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On the relation of earthquake stress drop and ground motion variability
Author(s) -
Oth Adrien,
Miyake Hiroe,
Bindi Dino
Publication year - 2017
Publication title -
journal of geophysical research: solid earth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.983
H-Index - 232
eISSN - 2169-9356
pISSN - 2169-9313
DOI - 10.1002/2017jb014026
Subject(s) - drop (telecommunication) , parametric statistics , seismology , geology , spectral acceleration , geodesy , peak ground acceleration , ground motion , mathematics , statistics , computer science , telecommunications
One of the key parameters for earthquake source physics is stress drop since it can be directly linked to the spectral level of ground motion. Stress drop estimates from moment corner frequency analysis have been shown to be extremely variable, and this to a much larger degree than expected from the between‐event ground motion variability. This discrepancy raises the question whether classically determined stress drop variability is too large, which would have significant consequences for seismic hazard analysis. We use a large high‐quality data set from Japan with well‐studied stress drop data to address this issue. Nonparametric and parametric reference ground motion models are derived, and the relation of between‐event residuals for Japan Meteorological Agency equivalent seismic intensity and peak ground acceleration with stress drop is analyzed for crustal earthquakes. We find a clear correlation of the between‐event residuals with stress drops estimates; however, while the island of Kyushu is characterized by substantially larger stress drops than Honshu, the between‐event residuals do not reflect this observation, leading to the appearance of two event families with different stress drop levels yet similar range of between‐event residuals. Both the within‐family and between‐family stress drop variations are larger than expected from the ground motion between‐event variability. A systematic common analysis of these parameters holds the potential to provide important constraints on the relative robustness of different groups of data in the different parameter spaces and to improve our understanding on how much of the observed source parameter variability is likely to be true source physics variability.