakes. The Coulomb failure stress change (ΔCFS) is defined as $\Delta \mathrm{C}\mathrm{F}\mathrm{S}=\Delta \mathsf{\tau }-\mathsf{\mu }\Delta {\mathsf{\sigma }}_{\mathrm{n}}$, where $\Delta \mathrm{C}\mathrm{F}\mathrm{S}=\Delta \mathsf{\tau }-\mathsf{\mu }\Delta {\mathsf{\sigma }}_{\mathrm{n}}\Delta \tau$ is the change in shear stress on the receiver fault, $\Delta {\mathsf{\sigma }}_{\mathrm{n}}$ is the change in normal stress (positive for tension), and µ is the coefficient of friction. Here, we utilized Coulomb 3.3 to calculate the ΔCFS induced by these earthquakes at depths of 4.8 km, 6.4 km, and 10.8 km. The coefficient of friction (μ′) was set to 0.4 [31,32]. The strike/dip/rake of the fault for the Mw 5.6 and Mw 5.7 earthquakes were set to 347°/121°/−171° and 357°/90°/−10°, respectively.

Figure 9 shows the ΔCFS calculation results. Coulomb stress analysis indicates that the Mw 5.6 earthquake exerted a stress-loading effect on the Mw 5.7 earthquake (Figure 9), as the increased Coulomb stress exceeded the typical threshold for earthquake triggering (approximately 0.01 MPa) [33], while its effect on the stress-loading of the subsequent event was relatively minor. Given that the epicenter of the third earthquake is situated at the boundary between positive and negative Coulomb stress, it is challenging to ascertain the stress-loading impact of the second earthquake on the third mainshock with precision. However, considering the overall trend of increasing compressive stress at depth in the April Mw 5.1 earthquake region, we suggest that the Mw 5.7 earthquake may have had a certain loading effect on the Mw 5.1 earthquake in April.

The Mw 5.6 earthquake exerted a slight stress-loading effect on segments of the Danghe Nanshan Fault and Halahu Fault, whereas the Mw 5.7 earthquake did not induce significant stress-loading on these faults. While the region of positive coseismic Coulomb stress change is relatively small, suggesting minimal stress loading, the possibility of intermediate-sized events on these faults could not be ignored.

6. Conclusions

Using Sentinel-1 InSAR data from ascending and descending tracks, we analyzed coseismic deformation fields for the Mw 5.6 and Mw 5.7 earthquakes in the 2022 Delingha sequence. This work identified west-dipping, right-lateral faults with dip angles of 59° and 89°, respectively, as the seismogenic structures. The Mw 5.6 earthquake slip was concentrated between depths of 2–7 km, peaking at 0.18 m at 4.7 km, while the Mw 5.7 earthquake slip ranged from 2–9 km, with a maximum of 0.4 m at 5.5 km. The Mw 5.6 earthquake likely influenced the Mw 5.7 event through stress-loading, with some impact on the following April Mw 5.1 earthquake. Coulomb stress analysis suggests that the Mw 5.7 earthquake may have contributed to the April event. Our study not only improves understanding of the fault structures, seismic hazards, and stress-triggering effects in the Delingha region but also offers insights for earthquake prediction and disaster prevention in the region.

Author Contributions

All the authors participated in editing and reviewing the manuscript. Conceptualization, X.H., D.W. and C.L.; methodology, X.W. and X.H.; validation, X.H., D.W. and C.L.; formal analysis, X.W. and Y.B.; data curation, X.W., X.H. and L.L.; writing—original draft preparation, X.W.; writing—review and editing, X.W., X.H., C.L. and L.L.; visualization, X.H.; supervision, C.L.; project administration, X.H.; funding acquisition, L.L. and C.L. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author.

Acknowledgments

The Sentinel-1 SAR data were freely provided by the Alaska Satellite Facility (https://search.asf.alaska.edu, accessed on 11 November 2024). All figures in this paper were generated using the Generic Mapping Tools software (version 6) [34]. The authors are grateful to Yanchuan Li and Xinjian Shan for their helpful discussions.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

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Figures and Tables

Figure 1. Seismogenic setting around the Delingha earthquake sequence. (a) The red triangle denotes the epicenters of the three main earthquakes. The blue rectangle indicates the location of Figure (b), and the gray-dotted rectangle represents the InSAR image convergences. DHNSF: Danghe Nanshan Fault; ELSF: Elashan Fault; QIL-HYF: Qilian–Haiyuan Fault; SN-QLF: Sunan–Qilian Fault; HLHF: Halahu Fault; HLHNSF: Halahu Nanshan Fault. (b) Red, green, and blue beach balls represent the three earthquakes, and the blue dots represent earthquakes with magnitude M3~M5 occurring nearby from 2010 to 2020 (USGS).

