Predicting the amplitude and runup of the water waves induced by rotational cliff collapse, considering fragmentation

Abstract. Cliff collapse-induced water waves in small lakes and reservoirs retain their energy due to short travel distance, and may cause significant damage to offshore infrastructure. Previously, scientists have analyzed the waves induced by granular/block sliding down the slope and hitting a water body, but none have studied the water waves induced by rotational cliff collapse, fragmenting upon impact with the water surface. So, in this study, we have experimentally and numerically analyzed the rotational cliff collapse and energy transfer mechanism, determined the amplitude and runup of the induced waves, and developed machine learning-based prediction models. Moreover, the effect of the fragmentation of the cliff upon impact on the induced wave has also been investigated. The results indicate that as the water depth decreases, the impact Froude number and relative wave amplitude increase, wave velocity decreases, and the splash becomes more elongated. A comparison between the wave induced by fragmented cliff collapse and an equivalent amount of granular mass sliding from a 30° slope indicates that the amplitude of the waves induced by granular mass is 42 %, 35 %, and 28 % less than that of fragmented cliff collapse. The wave amplitude induced by fragmented cliff collapse indicates that the rotational motion of the cliff imparts a more sudden and concentrated impact that allows an efficient energy transfer to water, resulting in higher wave amplitudes. The results for the prediction model indicate that the amplitude and runup model performed well both in the training and testing stages, with higher R2 values. The developed model was validated by comparing the results with established statistical indices and by performing sensitivity and parametric analysis, highlighting that wave amplitude is greatly influenced by impact velocity, cliff height, and the number of fragments, contributing approximately 90 % to the wave amplitude. In comparison, runup is greatly influenced by bank slope angle, impact velocity, cliff mass, and height. The experimental results and developed prediction models can provide the basis for understanding the rotational cliff collapse-induced waves and can help with disaster mitigation and risk assessment by effectively predicting the wave amplitude and runup.