This U.S. Geological Survey (USGS) data release includes input and output tabular files associated with mean seasonal 2002 simulations of total nitrogen and total phosphorus loads of the northeastern United States. The mean seasonal (MS) simulations are performed using a dynamic configuration of the USGS’s Spatially Referenced Regression On Watershed attributes (dynamicSPARROW-MS) model, nonlinear regression techniques, and monitored data. Model development, calibration, and results are described in the related external resource (Schmadel et al., 2021).

The U.S. Geological Survey's (USGS) SPAtially Referenced Regression On Watershed attributes (SPARROW) model was used to aid in the interpretation of monitoring data and simulate streamflow and water-quality conditions in streams across the Northeast Region of the United States. SPARROW is a hybrid empirical/process-based mass balance model that can be used to estimate the major sources and environmental factors that affect the long-term supply, transport, and fate of contaminants in streams. The spatially explicit model structure is defined by a river reach network coupled with contributing catchments. The model is calibrated by statistically relating watershed sources and transport-related properties to monitoring-based water-quality load estimates. This USGS data release includes input and output files associated with 2012 SPARROW simulations of streamflow, total nitrogen, total phosphorus and suspended-sediment load in streams of the Northeast region. Model construction, calibration and results are described in Ator (2019, https://doi.org/10.3133/sir20195118).

The U.S. Geological Survey's (USGS) SPAtially Referenced Regression On Watershed attributes (SPARROW) model was used to aid in the interpretation of monitoring data and simulate streamflow and water-quality conditions in streams across the Northeast Region of the United States. SPARROW is a hybrid empirical/process-based mass balance model that can be used to estimate the major sources and environmental factors that affect the long-term supply, transport, and fate of contaminants in streams. The spatially explicit model structure is defined by a river reach network coupled with contributing catchments. The model is calibrated by statistically relating watershed sources and transport-related properties to monitoring-based water-quality load estimates. This USGS data release includes input and output files associated with 2012 SPARROW simulations of streamflow, total nitrogen, total phosphorus and suspended-sediment load in streams of the Northeast region. Model construction, calibration and results are described in Ator (2019, https://doi.org/10.3133/sir20195118).

The U.S. Geological Survey’s (USGS) SPAtially Referenced Regression On Watershed attributes (SPARROW) model was used to aid in the interpretation of monitoring data and simulate nutrient loads in streams across the Midwest Region of the United States. SPARROW is a hybrid empirical/process-based mass balance model that can be used to estimate the major sources and environmental factors that affect the long-term supply, transport, and fate of contaminants in streams. The spatially explicit model structure is defined by a river reach network coupled with contributing catchments. The model is calibrated by statistically relating watershed sources and transport-related properties to monitoring-based water-quality load estimates. This USGS data release includes input, output, control, model coefficient and summary statistic files associated with 2012 SPARROW simulations of total phosphorus load in streams of the Midwest and represents a variation of a similar model described in Robertson and Saad (2019, https://doi.org/10.3133/sir20195114). This version of the model utilizes cover crops as a land-to-water delivery term in place of the phosphorus loss rate term included in the original model. The impacts of cover crops on total phosphorus load in streams was evaluated by increasing and decreasing the percent of cover crop in catchments of the Midwest. The results of this evaluation are described in Roland and others (2022, https://doi.org/10.2489/jswc.2022.00162).

The U.S. Geological Survey’s (USGS) SPAtially Referenced Regression On Watershed attributes (SPARROW) model was used to aid in the interpretation of monitoring data and simulate nutrient loads in streams across the Midwest Region of the United States. SPARROW is a hybrid empirical/process-based mass balance model that can be used to estimate the major sources and environmental factors that affect the long-term supply, transport, and fate of contaminants in streams. The spatially explicit model structure is defined by a river reach network coupled with contributing catchments. The model is calibrated by statistically relating watershed sources and transport-related properties to monitoring-based water-quality load estimates. This USGS data release includes input, output, control, model coefficient and summary statistic files associated with 2012 SPARROW simulations of total phosphorus load in streams of the Midwest and represents a variation of a similar model described in Robertson and Saad (2019, https://doi.org/10.3133/sir20195114). This version of the model utilizes cover crops as a land-to-water delivery term in place of the phosphorus loss rate term included in the original model. The impacts of cover crops on total phosphorus load in streams was evaluated by increasing and decreasing the percent of cover crop in catchments of the Midwest. The results of this evaluation are described in Roland and others (2022, https://doi.org/10.2489/jswc.2022.00162).

