Seismic velocity changes in the epicentral region of the 2008 Wenchuan earthquake measured from three-component ambient noise correlation techniques

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1 GEOPHYSICAL RESEARCH LETTERS, VOL. 41, 37 42, doi: /2013gl058682, 2014 Seismic velocity changes in the epicentral region of the 2008 Wenchuan earthquake measured from three-component ambient noise correlation techniques Zhikun Liu, 1,3 Jinli Huang, 2 Zhigang Peng, 4 and Jinrong Su 5 Received 13 November 2013; accepted 4 December 2013; published 8 January [1] We investigate temporal changes of seismic velocity in the epicentral region of the 12 May 2008 M w 7.9 Wenchuan earthquake using three-component continuous waveforms recorded by a seven-station small-aperture array. We use an ambient noise cross-correlation technique to compute the empirical Green s function between station pairs from August 2004 to September Our results show no obvious precursory change immediately before the main shock, clear coseismic reduction of seismic velocity of up to 0.2%, and initial postseismic recovery followed by a long-lived velocity reduction. The coseismic and postseismic velocity changes are most prominent in the period band of 2 4 s (approximate depth of 1 4km), and the velocity changes are smaller in other period bands. The seismic velocity in the period band of 1 2 s (i.e., top 2 km) correlates well with the water level change of the Zipingpu Reservoir. The observed temporal changes likely reflect damage and healing processes with possible permanent deformation in the upper crust associated with the Wenchuan main shock. Citation: Liu, Z., J. Huang, Z. Peng, and J. Su (2014), Seismic velocity changes in the epicentral region of the 2008 Wenchuan earthquake measured from three-component ambient noise correlation techniques, Geophys. Res. Lett., 41, 37 42, doi: /2013gl Introduction [2] It has been shown that cross correlation of ambient noise recorded at two stations results in an empirical Green s function (EGF) that mimics the impulse response between them [e.g., Lobkis and Weaver, 2001]. Because of the high similarities of the EGFs at different time periods, many studies have used ambient noise cross-correlation (ANCC) technique to detect temporal changes in the crust. These include seasonal Additional supporting information may be found in the online version of this article. 1 School of Earth and Space Sciences, University of Science and Technology of China, Hefei, China. 2 School of Geophysics and Information Technology, China University of Geosciences, Beijing, China. 3 Institute of Earthquake Science, China Earthquake Administration, Beijing, China. 4 School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA. 5 Earthquake Administration of Sichuan Province, Chengdu, China. variations [e.g., Sens-Schönfelder and Wegler, 2006; Meier et al., 2010], velocity changes related to the volcanic eruptions [e.g., Brenguier et al., 2008a], slow slip events [Rivet et al., 2011], and occurrence of nearby large earthquakes [e.g., Brenguier et al., 2008b; Wegler et al., 2009; Zhao et al., 2010; Chen et al., 2010; Liu and Huang, 2010; Zaccarellietal., 2011; Takagi et al., 2012; Schaff, 2012; Hobiger et al., 2012]. [3] Several recent studies have used the ANCC technique to examine temporal changes of seismic velocity around the 12 May 2008 M w 7.9 Wenchuan earthquake in southwestern China. The main shock occurred along the boundary between the eastern Tibet plateau and the Sichuan Basin (Figure 1a). It generated a 240 km surface rupture along the Yinxiu-Beichuan fault and another 72 km rupture along the Pengguan fault [Xu et al., 2009]. Based on surface waves of cross-correlated ambient noise recorded by the Sichuan Regional Seismic Network (SRSN), Cheng et al. [2010] found that the coseismic velocity drop was located in the deep rupture area of the Longmenshan Fault. Liu and Huang [2010] used the same data but measured the velocity changes from the coda of EGF in the 2 10 s period band. They found clear coseismic velocity drop in the Sichuan Basin, whereas only small fluctuation was detected in the Tibetan Plateau. This spatial pattern of coseismic change was confirmed by using a dense Western Sichuan Seismic Array (WSSA) around the southern section of the Longmenshan region [Chen et al., 2010]. By comparing the velocity changes in the s period band with 1 3 s period band using data from WSSA, Froment et al. [2013] suggested that the measurements at the longer period may reflect the deformation in the middle crust following the Wenchuan main shock. [4] In these studies, the average station spacing for the SRSN and WSSA is about 50 and km, respectively, and most stations