1 / 14

Observations on Non-Uniqueness of Simulated Annealing Results for UCERF3

Observations on Non-Uniqueness of Simulated Annealing Results for UCERF3. Art Frankel USGS Feb 21, 2013. k. rate. Simulated annealing run #. Ruptures involving Mojave S portion of SAF. Each “series” is a rupture, ranked by mean rate These are the 14 ruptures with the highest mean rates,

dmitri
Download Presentation

Observations on Non-Uniqueness of Simulated Annealing Results for UCERF3

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Observations on Non-Uniqueness of Simulated Annealing Results for UCERF3 Art Frankel USGS Feb 21, 2013

  2. k rate Simulated annealing run # Ruptures involving Mojave S portion of SAF. Each “series” is a rupture, ranked by mean rate These are the 14 ruptures with the highest mean rates, for ruptures involving Mojave S SAF. Note correlation in peaks between different colors indicating rates of some ruptures are correlated (series 2-5, all M6.3’s)

  3. Ruptures 15-19

  4. Specifying slip on combined Little Salmon (thrust) + Bartlett Springs (strike-slip) Is problematic (see Susitna Glacier and Denali faults) Are the inversion results meaningful, given the boxcar or tapered slip simplification? Hazard for Little Salmon decreased in UCERF 3 UCERF3 does not consider simultaneous rupture of Cascadia SZ and crustal faults

  5. rupture 74170 M6.7 Little Salmon Rate Simulated Annealing Run #

  6. Rupture 73518 Eaton Roughs to Table Bluff, M7.3

  7. rupture 73331 M7.6 Eaton Roughs to Little Salmon (offshore)

  8. Little Salmon, top 19 ruptures

  9. Rates for individual ruptures are not uniquely resolved: underdetermined problem • Each run represents a collection of rupture rates that fits the data and constraints to some degree. Each run is a viable model • Given the variability of rates for a given rupture between simulated annealing runs, what does the mean rate over 100 runs mean? (pun intended) • Are the values for a given rupture normally-distributed over the s.a runs? No • Are the mean rates stable over a larger set of s.a. runs? • What are implications for fractile hazard curves? • Do the loss modelers have to use the results from each s.a. run, rather than the mean?

  10. UCERF3 has added about 200,000 ruptures over UCERF 2 with rates that are not uniquely resolved, but are dependent on each other in a complex manner. Some of these are ruptures that differ by one segment. Are there other correlations? • Hazard value is strongly controlled by the total rate of rupture at any given spot on a fault, less sensitive to magnitude distribution • Need to check this for longer periods of 2-4 sec • Need to compare hazard maps for different s.a. runs to see where they are different • How can we visualize the correlation of rates for different ruptures? How do we identify collective rupture characteristics that we think are well-resolved. What have we learned from allowing 220,000 ruptures? • How is this non-uniqueness conveyed to the user? • How can this be applied in deterministic hazard maps for that portion of the building codes?

  11. Other issues (mentioned atprevious workshop) • Making the on-fault target MFD for the inversion: Assumes that sub-seismogenic and supra-seismogenicrates are collectively continuous in rate (an assumption that can be questioned; sub-seismo may be on small faults; supra on main fault) • Adherence to GR b=1.0; e.g., slide for NorthridgeBox: but perhaps M6.5’s are more characteristic for San Fernando Valley area • Only considering GR b=1 will underestimate epistemic uncertainty

More Related