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Deciphering past earthquakes from the probabilistic modeling of paleoseismic records – the Paleoseismic EArthquake CHronologies code (PEACH, version 1)

Gómez-Novell, O; Pace, B; Visini, F; Faure Walker, J; Scotti, O; (2023) Deciphering past earthquakes from the probabilistic modeling of paleoseismic records – the Paleoseismic EArthquake CHronologies code (PEACH, version 1). Geoscientific Model Development , 16 (24) pp. 7339-7355. 10.5194/gmd-16-7339-2023. Green open access

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Abstract

A key challenge in paleoseismology is constraining the timing and occurrence of past earthquakes to create an earthquake history along faults that can be used for testing or building fault-based seismic hazard assessments. We present a new methodological approach and accompanying code (Paleoseismic EArthquake CHronologies, PEACH) to meet this challenge. By using the integration of multi-site paleoseismic records through probabilistic modeling of the event times and an unconditioned correlation, PEACH improves the objectivity of constraining paleoearthquake chronologies along faults, including highly populated records and poorly dated events. Our approach reduces uncertainties in event times and allows increased resolution of the trench records. By extension, the approach can potentially reduce the uncertainties in the estimation of parameters for seismic hazard assessment such as earthquake recurrence times and coefficient of variation. We test and discuss this methodology in two well-studied cases: the Paganica Fault in Italy and the Wasatch Fault in the United States.

Type: Article
Title: Deciphering past earthquakes from the probabilistic modeling of paleoseismic records – the Paleoseismic EArthquake CHronologies code (PEACH, version 1)
Open access status: An open access version is available from UCL Discovery
DOI: 10.5194/gmd-16-7339-2023
Publisher version: http://dx.doi.org/10.5194/gmd-16-7339-2023
Language: English
Additional information: © Author(s) 2023. This work is distributed under the Creative Commons Attribution 4.0 License.
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10185956
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