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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
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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 |
Sumario: | 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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