1. A New Approach To Paleoseismic Event Correlation Glenn Biasi and Ray Weldon University of Nevada Reno Acknowledgments: Tom Fumal, Kate Scharer, SCEC and the USGS.

2. Big Question How do we estimate seismic hazard when we can’t prove events correlate between paleoseismic sites? –Why it matters (1): If they correlate: longer, less frequent ruptures If not: shorter, more frequent ruptures. –Why it matters (2): Support for future paleoseismic investigations.

3. 0 2000 Calendar Year The Data: Paleoseismic event date pdf’s.

4. Correlating Events Between Paleoseismic Sites Time correlation is not likely to ever be entirely convincing. Example: two exactly overlapping uniform date pdf’s six years wide give 1/6 chance that the events are in the same year. Probabilities of correlation based on displacement fall off with site separation (ask me later what can be done).

5. Ways to build a rupture history (1) N. Bend/ S. Bend No pattern Big events Example from Weldon et al. (2004) Science

6. Ways (2) Pearls to Scenarios Find all ruptures consistent at some level with the data Build a large suite of rupture scenarios Select likely histories using other constraints (slip rate, dating consistency, etc.) Study the properties of likely histories for recurrence, segmentation, etc.

8. Pair-wise joint probability range: ~3e-2 to 3e-3; -> absolute likelihoods are all small Linking involves some rules for overlap. Rules don’t seem to dominate results.

9. Example ruptures.

10. Building Scenarios from Ruptures Draw from all possible ruptures until each paleoquake is included exactly once. Scenario is one possible history of rupture on the fault. Construct 10,000 scenarios. Core rupture lengths set by sites in rupture. Tails added by drawing around the average per-event displacement d, then tapering by 9900*d. Use measured d where available. Tail truncated if rupture would cross a neighboring site. Tails can extend into creeping zone and Bombay Beach.

11. Scoring Scenarios Degree of time agreement in ruptures Total displacement compared to rupture prediction in some time. Recurrence rate in light of hiatus since 1857 (number of ruptures)

12. The lack of a southern SAF earthquake since 1857 constrains the probable number of ruptures in viable scenarios. E.g., 15 rupture scenarios are twice as likely as 22 rupture scenarios.

14. Fewest ruptures case. Two wall-to-wall (W2W) ruptures since AD 900. Displacement scales with length. W2W cause serious over- prediction of total displace- ment. (14.7 m mean). How much misfit is too much? Segment bounds (WGCEP) - frequency of single- and multiple segment ruptures fall out directly.

15. predicted from slip rate Coachella misfit No wall-to-wall events; 2 pre-1857 north-bend events, one bigger. WW: several short events - un- correlated. maximum displacement among all ruptures. Best case: 1.43 m. avg. misfit. Max age of complete record.

16. Time overlap score Product time score vs. displace- ment fit. Displ. vs. # of ruptures; trend below 21 ruptures is too few. Product score vs. # of ruptures Displ. score vs. rupture number No. Ruptures Displ. Score Time Score No. Ruptures Best time scores Fewest ruptures, okay displ. scores Best displ. scores

21. Ensembles of scenarios => probabilities of single and multiple-segment ruptures. 20 scenarios - ~450 ruptures. Rules for counting segments are required. segs 1, 2 no segs seg 2, but L1>L2 Applications of Rupture Scenarios (2) L1L2

22. Conclusions for Data Collection Complete count and rough event dates are most valuable Don’t need great dating precision (but don’t stop trying to get it) Slip-per event measurements are valuable New sites are most valuable in large spatial gaps. Do need geologic or geodetic slip rates

23. Conclusions for Hazard Estimation Scenarios include earthquake location, magnitude, and frequency: essentials for seismic hazard estimation Ensembles of likely scenarios support hazard calculations without having to resolve the per- event correlation issues Scenarios are data-based - the paleoseismic record. Can quantify single- and multi-segment rupture frequency for the whole fault (or use it to question segmentation!)

25. Surface Slip versus Rupture Length Relationship for reverse and normal may be linear but may NOT for strike-slip Rate of increase of strike-slip decreases with length for strike-slip without apparently reaching a plateau.

26. Pallett Cr. - Wrightwood Pallett Cr. - Carrizo Having rupture displacements helps. Even with displacement measurements, P(correl) is often small. This case: all magnitudes equally likely: