Tributary loading estimation methods were evaluated by conducting retrospective studies with comprehensive sets of field data for flow rates, nutrients, heavy metals, and polychlorinated biphenyls. Three broad classes of loading estimation methods were investigated: simple averaging methods, ratio estimation methods, and regression methods. Estimators were evaluated using Monte Carlo sampling studies in which random subsamples of complete loading records were used to estimate annual loadings. These estimates were then compared to “true” loadings determined by calculations using the entire record. No group of estimators were found to be superior for all test cases considered. However, individual estimation approaches within each group often provided low error estimates. Results were inconsistent among test cases and these inconsistencies appeared to be related to specific test case characteristics such as the strength and form of the flow‐concentration relationship and the nature of the annual hydrograph. Ratio estimators appeared to be more robust to sources of bias than other estimation approaches.

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-term mean annual stream nutrient loads as a function of a wide range of known sources and climatic (precipitation, temperature), landscape (e.g., soils, geology), and aquatic factors affecting nutrient fate and transport. The results confirm the dominant effects of urban and agricultural sources on stream nutrient loads nationally and regionally, but reveal considerable spatial variability in the specific types of sources that control water quality. These include regional differences in the relative importance of different types of urban (municipal and industrial point vs. diffuse urban runoff) and agriculture (crop cultivation vs. animal waste) sources, as well as the effects of atmospheric deposition, mining, and background (e.g., soil phosphorus) sources on stream nutrients. Overall, we found that the SPARROW model results provide a consistent set of information for identifying the major sources and environmental factors affecting nutrient fate and transport in United States watersheds at regional and subregional scales.

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