Comparison of deep-water-parameter-based wave overtopping with wirewall field measurements and social media reports at Crosby (UK)

Wave overtopping formulae, which often underlie coastal hazard early warning systems, are typically parameterised using wave conditions at the toe of the structure. For very shallow conditions where significant wave breaking occurs over the foreshore, this usually requires computationally-demanding numerical models—and practitioners skilled in their application—to accurately transform offshore waves to the structure toe. An additional concern is that overtopping formulae are scarcely validated in the field due to the very limited availability of in-situ overtopping data obtained at actual structures. Here, we validate a set of deep-water-parameter-based formulae for mean overtopping discharge (q) at smooth slopes, which remove the need for nearshore measurements or additional numerical modelling but require that a single representative foreshore slope angle (m) be defined. The validation is carried out against field data gathered at Crosby (UK) using two novel approaches: i) a new overtopping measurement system called “WireWall”; and ii) crowd-sourced data in the form of overtopping images obtained from a community Facebook page (social media). A method is introduced to define m for irregular bathymetries, based on the location where the local water depth is equal to the offshore significant wave height. The overtopping formulae proved accurate—with estimates of q being within a factor of 4 of observations—when compared to both 1-h averaged and 15-min averaged overtopping data, suggesting that the approach can be used for both design and assessment and now-casting hazard information. Finally, hindcasts made using the newly validated formulae for the events reported by the community indicate that q can exceed 10 l/s/m under yearly winter conditions, posing a serious hazard to pedestrians. This highlights the pressing need to update the current hazard warning system at Crosby, which estimates q to be a factor of 3 lower than the deep-water-parameter-based approach, on average