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Finite-fault models for the 2010 M w 8.8 Maule, Chile earthquake indicate bilateral rupture with large-slip patches located north and south of the epicenter. Previous studies also show that this event features significant slip in the shallow part of the megathrust, which is revealed through correction of the forward tsunami modeling scheme used in tsunami inversions. The presence of shallow slip is consistent with the coseismic seafloor deformation measured off the Maule region adjacent to the trench and confirms that tsunami observations are particularly important for constraining far-offshore slip. Here, we benchmark the method of Optimal Time Alignment (OTA) of the tsunami waveforms in the joint inversion of tsunami (DART and tide-gauges) and geodetic (GPS, InSAR, land-leveling) observations for this event. We test the application of OTA to the tsunami Green’s functions used in a previous inversion. Through a suite of synthetic tests we show that if the bias in the forward model is comprised only of delays in the tsunami signals, the OTA can correct them precisely, independently of the sensors (DART or coastal tide-gauges) and, to the first-order, of the bathymetric model used. The same suite of experiments is repeated for the real case of the 2010 Maule earthquake where, despite the results of the synthetic tests, DARTs are shown to outperform tide-gauges. This gives an indication of the relative weights to be assigned when jointly inverting the two types of data. Moreover, we show that using OTA is preferable to subjectively correcting possible time mismatch of the tsunami waveforms. The results for the source model of the Maule earthquake show that using just the first-order modeling correction introduced by OTA confirms the bilateral rupture pattern around the epicenter, and, most importantly, shifts the inferred northern patch of slip to a shallower position consistent with the slip models obtained by applying more complex physics-based corrections to the tsunami waveforms. This is confirmed by a slip model refined by inverting geodetic and tsunami data complemented with a denser distribution of GPS data nearby the source area. The models obtained with the OTA method are finally benchmarked against the observed seafloor deformation off the Maule region. We find that all of the models using the OTA well predict this offshore coseismic deformation, thus overall, this benchmarking of the OTA method can be considered successful. 

Tsunamis are a series of long gravity waves generated by abrupt displacement of a significant volume of water that propagate under the action of gravity, returning the water layer to an equilibrium position. Differently from common wind-generated waves, tsunamis are characterized by large wavelengths (ranging from tens to hundreds of km) and long periods (ranging from minutes to hours) with water motions extending across the entire depth range of the water layer. Several natural phenomena such as earthquakes, landslides, volcanic eruptions, rapid changes of atmospheric pressure (meteotsunami), or asteroids impacts can be the source of the initial water displacement of a tsunami; among these, the most frequent involves submarine earthquakes. Most tsunamigenic earthquakes occur near Earth’s convergent plate tectonic boundaries (Fig. 1), at subduction zones, where an oceanic plate underthrusts another plate. During the last 15 years (2004-2019), subduction zones hosted a particularly high number of great magnitude tsunamigenic earthquakes with catastrophic consequences in terms of casualties and damages. This spate of activity is consistent with normal statistical fluctuations of seismicity rate over the past century (Lay, 2015), however, the collective tsunami impact was particularly severe in terms of fatalities, people missing, building destruction, and damage to infrastructures (e.g., ports, power plants, coastal towns). The largest tsunamis since 2004 were those ensuing from the 2004 Mw 9.2 Sumatra-Andaman (Indonesia) and the 2011 Mw 9.0 Tohoku (Japan) earthquakes (e.g., Lorito et al., 2016), causing 220,000+ and 15,000+ victims, respectively.