  Tsunami deposits are recordings of tsunami events that contain information
about flow conditions. Deciphering quantitative information from tsunami
deposits is especially important for analyzing paleo-tsunami events in which
deposits comprise the only leftover physical evidence. 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 errors and uncertainties that inherent within them. 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
2004 India ocean tsunami. TSUFLIND-EnKF model 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 tentative 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.
