An Extremely Shallow Mw4.1 Thrust Earthquakein the Eastern Sichuan Basin (China) LikelyTriggered by Unloading DuringInfrastructure ConstructionYunyi Qian1,2, Xiaofei Chen1, Heng Luo3, Shengji Wei4,5, Teng Wang6, Zhenguo Zhang1,and Xinyu Luo2

1Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen, China, 2School ofEarth and Space Sciences, University of Science and Technology of China, Hefei, China, 3The State Key Laboratory forInformation Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China, 4EarthObservatory of Singapore, Nanyang Technological University, Singapore, 5Asian School of the Environment, NanyangTechnological University, Singapore, 6School of Earth and Space Sciences, Peking University, Beijing, China

Abstract Triggered or induced earthquakes have been widely reported as resulting from varioushuman activities, yet seismicity triggered by small‐scale infrastructure construction is rare. Here, wereport on an investigation of an extremely shallow Mw4.1 earthquake which occurred on 11 August 2016in the Sichuan Basin (China), a region with historically low seismicity. Our seismic waveformanalyses indicate an almost pure thrust focal mechanism at a centroid depth of ~1 km. Furthermore,18 Sentinel‐1 synthetic aperture radar interferograms, stacked to obtain subcentimeter accuracy, revealup to 3 cm line‐of‐sight deformation which overlaps with an automotive testing site constructed in 2014.Removal of 10 m of a surface rock layer during the construction may have produced an unloading effectand resulted in up to 0.11 MPa Coulomb stress changes on a blind fault, larger than the 0.01 MPathreshold typically invoked in studies of tectonic earthquakes. However, the delayed triggering stillrequires further investigation.

Plain Language Summary While induced earthquakes in the shallow part of the crust have beenobserved globally, a remaining knowledge gap is whether small‐scale infrastructure construction cantrigger earthquakes or not. We investigate these questions on an extremely shallowMw4.1 earthquake in theeastern Sichuan Basin (China). To determine earthquake source parameters, we combine seismologicaldata with satellite imaging. We find this thrust event ruptured at the depth of ~1 km, located just beneath anautomotive testing site constructed in 2014. Crucially, we note the testing site construction involvedremoval of a large volume of surface rock. We further analyze the stress changes produced by the unloadingof the surface rock. We find a possible triggering relationship between the infrastructure constructionand the occurrence of this shallow earthquake. Our results thus shed new light on the causes of shallowearthquakes associated with small‐scale infrastructure construction.

1. Introduction

In the last decade, human‐induced seismicity has received extensive attention of the scientific community,industry, government, and general public due to its potential risk and increasing frequency. Induced ortriggered earthquakes have been linked to a wide range of human activities (Foulger et al., 2018), such aswater injection (e.g., Deng et al., 2016; Tadokoro et al., 2000), dam construction (e.g., Ge et al., 2009;Talwani, 1997), megainfrastructure construction (e.g., Lin, 2005), open mining (e.g., Dent, 2015; Edwardset al., 2010), and other sources (Gibson & Sandiford, 2013). Much less, however, is known about the relation-ship between induced seismicity and small‐scale infrastructure construction. Studying this link is importantnot only to better understand seismogenic processes but also for seismic hazard mitigation since small‐scaleconstruction is common worldwide. Here, we report on a case of an extremely shallow Mw4.1 earthquakewhich occurred on 11 August 2016 in Dianjiang, a county in the eastern Sichuan Basin of China (hereafternamed the Dianjiang earthquake), which was likely triggered by the unloading of a ~10‐m layer of surfacerock during an automotive testing site construction.

©2019. American Geophysical Union.All Rights Reserved.

