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Article

Cross-Shore Modeling Features: Calibration and Impacts of Wave Climate Uncertainties

1
RISCO & Department of Civil Engineering, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
2
Vatnaskil, Síðumúli 28, 108 Reykjavík, Iceland
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2024, 12(5), 760; https://doi.org/10.3390/jmse12050760
Submission received: 26 March 2024 / Revised: 16 April 2024 / Accepted: 28 April 2024 / Published: 30 April 2024

Abstract

Numerical models can be powerful tools for evaluating the best scenarios for the construction of artificial nourishments to mitigate coastal erosion. Until recent decades, when looking at medium- to long-term simulations, cross-shore and alongshore processes have been studied separately. Accounting for both processes in a shoreline evolution numerical model would improve the understanding and predictive capacity of future changes in coastline evolution. The AX-COAST project aims to develop new capacities in modeling cross-shore sediment transport processes by adding the CS-Model, a cross-shore numerical model, into the existing LTC (Long-Term Configuration) model. The LTC model is a shoreline evolution numerical model which is a module of the cost–benefit assessment tool COAST. This work presents the first steps of the CS-Model implementation, which involve evaluating its performance by calibrating the model with extensive measured datasets of wave climate, beach profiles, tide levels, etc., from coastal areas in IJmuiden and Sand Motor in the Netherlands. The results show good agreement between modeled and observed values. Additionally, wave climate datasets derived from global and regional wave models were considered to evaluate modeling performance at IJmuiden. Using derived timeseries from the wave models did not significantly lead to different results compared to using measured data. The obtained mean absolute and relative errors for each profile were low for both types of datasets. Calibration processes with consistent data are important in modeling simulations to accurately represent the study area and ensure the credibility of future simulations.
Keywords: artificial nourishments; cross-shore processes; coastal erosion; numerical models; beach profiles; AX-COAST artificial nourishments; cross-shore processes; coastal erosion; numerical models; beach profiles; AX-COAST

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MDPI and ACS Style

Romão, F.; Coelho, C.; Lima, M.; Ásmundsson, H.; Myer, E.M. Cross-Shore Modeling Features: Calibration and Impacts of Wave Climate Uncertainties. J. Mar. Sci. Eng. 2024, 12, 760. https://doi.org/10.3390/jmse12050760

AMA Style

Romão F, Coelho C, Lima M, Ásmundsson H, Myer EM. Cross-Shore Modeling Features: Calibration and Impacts of Wave Climate Uncertainties. Journal of Marine Science and Engineering. 2024; 12(5):760. https://doi.org/10.3390/jmse12050760

Chicago/Turabian Style

Romão, Frederico, Carlos Coelho, Márcia Lima, Hrólfur Ásmundsson, and Eric M. Myer. 2024. "Cross-Shore Modeling Features: Calibration and Impacts of Wave Climate Uncertainties" Journal of Marine Science and Engineering 12, no. 5: 760. https://doi.org/10.3390/jmse12050760

APA Style

Romão, F., Coelho, C., Lima, M., Ásmundsson, H., & Myer, E. M. (2024). Cross-Shore Modeling Features: Calibration and Impacts of Wave Climate Uncertainties. Journal of Marine Science and Engineering, 12(5), 760. https://doi.org/10.3390/jmse12050760

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