Merging Remote Sensing Derived River Slope Datasets with High-Resolution Hydrofabrics for the United States

Chen, Yixian; Cohen, Sagy; Baruah, Anupal; Devi, Dipsikha; Dhital, Supath; Tian, Dan; Munasinghe, Dinuke

doi:10.1038/s41597-025-05941-6

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Merging Remote Sensing Derived River Slope Datasets with High-Resolution Hydrofabrics for the United States

2025
By Chen, Yixian ; Cohen, Sagy ; Baruah, Anupal ; ...

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Journal Title:

Scientific Data
Personal Author:

Chen, Yixian ; Cohen, Sagy ; Baruah, Anupal ; Devi, Dipsikha ; Dhital, Supath ; Tian, Dan ; Munasinghe, Dinuke
NOAA Program & Office:

NWS (National Weather Service) ; CIROH (Cooperative Institute for Research to Operations in Hydrology)
Description:

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.
Source:

Scientific Data, 12(1)
DOI:

https://doi.org/10.1038/s41597-025-05941-6
ISSN:

2052-4463
Format:

PDF
Publisher:

Springer Science and Business Media LLC
Document Type:

Journal Article
Funding:

Grant no. NA22NWS4320003
License:

https://creativecommons.org/licenses/by/4.0
Rights Information:

CC BY
Compliance:

Submitted
Main Document Checksum:

urn:sha-512:93ebf9b437576238908d92b9c23d30a4295b7fc6f787b1b3085b326eb0000288ba27f431a462ce7d02a658313ba5734235f8c4e62def017098e64651229e819a
Download URL:

https://repository.library.noaa.gov/view/noaa/72744/noaa_72744_DS1.pdf
File Type:

[PDF - 8.48 MB ]

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