Tsunamis and storms are the most devastating coastal hazards that can cause great loss of life and infrastructure damage. To assess tsunami and storm hazard, the magnitude and frequency of each type of event are needed. However, major tsunamis and storms are very infrequent, especially tsunamis, and the only reliable record is the deposits they leave behind. Tsunami and storm deposits can be used to calculate the magnitudes of the respective event, and to contribute to the hazard frequency where there is no historical records. Therefore, for locations where both events could occur, it is crucial to differentiate between the two types of events. Existing studies on the similarities and differences between the two types of deposits all suffer from paucity of the number of events and field data, and a wide range of initial conditions, and thus an unequivocal set of distinguishing deposit characteristics has not been identified yet. In this study, we aim to tackle the problem with the MEso-SCAle Particle Transport model (MESCAPT) that combines the advantages of concentration-based Eulerian methods and particle-based method. The advantage of the former is efficiency and the latter is detailed sediment transport and deposit information. Instead of modeling individual particles, we assume that a group of sediment grains travel and deposit together, which is called a meso-scale particle. This allows simulation domains that are large enough for tsunami and storm wave propagation and inundation. The sediment transport model is coupled with a hydrodynamic model based on the shallow water equations. Simulation results of a case study show good agreements with field measurements of deposits left behind by the 2004 Indian Ocean Tsunami. Idealized tsunami and storm case studies demonstrate the model's capabilities of reproducing morphological changes, as well as microscopic grain-size trends. / Ph. D.