Machine learning improves the modelled wave spectrum in the North Sea

To improve the energy density and directional spectra computed with the SWAN model for the North Sea, a data-driven model is trained to correct the SWAN spectra. After training of the data-driven model on a year of observed and modelled data, the energy density and directional spectrum are corrected for three locations in the North Sea. When...

Efficient two-layer non-hydrostatic wave model with accurate dispersive behaviour

A 2-layer non-hydrostatic model with improved dispersive behaviour is presented. Due to the assumption of a constant non-hydrostatic pressure distribution in the lower layer, the dispersive behaviour is improved without much additional computational time. A comparison with linear wave theory showed that this 2-layer model gives a better...

Determining water reservoir characteristics with global elevation data

Quantification of human impact on water, sediment, and nutrient fluxes at the global scale demands characterization of reservoirs with an accuracy that is presently unavailable. This letter presents a new method, based on virtual dam placement, to make accurate estimations of area-volume relationships of large reservoirs, using solely readily...