Abstract
Abstract. This paper describes a methodology to stochastically simulate a large number of storm surge scenarios (here: 10 million). The applied model is very cheap in computation time and will contribute to improve the overall results from integrated risk analyses in coastal areas. Initially, the observed storm surge events from the tide gauges of Cuxhaven (located in the Elbe estuary) and Hörnum (located in the southeast of Sylt Island) are parameterised by taking into account 25 parameters (19 sea level parameters and 6 time parameters). Throughout the paper, the total water levels are considered. The astronomical tides are semidiurnal in the investigation area with a tidal range >2 m. The second step of the stochastic simulation consists in fitting parametric distribution functions to the data sets resulting from the parameterisation. The distribution functions are then used to run Monte-Carlo-Simulations. Based on the simulation results, a large number of storm surge scenarios are reconstructed. Parameter interdependencies are considered and different filter functions are applied to avoid inconsistencies. Storm surge scenarios, which are of interest for risk analyses, can easily be extracted from the results.
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