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User Manual for a Beta Streamflow Duration Assessment Methods for the Northeast and Southeast regions of the United States. Version 1.0
Citation:
James, A., Tracie-Lynn Nadeau, K. Fritz, B. Topping, R. Edgerton, R. Mazor, J. Kelso, AND K. Nicholas. User Manual for a Beta Streamflow Duration Assessment Methods for the Northeast and Southeast regions of the United States. Version 1.0. U.S. Environmental Protection Agency, Washington, DC, EPA/600/B-23/087, 2023.
Impact/Purpose:
Flow duration classification is used to implement several federal, state and local stream management programs. Because the flow duration of streams via existing maps, remote sensing, and gauging is constrained, field-based tools are often needed by practitioners. The manual describes beta methods to rapidly classify stream reaches as ephemeral, intermittent, perennial, and at-least intermittent in the Northeast and Southeast regions of the United States.
Description:
This manual describes beta Streamflow Duration Assessment Methods (SDAMs) that are intended to distinguish flow duration classes (ephemeral, intermittent, and perennial) of stream reaches in the Northeast (NE) region and in the Southeast (SE) region of the United States. All indicators are quantified during a single field visit and across the entire assessment reach. It is anticipated that the beta methods will be made available for one year to allow the user community to provide feedback before final SDAMs for the NE and SE are produced. The manual provides an overview of the beta SDAM process, data collection, data interpretation, and preparation of a beta SDAM report. Three biological, three geomorphological indicators, and two geospatial (GIS) indicators form the basis of the beta SDAM for the NE. Three biological, two geographical, and two GIS indicators for the basis of the beta SDAM for the SE. These indicators are evaluated together to assign a preliminary flow duration class to a stream reach within each region. The beta SDAMs for the NE and the SE assign reaches to one of four possible classifications: ephemeral, intermittent, perennial, and at least intermittent. The latter classification occurs when an intermittent or perennial classification cannot be made with high confidence, but an ephemeral classification can be ruled out. Each region's protocol uses a machine learning model known as random forest. Random forest models are increasingly common in the environmental sciences because of their superior performance in handling complex relationships among indicators used to predict classifications. In addition to describing the protocols for collecting field data, the manual describes the open-access, user-friendly web application for entering indicator data and running the developed random forest models to obtain the classification for individual assessment reaches in the NE and SE regions.