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SSC 307 Page 2 10 Evidence for and against G-R Scaling on Faults 1 10 0 10 −1 10 −2 10 Number >= M per Year M Number >= −3 10 Morgan Page USGS Pasadena −4 10 4 4.5 5 5.5 6 6.5 7 7.5 8 Magnitude (M) Evidence for and against G-R Scaling on Faults Southern San Andreas Fault Insights from Constructing UCERF3 G-R Branch Characteristic Slip Aftershock Statistics 20 km from South-Central SAF Characteristic Magnitude Distribution Hypothesizes: Rate of Largest Earthquakes is Higher than G-R Prediction Schwartz and Coppersmith (1984) Aftershocks of 1952 Kern country and 1971 San Fernando earthquakes removed 2 20 km from Southern San Andreas Fault 10 1850−1931 1932−1983 1 Modern Instrumental 1984−2006 10 Paleo 0 10 Early Instrumental Historical −1 10 Paleo −2 10 b=1 −3 10 Cumulative Number >= M per Year −4 10 4 4.5 5 5.5 6 6.5 7 7.5 8 Magnitude Paleo data constructed using the “stringing pearls” methodology of Biasi and Weldon (2009) Different a-values? 2 20 km from Southern San Andreas Fault 10 1850−1931 1932−1983 1 Modern Instrumental 1984−2006 10 Paleo 0 10 Early Instrumental Historical −1 10 Paleo −2 10 b=1 −3 10 Cumulative Number >= M per Year −4 10 4 4.5 5 5.5 6 6.5 7 7.5 8 Magnitude Different b-values? 2 20 km from Southern San Andreas Fault 10 1850−1931 1932−1983 1 Modern Instrumental 1984−2006 10 Paleo 0 10 Early Instrumental Historical −1 10 Paleo −2 10 b=1 −3 10 Cumulative Number >= M per Year −4 10 4 4.5 5 5.5 6 6.5 7 7.5 8 Magnitude Evidence that b-values are lower near faults Earthquakes stacked by distance to SCEC Community Fault Model Page, Alderson, and Doyle (2011) Characteristic? 2 20 km from Southern San Andreas Fault 10 1850−1931 1932−1983 1 Modern Instrumental 1984−2006 10 Paleo 0 10 Early Instrumental Historical −1 10 Paleo −2 10 b=1 −3 10 Cumulative Number >= M per Year −4 10 4 4.5 5 5.5 6 6.5 7 7.5 8 Magnitude Short Catalogs Seldom See the Long-Term Rate Distribution of seismicity rate long-termrate 0.1 0.08 0.06 0.04 0.02 0 0 0.5 1 1.5 2 Normalized seismicity rate 1-year catalogs ETAS Simulations: Rate variation is a result of aftershock clustering (no background rate variation assumed) Short Catalogs Seldom See the Long-Term Rate Distribution of seismicity rate long-termrate 0.08 0.06 0.04 0.02 0 0 0.5 1 1.5 2 Normalized seismicity rate 10-year catalogs ETAS Simulations: Rate variation is a result of aftershock clustering (no background rate variation assumed) Short Catalogs Seldom See the Long-Term Rate Distribution of seismicity rate long-termrate 0.08 0.06 0.04 0.02 0 0 0.5 1 1.5 2 Normalized seismicity rate 100-year catalogs ETAS Simulations: Rate variation is a result of aftershock clustering (no background rate variation assumed) Short Catalogs Seldom See the Long-Term Rate ETAS simulation #17 1 10 Last 23 years Entire 1000 years 0 10 b=1 reference −1 10 −2 10 Rate per Year −3 10 −4 10 4 5 6 7 8 Magnitude G-R Simulations can produce similar catalogs to SSAF ETAS Simulations: Rate variation is a result of aftershock clustering (no background rate variation assumed) Evidence for and against G-R Scaling on Faults Southern San Andreas Fault Insights from Constructing UCERF3 G-R Branch Characteristic Slip Aftershock Statistics For Gutenberg-Richter Branch: The hypothesis is that each point in space (or fault subsecon) nucleates a GR distribu4on of earthquakes What happens if we sum all these GR subsecon MFDs up? GR a-value set to match subsecon slip rate Subsec'on MFD b=1 Local Mmax Largest Mag that Mag of the subsec;on smallest par;cipates in rupture on Mmax for each fault subsec;on