are relatively far from the epicenter and surface ruptures of the Wenchuan main shock (Figure 1). Hence, they may not be dense enough to detect temporal changes associated with the main shock rupture zone, especially possible preseismic changes. In this study, we use cross correlations of 7 years of three-component waveforms from a small-aperture seismic array near the epicentral region of the Wenchuan earthquake. We obtain preseismic, coseismic, and postseismic velocity changes in different period bands. Based on these results, we further discuss possible physical mechanisms of velocity changes in this region. Corresponding author: J. Huang, School of Geophysics and Information Technology, China University of Geosciences, No. 29 Xue Yuan Rd., Beijing , China. (huangjl@cugb.edu.cn) American Geophysical Union. All Rights Reserved /14/ /2013GL Data and Method [5] The seismic data used in this study were recorded by seven short-period stations in the Zipingpu Reservoir Seismic Network (ZRSN) and one broadband station YZP 37

2 Figure 1. (a) A map showing the study region along the rupture zone of the Wenchuan earthquake. The black triangles denote seismic stations from Zipingpu Reservoir Seismic Network (ZRSN). The gray and white triangles denote seismic stations in previous studies from Sichuan Regional Seismic Network (SRSN) and Western Sichuan Seismic Array (WSSA), respectively. The big star and red dots represent the Wenchuan main shock and aftershocks. The dashed black and solid lines indicate the coseismic surface ruptures and active faults, respectively. (b) An enlarged map showing seismic stations around the epicentral region of the Wenchuan main shock. Seven stations used in this study are black fonts including one station from SRSN and six stations from ZRSN. The station, TZP, with red font was damaged during the 2008 M w 7.9 Wenchuan main shock. The blue area indicates the Zipingpu Reservoir. All other symbols are the same as in Figure 1a. from the SRSN. The ZRSN was designed to monitor the seismicity around the Zipingpu Reservoir and was deployed in bedrocks around the epicentral region of the Wenchuan main shock. All stations have the same short-period sensor (RSFS-1A, 1 Hz) and data acquisition (EDAS-24 L) system, and the data are recorded at 100 samples per second. Station TZP was damaged during the Wenchuan earthquake, so we only have six stations in the ZRSN for further analysis. In this study, we use three-component continuous waveforms recorded by the ZRSN from August 2004 to September The network missed data in the first 2 months of 2010, and stations LYS and BAY were down in September 2010 and June 2011, respectively. We also include station YZP from the SRSN because it is the closest station to the ZRSN. It has a CMG-3ESPC sensor (120 s), and the data acquisition system is EDAS-24IP. Data are available at this station from January 2007 to September The average interstation spacing of these seven stations is about 10 km, and the distance between the closest station (BAJ) and the main shock epicenter is less than 5 km. Two separate branches of the main shock surface rupture passed through thearray(figure1b). [6] The analysis procedures generally follow those of Liu and Huang [2010] and are described below. We first check the polarity and orientations of the three-component sensors by analyzing particle motions of teleseismic P waves for all the stations (see Figures S1 and S2 in the supporting information). All stations from ZRSN show a ~180 flip of the particle motions around 10 August 2007, indicating a reversal in the orientations of the two horizontal components. We correct the misorientation of all the stations in the entire study period. Next we downsample the daily three-component data to 10 samples per second and band-pass filter between 0.8 and 10 s. The two horizontal components are rotated to the radial (R) and transverse (T) directions for each station pair. Then we calculate the daily correlation functions (CF) of all nine components (ZZ, TT, RR, ZT, TZ, TR, RT, RZ, and ZR) for each station pair. [7] The reference CF for each station-component combination is obtained from the stack of all the CFs starting from August 2004 to right before the Wenchuan earthquake. This allows us to quantify possible coseismic and postseismic changes relative to the pre-main shock level. Next, we stack the daily CFs to obtain stable coda waves for measuring temporal changes. We define a current CF as a stack of 51 day data, which contains the current daily CF and 25 day daily CFs before and after the current day, respectively. To avoid mixing of preseismic and postseismic signals, we do not allow a stacking window that includes the main shock