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Task R1: Distribution of Slip in Surface Ruptures Glenn Biasi University of Nevada Reno 1 Glenn Biasi University of Nevada Reno

Task R1: Distribution of Slip in Surface Ruptures

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Task R1: Distribution of Slip in Surface Ruptures. Glenn Biasi University of Nevada Reno. All ruptures.

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Page 1: Task R1: Distribution  of Slip in Surface Ruptures

Glenn Biasi University of Nevada Reno 1

Task R1: Distribution of Slip in Surface Ruptures

Glenn BiasiUniversity of Nevada Reno

Page 2: Task R1: Distribution  of Slip in Surface Ruptures

Glenn Biasi University of Nevada Reno 2

-- Sinesqrt was the only shape used in UCERF 2. -- Shape from 13 events in Hemphill-Haley and Weldon-- Redo analysis, Wesnousky dataset, normalize and stack… <30 km ruptures >200 km ruptures All available-- Sinesqrt shape average works for all event subsets

<30 km

<30 km with reflections

>200 km

>200 km w. refl.

All ruptures

All w. refl.

Sin(x/2L)

Sqrt(sin(x/2L))

Page 3: Task R1: Distribution  of Slip in Surface Ruptures

Glenn Biasi University of Nevada Reno 3

Example rupture profiles from Wesnousky (2008). Red line at average displacement

Page 4: Task R1: Distribution  of Slip in Surface Ruptures

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Paleoseismic Rupture Scenarios

• New records since WGCEP-2:– Bidart Fan Six events since

~1300 A.D., compared with five events since ~950 A.D.

– Five to seven events at Coachella since ~900 A.D. vs. four at Indio since A.D. 1000.

– Seven new events at Frazier Park.

– AMS redating of Pallett Creek.

• Shorter period of complete records, greater variability in scenarios.

Page 5: Task R1: Distribution  of Slip in Surface Ruptures

Glenn Biasi University of Nevada Reno 5

Notes on Averaged Rupture Shapes• Average rupture shape affects which scenarios from pearl-stringing fit

total displacement criteria. Feeds into N(M) vs. M.• Proposed: Use an empirical L->Davg regression instead of a fixed

Hanks-Bakun (from Task R2?).• Can average shape be used w/o removing the stress-drop?

1857 was here

Rupture Length (km)

Page 6: Task R1: Distribution  of Slip in Surface Ruptures

Glenn Biasi University of Nevada Reno 6

Multiple-Fault and Multiple Section Ruptures

• Geologic assessment of step-overs should give clues to the mechanical linkage of faults.

• At subfault ends:– Greater degrees of distributed displacement– Local rotation and extension– Exaggerated displacement gradients

• Obliquity of GPS strain field to fault orientation may be useful.

Page 7: Task R1: Distribution  of Slip in Surface Ruptures

Glenn Biasi University of Nevada Reno 7

Wesnousky, 2008

Wells and Coppersmith1994

12 events could contribute to this plot

Page 8: Task R1: Distribution  of Slip in Surface Ruptures

Glenn Biasi University of Nevada Reno 8

Overlap Illustration (5%)

Page 9: Task R1: Distribution  of Slip in Surface Ruptures

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Considerations for UCERF-3

• Displacements on shorter faults are out of proportion to their lengths. – Is this a general feature when Type B or C faults link?– How do short faults “know” what displacement to have?– Up to 12 ruptures are available to study it

• Systematize slip gradients at ends as inputs to other models.

• Re-stringing pearls would give one view of the MFD and rupture end points from paleoseismic data.

• Alternate Length-Daverage relation would change ratio of long and short ruptures.

Page 10: Task R1: Distribution  of Slip in Surface Ruptures

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Finite-Fault Rupture Displacements

• Finite-fault inversion: Seismic data inverted for slip on the fault. Potential uses:– Rupture displacement with strike and depth.– Evaluation of overlap/tapering at fault-to-fault ruptures.

• Pros and Cons– Depth filters out variability compared with near-surface measurements– Wavelengths may reflect larger, more important structures– Inversions differ, sometimes even in gross structure– Smoothing, resolution vary from earthquake to earthquake– Analyses can be one plane or in sub-fault panels

• Resource– Compilation by Mai: 152 ruptures for 80 earthquakes

Page 11: Task R1: Distribution  of Slip in Surface Ruptures

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Page 12: Task R1: Distribution  of Slip in Surface Ruptures

Glenn Biasi University of Nevada Reno 12

Finite-Fault Rupture Displacements

• Evaluation approach– Develop slip differences in depth and horizontal

separation (e.g., Shaw, 2010)– Compare with min, max frequencies in inversion– Evaluate for patterns in slip and normalized slip– Compare with available surface slip– Recommend use (or not) in UCERF-3

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Page 14: Task R1: Distribution  of Slip in Surface Ruptures

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Candidate ruptures to add to Wesnousky 2008 database

• 2010 Christchurch, New Zealand• 2010 El Mayor Cucapah, Mexico• 2009 L’Alquila, Italy• 2008 Wenchaun, China• 2006 Machaze, Mozambique• 2005 Pakistan• 2004 Parkfield, California• 2004 Mid-Niigata, Japan• 1995 Kobe, Japan• 1976 Montagua, Guatemala• 1973 Luhuo, China• 1931 Funyun, China• 1905 Bulnay, Mongolia