Articles | Volume 23, issue 6
Research article
16 Jun 2023
Research article |  | 16 Jun 2023

A predictive equation for wave setup using genetic programming

Charline Dalinghaus, Giovanni Coco, and Pablo Higuera

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Cited articles

Battjes, J. A.: Computation of set-up, longshore currents, run-up and overtopping due to wind-generated waves, Ph.D. thesis, Delft University of Technology, (last access: 5 April 2022), 1974. a, b, c
Beuzen, T. and Splinter, K.: Machine learning and coastal processes, in: Sandy Beach Morphodynamics, edited by: Jackson, D. W. T. and Short, A. D., 689–710, Elsevier,, 2020. a, b
Bowen, A., Inman, D., and Simmons, V.: Wave “set-down”and set-up, J. Geophys. Res., 73, 2569–2577,, 1968. a, b, c, d, e
Camus, P., Mendez, F. J., and Medina, R.: A hybrid efficient method to downscale wave climate to coastal areas, Coast. Eng., 58, 851–862,, 2011. a, b
Coast and Ocean Collective: Data, Coast and Ocean Collective [data set], (last access: 8 November 2022), 2019. a
Short summary
Wave setup is a critical component of coastal flooding. Consequently, understanding and being able to predict wave setup is vital to protect coastal resources and the population living near the shore. Here, we applied machine learning to improve the accuracy of present predictors of wave setup. The results show that the new predictors outperform existing formulas demonstrating the capability of machine learning models to provide a physically sound description of wave setup.
Final-revised paper