determined by subsecon connec;vity of fault model G-R Model needs: • Higher total seismicity rate, • Higher maximum magnitudes (more connec;vity), and/or • Lower b-values on faults Evidence for and against G-R Scaling on Faults Southern San Andreas Fault Insights from Constructing UCERF3 G-R Branch Characteristic Slip Aftershock Statistics Carrizo Plain Paleoslips Characteristic-looking slips are actually composed of multiple events Channel incision is less frequent than surface-rupturing earthquakes? Ludwig, Akçiz, Noriega, Zielke, and Arrowsmith (2010) Zielke, Arrowsmith, Ludwig, and Akçiz (2010) COVs from UCERF3 Models Takes into account probability of seeing slip paleoseismically Does not take into intra- or inter-event slip variations tapered slip distribution Weldon et al. 2007 COVs from UCERF3 Models Takes into account probability of seeing slip paleoseismically Does not take into intra- or inter-event slip variations COV Histogram 160 150 140 130 120 110 Characteristic Branch 100 90 80 70 Mean COV = 0.73 60 Fraction Per Bin 50 40 Median COV = 0.51 30 20 10 0 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 COV COV Histogram 110 100 90 80 70 G-R Branch 60 50 Mean COV = 0.78 Fraction Per Bin 40 30 Median COV = 0.60 20 10 0 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 COV COVs from UCERF3 Models Takes into account probability of seeing slip paleoseismically Does not take into intra- or inter-event slip variations COV Histogram 160 150 140 130 120 110 Characteristic Branch 100 90 80 70 Mean COV = 0.73 60 Fraction Per Bin 50 40 Median COV = 0.51 30 20 10 0 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 UCERF3 Scaling Relations COV COV Histogram 110 100 90 80 70 60 50 Fraction Per Bin 40 30 20 10 0 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 COV Evidence for and against G-R Scaling on Faults Southern San Andreas Fault Insights from Constructing UCERF3 G-R Branch Characteristic Slip Aftershock Statistics ETAS simulations of M6.75 Northridge earthquake with UCERF2 earthquake rate model 50% foreshock probability UCERF3 Preview! MFDs near Diablo Canyon Nucleation MFDs from UCERF3 Characteristic Branch: MFDs constrained to be close to UCERF2 Methodology Shoreline fault Hosgri fault Nucleation MFD for Shoreline (547) Nucleation MFD for Hosgri (30) - 1 - 1 1 0 1 0 UCERF3 (cumulative) UCERF2 (cumulative) UCERF3 (cumulative) - 2 - 2 1 0 UCERF3 (incremental) 1 0 UCERF2 (incremental) UCERF3 (incremental) - 3 - 3 1 0 1 0 - 4 - 4 1 0 1 0 e e - 5 - 5 1 0 1 0 - 6 - 6 1 0 1 0 Nucleation Rat Nucleation Rat - 7 - 7 1 0 1 0 - 8 - 8 1 0 1 0 - 9 - 9 1 0 1 0 -10 -10 1 0 1 0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 Magnitude Magnitude Nucleation MFDs from UCERF3 Characteristic Branch: MFDs constrained to be close to UCERF2 Methodology Hosgri fault Nucleation MFD for Hosgri (30) - 1 1 0 UCERF2 (cumulative) UCERF3 (cumulative) - 2 1 0 UCERF2 (incremental) UCERF3 (incremental) - 3 1 0 - 4 1 0 e - 5 1 0 - 6 1 0 Nucleation Rat - 7 1 0 - 8 1 0 - 9 1 0 -10 1 0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 Magnitude Hosgri connects to San Gregorio, NSAF Statewide Magnitude-Frequency Distribution 0 1 0 UCERF3 target (from seismicity) - 1 1 0 - 2 UCERF3 on-fault 1 0 (supraseismogenic- ) thickness rups) - 3 1 0 UCERF3 background Frequency (per bin UCERF3 total - 4 1 0 - 5 1 0 UCERF2 background UCERF3 total - 6 1 0 5.00 5.25 5.50 5.75 6.00 6.25 6.50 6.75 7.00 7.25 7.50 7.75 8.00 8.25 8.50 8.75 9.00 Magnitude Multi-fault ruptures help to eliminate magnitude “bulge” problem in UCERF2.
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