In response to record flooding along lake ontario in 2017 and 2019, this project will upgrade the great lakes operational forecast system (GLOFS) to simulate coastal flood processes along the lake…

In response to record flooding along lake ontario in 2017 and 2019, this project will upgrade the great lakes operational forecast system (GLOFS) to simulate coastal flood processes along the lake ontario shoreline. The current modeling system provides forecast guidance throughout the great lakes, supporting commercial navigation, flood preparedness and coastal resiliency, recreation, and natural resource management. However, IT is limited to the nominal shoreline of the lakes, with many ports, harbors, and bays not represented in the model domain, and with no representation of floodplain regions. Through the coastal and inland flood inundation mapping initiative, this project will expand the lake ontario model to include these critical areas, adding the capability to dynamically simulate coastal inundation and improving representation of nearshore processes. In addition, as a separate task, this project will explore and develop a framework for a 3D fully-coupled hydrologic-hydrodynamic experimental modeling approach to improve representation of processes in the transitional coastal domain. This project is part of a larger BIL-funded effort to produce real-time flood inundation forecasts and maps for the US shoreline.