Evidence map›Paper›PMID 41115917›Full record

ArticleScientific data2025

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

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

Abstract read
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yixian ChenDepartment of Geography and the Environment, The University of Alabama, Tuscaloosa, AL, 35401, USA. ychen223@ua.edu.ORCID http://orcid.org/0000-0002-7710-580X
Sagy CohenDepartment of Geography and the Environment, The University of Alabama, Tuscaloosa, AL, 35401, USA.ORCID http://orcid.org/0000-0002-3354-2864
Anupal BaruahDepartment of Geography and the Environment, The University of Alabama, Tuscaloosa, AL, 35401, USA.
Dipsikha DeviDepartment of Geography and the Environment, The University of Alabama, Tuscaloosa, AL, 35401, USA.
Supath DhitalDepartment of Geography and the Environment, The University of Alabama, Tuscaloosa, AL, 35401, USA.
Dan TianDepartment of Geography and the Environment, The University of Alabama, Tuscaloosa, AL, 35401, USA.
Dinuke MunasingheDepartment of Geography and the Environment, The University of Alabama, Tuscaloosa, AL, 35401, USA.

Funding

United States Department of Commerce | National Oceanic and Atmospheric Administration (NOAA) NA22NWS4320003
6 · The paper itself

Abstract

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.

Identifiers

PMID41115917
PMCPMC12537858

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.