Modeling compound flooding in coastal systems using a computationally efficient reduced-physics solver: Including fluvial, pluvial, tidal, wind- and wave-driven processes
Modeling compound flooding in coastal systems using a computationally efficient reduced-physics solver: Including fluvial, pluvial, tidal, wind- and wave-driven processes
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DOI:
10.1016/j.coastaleng.2020.103796
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发表时间:
2021-01-01
影响因子:
4.4
通讯作者:
van Dongeren, Ap
中科院分区:
文献类型:
--
作者:
Leijnse, Tim;van Ormondt, Maarten;van Dongeren, Ap
SFINCS, a new reduced-physics solver to compute compound flooding in coastal systems due to fluvial, pluvial, tidal, windand wave-driven processes in a computationally efficient way, is presented and validated for a number of verification and application cases. The model solves simplified equations of mass and momentum, which are driven by storm surge and wave boundary conditions, precipitation rates and upstream river discharges. It includes spatially-varying infiltration and bed roughness terms as well as an absorbing-generating seaward boundary to enable wave-driven flooding. Furthermore, advection and wind stress terms can be included. We demonstrate for the application case of hurricane impact on Jacksonville (Florida, USA) that the observed flooding was a combination of fluvial, pluvial, tidal and wind-driven flooding and that this can be modeled well using the reduced-physics solver. We show that the addition of an advection term to the momentum equations is necessary to model shock flows such as dam breaks but also incident broken waves. Thus, wave-driven flooding can be modeled with high computational efficiency and adequate accuracy as demonstrated for the case of Hernani (the Philippines). The model results show the potential of achieving good accuracy at limited computational expense.