To better understand the influence of human activities and natural processes on surface-water quality, the U.S. Geological Survey (USGS) developed the SPARROW (SPAtially Referenced Regressions On Watershed attributes) (Schwarz and others, 2006; Alexander and others, 2008) model. The framework is used to relate water-quality monitoring data to sources and watershed characteristics that affect the fate and transport of constituents to receiving surface-water bodies. The core of the model consists of using a nonlinear-regression equation to describe the non-conservative transport of contaminants from point and nonpoint sources on land to rivers, lakes and estuaries through the stream and river network. In North Carolina, excessive sediment loadings have contributed to the degradation of surface-water quality, and point and nonpoint nutrient sources are recognized as major contributors of this degradation in rivers, lakes and estuaries. The SPARROW model was configured for North Carolina to predict total nitrogen and total phosphorus loads in streams and to evaluate the relative importance and contributions of nitrogen and phosphorus sources and other landscape characteristics. The model time period is 1999 to 2014, centered at 2012. This data release includes model input (data1_vTNTP.zip), model predictions (predict_TN.zip and predict_TP.zip) that represent simulated stream load, model catchment shapefile (model_catchments.zip), and a brief methodology (Methodology_TNTP.pdf). See the 'Methodology_TNTP.pdf' file for model documentation.

This data release contains mean-annual total nitrogen (TN) loads predicted by a SPARROW model for individual stream and shoreline reaches in the Chesapeake watershed as defined by NHDPlus, a 1:100,000 scale representation of stream hydrography built upon the National Hydrography Dataset (NHD) (Horizon Systems, 2010). Also included are the input variables required to execute the model, including landscape characteristics, nutrient inputs to land, and calibration data from water quality monitoring stations. Further details on model construction and results are described in Ator (2011, https://doi.org/10.3133/sir20115167).

This data release contains mean-annual total nitrogen (TN) loads predicted by a SPARROW model for individual stream and shoreline reaches in the Chesapeake watershed as defined by NHDPlus, a 1:100,000 scale representation of stream hydrography built upon the National Hydrography Dataset (NHD) (Horizon Systems, 2010). Also included are the input variables required to execute the model, including landscape characteristics, nutrient inputs to land, and calibration data from water quality monitoring stations. Further details on model construction and results are described in Ator (2011, https://doi.org/10.3133/sir20115167).

The U.S. Geological Survey’s (USGS) SPAtially Referenced Regression On Watershed attributes (SPARROW) model was developed to aid in the interpretation of monitoring data and simulate water-quality conditions in streams across the Midcontinental Region of Canada and the Unites States. SPARROW is a hybrid empirical⁄process-based mass balance model that can be used to estimate the major sources and environmental factors that affect the long-term supply, transport, and fate of contaminants in streams. The spatially explicit model structure is defined by a river reach network coupled with contributing catchments. The model is calibrated by statistically relating watershed sources and transport-related properties to monitoring-based water-quality load estimates. This USGS data release, prepared in cooperation with the International Joint Commission and National Research Council Canada, includes output files representing 2002 SPARROW simulations of total nitrogen and total phosphorus in streams of the Midcontinent. Model calibration and results are described in Robertson and others (2019, https://doi.org/10.1111/1752-1688.12792). Geospatial data used for developing the Midcontinental SPARROW nutrient models are described in Vouk and others (2018, https://doi.org/10.4224/23004810). Model calibration targets used in the SPARROW models are described in Saad and others (2018, https://doi.org/10.3133/sir20185051).

The U.S. Geological Survey’s (USGS) SPAtially Referenced Regression On Watershed attributes (SPARROW) model was developed to aid in the interpretation of monitoring data and simulate water-quality conditions in streams across the Midcontinental Region of Canada and the Unites States. SPARROW is a hybrid empirical⁄process-based mass balance model that can be used to estimate the major sources and environmental factors that affect the long-term supply, transport, and fate of contaminants in streams. The spatially explicit model structure is defined by a river reach network coupled with contributing catchments. The model is calibrated by statistically relating watershed sources and transport-related properties to monitoring-based water-quality load estimates. This USGS data release, prepared in cooperation with the International Joint Commission and National Research Council Canada, includes output files representing 2002 SPARROW simulations of total nitrogen and total phosphorus in streams of the Midcontinent. Model calibration and results are described in Robertson and others (2019, https://doi.org/10.1111/1752-1688.12792). Geospatial data used for developing the Midcontinental SPARROW nutrient models are described in Vouk and others (2018, https://doi.org/10.4224/23004810). Model calibration targets used in the SPARROW models are described in Saad and others (2018, https://doi.org/10.3133/sir20185051).