Paleoseismic and Geologic Data for Earthquake Simulations

1. Paleoseismic and Geologic Data for Earthquake Simulations Lisa B. Grant and Miryha M. Gould

2. Overview • Paleoseismic data is needed to understand and simulate long time scale, multi-cycle fault behavior for predictive simulation • Uncertainty in paleoseismic observations is a major challenge for data assimilation • Existing paleoseismic databases for hazard calculations should be modified for predictive simulations • Paleoseismic data can identify areas for predictive simulations of fault interactions

3. Primary Objective of the ACES Science Plan “…to develop physically based numerical simulation models for the complete earthquake generation process and to assimilate observations into these models at all time and space scales relevant to the earthquake cycle” (Mora, ACES Proceedings 2000).

4. Significance of Geologic Data • Fault data provides framework for simulations • Paleoseismic data is required for modeling multi-cycle rupture behavior San Andreas fault (courtesy of J R. Arrowsmith)

6. Paleoseismic DataDescribes pre-instrumental earthquakes • Site specific geologic investigations • Data sets are small, sparse and analog • Quantification of uncertainty is a major challenge for data assimilation • Existing paleoseismic databases for probabilistic seismic hazard assessment include • Direct measurements • Interpreted parameters

7. Site specific (point) measurements Date of last rupture Dates of multiple ruptures Average recurrence interval Surface displacement Slip rate Fault segments and segment properties (spatially averaged) Characteristic recurrence interval Magnitude Rupture extent Slip distribution Direct Measurements andInterpreted Data

10. Example Fault Database from California (CDMG) (visualization by Peggy Li)

11. San Andreas Fault, California (courtesy of J R. Arrowsmith)

12. Fault Segments

13. Slip Rates (mm/yr) By Segment

14. Slip Rates (mm/yr) at Measurement Sites

15. Per Segment

16. Average Recurrence Interval (years) At Measurement Sites

17. 1600 year Southern San Andreas Fault Earthquake Dates and Interpreted Rupture History New data sites

18. Paleoseismology of the San Andreas Fault System Bulletin Seismological Society of AmericaEdited by Grant, Lettis and Schwartz • Dedicated Issue • Expected late 2002 • New sites • Additional data and reduced uncertainty at existing sites

19. A Northward Propagating Earthquake Sequence in Coastal Southern California? L. B. Grant and T. K. Rockwell, in press, SRL Example of using paleoseismic data to identify potentially hazardous areas for predictive simulation

20. Deformation and Fault Slip Rates in S. California From Geodetic and Paleoseismic Measurements

21. Coulomb Stress Change Model (Stein et al. Science, 1994) Suggests northern Newport-Inglewood fault is close to failure

22. Questions for Predictive Simulation: - Is this a northward propagating rupture sequence? - When will the northern Newport-Inglewood Fault Zone rupture? Dates of Most Recent Rupture from Paleoseismic Research S. California Coastal Fault Zone

23. Conclusions • Paleoseismic data is needed to understand and simulate long time scale, multi-cycle fault behavior for predictive simulation • Uncertainty in paleoseismic observations is a major challenge for data assimilation • Existing paleoseismic databases for hazard calculations should be modified for predictive simulations • Paleoseismic data can identify areas for predictive simulations of fault interactions

24. TheEnd