2011
DOI: 10.1111/j.1752-1688.2011.00577.x
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Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States1

Abstract: We compared the results of 12 recently calibrated regional SPARROW (SPAtially Referenced Regressions On Watershed attributes) models covering most of the continental United States to evaluate the consistency and regional differences in factors affecting stream nutrient loads. The models – 6 for total nitrogen and 6 for total phosphorus – all provide similar levels of prediction accuracy, but those for major river basins in the eastern half of the country were somewhat more accurate. The models simulate long-te… Show more

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Cited by 109 publications
(100 citation statements)
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References 35 publications
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“…The yield R-squared is a better measure of fit than load R-squared given that the basin sizes were variable for the monitoring stations. For comparison, the yield R-squared for six regional SPARROW models with similar monitoring station densities as that of this study ranged from 0.72 to 0.86 for nitrogen, and 0.60 to 0.80 for phosphorus (Preston, Alexander, Schwarz, and Crawford, 2011).…”
Section: Model Descriptionmentioning
confidence: 67%
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“…The yield R-squared is a better measure of fit than load R-squared given that the basin sizes were variable for the monitoring stations. For comparison, the yield R-squared for six regional SPARROW models with similar monitoring station densities as that of this study ranged from 0.72 to 0.86 for nitrogen, and 0.60 to 0.80 for phosphorus (Preston, Alexander, Schwarz, and Crawford, 2011).…”
Section: Model Descriptionmentioning
confidence: 67%
“…Smith and others (1997) developed the SPARROW modeling technique and applied it to build an understanding of nitrogen and phosphorus sources and transport in streams of the conterminous United States. Subsequent efforts that have developed SPARROW models include but are not limited to nitrogen and phosphorus sources and transport for streams in specific major river basins of the United States (Preston, Alexander, and Wolock, 2011;Preston, Alexander, Schwarz, and Crawford, 2011), dissolved-solids sources and transport in streams of the Upper Colorado River Basin (Kenney and others, 2009), and dissolved-solids sources and transport in streams of the southwestern United States (Anning and others, 2007;Anning, 2011). SPARROW models have been used to (1) extrapolate known water-quality conditions in monitored reaches to estimate conditions in unmonitored reaches; (2) establish links between water quality and constituent sources; (3) track the transport of constituents to streams and downstream receiving waters, such as estuaries; (4) assess the natural processes that attenuate constituents as they are transported from land and downstream; and (5) predict changes in water quality that may result from management actions or changes in land use.…”
Section: Modeling Approachmentioning
confidence: 99%
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“…Losses from specific sectors/industries are detailed in these reports. For 2002, leaching of Nr to surface waters was based on the USGS SPARROW model (Preston et al 2011); we assumed that 2007 was the same as 2002.…”
Section: N Use Datamentioning
confidence: 99%
“…The SPARROW model has been calibrated by the USGS to estimate nitrogen loads for the base year 2002 from point sources (wastewater discharges) and nonpoint sources (atmospheric deposition, agriculture fertilizer/manure, and urban/suburban land) and accounts for watershed characteristics such as precipitation, temperature, soil permeability, stream density, flow rate, velocity, and lake/reservoir hydraulics [41]. The USGS SPARROW model simulates nitrogen removal based on hydrological processes such as denitrification, particulate settling, and water velocity [42]. SPARROW is a nonlinear least squares regression model where the mean annual N load, as the dependent variable, is weighted by land-to-water movement, instream transport, and assimilation of nitrogen as the explanatory variable (Table 3).…”
Section: Methodsmentioning
confidence: 99%