RESEARCH LETTER10.1029/2019GL085199

Key Points:• The 11 August 2016 Mw4.1

Dianjiang earthquake was anextremely shallow thrust event(~1 km)

• Stacking of Sentinel‐1A SARinterferograms with subcentimeterresolution reveals LOS deformationof up to 3 cm produced by theearthquake

• The earthquake was likely triggeredby the unloading effect after surfacerock layer was removed duringinfrastructure construction

Supporting Information:• Supporting Information S1

Correspondence to:Y. Qian, and S. Wei,qianyy@sustech.edu.cnshjwei@ntu.edu.sg

Citation:Qian, Y., Chen, X., Luo, H., Wei, S.,Wang, T., Zhang, Z., & Luo, X. (2019).An extremely shallow Mw4.1 thrustearthquake in the eastern SichuanBasin (China) likely triggered byunloading during infrastructureconstruction. Geophysical ResearchLetters, 46, 13,775https://doi.org/10.1029/2019GL085199

Received 30 AUG 2019Accepted 21 NOV 2019Accepted article online 3 DEC 2019

QIAN ET AL. 13,775

–13,784.

Published online 10 DEC 2019

The Dianjiang earthquake was located within the thin‐skinned thrust fold belts at the eastern Sichuan Basin(Yan et al., 2003), which generated shaking intensity larger than V within more than a 100 km2, injuringthree people (www.cqdzj.gov.cn). The region is dominated by chevron anticlines and thrust faults(Li et al., 2015), such as the NWdipping Huayingshan basement fault and the SE dipping Fangdoushan base-ment fault (Figure 1a). The basement faults are hidden in the crystal basement (>5 km) and show minoractivity (Wang et al., 2008). The orientation of compressional principal stress in the crust is perpendicularto these NE‐SW folds (Ding et al., 2004). Based on the Chongqing Seismic Network catalog (1990 to 2018),there was no otherM > 3.5 event within 100 km of the Dianjiang earthquake, indicating a low backgroundseismic rate, although many shallow earthquakes in the Sichuan Basin have been linked with wastewaterinjection (e.g., Lei et al., 2008) and hydraulic fracturing in shale gas fields (e.g., Lei et al., 2017; Figure 1a).

The Dianjiang earthquake was recorded by short‐period and broadband seismic stations with high quality.Short‐period surface waves were very strong at the nearest (~10 km) XIM station (Figures S1 and S2 in thesupporting information), indicating a very shallow source depth. Moreover, the coseismic displacement wascaptured by the C‐band (5.6 cm) Sentinel‐1 satellite radar images. The maximal line‐of‐sight deformation inthe Interferometric Synthetic Aperture (InSAR) image was ~3 cm (Figure 1a, upper inset), also indicating avery shallow focal depth. These observations provide valuable constraints on the absolute location, depth,and focal mechanism of the earthquake. More interestingly, the peak deformation in the InSAR datavirtually overlaps with an automotive testing site (Figure 1a, upper inset), which was constructed in 2014.Prior to the construction, the site was a hilly area without any infrastructure visible on a 2004 GoogleEarth image (Figure 1b, left). During the construction, the tops of the hills were leveled. Archiver recordsof the construction plan provided by the Chongqing Housing and Construction Commission show thatthe testing site is designed to be flat (Figure 1c, dashed black lines), with 10 to 20 m of a surface rock layerhaving been removed (Figure 1c, solid green lines). Photos taken in 2019 show the hills next to the site areabout 20 m higher (Figures 1d and S3). These observations suggest a link between this infrastructureconstruction and the earthquake. Yet questions remain as follows: (1) How accurately can we determinethe source parameters of the earthquake? (2) Is there a physical relationship between this earthquake andthe infrastructure construction?

To address these questions, we first use regional seismic waveforms to determine the source parameters ofthe earthquake. We then analyze the Rayleigh wave amplitude spectra and the high‐frequency teleseismicP wave to provide further constraints on the earthquake depth. Our seismic waveform analysis results arethen verified by InSAR inversions, which is followed by a Coulomb stress analysis which considersunloading of the rock layer during the construction. Finally, we discuss the results and suggest a triggeringrelationship between the infrastructure construction and the Dianjiang earthquake.

