Geology topics

Colin Pennington

Publications and source records attributed to Colin Pennington.

3 recordsLinked to original sources

USGS2025

Overview of The SCEC/USGS Community Stress Drop Validation Study using the 2019 Ridgecrest earthquake sequence

We present initial findings from the ongoing Community Stress Drop Validation Study to compare spectral stress‐drop estimates for earthquakes in the 2019 Ridgecrest, California, sequence. This study uses a unified dataset to independently estimate earthquake source parameters through various methods. Stress drop, which denotes the change in average shear stress along a fault during earthquake rupture, is a critical parameter in earthquake science, impacting ground motion, rupture simulation, and source physics. Spectral stress drop is commonly derived by fitting the amplitude‐spectrum shape, but estimates can vary substantially across studies for individual earthquakes. Sponsored jointly by the U.S. Geological Survey and the Statewide (previously, Southern) California Earthquake Center our community study aims to elucidate sources of variability and uncertainty in earthquake spectral stress‐drop estimates through quantitative comparison of submitted results from independent analyses. The dataset includes nearly 13,000 earthquakes ranging from M 1 to 7 during a two‐week period of the 2019 Ridgecrest sequence, recorded within a 1° radius. In this article, we report on 56 unique submissions received from 20 different groups, detailing spectral corner frequencies (or source durations), moment magnitudes, and estimated spectral stress drops. Methods employed encompass spectral ratio analysis, spectral decomposition and inversion, finite‐fault modeling, ground‐motion‐based approaches, and combined methods. Initial analysis reveals significant scatter across submitted spectral stress drops spanning over six orders of magnitude. However, we can identify between‐method trends and offsets within the data to mitigate this variability. Averaging submissions for a prioritized subset of 56 events shows reduced variability of spectral stress drop, indicating overall consistency in recovered spectral stress‐drop values.

California↗

USGS2024

SCEC/USGS Community Stress Drop Validation Study: How spectral fitting approaches influence measured source parameters

Spectral source parameters used to estimate an earthquake’s stress drop (Δσ) can vary significantly across measurement approaches. The Statewide California Earthquake Center/U.S. Geological Survey Community Stress-Drop Validation Study was initiated to compare source parameter estimates, focusing initially on a dataset from the 2019 Ridgecrest earthquake sequence. As part of that validation effort, here we focus on one potential source of uncertainty: whether spectral fitting approaches alone, applied to a common set of spectra from the 2019 Ridgecrest sequence result in different source parameter estimates. By using a common set of benchmark spectra analyzed across a consistent frequency band of 1–40 Hz, we eliminate many sources of variability. A subgroup of validation study participants volunteered to estimate the low-frequency displacement (Ω0) and corner frequency ( f c ) by fitting a smooth function to benchmark displacement spectra. Participants used linear- or log-sampled spectra, assumed a Brune or Boatwright spectral model, and applied different misfit criteria. We compare 17 approaches used to estimate Ω0, f c , and Δσ for 54 earthquake spectra. Our results reveal that 35% of events have Δσ estimates within a factor of two, whereas others exhibit variations exceeding an order of magnitude. The variability in Ω0 and f c can largely be attributed to whether a spectrum is consistent with the smooth function of an idealized simple crack model. The trade-off between Ω0 and f c may be more pronounced when using linearly sampled spectra, as higher frequency spectral bumps control the fits. As expected, methods that assumed a Boatwright model tended to have lower Ω0 and somewhat higher f c compared to those assuming a Brune model, although resulting Δσ estimates are similar. When compared to the overall validation study results, the fitting approach alone may account for between 5% and 90% (25% on average) of the total variability in spectral Δσ.

California↗

USGS2023

Quantifying site effects and their influence on earthquake source parameter estimations using a dense array in Oklahoma

We investigate the effects of site response on source parameter estimates using earthquakes recorded by the LArge-n Seismic Survey in Oklahoma (LASSO). While it is well known that near-surface unconsolidated sediments can cause an apparent breakdown of earthquake self-similarity, the influence of laterally varying site conditions remains unclear. We analyze site conditions across the 1825-station array on a river plain within an area of 40 km by 23 km using vertical ground motions from 14 regional earthquakes. While the source radiation pattern controls P-wave ground motions below 8 Hz, the surface geology correlates with P-wave ground motions above 8 Hz and S-wave ground motions at 2–21 Hz. Stations installed in alluvial sediments have vertical ground motions that can exceed three times the array median. We use the variation of ground motion of regional earthquakes across the array as a proxy for site effects. The corner frequencies and stress drops of local earthquakes ( M L = 0.01–3) estimated using a standard single-spectra approach show negative correlations with the site-effect proxy, while the seismic moments show positive correlations. In contrast, the spectral-ratio approach effectively shows no correlation. The overall bias is small as expected for this relatively homogeneous structure; accurate estimation of site-related biases requires at least 30 stations. Correcting for site-related biases reduces the standard deviations of the source parameters by less than 13% of the total variations. Remaining variations are partially associated with source directivity and model misfits— as small earthquakes can have complex ruptures.

Oklahoma↗