Data-driven approaches to identify geophysical signals have proven beneficial in high dimensional environments where model-driven methods fall short. GNSS offers a source of unsaturated ground motion observations that are the data currency of ground motion forecasting and rapid seismic hazard assessment and alerting. However, these GNSS-sourced signals are superposed onto hardware-, location- and time-dependent noise signatures influenced by the Earth’s atmosphere, low-cost or spaceborne oscillators, and complex radio frequency environments. Eschewing heuristic or physics based models for a data-driven approach in this context is a step forward in autonomous signal discrimination. However, the performance of a data-driven approach depends upon substantial representative samples with accurate classifications, and more complex algorithm architectures for deeper scientific insights compound this need. The existing catalogs of high-rate (≥1Hz) GNSS ground motions are relatively limited. In this work, we model and evaluate the probabilistic noise of GNSS velocity measurements over a hemispheric network. We generate stochastic noise time series to augment transferred low-noise strong motion signals from within 70 kilometers of strong events (≥ MW 5.0) from an existing inertial catalog. We leverage known signal and noise information to assess feature extraction strategies and quantify augmentation benefits. We find a classifier model trained on this expanded pseudo-synthetic catalog improves generalization compared to a model trained solely on a real-GNSS velocity catalog, and offers a framework for future enhanced data driven approaches.
Observations of strong ground motion during large earthquakes are generally made with strong-motion accelerometers. These observations have a critical role in early warning systems, seismic engineering, source physics studies, basin and site amplification, and macroseismic intensity estimation. In this manuscript, we present a new observation of strong ground motion made with very high rate (>= 5 Hz) Global Navigation Satellite System (GNSS) derived velocities. We demonstrate that velocity observations recorded on GNSS instruments are consistent with existing ground motion models and macroseismic intensity observations. We find that the ground motion predictions using existing NGA-West2 models match our observed peak ground velocities with a median log total residual of 0.03-0.33 and standard deviation of 0.72-0.79, and are statistically significant following normality testing. We finish by deriving a Ground Motion Model for peak ground velocity from GNSS and find a total residual standard deviation 0.58, which can be improved by ~2% when considering a simple correction for Vs30.
more » « less- Award ID(s):
- 1835791
- NSF-PAR ID:
- 10485869
- Publisher / Repository:
- Seismica
- Date Published:
- Journal Name:
- Seismica
- Volume:
- 2
- Issue:
- 1
- ISSN:
- 2816-9387
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Earthquake early warning (EEW) systems aim to forecast the shaking intensity rapidly after an earthquake occurs and send warnings to affected areas before the onset of strong shaking. The system relies on rapid and accurate estimation of earthquake source parameters. However, it is known that source estimation for large ruptures in real‐time is challenging, and it often leads to magnitude underestimation. In a previous study, we showed that machine learning, HR‐GNSS, and realistic rupture synthetics can be used to reliably predict earthquake magnitude. This model, called Machine‐Learning Assessed Rapid Geodetic Earthquake model (M‐LARGE), can rapidly forecast large earthquake magnitudes with an accuracy of 99%. Here, we expand M‐LARGE to predict centroid location and fault size, enabling the construction of the fault rupture extent for forecasting shaking intensity using existing ground motion models. We test our model in the Chilean Subduction Zone with thousands of simulated and five real large earthquakes. The result achieves an average warning time of 40.5 s for shaking intensity MMI4+, surpassing the 34 s obtained by a similar GNSS EEW model. Our approach addresses a critical gap in existing EEW systems for large earthquakes by demonstrating real‐time fault tracking feasibility without saturation issues. This capability leads to timely and accurate ground motion forecasts and can support other methods, enhancing the overall effectiveness of EEW systems. Additionally, the ability to predict source parameters for real Chilean earthquakes implies that synthetic data, governed by our understanding of earthquake scaling, is consistent with the actual rupture processes.
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ABSTRACT Frictional heating during earthquake rupture raises the fault-zone fluid pressure, which affects dynamic rupture and seismic radiation. Here, we investigate two key parameters governing thermal pressurization of pore fluids – hydraulic diffusivity and shear-zone half-width – and their effects on earthquake rupture dynamics, kinematic source properties, and ground motions. We conduct 3D strike-slip dynamic rupture simulations assuming a rate-and-state dependent friction law with strong velocity weakening coupled to thermal-pressurization of pore fluids. Dynamic rupture evolution and ground shaking are densely evaluated across the fault and Earth’s surface to analyze the variations of rupture parameters (slip, peak slip rate, rupture speed, and rise time), correlations among rupture parameters, and variability of peak ground velocity. Our simulations reveal how variations in thermal-pressurization affect earthquake rupture properties. We find that the mean slip and rise time decrease with increasing hydraulic diffusivity, whereas mean rupture speed and peak slip-rate remain almost constant. Mean slip, peak slip-rate, and rupture speed decrease with increasing shear-zone half-width, whereas mean rise time increases. Shear-zone half-width distinctly affects the correlation between rupture parameters, especially for parameter pairs (slip, rupture speed), (peak slip-rate, rupture speed), and (rupture speed, rise time). Hydraulic diffusivity has negligible effects on these correlations. Variations in shear-zone half-width primarily impact rupture speed, which then may affect other rupture parameters. We find a negative correlation between slip and peak slip-rate, unlike simpler dynamic rupture models. Mean peak ground velocities decrease faster with increasing shear-zone half-width than with increasing hydraulic diffusivity, whereas ground-motion variability is similarly affected by both the parameters. Our results show that shear-zone half-width affects rupture dynamics, kinematic rupture properties, and ground shaking more strongly than hydraulic diffusivity. We interpret the importance of shear-zone half-width based on the characteristic time of diffusion. Our findings may inform pseudodynamic rupture generators and guide future studies on how to account for thermal-pressurization effects.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.26443/seismica.v2i1.239
