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Zeinab Jeddi et al. The eastern events have low magnitude, mostly between -0.5 and 0.5 ML and a high b-value of 1.6±0.1. Estimates of the b-value in volcanic earth- quake populations are often anomalously high as in this case (Roberts et al., 2015). Based on their fre- quency content (4–25 Hz) and clear P and S ar- rivals, the eastern events are classified as VT (McNutt, 2005). We identified two main families of waveforms sharing the same frequency content, but with differ- ent amplitude ratios of P and S phases on different components. Therefore, their mechanisms might dif- fer. However, the SIL system identifies only a few events with a double-couple mechanism and those are not consistent. This may be due to amplitude distor- tions at individual stations due to local topographic effects. Their temporal evolution indicates that they often occur in swarms of tens to hundreds of events within several days. Two main swarms occurred in November 2010 and December 2011. However, be- cause the seismic network was densified in the period 2011–2013, we are able to analyze the seismicity in detail only during this time period. Before this time, the seismic station coverage in the area (the perma- nent monitoring network of the IMO) was not dense enough to detect and provide good locations of such small-magnitude events. Therefore, we are not able to infer when the area became seismically active. We have been able to locate the hypocenters at an average absolute depth of around 3.5 km with a non- linear location method. The combined distribution of their depth and depth error suggests that they do not occur near the surface and, therefore, they cannot be due to glacial processes. We see no clear temporal migration of our detailed locations. However, the vast majority of events oc- curred during a short time span (less than two weeks). We cannot rule out the possibility that the source re- gion may have migrated on a time scale longer than the deployment of our temporary network (2 years). VT events are often associated with shear move- ments on near-planar faults, similar to tectonic earth- quakes. This can sometimes be inferred from the shape of seismic clusters after relative location (Hjaltadóttir, 2009, Got et al., 1994). We applied a relative-location technique to the two families of events. The resulting distribution of hypocenters is small and does not clearly indicate that they lie on a plane. However, there is some suggestion that the central cluster of events in family 1 is elongate with a strike of NNE/SSW and dipping towards the north. This suggestive strike is intermediate between that of the EVZ and the inferred orientation of the southern- most sections of the Eldgjá fissure near Kriki (see Fig- ure 1), where a hyaloclastite deposit has been associ- ated with the Eldgjá fires (Larsen, 2000). The events are mostly confined to a 400 m wide depth interval, but some are distributed over a 1 km depth range be- low that. This distribution differs significantly from that of the absolute locations of Jeddi et al. (2016) who found a cylindrical distribution over the depth range from 0 to 6 km with an average depth uncer- tainty of 300 m. We note that 35% of the events located in the tomographic study were not included in the relative locations due to low correlation coef- ficients and/or outlying data (presumably because of cycle skipping in the differential-time measurements). This may partly explain the difference, either in terms of larger errors due to poor correlation or because the poor correlation may be a result of the events being located away from the master events of the two iden- tified families. However, the events near the center of the distribution of Jeddi’s et al. (2016) absolute locations all yield differential measurements with a high correlation coefficient. Furthermore, the lack of consistency between these absolute locations and our relative locations can be explained if their uncertain- ties are underestimated. This may very well be the case. In both cases, the error estimation is at best sim- plistic as is generally the case in earthquake location. First, it should be noted that in both cases the error es- timate includes only random errors and ignores any bias that may arise, e.g., from an erroneous veloc- ity model. Second, the error estimates are in general based on the inconsistencies of relatively few data and are, therefore, not very robust. Third, Gaussian statis- tics are assumed by applying a least-squares optimiza- tion, while this may not be justified. In fact, we find that the residual distribution after relative location is more akin to an exponential distribution than a Gaus- 12 JÖKULL No. 67, 2017
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