Conjugate ruptures and seismotectonic implications of the 2019 Mindanao earthquake sequence inferred from Sentinel-1 InSAR data

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Int J Appl Earth Obs Geoinformation

journal homepage:www.elsevier.com/locate/jag

Conjugate ruptures and seismotectonic implications of the 2019 Mindanao earthquake sequence inferred from Sentinel-1 InSAR data

Bingquan Li, Yongsheng Li*, Wenliang Jiang, Zhe Su, Wenhao Shen

Institute of Crustal Dynamics, China Earthquake Administration, Beijing 100085, China

A R T I C L E I N F O

Keywords:

Mindanao earthquake sequence InSAR

Coulomb stress change Conjugate fault

A B S T R A C T

In 2019, four strong earthquakes of Mw > 6.4 occurred successively in Mindanao, Philippines. Based on the reports from the USGS and PHIVOLCS, these earthquakes were dominated by strike-slip ruptures. Whether these earthquakes are temporally and spatially related remained unknown. We characterized the coseismic dis- placementﬁelds during the earthquake sequence using an InSAR technique with Sentinel-1 SAR data. The InSAR deformation measurements convincingly reveal that the four earthquakes produced distinct coseismic displacement patterns. We estimated the source parameters of the earthquakes with a two-step inversion strategy.

The optimal model suggests that the earthquake sequence resulted from the reactivation of a conjugate fault structure that involves two nearly vertical left-lateral strike-slip faults and two high-angle right-lateral strike-slip faults. We calculated Coulomb stress changes from the earthquake sequence, suggesting that the previous strong earthquakes had signiﬁcant stress-encouraging eﬀects on the following events. The regional velocities based on the GPS analysis suggest that the formation of this conjugate structure is mainly due to the westward movement of the subducting Philippine Sea Plate. This earthquake sequence provides a seismotectonic background for subsequent strong earthquakes and helps to better understand the formation mechanisms and seismotectonic implications of conjugate structure rupturing.

1. Introduction

Four strong earthquakes (Mw > 6.4) occurred in sequence in Mindanao, Philippines in 2019. The Mindanao earthquake sequence was initiated on 16 Oct. 2019 with a magnitude of 6.4 (hereafter referred to as’ EQ1’). The Philippine Institute of Volcanology and Seismology (PHIVOLCS) reported that theﬁrst hypocenter was located at a depth of 14.1 km and located in Tulunan, 22 km southeast of Cotabato (https://www.phivolcs.dost.gov.ph). PHIVOLCS suggested that this quake was the result of a left-lateral strike-slip rupture in the NW-SE direction. The second quake (hereafter referred to as ‘EQ2’) struck to the northeast of EQ1 on 29 Oct. 2019 with a magnitude of 6.6.

The United States Geological Survey (USGS) reported that this quake, whose hypocenter was at a depth of 15 km, was caused by a strike-slip fault diﬀerent from that corresponding to the EQ1 event (https://

earthquake.usgs.gov/earthquakes/). The third earthquake (hereafter referred to as‘EQ3’) occurred on 31 Oct. 2019 with a magnitude of 6.5 and a hypocentral depth of 10 km. On 15 Dec. 2019, a Mw 6.8 strike- slip earthquake (hereafter referred to as‘EQ4’) ruptured along a fault that extended from the EQ1 event. The USGS reported that the following events were not only just aftershocks of EQ1 but also connected.

The PHIVOLCS recorded thousands of aftershocks from these earthquakes (Fig. 1), and three large earthquakes with similar magnitudes occurred sequentially in this area in the following two months.

The effect of thefirst shocks on their aftershocks became a matter of general concern (Lin and Stein, 2004;Toda et al., 2005,1998;Toda and Stein, 2002). The relationship between these four successive earthquakes is still unknown, and the triggering effects of the previous earthquakes on the subsequent events require additional research. In this paper, InSAR technology and Sentinel-1 images are used to calcu- late the coseismic deformationfields caused by the four earthquakes.

Through the inversion of the source parameters of the ruptured faults and analysis of the stress state of this area, the internal relations among these four earthquakes are further analyzed. The Mindanao earthquake sequence provides a unique opportunity to reveal the local fault structures and mechanism properties, characterize the geometrical complexity of dynamic ruptures and better understand the tectonic implication of these events.

This paper is organized as follows. (1) The coseismic deformation maps of the four earthquakes that occurred in Mindanao are mapped from InSAR data. (2) The best-ﬁt source parameters for the four large earthquakes are determined, and the eﬀects of the Coulomb stress

https://doi.org/10.1016/j.jag.2020.102127

Received 2 January 2020; Received in revised form 29 March 2020; Accepted 8 April 2020

⁎Corresponding author.

E-mail address:[email protected](Y. Li).

