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A new predictive tool for modeling wave attenuation produced by saltmarshes in SWAN based on standing biomass

Abstract: Several numerical tools have been developed to quantify the wave height decay through vegetation, such as saltmarshes. Among them, one of the most widely used is SWAN (Simulating Waves Nearshore), where Suzuki et al. (2012) implemented and validated Mendez and Losada (2004) formulation. The reliability of this approach is based on a good estimation of plant traits and the suitable choice of the bulk drag coefficient (?CD), which is usually used as a calibration coefficient. Recently, Maza et al. (2022) described a new predictive approach to quantify wave attenuation by saltmarshes without the need for calibration coefficients. They estimate the wave damping coefficient (?) as a function of the Hydraulic Standing Biomass (HSB), a parameter defined as a function of the standing biomass, the mean height of the meadow and the wave incident conditions. In this work, Maza et al. (2022) formulation is implemented in SWAN, and validation with laboratory and field data is carried out for six saltmarsh species, showing the good performance of SWAN without calibration. Additionally, the model is extended for including standing biomass and plant height spatial variation to consider the natural variability of the vegetation characteristics along a transect from the lower-marsh to the upper-marsh. Finally, it is shown that the new implementation presents significant advantages in the modeling of wave height evolution along different saltmarsh fields when compared with the standard drag-based approach applied by using existing empirical formulations.

Otras publicaciones de la misma revista o congreso con autores/as de la Universidad de Cantabria

 Fuente: Coastal Engineering, 2023, 185, 104380

Editorial: Elsevier

 Año de publicación: 2023

Nº de páginas: 14

Tipo de publicación: Artículo de Revista

 DOI: 10.1016/j.coastaleng.2023.104380

ISSN: 0378-3839,1872-7379

 Proyecto español: RTI2018-097014-B-I00

Url de la publicación: https://doi.org/10.1016/j.coastaleng.2023.104380