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Shared Chronologies: developing tools to improve age–depth modeling by incorporating common event layers among several sedimentary records
  • Rodrigo Vega,
  • Daniel Melnick
Rodrigo Vega
Instituto de Ciencias de la Tierra, Universidad Austral de Chile

Corresponding Author:[email protected]

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Daniel Melnick
Instituto de Ciencias de la Tierra, Universidad Austral de Chile
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Abstract

Sedimentary records provide an invaluable background for understanding of complex phenomena that vary within multiple spatio--temporal scales, such as climate and the seismic cycle. Understanding the latter in southern Chile has yielded motivation to develop new tools to deal with such records, in order to build a comprehensive peleoseismic catalog from them. The region inherited an extensive chain of lakes from the pleistocene glaciations, and a strong tephrochronological framework has been developed during the last two decades. Lake deposits have been extensively studied and shown to contain an incredibly sensitive paleoseismic record in the form of lacustrine turbidites. The task is thus to build the best possible chronology making use of all available data. Age--depth modeling is now routinely done by means of bayesian techniques, by using a sedimentation model as prior information and a set of age determinations as data. This approach provides the best results for any single record, but not necessarily for a set of records taken together. This is the goal of the shared chronologies approach, to build the tools for estimating the best chronologies for a set of sedimentary records given some chronological data for each and a set of shared events or stratigraphic markers. We use for this purpose the fact that two or more of such layers should yield age differences close to zero, within the general age uncertainty. This fact is incorporated to the model as prior information, along with the sedimentation model. The idea is clearly usable in a wide range of contexts, and for this reason we would like to share the implementation in a very early stage of development in order to incorporate feedback into design decisions that could affect extensibility and modularity, and to forge collaboration. This contribution shares an early experiment against a simulated data set, as well as the current R implementation and future plans.