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U.S. GEOLOGICAL SURVEY
Scientific Investigations Report 2009–5015

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Limitations and Areas for Further Study

The GLS regression equations were generated using streamflow-gaging station data and are applicable for stream sites in the study area with drainage areas ranging from 3.0 to 12,228 mi²; however, this range varies by region. Ranges for other explanatory variables used to develop the regression equations are presented in table 2. The regression equations were applied outside the range of values in table 2 to predict endpoints of perennial flow along stream reaches. Such extrapolation cannot be avoided because of a lack of streamflow data for small streams. As a result, considerable uncertainty exists in the perennial streams model presented in this report, though agreement with independent datasets was good. The regression models provide overall estimates based on the general trends within each region.

Local factors such as a large spring or a losing reach are not included in these regression models, and these factors may greatly affect flows at any given point. Site-specific flow data, assuming a sufficient period of record, generally would be considered to better represent flow conditions at a given site than flow estimates based on regionalized regression models. However, this information rarely is available and is not always practical to obtain. The map is considered a first-cut, broad scale estimate of the locations of perennial streams that could be used for state-wide planning, assessment, and reporting purposes. The regression equations and perennial streams model presented are applicable only to unregulated, naturally-flowing streams.

Most studies to predict low-flow statistics at ungaged sites have relied on regression equations with basin characteristics such as drainage area, slope, elevation, and land cover. Permanence of flow in small streams is expected to depend on these characteristics as well as on ground water, or baseflow, contributions to the stream throughout the year. Baseflow recession information would be helpful in quantifying low-flow characteristics on a regional basis. Many studies have shown that the use of a baseflow recession constant or streamflow variability predictor greatly reduces the error of estimation of low-flow statistics (Vogel and Kroll, 1992; Yu and others, 2002; Kroll and others, 2004; Eng and Milly, 2007). However, baseflow information typically is gathered from long-term, continuous streamflow-gaging stations. Quantifying and predicting the baseflow recession constant (tau) at ungaged headwater sites, through procedures outlined in Eng and Milly (2007), may be an important element in improving accuracy in low flow statistics and stream classification.

In June 2006, the United States Supreme Court issued a ruling in the consolidated cases Rapanos vs. United States and Carabell vs. United States that changed the interpretation of stream classifications under the jurisdiction of the Clean Water Act. The ruling, called the Rapanos Decision, may eventually supersede many State and Federal stream management and regulatory guidelines that once were applied based on intermittent and perennial classifications. The new classification considers waters jurisdictional if they are “relatively permanent”, and possibly jurisdictional if “non-relatively permanent” when there is a “significant nexus” to an otherwise jurisdictional water (U.S. Environmental Protection Agency and U.S. Army Corps of Engineers, 2007). Streams are considered relatively permanent if flow is continuous on a seasonal basis (for example, 90 days or more). This report describes an example where streamflow information from the USGS streamflow-gaging network has been used to develop regression equations that predict streamflow characteristics at ungaged sites. However, under the Rapanos Decision, water quality standards may be applied to streams despite long durations of zero flow, and few to no long-term streamflow-gaging stations are located on such streams. Therefore, the existing USGS streamflow-gaging network cannot be used alone to extrapolate statistics to the level necessary to classify and map streams under the Rapanos guidance. A new flow-detection monitoring network and prediction methodology are needed to develop a map of relatively permanent streams to assist regulators and water-resource managers in making jurisdictional determinations. The map of perennial streams described in this report would be useful as a reference when selecting locations of flow-detection monitoring sites.

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