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. Despite the high historical losses attributed to flood events, Canadianflood mitigation efforts have been hindered by a dearth of current,accessible flood extent/risk models and maps. Such resources often entaillarge datasets and high computational requirements. This study presents anovel, computationally efficient flood inundation modeling framework(“InundatEd”) using the height above nearest drainage (HAND)-based solution forManning's equation, implemented in a big-data discrete global gridsystem (DGGS)-based architecture with a web-GIS (Geographic InformationSystems) platform. Specifically, this studyaimed to develop, present, and validate InundatEd through binaryclassification comparisons to recently observed flood events. The frameworkis divided into multiple swappable modules including GIS pre-processing;regional regression; inundation models; and web-GIS visualization. Extenttesting and processing speed results indicate the value of a DGGS-basedarchitecture alongside a simple conceptual inundation model and a dynamicuser interface.

InundatEd-v1.0: a height above nearest drainage (HAND)-based flood risk modeling system using a discrete global grid system