Figure 2. Coseismic interferograms and deformation maps for the 2022 Mw 5.6 and Mw 5.7 earthquakes. Red and blue beach balls represent the Mw 5.6 earthquake on 23 January 2022, and the Mw 5.7 earthquake on 25 March 2022, respectively. (a,c) are the interference diagrams of the ascending and descending orbits for the Mw 5.6 earthquake. (b,d) are the deformation diagram of the ascending and descending orbits for the Mw 5.6 earthquake. (e,g) are the interference diagram of the ascending and descending orbits for the Mw 5.7 earthquake. (f,h) are the deformation diagram of the ascent and descent orbits for the Mw 5.7 earthquake.

Figure 3. Fault geometric parameters for the Mw 5.6 and Mw 5.7 earthquakes. Strike and dip of fault planes for the Mw 5.6 and Mw 5.7 earthquakes. (a,b) are the strike and dip of fault planes, along with their marginal posterior probability distributions for the Mw 5.6 earthquake. (c,d) are the strike and dip of fault planes, along with their marginal posterior probability distributions for the Mw 5.7 earthquake.

Figure 4. Trade-off curves for the Mw 5.6 and Mw 5.7 earthquakes. (a) Smoothing factor test for the Mw 5.6 earthquake; (b) smoothing factor test for the Mw 5.7 earthquake. The red dot is the preferred smoothing factor.

Figure 5. Inversion of ascending and descending track data for the Mw 5.6 and Mw 5.7 earthquakes. The large, dashed rectangle represents the extent of the uniform-slip fault plane, with the solid line indicating the side of the fault closest to the surface. The smaller dashed rectangle shows the primary extent of the uniform-slip fault plane. (a–c) are the observed, modeled, and residual values for the ascending track of the Mw 5.6 earthquake. (d–f) are the observed, modeled, and residual values for the descending track of the Mw 5.6 earthquake. (g–i) are the observed, modeled, and residual values for the ascending track of the Mw 5.7 earthquake. (j–l) are the observed, modeled, and residual values for the descending track of the Mw 5.7 earthquake.

Figure 6. Three−dimensional slip distribution of the Mw 5.6 and Mw 5.7 earthquakes from InSAR inversion. (a,b) show the InSAR inverted separate views of the three-dimensional slip distribution for the Mw 5.6 and Mw 5.7 earthquakes. (c) presents the InSAR inverted three-dimensional slip distribution for both the Mw 5.6 and Mw 5.7 earthquakes.

Figure 7. Aftershocks and cross-fault profiles. (a,b) The distribution of relocated aftershocks for the Mw 5.6 and Mw 5.7 earthquakes. The dashed lines represent the cross-section locations. The red pentagram represents the Mw 5.6 earthquake; the blue pentagram represents the Mw 5.7 earthquake. (c–e) display the cross-sectional aftershock relocations for the Mw 5.6 earthquake. (f–h) show the relocations for the Mw 5.7 earthquake. The dashed lines indicate the dip angles determined by the Bayesian algorithm.

Figure 8. Coseismic slip and aftershock distribution. (a) Slip on the fault for the Mw 5.6 earthquake. (b) Slip on the fault for the Mw 5.7 earthquake. Black arrows indicate the direction of the slip. (a) shows a blue pentagram representing the Mw 5.6 earthquake, with other blue circles indicating the distribution of its aftershocks; (b) shows a blue pentagram representing the Mw 5.7 earthquake, with other blue circles indicating the distribution of its aftershocks.

Figure 9. Coulomb stress variation of Mw 5.6 and Mw 5.7 earthquakes. (a–c) represent Mw 5.6 earthquake stress variations at the depths of the three main earthquakes (4.8 km, 6.4 km, and 10.8 km), respectively. (d–f) represent Mw 5.7 earthquake stress variations at the depths of the three main earthquakes (4.8 km, 6.4 km, and 10.8 km), respectively. Red, green, and blue beach balls represent the three earthquakes.

Table 1

Sentinel-1A data utilized in this study.

23 January 2022 Mw 5.6
Satellite	Track	Reference Date	Secondary Date	Mean Inc.Angle	Mean Azi.Angle
Sentinel-1A	T99A	15 January 2022	27 January 2022	37.7911°	−10.243°
Sentinel-1A	T4D	20 January 2022	1 February 2022	38.0727°	190.2117°
25 March 2022 Mw 5.7
Satellite	Track	Reference Date	Secondary Date	Mean Inc.Angle	Mean Azi.Angle
Sentinel-1A	T99A	16 March 2022	8 March 2022	37.7911°	−10.243°
Sentinel-1A	T4D	21 March 2022	2 April 2022	38.0727°	190.2117°

Table 2

Bayesian search parameter settings for Mw 5.6 and Mw 5.7 earthquakes.

The Mw 5.6 Earthquake on 23 January 2022
	Length (km)	Width (km)	Strike (°)	Dip (°)	Slip (°)
Start Value	7	5	329	−80	0.00
Range	0–20	0–20	320–360	−90–0	−0.2–0.2
The Mw 5.7 Earthquake on 25 March 2022
	Length (km)	Width (km)	Strike (°)	Dip (°)	Slip (°)
Start Value	12	5	345	−60	0.00
Range	0–20	0–20	300–360	−90–90	−0.2–0.2

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