A flood risk estimation model for two study watersheds in Canada and an interactive visualization platform using publicly available hydrometric data are presented. The risk model uses a height above nearest drainage (HAND)-based solution for Manning’s formula and is implemented on a big-data discrete global grid system framework. Overall, the novel data model decreases processing time and provides easy parallelization, resulting in performance gains in online flood analytics.