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A wave damping model for flexible marsh plants with leaves considering linear to weakly nonlinear wave conditions.

Authors :
Zhang, Xiaoxia
Lin, Pengzhi
Nepf, Heidi
Source :
Coastal Engineering. Aug2022, Vol. 175, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

Marsh plants protect the coasts and coastal communities by dissipating wave energy. The dissipation of wave energy depends on the geometric (leaf and stem dimensions) and mechanical (material rigidity) properties of the plants. First, flexible plants bend in response to hydrodynamic drag (called reconfiguration), which diminishes wave decay relative to a rigid plant of the same morphology. Second, mutual sheltering between plant leaves and stem can reduce the drag, and thus wave damping. This study connects the prediction of drag on an individual plant and the measurement of wave decay over a meadow of plants to build a physically-based wave-damping model that includes leaves, the impact of reconfiguration, and the impact of sheltering between plant elements. Model plants were constructed to be both geometrically and dynamically similar to Spartina alterniflora. The wave damping model assumed linear wave conditions, but was validated using a wide range of weakly nonlinear wave conditions within model plants, over a patch of live Spartina anglica in the laboratory, and over a meadow of Spartina alterniflora in the field. After validation, the model was used to explore the variation in wave decay over a range of wave parameters and plant geometric and bio-mechanic parameters, including stem length, stem diameter, number of leaves per plant, leaf length, leaf width, the rigidity of the stem and the leaf. • A physics-based prediction for wave dissipation by flexible marsh plants with leaves was developed and validated with laboratory experiments. • The dependence of wave dissipation on water depth, wave amplitude, and wave period was explored in detail with model predictions. • The impact of leaf and stem geometry and mechanical properties on wave dissipation were revealed by systematic model predictions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03783839
Volume :
175
Database :
Academic Search Index
Journal :
Coastal Engineering
Publication Type :
Academic Journal
Accession number :
157250297
Full Text :
https://doi.org/10.1016/j.coastaleng.2022.104124