Optimizing Nourishment Strategies: A Multi-Model Approach for a Massachusetts Barrier Beach

Abstract: Marsh barrier beaches form a line of defense against storm surges and sea level rise for coastal communities. Along the Massachusetts coastline near Boston, USA, there are several beaches composed of coarse pebbles and cobbles, transitioning into a diverse intertidal zone with mud flats, sand, gravel, and boulders. However, their low elevation and proximity to the ocean render these beaches susceptible to erosion and coastal inundation. Winter storms and Nor'easter events further intensify these threats, posing challenges for both the natural habitats within the system and nearby infrastructure. To address these challenges and optimize coastal protection strategies, advanced numerical modeling techniques are increasingly being used.

One approach to coastal protection is beach and dune nourishment, which involves adding sand or compatible material to replenish the beach profile. This study utilizes the SWAN (Simulating WAves Nearshore) and XBeach coastal modeling tools to evaluate the effectiveness of different beach nourishment strategies under various forcing conditions. SWAN, a third-generation wave model, computes wind-generated waves providing insights for setting boundary conditions in XBeach. SWAN operates by solving the spectral action balance equation, accounting for wave generation, propagation, transformation, and dissipation. XBeach is a process-based numerical model capable of simulating morphological changes during storm events. It computes radiation stress gradients and employs a generalized Lagrangian mean formulation to account for short wave-induced mass fluxes and return flows in shallow waters. Sediment transport rates are calculated via an advection-diffusion equation, incorporating the Soulsby-Van Rijn formulation for equilibrium concentration source-sink terms.

Our study selected four beach profiles, capturing variations in morphology and sediment composition in the area. We then conducted simulations to explore three nourishment scenarios, facilitating a comparison of coastal resilience strategies. Incorporating potential sea-level rise projections, our simulations provided data on key metrics such as post-nourishment wave runup levels, overwash extents, and predicted beach profile changes post-storm. Our analysis extended to evaluating the associated costs of implementing and maintaining each nourishment approach, ensuring a balanced approach between protection benefits and economic feasibility. Furthermore, we identified strategies aimed at minimizing disruption to sensitive habitats, such as adjacent salt marshes, and even incorporated techniques to enhance their overall health and resilience.

Our study utilizes a data-driven methodology to assess nourishment strategies for marsh barrier beaches in Massachusetts. We analyze various factors, including effectiveness, cost-efficiency, and ecological impact. The simulation-derived data aids decision-making and facilitates the adoption of evidence-based coastal protection measures. By integrating environmental, social, and economic considerations, our study contributes to the development of resilient coastal communities. Ultimately, our findings aim to empower decision-makers with the insights needed to implement sustainable and effective coastal protection strategies in the greater Boston area.

Please describe the young professional’s contributions to the project, including but not limited to, building a model, writing a technical report, performing calculations, construction administration and observation tasks, and any aspects of design. (500 words max): Dr. Pontiki selected appropriate numerical models to represent the coastal system under examination. Maria created the model domains and high-resolution computational grids. Subsequently, she established the model's boundary conditions, specifying factors such as wave heights, currents, and water levels.

After grid generation and boundary condition specification, Maria calibrated the numerical models. This involved adjusting model parameters to ensure the model outputs closely align with real-world observations. She then validated the models by comparing simulated results with observed data, such as wave heights, currents, and shoreline positions.

Maria further developed a comprehensive array of coastal management scenarios, considering variables such as sea level rise and extreme storm events. These scenarios were executed within the calibrated models, enabling the prediction of coastal dynamics under diverse forcing conditions. To understand the model responses to variations in specific parameters, Maria conducted sensitivity analyses. Finally, she interpreted the simulation data, suggesting beach nourishment designs.