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- W4306176458 abstract "Existing tidal input reduction approaches applied in accelerated morphodynamic simulations aim to capture the dominant tidal forces in a single or double representative tidal cycle, often referred to as a “morphological tide”. These heavily simplified tidal signals fail to represent the tidal extremes, and hence poorly allow to represent hydrodynamics above the intertidal areas. Here, a generic method is developed to construct a synthetic spring-neap tidal cycle that (1) represents the original signal; (2) is exactly periodic; and (3) is constructed directly from full-complexity boundary information. The starting point is a fortnightly modulation of the semi-diurnal tide to represent spring-neap variation, while conserving periodicity. Diurnal tides and higher harmonics of the semi-diurnal tide are included to represent the asymmetry of the tide. The amplitudes and phases are then adjusted to give a best fit to histograms of water levels and water level gradients. A depth-averaged model of the Ems estuary (The Netherlands) demonstrates the effects of alternative tidal input reduction techniques. Adopting the new approach, the shape of the tidal wave is well-represented over the entire length of the estuary, leading to an improved representation of extreme tidal conditions. In particular, representing intertidal dynamics benefits from the new approach, which is reflected by hydrodynamics and residual sand transport patterns that approach non-schematized tidal dynamics. Future morphodynamic simulations forced with the synthetic signal are expected to show a more realistic exchange of sediment between the channels and tidal flats, likely improving their overall predictive capacity." @default.
- W4306176458 created "2022-10-14" @default.
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- W4306176458 date "2022-10-14" @default.
- W4306176458 modified "2023-10-15" @default.
- W4306176458 title "A synthetic spring-neap tidal cycle for long-term morphodynamic models" @default.
- W4306176458 doi "https://doi.org/10.1002/essoar.10511671.2" @default.
- W4306176458 hasPublicationYear "2022" @default.
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