Uncertainty in tsunami sediment transport modeling

Bruce Jaffe, Kazuhisa Goto, Daisuke Sugawara, Guy Gelfenbaum, Sean Paul La Selle

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)

Abstract

Erosion and deposition from tsunamis record information about tsunami hydrodynamics and size that can be interpreted to improve tsunami hazard assessment. We explore sources and methods for quantifying uncertainty in tsunami sediment transport modeling. Uncertainty varies with tsunami, study site, available input data, sediment grain size, and model. Although uncertainty has the potential to be large, published case studies indicate that both forward and inverse tsunami sediment transport models perform well enough to be useful for deciphering tsunami characteristics, including size, from deposits. New techniques for quantifying uncertainty, such as Ensemble Kalman Filtering inversion, and more rigorous reporting of uncertainties will advance the science of tsunami sediment transport modeling. Uncertainty may be decreased with additional laboratory studies that increase our understanding of the semi-empirical parameters and physics of tsunami sediment transport, standardized benchmark tests to assess model performance, and development of hybridmodeling approaches to exploit the strengths of forward and inverse models.

Original languageEnglish
Pages (from-to)647-661
Number of pages15
JournalJournal of Disaster Research
Volume11
Issue number4
DOIs
Publication statusPublished - 2016 Aug

Keywords

  • Modeling
  • Sedimentary deposits
  • Tsunami sediment transport
  • Uncertainty

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Engineering (miscellaneous)

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