Available online 18 April 2020

T

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changes of the previous earthquakes on subsequent events are explored.

(3) The implications of the conjugate structure formation by the seismogenic faults are discussed.

2. Tectonic and seismological background

The Philippines islands were formed in evolutionary processes in- volving subductions, collisions, and strike-slip faulting (Barrier et al., 1991). Earthquakes are frequent there as a result of collision processes between the Philippine Sea Plate (PSP) and the Sunda Plate (SP). The slip convergence between PSP and the SP boundary is obliquely accommodated by the Philippine fault system, which is a major left-lateral strike-slip fault system (Fig. 1) (Smoczyk et al., 2013;Zheng et al., 2013). The Philippine fault has been slipping at a rate of 33 ± 11 mm/

yr in the northern and central Leyte sections (Fukushima et al., 2019).

The southern part of the Philippine fault (Fig. 1) is mainly located in eastern Mindanao and constitutes a complex fault system with discrete strands and splays (Braxton, 2007). Mindanao island is located on the complex collision boundary between the SP and the PSP. Some parts of the convergence between these plates are consumed by the Philippine fault and subduction at the Cotabato trench (Fig. 1). Some other parts of the convergence are accommodated by the fault system in Mindanao, and a series of strike-slip faults have developed (Hammarstrom et al., 2014). The Mindanao earthquake sequence occurred in a region within a faulting zone known as the Cotabato fault system, which is a

seismically active region due to the presence of several active faults, including the NW-SE trending Makilala-Malungon, M'lang, North and South Columbio and Tangbulan faults, and the SW-NE trending Maki- lala and Balabag faults (Fig.1). These faults may work with subduction zones to accommodate diﬀerent components of regional tectonic strain in the slip partitioning system caused by the relative motion between the PSP and SP. Characterizing the geometrical complexity of these source faults has great signiﬁcance for understanding the seismotectonic implications of the large earthquakes occurring in the Mindanao regions.

3. InSAR deformation 3.1. Data and methods

Six Sentinel-1 images from descending track 163 and six images from ascending track 69 were received to capture the deformation signals of these earthquakes (Fig. 1). The ascending track 69 and descending track 163 images were acquired at 17:55 and 05:25 (Local Time), respectively. The details of the Sentinel-1 SAR data used in this study can be found inTable 1. Six coseismic interferograms were produced to cover these four earthquakes from the ascending and descending tracks. The interferometric pairs spanning from 14 Oct. and 26 Oct. (hereafter referred to as‘Inf_0’and‘Inf_1’, respectively) cover the first earthquake that occurred on 16 Oct. (EQ1). The ascending and Fig. 1.The regional map shows the locations of the aftershocks and regional tectonics settings. The black lines represent active faults (Pubellier et al., 1999;Smoczyk et al., 2013;Wu et al., 2017), and the lines with triangles indicate trenches. The dotted boxes represent the coverage of the Sentinel-1 images. The red stars represent the locations of the four large shocks (Mw > 6.4) recorded by the USGS and PHIVOLCS. The yellow points indicate the aftershocks following thefirst event (PHIVOLCS). The arrows represent the relative plate motion between the Philippine Sea Plate (PSP) and Sunda Plate (SP) near Mindanao Island (Smoczyk et al., 2013). F1–F5 are a series of secondary faults of the Cotabato fault system (https://hazardhunter.georisk.gov.ph/). (For interpretation of the references to colour in thisfigure legend, the reader is referred to the web version of this article).

B. Li, et al. Int J Appl Earth Obs Geoinformation 90 (2020) 102127

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descending interferograms from 26 Oct. and 07 Nov. (hereafter referred to as‘Inf_2’and‘Inf_3’, respectively) can cover the coseismic cumulative deformationﬁelds of the second and third earthquakes that occurred on 29 Oct. (EQ2) and 31 Oct. (EQ3), respectively. The deformationﬁelds derived from the 15 Dec. earthquake (EQ4) can be obtained by the interferometry pair from 13 Dec. and 19 Dec. images from the descending track (hereafter referred to as‘Inf_4’) and 13 Dec. and 25 Dec.

images from the ascending track (hereafter referred to as‘Inf_5’). The InSAR Scientiﬁc Computing Environment (ISCE) was used to process SAR images of the Sentinel-1 Terrain Observation Progressive Scans (TOPS) model (Rosen et al., 2018,2012). The Goldsteinﬁlter algorithm was employed to reduce the phase noise (Goldstein and Werner, 1998).

A 30 m Digital Elevation Model (DEM) from the Shuttle Radar Topo- graphy Mission (SRTM)was used to correct the topographic contribu- tions (Farr et al., 2007). The SNAPHU was used to unwrap theﬁltered interferograms (Chen and Zebker, 2000), and the line-of-sight (LOS) displacement maps were then obtained.

