SCEC Award Number 13116 View PDF
Proposal Category Workshop Proposal
Proposal Title Source Inversion Validation (SIV) Workshop
Name Organization
Paul Martin Mai King Abdullah University of Science and Technology (Saudi Arabia) Danijel Schorlemmer University of Southern California Morgan Page United States Geological Survey
Other Participants
SCEC Priorities 2, 3, 6 SCEC Groups SIV, Seismology, FARM
Report Due Date 10/08/2013 Date Report Submitted N/A
Project Abstract
The Source Inversion Validation (SIV) group conducted its 8th workshop (since 2008) in conjunction with the Annual SCEC meeting in Palm Springs (Sept 8-11, 2013). There were approximately 50 participants in attendance during the 4-hr workshop, to discuss methods and approaches to source inversion, to share the latest results related to the SIV exercises, and to discuss the continuation of the SIV project. The detailed program of the workshop can be found at, with links to individual presentations. The “Notes” below summarize the presentation and subsequent discussion of the workshop. The main outcome of the 2013 SIV workshop was a plan for developing a benchmark exercise using teleseismic data for the source-inversion problem as well as for testing back-projection approaches. It was also decided to hold a dedicated workshop in Southern California (Caltech/USC), presumably in March 2014, focusing on the teleseismic benchmarking as well as quantitative measures of “goodness-of-fit” of rupture-model solutions.
Intellectual Merit + continuation and expansion of efforts to understand and quantify uncertainties in earthquake source imaging
+ more accurately resolved earthquake source models, including proper characterization and quantification of their uncertainties, are mandatory to improve our understanding of earthquake source physics
+ benchmarking of codes and forward-modeling & inversion methods, and developing tools to quantify rupture-model differences / similarities are key to advance earthquake source studies
Broader Impacts + rigorous benchmarking of codes and methods, development of Bayesian approaches, and tools to quantify rupture-model differences & similarities are the main outcomes of the SIV efforts that have a broad impact on how earthquake source inversions are perceived and what we can learn from them
Exemplary Figure Figure 1:
Submitted inversion solutions from four teams, shown in the graphical represenation provided by the SIV online collaboration platform (, and the actual „target model“ for which synthetic near-field data at 40 sites were computed and distributed.