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User-focused evaluation of National Ecological Observatory Network streamflow estimates

Accurately estimating stream discharge is crucial for many ecological, biogeochemical, and hydrologic analyses. As of September 2022, The National Ecological Observatory Network (NEON) provided up to 5 years of continuous discharge estimates at 28 streams across the United States. NEON created ratin...

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Autores principales: Rhea, Spencer, Gubbins, Nicholas, DelVecchia, Amanda G., Ross, Matthew R. V., Bernhardt, Emily S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9922330/
https://www.ncbi.nlm.nih.gov/pubmed/36774381
http://dx.doi.org/10.1038/s41597-023-01983-w
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author Rhea, Spencer
Gubbins, Nicholas
DelVecchia, Amanda G.
Ross, Matthew R. V.
Bernhardt, Emily S.
author_facet Rhea, Spencer
Gubbins, Nicholas
DelVecchia, Amanda G.
Ross, Matthew R. V.
Bernhardt, Emily S.
author_sort Rhea, Spencer
collection PubMed
description Accurately estimating stream discharge is crucial for many ecological, biogeochemical, and hydrologic analyses. As of September 2022, The National Ecological Observatory Network (NEON) provided up to 5 years of continuous discharge estimates at 28 streams across the United States. NEON created rating curves at each site in a Bayesian framework, parameterized using hydraulic controls and manual measurements of discharge. Here we evaluate the reliability of these discharge estimates with three approaches. We (1) compared predicted to observed discharge, (2) compared predicted to observed stage, and (3) calculated the proportion of discharge estimates extrapolated beyond field measurements. We considered 1,523 site-months of continuous streamflow predictions published by NEON. Of these, 39% met our highest quality criteria, 11% fell into an intermediate classification, and 50% of site-months were classified as unreliable. We provided diagnostic metrics and categorical evaluations of continuous discharge and stage estimates by month for each site, enabling users to rapidly query for suitable NEON data.
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spelling pubmed-99223302023-02-13 User-focused evaluation of National Ecological Observatory Network streamflow estimates Rhea, Spencer Gubbins, Nicholas DelVecchia, Amanda G. Ross, Matthew R. V. Bernhardt, Emily S. Sci Data Analysis Accurately estimating stream discharge is crucial for many ecological, biogeochemical, and hydrologic analyses. As of September 2022, The National Ecological Observatory Network (NEON) provided up to 5 years of continuous discharge estimates at 28 streams across the United States. NEON created rating curves at each site in a Bayesian framework, parameterized using hydraulic controls and manual measurements of discharge. Here we evaluate the reliability of these discharge estimates with three approaches. We (1) compared predicted to observed discharge, (2) compared predicted to observed stage, and (3) calculated the proportion of discharge estimates extrapolated beyond field measurements. We considered 1,523 site-months of continuous streamflow predictions published by NEON. Of these, 39% met our highest quality criteria, 11% fell into an intermediate classification, and 50% of site-months were classified as unreliable. We provided diagnostic metrics and categorical evaluations of continuous discharge and stage estimates by month for each site, enabling users to rapidly query for suitable NEON data. Nature Publishing Group UK 2023-02-11 /pmc/articles/PMC9922330/ /pubmed/36774381 http://dx.doi.org/10.1038/s41597-023-01983-w Text en © The Author(s) 2023, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Analysis
Rhea, Spencer
Gubbins, Nicholas
DelVecchia, Amanda G.
Ross, Matthew R. V.
Bernhardt, Emily S.
User-focused evaluation of National Ecological Observatory Network streamflow estimates
title User-focused evaluation of National Ecological Observatory Network streamflow estimates
title_full User-focused evaluation of National Ecological Observatory Network streamflow estimates
title_fullStr User-focused evaluation of National Ecological Observatory Network streamflow estimates
title_full_unstemmed User-focused evaluation of National Ecological Observatory Network streamflow estimates
title_short User-focused evaluation of National Ecological Observatory Network streamflow estimates
title_sort user-focused evaluation of national ecological observatory network streamflow estimates
topic Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9922330/
https://www.ncbi.nlm.nih.gov/pubmed/36774381
http://dx.doi.org/10.1038/s41597-023-01983-w
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