A digital elevation model (DEM) is commonly used as a substitute for surveyed topographic data. Selection of suitable DEM and optimum spatial resolution is, thus, a key for achieving expected accuracy within sufficient simulation time. This study compared DEMs from different sources (i.e. Shuttle Radar Topography Mission, Advanced Spaceborne Thermal Emission and Reflection Radiometer, National Elevation Dataset, and Light Detection and Ranging) with various spatial resolutions for a 35 km long stretch of the American River downstream of Folsom Dam in California. The study period was the 1997 ‘New Year's Flood’ used to estimate downstream flood consequences, especially in urban areas near Sacramento. The objective of this study was to quantify the comparative deviation of model accuracy for each specific set of topographic data. This study also looked into developing correlations between consequences and flood magnitude. The hydrodynamic model furnished input for flood damage assessment. The Hydrologic Engineering Center's Flood Impact Analysis (HEC‐FIA) was employed to estimate flood losses for each scenario. This analysis will assist decision‐makers in selecting the appropriate DEM for flood consequence assessment to get reasonable results within a convenient amount of time. It is also expected that this study will be useful for estimating consequences in absence of high‐quality terrain data, which will be especially helpful in remote study areas.
This study assessed the uncertainty in flood impact assessment (FIA) that may be introduced by errors in moderate resolution regional and moderate resolution global Digital Elevation Models (DEM). One arc-second National Elevation Dataset (NED) and one arc-second Shuttle Radar Topography Mission (SRTM) DEMs were selected to represent moderate resolution regional and global DEMs. The relative performance for scenarios based on each of the DEMs was compared to a "control" terrain (combination of surveyed river bathymetry and a 1/3 arc-second LiDAR for floodplains)-based scenario. Furthermore, a conveyance-based DEM correction technique was applied to the DEMs for investigating the suitability of the technique on selected DEMs, and determining subsequent improvement in the FIA. The May 2010 flood on the Cumberland River near Nashville, TN, was selected as the case study. It was found that the hydraulic properties necessary to implement the selected DEM correction technique could be more readily estimated from NED compared to SRTM. However, this study also prescribed alternate methods to extract necessary hydraulic properties if the DEM quality was compromised. NED-based hydrodynamic modeling resulted in a high overestimation of the simulated flood stage, but the SRTM-based model was unable to produce any reasonable result prior to DEM correction. Nevertheless, after DEM correction, both models became stable and produced less error. Error in simulated flood consequence (i.e., total structures affected and total loss in dollars) also dropped accordingly, following the DEM correction. Therefore, application of this conveyance-based correction technique is reasonably effective on both moderate-resolution regional and global DEMs. The effectiveness of the technique on moderate resolution global DEM underscores the potential for users of remote and data-poor areas.
Digital Elevation Models (DEMs) are widely used as a proxy for bathymetric data and several studies have attempted to improve DEM accuracy for hydrodynamic (HD) modeling. Most of these studies attempted to quantitatively improve estimates of channel conveyance (assuming a non-braided morphology) rather than accounting for the actual channel planform. Accurate representation of river conveyance and planform in a DEM is critical to HD modeling and can be achieved with a combination of remote sensing (e.g., satellite image) and field data, such as water surface elevation (WSE). Therefore, the objectives of this study are (i) to develop an algorithm for predicting channel conveyance and characterizing planform via satellite images and in situ WSE and (ii) to estimate discharge using the predicted conveyance via an HD model. The algorithm is named River Bathymetry via Satellite Image Compilation (RiBaSIC) and uses Landsat satellite imagery, Shuttle Radar Topography Mission (SRTM) DEM, Multi-Error-Removed Improved-Terrain (MERIT) DEM, and observed WSE. The algorithm is tested on four study areas along the Willamette River, Kushiyara River, Jamuna River, and Solimoes River. Channel slope and predicted hydraulic radius are subsequently estimated for approximating Manning’s roughness factor. Two-dimensional HD models using DEMs modified by the RiBaSIC algorithm and corresponding Manning’s roughness factors are employed for discharge estimation. The proposed algorithm can represent river planform and conveyance in single-channeled, meandering, wandering, and braided river reaches. Additionally, the HD models estimated discharge within 14–19% relative root mean squared error (RRMSE) in simulation of five years period.
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