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Tsunami deposits are recordings of tsunami events that contain informationabout flow conditions. Deciphering quantitative information from tsunamideposits is especially important for analyzing paleo-tsunami events in whichdeposits comprise the only leftover physical evidence. The physical meaning ofthe deciphered quantities depends on the physical assumptions that are applied.The aim of our study is to estimate the characteristics of tsunamis andquantify the errors and uncertainties that inherent within them. To achievethis goal, we apply the TSUFLIND-EnKF inversion model to study the depositionof an idealized deposit created by a single tsunami wave and one real case from2004 India ocean tsunami. TSUFLIND-EnKF model combines TSUFLIND for thedeposition module with the Ensemble Kalman Filtering (EnKF) method. In ourmodeling, we assume that grain-size distribution and thickness from theidealized deposits at different depths can be used as an observationalvariable. Our tentative results indicate that sampling methods and samplingfrequencies of tsunami deposits influence not only the magnitude of theinverted variables, but also their errors and uncertainties. An interestingresult of our technique is that a larger number of samples from a given tsunamideposit does not automatically mean that the inversion results are more robustwith smaller errors and decreased uncertainties.

TSUFLIND-EnKF inversion model applied to tsunami deposits for estimation of transient flow depth and speed with quantified uncertainties