SPARROW Major River Basin (MRB) Studies
BACKGROUNDThe NAWQA Program has adopted SPARROW modeling to assess nutrient conditions in six large regions of the conterminous United States that cover all areas except for California and the Southwest (see map).
The nutrient modeling studies are part of NAWQA's Major River Basin (MRB) status and trends assessments of stream chemistry, with emphasis on nutrients, pesticides, and ecosystem health. A SPARROW salinity model of the Southwest was previously developed to estimate the spatial distribution of total dissolved solids and natural and human factors controlling salinity throughout the region (Anning and others, 2007).
REGIONAL NUTRIENT MODELSSPARROW models were recently completed for the base year 2002 for six major regions of the conterminous United States (all regions except for California and the Southwest). Results from the models can be used to compare nutrient sources and watersheds that contribute elevated nutrient loads to estuaries and other receiving waters, such as the South Atlantic and Gulf of Mexico, inland and coastal waters of the Northeast, the Upper Mississippi and Great Lakes, and Puget Sound.
These models provide a variety of types of information that will be useful in evaluating stream-water quality for management or regulatory objectives.
The models use data on atmospheric deposition, commercial fertilizer applied to agricultural land, animal-manure production, point-source discharges, population density, and land cover (urban, agricultural, and forested). The data describing many of these nutrient sources and watershed characteristics have been refined since earlier SPARROW models.
The models also include nutrient-monitoring data from local, State, and other federal agencies, which substantially increases the number of model-calibration sites. For instance, the South-Atlantic Gulf model includes data from 321 monitoring sites, which is 233 sites more than were used in prior national models (based on USGS monitoring only) for the same region.
The combination of more calibration sites and refined geospatial data provides significant improvement over previous models in prediction accuracy and the identification of regional nutrient sources and transport factors.