Longshore Sediment Transport (LST) is one of the main drivers of beach morphology. It works at temporal scales ranging from hours to centuries and at spatial scales ranging from tens of meters to hundreds of kilometres. Episodic, large LST rates can result in important physical impacts such as inlet closure, rapid build-up of ebb/flood shoals, headland bypassing of large volumes of sand and rotation of pocket beaches. Persistent alongshore gradients in LST, however small in magnitude, could result in chronic impacts, such as coastline recession, inlet migration and ebb/flood delta depletion/accretion. In general most, if not all, of these impacts are by coastal managers generally considered as negative impacts. Perhaps the most negative impact comes from coastline recession, which poses an immediate threat to populations living in vulnerable coastal areas. Motivated by these problems, a considerable research effort was invested on developing models to predict LST rates. Two approaches to predict LST can be roughly defined: 1) bulk transport formulas; these are explicit equations based on simplified representations of physical processes, which mostly use empirical coefficients for calibration, and 2) process based models; these include a large number of physical processes attempting to simulate LST in detail. This research was motivated by a rather generic question: "how do results of LST bulk formulas compare with results of process based models?"The starting point was the evaluation of the most commonly used bulk formulas (CERC, Kamphuis and Bayram). The predictive skill of these bulk LST formulas was rigorously valuated using an extensive LST data set. As a result, the calibration coefficients of the three formulas were updated resulting in a significant improvement of their predictive skill. Explaining the uncertainty, that was still observed in the predictions of the bulk formulas, was the next step. It was assumed that this uncertainty was not a result of measurement errors alone, and that factors that influence LST were not represented in bulk formulas. The research was focused on profile related factors, such as slope or presence of bars. Using a process based model LST rates were calculated in profiles showing different kinds of features and a significant dependence on several of those features was found. These results led to a new question: "which phenomena lead to the influence of profile features in LST rates?". To answer this question, the effect of wave breaking induced turbulence on bed shear stresses was investigated and a new LST model that includes the effect of wave breaking generated turbulence was implemented. The model includes a simple turbulence model and uses a novel parametrization for the vertical decay of the wave breaking generated turbulence. Laboratory data, that include test cases with different wave breaking types were used to calibrate the model. The model was able to reproduce the differences in turbulence decay profiles between different wave breaking types and produced realistic cross-shore profiles of LST. A parameter space exploration was performed, using constant slope (“flat”) and real profiles, and it was observed that the results are in the same order of magnitude as the results of bulk formulas, and in agreement to what was expected. The model was applied to field data measured at Vluchtenburg, on the Dutch coast. This survey comprises measurements that detail the evolution of a large scale nourishment. The results of the model follow a trend that is similar to the observed data, showing higher volume losses in the period immediately after the conclusion of the nourishment. The main results of the research are: 1) the accuracy of the three most commonly used bulk formulas (CERC, Kamphuis and Bayram) was significantly improved, 2) the accuracy is still low for several purposes but there is potential for improvement if the effect of profile features, more specifically, slope related parameters are included, 3) this effect of slope on LST was attributed to wave breaking induced turbulence that reaches the bottom and stirs sediment more efficiently than bed shear stresses caused by orbital velocity, 4) a novel parametrization for the decay of wave breaking induced turbulence, that attempts to account for this phenomenon, was implemented and tested successfully against laboratory data, and 5) an application of an LST model using this parametrization was able to produce similar trends to field data, which is evidence that this approach may be valid.