Richard B. Alexander(1), Penny J. Johnes(2), Elizabeth W. Boyer(3), and Richard A. Smith(1)
1 U.S. Geological Survey, 413 National Center, Reston, Virginia 20192, USA
2 University of Reading, Aquatic Environments Research Centre, Dept. of Geography, Whiteknights Reading RG6 6AB, U.K.
3 State University of New York, College of Environmental Science and Forestry, 1 Forestry Dr., Syracuse, N.Y., 13210, USA
Biogeochemistry, 2002, v. 57/58, p. 295-339
Abstract. We evaluated the accuracy of six watershed models of nitrogen export in streams (kg km-2 yr-1) developed for use in large watersheds and representing various empirical and quasi-empirical approaches described in the literature. These models differ in their methods of calibration and have varying levels of spatial resolution and process complexity, which potentially affect the accuracy (bias and precision) of the model predictions of nitrogen export and source contributions to export. Using stream monitoring data and detailed estimates of the natural and cultural sources of nitrogen for 16 watersheds in the northeastern United States (drainage sizes=475 to 70,000 km2), we assessed the accuracy of the model predictions of total nitrogen and nitrate-nitrogen export. The model validation included the use of an error modeling technique to identify biases caused by model deficiencies in quantifying nitrogen sources and biogeochemical processes affecting the transport of nitrogen in watersheds. Most models predicted stream nitrogen export to within 50% of the measured export in a majority of the watersheds. Prediction errors were negatively correlated with cultivated land area, indicating that the watershed models tended to over predict export in less agricultural and more forested watersheds and under predict in more agricultural basins. The magnitude of these biases differed appreciably among the models. Those models having more detailed descriptions of nitrogen sources, land and water attenuation of nitrogen, and water flow paths were found to have considerably lower bias and higher precision in their predictions of nitrogen export.
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