Dr. Benavente-Bravo, Roberto

We deployed a dense geodetic and seismological network in the Atacama seismic gap in Chile. We derive a microseismicity catalog of >30,000 events, time series from 70 GNSS stations, and utilize a transdimensional Bayesian inversion to estimate interplate locking. We identify two highly locked regions of different sizes whose geometries appear to control seismicity patterns. Interface seismicity concentrates beneath the coastline, just downdip of the highest locking. A region with lower locking (27.5°S–27.7°S) coincides with higher seismicity levels, a high number of repeating earthquakes and events extending toward the trench. This area is situated where the Copiapó Ridge is subducted and has shown previous indications of both seismic and aseismic slip, including an earthquake sequence in 2020. While these findings suggest that the structure of the downgoing oceanic plate prescribes patterns of interplate locking and seismicity, we note that the Taltal Ridge further north lacks a similar signature.

Since the 1985 M 8.0 central Chile earthquake, national strong‐motion seismic networks have recorded ten megathrust earthquakes with magnitudes greater than M 7.5 at the convergent margin, defined by the contact between the Nazca and South American plates. The analysis of these earthquake records have led to improved hazard analyses and design codes for conventional and seismically protected structures. Although strong‐motion baseline correction is required for a meaningful interpretation of these records, correction methods have not been applied consistently in time. The inconsistencies between correction methods have been neglected in the practical use of these records in practice. Consequently, this work aims to provide a new strong‐motion database for researchers and engineers, which has been processed by traceable and consistent data processing techniques. The record database comes from three uncorrected strong motion Chilean databases. All the records are corrected using a four‐step novel methodology, which detects the P‐wave arrival and introduces a baseline correction based on the reversible‐jump Markov chain Monte Carlo method. The resulting strong motion database has more than 2000 events from 1985 to the date, and it is available to download at the Simulation Based Earthquake Risk and Resilience of Interdependent Systems and Networks (SIBER‐RISK) project website.

Here, the ionospheric response to earthquakes, earthquakes inducing tsunamis, and volcanic eruptions are presented as a contribution to the so‐called ionospheric seismology with the eventual development of real‐time warning systems in mind. A thorough analysis of Traveling Ionospheric Disturbances (TIDs) observed after these lithospheric events in South America is presented. It is based on a decade of total electron content (TEC) anomaly maps constructed explicitly for this purpose, likely the most extensive survey ever for South America. Three disturbance types are identified: TIDs generated by shock‐acoustic waves, by gravity waves, possibly induced by tsunami waves, and by Rayleigh surface waves. TIDs are observed after earthquakes with epicenters on the Pacific Ocean east coast, except one in the middle of the ocean. TIDs‐generating earthquake thresholds are found to be Mw ≥ 7.0 and depth ≤40, and TID amplitudes and ranges are proportional to earthquake magnitude. Fault mechanism and satellite‐receiver pair geometry are also considered. TIDs after volcanic eruptions confirm that atmospheric resonances are already reported. TIDs propagation direction depends strongly on the geomagnetic field direction, propagation toward the geomagnetic equator being more efficient. It was only possible to add some kind of vertical disturbance‐propagation evidence to TEC TIDs identification in some cases using ionograms from nearby ionosondes. A denser ionosonde network with greater sounding frequency would be necessary for further study.

The b-value can be used to characterize the seismic activity for a given earthquake catalog and provide information on the stress level accumulated at active faults. Here we develop an algorithm to objectively estimate variations of b-value along one arbitrary dimension. To this end, we employ a Bayesian transdimensional approach where the seismic domains will be self-defined according to information in the seismic catalog. This makes it unnecessary to prescribe the location and extent of domains, as it is commonly done. We first show the algorithm’s robustness by performing regressions from synthetic catalogs, recovering the target models with great accuracy. We also apply the algorithm to a microseismicity catalog for the Central Chile region. This segment is considered a seismic gap where the last major earthquake with shallow slip was in 1730. Our results illuminate the downdip limit of the seismogenic zone and the transition to intraslab seismicity. In the along-strike direction, low b-value coincides with the extent of locked asperities, suggesting a high-stress loading at the Central Chile seismic gap. Our results indicate the reliability of the Bayesian transdimensional method for capturing robust b-value variations, allowing us to characterize the mechanical behavior on the plate interface of subduction zones.

Inversions of geodetic data are regularly used to estimate interseismic locking in subduction zones. However, the ill‐posed nature of these problems motivates us to include prior information, physically consistent with processes of the subduction seismic cycle. To deal with model instabilities, we present an inversion method to estimate both plate‐locking and model uncertainties by inverting Global Navigation Satellite System derived velocities based on a Bayesian model selection scheme. Our method allows us to impose positivity constraints via a multivariate folded‐normal distribution, with a specified covariance matrix. Model spatial correlations are explored and ranked to find models that best explain the observed data and for a better understanding of locking models. This approach searches for hyperparameters of the prior joint multivariate probability density function (PDF) of model parameters that minimize the Akaike Bayesian Information Criterion (ABIC). To validate our approach, we invert synthetic displacements from analytic models, yielding satisfactory results. We then apply the method to estimate the plate‐locking in Central Chile (28°–39°S) and its relation to the coseismic slip distribution of earthquakes with magnitudes Mw > 8.0, on the subduction zone since 2010. We also search among different prior PDFs for a single ductile‐fragile limit depth. Our results confirms a spatial correlation between locked asperities and the 2010 Mw 8.8 Maule and 2015 Mw 8.3 Illapel earthquake rupture zones. The robustness of our locking model shows potential to improve future seismic and tsunami hazard estimations.

