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AuthorsHaller, K. M.* 
Basili, R.* 
TitleDeveloping Seismogenic Source Models Based on Geologic Fault Data
Issue DateJul-2011
Series/Report no.4/82(2011)
KeywordsActive fault
fault source
seismic hazard
Subject Classification04. Solid Earth::04.04. Geology::04.04.01. Earthquake geology and paleoseismology 
04. Solid Earth::04.04. Geology::04.04.09. Structural geology 
04. Solid Earth::04.06. Seismology::04.06.01. Earthquake faults: properties and evolution 
04. Solid Earth::04.06. Seismology::04.06.11. Seismic risk 
04. Solid Earth::04.07. Tectonophysics::04.07.04. Plate boundaries, motion, and tectonics 
04. Solid Earth::04.07. Tectonophysics::04.07.07. Tectonics 
AbstractCalculating seismic hazard usually requires input that includes seismicity associated with known faults, historical earthquake catalogs, geodesy, and models of ground shaking. This paper will address the input generally derived from geologic studies that augment the short historical catalog to predict ground shaking at time scales of tens, hundreds, or thousands of years (e.g., SSHAC 1997). A seismogenic source model, terminology we adopt here for a fault source model, includes explicit three-dimensional faults deemed capable of generating ground motions of engineering significance within a specified time frame of interest. In tectonically active regions of the world, such as near plate boundaries, multiple seismic cycles span a few hundred to a few thousand years. In contrast, in less active regions hundreds of kilometers from the nearest plate boundary, seismic cycles generally are thousands to tens of thousands of years long. Therefore, one should include sources having both longer recurrence intervals and possibly older times of most recent rupture in less active regions of the world rather than restricting the model to include only Holocene faults (i.e., those with evidence of large-magnitude earthquakes in the past 11,500 years) as is the practice in tectonically active regions with high deformation rates. During the past 15 years, our institutions independently developed databases to characterize seismogenic sources based on geologic data at a national scale. Our goal here is to compare the content of these two publicly available seismogenic source models compiled for the primary purpose of supporting seismic hazard calculations by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) and the U.S. Geological Survey (USGS); hereinafter we refer to the two seismogenic source models as INGV and USGS, respectively. This comparison is timely because new initiatives are emerging to characterize seismogenic sources at the continental scale (e.g., SHARE in the Euro- Mediterranean,; EMME in the Middle East, http://www.emmegem. org/) and global scale (e.g., GEM,; Anonymous 2008). To some extent, each of these efforts is still trying to resolve the level of optimal detail required for this type of compilation. The comparison we provide defines a common standard for consideration by the international community for future regional and global seismogenic source models by identifying the necessary parameters that capture the essence of geological fault data in order to characterize seismogenic sources. In addition, we inform potential users of differences in our usage of common geological/seismological terms to avoid inappropriate use of the data in our models and provide guidance to convert the data from one model to the other (for detailed instructions, see the electronic supplement to this article). Applying our recommendations will permit probabilistic seismic hazard assessment codes to run seamlessly using either seismogenic source input. The USGS and INGV database schema compare well at a first-level inspection. Both databases contain a set of fields representing generalized fault three-dimensional geometry and additional fields that capture the essence of past earthquake occurrences. Nevertheless, there are important differences. When we further analyze supposedly comparable fields, many are defined differently. These differences would cause anomalous results in hazard prediction if one assumes the values are similarly defined. The data, however, can be made fully compatible using simple transformations.
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