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Review

Classifying Streamflow Duration: The Scientific Basis and an Operational Framework for Method Development

1
Center for Environmental Measurement and Modeling, Office of Research and Development, US Environmental Protection Agency, Cincinnati, OH 45268, USA
2
Region 10, US Environmental Protection Agency, Portland, OR 97205, USA
3
Office of Wetlands, Oceans, and Watersheds, US Environmental Protection Agency, Washington, DC 20460, USA
4
Oak Ridge Institute for Science and Education Fellow, Oak Ridge, TN 37831, USA
5
Southern California Coastal Water Research Project, Costa Mesa, CA 92626, USA
*
Author to whom correspondence should be addressed.
Current Affiliation: Region 8, US Environmental Protection Agency, Denver, CO 80202, USA.
Water 2020, 12(9), 2545; https://doi.org/10.3390/w12092545
Received: 7 July 2020 / Revised: 4 September 2020 / Accepted: 6 September 2020 / Published: 11 September 2020
Streamflow duration is used to differentiate reaches into discrete classes (e.g., perennial, intermittent, and ephemeral) for water resource management. Because the depiction of the extent and flow duration of streams via existing maps, remote sensing, and gauging is constrained, field-based tools are needed for use by practitioners and to validate hydrography and modeling advances. Streamflow Duration Assessment Methods (SDAMs) are rapid, reach-scale indices or models that use physical and biological indicators to predict flow duration class. We review the scientific basis for indicators and present conceptual and operational frameworks for SDAM development. Indicators can be responses to or controls of flow duration. Aquatic and terrestrial responses can be integrated into SDAMs, reflecting concurrent increases and decreases along the flow duration gradient. The conceptual framework for data-driven SDAM development shows interrelationships among the key components: study reaches, hydrologic data, and indicators. We present a generalized operational framework for SDAM development that integrates the data-driven components through five process steps: preparation, data collection, data analysis, evaluation, and implementation. We highlight priorities for the advancement of SDAMs, including expansion of gauging of nonperennial reaches, use of citizen science data, adjusting for stressor gradients, and statistical and monitoring advances to improve indicator effectiveness. View Full-Text
Keywords: classification; flow duration; indicators; perennial; intermittent; ephemeral; temporary; flow permanence; intermittency; rapid assessment classification; flow duration; indicators; perennial; intermittent; ephemeral; temporary; flow permanence; intermittency; rapid assessment
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MDPI and ACS Style

Fritz, K.M.; Nadeau, T.-L.; Kelso, J.E.; Beck, W.S.; Mazor, R.D.; Harrington, R.A.; Topping, B.J. Classifying Streamflow Duration: The Scientific Basis and an Operational Framework for Method Development. Water 2020, 12, 2545. https://doi.org/10.3390/w12092545

AMA Style

Fritz KM, Nadeau T-L, Kelso JE, Beck WS, Mazor RD, Harrington RA, Topping BJ. Classifying Streamflow Duration: The Scientific Basis and an Operational Framework for Method Development. Water. 2020; 12(9):2545. https://doi.org/10.3390/w12092545

Chicago/Turabian Style

Fritz, Ken M.; Nadeau, Tracie-Lynn; Kelso, Julia E.; Beck, Whitney S.; Mazor, Raphael D.; Harrington, Rachel A.; Topping, Brian J. 2020. "Classifying Streamflow Duration: The Scientific Basis and an Operational Framework for Method Development" Water 12, no. 9: 2545. https://doi.org/10.3390/w12092545

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