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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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A Geodetic-Based Earthquake Early Warning System for Colombia and Ecuador
Colombia and Ecuador sit at one of the most diverse tectonic regimes in the world, located at the intersection of five tectonic plates (Bird, 2003) encompassing many geophysical hazard regimes, multiple subduction zones, and broad diffuse areas of significant deformation. Notably, the subduction of the Nazca plate under South America has produced at least seven large (Mw 7) and damaging earthquakes since 1900—the largest being the 1906 Mw 8.8 event. Both Colombia and Ecuador have made significant investments in Global Navigation Satellite System (GNSS) networks to study tectonic and volcanic deformation. Earthquake early warning (EEW) systems like the U.S.-operated ShakeAlert system (Murray et al., 2018, 2023) utilize real-time Global Navigation Satellite System (RT-GNSS) to rapidly characterize the largest, most damaging earthquakes in situations where seismic networks alone saturate (Melgar et al., 2015, 2016; Allen and Melgar, 2019; Ruhl et al., 2019). Both Colombia and Ecuador have large vulnerable populations proximal to the coast that may sustain significant damage in these large subduction events (Pulido et al., 2020) and yet farther enough away that an RT-GNSS EEW system could offer significant warning times to these populations and associated infrastructure. We examine the status of the Servicio Geológico Colombiano Geodesia: Red de Estudios de Deformación GNSS network in Colombia and the Escuela Politécnica Nacional GNSS network in Ecuador, their spatial distribution, and the current status of their data streams to determine what augmentations are required to support the real-time detection and modeling of large destructive earthquakes in and near Colombia and Ecuador.
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- Award ID(s):
- 1835791
- PAR ID:
- 10568659
- Publisher / Repository:
- SSA
- Date Published:
- Journal Name:
- Seismological Research Letters
- Volume:
- 96
- Issue:
- 1
- ISSN:
- 0895-0695
- Page Range / eLocation ID:
- 294 to 309
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1785/0220230390
