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 United States Geological Survey’s (USGS) SPAtially Referenced Regressions On Watershed attributes (SPARROW) model was developed to aid in the interpretation of monitoring data and simulate water-quality conditions in streams across large spatial scales. 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. Load estimates used in recent Midcontinent SPARROW model applications (2002 base year) are described in Saad and others, 2018 (https://doi.org/10.3133/sir20185051). Load estimation methods described in this report include the Beale Ratio Estimator and Fluxmaster models. This USGS data release, prepared in cooperation with the International Joint Commission, contains all of the input and output files necessary to reproduce the load estimates considered for inclusion in the 2002 Midcontinent SPARROW models. Data preparation for input to the load estimation models is also fully described in the above-mentioned report.

The United States Geological Survey’s (USGS) SPAtially Referenced Regressions On Watershed attributes (SPARROW) model was developed to aid in the interpretation of monitoring data and simulate water-quality conditions in streams across large spatial scales. 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. Load estimates used in recent Midcontinent SPARROW model applications (2002 base year) are described in Saad and others, 2018 (https://doi.org/10.3133/sir20185051). Load estimation methods described in this report include the Beale Ratio Estimator and Fluxmaster models. This USGS data release, prepared in cooperation with the International Joint Commission, contains all of the input and output files necessary to reproduce the load estimates considered for inclusion in the 2002 Midcontinent SPARROW models. Data preparation for input to the load estimation models is also fully described in the above-mentioned report.

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.

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.

The existing long-term Total Nitrogen (TN) and Total Phosphorus (TP) steady-state models, originally developed on a regional scale for the Pacific Region of the United States (Wise, 2019), were utilized to estimate TN and TP loads for the Clear Lake watershed. To support this analysis, input data for the Pacific Region model were updated to reflect climate, land use, and agricultural activities for the 2016-2024 period. Following these updates, the models were run in prediction mode, using model coefficients from the 2012 Pacific Region TN and TP SPARROW models. Model data set updates included incorporating the 2019 National Land Cover Data (NLCD), 2017 county-level applied agricultural fertilizer and manure data, updated streamflow data representing 2016-2024 conditions, and adjustments for areas affected by the 2017 and 2018 wildfires in the Clear Lake watershed. The revised Pacific Region SPARROW models were then run in prediction mode, and the resulting TN and TP load estimates were compared to those from the 2012 Pacific Region model to assess changes in TN and TP loads relative to historical conditions. Initially developed in the Statistical Analysis System (SAS), the Pacific Region SPARROW models were converted to R (RSPARROW) for this analysis. RSPARROW is available at https://doi.org/10.5066/P9G64CAN.

Degradation of water quality from nutrient pollution continues to be a challenge for water resource managers. The development of effective management strategies begins with tools that facilitate an understanding of nutrient sources and transport. SPARROW (SPAtially Referenced Regression On Watershed attributes) is a spatially explicit model platform that correlates water-quality observations with sources and transport-related properties of the watershed to predict constituent loads for streams and catchments. Several large-scale regional SPARROW models have been previously developed by the USGS that predict nutrient loads for large portions of the U.S. (see https://www.usgs.gov/mission-areas/water-resources/science/sparrow-mappers). However, relatively smaller-scaled and more focused, state-based SPARROW models may also be of particular benefit to state and local resource managers related to assessment of total maximum daily loads, nutrient criteria, and prioritizing nutrient reduction strategies. For this study, the USGS, in cooperation with Mississippi Department of Environmental Quality (MDEQ), developed state-based SPARROW models for Mississippi using RSPARROW software (Alexander and Gorman Sanisaca, 2019). Mississippi SPARROW models were developed by utilizing published input datasets of nutrients sources and delivery variables compiled from the Midwest (Saad and Robertson, 2020) and Southeast regional SPARROW models (Roland and Hoos, 2020). Source and delivery variables included land characteristics (urban coverage), instream and reservoir attenuation, and various sources of nitrogen and phosphorus (atmospheric deposition, point-sources, fertilizer/manure application, geologic material, etc.). Updated load estimates were calculated using streamflow and nutrient data for the period of 2005 through 2020 from USGS streamgages throughout Mississippi and portions of Alabama, Georgia, Tennessee, North Carolina, and Virginia. Load estimates were used to calibrate total nitrogen and total phosphorus SPARROW models for the base year of 2018. This data release includes the raw input and output files used in the development of Mississippi SPARROW models. Please note: the spatial footprint of these datasets includes calibration sites, stream reaches, and catchments that extend outside of the state of Mississippi; however, the associated report by Roland and Gain (2025) and web-based mapper (https://sparrow.wim.usgs.gov/sparrow-mississippi/) only include model results for stream reaches and catchments that are within or drain into the state of Mississippi. Included datasets: ms_sparrow_data1.csv (model input data file "data1") ms_sparrow_catchments.zip (catchment shapefile) ms_sparrow_reaches.zip (stream reach shapefile) ms_sparrow_output_TN.csv (total nitrogen model results - predicted loads and yields) ms_sparrow_output_TP.csv (total phosphorus model results - predicted loads and yields) Cited works: Alexander, Richard B., and Gorman Sanisaca, Lillian. (2019). RSPARROW: An R system for SPARROW modeling. U.S. Geological Survey Software release. DOI: https://doi.org/10.5066/P9UAZ6FO. Roland, V.L., II, and Hoos, A.B., 2020, SPARROW model inputs and simulated streamflow, nutrient and suspended-sediment loads in streams of the Southeastern United States, 2012 Base Year: U.S. Geological Survey data release, https://doi.org/10.5066/P9A682GW. Saad, D.A., and Robertson, D.M., 2020, SPARROW model inputs and simulated streamflow, nutrient and suspended-sediment loads in streams of the Midwestern United States, 2012 Base Year: U.S. Geological Survey data release, https://doi.org/10.5066/P93QMXC9.

