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UCERF3 Spatio-Temporal Clustering

UCERF3 Spatio-Temporal Clustering. Current implementation is dependent on current long term model. What about faults for which there is no slip data (grey faults) ? What about faults with low background rates ?. What to do in the absence of data?.

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UCERF3 Spatio-Temporal Clustering

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  1. UCERF3 Spatio-Temporal Clustering Current implementation is dependent on current long term model. What about faults for which there is no slip data (grey faults) ? What about faults with low background rates ?

  2. What to do in the absence of data? ETAS models of triggered seismicity commonly prescribe an isotropic distribution for the aftershocks of small earthquakes (M < 5): We propose an improved spatial kernel that takes into account the mainshock distance from a fault by incorporating strike-parallel elongation and a near-fault bias effect:

  3. SoCal Motivation NoCal • Rate of small earthquakes (M < 5) scales with distance from a fault according to: • Clustered events tend to be more localized on faults

  4. Aftershock Data (SoCal) 2.5 < M < 4.5 T = 1.5 days

  5. Aftershock Data (SoCal)

  6. Aftershock Data (SoCal)

  7. Aftershock Data (NoCal)

  8. Near-fault bias

  9. Data Check (on-fault and off-fault) b-values Omori Law Radial decay (Felzer and Brodsky, 2006)

  10. Model of near-fault aftershock distribution

  11. Model of near-fault aftershock distribution Productivity

  12. Model of near-fault aftershock distribution Near-fault bias

  13. Model of near-fault aftershock distribution Near-mainshock spatial kernel

  14. Model of near-fault aftershock distribution Aspect ratio

  15. Model of near-fault aftershock distribution

  16. Parameter Estimation Hold fixed and estimate using maximum likelihood Significant tradeoffs Use secondary constraints: Ensure synthetics replicate radial decay Consider on-fault aspect ratios

  17. Source Synthetic SoCal NoCal

  18. An spatial kernel with a strike-parallel elongation and near-fault effect best describes the near-fault distribution of aftershocks of small earthquakes. • Parameters for SoCal: • g = 1.2 d = 0.2 A0 = 4 b = 2.7 h = 0.03 • Parameters for NoCal: • g = 1.6 d = 0.1 A0 = 7 b = 2.3 h = 0.03 Conclusions: Application to UCERF3: • Expand fault network for to include grey faults; others? • Encode distance and direction to nearest fault(s)

  19. Northridge

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