Investigating Nearshore Morphodynamics Response to Extreme Storms and Storm Groups

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Zhang, Hong

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Vieira da Silva, Guilherme

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Combating coastal erosion is becoming increasingly challenging due to population growth near beaches, and the dynamic nature of nearshore morphological processes. Along a zeta-shaped coastline, such as Gold Coast in Australia, the degree of exposure of the beaches to waves varies alongshore depending on the incident wave direction. Since waves are one of the main drivers of sediment transport along the coast, changing wave direction can disturb the modal sediment transport. This phenomenon can cause localised erosion, and it is therefore important to quantify the impact at different locations along the coast. By doing so, effective coastal protection strategies can be developed to ensure the resilience of coastal communities. Recent studies have reported changes in wave climate (e.g., frequency and intensity of storms, shifts in wave direction) in response to climate change, making coasts more vulnerable to unusual waves. In addition to the waves, water levels play an important role in beach erosion, and the non-astronomical component of water levels (i.e., surge) presents a correlation with wave height during extreme storm events. Moreover, storm groups, where beach recovery is near zero between successive storms, may further increase erosion along the coast. Therefore, an investigation of the impact of waves, surge, and storm groups is important for effective coastal management. In this context, this study aimed to understand the beach response to extreme storms and storm groups on a zeta-shaped open coastline. This was achieved through analysis of (i) storm wave fields using different boundary forcing to study the wave transformations from offshore to nearshore, (ii) extreme joint probability of significant wave height and water level, and (iii) the response of different antecedent beach profiles induced by a storm group and its order. A numerical modelling approach was used, incorporating a spectral wave model and a morphological model for wave and beach erosion predictions, respectively. In addition, a technique using an artificial neural network (ANN) to perform spatial wave assimilation was used to improve wave hindcasting. [...]

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Thesis (PhD Doctorate)

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Doctor of Philosophy (PhD)


School of Eng & Built Env

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The author owns the copyright in this thesis, unless stated otherwise.

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wave assimilation

joint probability

storm group

beach erosion

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