Failure of grass covered flood defences with roads on top due to wave overtopping

A probabilistic assessment method

Journal Article (2018)
Author(s)

Juan Pablo Aguilar-López (University of Twente, TU Delft - Hydraulic Structures and Flood Risk)

Jord J. Warmink (University of Twente)

Anouk Bomers (University of Twente)

RMJ Schielen (Rijkswaterstaat, University of Twente)

Suzanne J.M.H. Hulscher (University of Twente)

Research Group
Hydraulic Structures and Flood Risk
DOI related publication
https://doi.org/10.3390/jmse6030074
More Info
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Publication Year
2018
Language
English
Research Group
Hydraulic Structures and Flood Risk
Issue number
3
Volume number
6
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Abstract

Hard structures, i.e., roads, are commonly found over flood defences, such as dikes, in order to ensure access and connectivity between flood protected areas. Several climate change future scenario studies have concluded that flood defences will be required to withstand more severe storms than the ones used for their original design. Therefore, this paper presents a probabilistic methodology to assess the effect of a road on top of a dike: it gives the failure probability of the grass cover due to wave overtopping over a wide range of design storms. The methodology was developed by building two different dike configurations in computational fluid dynamics Navier-Stokes solution software; one with a road on top and one without a road. Both models were validated with experimental data collected from field-scale experiments. Later, both models were used to produce data sets for training simpler and faster emulators. These emulators were coupled to a simplified erosion model which allowed testing storm scenarios which resulted in local scouring conditioned statistical failure probabilities. From these results it was estimated that the dike with a road has higher probabilities (5 × 10-5 > Pf > 1 × 10-4) of failure than a dike without a road (Pf < 1 × 10-6) if realistic grass quality spatial distributions were assumed. The coupled emulator-erosion model was able to yield realistic probabilities, given all the uncertainties in the modelling process and it seems to be a promising tool for quantifying grass cover erosion failure.