Wave damping potential of woody riparian vegetation

Abstract

Including vegetation in flood defense systems has the potential to be a more cost-effective solution than conventional dike reinforcement measures, as vegetation contains wave damping properties. However, more insight is required on the complex physical processes due to wave-vegetation interaction in order to predict the amount of wave damping. Past research found that these processes are dependent on both flow conditions and vegetation characteristics. Therefore, reliable quantification of these vegetation characteristics is
of importance to understand these processes and thus to improve predictions for wave dissipation due to vegetation. This study aims to gain insight on practical methods for quantifying relevant vegetation characteristics
for wave damping. Data is used from full scale physical experiments conducted in the Delta Flume at Deltares, with 40 meters of willow forest. The vegetation characteristics are quantified in this study both by manual measurements on the willow trees and by executing Terrestrial 3D laser scans (TLS) of the whole forest. The frontal area of vegetation is found in literature to be a relevant parameter for determining the wave attenuation, therefore the focus in this study lies on schematizing this parameter over the vertical, which is seen as representations of the average willow tree. This schematization is referred to in this report as “tree model”. In this study, four tree models are obtained. The four tree models include: tree model 1a (manual measurements on the primary branches, excluding side branches), tree model 1b (branching method based on Strahlers ordering scheme, including side branches), tree model 1c (adjusted branching method) and tree model 2 (from terrestrial laser scanner). The reconstructed area from the TLS point cloud is determined by using Matlab built-in alpha shape function. The tree models are compared in terms of frontal area distribution over the vertical and of their effect on the corresponding wave attenuation. The latter comparison is achieved by using the numerical wave model SWAN and confronting the results with the measured wave attenuation from the physical experiments. With regards to the manual measuring methods, the frontal area of the average tree from tree model 1a serves as a lower limit, while tree model 1b gives the upper limit. The TLS outcome (tree model 2) underestimates the frontal area as computed by the other tree models. In particular, the underestimation is 70% when compared with tree model 1b, and 30 % when compared to tree model 1a. Adjustments on tree model 1b leads to tree model 1c. This tree model accounts for the tapering form of the branches and results in a total frontal area in between tree model 1a and tree model 1b. In this study, the representative area for the willow trees can be best captured with tree model 1c. This tree model results in a drag coefficient (CD) of 1.15 averaged over the tests with leafless willows and showed a negative correlation with the Keulegan-Carpenter number (KC). However, the capabilities of the TLS should be analyzed further and this study encourages to use a larger data set of trees in order to find a relation between the laser penetration and corresponding mismatch. Gathering of vegetation parameters by hand is in fact not economically attractive forwoody riparian vegetation, as these trees are characterized by complex canopy structures and high elevations. The TLS can serve as a practical tool for obtaining these relevant vegetation parameters for applying willows in hybrid solutions.