Dr. Benavente-Bravo, Roberto

Large earthquakes and tsunamis often occur around the Pacific Ring of Fire, in which Traveling Ionospheric Disturbances (TIDs) have been observed after these events. Sometimes (depending on seismic source features), TIDs can be observed near the epicenter of the generated earthqucovering 14ake due to the shock-acoustic wave. Additionally, TIDs can be induced by tsunamis due to the generated gravity waves and be detected several thousand kilometers away from the source. TIDs can be detected by analyzing Total Electron Content (TEC), which is calculated, indirectly, using signals from Global Navigation Satellite System (GNSS) receivers. The procedure allows for studying the ionospheric disturbance with a good spatial and temporal resolution. This study aims to identify tsunami-induced TIDs in the near- and far-fields following significant events in the Oriental and Occidental South Pacific Ocean. The selection criteria covering 14 tsunamis that occurred between 2010 and 2021 generated by earthquakes with Mw > 7.8 and depth less than 50 km. Tsunamis were modeled and compared with the TIDs obtained from TEC deviations. Near-field and far-field TIDs observed in hodochrons differ primarily in the clarity of their association with tsunamis. The simulated tidal gauges show a possible connection with the observed TEC anomalies, behaving similarly but with different delay times, showing some events even hours in advance. This potential correlation between TID parameters and tsunamis propagated in the Pacific Ocean can contribute to understanding the involved mechanisms and facilitate the development of near real-time early warning systems.

The spatial correlation of coseismic slip is a necessary input for generating stochastic seismic rupture models, which are commonly used in seismic and tsunami hazard assessments. To date, the spatial correlation of individual earthquakes is characterized using finite fault models by finding the combination of parameters of a von Kármán autocorrelation function that best fits the observed autocorrelation function of the finite fault model. However, because a priori spatial correlation conditions (i.e. not in the data) are generally applied in finite fault model generation, the results obtained using this method may be biased. Additionally, robust uncertainty estimates for spatial correlations of coseismic slip are generally not performed. Considering these limitations in the classic method, here, a method is developed based on a Bayesian formulation of Finite Fault Inversion (FFI) with positivity constraints. This method allows for characterizing the spatial correlation of coseismic slip and its uncertainties for an earthquake by using samples of coseismic slip from a posterior probability density function (PDF). Furthermore, a Bayesian model selection criterion called Akaike Bayesian Information Criterion (ABIC) is applied to objectively choose between different prior spatial correlation schemes before computing the posterior, to reduce subjectivity due to this prior condition. The ABIC is calculated using an approximate analytical expression of Bayesian evidence. The method is applied to simulated P waves, demonstrating that model selection allows for objectively estimating the most suitable prior spatial correlation scheme in FFI. Additionally, the target spatial correlation of coseismic slip is accurately recovered using samples from the posterior PDF, as well as their uncertainties. Moreover, in the simulated experiment, it is shown that a non-robust choice of the prior spatial correlation scheme can significantly bias the estimated spatial correlations of coseismic slip. We apply our method to observed P waves from the 2015, Illapel earthquake ($M_{\rm w} = 8.3$), finding that the spatial correlation of coseismic slip of this earthquake is better described by a von Kármán ACF, with mean correlation lengths of around 47 km and Hurst parameter of 0.58. We conclude that using our method reduces biases associated with prior spatial correlation conditions and allows for robust estimation of spatial correlations of coseismic slip and their uncertainties.

Estimating locking degree at faults is important for determining the spatial distribution of slip deficit at seismic gaps. Inverse methods of varying complexity are commonly used to estimate fault locking. Here we present an innovative approach to infer the degree of locking from surface GNSS velocities by means of supervised learning (SL) algorithms. We implemented six different SL regression methods and apply them in the Central Chile subduction. These methods were first trained on synthetic distributions of locking and then used to infer the locking from GNSS observations. We tested the performance of each algorithm and compared our results with a least squares inversion method. Our best results were obtained using the Ridge regression, which gives a root mean square error (RMSE) of 1.94 mm/yr compared to GNSS observations. The ML-based locking degree distribution is consistent with results from the EPIC Tikhonov regularized least squares inversion and previously published locking maps. Our study demonstrates the effectiveness of machine learning methods in estimating fault locking and slip, and provides flexible options for incorporating prior information to avoid slip instabilities based on the characteristics of the training set. Exploring uncertainties in the physical model during training could improve the robustness of locking estimates in future research efforts.

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.

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.

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.

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.