Rapid climate change and the corresponding estimated sea level rise can affect the performance of the coastal defense structures such as breakwaters, seawalls, and dikes. In order to improve these coastal defenses, a detailed understanding of the processes which contribute to wave run-up and overtopping over the coastal defenses needs to be established. Following the exponential growth of computing capacity around 1970’s, a wide variety of computational models were developed to study fluid flow. Traditionally, three computational paradigms have existed in order to study wave transformation and surf zone hydrodynamics: phase averaged models, phase resolving models, and Computational Fluid Dynamics (CFD) models. Limitations posed by the underlying linear wave theory in phase averaged and other simplifications in the phase resolving models, may not provide sufficient detail in wave breaking, wave energy dissipation, wave run-up, wave overtopping, and potentially other detailed hydrodynamic processes. This lack of resolution in depth averaged models for wave-breaking, wave run-up, and wave overtopping processes motivates a detailed investigation using CFD based models, which can correctly mimic wave-breaking and other hydrodynamic processes.

The recent growth in available computational capacity has greatly improved the applicability of CFD based models for large scale transient flows such as waves near a coast. Additionally, the developments in wave generation and wave absorption boundary conditions by Jacobsen et al. [2012] in the open-source CFD toolbox OpenFOAM, have facilitated the use of OpenFOAM in coastal engineering applications. This encourages investigating the coastal environment using relatively complex models, thus providing insights into fundamental processes which contribute to coastal safety. To that end, this thesis focuses on investigating wave overtopping and the underlying processes which contribute to the aforementioned hydrodynamic aspects.

Overtopping demands accurate capture of the free surface (interface between water and air). The waveFoam solver suffers from numerical diffusion of the interface, consequently requiring a different approach to mimic the sharp interface. In order to cater to this deficiency, a new solver which combines the capabilities of waveFoam [Jacobsen et al., 2012] and isoAdvection [Røenby et al., 2016] which has the ability to capture sharp interfaces by means of a sub-grid approach has been integrated (waveFlow) and used in this study. In addition to the new solver, a new set of Reynolds Averaged Navier-Stokes (RANS) closures developed by Larsen and Fuhrman [2018] for wave modeling applications have been employed to correctly capture turbulence levels under breaking waves. The preliminary steps include calibrating and assessment of the newly integrated waveFlow solver. Using a relatively simple conceptual test case, a comparison of the free surface behavior and overtopping discharge was carried out. This calibration test was followed by a comparison of numerical results with the experimental investigations carried out by Ting and Kirby [1994]. Following this benchmarking study, experimental studies carried out by Flanders Hydraulics investigating wave overtopping over dikes in shallow foreshore environments was validated. A comparison of waveFlow and waveFoam was made to assess the qualitative and quantitative differences between the two interface capture methods on overtopping. Using this new solver, OpenFOAM was able to reproduce the surface elevation and significant improvement in the overtopping results were obtained for identical model setup in comparison to the waveFoam solver. A coupled approach using a potential flow solver named OceanWave3D aided simulation of large domain wave propagation and helped to cut down the computational time.

The increasing frequency and intensity of extreme events due to global warming and climate change is increasing flood risk. To act, rather than react, nature-based solutions (NBS) involving vegetation and wetlands are being explored on top of conventional solutions like dikes. WHY? There was a dire need for global study quantifying the potential of vegetation in reducing flood risk and eventually make a decision support tool which enables quick assessments about flood risk reduction in a vegetated hydrodynamic system. WHAT? The developed tool can predict flood risk anywhere in the world without rigorous modeling through user defined conditionalization of in-situ hydrodynamic or vegetation characteristics. HOW? Multivariate dependence among parameters of schematized system can exhibit characteristics of vegetated hydrodynamics. To ensure global representation of vegetated hydrodynamics a copula-based multivariate stochastic model has been developed which caters global ranges of each parameter, their probability distributions and the inter-parameter dependencies through ranked correlations. Numerical modeling has been carried out through XBeach non-hydrostatic model by resolving full spectrum of high and low frequency waves. A non-parametric Bayesian network-based flood risk prediction tool has been developed from the synthetic dataset developed from the simulations. SO? Bulk results conclude that saltmarshes attenuates waves by 87% and mangroves by 94% as a mean value. Wave attenuation, flood risk reduction and wave run-up manifests maximum dependence on offshore wave height, water depth, drag coefficient, vegetation height, frontal width, and forest length and least on offshore slope and vegetation density. NOW? The flood risk prediction tool would help decision makers in implementing NBS, in making better informed decisions about early warnings and policy making related to flood risk reduction and climate change adaptation by incorporating vegetation. NOVELTY? To the author's knowledge no such study exists which captures natural variability of hydrodynamics and vegetation together in a probabilistic model over global scales. Additionally, no such study exist which applies non-parametric Bayesian networks to predict flood risk. The dependence modeling of global vegetated hydrodynamic environments is also unique which skims out the most critical parameters.