3.2. Coseismic deformation of the 16 Oct. event

The coseismic deformation signals in the Inf_0 are not obvious (Fig.

S1a), and the interferogram may be greatly affected by the turbulent atmospheric disturbances. Although Generic Atmospheric Correction Online Service (GACOS) data were used to correct the atmospheric disturbances (Fig. S1b) (Yu et al., 2018b,2018a,2017), the corrected result still shows considerable noise (Fig. S1c). Thus, it was not used in the following inversions because it was too noisy to constrain the solution. The turbulent atmospheric is always changing, and the atmospheric environment is completely different within a few hours (Hanssen, 2001). Application of atmospheric correction techniques does not always guarantee a clean tectonic signal. Thus, the atmospheric corrections are still an open issue that should always be tackled with caution. The Inf_1 was less affected by the turbulent atmosphere (Fig. 2a) and selected for the inversion constraints. After GACOS

atmospheric correction, the overall accuracy improvement is limited (Fig. S2). Thus, this interferogram does not require atmospheric correction. The strike of EQ1reported from the USGS and PHIVOLCS is approximately parallel to the LOS direction of the descending track of Sentinel-1. The fault is not exposed at the surface, and no fault rupture traces have been reported. The boundary between positive and negative LOS changes runs in the NW-SE direction (Fig. 2a), suggesting the earthquake may be dominated by a left-lateral strike-slip fault. The largest deformation in the LOS direction on the southwest side of the fault was up to 3 cm, while the maximum deformation in the LOS direction on the northeast side reaches−5 cm.

3.3. Coseismic deformation of the 29 and 31 Oct. events

Two large earthquakes with magnitudes of 6.6 and 6.5 occurred on 29 Oct. (EQ2) and 31 Oct. (EQ3), respectively, only two days apart. No radar data acquisition was available between these two events, and the earliest images from the Sentinel-1 after these two earthquakes were acquired on 07 Nov. 2019. Therefore, the deformation ﬁelds in the ascending interferogram (Inf_2,Fig. 3a) and descending interferogram (Inf_3, Fig. 3d) include the cumulative deformation caused by two earthquakes. Both the ascending and descending interferograms suggest that the strikes of the faults responsible for these two earthquakes may have been in the NE-SW direction, which is consistent with the USGS and PHIVOLCS results. In the ascending interferogram (Inf_2,Fig. 3a), the motion on the northwest side of the inferred fault is dominated by the negative values, which indicates a movement away from the satellite with a cumulative deformation of -12 cm. The peak deformation in the LOS direction is approximately 12 cm on the southeast side of the inferred fault, implying the movement toward the satellite of 11 cm. In the descending interferogram (Inf_3,Fig. 3d), the positive values with a peak deformation of 12 cm are distributed on the northwest side of the fault, while the southeast side of the fault shows a deformation pattern of negative values with a peak deformation of -20 cm.

Table 1

Sentinel-1 data used in this study.

Event No. EQ Time Inf. No. Track Master Data Slave Data Perp. Baseline (m) Local Incidence Angle (°)

EQ1 2019/10/16 Inf_0 T69A 2019/10/14 2019/10/26 28 39–41

EQ1 2019/10/16 Inf_1 T163D 2019/10/14 2019/10/26 34 40–42

EQ2&3 2019/10/29&31 Inf_2 T69A 2019/10/26 2019/11/07 27 39–41

EQ2&3 2019/10/29&31 Inf_3 T163D 2019/10/26 2019/11/07 97 40–42

EQ4 2019/12/15 Inf_4 T163D 2019/12/13 2019/12/19 29 40–42

EQ4 2019/12/15 Inf_5 T69A 2019/12/13 2019/12/25 30 39–41

Fig. 2.(a) Coseismic deformationfields of EQ1, which are interfered from the descending track 163 of Sentinel-1 (Inf_1). Positive values represent a movement toward the satellite, while negative values represent a movement away from the satellite. (b) Simulated interferogram of EQ1 with the best-fitting inversion model for Sentinel-1 descending track 163. (c) Residual after removing (b) from the original obversion shown in (a). (For interpretation of the references to colour in thisfigure legend, the reader is referred to the web version of this article).

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3.4. Coseismic deformation of 15 Dec. events

The fourth large earthquake occurred on 15 Dec. (EQ4). It can be inferred from the deformation patterns in the interferogram (Inf_4 and Inf_5) that this earthquake may have been due to a SE-NW strike-slip rupture, which is similar to the characteristics of the EQ1 (Fig. 4a, d).

