Description
(1) Rachel Abercrombie, (2) Annemarie Baltay, (1) Boston University, (2) U.S. Geological Survey
In 2021 we launched the Community Stress Drop Validation Study, focused on the 2019 Ridgecrest earthquake, California, sequence, using a common dataset. The broad aim of the collaboration is to improve the quality of estimates of stress drop and related fundamental earthquake source parameters (corner frequency, source duration, etc.) and their uncertainties, to enable more reliable ground motion forecasting, and to obtain a better understanding of earthquake source physics. Seismological estimates of stress drop from earthquake spectral measurements have become standard practice over the last 50 years, but their wide variability, model dependence and inconsistency between studies have led to controversy and concerns about how to assess and interpret these measurements.
The SCEC/USGS community study has engaged a wide international community focused on improving methods and distinguishing the sources of variability between physical earthquake source variation, and random and systematic scatter and bias. To date, 18 research groups have submitted 28 different measurements of source parameters for earthquakes in the 2019 Ridgecrest sequence, with a focus on 55 events of M2 to 5. These approaches include spectral decomposition/generalized inversion, empirical Green’s function analysis in both frequency and time domains, and ground-motion and single-station based approaches. Comparison of submitted stress drops reveals considerable systematic and random scatter, but also shows consistency between events; for some events, methods are in agreement on either relatively high or low stress drops. Ongoing focus is on understanding the relative influences of different analysis parameter choices, assumptions about attenuation, frequency range of the data, and the growing evidence of widespread complexity and heterogeneity in even small earthquake ruptures. We welcome new members wishing to observe, learn or more actively participate; more information can be found at https://www.scec.org/research/stress-drop-validation.
Omar Issa, ResiQuant (Co-Founder)/Stanford University
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Martijn van den Ende, Université Côte d'Azur
Already for several years it has been suggested that Distributed Acoustic Sensing (DAS) could be a convenient, low-cost solution for Earthquake Early Warning (EEW). Several studies have investigated the potential of DAS in this context,...
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