Geodetically constrained interseismic interplate coupling has been widely used to assess seismic potential in subduction zones. Modeling interseismic deformation is challenging, as it involves interplate coupling and often ignores continental internal deformation processes. We present a novel methodology to jointly estimate interplate coupling along with upper plate rigid motion and surface strain, constrained by GNSS‐derived velocities. We use a least squares inversion with a spatially variable Equal Posterior Information Condition Tikhonov regularization, accounting for observational and elastic structure uncertainties. Our modeling reveals three megathrust regions with high tsunamigenic earthquake potential located within the Atacama Seismic Gap (Chile). This study indicates the presence of a downdip segmentation located just above the 1995 (Mw8.0) Antofagasta earthquake rupture, raising concerns for the potential of tsunamigenic earthquake occurrence at shallower depths. Additionally, we show that surface motion is dominated by strain, with rather negligible rigid motion, dismissing the rigid Andean microplate model typically assumed in previous studies.

We compiled a novel microseismicity catalog for the Central Chile megathrust (29°–35°S), comprising 8,750 earthquakes between April 2014 and December 2018. These events describe a pattern of three trenchward open half-ellipses, consisting of a continuous, coast-parallel seismicity band at 30–45 km depth, and narrow elongated seismicity clusters that protrude to the shallow megathrust and separate largely aseismic regions along strike. To test whether these shapes could outline highly coupled regions (“asperities”) on the megathrust, we invert GPS displacement data for interplate locking. The best-fit locking model does not show good correspondence to seismicity, possibly due to lacking resolution. When we prescribe high locking inside the half-ellipses, however, we obtain models with similar data fits that are preferred according to the Bayesian Information Criterion (BIC). We thus propose that seismicity on the Central Chile megathrust may outline three adjacent highly coupled regions, two of them located between the rupture areas of the 2010 Maule and the 2015 Illapel earthquakes, a segment of the Chilean margin that may be in a late interseismic stage of the seismic cycle.

The detection of transient events related to slow earthquakes in GNSS positional time series is key to understanding seismogenic processes in subduction zones. Here, we present a novel Principal and Independent Components Correlation Analysis (PICCA) method that allows for the temporal and spatial detection of transient signals. The PICCA is based on an optimal combination of the principal (PCA) and independent component analysis (ICA) of positional time series of a GNSS network. We assume that the transient signal is mostly contained in one of the principal or independent components. To detect the transient, we applied a method where correlations between sliding windows of each PCA/ICA component and each time series are calculated, obtaining the stations affected by the slow slip event and the onset time from the resulting correlation peaks. We first tested and calibrated the method using synthetic signals from slow earthquakes of different magnitudes and durations and modelled their effect in the network of GNSS stations in Chile. Then, we analyzed three transient events related to slow earthquakes recorded in Chile, in the areas of Iquique, Copiapó, and Valparaíso. For synthetic data, a 150 days event was detected using the PCA-based method, while a 3 days event was detected using the ICA-based method. For the real data, a long-term transient was detected by PCA, while a 16 days transient was detected by ICA. It is concluded that simultaneous use of both signal separation methods (PICCA) is more effective when searching for transient events. The PCA method is more useful for long-term events, while the ICA method is better suited to recognize events of short duration. PICCA is a promising tool to detect transients of different characteristics in GNSS time series, which will be used in a next stage to generate a catalog of SSEs in Chile

We propose a method for defining the optimal locations of a network of tsunameters in view of near real-time tsunami forecasting using sea surface data assimilation in the near and middle fields, just outside of the source region. The method requires first the application of the empirical orthogonal function analysis to identify the potential initial locations, followed by an optimization heuristic that minimizes a cost-benefit function to narrow down the number of stations. We apply the method to a synthetic case of the 2015 Mw8.4 Illapel Chile earthquake and show that it is possible to obtain an accurate tsunami forecast for wave heights at near coastal points, not too close to the source, from assimilating data from three tsunameters during 14 min, but with a minimum average time lag of nearly 5 min between simulated and forecasted waveforms. Additional tests show that the time lag is reduced for tsunami sources that are located just outside of the area covered by the tsunameter network. The latter suggests that sea surface data assimilation from a sparse network of stations could be a strong complement for the fastest tsunami early warning systems based on pre-modelled seismic scenarios.

Variability characterization of tsunami generation is quintessential for proper hazard estimation. For this purpose we isolate the variability which stems solely from earthquake spatial source complexity, by simulating tsunami inundation in the near-field with a simplified digital elevation model, using nonlinear shallow water equations. For earthquake rupture, we prescribe slip to have a log-normal probability distribution function and von Kármán correlation between each subfault pair, which we assume decreases with increasing euclidean distance between them. From the generated near-field inundation time-series, emanating from several thousand synthetic slip realizations across a magnitude 9 earthquake, we extract several tsunami intensity measures at the coast. Results show that all considered tsunami intensity measures and potential energy variability increase with increasing spatial slip correlations. Finally, we show that larger spatial slip correlations produce higher tsunami intensity measure exceedance probabilities within the near-field, which highlights the need to quantify the uncertainty of earthquake spatial slip correlation.