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Modeling compound flooding in coastal systems using a computationally efficient reduced-physics solver: Including fluvial, pluvial, tidal, wind- and wave-driven processes
被引:58
|作者:
Leijnse, Tim
[1
]
van Ormondt, Maarten
[1
]
Nederhoff, Kees
[2
]
van Dongeren, Ap
[1
,3
]
机构:
[1] Deltares, Marine & Coastal Syst, Boussinesqweg 1, NL-2629 HV Delft, Netherlands
[2] Deltares USA, 8601 Georgia Ave,Suite 508, Silver Spring, MD 20910 USA
[3] IHE Delft, Water Sci & Engn Dept, Westvest 7, NL-2611 AX Delft, Netherlands
关键词:
Compound flooding;
Wave-driven flooding;
Flooding;
Reduced-physics solver;
Tropical cyclones;
SFINCS;
STORM-SURGE;
INUNDATION;
RIVER;
UNCERTAINTIES;
PREDICTIONS;
ASSESSMENTS;
EQUATIONS;
SCHEME;
SWASH;
RISK;
D O I:
10.1016/j.coastaleng.2020.103796
中图分类号:
TU [建筑科学];
学科分类号:
0813 ;
摘要:
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.
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