Dynamic strains have never played a role in determining local earthquake magnitudes, which are routinely set by displacement waveforms from seismic instrumentation (e.g., ML). We present a magnitude scale for local earthquakes based on broadband dynamic strain waveforms. This scale is derived from the peak root-mean-squared strains (A) in 4589 records of dynamic strain associated with 365 crustal earthquakes and 77 borehole strainmeters along the Pacific-North American plate boundary on the west coast of the United States and Canada. In this data set, catalog moment magnitudes range from 3.5≤Mw≤7.2, and hypocentral distances range from 6≤R≤500 km. The 1D representation of geometrical spreading and attenuation of A common to all strain data is logA0(R)=−0.00072R−1.45log(R). After correcting for instrument gain, site terms, and event terms, the magnitude scale, MDS=logA−logA0(R)−log(3×10−9), scales as ≈0.92Mw with a residual standard deviation of 0.19. This close association with Mw holds for events east of the −124° meridian; west of this boundary, however, a constant correction of 0.41 is needed to adjust for additional along-path attenuation effects. As a check on the accuracy of this magnitude scale, we apply it to dynamic strain records from three strainmeters located in the near field of the 2019 M 6.4 and 7.1 Ridgecrest earthquakes. Results from these six records are in agreement to within 0.5 magnitude units, and five out of six records are in agreement to within 0.34 units.
As the seismological community embraces fiber optic distributed acoustic sensing (DAS), DAS arrays are becoming a logical, scalable option to obtain strain and ground-motion data for which the installation of seismometers is not easy or cheap, such as in dense offshore arrays. The potential of strain data in earthquake early warning (EEW) applications has been recently demonstrated using records from borehole strainmeters (BSMs). However, current BSM networks are sparse, installing more BSMs is expensive and often impractical, and BSMs have the same limitations in offshore environments as other traditional seismic instruments. Here, we aim to provide a road map about how DAS data could be used in existing EEW applications, using the ShakeAlert EEW System for the West Coast of the United States as an example. We review the data requirements for EEW systems, examine ways in which strain-derived ground-motion data can be incorporated into such systems without significant modifications, and determine what is still needed for full utilization of DAS data in these applications. Importantly, EEW algorithms require ground-motion amplitude information for rapid earthquake source characterization; thus, accurate strain amplitude observations, not only phase information, are necessary for deriving these ground-motion metrics from DAS data. To obtain high-quality ground-motion observations, EEW-compatible DAS arrays need to be multicomponent, well coupled, and low noise. We suggest ways to achieve such data requirements using existing DAS technology and discuss areas in which further research is needed to optimize DAS array performance for EEW.
The URTeC Technical Program Committee accepted this presentation on the basis of information contained in an abstract submitted by the author(s). The contents of this paper have not been reviewed by URTeC and URTeC does not warrant the accuracy, reliability, or timeliness of any information herein. All information is the responsibility of, and, is subject to corrections by the author(s). Any person or entity that relies on any information obtained from this paper does so at their own risk. The information herein does not necessarily reflect any position of URTeC. Any reproduction, distribution, or storage of any part of this paper without the written consent of URTeC is prohibited.
Peak ground velocity (PGV) is a commonly used parameter in earthquake ground-motion models (GMMs) and hazard analyses, because it is closely related to structural damage and felt ground shaking, and is typically measured on broadband seismometers. Here, we demonstrate that strainmeters, which directly measure in situ strain in the bulk rock, can easily be related to ground velocity by a factor of bulk shear-wave velocity and, thus, can be used to measure strain-estimated PGV. We demonstrate the parity of velocity to strain utilizing data from borehole strainmeters deployed along the plate boundaries of the west coast of the United States for nine recent M 4.4–7.1 earthquakes in California, including the largest two events of the July 2019 Ridgecrest earthquake sequence. PGVs derived from maximum horizontal shear strains fall within the range of seismic-estimated values recorded at the same distances. We compare the strain-estimated data with GMMs based on seismic PGVs and find consistency in residual polarity (positive vs. negative; the sign of the difference between observed and modeled data) for certain earthquake–station paths, where some paths indicate an overestimation and others indicate an underestimation of strain-derived PGVs, as compared with the GMMs. We surmise that this may be indicative of over or underestimation of shear-wave velocity along those paths, as compared with the average velocity used to derive PGV from strain measurements, or indicative of repeatable site and path effects that are not accounted for in our analyses. This direct comparison of strain with velocity can highlight physical path effects, as well as improve the density and capability of ground-motion recordings.
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