We use continuous and survey GNSS data to image the spatial and temporal evolution of afterslip during the two-months following the Mw8.3 Illapel earthquake. Our approach solves for the incremental daily slip on the subduction interface using non-negative least-squares and spatial/temporal minimum Laplacian constraints. We find that afterslip developed at three specific areas at the megathrust, surrounding the coseismic rupture. The largest patch takes place at shallow depth north of the coseismic rupture. Smaller patches occur at greater depth north and south of the rupture, but no afterslip is found downdip. In addition, well resolved afterslip also occurs within the coseismic area that experienced 3-5 meters of seismic slip. Our afterslip model shows striking correlations with the spatial distribution of aftershocks and repeating earthquakes. A Mw6.8 aftershock occur on November 7 at the deep patch of enhanced afterslip and our inversion captures the triggered afterslip. Two Mw6.9 events occurred 100 km north of the rupture 55 days after the mainshock. The enhanced shallow afterslip developing northward possibly triggered these remote and delayed events. Enhanced afterslip spatially correlates with areas having experienced regular seismic swarms observed during the years prior to the Illapel earthquake. This correlation supports the view of localized fluid high-pore pressure areas behaving aseismically and surrounding a highly locked asperity, preventing the seismic rupture to propagate into them. The similarity with the behavior observed for the Mw7.8 2016 Ecuador and Mw7.6 2012 Costa Rica, suggests a common behaviour for heterogeneous subduction interfaces.

A devastating tsunami struck Palu Bay in the wake of the 28 September 2018 M$_{\mathrm{w}}=7.5$ Palu earthquake (Sulawesi, Indonesia). With a predominantly strike-slip mechanism, the question remains whether this unexpected tsunami was generated by the earthquake itself, or rather by earthquake-induced landslides. In this study we examine the tsunami potential of the co-seismic deformation. To this end, we present a novel geodetic dataset of GPS and multiple SAR-derived displacement fields to estimate a 3D co-seismic surface deformation field. The data reveal a number of fault bends, conforming to our interpretation of the tectonic setting as a transtensional basin. Using a Bayesian framework, we provide robust finite fault solutions of the co-seismic slip distribution, incorporating several scenarios of tectonically feasible fault orientations below the bay. These finite fault scenarios involve large co-seismic uplift (~2 m) below the bay due to thrusting on a restraining fault bend that connects the offshore continuation of two parallel onshore fault segments. With the co-seismic displacement estimates as input we simulate a number of tsunami cases. For most locations for which video-derived tsunami waveforms are available our models provide a qualitative fit to leading wave arrival times and polarity. The modeled tsunamis explain most of the observed runup. We conclude that co-seismic deformation was the main driver behind the tsunami that followed the Palu earthquake. Our unique geodetic dataset constrains vertical motions of the sea floor, and sheds new light on the tsunamigenesis of strike-slip faults in transtensional basins.