A Novel Approach to Scalable Data-Driven Pluvial Modeling with a 1D and 2D Hydrodynamic Flood Model Tool

In the summer of 2023, Cleveland, Ohio, faced extreme convective storms that caused localized flooding due to intense rainfall overwhelming catch basins. However, a catchment flood model simulation showed no flooding, highlighting the model’s failure to capture surface water. To address catchment model limitations, Northeast Ohio Regional Sewer District (NEORSD) partnered with MIT to develop a regional, 2D, ICM model. This research develops a scalable, data-driven, pluvial flood model using a 2D, rain-on-mesh, ICM hydrodynamic model with detailed urban textures. The ICM model findings accurately replicated observed flood locations. High-resolution model validation is key, supported by advances in sensors, monitoring, and crowd-sourced data (though often underused). NEORSD and the City of Cambridge (Massachusetts) offer rich data sets. This presentation will showcase a novel validation framework integrating remote sensing and real-time data, applied to a city-scale, high-resolution flood model in Cleveland and Cambridge in collaboration with local agencies.