• Open Access

A Multi-Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models

Authors

  • David A. Saad,

    1. Respectively, Hydrologist, Research Hydrologist, IT Specialist (Saad, Robertson, Booth), U.S. Geological Survey, Wisconsin Water Science Center, 8505 Research Way, Middleton, Wisconsin 53562
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  • Gregory E. Schwarz,

    1. Economist (Schwarz), U.S. Geological Survey, National Center, Reston, Virginia
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  • Dale M. Robertson,

    1. Respectively, Hydrologist, Research Hydrologist, IT Specialist (Saad, Robertson, Booth), U.S. Geological Survey, Wisconsin Water Science Center, 8505 Research Way, Middleton, Wisconsin 53562
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  • Nathaniel L. Booth

    1. Respectively, Hydrologist, Research Hydrologist, IT Specialist (Saad, Robertson, Booth), U.S. Geological Survey, Wisconsin Water Science Center, 8505 Research Way, Middleton, Wisconsin 53562
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  • Paper No. JAWRA-10-0174-P of the Journal of the American Water Resources Association (JAWRA). Discussions are open until six months from print publication.

  • Re-use of this article is permitted in accordance with the Terms and Conditions set out at http://wileyonlinelibrary.com/onlineopen#OnlineOpen_Terms

(E-Mail/Saad: dasaad@usgs.gov).

Abstract

Saad, David A., Gregory E. Schwarz, Dale M. Robertson, and Nathaniel L. Booth, 2011. A Multi-Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models. Journal of the American Water Resources Association (JAWRA) 47(5):933-949. DOI: 10.1111/j.1752-1688. 2011.00575.x

Abstract:  Stream-loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long-term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water-quality model, the flow-bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water-quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.

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