occurrence day. For example, the current CF on 28 May 2008 is obtained from stacking only postseismic daily CFs from 13 May 2008 to 12 June Thus, the window length is smaller for the 25 days before and after the main shock, resulting in a larger error as compared with other time windows. [8] Figure S3 shows an example of the stacked reference and daily CFs for station pair GHS-LYS in the TT component. Strong direct wave energies are shown in both positive and negative parts of CFs with weak seasonal variations. Most coda waves are stable and coherent in the entire study period. Because the direct waves may contain the effect of seasonal change of seismic noise sources [Stehly et al., 2007], we only use coda part of CFs ( s) to estimate the velocity change in this work, similar to those used in previous studies [Chen et al., 2010; Hobiger et al., 2012]. [9] The relative velocity changes between the current and reference CFs for each station-component combination are estimated using a moving-window cross-spectrum technique [e.g., Brenguier et al., 2008a] in the 1 8 s period band (see supporting information). Figure 2a shows an example of the temporal changes for nine components of the CFs at the station pair GHS-LYS. Although the velocity changes show variations at different components, their overall shapes are similar. Hence, we average all nine components to obtain a mean velocity change for a station pair. Such average further increases the stability and accuracy of the velocity change measurements (Figure 2b). 38

3 of early aftershocks, the measurements are more scattered in the first month after the main shock (Figures S5 S7). Thus, we average 2 months of measurements after the main shock to compute an apparent coseismic velocity change for each station pair. Figures 4a 4c show spatial variations of the coseismic velocity changes for three period bands. Again, the largest coseismic changes are shown in the period of 2 4 s, which corresponds to the sensitivity depth of ~1 4 km (Figure 4d). We do not find coseismic velocity increase for any station pair Postseismic Velocity Changes [12] Figure 3b shows postseismic velocity changes in logarithmic time scale. The seismic velocity overall recovers in approximate logarithmic form in first tens of days after the main shock. Among the three subbands, the period band of 2 4 s shows the best postseismic signal, whereas the period band of 1 2 s has the strongest fluctuation. [13] We also find that the velocity reduction is almost constant following the initial postseismic recovery. The velocity reductions for more than 3 years after the main shock in the period band of 2 4 s and 4 8 s are 0.13% and 0.08%, respectively. The long-lived velocity reduction is also observed at the closest station pair from SRSN (Figure S8). Figure 2. The relative seismic velocity changes for station pairs GHS-LYS in the period band of 1 8 s. (a) The nine panels show the measurements for different components. The name of component is shown at the lower left corner of each panel. The vertical dashed line denotes the time of the Wenchuan main shock. The colors of points indicate the errors of measurements, and the error scale is shown at the right. (b) The mean velocity change for station pair GHS-LYS, which is obtained by averaging over nine component combinations. [10] Figure S4 shows the mean velocity changes for all 21 station pairs in the 1 8 s period band. Because the coda of a CF is primarily composed of surface wave [Froment et al. 2013], the depth sensitivity of velocity change depends on its periods. In the period of 1 8 s, surface waves have a wide range of depth sensitivity from hundreds of meters to about 8 km. Hence, we estimate the velocity changes in three subbands (1 2s,2 4 s, and 4 8 s) and use them to constrain the depth extent of the temporal change (Figures S5 S7). Since the temporal changes for most station pairs are similar, we further average these measurements to obtain a mean velocity change in the epicentral region (Figure 3a). 3. Results 3.1. Coseismic Velocity Changes [11] Figures 3 and S5 S7 show that the seismic velocity dramatically decreased at the time of the main shock in all period bands. The largest coseismic deduction, ~0.2%, is observed in the period band of 2 4 s. However, due to short-length stack of current CF and potential contaminations 3.3. Preseismic Velocity Changes [14] Before the main shock, the velocity change is around zero point with 2 standard deviation (2σ) of less than 0.01% in the period of 1 8 s. The largest variations for three subbands is in the period band of 4 8s,with2σ of ~0.03%, which indicates that the preseismic velocity changes are stable. [15] We note that the seismic velocity gradually increased in the last half year before the main shock in the period band of 1 2 s. However, a close comparison between the seismic velocity change in this period and the water level of Zipingpu Reservoir reveals a clear correlation (Figure 5), especially after the impound in October 2005 (with correlation coefficients (CC) value of 0.50 and p value less than 0.001). Hence, the variations in the 1 2 s period band right before the main shock are likely associated with the water level change, rather than reflecting any precursory velocity changes in the epicentral region before the Wenchuan main shock. 