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Characteristic earthquake magnitude frequency distributions on faults calculated from consensus data in California

November 30, 2018

An estimate of the expected earthquake rate at all possible magnitudes is needed for seismic hazard forecasts. Regional earthquake magnitude frequency distributions obey a negative exponential law (Gutenberg‐Richter), but it's unclear if individual faults do. We add three new methods to calculate long‐term California earthquake rupture rates to the existing Uniform California Earthquake Rupture Forecast (UCERF3) efforts to assess method and parameter dependence on magnitude frequency results for individual faults. All solutions show strongly characteristic magnitude‐frequency distributions on the San Andreas and other faults, with higher rates of large earthquakes than would be expected from a Gutenberg‐Richter distribution. This is a necessary outcome that results from fitting high fault slip rates under the overall statewide earthquake rate budget. We find that input data choices can affect the nucleation magnitude‐frequency distribution shape for the San Andreas fault; solutions are closer to a Gutenberg‐Richter distribution if the maximum magnitude allowed for earthquakes that occur away from mapped faults (background events) is raised above the consensus threshold of M=7.6, if the moment rate for background events is reduced, or if the overall maximum magnitude is reduced from M=8.5. We also find that participation magnitude‐frequency distribution shapes can be strongly affected by slip‐rate discontinuities along faults that may be artifacts related to segment boundaries.

Publication Year 2018
Title Characteristic earthquake magnitude frequency distributions on faults calculated from consensus data in California
DOI 10.1029/2018JB016539
Authors Thomas E. Parsons, Eric L. Geist, Rodolfo Console, Roberto Carluccio
Publication Type Article
Publication Subtype Journal Article
Series Title Journal of Geophysical Research B: Solid Earth
Index ID 70201132
Record Source USGS Publications Warehouse
USGS Organization Pacific Coastal and Marine Science Center