Integrating incident and infragravity wave effects in a fast compound flood model
Authors: Leijnse Tim , van Dongeren Ap , van Ormondt Maarten , Aerts Jeroen , Muis Sanne 
Published: March 2024

Coastal communities worldwide are under threat of flooding due to multiple hazards (Mousavi et al., 2011). In some coastal areas, waves are the dominant driver of extreme water levels (Parker et al., 2023). However, for regional to continental scales coastal flooding assessments, waves are often not or only crudely accounted for, due to the high computational expense of wave resolving numerical models (e.g., XBeach; Roelvink et al., 2009).Recently, Leijnse et al. (2021) has shown that it is possible to model waves in a fast reduced-complexity compound flood model such as SFINCS. However, boundary conditions for SFINCS are still derived from a computationally expensive numerical model like XBeach or are generated using 1D based (meta) models (e.g., Bertoncelj et al., 2021), that do not (fully) account for alongshore varying 2D effects. To be able to include dynamic wave runup and overtopping in a 2D fast flooding model, we need to derive nearshore infragravity wave conditions also in a fast way.To overcome this challenge, we introduce an integrated model approach, where we couple a fast stationary wave spectral model (SnapWave) to the fast compound flood model SFINCS. Besides incident waves, the SnapWave model can also efficiently estimates nearshore infragravity wave conditions (Leijnse et al. 2024, in review). Together with a nearshore wave generating boundary condition (van Ormondt et al., 2023), our new integrated wave-resolving approach internally drives the flood model SFINCS with waves and can therefore assess the effects of waves on coastal flooding. The performance is validated for several laboratory tests and against XBeach simulations of van Ormondt et al. (2021).ReferencesBertoncelj, V., Leijnse, T., Roelvink, F., Pearson, S., Bricker, J., Tissier, M., and van Dongeren, A.: Efficient and accurate modeling of wave-driven flooding on coral reef-lined coasts: Case Study of Majuro Atoll, Republic of the Marshall Islands, EGU General Assembly 2021, online, 19&#8211;30 Apr 2021, EGU21-5418, https://doi.org/10.5194/egusphere-egu21-5418, 2021.Leijnse, van Ormondt, Nederhoff, van Dongeren (2021). Modeling compound flooding in coastal systems using a computationally efficient reduced-physics solver: Including fluvial, pluvial, tidal, wind- and wave-driven processes. Coastal Engineering, 163, 103796. https://doi.org/10.1016/j.coastaleng.2020.103796Leijnse, van Ormondt, van Dongeren, Aerts, Muis (2024, in review). Estimating nearshore infragravity wave conditions at large spatial scales. Frontiers in Marine Science.Mousavi, Irish, Frey, Olivera, Edge (2011). Global warming and hurricanes: The potential impact of hurricane intensification and sea level rise on coastal flooding. Climatic Change, 104(3&#8211;4), 575&#8211;597. https://doi.org/10.1007/s10584-009-9790-0Parker, Erikson, Thomas, Nederhoff, Barnard, Muis (2023). Relative contributions of water-level components to extreme water levels along the US Southeast Atlantic Coast from a regional-scale water-level hindcast. Natural Hazards. https://doi.org/10.1007/s11069-023-05939-6Roelvink, Reniers, van Dongeren, van Thiel de Vries, McCall, Lescinski (2009). Modelling storm impacts on beaches, dunes and barrier islands. Coastal Engineering, 56(11&#8211;12), 1133&#8211;1152. https://doi.org/10.1016/j.coastaleng.2009.08.006Van Ormondt, Roelvink, van Dongeren (2021). A Model-Derived Empirical Formulation for Wave Run-Up on Naturally Sloping Beaches. Journal of Marine Science and Engineering, 9(11), 1185. https://doi.org/10.3390/jmse9111185Van Ormondt, Roelvink, van Dongeren (2023). Wave effects in a rapid compound flood model. 17th International Workshop on Wave Hindcasting and Forecasting.