2. Precise Source Parameters of the Dianjiang Earthquake2.1. Seismic Waveform Analyses

To obtain the centroid depth and focal mechanism of the earthquake, we invert regional broadband wave-forms and P wave first motion polarities, using the generalized Cut and Paste method (Zhu & Ben‐Zion,2013; Zhu & Helmberger, 1996). With a 1‐D velocity model extracted from Crust1.0 (Laske et al., 2012)and Wang et al. (2016; Figure S4), we adopt the FK package (Zhu & Rivera, 2002) to compute theGreen's functions. Waveforms recorded by the China National Seismic Network within the 400‐kmepicentral distance (Figure S5) are used in the inversion. We set the frequency band from 0.01 to 0.2 Hzfor Pnl waves and from 0.01 to 0.1 Hz for surface waves to ensure high quality of waveform fits. The lowerhemisphere projections of P, SH, and SV wave radiation patterns of the preferred focal mechanism areshown in Figure 2a. Figure 2b shows the grid search result for depth as a function of misfit, which showsthe best centroid depth of 1 km, corresponding to a moment magnitude ofMw4.1 and a fault plane solutionof nodal plane 1 (np1): strike 281°, dip 45°, rake 93°, and nodal plane 2 (np2): strike 97°, dip 45°, rake 87°.The waveform fits for stations within 170 km (the white triangles in Figure 2a and the peach triangles inFigure S5) are shown in Figure 2c. The waveform fits for the other stations (the black triangles inFigure 2a and brown triangles in Figure S5) can be found in Figure S6. The fits between synthetics andobservations are very good, with an averaged cross‐correlation coefficient of 83%, indicating a well‐constrained focal mechanism and depth.

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To further verify the depth, we use a method proposed by Bath (1975) to model the fundamental modeRayleigh wave. The spectrum of Rayleigh waves is highly sensitive to source depth (Tsai & Aki, 1970). Ingeneral, surface waves only develop well at a distance larger than at least three wavelengths (Bensenet al., 2007), and sources at shallow depths are more efficient at generating surface waves (Aki &

Figure 1. (a) The Dianjiang earthquake, historical earthquakes (1990–2018, red dots), seismic stations (triangles, blackfor short period and blue for broadband), fault traces (black lines), and seismic clusters near gas wells (purple outlines,from Lei et al. (2017)). The upper right inset shows the InSAR data. The black line sketches the contour of an automotivetesting site, constructed in 2014. (b) The Google Earth images acquired in April 2004 (left) and July 2014 (right). AA′and BB′ indicate the location of two profiles in (c). The black rectangle indicates the flat region. The red arrows indicatethe directions toward which photos in (d) were taken. (c) Two profiles from the archived construction plan showingthe elevation before (solid green) and after (dashed black) the construction along the AA′ and BB′ in (b). (d) The photostaken in 2019 at two hills outside of the testing site.

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Figure 2. Earthquake source parameters inversion results. (a) The lower hemisphere projection of P, SH, and SV waves radiation patterns, with stations (triangles)projected on them. The black/blue and white/gray triangles indicate those with takeoff angle smaller and larger than 90°, respectively. Teleseismic stationWRAB (blue triangle) is shown in P wave radiation. The gray triangle is the short‐period station XIM. (b) Depth resolution for the regional waveform inversion.(c) The waveform fits for the regional stations (the white triangles in panel a). The waveform fits for the other regional stations are shown in Figure S6 in thesupporting information. The station names are labeled on the left of waveforms, with the azimuth and epicenter distance shown at the bottom. The time shifts (s)and waveform fitting cross‐correlation coefficients in percentage are listed beneath each trace. (d) Modeling the fundamental mode RWAS at four stations(bold station names in panel c).

