Large-Scale Variation in Wave Attenuation of Oyster Reef Living Shorelines and the Influence of Inundation Duration

One of the paramount goals of oyster reef living shorelines is to achieve sustained and adaptive coastal protection, which requires meeting ecological (i.e., develop a self-sustaining oyster population) and engineering (i.e., provide coastal defense) targets. In a large-scale comparison along the Atlantic and Gulf coasts of the United States, the efficacy of various designs of oyster reef living shorelines at providing wave attenuation was evaluated accounting for the ecological limitations of oysters with regards to inundation duration. A critical threshold for intertidal oyster reef establishment is 50% inundation duration. Living shorelines that spent less than half of the time (\u3c 50%) inundated were not considered suitable habitat for oysters, however, were effective at wave attenuation (68% reduction in wave height). Reefs that experienced \u3e 50% inundation were considered suitable habitat for oysters, but wave attenuation was similar to controls (no reef; ~5% reduction in wave height). Many of the oyster reef living shoreline approaches therefore failed to optimize the ecological and engineering goals. In both inundation regimes, wave transmission decreased with an increasing freeboard (difference between reef crest elevation and water level), supporting its importance in the wave attenuation capacity of oyster reef living shorelines. However, given that the reef crest elevation (and thus freeboard) should be determined by the inundation duration requirements of oysters, research needs to be re-focused on understanding the implications of other reef parameters (e.g. width) for optimising wave attenuation. A broader understanding of the reef characteristics and seascape contexts that result in effective coastal defense by oyster reefs is needed to inform appropriate design and implementation of oyster-based living shorelines globally

Quantification of Wave Attentuation of a Marsh Sill Living Shoreline and Application of Numerical Modeling for Design Optimization and Adaptation

Living shorelines integrate structural and natural features to stabilize the shoreline, through reduction of erosion from the wave climate, while keeping the connectivity between land and aquatic ecosystems. With increasing sea levels, living shorelines have the potential to adapt to changing conditions when compared to armored shorelines due to maintaining a level of interconnectivity between land and water. However, to reduce the ecological tradeoffs associated with any type of shoreline erosion protection project that alters the natural state, the design should seek to minimize structural components to those necessary to provide the protection needed for upland habitat to survive erosive forces for the project design life. For this study, field data were collected at the Captain Sinclair Recreational Area marsh sill living shoreline project in southeastern Virginia. Wave data were collected along two profiles, one across a sill structure and one across a gap between two sills to analyze the wave attenuation properties of the structure and vegetation components of the living shoreline project. Following quantification of the wave attenuation services of this project, the data were used to calibrate a Non-hydrostatic WAVE model, NHWAVE, for additional numerical analysis regarding structure crest elevation and sea level rise. The study showed that the structure profile of the marsh sill design was quite effective at attenuating wave energy across the spectrum, with some frequencies better attenuated than other frequencies. The results of the numerical portion of the study revealed that NHWAVE was able to calibrate well with the landward and marsh gauges from the field study and show that the vegetation portion of the living shoreline design has a greater impact on wave energy attenuation than the crest height of the structure when the latter is reduced in elevation. The numerical modeling assessment also showed the capacity of the living shoreline to adapt to potential sea level rise scenarios for the next 30 years and still provide considerable wave attenuation services

A multi-layer perceptron approach for accelerated wave forecasting in Lake Michigan

[[abstract]]A machine learning framework based on a multi-layer perceptron (MLP) algorithm was established and applied to wave forecasting in Lake Michigan. The MLP model showed desirable performance in forecasting wave characteristics, including significant wave heights and peak wave periods, considering both wind and ice cover on wave generation. The structure of the MLP regressor was optimized by a cross-validated parameter search technique and consisted of two hidden layers with 300 neurons in each hidden layer. The MLP model was trained and validated using the wave simulations from a physics-based SWAN wave model for the period 2005–2014 and tested for wave prediction by using NOAA buoy data from 2015. Sensitivity tests on hyperparameters and regularization techniques were conducted to demonstrate the robustness of the model. The MLP model was computationally efficient and capable of predicting characteristic wave conditions with accuracy comparable to that of the SWAN model. It was demonstrated that this machine learning approach could forecast wave conditions in 1/20,000th to 1/10,000th of the computational time necessary to run the physics-based model. This magnitude of acceleration could enable efficient wave predictions of extremely large scales in time and space.[[notice]]補正完