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

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 a...

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Bibliographic Details
Published in:Water (Basel) 2020-09, Vol.12 (9), p.1-2545
Main Authors: Fritz, Ken M, Nadeau, Tracie-Lynn, Kelso, Julia E, Beck, Whitney S, Mazor, Raphael D, Harrington, Rachel A, Topping, Brian J
Format: Article
Language:English
Subjects:
Classification
Creeks & streams
Data collection
Environmental aspects
Environmental conditions
Flow duration
Gaging
Gauges
Groundwater
Hydrography
Hydrologic data
Hydrology
Identification and classification
Indicators
Management
Management decisions
Measurement
Remote sensing
Resource management
Sediments
Stream discharge
Stream flow
Streamflow
Streams
Surface water
Terrestrial environments
Water
Water management
Water resources
Water resources management
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Summary: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.
ISSN:2073-4441
2073-4441
DOI:10.3390/w12092545