Factors that influence variability in stress drop measurements using spectral decomposition and spectral ratio methods for the 2019 Ridgecrest earthquake sequence

Xiaowei Chen, Qimin Wu, & Colin Pennington

Accepted March 14, 2025, SCEC Contribution #14170

Stress drop is a fundamental parameter related to earthquake source physics, but is hard to measure accurately.
To better understand how different factors influence stress drop measurements, we compare two different methods
using the Ridgecrest stress drop validation dataset: spectral decomposition and spectral ratio, each with different processing options. We also examine the influence of spectral complexity on source parameter measurement.
Applying the spectral decomposition method, we find that frequency bandwidth and time-window length could influence spectral magnitude calibration, whilst depth-dependent attenuation is important to correctly map
stress drop variations. For the spectral ratio method, we find that the selected source model has limited
influence on the measurements, however, the Boatwright model tends to produce smaller standard deviation and larger magnitude dependence than the Brune model. Variance reduction threshold, frequency bandwidth, and time-window length, if chosen within an appropriate parameter range, have limited influence on source parameter measurement. For both methods, wave type, attenuation correction and spectral complexity strongly influence the
result. The scale factor that quantifies the magnitude dependence of stress drop show large variations with different processing options, and earthquakes with complex source spectra deviating from the Brune-type source models tend to have larger scale factor than earthquakes without complexity. Based on these detailed comparisons, we make a few specific suggestions for data processing workflows that could help future studies of source parameters and interpretations.

Citation
Chen, X., Wu, Q., & Pennington, C. (2025). Factors that influence variability in stress drop measurements using spectral decomposition and spectral ratio methods for the 2019 Ridgecrest earthquake sequence. Bulletin of the Seismological Society of America, (accepted).