Due to climate change and urbanization, urban flood modelling has become an increasingly important tool in assessing flooding and associated damage costs. However, large computational demands of state-of-the art hydrodynamic flood models makes multiple and real-time simulations unfeasible. This study presents a fast-dynamic GIS-based flood model, FloodStroem. FloodStroem generates a surface network of depressions (bluespots) and flow paths, and routes surcharged water from a subsurface drainage model through the network resulting in flood depth maps and associated damage costs. FloodStroem is tested on three sub-catchments in Elster Creek Catchment, Melbourne, Australia and benchmarked against the 2D distributed hydrodynamic model MIKE 21 and two other simplified models, RUFIDAM and CA-ffé. FloodStroem is robust to the number of bluespots included. For the three sub-catchments, FloodStroem can reproduce flooding time, pattern, depth, and damage costs sufficiently, but has a tendency to underestimate flooding upstream and overestimate flooding downstream. Performance is best for the large, steep sub-catchments and largest rainstorms, where FloodStroem performs better than the two other simplified models. The Critical Success Index (CSI) ranges from 23% for a 5-year storm event in a flat catchment to 65% for a 100-year return period for a steeper catchment. With respect to simulation time, FloodStroem is five orders of magnitude faster than the 2D hydrodynamic model, and 33 times faster when including the entire model setup time, which has potential for further reduction by optimization of the workflow.