Resumen
Flooding is one of the most frequent natural disasters across the world, which damages properties and may take the lives of people. Flood warning systems can play a significant role in minimizing those effects by helping to evacuate people from the probable affected areas during peak flash flood times. Therefore, a conceptual approach of an automated flood warning system is presented in this research to protect several houses, roads, and infrastructures along the Grand River, which are vulnerable to flooding during a 500 year return period flash flood. The Grand River is a tributary of Lake Erie, which lies in the Grand River watershed in the northeastern region of the United States and has a humid continental climate and receives lake-effect precipitation. The flood warning system for the Grand River was developed specifically during high flow conditions by calculating flood travel time and generating the inundation mapping for 12 different selected flood stages, which were approximately 2 to 500 years in recurrence interval, ranging from 10 ft. to 21 ft. at gage station 04212100, near the City of Painesville, OH. A Hydraulic Engineering Center-River Analysis System (HEC-RAS) was utilized for hydraulic modeling. Geospatial data required for HEC-RAS was obtained using a Digital Elevation Model (DEM) derived from Light Detection and Ranging (LiDAR) datasets, which were pre-processed and post-processed in HEC-GeoRAS to produce flood inundation maps. The flood travel time and flood inundation maps were generated by integrating LiDAR data with field verified survey results in order to provide the evacuation lead time needed for the people of probable affected areas, which is different from earlier studies. The generated inundation maps estimate the aerial extent of flooding along the Grand River corresponding to the various flood stages at the gage station near the City of Painesville and Harpersfield. The inundation maps were overlaid on digital orthographic maps to visualize its aerial extents, which can be uploaded online to provide a real-time inundation warning to the public when the flood occurs in the river.