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Digital Elevation Models (DEMs) act as an essential input to hydraulic models for the simulation of flood hazard maps. Coarser resolution DEMs are subject to higher levels of uncertainty, particularly in capturing river‐bed bathymetry. The principal aim of the present study was to assess the potential use of freely available DEMs and the 1D and 2D HEC‐RAS modeling approaches for flood mapping in four different types of river morphology. The DEM created from direct river survey (Surveyed DEM) was used as a benchmark to assess three remote sensing‐based DEMs (i.e., ALOS, SRTM, and ASTER). The results indicated that ALOS is more accurate. However, the regeneration of main‐channel bathymetry was poor for floodplain‐meandering and braided river reaches. The DEMs were then corrected by optimizing the number and layout of representative sections. A total of 144 tests were carried out. The results indicated that the flood‐mapping index F of ALOS increased from 86% to 91%. The flood mapping with a 1D model was sufficient in straight reaches (F‐index 84%). In floodplain‐meandering rivers, a 2D model had to be used to reach an F‐index up to 81%. The responses of both 1D and 2D models were almost identical in the case of wide‐braided rivers. [ABSTRACT FROM AUTHOR]

Abstract Digital Elevation Models (DEMs) act as an essential input to hydraulic models for the simulation of flood hazard maps. Coarser resolution DEMs are subject to higher levels of uncertainty, particularly in capturing river‐bed bathymetry. The principal aim of the present study was to assess the potential use of freely available DEMs and the 1D and 2D HEC‐RAS modeling approaches for flood mapping in four different types of river morphology. The DEM created from direct river survey (Surveyed DEM) was used as a benchmark to assess three remote sensing‐based DEMs (i.e., ALOS, SRTM, and ASTER). The results indicated that ALOS is more accurate. However, the regeneration of main‐channel bathymetry was poor for floodplain‐meandering and braided river reaches. The DEMs were then corrected by optimizing the number and layout of representative sections. A total of 144 tests were carried out. The results indicated that the flood‐mapping index F of ALOS increased from 86% to 91%. The flood mapping with a 1D model was sufficient in straight reaches (F‐index 84%). In floodplain‐meandering rivers, a 2D model had to be used to reach an F‐index up to 81%. The responses of both 1D and 2D models were almost identical in the case of wide‐braided rivers.

• River bathymetry affects various flood inundation outputs differently. • Cross-sectional area, and not the channel shape, is critical to hydraulic modeling. • Both channel area and thalweg are important for velocity and shear estimates. • Simplified geometries can be used for reaches with small sinuosity, width or depth. River bathymetry, which is vital for accurate hydraulic modeling, is not readily available at large scales because of the logistical difficulties in field surveys and uncertainties associated with remote sensing techniques. Several studies have explored the potential of conceptual models and interpolation algorithms to estimate bathymetry. These models have certain underlying assumptions that limit their accuracy and widespread implementation. This study aims to provide insights into the choice of bathymetric model for different hydraulic applications by analyzing the effect of different bathymetric models on hydraulic modeling under different geomorphologic and flow settings. This study does not aim to reinforce the importance of bathymetry, rather its objective is to identify the bathymetric properties that are critical to accurate estimation of different hydraulic outputs. The study accomplishes its objectives by implementing three different bathymetric models with varying cost and efficiency at four sites with diverse bathymetric characteristics. Five hydraulic outputs, namely wetted cross-sectional area, water surface elevation, inundation extents, velocity and shear are estimated at three characteristic low and high flows and the results from the four sites are grouped together to perform an unbiased and robust evaluation. The performance of these models is evaluated using the best available bathymetric representation generated from detailed field surveys as a benchmark. The results indicate that 1D flood modeling is somewhat insensitive to channel shape as long as the estimated shape reflects the channel storage accurately. Velocity and shear related applications should incorporate bathymetry that represent both the cross-sectional area and channel thalweg accurately. Reaches with low sinuosity (<1.5), or small width and depth can be modeled reasonably using simple geometric shapes, whereas for larger streams, interpolation of surveyed data along the thalweg or complex bathymetric models that account for river anisotropy, are recommended. [ABSTRACT FROM AUTHOR]

River bathymetry has a crucial role in numerical modelling of flow hydrodynamics. The aim of the present study is to (1) investigate the capability of three different methods to trace the river bed, with the geodetic data derived from in situ survey of the river bed topography to be used as reference data, and moreover (2) assess the impact of the different river geometries on the performance of a one‐dimensional (1D) model of flood hydraulics. The Hydrologic Engineering Center's River Analysis System (HEC‐RAS) hydraulic model, in particular, calibrated and validated on hydrometric data uses a number of cross‐sections derived from aerial laser scanning (ALS), artificial sinking of riverbed, and acoustic Doppler current profiler (ADCP) methods. Water level, discharges, and flood extent derived from the model for 3 N‐year floods (Q1, Q50, Q100) were evaluated while the extent of the inundation areas were exported into geographic information systems for visualisation and interpretation of the findings. Case study area is a 2.2 km river section of the Otava River (Czech Republic), with a history of flood events. The results showed that ALS data need further processing when dealing with the riverbed zone, while ADCP presented high correlation to the reference model. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Summary: Technological aspects of producing, delivering and updating of flood hazard maps in the US have has gone through a revolutionary change through Federal Emergency Management Agency’s Map Modernization program. In addition, the use of topographic information derived from Light Detection and Ranging (LIDAR) is enabling creation of relatively more accurate flood inundation maps. However, LIDAR is not available for the entire United States. Even for areas, where LIDAR data are available, the effect of other factors such as cross-section configuration in one-dimensional (1D) models, mesh resolution in two-dimensional models (2D), representation of river bathymetry, and modeling approach is not well studied or documented. The objective of this paper is to address some of these issues by comparing newly developed flood inundation maps from LIDAR data to maps that are developed using different topography, geometric description and modeling approach. The methodology involves use of six topographic datasets with different horizontal resolutions, vertical accuracies and bathymetry details. Each topographic dataset is used to create a flood inundation map for twelve different cross-section configurations using 1D HEC-RAS model, and two mesh resolutions using 2D FESWMS model. Comparison of resulting maps for two study areas (Strouds Creek in North Carolina and Brazos River in Texas) show that the flood inundation area reduces with improved horizontal resolution and vertical accuracy in the topographic data. This reduction is further enhanced by incorporating river bathymetry in topography data. Overall, the inundation extent predicted by FESWMS is smaller compared to prediction from HEC-RAS for the study areas, and that the variations in the flood inundation maps arising from different factors are smaller in FESWMS compared to HEC-RAS. [Copyright &y& Elsevier]