The interferograms of the ascending and descending tracks show that the deformation pattern is obvious, and the turbulent atmospheric effects are minimal. Thus, GACOS-based correction is not needed. The largest deformation in the LOS direction is approximately 30 cm in the descending track (Inf_4,Fig. 4a), moving away from the satellite, implying a left-lateral strike-slip motion. The ascending track interferogram (Inf_5,Fig.4d) suggests that the deformation is approximately -20 cm on the southwest side of the interred fault and approximately 20 cm on its northeast side, which suggests that the rupture is also accompanied by a slight thrust component.

4. Geophysical modeling and results 4.1. Inversion method

To reduce the computational cost, a data resolution-based sampling method was employed to downsample the unwrapped interferograms (Lohman and Simons, 2005). Thus, the number of calculations for inversion can be greatly reduced, and the inversion accuracy of inversion was not greatly aﬀected. In this paper, a two-step inversion method was used to estimate the geometric parameters of the fault rupture and the slip distribution. First, fault planes with a uniform slip are determined through non-linear inversion by using the particle swarm optimization (PSO) algorithm (Feng et al., 2018,2013). Then, the slip distribution on the fault plane is estimated using a linear inversion algorithm.

4.1.1. Uniform slip model

The primary purpose of this step using a uniform slip model is to determine the location (latitude and longitude), top burial depth, strike, dip and rake angles, length, width and slip of the fault. Based on the Okada elastic dislocation model (Okada, 1985), we employed a PSO non-linear optimization algorithm to compare the observation and simulation results and automatically search for optimal parameters, that is,ﬁnd the solution that minimizes an objective function throughout the whole parameter domain. The objective function used in this paper is deﬁned as

= − −

σ (d Gs W d)^T ( Gs n)/ (1)

The coeﬃcient matrix G represents the surface deformation response caused by slip on the uniform fault (1 m);s represents the slip vector;W indicates the relative weight of each dataset;dindicates the observed value of surface deformation, and n is the number of deformation observations.

4.1.2. Distributed slip model

To further determine the spatial distribution of slip on the faults, the uniform slip model is divided into several subfaults. To prevent ex- cessive instability of slip on the subfaults, the slip roughness is constrained by the quadratic diﬀerence Laplace operator (Harris and Segall, 1987). Although the non-linear inversion results determine the optimalﬁtting solution, the optimal dip angle changes slightly in slip distribution inversion (Bürgmann et al., 2002;Feng et al., 2013). La- placian smoothing was employed to constrain the slip roughness and prevent a physically impossible oscillatory slip(Feng et al., 2013). The relationship is shown as follow.

⎡

⎣

⎤

⎦ = ⎡

⎣ ⎤

⎦ G

α L s d 0

2 (2)

Fig. 3.Coseismic deformationﬁelds of EQ2 and EQ3. Positive values represent movement toward the satellite, while negative values represent a movement away from the satellite. (a) Coseismic observation from ascending track 69(Inf_2). (b) Simulated interferogram for Inf_2. (c) Residual interferogram for Inf_2. (d) Coseismic observation from descending track 163 (Inf_3). (e) Simulated interferogram for Inf_3. (f) Residual interferogram of Inf_3. (For interpretation of the references to colour in thisﬁgure legend, the reader is referred to the web version of this article).

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Lrepresents a second-order diﬀerential operator to evaluate the slip roughness.α²represents the smoothing factor.

4.2. Inversion results

In this study, four earthquakes are considered. For the inversion of EQ1, the initial fault model is constructed according to the preliminary focal mechanism from the USGS (Table 2) and InSAR deformationﬁelds of Inf_1 (Fig. 2a). We used the coseismic deformation observation to constrain the location for EQ1 and inverted its source parameters through the method described in Section4.1. For determining the uncertainties of fault geometric parameters, we adopted the Monte Carlo method to estimate the error for the uniform slip model (Feng et al., 2013;Parsons et al., 2006). One hundred sets of predicted errors were generated by a random number from the normal distribution and then added into the observations. We simulated 100 sets of geometric parameters from the simulated observations. From uncertainties and

trade-oﬀs of fault geometric parameters (Fig. S3), we found that the standard deviations of all parameters are small, which suggest that the non-linear solution is one of the best-ﬁt geometric parameters.

We determined optimal smoothing factors for eachﬁxed given dip angle within a speciﬁc range and then investigated the variation trends, which allowed us to obtain the global minimum point (red star in Fig.

S4). The initial rake angle was constrained to a range of−25° to 25°.

