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
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).
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)
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
Direct Measurements and Interpreted Data
• 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
1600 year Southern San Andreas Fault Earthquake Dates and Interpreted Rupture History
New data sites
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
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
Coulomb Stress Change Model
(Stein et al.Science, 1994)
Suggests northern Newport-Inglewood fault is close to failure
Dates of Most Recent Rupture from Paleoseismic Research
Questions for Predictive Simulation: - Is this a northward propagating rupture sequence? - When will the northern Newport-Inglewood Fault Zone rupture?
S. California Coastal Fault Zone
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