Evidence map›Paper›PMID 33133647›Full record

ArticleWater2020

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

Ken M Fritz, Tracie-Lynn Nadeau, Julia E Kelso, Whitney S Beck, Raphael D Mazor, Rachel A Harrington, Brian J Topping

Open access · goldAbstract read
In one paragraph

Article in Water, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.9field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 36 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Ken M FritzCenter for Environmental Measurement and Modeling, Office of Research and Development, US Environmental Protection Agency, Cincinnati, OH 45268, USA.ORCID 0000-0002-3831-2531
Tracie-Lynn NadeauRegion 10, US Environmental Protection Agency, Portland, OR 97205, USA.
Julia E KelsoOffice of Wetlands, Oceans, and Watersheds, US Environmental Protection Agency, Washington, DC 20460, USA.
Whitney S BeckOffice of Wetlands, Oceans, and Watersheds, US Environmental Protection Agency, Washington, DC 20460, USA.
Raphael D MazorSouthern California Coastal Water Research Project, Costa Mesa, CA 92626, USA.
Rachel A HarringtonOffice of Wetlands, Oceans, and Watersheds, US Environmental Protection Agency, Washington, DC 20460, USA.
Brian J ToppingOffice of Wetlands, Oceans, and Watersheds, US Environmental Protection Agency, Washington, DC 20460, USA.
Environmental Protection Agency · USOak Ridge Associated Universities · USSouthern California Coastal Water Research Project · US

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

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.

Indexed as

classificationephemeralflow durationflow permanenceindicatorsintermittencyintermittentperennialrapid assessmenttemporary

Identifiers

PMID33133647
PMCPMC7592706
OpenAlexW3085939241

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.