This paper presents a data-informed, probabilistic methodology employed to assess regional co-seismic landslide hazards in California, primarily by jointly analyzing geologic data and geotechnical properties of various geologic units and incorporating uncertainties in the prediction analyses. Geotechnical data from a borehole database, a California statewide geologic map, and judgment in consultation with local geologists/geotechnical engineers are integrated to estimate a range of plausible shear strength parameters and slope properties that represent the epistemic uncertainty in these parameters. A logic tree approach is implemented to account for the epistemic uncertainties in the input model parameters, as well as in empirical displacement models, that may influence the accuracy of the co-seismic landslide displacement predictions.

Framework for regional earthquake-induced landslide assessment using a data-informed probabilistic approach

Zimmaro P.;
2022

Abstract

This paper presents a data-informed, probabilistic methodology employed to assess regional co-seismic landslide hazards in California, primarily by jointly analyzing geologic data and geotechnical properties of various geologic units and incorporating uncertainties in the prediction analyses. Geotechnical data from a borehole database, a California statewide geologic map, and judgment in consultation with local geologists/geotechnical engineers are integrated to estimate a range of plausible shear strength parameters and slope properties that represent the epistemic uncertainty in these parameters. A logic tree approach is implemented to account for the epistemic uncertainties in the input model parameters, as well as in empirical displacement models, that may influence the accuracy of the co-seismic landslide displacement predictions.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/335694
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