Person | TU Delft Repository

Tim Leijnse

2 records found

Authored

Computationally Efficient Modelling of Compound Flooding due to Tropical Cyclones with the Explicit Inclusion of Wave-Driven Processes

Research into the required processes and the implementation within the SFINCS model

Master thesis (2018) - T.W.B. Leijnse, A.J.H.M. Reniers, J.D. Bricker, R.J. Labeur, Kees Nederhoff, Maarten van Ormondt

Tropical cyclones (TCs) have tremendous impact on coastal communities in terms of damage due to flooding and high wind velocities, as shown by the recent hurricane season of 2017. Coastal flooding due to TCs can be contributed to different types of forcing (e.g. high offshore water levels, rainfall, etc.), or multiple at the same time (i.e. compound flooding). While the impact of TCs increases, there is the need for better predictions and early warning systems (EWSs). Probabilistic forecasting by modelling different ensembles is wanted to account for uncertainties, which requires fast models. Current modelling options are static models (bathtub approach), which are fast but too simple. Furthermore there are advanced process-based models (like Delft3D, XBeach) which are accurate but too computationally expensive. The solution is the use of a semi-advanced model which solves all relevant processes, but does that in a computationally efficient way. The semi-advanced SFINCS model is developed to solve all necessary processes with computationally efficiency in mind, but is still in its development phase.

This research assesses how compound flooding due to TCs can be modelled in an accurate and computationally efficient way. Besides assessing the relevant physical processes, the implementation in a semi-advanced model is tested. In multiple tests it is shown that for conceptual situations a semi-advanced model can give accurate results within certain limits. Also it is shown in what conditions the advection term of the momentum balance needs to be solved and that a swash zone model approach with an indirect random forcing can give realistic results in 1D runup tests.

A case study of the compound flooding at Jacksonville, Florida, during Hurricane Irma (2017) shows that using a semi-advanced model, a similar accuracy compared to Delft3D can be achieved while being two orders of magnitude faster. Furthermore, a first test with wave-driven flooding in a real case study at Hernani, the Philippines, during Typhoon Haiyan (2013) shows that wave-driven processes have to be explicitly included to model all types of compound flooding. The approach to include these processes with the semi-advanced SFINCS model gives reasonable results compared to XBeach, although they can be further improved with more research. The resulting computational efficiency seems to get in the right range as needed for EWSs.

Contributed

Efficient and accurate modeling of wave-driven flooding on coral reef-lined coasts

On the interpolation of parameterized boundary conditions

Master thesis (2021) - V. Bertoncelj, M.F.S. Tissier, Ap Van Dongeren, T.W.B. Leijnse, S.G. Pearson, J.D. Bricker, F.E. Roelvink

Many coral reef islands are low-lying, which in combination with population growth, sea level rise and possibly more frequent extreme weather events is likely to result in increased coastal risk (e.g. Storlazzi et al., 2015). On smaller scales of O(10 km) wave-driven coastal inundation can be accurately predicted with advanced models such as XBeach (Roelvink et al., 2009), at already high computational costs. For larger scales, larger number of islands, for scenario modelling, and for implementation in early warning systems, computationally faster methods are needed. Reduced physics models, which neglect some of the processes (e.g. non-hydrostatic pressure gradient term and viscosity), are a potential solution. However, their accuracy and the best method to force them has not been established. In this research we propose a new methodology to model wave-driven flooding on coral reef-lined coasts. A look-up-table (LUT), composed of XBeach model runs, is combined with a reduced-physics model, SFINCS (Leijnse et al., 2021), to achieve high accuracy predictions at limited computational expense. The LUT consists of pre-run 1D XBeach simulations for several reef profiles from Scott et al. (2020), forced with different offshore wave and water level conditions. Wave conditions close to the shore as predicted by the LUT are used to force SFINCS which then simulates the wave runup, overtopping and flooding. These are forced in SFINCS using random wave timeseries from an interpolated parameterized wave spectrum following Athif (2020). The accuracy of the method is investigated for 6 distinctive cross-shore profiles from Scott et al. (2020), for two wave scenarios (gentle swell and stormy conditions). Results of complete XBeach simulations are compared to LUT-SFINCS simulations with different boundary forcing locations. The sensitivity analysis shows that the most optimal boundary location to initialize the SFINCS model is at a water depth of 0.5 m, shore-ward of the reef edge. Interpolation of the forcing conditions at the boundary is investigated with 9 different interpolation methods. Results reveal that the most accurate method to interpolate spectral parameters (the amount of high frequency wave energy, the amount of low frequency wave energy and the frequency peak of high frequency part of the spectrum) and wave setup at the boundary is the Inverse Distance Weighting method with a power of -2. Errors introduced by the interpolated parameterized boundary conditions lead to runup estimation errors of 10-20% on average with the maximal errors up to 60%. Simulating wave runup with XBeach LUT – SFINCS couple leads to about 50-times higher computational speed compared to the XBeach model simulating hydrodynamic processes along the entire reef profile.