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

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

doi:10.3390/w12092545

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.

Highlights

IntroductionWhile gauging stations provide direct hydrological data for streamflow classification, the cost of maintaining gauging networks limits their lifespan and geographical extent [1]
Because streamflow influences patterns and processes in streams and adjacent riparian areas, streamflow classification is often used to support environmental management and restoration decisions.While gauging stations provide direct hydrological data for streamflow classification, the cost of maintaining gauging networks limits their lifespan and geographical extent [1]
Our objective is to provide the scientific basis and an operational framework to use environmental indicators for streamflow duration classification at the reach scale (101 –102 m)

Summary

Introduction

While gauging stations provide direct hydrological data for streamflow classification, the cost of maintaining gauging networks limits their lifespan and geographical extent [1]. Gauges tend to be located on large, generally perennially flowing streams and rivers, so most of the stream miles in the United States (U.S.) are underrepresented by the gauge network [2]. Hydrographic Dataset (NHD) is the most comprehensive source on stream extent and streamflow classification in the U.S.; the NHD is a static characterization that tends to more accurately characterize larger streams and rivers than the more abundant headwater streams [5,6]. Remote sensing approaches have the potential to characterize hydrology across landscapes [7,8]

Objectives

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Results