Prediction of travel time and development of flood inundation maps for flood warning system including ice jam scenario : a case study of the Grand River, Ohio

Abstract

The flood warning system can be effectively used to reduce the potential property damages and loss of lives. Therefore, a reliable flood warning system is required for the evacuation of people from probable inundation area in sufficient lead time. Hence, this study was commenced to predict the travel time and generate inundation maps along the Grand River, Ohio for various flood stages. A widely accepted hydraulic tool, Hydraulic Engineering Center River Analysis System (HEC-RAS), was used to perform the hydraulic simulation. HEC-GeoRAS, an ArcGIS extension tool, was used to prepare geospatial data and generate flood inundation maps for various flood stages. A topographic survey was conducted to obtain the accurate elevation of river channels. The hydraulic simulations were carried out using six different elevation datasets and various ranges of Manning's roughness to quantify the uncertainties in travel time and inundation area prediction due to the resolutions of the elevation datasets and Manning's roughness. The study showed that the coarse elevation dataset, which was 30m Digital Elevation Model (DEM) without integration of survey data, provided higher travel time and inundation area. It over predicted (11.03%-15.01%) in travel time and inundation area (32.56%-44.52%) for various return period floods when compared with the results of Light Detection and Ranging (LiDAR) integrated with survey data. Moreover, Manning's roughness was found to be more sensitive in channel sections than that of floodplains. The decrease in travel time and inundation area was observed with the decrease in Manning's roughness. The highest decrement of 21.38% and 8.97% in travel time and inundation area was observed when roughness value was decreased in channel sections, while the decrement in travel time and inundation area was 3.45% and 1.49% when roughness value was decreased in floodplains. The difference in predicted travel time and inundation area, while using LiDAR integrated with survey data, was not considerably different