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Richards, 2002). In the case of the Dianjiang earthquake, the observed Rayleigh waves at the nearest(10.78 km) short‐period XIM station were very strong (Figures S1 and S2), which indicates a shallow sourcedepth. To further constrain the depth, we model the fundamental mode vertical component Rayleigh WaveAmplitude Spectra (RWAS) at regional (<350 km) broadband stations. We conduct multiple filter analysesusing the CPS package (Herrmann & Ammon, 2004) to obtain RWAS at 4 to 40 s for the data, which allshow nearly flat spectra (Figure 2d). The synthetic RWAS are computed for various depths to find the bestfitting depth, following Jia et al. (2017). When the depth is larger than 1 km, the spectra always show atrough between 5 and 20 s, corresponding to weaker surface wave energy. The RWAS modeling clearlyreveals a centroid depth of 1 km.

Further seismic evidence for a shallow depth is also provided by modeling of high‐frequency teleseismic Pwaves (Figure S7).

2.2. InSAR Analyses

In addition to various seismological evidence for a very shallow centroid depth (~1 km), further supportcomes from InSAR images and static slip inversions. The surface displacement produced by the earthquakewas captured by the Sentinel‐1 satellite. The InSAR data processing method in Jiang et al. (2017) is adoptedto produce interferograms. It is clear from Figure S8 that only the interferograms spanning the occurrencetime of the earthquake show a localized deformation signal, suggesting a causal relationship between thesignal and the earthquake. However, due to the event's small magnitude (Mw4.1) and consequently verysmall surface deformation (only up to a few cm), traditional InSAR techniques are not sufficient to obtainhigh‐quality measurements. To improve the signal‐to‐noise ratio of our measurements, we stack 6 preseis-mic and 13 postseismic images (Table S1), with the last image acquired before the earthquake selected asthe reference image, thus forming 18 interferograms (Figure S8). Assuming the atmosphere influence is tem-porally uncorrelated, the unwrapped interferograms before and after the earthquake are separately averagedand then differenced to obtain the coseismic displacements. The stacked InSAR data, in which the noise hasbeen greatly suppressed, clearly show a localized deformation near the epicenter of the earthquake(Figure 1a, upper inset). Because of naturally high accuracy in geocoordination, we consider the peak displa-cement location in the InSAR data as the best approximation to the ground‐truth location of the earthquake.

We thenmodel the InSAR data to derive a static slip model for the earthquake. We first downsample the datato 443 data points with a quadtree procedure (Jonsson et al., 2002; Figure 3). Since the earthquake is toosmall to derive a stable distributed slip model, we assume a uniform slip on a rectangular fault plane. Thestatic Green's functions are computed for a homogeneous elastic half‐space (Okada, 1985), with a shear mod-ulus (~17 GPa) extracted from the 1‐D model (Figure S4). The slip model is defined by nine parameters,describing fault size, orientation, location of the midpoint for the upper edge, fault slip amplitude and direc-tion. These fault parameters are inverted with a two‐step nonlinear inversion algorithm (Jonsson et al.,2002). Since only ascending tracks are available, we allow only the strike and rake to vary within 5° of theseismological solution to ensure stable inversions. The inversion results for two fault planes are presentedin Figures 3 and S9 and Table S2, in which the NE dipping fault has a slightly smaller root‐mean‐square(RMS) misfit. Since the misfit difference is small and trade‐off exists between source parameters, we cannotrule out the possibility that the earthquake might have occurred on the SW dipping fault. Nevertheless, inboth cases, the slip did not reach the surface, which is consistent with field investigations that reported nosurface rupture or damage at the automotive testing site, despite observed damage to the surrounding oldbuildings (Figure S10). There is also no geomorphological signature of thrust faulting around the sourceregion, therefore there is no further support to determine the ruptured fault plane. Regardless of the dipdirection, both geodetic solutions suggest a very shallow source depth (~1 km), consistent with ourseismological results.

