Flood is already one of the most common disaster at a global scale.With the combined effects of the continuing urbanization and ongoing climate change, the number of both inundation events and affectees is set to increase.Numerical flood simulation is a key tool to be better prepared to tackle those changes, as it allows us to evaluate the impacts of multiple weather and development scenarios at a reduced cost.In the past decades, flood models have become more reliable and accessible, leading them to be now part of the common toolbox of consulting engineers, public authorities and academics.However, correctly model the hydrological processes occurring in a urban environment is a challenging task.A successful urban flood model should be able to resolve the overland flows, the drainage network flows, and the complex interactions that are taking place between those two systems.Furthermore, the combination of the large scale of modern cities and the fine resolution needed to adequately model the overland flows requires large computational resources, and limits the models usefulness for advanced applications, like ensemble analysis.The present describes a new, open-source, coupled flood model that takes advantage of recent advances in urban inundation modelling. The surface model of the developed tool employs a simplified numerical scheme that allows fast simulation at high resolution.The drainage network model is the well known SWMM, developed by the EPA.The simulation of the coupling between the drainage and the surface models is based on the knowledge recently acquired by physical modelling.The developed surface model is first evaluated against a combination of analytic solutions and a well-known similar model.It is then employed to the reproduction of an historical flood in the city of Hull, UK.The coupled surface-drainage model is first compared to similar commercial and academic models.Then, the coupled model is applied to an historical flood in the city of Kolkata, India.In all those tests, the developed software gives adequate results and paves the way to its use for flood risk mapping and drainage network design.