Hydrological Sciences Journal · 2018 · 44 citations · 38 references
Natural ResourcesCivil EngineeringHydrologyDigital Elevation ModelingFlood HydrologyHydrologic ModelingFlood Inundation ModelingFlood WarningFloodplain HydraulicsFloodplain HydrologyFloodplain MappingHydraulic ModelingDigital Elevation Model Error AnalysisFlood Warning SystemsFloodplain Inundation MappingFloodplain Roughness EstimationHydraulic System ModelingInput Data AnalysisInundation MappingTime Computation
The study aimed to quantify how input data resolution and Manning’s roughness affect travel time and floodplain mapping errors. The authors used the HEC‑RAS model on the Grand River in Ohio to conduct the analysis. LiDAR combined with survey data produced conservative flood predictions, while coarser elevation data increased travel time by 11–15 % and inundation area by 33–45 %; the smallest errors occurred when a 10‑m DEM was used in the channel with LiDAR in the floodplain, and Manning’s roughness was found to be more sensitive than floodplain roughness, with a lower roughness reducing inundation area by 9 %.
The main objective of this study was to quantify the error associated with input data, including various resolutions of elevation datasets and Manning's roughness for travel time computation and floodplain mapping. This was accomplished on the test bed, the Grand River (Ohio, USA) using the HEC-RAS model. LiDAR data integrated with survey data provided conservative predictions, whereas coarser elevation datasets provided a positive difference in the travel time (11.03–15.01%) and inundation area (32.56–44.52%). The minimum differences in travel time and inundation area were 0.50–4.33% and 3.55–7.16%, respectively, when the result from LiDAR integrated with survey data was compared with a 10-m DEM integrated with survey data. The results suggest that a 10-m DEM in the channel and LiDAR data in the floodplain combined with survey data would be appropriate for a flood warning system. Additionally, Manning's roughness of the channel section was found to be more sensitive than that of the floodplain. The decrease in inundation area was highest (8.97%) for the lower value of Manning's roughness.
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