4. Discussions [16] Temporal changes of velocities associated with large nearby earthquake have been observed at various depth range. Using both repeating earthquakes and ANCC techniques, many studies have shown that temporal changes were mainly constrained in the top few hundred meters of the upper most crust [e.g., Rubinstein and Beroza, 2004; Peng and Ben-Zion, 2006; Wegler et al., 2009; Zaccarelli et al., 2011; Takagi et al., 2012]. Such observations are generally associated with opening of fractures under large ground motions, resulting in a nonlinear site response [Beresnev and Wen, 1996]. In addition, temporal changes associated with active fault zones have also been identified from systematic analysis of repeating earthquakes around recent ruptures [e.g., Rubinstein et al., 2007; Zhao and Peng, 2009]. The inferred depth extent of the temporal change ranges from a few kilometers to up to bottom of the seismogenic zone and is likely associated with damages generated by the dynamic ruptures of large earthquakes. 39

4 Figure 3. (a) The mean seismic velocity changes in the epicentral region of the Wenchuan earthquake estimated in the period band of 1 8 s and three subbands. The period band is shown at the top left corner of each panel. The vertical dashed lines denote the times of the Wenchuan main shock, and the horizontal dashed lines mark the zero levels. (b) Postseismic velocity changes plotted in semilogarithmic time scale. Figure 4. (a c) The coseismic velocity changes in the period band of 1 2 s, 2 4 s, and 4 8 s, respectively. The coseismic changes are obtained from averaging the measurements for a period of 2 months after the main shock minus the average level before the main shock. The color of a line connecting two stations indicates the magnitude of velocity change between these stations. The dashed lines indicate the two branches of main shock surface rupture. (d) Rayleigh wave velocity sensitivity in the period ranges of 1 to 8 s in our study region. 40

5 Figure 5. (a) The comparison between the water level of the Zipingpu Reservoir and the velocity changes in the period of 1 2 s. The numbers in the figure are the correlation coefficients (CCs) between water level and seismic velocity at three time periods. These include before the reservoir impoundment, from the impoundment to the main shock, and after the main shock. [17] If the velocity change obtained in the epicentral region is caused only by nonlinear strong ground motion, we should have observed that the largest velocity deduction occurred in shallow layer (i.e., top 2 km) in the period of 1 2s. However, the largest coseismic change was detected in the period band of 2 4 s, which corresponds to the sensitivity depth of 1 4 km (Figure 4d). In the period band of 4 8s, the coseismic velocity deduction is somewhat smaller but is still similar to the level in the period band of 1 2 s. These observations are slightly different to the recent work of Hobiger et al. [2012] for the 2008 M w 6.9 Iwate-Miyagi Nairiku earthquake, where they observed the largest temporal changes in the shortest period band of 1 2s. Hence, in our study region near-surface damage likely contributes but is not the dominant mechanism to explain the observed coseismic changes associated with the Wenchuan main shock. [18] Detailed seismic reflection data in our study region have shown that the depth of Precambrian basement is approximately 4 km [Hubbard et al., 2010]. In addition, a recent seismic tomography study [Li et al., 2011] using the same ZRSN data revealed a low-velocity zone beneath the Zipingpu Reservoir up to 3.5 km, and the area between the Yinxiu-Beichuan and Pengguan faults is mostly covered by Proterozoic sedimentary rocks. Their study also identified a low-velocity zone extending up to 6 km around these active faults. [19] Although we detected significant coseismic velocity changes in different period bands in the epicentral region, we could not accurately locate the exact region with the largest velocity change, largely due to the inadequate raypaths. Nevertheless, we suggest that the