The source parameters we derived from seismic waveforms and InSAR are in remarkable agreement (TableS3), both indicating a thrust focal mechanism with a centroid depth of 1 to 1.5 km, much shallower than thesolutions reported by the China Earthquake Networks Center (10 km) or the United States GeologicalSurvey (15 km; Table S4). An interesting observation from the InSAR image is the overlapping of the peaksurface deformation area with the automotive testing site (Figure 3). Archives of the construction plan(Figure 1c) and the sharp vertical cutoff of the hills at the margin of the current site (Figures 1d and S3) bothindicate that the tops of the hills have been partly leveled.

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3. Coulomb Stress Change Analysis

To better understand the relationship between the automotive testing site construction and the earthquake,we further conduct a Coulomb stress change analysis. The change of Coulomb failure stress is defined as

ΔCFS ¼ Δτ þ μ Δσ þ Δρð Þ; (1)

where Δτ and Δσ are the shear stress (positive in the slip direction) and normal stress changes (positive fortension), respectively, for a given fault geometry and slip direction, Δρ is the change of pore fluid pressure(assumed to be 0 in this study), and μ is the friction coefficient.

FromGoogle Earth images (Figure 1b), the area now occupied by this automotive testing site was at the sameheight as the surrounding hills prior to construction. Based on field investigations (Figures 1d and S3), theflattened area is at least 1.0 km2, with an elevation of ~20 m lower than the nearby hills. Considering theirregular topography in this region (Figures 1b and 1c), we assume the elevation was reduced on averageby 10 m, which produced an unloading effect on the fault. To calculate the Coulomb stress change on thethrust fault, we simplify the unloading as a 1.0 km2 cuboid of 10 m thick rock (Figure 4). The density ofthe rock is assumed to be a common value of 2,500 kg/m3. We discretize this cuboid unloading at the surfaceinto 100 × 100 grid points, with each point further simplified as a vertical force, equal to the gravitationalunloading from the rocks. Based on the solution to Boussinesq's problem for surface loading/unloadingon an isotropic elastic half‐space (Selvadurai, 2001), we compute the stress tensor on the fault caused bythe vertical forces. The summed stress tensor is then projected on the fault to compute the change of normaland shear stresses. These perturbations are used in equation (1) to calculate the Coulomb stress changes.

The Coulomb stress changes on the fault along the slip direction for the seismic and geodetic (InSAR) solu-tions are shown in Table S3. The result on the NE dipping fault shows a bull's‐eye shaped Coulomb stresschange pattern, with peak values almost overlapping with static slip model (Figure 4). The maximumCoulomb stress change is 0.11 MPa, much larger than the typical threshold of 0.01 MPa, which is consideredto be able to trigger a seismic event (Brodsky & Prejean, 2005; Lockner & Beeler, 1999). Our Coulomb stresschange analysis suggests a clear positive triggering relation between the unloading and the earthquake.

4. Discussion

An interesting aspect of the Dianjiang earthquake is the lack of topography signature for the ruptured fault.The geomorphology in this part of the Sichuan Basin is dominated by a sequence of NE/SW oriented

Figure 3. The inversion results for the NE (a) and SW (b) dipping fault planes. The downsampled InSAR observations (first and second columns), synthetics (thirdcolumn), and the differences (fourth columns), with the center of upper edge located at a depth of 1.1 km.

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anticlines and NW/SE verging Miocene thrust basement faults along anticlines under SE/NW orientedcompressional stress (Figure 1a; Li et al., 2015). The thrust focal mechanism of the Dianjiang earthquakeseems consistent with the compressional background stress in the crust. But, this event was not locatedon these basement faults, and the strikes of the fault plane solution (281° or 97°) do not agree with theorientation of these anticlines (Figure 1a). Therefore, these existing but inactive faults did not host theearthquake. In fact, we did not find any topographic feature consistent with the strikes in the focalmechanism. Alternatively, the Dianjiang earthquake is likely related to a localized stress heterogeneity onan unidentified blind fault.

