2 10 Evidence for and against G-R Scaling on Faults 1 10

0 10

−1 10

−2 10 Number >= M per Year per 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 distribuon of earthquakes What happens if we sum all these GR subsecon MFDs up?

GR a-value set to match subsecon slip rate

Subsecon MFD

b=1

Local Mmax

Largest Mag that Mag of the subsecon smallest parcipates in rupture on Mmax for each fault subsecon determined by subsecon connecvity of fault model

G-R Model needs: • Higher total seismicity rate, • Higher maximum magnitudes (more connecvity), 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