task r1 distribution of slip in surface ruptures n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Task R1: Distribution of Slip in Surface Ruptures PowerPoint Presentation
Download Presentation
Task R1: Distribution of Slip in Surface Ruptures

Loading in 2 Seconds...

play fullscreen
1 / 14

Task R1: Distribution of Slip in Surface Ruptures - PowerPoint PPT Presentation


  • 85 Views
  • Uploaded on

Task R1: Distribution of Slip in Surface Ruptures. Glenn Biasi University of Nevada Reno. All ruptures. <30 km. Sin(x/2L). Sqrt(sin(x/2L)). <30 km with reflections. All w . refl. -- Sinesqrt was the only shape used in UCERF 2. -- Shape from 13 events in Hemphill-Haley and Weldon

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Task R1: Distribution of Slip in Surface Ruptures' - theta


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.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
task r1 distribution of slip in surface ruptures

Task R1: Distribution of Slip in Surface Ruptures

Glenn Biasi

University of Nevada Reno

Glenn Biasi University of Nevada Reno

slide2

All ruptures

<30 km

Sin(x/2L)

Sqrt(sin(x/2L))

<30 km with reflections

All w. refl.

-- Sinesqrt was the only shape used in UCERF 2.

-- Shape from 13 events in Hemphill-Haley and Weldon

-- Redo analysis, Wesnousky dataset, normalize and stack…

<30 km ruptures

>200 km ruptures

All available

-- Sinesqrt shape average works for all event subsets

>200 km

>200 km w. refl.

Glenn Biasi University of Nevada Reno

slide3

Example rupture profiles from Wesnousky (2008). Red line at average displacement

Glenn Biasi University of Nevada Reno

paleoseismic rupture scenarios
Paleoseismic Rupture Scenarios
  • New records since WGCEP-2:
    • BidartFan Six events since ~1300 A.D., compared with five events since ~950 A.D.
    • Five to seven events at Coachella since ~900 A.D. vs. four at Indio since A.D. 1000.
    • Seven new events at Frazier Park.
    • AMS redating of Pallett Creek.
  • Shorter period of complete records, greater variability in scenarios.

Glenn Biasi University of Nevada Reno

notes on averaged rupture shapes
Notes on Averaged Rupture Shapes
  • Average rupture shape affects which scenarios from pearl-stringingfit total displacement criteria. Feeds into N(M) vs. M.
  • Proposed: Use an empirical L->Davgregression instead of a fixedHanks-Bakun (from Task R2?).
  • Can average shape be used w/o removing the stress-drop?

1857 was here

Rupture Length (km)

Glenn Biasi University of Nevada Reno

multiple fault and multiple section ruptures
Multiple-Fault and Multiple Section Ruptures
    • Geologic assessment of step-overs should give clues to the mechanical linkage of faults.
  • At subfault ends:
    • Greater degrees of distributed displacement
    • Local rotation and extension
    • Exaggerated displacement gradients
  • Obliquity of GPS strain field to fault orientation may be useful.

Glenn Biasi University of Nevada Reno

slide7

Wesnousky, 2008

Wells and

Coppersmith

1994

12 events could contribute to this plot

Glenn Biasi University of Nevada Reno

overlap illustration 5
Overlap Illustration (5%)

Glenn Biasi University of Nevada Reno

considerations for ucerf 3
Considerations for UCERF-3
  • Displacements on shorter faults are out of proportion to their lengths.
    • Is this a general feature when Type B or C faults link?
    • How do short faults “know” what displacement to have?
    • Up to 12 ruptures are available to study it
  • Systematize slip gradients at ends as inputs to other models.
  • Re-stringing pearls would give one view of the MFD and rupture end points from paleoseismic data.
  • Alternate Length-Daverage relation would change ratio of long and short ruptures.

Glenn Biasi University of Nevada Reno

finite fault rupture displacements
Finite-Fault Rupture Displacements
  • Finite-fault inversion: Seismic data inverted for slip on the fault. Potential uses:
    • Rupture displacement with strike and depth.
    • Evaluation of overlap/tapering at fault-to-fault ruptures.
  • Pros and Cons
    • Depth filters out variability compared with near-surface measurements
    • Wavelengths may reflect larger, more important structures
    • Inversions differ, sometimes even in gross structure
    • Smoothing, resolution vary from earthquake to earthquake
    • Analyses can be one plane or in sub-fault panels
  • Resource
    • Compilation by Mai: 152 ruptures for 80 earthquakes

Glenn Biasi University of Nevada Reno

finite fault rupture displacements1
Finite-Fault Rupture Displacements
  • Evaluation approach
    • Develop slip differences in depth and horizontal separation (e.g., Shaw, 2010)
    • Compare with min, max frequencies in inversion
    • Evaluate for patterns in slip and normalized slip
    • Compare with available surface slip
    • Recommend use (or not) in UCERF-3

Glenn Biasi University of Nevada Reno

candidate ruptures to add to wesnousky 2008 database
Candidate ruptures to add to Wesnousky 2008 database
  • 2010 Christchurch, New Zealand
  • 2010 El Mayor Cucapah, Mexico
  • 2009 L’Alquila, Italy
  • 2008 Wenchaun, China
  • 2006 Machaze, Mozambique
  • 2005 Pakistan
  • 2004 Parkfield, California
  • 2004 Mid-Niigata, Japan
  • 1995 Kobe, Japan
  • 1976 Montagua, Guatemala
  • 1973 Luhuo, China
  • 1931 Funyun, China
  • 1905 Bulnay, Mongolia

Glenn Biasi University of Nevada Reno