Implementing an Operational Framework to Develop a Streamflow Duration Assessment Method: A Case Study from the Arid West United States
| Autor: | Brian J. Topping, Tracie-Lynn Nadeau, James T. Robb, Whitney S. Beck, Aaron O. Allen, Kenneth S. McCune, Robert Leidy, Gabrielle C. L. David, Julia E. Kelso, Ken M. Fritz, Raphael D. Mazor, Rachel A. Harrington |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Data collection
Water supply for domestic and industrial purposes Ephemeral key Geography Planning and Development Variance (accounting) Hydraulic engineering Aquatic Science classification flow duration streams perennial intermittent ephemeral temporary flow permanence intermittency rapid assessment Biochemistry Arid Random forest Consistency (database systems) Streamflow Environmental science Duration (project management) Water resource management TC1-978 TD201-500 Water Science and Technology |
| Zdroj: | Water, Vol 13, Iss 3310, p 3310 (2021) Water; Volume 13; Issue 22; Pages: 3310 |
| ISSN: | 2073-4441 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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