ABSTRACT:

This HydroShare resource contains the data, Python scripts, and documentation used in the study “Evaluating the U.S. National Water Model Retrospective Evapotranspiration Simulation using Eddy-Covariance Flux Tower Measurements” (Chapagain et al., 2025, Journal of Hydrology: Regional Studies).The study evaluates National Water Model (NWM) evapotranspiration (ET) estimates across the contiguous United States (CONUS) using multi-year comparisons with AmeriFlux tower observations at 72 sites spanning diverse hydroclimatic settings.

The analysis assesses NWM ET performance at the site level and across categorical groupings based on National Weather Service River Forecast Centers (RFCs), Köppen–Geiger climate zones, and land cover types. It also examines temperature forcing accuracy and contrasts ET behavior under water- and energy-limited (P/PET) regimes.

Results reveal wide performance variability, with stronger agreement in cold climates and forested basins and lower skill in arid and agricultural regions. ET estimates tend to perform better under water-limited than energy-limited conditions, while temperature forcings show strong agreement with observations.

The resource includes:

- Preprocessed NWM and AmeriFlux ET and meteorological datasets.
- Python scripts for computing performance metrics (e.g., Scaled KGE, PBIAS).
- Group-based and regime-based analysis notebooks.
- Visualization workflows reproducing key figures from the paper.
- ArcGIS files for site-location mapping.

Most analyses were performed in Python, with ArcGIS Pro was used for spatial processing and visualization. These materials enable reproducibility of the paper’s results and facilitate further analysis of NWM ET performance across CONUS.

ABSTRACT:

This app connector is for map viewer page is displaying a Leaflet map using Open Street Map tiles as a base map. It is also able to load a WMS layer from a HydroShare Geoserver WMS service if the parameters "resourceid" and "layername" are specified from a valid HydroShare resource.

ABSTRACT:

THis is just a test

ABSTRACT:

This study evaluates the performance metrics of observed gauges worldwide on the GEOGloWS versions 1 and 2. The primary objective is to assess the accuracy of the basin identification (comid) assignment on version 2 for bias correction using SABER method. By calculating and comparing performance metrics with the findings from Jorges dissertation on version 1, the analysis aims to validate the comid assignments in GEOGloWS V2, which were determined through an automated process. The goal is to determine whether manual inspection of the approximately 18,000 global gauge stations is necessary to ensure accurate comid assignments, critical for effective bias correction.[EDITED]

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.