POSTSEISMIC DEFORMATION IN SOUTH ICELAND STUDIED USING MULTIPLE ACQUISTION RADAR INTERFEROMETRY

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1 POSTSEISMIC DEFORMATION IN SOUTH ICELAND STUDIED USING MULTIPLE ACQUISTION RADAR INTERFEROMETRY Sigurjón Jónsson (1), Jörn Hoffmann (2), Thóra Árnadóttir (3) (1) Institute of Geophysics, ETH Zurich, Schafmattstr. 30, 8093 Zurich, Switzerland, (2) DLR, Space Agency, Königswinterer Str , Bonn, Germany, (3) Nordic Volcanic Center, University of Iceland, Sturlugata 7, 101 Reykjavík, Iceland, ABSTRACT Models of two different postseismic mechanisms, viscoelastic relaxation and afterslip, can both explain yearly GPS observations following two magnitude 6.5 earthquakes that occurred in South Iceland in 2000, as these models predict very similar horizontal displacements. However, the predicted vertical displacements of these models differ, and thus good information about the vertical displacements is needed to distinguish between these competing explanations. Within this project we attempt to retrieve information about the vertical deformation using persistent scatterer (PS) interferometric analysis with 32 ERS-2 SAR scenes of the area from However, the results of the PS analysis were limited as the work was hampered by a typically low density of stable points in this rural farming area and by large Doppler centroids. More success was achieved by using a small baseline approach with ~25 multilooked and filtered interferograms that were unwrapped and then used in time-series analyses. 1. INTRODUCTION Large earthquakes cause major stress changes in the surrounding crust leading to triggered quakes and aftershocks. Several time-dependent postseismic processes can further alter the stress state and change the tendency for triggered future events. Such processes may include: viscous flow of the lower crust and upper mantle (e.g., [1]), (2) afterslip on the mainshock rupture (e.g., [2]), (3) pore-fluid flow caused by coseismic pore-pressure changes (e.g. [3]), and delayed response of the triggered fault as predicted by rate and state friction [4]. Despite considerable efforts, it has proven difficult to distinguish between these postseismic mechanisms for virtually all of the world s recent major strike-slip earthquakes [5]. However, observations of postseismic deformation following the two June 2000 South Iceland Seismic Zone (SISZ) earthquakes have provided a unique opportunity to enhance our understanding of these processes in general [6,7]. The two magnitude 6.5 SISZ earthquakes occurred on June 17 th and June 21 st, 2000, and led to triggered events and increased seismic activity over a large area in southwest Iceland [8,9]. Earthquakes in the SISZ are caused by left-lateral transform motion across the area due to spreading on Reykjanes peninsula and in central Iceland [10,11]. However, this transform motion is not accommodated by one large east-west striking left-lateral transform fault, but by many north-south striking right-lateral faults [12]. The earthquakes in 2000 occurred on two of these faults (Fig. 1). Figure 1: Shaded relief map of the study area showing surface ruptures of the two north-south faulting earthquakes [13]. Inset shows the approximate location of the active plate boundary in Iceland with a full spreading rate of 1.94 cm/year, indicating leftlateral transform motion across the SISZ. Both GPS measurements and satellite radar acquisitions were carried out shortly after the SISZ earthquakes to record postseismic deformation. During the first few months the deformation was dominated by localized displacements (within 5-10 km from the faults), showing quadrants of uplift and subsidence around the two faults [6]. This pattern of deformation was caused by postseismic groundwater pressure changes during the time when co-seismic pore-pressure changes were dissipating [6]. This poro-elastic transient deformation was not long lived; it lasted only 2-3 months, which is in an agreement with water-level recovery recorded in many boreholes in South Iceland. Yearly GPS measurements in south Iceland have revealed another pattern of postseismic Proc. Envisat Symposium 2007, Montreux, Switzerland April 2007 (ESA SP-636, July 2007)