Previous studies have reported some shallow earthquakes in the southern Sichuan Basin in the vicinity ofthe oil and gas wells, mostly triggered by hydraulic fracturing (e.g., Lei et al., 2008, 2017). However, the clo-sest oil and gas wells with associated induced seismicity are located at least 40 km away from the Dianjiangearthquake. Therefore, we can rule out the possibility that the earthquake was related tohydraulic fracturing.

Unlike the Kalgoorlie Consolidated Gold Mine super pit (1.5 km × 3.5 km × 600 m) case (Dent, 2015), theunloading volume for the automotive testing site in Dianjiang (1 km × 1 km × 10 m) was much smaller.This kind of small‐scale infrastructure construction is much more frequent worldwide. In fact, very fewearthquakes have been associated with such human activities. An important aspect of this testing site con-struction was the removal of a large volume of surface rock, up to 20 m (Figures 1b and 1c). Such a feature isprobably quite different from many other similar‐scale constructions worldwide, thus the unloading mightbe responsible for the occurrence of the Dianjiang earthquake. However, while surface rock removal or hill-top leveling may not apply to all similar‐scale construction, it is not uncommon in the Chongqing province,where the Dianjiang earthquake occurred. Therefore, unloading tens of meters of surface rock was probablynot the sole reason for this earthquake. Thus, the stress condition in the shallow part of the crust at the loca-tion of the earthquake must have been near failure. The absolute stress in the crust is not well known in gen-eral, which impedes better estimates of the triggering potential and of seismic hazard. Given that this regionof the Sichuan Basin was highly deformed in the past by the compressional stress, as is evident in theMiocene topography (Figure 1a), it is likely that local stress in the shallow crust is still highly heterogeneous.The combination of these two factors is possibly responsible for the Dianjiang earthquake.

The Dianjiang earthquake and other shallow earthquakes (e.g., Brune & Allen, 1967; Wei et al., 2015)indicate that earthquakes can still nucleate in the shallow crust. The stress at shallow depth is consideredquite different from the seismogenic depth range. The shallow crust (<5 km) is commonly viewed as slipstrengthening, and therefore earthquakes are less likely to nucleate there (Scholz, 2002). Nevertheless, sev-eral shallow earthquakes have been reported in the Sichuan Basin, in connection with stress perturbations

Figure 4. 3‐D view of the NE dipping fault and Coulomb stress change. The dashed line on the fault shows the slip area ofstatic model (1.2 km2). Based on the preferred mechanism, the Coulomb stress change caused by the unloading is colorcoded. The rock layer is approximated by a 10 m high hexahedron with an area of 1.0 km2. The Coulomb stress changepeak value is 0.11 MPa. The result for the conjugated fault is shown in Table S3.

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induced by large earthquakes or hydraulic fracturing. For example, the Ms5.7 Wenchuan aftershock in thewestern Sichuan Basin was located at 3 km depth (Luo et al., 2010); theMs5.1 Suining‐Tongnan earthquakein the center of the Sichuan Basin had a centroid depth of 2 km (Luo et al., 2011); the ML3.8 Chongqingearthquake in the eastern Sichuan Basin was as shallow as 3 km (Han et al., 2017), and more inducedearthquakes with similarly shallow depth (Lei et al., 2019). It seems that the Sichuan Basin is probablyconditionally slip strengthening or even slip weakening, so that shallow earthquakes in this stable regioncan be often triggered by transient local stress perturbations or fault strength variety due to externalenvironmental changes.

