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• W4210316125 endingPage "1528" @default.
• W4210316125 startingPage "1499" @default.
• W4210316125 abstract "In regions of infrequent moderate-to-large earthquakes, historic earthquake catalogs are often insufficient to provide inputs to seismic-hazard analyses (i.e. fault locations and magnitude–frequency relations) or to inform ground-motion predictions for certain seismic sources. In these regions, analysis of relic coseismic evidence, such as paleoliquefaction, is commonly used to infer information about the seismic hazard. However, while paleoliquefaction studies have been performed widely, all existing analysis techniques require a priori assumptions about the causative earthquake’s location (i.e. rupture magnitude and ground motions can otherwise not be estimated). This may lead to inaccurate assumptions in some settings, and by corollary, erroneous results. Accordingly, this article proposes an inversion framework to probabilistically constrain seismic-source parameters from paleoliquefaction. Analyzing evidence at regional scale leads to (a) a geospatial likelihood surface that constrains the rupture location and (b) a probability distribution of the rupture magnitude, wherein source-location uncertainty is explicitly considered. Simulated paleoliquefaction studies are performed on earthquakes with known parameters. These examples demonstrate the framework’s potential, even in cases of limited field evidence, as well as important caveats and lessons for forward use. The proposed framework has the potential to provide new insights in enigmatic seismic zones worldwide." @default.
• W4210316125 created "2022-02-08" @default.
• W4210316125 creator A5034126474 @default.
• W4210316125 creator A5037291633 @default.
• W4210316125 date "2022-01-29" @default.
• W4210316125 modified "2023-10-17" @default.
• W4210316125 title "Probabilistic seismic source location and magnitude via inverse analysis of paleoliquefaction evidence" @default.
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• W4210316125 doi "https://doi.org/10.1177/87552930211056355" @default.
• W4210316125 hasPublicationYear "2022" @default.
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