ABSTRACT:

This HydroShare resource contains the data, Python scripts, and documentation used in the study titled "Evaluating the U.S. National Water Model Retrospective Evapotranspiration Simulation using Eddy-Covariance Flux Tower Measurements" by Chapagain, Maghami, and Ames. The study assesses monthly evapotranspiration (ET) outputs from the National Water Model (NWM) retrospective simulation across 72 AmeriFlux tower sites representing a range of climate zones, land cover types, and hydrologic regimes within the contiguous United States. The resource includes:

1- Preprocessed ET and meteorological data from NWM and AmeriFlux

2- Analysis scripts for computing performance metrics (e.g., Scaled KGE, PBIAS)

3- Group-wise evaluation by RFC, Köppen-Geiger climate zone, and land use

4- Visualization code for reproducible plots in the manuscript

5- Regime classification and temperature bias assessments

Note: The majority of analysis and visualization steps are provided as Jupyter notebooks, which were run locally in a Python environment. Most results can be reproduced with the included scripts, though some raw input data or dependencies may require additional setup. Additionally, ArcGIS Pro was used primarily for generating the map showing site locations and their hydroclimatic attributes.

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 resource contains a series of Python-based Jupyter Notebooks used to evaluate the performance of short-range flood forecasts from the National Water Model (NWM) across 17 major U.S. flood events between 2021 and 2022. The workflows include gage selection, watershed delineation, land cover and topographic analysis, NWM forecast retrieval via API, and forecast performance evaluation using peak flow, timing, volume, and Kling-Gupta Efficiency metrics. These notebooks support the analyses presented in the mansucript "Comprehensive Evaluation of Short-Range Flood Forecasts in the U.S. National Water Model: A Multi-Region Analysis of Flood Timing, Magnitude, and Basin Influences" submitted to the journal and are intended to promote reproducibility and transparency in large-scale hydrologic model evaluation.

Note: The resource is currently discoverable only. Upon publication of the manuscript, the full dataset will be made accessible and the resource will be published with a DOI.