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Implementing an Operational Framework to Develop a Streamflow Duration Assessment Method: A Case Study from the Arid West United States

Streamflow duration information underpins many management decisions. However, hydrologic data are rarely available where needed. Rapid streamflow duration assessment methods (SDAMs) classify reaches based on indicators that are measured in a single brief visit. We evaluated a proposed framework for...

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Autores principales: Mazor, Raphael D., Topping, Brian J., Nadeau, Tracie-Lynn, Fritz, Ken M., Kelso, Julia E., Harrington, Rachel A., Beck, Whitney S., McCune, Kenneth S., Allen, Aaron O., Leidy, Robert, Robb, James T., David, Gabrielle C. L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8715911/
https://www.ncbi.nlm.nih.gov/pubmed/34976403
http://dx.doi.org/10.3390/w13223310
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author Mazor, Raphael D.
Topping, Brian J.
Nadeau, Tracie-Lynn
Fritz, Ken M.
Kelso, Julia E.
Harrington, Rachel A.
Beck, Whitney S.
McCune, Kenneth S.
Allen, Aaron O.
Leidy, Robert
Robb, James T.
David, Gabrielle C. L.
author_facet Mazor, Raphael D.
Topping, Brian J.
Nadeau, Tracie-Lynn
Fritz, Ken M.
Kelso, Julia E.
Harrington, Rachel A.
Beck, Whitney S.
McCune, Kenneth S.
Allen, Aaron O.
Leidy, Robert
Robb, James T.
David, Gabrielle C. L.
author_sort Mazor, Raphael D.
collection PubMed
description Streamflow duration information underpins many management decisions. However, hydrologic data are rarely available where needed. Rapid streamflow duration assessment methods (SDAMs) classify reaches based on indicators that are measured in a single brief visit. We evaluated a proposed framework for developing SDAMs to develop an SDAM for the Arid West United States that can classify reaches as perennial, intermittent, or ephemeral. We identified 41 candidate biological, geomorphological, and hydrological indicators of streamflow duration in a literature review, evaluated them for a number of desirable criteria (e.g., defensibility and consistency), and measured 21 of them at 89 reaches with known flow durations. We selected metrics for the SDAM based on their ability to discriminate among flow duration classes in analyses of variance, as well as their importance in a random forest model to predict streamflow duration. This approach resulted in a “beta” SDAM that uses five biological indicators. It could discriminate between ephemeral and non-ephemeral reaches with 81% accuracy, but only 56% accuracy when distinguishing 3 classes. A final method will be developed following expanded data collection. This Arid West study demonstrates the effectiveness of our approach and paves the way for more efficient development of scientifically informed SDAMs.
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spelling pubmed-87159112022-11-22 Implementing an Operational Framework to Develop a Streamflow Duration Assessment Method: A Case Study from the Arid West United States Mazor, Raphael D. Topping, Brian J. Nadeau, Tracie-Lynn Fritz, Ken M. Kelso, Julia E. Harrington, Rachel A. Beck, Whitney S. McCune, Kenneth S. Allen, Aaron O. Leidy, Robert Robb, James T. David, Gabrielle C. L. Water (Basel) Article Streamflow duration information underpins many management decisions. However, hydrologic data are rarely available where needed. Rapid streamflow duration assessment methods (SDAMs) classify reaches based on indicators that are measured in a single brief visit. We evaluated a proposed framework for developing SDAMs to develop an SDAM for the Arid West United States that can classify reaches as perennial, intermittent, or ephemeral. We identified 41 candidate biological, geomorphological, and hydrological indicators of streamflow duration in a literature review, evaluated them for a number of desirable criteria (e.g., defensibility and consistency), and measured 21 of them at 89 reaches with known flow durations. We selected metrics for the SDAM based on their ability to discriminate among flow duration classes in analyses of variance, as well as their importance in a random forest model to predict streamflow duration. This approach resulted in a “beta” SDAM that uses five biological indicators. It could discriminate between ephemeral and non-ephemeral reaches with 81% accuracy, but only 56% accuracy when distinguishing 3 classes. A final method will be developed following expanded data collection. This Arid West study demonstrates the effectiveness of our approach and paves the way for more efficient development of scientifically informed SDAMs. 2021-11-22 /pmc/articles/PMC8715911/ /pubmed/34976403 http://dx.doi.org/10.3390/w13223310 Text en https://creativecommons.org/licenses/by/4.0/This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mazor, Raphael D.
Topping, Brian J.
Nadeau, Tracie-Lynn
Fritz, Ken M.
Kelso, Julia E.
Harrington, Rachel A.
Beck, Whitney S.
McCune, Kenneth S.
Allen, Aaron O.
Leidy, Robert
Robb, James T.
David, Gabrielle C. L.
Implementing an Operational Framework to Develop a Streamflow Duration Assessment Method: A Case Study from the Arid West United States
title Implementing an Operational Framework to Develop a Streamflow Duration Assessment Method: A Case Study from the Arid West United States
title_full Implementing an Operational Framework to Develop a Streamflow Duration Assessment Method: A Case Study from the Arid West United States
title_fullStr Implementing an Operational Framework to Develop a Streamflow Duration Assessment Method: A Case Study from the Arid West United States
title_full_unstemmed Implementing an Operational Framework to Develop a Streamflow Duration Assessment Method: A Case Study from the Arid West United States
title_short Implementing an Operational Framework to Develop a Streamflow Duration Assessment Method: A Case Study from the Arid West United States
title_sort implementing an operational framework to develop a streamflow duration assessment method: a case study from the arid west united states
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8715911/
https://www.ncbi.nlm.nih.gov/pubmed/34976403
http://dx.doi.org/10.3390/w13223310
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