Across the world, the presence of humans in coastal regions is always increasing. Hydraulic forcing from extreme events is a large risk around the global coastlines, the risk being complicated by the increased human presence along the coasts. The knowledge that vegetation can be used as a coastal protection measure is not something new. The benefits of vegetation have been seen throughout history and are being researched on till date. If we know to a certain confidence what the wave heights are at the shoreline, coastal defence structures, used as a hybrid protection measure, can be designed accordingly. Not much research has been done on the wave behaviour on shallow foreshores. Localised studies have been previously done on tropical vegetated coasts, but there is a lack of efficient and accurate analysis on a large scale. As we bring more clarity on how waves transform and attenuate in a typically vegetated coast, some questions get answered, and some more questions arise, which also happened during the research done for this thesis. Observed data, be it laboratory or field, is very crucial in validating numerical models. A laboratory experiment was done in the TU Delft Laboratory of Fluid Mechanics flume, for a complete vegetation-free profile, where the surface elevations were observed for different wavemaker input conditions. A lot of numerical models have been developed that predict wave transformation and dissipation through vegetated foreshores. However, these models lack validation from observed data. This thesis first focuses on understanding the wave transformation for two unique (and mainly theoretical) wave conditions: a regular sinusoidal wave and a bichromatic wave. It was checked if the transformation is reflected in the models – SWAN and SWASH, which they did. The research proceeded on to validating the models by comparing the wave heights observed in the laboratory experiment versus when the models were inputted with the same conditions, including inputting the observed data into the models. When the laboratory conditions were replicated, the SWASH results obtained correlated quite well with what was observed in the laboratory. The same was not true in the case of SWAN. When a spectral analysis was done for the observed data, a presence of very low frequencies (VLF) as well as some minor higher frequencies was noticed. To check its effect, if any, on the model results, they were filtered out. Both the original and filtered data was inputted into the models. The difference in the foreshore region was more distinct in the filtered case, i.e., making a bichromatic elevation input purer resulted in more pronounced undulations in the wave heights than what was predicted in the unfiltered data. This result does not fit well with the existing knowledge on wave dissipation processes. It is widely known that the presence of VLFs and higher frequencies are the driving mechanisms that result in the undulations in the foreshore region, but the predicted results were exactly opposite to this knowledge. What can be thought of from the anomaly is that the presence of various frequencies (that is, waves with different periods) counteract each other’s effects and make the undulating wave heights milder, but when the signal is made purely bichromatic, it leads to more distinct undulations. This proposition is also backed by the similar SWASH results for the laboratory condition-replicating theoretical inputs. This anomaly needs further investigation. Another interesting observation was that the changes happening in the offshore region did not affect the results in the foreshore region, for varying parameters in SWAN. SWASH can be concluded as a better model for predicting wave heights, especially in the foreshore region. SWAN could not predict the fluctuations in the wave heights. Obtaining the wave heights at the shoreline with SWAN, and designing a dike with those results, for example, will lead to disastrous consequences, as SWAN underestimates the wave heights. The study is limited by the consideration of hydrodynamics only, and by the many simplifications made to simulate the conditions. One of the recommendations formulated is to obtain field data and to make a similar comparison with the models to corroborate (or correct) the observations made. This study tried to see the correlation between the models and observed data in the laboratory, for simple (and somewhat purely theoretical) cases. It is, nonetheless, a starting point for more complicated cases, the basis for which can be laid on this study.