Vegetation in front of levees, dikes and seawalls can decrease wave energy and therefore contribute to the safety against flooding. However, wave damping predictions by vegetation are still inaccurate due to measurement and modelling uncertainties. Many studies focused on finding reliable predictive tools using scaled flume tests with vegetation mimics. Scaling down vegetation can however lead to discrepancies with realistic scales, known as scale errors. In this work scaled tests were conducted on 3D-printed elastic replicas of willow trees and compared with real-scale experiments. We identified differences in measured wave dissipation between the scaled hydraulic model (1:10) and its real-scale prototype with 5m high live willow trees under storm conditions (1:1). The maximum measured wave damping (30%) was roughly 1.5 times higher than the real-scale experiments (20%). Following the same trend of the real-scale experiments, this amount of wave height damping declined for larger water levels. Largest effects are argued to be due to increased viscous damping (smaller branch Reynolds numbers) and non-exact flexibility scaling. These significant deviations illustrate that full-scale experiments, although expensive, are still needed to validate the results of scaled experiments for woody vegetation. Alternatively, accounting for these discrepancies can make scaled experiments more reliable and expensive real-scale experiments less needed for wave damping studies on woody vegetation.

Worldwide, communities are facing increasing flood risk, due to more frequent and intense hazards and rising exposure through more people living along coastlines and in flood plains. Nature-based Solutions (NbS), such as mangroves, and riparian forests, offer huge potential for adaptation and risk reduction. The capacity of trees and forests to attenuate waves and mitigate storm damages receives massive attention, especially after extreme storm events. However, application of forests in flood mitigation strategies remains limited to date, due to lack of real-scale measurements on the performance under extreme conditions. Experiments executed in a large-scale flume with a willow forest to dissipate waves show that trees are hardly damaged and strongly reduce wave and run-up heights, even when maximum wave heights are up to 2.5 m. It was observed for the first time that the surface area of the tree canopy is most relevant for wave attenuation and that the very flexible leaves limitedly add to effectiveness. Overall, the study shows that forests can play a significant role in reducing wave heights and run-up under extreme conditions. Currently, this potential is hardly used but may offer future benefits in achieving more adaptive levee designs.

The last years, capacity of vegetation to reduce wave impact is receiving considerable attention. To predict wave attenuation processes within vegetation fields reliable estimates of vegetation parameters are needed. This proves to be difficult for woody vegetation as it consists of complex branch structures, characterized by varying branch densities, diameters and angles. State of the art physical and numerical models effectively use a single value for the diameter, b _v and density, N of vegetation, which is unrepresentative for complex vegetation, such as trees. Trees can be better described by the projected frontal-surface area, A _v. Hence, this work compares methods to quantify the A _v in space for a pollard willow forest, and determines suitability of these methods for predicting wave attenuation using a spectral wave model (SWAN). We use data from manual measurements and Terrestrial Laser Scans (TLS), to estimate the vertical distribution of A _v; and data from large-scale flume experiments performed on a willow forest to verify model sensitivity to A _v inferences. As a baseline for comparison, tree models that describe the structure of the trees in various degrees of complexity are compiled. The most realistic tree model is used to quantify potential errors in TLS and basic manual measurements of N and b _v. An initial comparison shows that the TLS data underestimates A _v, which indicates that conducting manual measurements is more suitable to quantify a homogeneous forest. We found that the TLS suffers from shadowing effects (i.e., blockage of laser beams) and we recommend to apply a correction factor to improve its measurements. Furthermore, we identified the impact that the different methods to determine A _v have on the estimation of wave attenuation using SWAN; in addition we verified the model results with data from large-scale flume experiments performed on the willow forest. The modeled sensitivity tests indicate large differences in wave attenuation and, consequently, a wide range (0.94–1.70) of bulk drag coefficients, (Formula presented.), for the various methods applied. This shows the variation of outcome between measuring methods and highlights the importance of stating the selected method for reliable frontal-surface area estimations, and consequently for reliable wave attenuation predictions.