Extreme Sea Level Estimation Combining Systematic Observed Skew Surges and Historical Record Sea Levels
Abstract
The estimation of sea levels corresponding to high return periods is crucial for coastal planning
and for the design of coastal defenses. This paper deals with the use of historical observations, that is, events
that occurred before the beginning of the systematic tide gauge recordings, to improve the estimation of design
sea levels. Most of the recent publications dealing with statistical analyses applied to sea levels suggest that
astronomical high tide levels and skew surges should be analyzed and modeled separately. Historical samples
generally consist of observed record sea levels. Some extreme historical skew surges can easily remain
unnoticed if they occur at low or moderate astronomical high tides and do not generate extreme sea levels.
The exhaustiveness of historical skew surge series, which is an essential criterion for an unbiased statistical
inference, can therefore not be guaranteed. This study proposes a model combining, in a single Bayesian
inference procedure, information of two different natures for the calibration of the statistical distribution of
skew surges: measured skew surges for the systematic period and extreme sea levels for the historical period.
A data-based comparison of the proposed model with previously published approaches is presented based on
a large number of Monte Carlo simulations. The proposed model is applied to four locations on the French
Atlantic and Channel coasts. Results indicate that the proposed model is more reliable and accurate than
previously proposed methods that aim at the integration of historical records in coastal sea level or surge
statistical analyses.
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