The dip angle was ranged from 83° to 87°, and the smoothing factor was varied between 0 and 4.5. The correlation coefficient between the observations and simulation is 88.4 %. The optimal solution for the slip distribution of EQ1indicates that the rupture is dominated by a left- lateral strike-slip motion, the strike angle is 304.5°, the dip angle is 86°, and the average rake angle is -10°. The slip is concentrated at a depth of 13 km (Fig. 5a). The maximum slip is approximately 0.84 m, and the moment magnitude is approximately 6.4. Based on the slip distribution, the deformation interferogram is simulated (Fig. 2b). From the residual interferogram (Fig. 2c), we found that the simulated interferogram can Fig. 4.Coseismic deformationfields of EQ4. Positive values represent movement toward the satellite, while negative values represent a movement away from the satellite. (a) Coseismic observation from descending track 163 (Inf_4). (b) Simulated interferogram for Inf_4. (c) Residual interferogram of Inf_4. (d) Coseismic observation from ascending track 69(Inf_5). (e) Simulated interferogram for Inf_5. (f) Residual interferogram for Inf_5. (For interpretation of the references to colour in thisfigure legend, the reader is referred to the web version of this article).

Table 2

Focal mechanisms and fault parameters of the four main earthquakes.

EQ. No. Source Lon (°E) Lat (°N) Strike (°) Dip (°) Rake (°) Len (km) Width (km) Depth (km) Mag (Mw)

16 Oct. (EQ1) USGS 125.009 6.714 303 86 9 – – 15.8 6.28

GCMT 125.01 6.860 307 85 3 – – 19.0 6.4

InSAR 125.08 6.77 304.5 86 −10 40 30 13 6.4

29 Oct. (EQ2) USGS 124.995 6.759 234 88 −176 – – 15 6.58

GCMT 125.06 6.880 232 87 173 – – 19.0 6.6

InSAR 125.076 6.856 234 87 176 20 14 8 6.6

31 Oct. (EQ3) USGS 125.183 6.908 36 71 177 – – 10 6.37

GCMT 125.11 6.96 39 67 −165 – – 12.0 6.5

InSAR 125.184 6.987 44 60 −160 30 18 9 6.5

15 Dec. (EQ4) USGS 125.188 6.708 319 82 −34 – – 22.4 6.77

GCMT 125.15 6.71 319 78 13 – – 12.8 6.7

InSAR 125.186 6.675 320 75 17 40 30 13 6.7

USGS:https://earthquake.usgs.gov/earthquakes/search/.

GCMT:https://www.globalcmt.org/CMTsearch.html.

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explain the coseismic deformationﬁeld well, which suggests that the simulation results are reasonable.

The acquisitions of Inf_2 and Inf_3 span the occurrence period of both EQ2 and EQ3. As expected, the displacement signals should include the cumulative displacements of these two events. Distinguishing the various signals of these two quakes from the spatial deformation fields is difficult. Therefore, we chose the simplest slip model for these two events. We assumed that the coseismic deformation fields were caused by the ruptures of two faults through EQ2 and EQ3. From the characteristics of the spatial distribution of the deformation (Inf_2 and Inf_3), we inferred that the ruptured faults are oriented in the NE-SW direction. According to this condition, we set the initial fault geometric parameters responsible for the earthquakes based on the focal mechanism solutions published by the Global Centroid Moment Tensor (GCMT) Project (https://www.globalcmt.org) and USGS in our inversion (Table 2). We used a two-segment fault model to simulate the deformationfields caused by the two earthquakes and jointly inverted for the two faults responsible for the earthquakes. To avoid a trade-off of seismic moments from the two sources, we added magnitudes as a further constraint in the inversion as done in Feng et al. (2019). The geometric characteristics of the two faults responsible for the earthquakes were obtained by using the PSO inversion method. We set the equal weight for the observations of ascending and descending observations. The inversion processes are similar to those of EQ1, and the initial rake angle was constrained at a range of 170°–179° for EQ2 and

−170°to−150° for EQ3. Wefixed the strike and dip angles for the non- linear inversions and used an InSAR-error estimation based Monte Carlo analysis (Figs. S5 and S6). From uncertainties of fault geometric parameters, we found that trade-offs of fault geometric parameters are strong enough, and they show a general non-uniqueness of geophysical inversion (Feng et al., 2018). Thefinal focal mechanism solution of EQ2 suggests that the strike angle is 234°, the dip angle is 87°, the average slip angle is 176°, and the slip is mainly concentrated at a depth of 8 km (Fig. 5b andTable 2). The focal mechanism solution of EQ3 is as follows: the strike angle is 44°, the dip angle is 60°, the average slip angle is−160°, and the slip is mainly concentrated at a depth of 9 km (Fig. 5c andTable 2). The fault projections of these two earthquakes on the surface have similar directions, but their dip-directions are different (Fig. 6). The fault plane of EQ2 is inclined toward the northwest, while the fault plane of EQ3 is inclined toward the southeast (Fig. 6). Al- though the dip directions of the EQ2 and EQ3 are different, the rupture

planes of these two quakes are nearly vertical. The simulated deformation interferograms (Fig. 3b and e) illustrate that the surface deformation signals caused by these two earthquakes can be explained well by the optimal model, although a noticeable local deformation residual remains at the northeast end of the ruptured fault corresponding to EQ3 (Fig. 3c). After comparison of the residual phase (Fig. 3c) and simulated atmospheric phase from GACOS (Fig. S8b), the residual cannot be fully accounted for by GACOS (Fig. S7, S8). The residual phase may involve 7–9 days of early afterslip following EQ2 and EQ3 because rapid afterslip after a large earthquake is a common phenomenon, as observed after the 2014 Napa earthquake (Li et al., 2015) and 2019 Ridgecrest earthquake (Wang and Bürgmann, 2020).

