Wave overtopping discharges at rubble mound structures in shallow water

Abstract

Physical model experiments are conducted in a wave basin to investigate the influence of directional spreading on wave overtopping in shallow water. Offshore wave steepness, wave height, water depth, and directional spreading are systematically varied to assess their impact on the non-dimensional mean overtopping discharge (q∗). Additional tests with oblique wave attack are performed to examine the role of the wave direction. To better understand the underlying hydrodynamics, the dependence of low-frequency wave energy on directional spreading is analyzed. Results confirm that low-frequency wave energy strongly depends on directional spreading, consistent with previous studies. An empirical formulation is introduced to predict the ratio of low-frequency wave height to total incident wave height using the relative water depth, the offshore wave steepness, and offshore directional spreading, achieving an R ²=0.91. Excluding directional spreading from the formulation decreases the R ² to 0.38, highlighting its importance. Variations in low-frequency wave energy also affect q∗, as low-frequency waves temporarily raise the water level, leading to larger overtopping volumes and thus higher q∗. Consequently, directional spreading influences q∗ primarily through its effect on low-frequency energy, particularly in shallow water. To evaluate how existing prediction tools perform under these conditions, several formulations for q∗ are assessed. Their performance ranges from poor to reasonable, with the best results using the formulation in De Ridder et al. (2024) that were based on 2DV tests in shallow water rather than 3D tests including directional spreading. The tests with oblique waves show that the existing formulation captures the trends found in shallow water. Therefore, the existing formulation for the influence of oblique wave attack is also recommended for shallow water. To incorporate directional spreading effects into overtopping prediction, the relative crest height was adjusted by including the contribution of the low-frequency wave height as done in De Ridder et al. (2024). Due to reduced correlation between the short-wave steepness and the low-frequency height in this new dataset, coefficients could be estimated more reliably. The revised equations are validated against (long-crested) wave flume and new datasets with both short- and long-crested conditions and oblique attack. The expression including the low-frequency wave height results in the highest accuracy (R ²=0.87, Equation (32)) and is recommended, while a relatively simple expression with only the relative crest and short-wave steepness also performs well (R ²=0.83, Equation (28)).