Abstract
In this paper, an advanced probabilistic method - Adaptive Directional Importance Sampling (ADIS) - is used in concert with a process-based dune erosion model - XBeach - to perform a dune safety assessment. The efficiency of the probabilistic method removes the restriction of only using simple empirical dune erosion models for probabilistic calculations. The proposed combination of ADIS and XBeach is able to handle complex cross-shore profiles that empirical dune erosion models cannot, as shown in several case studies.
Highlights
Reduction of flood risk in densely inhabited and economically valuable coastal zones is an important challenge for many coastal regions
To demonstrate the accuracy and efficiency of the Adaptive Directional Importance Sampling (ADIS) method, the Duros+ dune erosion model is used in combination with both ADIS and Monte Carlo with Importance Sampling
There is a difference in the resulting failure probability between the two probabilistic methods, but it is considered acceptably small considering the large gain in efficiency
Summary
Reduction of flood risk in densely inhabited and economically valuable coastal zones is an important challenge for many coastal regions. To be able to assess the present and future safety level of dune coasts, a dune safety assessment method, accounting for uncertainties in hydraulic forcing conditions, is necessary. For a limited number of representative locations, the normative hydraulic boundary conditions are determined in a fully probabilistic manner. These normative hydraulic boundary conditions are translated to the remaining locations through spatial interpolation. Using these normative boundary conditions, a single deterministic 1D dune erosion model calculation is carried out for each location, to determine whether that location meets the legal normative safety level
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