The interferograms (Inf_4 and Inf_5) related to EQ4 reveal distinct deformation signals. Equal weights were set for the interferograms in the inversion. We obtained an optimum slip distribution result from the PSO inversion method. The uncertainties of the fault geometric parameters were estimated using a Monte Carlo analysis (Fig. S9). We found that the uncertainties in the model are small, and the trade-oﬀs between model parameters are strong. The inversion results show that the rupture was distributed between 0 and 30 km (Fig. 5d). The deformation simulation of the descending track based on the optimal solution can explain the deformation distribution well (Fig. 4b), and there are few residual signals remaining (Fig. 4c). In the ascending track, the deformation signals are fully estimated (Fig. 4e) except for some residual signals in the region close to the fault (Fig. 4f), which may have been caused by a rapid afterslip. The optimal model indicates that the ruptured faults of EQ4 are dominated by a left-lateral strike-slip motion similar to that of EQ1; the best-ﬁt strike angle is 320°, and the corresponding dip angle is approximately 75° (Fig. 6, Table 2). The slip patches on the rupture plane were mainly concentrated at a depth between 1 and 15 km (Fig. 5d). The upper patch is located at a depth of 3–9 km, with the maximum slip of∼2.8 m and an average rake angle of

−5° to 0°. Besides, a deeper slip patch occurs at a depth of 8–15 km, with the maximum slip of∼1.5 m and an average rake angle of∼40°.

This distribution of slip represents that the focal mechanism of EQ4 was dominated by a strike-slip motion with a considerable number of thrust- slip components, which can explain the uplift and subsidence signals in Fig. 4a.

Fig. 5.Slip distributions of the four 2019 shocks that studied in this study. (a)EQ1, (b) EQ2, (c) EQ3, (d) EQ4. (For interpretation of the references to colour in this ﬁgure legend, the reader is referred to the web version of this article).

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4.3. Coulomb stress accumulation and earthquake triggering

According to the static Coulomb stress triggering hypothesis, aftershocks generally occur in the area where the Coulomb stress increases (Harris, 1998;Wu et al., 2016). We computed Coulomb stress changes using Coulomb 3.3 software (Toda et al., 1998, 2015;Toda and Stein, 2002). Based on the fault geometries and the slip distribution on the fault ruptured by the four signiﬁcant earthquakes, we explore whether static stress changes of previous events triggered the subsequent events during the 2019 earthquake sequence. We calculated the static Cou- lomb stress step by step by setting the upcoming event as a receiver fault and provided the cumulative maps of the stress changes from the previous events.

Wefirst estimated the effects of the stress changes from the EQ1 event on the following EQ2event. The slip distribution of EQ1from Section4.2(Table 2) was used for the source fault, and the rupturing fault of EQ2was selected as the receiver fault. The fault geometries of EQ2were also inferred fromTable 2. We selected 0.6 as the friction coefficient and 8 km as the depth constraint. We calculated various values ranged from 0.1 to 0.8 for the coefficient of friction, and the stress changes did not show significant differences from that for 0.6 (Park and Mori, 2007). The depth was determined from the maximum slip on the rupture plane inFig. 5andTable 2.Fig. 7shows that the Coulomb stress change map of EQ1 exhibits areas with increases in stress as indicated in red, while decreases in stress are shown in blue.

The Coulomb stress change simulations indicate that EQ1 encouraged the subsequent EQ2 event by increasing the Coulomb stress in the hypocenter regions of EQ2. We then calculated the combined Coulomb stress changes from the EQ1 and EQ2 events. The rupturing fault of EQ3 was selected as the receiver fault. The friction coeﬃcient was the same as that previously selected, and 9 km was used as the depth constraint.

From the combined stress changes map (Fig. 8), the hypocenter and all the fault rupture areas of EQ3 are located in the regions of positive stress change. The magnitude of the stress increase around the rupture of EQ3 is approximately 2.5–3.0 bars. Therefore, the stress change from the previous earthquake had a particular eﬀect on the subsequent earthquake event. Lastly, the combined Coulomb stress changes from the EQ1, EQ2 and EQ3 were calculated based on the cumulative slip distribution of these earthquake events. The rupturing fault of EQ4 was selected as the receiver fault. We estimated the Coulomb stress changes at a depth of 13 km, which was also inferred from the result inTable 2.

