SCEC Award Number 20039 View PDF
Proposal Category Individual Proposal (Integration and Theory)
Proposal Title Developing earthquake simulators for use in seismic hazard estimates: Buried ruptures and implications for source and ground motions
Investigator(s)
Name Organization
Bruce Shaw Columbia University
Other Participants
SCEC Priorities 5a, 4c, 5b SCEC Groups FARM, EFP, GM
Report Due Date 03/15/2021 Date Report Submitted 05/13/2021
Project Abstract
 Earthquake simulators have the potential to contribute to our understanding of earthquake hazard in a number of different ways. One way, is in directly estimating earthquake rupture forecasts, which, when combined with ground motion models, give hazard estimates which compare very well with traditional statistical model estimates [Shaw, et al, 2018]. A second way is to use the models to help develop and constrain assumptions in the statistical models. A third way is to use the simulators as source models for ground motion studies. All three approaches have shown much promise. Here, we seek to push this simulator effort forward with a project that overlaps in a variety of ways, aiming to help guide statistical models, guide ground motion models, and further validate the simulators. The physical phenomena we studied is buried ruptures, ruptures which do not show substantial surface slip, and their comparison and contrast with ruptures which substantially break the surface. We report here on progress made in the last year. One paper on ground motions was published [Milner, Shaw, et al, 2021], and one paper on a New Zealand simulator was submitted [Shaw, et al, 2021]. A third paper related to scaling relations and how they are impacted by rupture aspect ratio and depth of burial of rupture and surface effects is in preparation. We have developed new magnitude-area scaling corrections valid across all mechanisms which corrects for aspect ratio and burial and surface effects. This scaling relation works well on the simulator ruptures.
Intellectual Merit Earthquake simulators have the potential to contribute to our understanding of earthquake hazard in a number of different ways. One way, demonstrated in recent work, is in directly estimating earthquake rupture forecasts, which, when combined with ground motion models, give hazard estimates which compare very well with traditional statistical model estimates [Shaw, et al, 2018]. A second way is to use the models to help develop and constrain assumptions in the statistical models. This approach was used in use UCERF3 to support magnitude dependent coefficient of variation in the time dependence of elastic rebound recurrence [Field, et al, 2015]. A third way being actively explored in the (soon expiring) Keck CISM project is to use the simulators as source models for ground motion studies. All three approaches have shown much promise. Here, we seek to push this simulator effort forward with a project that overlaps in a variety of ways, aiming to help guide statistical models, guide ground motion models, and further validate the simulators.
Broader Impacts Developed further scientific foundation for improved ground motion and hazard calculations. This is important for engineering and building code use and improving hazard mitigation and societal resilience.
Exemplary Figure Figure 2: Example ground motions from simulator events compared with Ground Motion Models (GMM). RotD50 spectra for site USC from ruptures on the Mojave section of the San Andreas Fault, computed with a one-dimensional (1D) velocity structure with VS30=500 m/s in the Southern California Earthquake Center (SCEC) BroadBand Platform (BBP). (a) Spectrum for a M 7.48 rupture on the Mojave section of the San Andreas Fault plotted as a thick black line. (b) Spectra for 185 different 7.0 ≤ M ≤ 7.5 RSQSim ruptures on the Mojave section of the San Andreas Fault simulated at USC plotted with thin gray lines, the mean of all 185 ruptures as a thick black line, and the mean plus and minus one standard deviation with dashed black lines. GMM comparisons (with plus and minus one standard deviation bounds marked with dashed lines) are plotted with colored lines. GMM predictions are slightly different for (b) because distributions are averaged across those predicted for each of the 185 RSQSim ruptures (rather than for a single M 7.48 rupture in (a)). From [Milner, Shaw, et al., 2020].