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Reproducible Workflows and Supporting Datasets for the Study “How Well Do U.S. National Water Model Short-Range Forecasts Predict Flood Event Timing and Magnitude?”
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| Storage: | The size of this resource is 402.3 MB | |
| Created: | Oct 11, 2022 at 3:48 p.m. (UTC) | |
| Last updated: | Nov 16, 2025 at 6:39 a.m. (UTC) | |
| Citation: | See how to cite this resource |
| Sharing Status: | Discoverable |
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Abstract
This HydroShare resource contains all datasets, reproducible workflows, and Python/Jupyter Notebook scripts used in the manuscript “How Well Do U.S. National Water Model Short-Range Forecasts Predict Flood Event Timing and Magnitude?” (Maghami et al., 2025; under revision). The study evaluates the U.S. National Water Model (NWM) v2.1 short-range (0–18 hr) forecasts for 306 USGS stream gauges across 16 study areas in the continental United States, covering flood events occurring between April 2021 and September 2023.
The resource provides a complete end-to-end reproducible pipeline, including:
- identification and selection of USGS gauges and flood peaks,
- watershed delineation and integration of land-cover, climate-zone, regulation status, stream order, and drainage-area attributes,
- gauge-to-COMID matching using NHDPlus V2.1,
- extraction of short-range NWM forecasts and return-period estimates via the NWM BigQuery API,
- quality-control screening of USGS observations,
- multi-event flood selection using consistent peak-based criteria, and
- computation of evaluation metrics (scaled KGE, time-to-peak bias, peak-discharge ratio, and flow-volume ratio) across 18 lead times.
The workflows also generate the hydrographs, performance plots, and stratified analyses used in the manuscript (by return period, climate zone, imperviousness, stream order, and regulation status). The notebooks (JN1–JN10) and directory structure are fully documented to support transparency and reproducibility.
A README file is included with instructions for running each workflow, required software environments, and detailed descriptions of all input and output files. This resource will be made public upon manuscript acceptance and assigned a DOI to support citation, reproducibility, and long-term accessibility.
Subject Keywords
Coverage
Spatial
Content
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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