Abstract. Flooding is an endemic global challenge with annual damages totalling billions of dollars. Impacts are felt most acutely in low- and middle-income countries, where rapid demographic change is driving increased exposure. These areas also tend to lack high-precision hazard mapping data with which to better understand or manage risk. To address this information gap a number of global flood models have been developed in recent years. However, there is substantial uncertainty over the performance of these data products. Arguably the most important component of a global flood model is the digital elevation model (DEM), which must represent the terrain without surface artifacts such as forests and buildings. Here we develop and evaluate a next generation of global hydrodynamic flood model based on the recently released FABDEM DEM. We evaluate the model and compare it to a previous version using the MERIT DEM at three study sites in the Central Highlands of Vietnam using two independent validation data sets based on a household survey and remotely sensed observations of recent flooding. The global flood model based on FABDEM consistently outperformed a model based on MERIT, and the agreement between the model and remote sensing was greater than the agreement between the two validation data sets.