Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/8337
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dc.contributor.authorallParsons, T.; U.S. Geological Survey, MS-999, 345 Middlefield Rd. Menlo Park, CA 94025, USAen
dc.contributor.authorallConsole, R.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italiaen
dc.contributor.authorallFalcone, G.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma2, Roma, Italiaen
dc.contributor.authorallMurru, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italiaen
dc.contributor.authorallYamashina, K.; Earthquake Research Institute (ERI), University of Tokyo, Yayoi 1-1-1, Bunkyo-ku, Tokyo 113–0032, Japanen
dc.date.accessioned2012-10-22T10:52:59Zen
dc.date.available2012-10-22T10:52:59Zen
dc.date.issued2012-09en
dc.identifier.urihttp://hdl.handle.net/2122/8337en
dc.description.abstractEarthquake forecasts are usually underinformed, and can be plagued by uncertainty in terms of the most appropriate model, and parameter values used in that model. In this paper, we explore the application of two different models to the same seismogenic area. The first is a renewal model based on the characteristic earthquake hypothesis that uses historical/palaeoseismic recurrence times, and fixed rupture geometries. The hazard rate is modified by the Coulomb static stress change caused by nearby earthquakes that occurred since the latest characteristic earthquake. The second model is a very simple earthquake simulator based on plate-motion, or fault-slip rates and adoption of a Gutenberg–Richter magnitude–frequency distribution. This information is commonly available even if historical and palaeoseismic recurrence data are lacking. The intention is to develop and assess a simulator that has a very limited parameter set that could be used to calculate earthquake rates in settings that are not as rich with observations of large-earthquake recurrence behaviour as the Nankai trough. We find that the use of convergence rate as a primary constraint allows the simulator to replicate much of the spatial distribution of observed segmented rupture rates along the Nankai, Tonankai and Tokai subduction zones. Although we note rate differences between the two forecast methods in the Tokai zone, we also see enough similarities between simulations and observations to suggest that very simple earthquake rupture simulations based on empirical data and fundamental earthquake laws could be useful forecast tools in information-poor settings.en
dc.language.isoEnglishen
dc.publisher.nameWiley-Blackwellen
dc.relation.ispartofGeophysical Journal Internationalen
dc.relation.ispartofseries3 / 190 (2012)en
dc.subjectTime series analysisen
dc.subjectSpatial analysisen
dc.subjectProbability distributionsen
dc.subjectSeismic cycleen
dc.subjectEarthquake interactionen
dc.subjectforecasting, and predictionen
dc.subjectStatistical seismology.en
dc.titleComparison of characteristic and Gutenberg–Richter models for time-dependentM ≥ 7.9 earthquake probability in the Nankai-Tokai subduction zone, Japanen
dc.typearticleen
dc.description.statusPublisheden
dc.type.QualityControlPeer-revieweden
dc.description.pagenumber1673-1688en
dc.subject.INGV04. Solid Earth::04.06. Seismology::04.06.02. Earthquake interactions and probabilityen
dc.subject.INGV04. Solid Earth::04.06. Seismology::04.06.05. Historical seismologyen
dc.subject.INGV04. Solid Earth::04.07. Tectonophysics::04.07.05. Stressen
dc.identifier.doi10.1111/j.1365-246X.2012.05595.xen
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dc.description.obiettivoSpecifico3.1. Fisica dei terremotien
dc.description.journalTypeJCR Journalen
dc.description.fulltextrestricteden
dc.relation.issn0956-540Xen
dc.relation.eissn1365-246Xen
dc.contributor.authorParsons, T.en
dc.contributor.authorConsole, R.en
dc.contributor.authorFalcone, G.en
dc.contributor.authorMurru, M.en
dc.contributor.authorYamashina, K.en
dc.contributor.departmentU.S. Geological Survey, MS-999, 345 Middlefield Rd. Menlo Park, CA 94025, USAen
dc.contributor.departmentIstituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italiaen
dc.contributor.departmentIstituto Nazionale di Geofisica e Vulcanologia, Sezione Roma2, Roma, Italiaen
dc.contributor.departmentIstituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italiaen
dc.contributor.departmentEarthquake Research Institute (ERI), University of Tokyo, Yayoi 1-1-1, Bunkyo-ku, Tokyo 113–0032, Japanen
item.openairetypearticle-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.grantfulltextrestricted-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
crisitem.author.deptU.S. Geological Survey, MS-999, 345 Middlefield Rd, Menlo Park, CA 94025, USA-
crisitem.author.deptIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Roma2, Roma, Italia-
crisitem.author.deptIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Roma1, Roma, Italia-
crisitem.author.deptIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Roma1, Roma, Italia-
crisitem.author.deptEarthquake Research Institute (ERI), University of Tokyo, Yayoi 1-1-1, Bunkyo-ku, Tokyo 113–0032, Japan-
crisitem.author.orcid0000-0002-0582-4338-
crisitem.author.orcid0000-0002-2554-4421-
crisitem.author.orcid0000-0002-7385-394X-
crisitem.author.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.author.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.author.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.classification.parent04. Solid Earth-
crisitem.classification.parent04. Solid Earth-
crisitem.classification.parent04. Solid Earth-
crisitem.department.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.department.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.department.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
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