A cloud-based flood warning system for forecasting impacts to transportation infrastructure systems

摘要: Abstract The ability to quickly and accurately forecast flooding is increasingly important as extreme weather events become more common. This work focuses on designing a cloud-based real-time modeling system for supporting decision makers in assessing flood risk. system, built using Amazon Web Services (AWS), automates access pre-processing of data, execution computationally expensive high-resolution 2D hydrodynamic model, Two-dimensional Unsteady Flow (TUFLOW), map-based visualization model outputs. A graphical processing unit (GPU) version TUFLOW was used, resulting an 80x time speed-up compared the central (CPU) version. designed run automatically produce near results consume minimal computational resources until triggered by event. demonstrated case study coastal plain Virginia vulnerability transportation infrastructure during events.