TSUFLIND-EnKF: Inversion of tsunami flow depth and flow speed from deposits with quantified uncertainties

TSUFLIND-EnKF: Inversion of tsunami flow depth and flow speed from deposits with quantified... Deciphering quantitative information from tsunami deposits is especially important for analyzing paleotsunami events in which deposits comprise one of the leftover physical evidences. The physical meaning of the deciphered quantities depends on the physical assumptions that are applied. The aim of our study is to estimate the characteristics of tsunamis and quantify the associated errors and uncertainties. To achieve this goal, we apply the TSUFLIND-EnKF inversion model to study the deposition of an idealized deposit created by a single tsunami wave and one real case from the 2004 Indian Ocean tsunami. TSUFLIND-EnKF combines TSUFLIND for the deposition module with the Ensemble Kalman Filtering (EnKF) method. In our modeling, we assume that grain-size distribution and thickness from the idealized deposits at different depths can be used as an observational variable. Our results indicate that sampling methods and sampling frequencies of tsunami deposits influence not only the magnitude of the inverted variables, but also their errors and uncertainties. An interesting result of our technique is that a larger number of samples from a given tsunami deposit does not automatically mean that the inversion results are more robust with smaller errors and decreased uncertainties. TSUFLIND-EnKF presents the final inversion results as a probability density distribution function instead of only one value or range of values. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Marine Geology Elsevier

TSUFLIND-EnKF: Inversion of tsunami flow depth and flow speed from deposits with quantified uncertainties

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Publisher
Elsevier
Copyright
Copyright © 2016 Elsevier B.V.
ISSN
0025-3227
eISSN
1872-6151
D.O.I.
10.1016/j.margeo.2016.11.009
Publisher site
See Article on Publisher Site

Abstract

Deciphering quantitative information from tsunami deposits is especially important for analyzing paleotsunami events in which deposits comprise one of the leftover physical evidences. The physical meaning of the deciphered quantities depends on the physical assumptions that are applied. The aim of our study is to estimate the characteristics of tsunamis and quantify the associated errors and uncertainties. To achieve this goal, we apply the TSUFLIND-EnKF inversion model to study the deposition of an idealized deposit created by a single tsunami wave and one real case from the 2004 Indian Ocean tsunami. TSUFLIND-EnKF combines TSUFLIND for the deposition module with the Ensemble Kalman Filtering (EnKF) method. In our modeling, we assume that grain-size distribution and thickness from the idealized deposits at different depths can be used as an observational variable. Our results indicate that sampling methods and sampling frequencies of tsunami deposits influence not only the magnitude of the inverted variables, but also their errors and uncertainties. An interesting result of our technique is that a larger number of samples from a given tsunami deposit does not automatically mean that the inversion results are more robust with smaller errors and decreased uncertainties. TSUFLIND-EnKF presents the final inversion results as a probability density distribution function instead of only one value or range of values.

Journal

Marine GeologyElsevier

Published: Feb 1, 2018

References

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