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1906 Revisited: Analyses of Shaking and Ground Failure

The Great 1906 San Francisco earthquake (April 18, M7.8) remains a monumental and unique historic event. In the U.S., it began an era in earthquake seismology: direct observations archived in Lawson’s (1908) lasting “Carnegie Report” of surface displacement, combined with analysis of the surrounding crustal deformation, led Reid (1910) to formulate the elastic rebound theory. The earthquake’s grandeur and extent resulted in shaking, damage and ground failures that were systematically studied in a new era of scientific excellence. Documentation includes archived seismic recordings from 96 stations worldwide, thousands of macroseismic observations and hundreds of reported landslides and liquefaction reports—many with evidential photos. For this session on Legacy Seismic Data, we focus on two of the datasets in particular: the macroseismic and ground failure observations. Specifically, we revisit the macroseismic data set aggregated by Boatwright and Bundock (2005) to generate a very well-constrained historical ShakeMap—while noting challenges reproducing these observations with existing ground motion models—and we digitize the locations of ground failure features documented in the Report to evaluate how well globally applicable ground failure models hindcast those effects. In general, the global models fare well, yet beg for regional model development that can accommodate more detailed geotechnical data constraints. We test models applicable at a regional scale to investigate if regional geotechnical constraints—not available at a global scale—significantly improve our landslide and liquefaction estimates. Such historical datasets uniquely allow testing and comparison of our ability to predict shaking-induced hazards given an event that has both well-constrained triggering and ground failure observations. The landslide and liquefaction data digitized as part of this project are archived in An Open Repository of Earthquake-Triggered Ground-Failure Inventories (Schmitt et al., 2017).

Presenting Author: David J. Wald

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