observed temporal changes in the top 4 km are likely associated with a combined effect of damages in shallow sedimentary rocks and around active faults. This interpretation is generally consistent with a recent simulation of widespread damage in the shallow crust and a flower-like damage zone near the fault that ruptured during large earthquakes [Ma, 2009]. Unfortunately, because of our use of short-period data, the temporal changes observed in the periods longer than 8 s is rather unstable (Figure S9). Hence, we are unable to detect temporal changes in the middle and lower crust, as was done by Froment et al. [2013]. [20] The initial recovery in the first tens of days after the main shock may reflect a fast-healing process of the coseismically damaged rock [e.g., Wang et al., 2010]. After that, it was followed by a near-constant level in all three periods. By the end of the analyzed time period at nearly 2000 days after the main shock, only 50% of the coseismic reductions have been recovered, suggesting either a very slow recovery process or a permanent damage in the shallow crust. Similar long-term recovery processes in the shallow crust were also observed after the 2008 M w 6.9 Iwate-Miyagi Nairiku earthquake [Hobiger et al., 2012] and after the 2011 M w 9.1 Tohoku-Oki earthquake [Wu and Peng, 2012]. These observations suggest a possible two-stage recovery process with different mechanisms. [21] In this study, we found that the correlation between velocity change in the period of 1 2 s and the water level of the Zipingpu Reservoir is weak (with CC value of 0.26) before the start of reservoir impoundment in October After that, we observed a clear negative correlation through the rest of the analyzed time period. That is, seismic velocity reduces when the water level is high, and vice versa. This is similar with other recent observations of variations in seismic velocity with ground water levels [e.g., Sens-Schönfelder and Wegler, 2006; Meier et al., 2010] and is consistent with the Biot theory that pore fluid should increase compressional velocity and decrease shear velocity of rocks [Biot, 1956]. Hence, the subtle velocity increase starting in January 2008 was most likely caused by a reduction in the water level height, rather than reflecting any precursory temporal changes before the Wenchuan main shock. [22] Finally, we note that the variation in the seismic velocity after the Wenchuan earthquake is significantly increased (by a factor of 3.8) as compared with before the main shock (Figure S10), indicating an increase of sensitivity to the water level change of the reservoir. We hypothesize that opening of fractures in shallow crust by strong shaking of main shock may significantly increase permeability or water mobility [Xue et al., 2013], which could in turn enhance the impact of water level on velocity change. 5. Conclusions [23] In this study, we used continuous waveforms recorded by seismic stations close to the epicenter of the 2008 Wenchuan earthquake, to study the temporal change of seismic velocity before, during, and after the main shock. Based on all possible station-component combinations of ANCC, we estimated the velocity change in the 1 8 s period band and its three subbands (1 2s, 2 4 s, and 4 8 s). The main shock produced a sudden drop of seismic velocity of up to 0.2% and followed by an initial fast recovery and then slow recovery or permanent damage. The patterns of coseismic and postseismic velocity changes vary with depth. In the 2 4 s period band, the coseismic drop is larger and postseismic recovery is slower than the other two bands. The velocity changes in the top 2 km (1 2 s period band) 41

6 correlate well with the water level change of the Zipingpu Reservoir since its impoundment in Hence, the subtle increase of seismic velocity in the 1 2 period band at the beginning of 2008 was likely associated with the seasonal variation of the water height, rather than reflecting any preseismic changes at the epicentral region of the Wenchuan main shock. [24] Acknowledgments. We are grateful to Xueze Wen, Lifeng Wang, Min Wang, and Maining Ma for helpful discussions. We thank Xianming Hu for providing water level data. We also thank David Schaff and an anonymous reviewer for their constructive comments on the paper. This research is supported by NSFC , , and and Basic Research Project of Institute of Earthquake Science, CEA (2011IES0201). Z.P. is partially supported by NSF CAREER award EAR [25] The Editor thanks David Schaff and Michel Campillo for their assistance in evaluating this paper. References Beresnev, I. A., and K. L. Wen (1996), Nonlinear soil response A reality?, Bull. 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