Abstract
Earthquake-induced deformation along the Sumatran plate boundary has been monitored by the Sumatran GPS Array (SuGAr) since 2002. This continuous GPS network recorded the coseismic deformation of 10 earthquakes with moment magnitude (Mw) larger than 7 and 20 with Mw in the range of 5.9–7 from 2002 to 2013. Among all these recorded events, one large Mw 7.2 event and most of the moderate ones (5.9 ≤ Mw < 7) have yet to be modeled with available GPS data. This is partially due to the limited number (≤ 4) of stations that recorded each event. In this paper, we explore the possibility of using the limited observations to derive sensible slip models for these “forgotten” Sumatran events. We model each event as a single rectangular patch of uniform slip and constrain most of the patch parameters using external information based on slab geometry and global teleseismic catalogs. For each event, we use a grid-search approach to find the preferred location of slip patches, which we present along with contours of error-weighted variance explained to indicate the uncertainties. We compare the center locations of our final slip patches with the centroid locations from the global Centroid Moment Tensor (gCMT) catalog and the epicenter locations from four other global catalogs. Our results show that the gCMT centroid locations for the 21 Sumatran earthquakes are systematically biased toward the southwest relative to the centers of our slip patches, while the epicenter locations from the four other catalogs are all consistently shifted toward the northeast. Although the available data have no resolving power for other source parameters, we find that simple forward modeling based on sparse but reliable near-field GPS data generally provides less biased and more accurate locations than global teleseismic catalogs along the Sumatran plate boundary. The catalog of slip models we present will have particular utility in the event of other significant earthquakes being generated by the same or proximal areas of the Sunda megathrust.
Highlights
The Sumatran plate boundary has experienced a surge of seismic activity in the years since the 26 December 2004 Mw 9.2 Sumatra–Andaman earthquake and is currently one of the most seismically active convergent plate boundaries in the world (Feng et al 2015)
Comparison with local seismic catalogs While someone could argue that the regional bias is due to the sparsity and one-sided geometry of our GPS data, we show that our GPS-based locations are overall less biased than the five global teleseismic catalogs by comparing the centers of our final slip patches with locations from three local seismic catalogs
Tilmann et al (2010) found a significant seaward bias in the global Centroid Moment Tensor (gCMT) locations and a lesser degree landward bias in the EHB locations relative to their locally determined locations. This bias is consistent with the regional bias we find in the gCMT and EHB locations relative to our locations (“Comparison with global teleseismic catalogs” section)
Summary
The Sumatran plate boundary has experienced a surge of seismic activity in the years since the 26 December 2004 Mw 9.2 Sumatra–Andaman earthquake and is currently one of the most seismically active convergent plate boundaries in the world (Feng et al 2015). The deformation caused by seismic events has been monitored continuously by the Sumatran GPS Array (SuGAr), which was. 16 August 2009 Mw 6.7 events (Wiseman et al 2011; Wang et al 2018)) have been modeled using the available SuGAr data, one Mw 7.2 event and the majority of the moderate events remained unmodeled geodetically. Events with the available SuGAr data and presents a catalog of coseismic slip models for the Mw 7.2 event and 20. The source parameters of these events are available from global teleseismic catalogs, but their solutions might be poorly constrained or biased. Our near-field GPS observations, though the number is limited, might provide some extra independent information on source parameters. We show in the rest of the paper that sparse near-field GPS data can be useful for determining and sometimes improving the location of moderate earthquakes. The improved locations will potentially be useful for providing a more complete and accurate slip history
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