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In response to potential increasing rate of sea-level rise, planners and engineers are making accommodations in their management plans for protection of coastal infrastructure and natural resources. Dunes and barrier islands are important for coastal protection and restoration, because they absorb storm energy and play an essential role in sediment transportation. Most of traditional coastal models do not simulate joint evolution of dunes and barrier islands and do not explicitly address sea-level rise. A new model was developed in this study that represents basic barrier island processes under sea-level rise and links dynamics of different components of barrier islands. The model was used to evaluate near-future (100 years) responses of a semi-synthetic island, with the characteristics of Santa Rosa Island of Florida, USA, to five rates of sea-level rise. The new model is capable of representing considerable practical information about effects of different sea level rise scenarios on the test island. The modeling results show that different areas and components of the island have different responses to sea-level rise. Depending on the rate of sea level rise and overwash sediment supply, evolution of dunes and barrier islands is important to habitat suitable for coastal birds or to backbarrier salt marshes. The modeling results are inherently uncertain due to unknown storm variability and sea-level rise scenarios. The storm uncertainty, characterized as parametric uncertainty, and its propagation to the modeling results, were assessed using the Monte Carlo (MC) method for the synthetic barrier island. A total of 1000 realizations of storm magnitude, frequency, and track through a barrier island were generated and used for the MC simulation. To address the scenario uncertainty, five sea-level rise scenarios were considered using the current rate and four additional rates that lead to sea-level rise of to 0.5m, 1.0m, 1.5m, and 2.0m in the next 100 years. Parametric uncertainty in the simulated beach dune heights and the backshore positions was assessed for the individual scenarios. For a given scenario, the parametric uncertainty varies with time, becoming larger when time increases. For different sea-level rise scenarios, the parametric uncertainty is different, being larger for more severe sea-level rise. The method of scenario averaging was used to quantify the scenario uncertainty. The scenario averaging results are between the results of smallest and largest sea-level rise scenarios. The results of uncertainty analysis provide guidelines for coastal management and protection of coastal ecology.
A Thesis submitted to the Department of Scientific Computing in partial fulfillment of the requirements for the degree of Master of Science.
Includes bibliographical references.
Ming Ye, Professor Directing Thesis; Dennis Slice, Committee Member; Tomasz Plewa, Committee Member.
Florida State University
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