The 1755 Lisbon earthquake triggered the largest historical tsunami ever registered in Western Europe. Despite the recent efforts to better understand this event, there are still questions to be answered. Understanding the past tsunami intensity is key to assessing tsunami hazard. Sedimentary imprints are the only evidence in the geological record able to quantify onshore tsunami flow characteristics through inverse modelling. On the other hand, forward numerical modelling is a powerful tool capable of simulating tsunami hydrodynamics and the induced sediment transport. This work presents results from inverse and forward modelling in order to assess tsunami characteristics onshore. The study site is located on the Portuguese southern coast, at Salgados lowland where inverse modelling was performed using TsuSedMod (Jaffe and Gelfenbaum, 2007, Sedimentary Geology) based on four Livingstone sediment cores. Forward modelling including tsunami generation and propagation was performed respectively using the methods of Okada (1985, Bulletin of the Seismological Society of America) and Delft3D-FLOW. Onshore topography was corrected for the 1755 scenario based on extensive deposit thickness data. The tsunami source was chosen based on recent results from the same authors that pointed to a good correlation between modeled and field tsunami data considering Marques de Pombal fault. Results from inverse model show tsunami onshore average speed varying from 7.3 up to 9.3 m/s and shear velocities from 0.52 up to 0.66 m/s. Varying the bottom roughness results in the forward model result in average flow velocities between 7.0 and 8.0 m/s, induced by a 3-meter high tsunami at 50 m depth. The good agreement between forward and inverse model estimates of tsunami velocity highlights the potential of numerical modelling (coupled with geological records) to improve the understanding of historical events. Additional research on correlating modelling and geological data is needed and will likely lead to a better understanding of the effects of similar events and contribute to the ability to assess tsunami hazard and coastal vulnerability. Acknowledgements: Work supported by Instituto Dom Luiz and by project OnOff ‑ PTDC/CTA‑GEO/28941/2017 – financed by FCT