Uncertainty in Tsunami Sediment Transport Modeling
Bruce Jaffe*,†, Kazuhisa Goto**, Daisuke Sugawara***, Guy Gelfenbaum*, and SeanPaul La Selle*
*US Geological Survey Pacific Coastal and Marine Science Center
2885 Mission Street, Santa Cruz, CA, 95060, USA
**International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
***Museum of Natural and Environmental History, Shizuoka, Japan
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 hybrid modeling approaches to exploit the strengths of forward and inverse models.
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