Another interesting observation is that the Dianjiang earthquake was not followed by any detectable after-shock, based on the CSN/CENC catalogs, which are complete forM > 1.5 earthquakes. We have confirmedthis by conducting a high‐frequency envelope analysis (Figures S11–S14) and template matching detection(Figure S15), which indicate that most of the stress accumulated on the fault was released, or the nearbystress field is not close to failure. To quantify the stress perturbation caused by this event, we use theInSAR slip model and the Coulomb3.3 program (Lin & Stein, 2004; Toda et al., 2005) to calculate theCoulomb stress changes at different depths. The result shows that the region with a Coulomb stress changelarger than 0.01 MPa was confined approximately within a 3 km × 3 km × 3 km volume (Figure S16).Absence of an aftershock suggests that either the remaining parts of this volume are not critically stressedor the other faults may be slip strengthening.

Although we show that the Coulomb stress change caused by unloading was much bigger than the thresholdof triggering, the earthquake did not occur until ~2 years after the construction had been finished. This timelapse raises the question of what factors contributed to the delayed triggering. One explanation widely usedto interpret delayed triggering in the case of injection‐induced seismicity is fluid migration (e.g., Keranenet al., 2013). Similarly, a possible explanation is that the construction removed the vegetation cover, thus cre-ated or exposed pathways for surface water to migrate to the depth of 1 km. However, this hypothesisrequires further supports, the delayed triggering mechanism awaits further investigation.

Our study shows the feasibility of applying stacked InSAR images to reveal subcentimeter coseismic surfacedeformation. The Sentinel‐1's revisit time of 6 days enables acquiring sufficient images for stacking toimprove the signal‐to‐noise ratio of coseismic deformation, which is particularly useful for small and shal-low inland earthquakes. Stacking InSAR images opens the possibility for detailed studies of this kind ofearthquakes by combining seismological and geodetic observations: Seismograms can constrain magnitudeand focal mechanism well, while synthetic aperture radar interferograms provide high spatial resolutions.By combining these two data sets, one can minimize the ambiguities and uncertainties of source properties,as well as study other geophysical processes that can be both recorded by good seismic observations and geo-detic surface deformations.

5. Conclusion

In this study, we have investigated the 11 August 2016 Mw4.1 Dianjiang earthquake in the eastern SichuanBasin (China) using multiple data sets. Seismological and geodetic evidence supports a thrust focal mechan-ism with a centroid depth of ~1 km. Surface deformation revealed by the stacked interferograms is highlyconsistent with the location of a small‐scale infrastructure constructed about 2 years before the earthquake.Our Coulomb stress change analysis indicates that the unloading of hills leveled during the infrastructureconstruction caused up to 0.11 MPa stress change on the ruptured fault. We suggest that this shallow earth-quake was triggered by the unloading from the small‐scale infrastructure construction just above a blindfault with concentrated compressional stresses.

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AcknowledgmentsWe thank the Associate Editor GavinHayes, Wanpeng Feng, and oneanonymous reviewer for theirconstructive comments andsuggestions. We thank Pavel Adamekfor his help on the writing. Regionalseismic data were provided by theChongqing Seismological Bureau, andcan be downloaded from MendeleyData repository https://data.mendeley.com/datasets/r2nbw8mvzk/draft?a=1e9334b1‐f0ac‐4a63‐bb82‐2678cab15274, which has a reservedDOI (https://doi.org/10.17632/r2nbw8mvzk.1). Teleseismic data wereobtained from the IncorporatedResearch Institutions for Seismology(DOIs: https://doi.org/10.7914/SN/IIand https://doi.org/10.7914/SN/IU).Sentinel‐1 SAR images in ascendingtrack DT175 were downloaded from theSentinel‐1 Scientific Data Hub (https://scihub.copernicus.eu). The figures weregenerated using GMT software (Wessel& Luis, 2017). Google Earth Pro helpedthis study. Yunyi Qian is supported bythe National Natural ScienceFoundation of China (41904052) andthe China Postdoctoral ScienceFoundation (2019M652198). XiaofeiChen is supported by the NationalNatural Science Foundation of China(41790465). Shengji Wei is supported bythe Singapore MOE project (MOE2019‐T2‐1‐182).

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