Degradation of water quality from nutrient pollution continues to be a challenge for water resource managers. The development of effective management strategies begins with tools that facilitate an understanding of nutrient sources and transport. SPARROW (SPAtially Referenced Regression On Watershed attributes) is a spatially explicit model platform that correlates water-quality observations with sources and transport-related properties of the watershed to predict constituent loads for streams and catchments. Several large-scale regional SPARROW models have been previously developed by the USGS that predict nutrient loads for large portions of the U.S. (see https://www.usgs.gov/mission-areas/water-resources/science/sparrow-mappers). However, relatively smaller-scaled and more focused, state-based SPARROW models may also be of particular benefit to state and local resource managers related to assessment of total maximum daily loads, nutrient criteria, and prioritizing nutrient reduction strategies. For this study, the USGS, in cooperation with Mississippi Department of Environmental Quality (MDEQ), developed state-based SPARROW models for Mississippi using RSPARROW software (Alexander and Gorman Sanisaca, 2019). Mississippi SPARROW models were developed by utilizing published input datasets of nutrients sources and delivery variables compiled from the Midwest (Saad and Robertson, 2020) and Southeast regional SPARROW models (Roland and Hoos, 2020). Source and delivery variables included land characteristics (urban coverage), instream and reservoir attenuation, and various sources of nitrogen and phosphorus (atmospheric deposition, point-sources, fertilizer/manure application, geologic material, etc.). Updated load estimates were calculated using streamflow and nutrient data for the period of 2005 through 2020 from USGS streamgages throughout Mississippi and portions of Alabama, Georgia, Tennessee, North Carolina, and Virginia. Load estimates were used to calibrate total nitrogen and total phosphorus SPARROW models for the base year of 2018. This data release includes the raw input and output files used in the development of Mississippi SPARROW models. Please note: the spatial footprint of these datasets includes calibration sites, stream reaches, and catchments that extend outside of the state of Mississippi; however, the associated report by Roland and Gain (2025) and web-based mapper (https://sparrow.wim.usgs.gov/sparrow-mississippi/) only include model results for stream reaches and catchments that are within or drain into the state of Mississippi. Included datasets: ms_sparrow_data1.csv (model input data file "data1") ms_sparrow_catchments.zip (catchment shapefile) ms_sparrow_reaches.zip (stream reach shapefile) ms_sparrow_output_TN.csv (total nitrogen model results - predicted loads and yields) ms_sparrow_output_TP.csv (total phosphorus model results - predicted loads and yields) Cited works: Alexander, Richard B., and Gorman Sanisaca, Lillian. (2019). RSPARROW: An R system for SPARROW modeling. U.S. Geological Survey Software release. DOI: https://doi.org/10.5066/P9UAZ6FO. Roland, V.L., II, and Hoos, A.B., 2020, SPARROW model inputs and simulated streamflow, nutrient and suspended-sediment loads in streams of the Southeastern United States, 2012 Base Year: U.S. Geological Survey data release, https://doi.org/10.5066/P9A682GW. Saad, D.A., and Robertson, D.M., 2020, SPARROW model inputs and simulated streamflow, nutrient and suspended-sediment loads in streams of the Midwestern United States, 2012 Base Year: U.S. Geological Survey data release, https://doi.org/10.5066/P93QMXC9.

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 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 and output files associated with 2012 SPARROW simulations of streamflow, total nitrogen, total phosphorus and suspended-sediment load in streams of the Midwest. Model construction, calibration and results are described in Robertson and Saad (2019, https://doi.org/10.3133/sir20195114).

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 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 and output files associated with 2012 SPARROW simulations of streamflow, total nitrogen, total phosphorus and suspended-sediment load in streams of the Midwest. Model construction, calibration and results are described in Robertson and Saad (2019, https://doi.org/10.3133/sir20195114).