As previously determined, the total stress change around the hypocenter of EQ4 is approximately 1.5–2.5 bars (Fig. 9).

5. Discussion

5.1. Aftershock triggering

From the Coulomb stress accumulation and earthquake triggering results (Figs. 7–9), it suggested that the stress change from the previous earthquake has a particular eﬀect on the subsequent earthquake sequence (Hayes et al., 2014;Herman et al., 2014;King, 2007;King et al., 1994). The positive stress changes are expected to encourage subsequent large earthquakes, which is a widespread phenomenon, as observed for the 1992 Landers earthquake and subsequent Big Bear and Hector earthquakes (Jones and Hough, 1995) and the 2019 Ridgecrest earthquake sequence (Barnhart et al., 2019). In addition to the large shocks, the static stress changes are also capable of triggering small aftershocks (Park and Mori, 2007). The fault dislocation during the EQ1 event results in small stress increases, which are also capable of triggering small earthquakes in the surrounding region (Park and Mori, 2007;Stein, 1999). To study the aftershocks triggering, we estimate the change in static stress after EQ1 by using slip distributions on the rupture fault and the aftershocks. Fig. 10 shows that most of the aftershocks and the three sequentially ruptured faults were located in the area with positive Coulomb stress change values greater than 1 bar.

The Coulomb stress changes from the EQ1 event formed a SE-NW trend that extended farther southeast and a NE-SW trend that extended farther northeast (Fig. 10). There are some aftershocks located in the area with a stress decrease; these aftershocks were triggered not only by EQ1 but also possibly the following signiﬁcant earthquakes directly.

5.2. Conjugate ruptured fault structure

The fault rupture of EQ1 occurred in the Cotabato fault system (Fig. 1 and 11a), which consists of NW-SE-trending left-lateral faults across the Mindanao. This fault system accommodates the elastic stress that was not consumed by the Philippine fault and the trenches around the Mindanao (Wu et al., 2017). A noticeable characteristic of the source faults of EQ2 and EQ3 is that they are nearly perpendicular to that of EQ1 and EQ4 (Figs. 6 and 11b), thus, the Mindanao earthquake sequence that occurred in a conjugate fault system. Such a conjugate Fig. 6.Perspective view of the rupture faults and spatial distributions of the fault slips. (For interpretation of the references to colour in thisﬁgure legend, the reader is referred to the web version of this article).

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fault system is not conventional, as we expect the angle between opti- mally oriented strike-slip conjugate faults to be approximately 60°

(Anderson, 1905;Liu et al., 2019). That is because the mutually perpendicular conjugate faults are mainly distributed in a region of young faults, and many of them were un-mapped, as they do not reach the surface. Thus, it is diﬃcult to trace them. Some reports have indicated that some relatively young faults in the epicentral area were discovered in recent years, and these young faults have modest cumulative oﬀset and low slip rates (https://hazardhunter.georisk.gov.ph/).

The regional GPS velocities suggest that the formation of this conjugate structure is mainly due to the westward movement of the subducting PSP. The GPS stations near Davao City (DAVA, PDAV and

PDDN) showed an apparent westerly component (Fig. 11a); the movement direction is perpendicular to the Philippine fault and Cota- bato trench and oblique to the Makilala, Balabag and M'lang faults in the Cotabato fault zone. These observations suggest that the southern section of the Philippine fault may not undergo lateral movement (Aurelio, 2000;Blewitt et al., 2018). Its westward movement results in the left-lateral strike-slip deformation of the M'lang fault and Makilala- Malungon fault, while oblique compression may have led to the right- lateral strike-slip Makilala fault and Balabag fault (Fig. 11b). This ﬁnding is consistent with that the four large earthquakes rupturing along with two conjugate faults (SE-NW and NE-SW) under a nearly E- W compressive stress (Fig. 11b). The compressive stress direction is Fig. 7.Coulomb stress change map from the 16 Oct. earthquake event (EQ1) to the 29 Oct. earthquake event (EQ2). The red line represents the source fault, and the blue one indicates the receiver fault.

The red stars represent the epicentre of the large shocks. (For interpretation of the references to colour in thisﬁgure legend, the reader is referred to the web version of this article).

Fig. 8.Coulomb stress change map from the 16 Oct. earthquake event (EQ1) and 29 Oct. earthquake event (EQ2) to the 31 Oct. earthquake event (EQ3). The red line represents the source fault, and the blue one indicates the receiver fault. The red stars represent the epicentre of the large shocks. (For interpretation of the references to colour in this ﬁgure legend, the reader is referred to the web version of this article).