2 deformation that had much slower decay than the poroelastic relaxation [7]. This transient extended at least 30 km away from the two faults and showed deformation at a decreasing rate from 2000 to The primary displacement pattern had GPS stations to the east move southward and stations to the west move northward, indicating a right-lateral overall motion across the two faults. Reference [7] explored mainly two different mechanisms to explain this longer-term postseismic deformation pattern. The former is viscoelastic relaxation of a layered medium below the elastic part of the crust that responds to sudden stress changes induced by the two earthquakes. The latter mechanism is postseismic slip (or afterslip) in the lower-crust on downward extensions of the two coseismic fault rupture planes. The idea behind this mechanism is that concentrated shear stresses at the bottom of the co-seismic faults induce aseismic slip that decays with time. Reference [7] found that models of both mechanisms are able to predict GPS observations equally well, making it impossible to reject one of these two potential explanations. Figure 2: Vertical displacement-rate predictions of visco-elastic (left) and afterslip (right) models for , based on models estimated from GPS observations [7]. This problem of distinguishing between potential postseismic mechanisms after large strike-slip earthquakes is not new and has been a subject of many recent debates [5], e.g. in cases of the 1992 Landers and 1999 Hector Mine earthquakes in Southern California. Several authors have reported afterslip as the primary mechanism after large strike-slip earthquakes (e.g. [2,14]), while others have argued for viscoelastic relaxation (e.g. [1,15,16]). The reason for this problem, both in Iceland and elsewhere, is that the horizontal displacement fields that models of these two mechanisms predict can be almost identical [7], which makes it impossible to reject one of the two mechanisms based on the horizontal GPS velocities alone. However, even though the horizontal displacement fields can be very similar, the corresponding vertical displacement fields differ (Fig. 2). Therefore, good information about vertical displacements field is the key additional information needed to be able to distinguish between these competing hypotheses. Observed vertical GPS displacements are usually poor and the Icelandic postseismic GPS observations are in this no exception [7]. Also, multiyear conventional InSAR has proven unsuccessful in the SISZ, primarily due to agricultural activities in the area. Therefore, in this project we attempt to retrieve reliable information about vertical postseismic displacements in the SISZ by using multiple acquisition SAR interferometry. Here we report on our efforts, both in using persistent scatterers and a smallbaseline approach. 2. RADAR DATA PROCESSING We ordered ERS-1/2 radar data acquired above South Iceland from descending track 324 as it covers the entire study area and as this track includes the largest number of suitable radar scenes from the postseismic period. We ordered 32 scenes from and we also ordered another 32 radar scenes from before the earthquake (Fig. 3). In the data processing we tested three different approaches to retrieve information about the postseismic deformation field in South Iceland. In the first two attempts we used different Persistent Scatterer Interferometry (PSI) software packages, the Interferometric Point Target Analysis (IPTA) package from Gamma Remote Sensing and PSI-GENESIS package developed at DLR. In our third approach we applied time-series analysis on many standard small-baseline interferograms. The conditions for using PSI analysis on this data set are far from being optimal and it is hampered by a typically low density of stable points in this rural farming area and the fact that the postseismic period falls within the time period for which ERS-2 SAR data are frequently unusable due to large Doppler centroids. Furthermore, winter snow, a poor Digital Elevation Model (DEM), and the expected non-linear deformation rate add to the complications in this case. Some parts of the SISZ remain coherent in standard interferograms that span several years, mainly due to limited vegetation cover, and therefore, we also explored if we can use a time-series analysis of conventional interferograms to retrieve the needed information about the vertical deformation DLR-PS Despite the difficult conditions for the application of PSI discussed above we attempted to process the ERS SAR data using the PSI-GENESIS software. We selected the acquisition on September 29, 1999 as a master scene. Importantly, this acquisition was made prior to the failure of the gyroscope on ERS-2.

3 Consequently, interferograms spanning time periods before the earthquakes generally had low differential Doppler values. Unfortunately, this also leads to large Doppler values and corresponding high phase noise at scatteres in many interferograms spanning the earthquakes. After selection of permanent scatterers by a signal-to-clutter ratio criterion [17], only 791 PS remained in the area of interest an extremely small number. The large average distances between the points lead to uncertain parameter estimates that are likely due to significant differential atmospheric effects between neighboring points. To avoid errors in the overall parameter values during parameter integration, statistical testing was used to remove points that could not be connected to others via connections (arcs), for which a robust parameter estimation was possible [18]. Only 553 points remained, for which parameter estimates were possible. Figure 3: Spatio-temporal baseline plot of ERS-1/2 descending track 324 showing pre-seismic (orange) and postseismic (green) interferograms. The red vertical bar marks the time of the earthquakes and gray shades indicate winter months. The next steps in the PSI-analysis would be to separate the effects of atmosphere and, critical to this investigation, the non-linear displacement. Unfortunately, we deemed the statistical descriptions for this separation to be unreliable given the very low density of points, particularly in the region close to the two earthquake fault traces. Furthermore, given the very low density of points in the area, it is uncertain how much constraint these data could offer to constrain models. We therefore did not pursue this analysis further IPTA Analysis In our IPTA analysis we encountered similar problems as in the PSI-GENESIS analysis. However, local analyses near towns proved to be successful as there the number of PS was sufficient to unwrap the phase reliably. We carried out such analysis near the towns of Hella and in Vestman islands. In both cases we did not detect any deformation within the towns. But due to the problems with the larger-scale analysis we did not continue further with this approach Small Baseline Approach In our small baseline approach we used the coregistered SLCs and formed most possible combinations of small-baseline standard differential interferograms using the Gamma software (Fig. 3). The interferograms have perpendicular baselines of up to 600 m and temporal baselines varying from one day to 5 years. The time-series analysis was carried out in two separate parts, using 82 pre-earthquake and 40 post-earthquake interferograms (Fig. 3). Many postearthquake radar scenes and possible small-baseline interferograms could not be included in the time-series analysis due to incompatible Doppler centroids. The collection of interferograms clearly shows that some areas retain good interferometric correlation over several years while other areas become decorrelated within a few months. The most stable area is to the east of the earthquake faults and the northern half of the image, although the latter area is at a higher elevation and is sometimes affected by snow. The area to the south of and around the earthquake faults stays coherent for only a few months, at the most, due to agricultural activities. The expected deformation signal is interseismic and postseismic deformation, which both have long spatial wavelengths. Therefore, to reduce the interferogram noise we multilooked all the differential interferograms to 32 looks in range and 5x32 looks in azimuth, resulting in ~640m pixel spacing, and then filtered them for further noise reduction. This was followed by unwrapping and a visual inspection to correct obvious unwrapping mistakes or to eliminate interferograms containing too many unwrapping errors. For each pixel in the stack of interferograms we estimate the unwrapped phase (model vector m) at the time the radar scene was acquired using the following system of coupled linear equations: d G = γ m 0 D (1) where d is the data vector containing the unwrapped interferogram phase values at the given pixel, G is a matrix containing values of -1, 0, and 1, D is a smoothing operator that minimizes the phase difference between consecutive acquisition dates, which is scaled by constant γ. 3. RESULTS Our results of the small-baseline approach for the first time interval indicate that deformation rates

