Estimates of long-term mean daily streamflow and annual nutrient and suspended-sediment loads considered for use in regional SPARROW models of the Conterminous United States, 2012 base year
Streamflow, nutrient, and sediment concentration data needed to estimate long-term mean daily streamflow and annual constituent loads were compiled from Federal, State, Tribal, and regional agencies, universities, and nongovernmental organizations. The streamflow and loads are used to develop Spatially Referenced Regressions on Watershed Attributes (SPARROW) models. SPARROW models help describe the distribution, sources, and transport of streamflow, nutrients, and sediment in streams throughout five regions of the conterminous United States. After the data were screened, approximately 5,200 streamflow, 3,000 sediment, and 3,300 nutrient sites, sampled by 137 agencies and organizations were identified as having suitable data for calculating the long-term mean daily streamflow and annual nutrient and sediment loads required for SPARROW model estimation. These sites are representative of a wide range in terms of watershed size, contaminant source types, and land-use and other important watershed characteristics. The methods used to estimate long-term mean annual loads include the Beale ratio estimator and Fluxmaster regression method with Kalman smoothing.
Citation Information
Publication Year | 2019 |
---|---|
Title | Estimates of long-term mean daily streamflow and annual nutrient and suspended-sediment loads considered for use in regional SPARROW models of the Conterminous United States, 2012 base year |
DOI | 10.3133/sir20195069 |
Authors | David A. Saad, Gregory E. Schwarz, Denise M. Argue, David W. Anning, Scott A. Ator, Anne B. Hoos, Stephen D. Preston, Dale M. Robertson, Daniel Wise |
Publication Type | Report |
Publication Subtype | USGS Numbered Series |
Series Title | Scientific Investigations Report |
Series Number | 2019-5069 |
Index ID | sir20195069 |
Record Source | USGS Publications Warehouse |
USGS Organization | Wisconsin Water Science Center; WMA - Integrated Modeling and Prediction Division; Upper Midwest Water Science Center |