Merging Remote Sensing Derived River Slope Datasets with High-Resolution Hydrofabrics for the United States
Yixian Chen1, Sagy Cohen2, Anupal Baruah2
1Department of Geography and the Environment, The University of Alabama, Tuscaloosa, AL, 35401, USA. ychen223@ua.edu.
None:
The CONtiguous United States scale (CONUS) Flood Inundation Mapping Hydrofabric - ICESat-2 River Surface Slope (FIM HF IRIS) dataset integrates satellite-derived global IRIS river slopes for 117,357 spatially corresponding main-stream reaches within National Oceanic and Atmospheric Administration (NOAA) Office of Water Prediction operational FIM forecasting system (OWP HAND-FIM). A spatial joining approach was first developed to align FIM HF and IRIS reaches, addressing differences in reach flowline sources. Original FIM HF slopes had an average bias of 76 ± 168% relative to IRIS slopes. Applying to OWP HAND-FIM, FIM HF IRIS improved FIM accuracy by average 31 ± 25% (CSI) across eight flood events compared to the FIM HF slopes. Using a common attribute, IRIS data were transferred from FIM HF IRIS to the CONUS Next Generation Water Resources Modeling Framework Hydrofabric (NextGen HF), creating the NextGen HF IRIS dataset. Leveraging a common attribute, the resulting datasets enable using SWOT vector data within OWP HAND-FIM and NextGen. The spatial joining approach enabling integrating the hydrofabrics with other hydrologic datasets via flowlines is provided.
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