4 were steady in time and we can therefore calculate the mean LOS velocity for this time period. The mean velocity map shows clear velocity gradient across the divergent plate boundary to the east and a north-south gradient across the transform zone in the southwest (Fig. 4). A comparison to interseismic GPS rates that have been projected into the line-of-sight direction shows a reasonable agreement, although the GPS LOS rates are not very accurate due to their poor vertical accuracy. Near the southwestern limit of the image the deformation field is affected by inflation that took place near Hrómundartindur volcano during the 1990s [19]. The center of uplift was centered just west of the image and this uplift explains why the area southwest of the faults has faster LOS velocities than the area directly to the south of them. the data processing and modeling is needed to find an unambiguous answer. 4. CONCLUSIONS In this project we used three different InSAR approaches to retrieve information about the postseismic deformation after the two June 2000 earthquakes in South Iceland. Our conclusions can be summarized by the following points: 1. The PSI analyses in South Iceland were difficult due to a low density of stable point scatterers and due to large Doppler centroids of many of the postseismic radar scenes. In this context it was particularly unfortunate that the time of the earthquakes coincided with the time at which ERS-2 data became strongly degraded in terms of Doppler stability. Hence, the ERS SAR data set available is of limited use for our PSI investigation. The Envisat data set cannot offset this disadvantage due to the small number of scenes available, which hampers the robust detection of PS. 2. Time-series analysis of small-baseline multilooked interferograms from shows interseismic LOS velocities that are in agreement with interseismic GPS velocities. 3. Preliminary results show that observed postseismic deformation is more prominent in the western part of the study area while less significant deformation is found in the east. We hope that this finding will enable us to distinguish between the two potential post-seismic mechanisms. 5. ACKNOWLEDGEMENTS This project was funded by the Icelandic Centre of Research. Satellite radar data were provided by ESA through Category-1 project #3846. Figure 4: The mean interseismic LOS displacement rate [mm/year] estimated from InSAR data in comparison with GPS LOS rates. The results of postseismic time-series analysis were corrected for interseismic deformation, which should only leave signals due to postseismic deformation. These results show that the postseismic transient lasted until 2003 or 2004, but the decay is not well constrained because of lack of radar data in The average LOS velocity map shows the more significant relative velocities in the western part of the area, while lower velocities are seen to the east of the two earthquake faults. We hope these findings will enable us to distinguish between the different potential post-seismic mechanisms, but further refinements to 6. REFERENCES 1. Polltiz, F.F., Wicks, C., & Thatcher, W. (2001). Mantle flow beneath a continental strike-slip fault: Post-seismic deformation after the 1999 Hector Mine earthquake. Science 293, Bürgmann, R., Ergintav, S., Segall, P., Hearn, E.H., McClusky, S., Reilinger, R.E., Woith, H. & Zschau, J. (2002). Time-space variable afterslip on and deep below the Izmit earthquake rupture. Bull. Seism. Soc. Am. 92, Peltzer, G., Rosen, P., Rogez, F. & Hudnut, K. (1996). Postseismic rebound in fault step-overs caused by pore-fluid flow. Science 273,

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