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considered to be due to the ongoing convergence of the PSP and SP. The opposite slip motions of the conjugate ruptures released the right- and left-lateral shear stress on each plane, respectively. According to the comparison of the locations, EQ1 and EQ4 most likely occurred along the M'lang fault and Makilala-Malungon fault, respectively, while the EQ2 and EQ3 probably occurred along the Makilala fault and Balabag fault, respectively (Fig. 11b).

5.3. Seismogenic implications of conjugate ruptures

The conjugate structure inferred from the 2019 Mindanao earthquake sequence provides new insights into the seismotectonic implications (Lin and Chiba, 2017). The conjugate rupture process of four large earthquakes that occurred in Mindanao showed that the faults

with a SE-NW orientation are a part of Cotabato fault system and are more mature than the SW-NE faults (Hammarstrom et al., 2014). This fault geometry is conducive to the accumulation of strain in the formation of seismogenic structures. These seismogenic characteristics suggest that the seismotectonic and rupture process in a conjugate fault system is closely related to the condition of mutual compatibility and mutual locking. Two groups of earthquakes that occur along conjugate faults can be distinguished based on the timing of the conjugate rupture with respect to the main rupture (Fukuyama, 2015). Thefirst group involves pairs of earthquakes that simultaneously occur along the conjugate faults, and the second group mainly refers to the conjugate fault rupturing that occurs sequentially after the main rupture. The Coulomb stress change map (Fig. 10) has confirmed that aftershocks mainly occurred in the regions around the conjugate faults that Fig. 9.Coulomb stress change map from the 16 Oct. earthquake event (EQ1), 29 Oct. earthquake event (EQ2) and 31 Oct. earthquake event (EQ3) to the 15 Dec. earthquake event (EQ4). The red line represents the source fault, and the blue one indicates the receiver fault. The red stars represent the epicentre of the large shocks. (For interpretation of the references to colour in thisfigure legend, the reader is referred to the web version of this article).

Fig. 10.Coulomb stress change map for the 16 Oct. earthquake event (EQ1), the parameters were set asFig. 7. The yellow dots show the aftershocks of EQ1, which was reported by PHIVOLCS (https://www.phivolcs.

dost.gov.ph/index.php/earthquake/earthquake-information3). (For interpretation of the references to colour in thisﬁgure legend, the reader is referred to the web version of this article).

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exhibited stress increases. These earthquakes in this study belong to the second group; the subsequent earthquake sequence was triggered by the ﬁrst event. There are some earthquake sequences that have been observed in recent years with similar characteristics, e.g., the 2019 Rid- gecrest earthquakes (Barnhart et al., 2019).

6. Conclusions

The 2019 Mindanao earthquake sequence highlights the complexity of the regional structure due to plate convergence. It provides a rare opportunity to understand the formation and seismogenic implications of the conjugate fault structure in Mindanao. In this study, Sentinel-1 data and InSAR were employed to produce the coseismic deformation ﬁelds caused by the four large earthquakes. The focal mechanism solutions for the four large earthquakes were then investigated by PSO methods. Based on the fault geometric and slip model of these events, the triggering eﬀect of combined Coulomb stress changes caused by the coseismic dislocation of the big earthquakes on subsequent earthquakes is studied. We found that the accumulation of static stress changes due to previous events can trigger subsequent events.

The conjugate fault structure and regional GPS velocities con- sistently explained the tectonic setting of the earthquake sequence. The Philippine fault does not entirely consume westward compression of the PSP. Its continued westward movement produces a left-lateral strike- slip motion on the M'lang fault and Makilala-Malungon fault and a right-lateral strike-slip motion on the Makilala fault and Balabag fault.

These secondary faults in the Cotabato fault system create a conjugate fault system. The continuous accumulation of stress along these conjugate faults eventually resulted in the occurrence of these earthquakes.

Research on the relationship between these successive rupture events is a signiﬁcant aspect of studying the focal mechanism of these earthquakes.

CRediT authorship contribution statement

Bingquan Li:Data curation, Writing - original draft.Yongsheng Li:

Conceptualization, Methodology, Validation, Funding acquisition.

Wenliang Jiang: Writing - review & editing, Supervision. Zhe Su:

Investigation, Formal analysis. Wenhao Shen: Investigation, Formal analysis.

Declaration of Competing Interest

The authors declare that they have no known competingﬁnancial interests or personal relationships that could have appeared to inﬂu- ence the work reported in this paper.

Acknowledgments

This work was supported by research grants from the Institute of Crustal Dynamics, China Earthquake Administration (grant numbers No. ZDJ2018-16) and National Natural Science Foundation of China under Grant (grant number 41704051). We sincerely thank the Editor and four reviewers’thorough reviews which signiﬁcantly improved the manuscript. The Sentinel-1 data were provided by the European Space Agency (ESA) through the Sentinels Scientiﬁc Data Hub.

Appendix A. Supplementary data

Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.jag.2020.102127.

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