Nitrogen and phosphorus losses from agricultural areas have impacted the water quality of downstream rivers, lakes, and oceans. As a result, investment in the adoption of agricultural best management practices (BMPs) has grown but assessments of their effectiveness at large spatial scales have been sparse. This study applies regional Spatially Referenced Regression On Watershed-attributes (SPARROW) models developed for the Midwest, Northeast, and Southeast regions of the United States to quantify regional effects of BMPs on nutrient losses from agricultural lands. These models were used because they account for specific BMPs in the prediction of instream nutrient loads. This data release accompanies the journal article "Quantifying regional effects of best management practices on nutrient losses from agricultural lands" (https:// doi:10.5066/pending), and it contains the input and output data for the modeling scenarios that were evaluated relative to the 2012 regional SPARROW models.

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.

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 streamflow and water-quality load estimates. Streamflow and load estimates considered for use in regional SPARROW model applications (2012 base year) are described in Saad and others, 2019 (https://dx.doi.org/10.3133/sir20195069). Load estimation methods described in this report include the Beale Ratio Estimator and Fluxmaster models. This USGS data release contains all of the input and output files necessary to reproduce the load estimates considered for inclusion in the 2012 regional SPARROW models. Data preparation for input to the load estimation models is also fully described in the above-mentioned report.

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.

This dataset consists of input and output datasets for estimating nitrogen (N) and phosphorus (P) balances for the Mississippi River Basin from 1950 to 2017. The N balance was calculated as the difference between inputs (fertilizer, manure, wastewater treatment facility effluent, N fixation, and atmospheric deposition) and outputs (crop uptake and removal in harvest and gaseous emissions to the atmosphere). The P balance was calculated as the difference between inputs (fertilizer, manure, wastewater treatment facility effluent, and weathering) minus outputs (specifically, P harvested and removed in crops, hay, and pasture).

This dataset consists of input and output datasets for estimating trends in river loads using the Weighted Regressions on Time Season and Discharge (WRTDS) model. The input datasets includes a discharge datafile and concentration datafiles for 6 water quality constituents: Total Phosphorus, Total Nitrogen, Nitrate plus Nitrite, Ammonium, Orthophosphate and Suspended Sediment. The period of record for the water quality data is from 1975 to 2017. The concentration and discharge data are for one site, the Mississippi River Outflow site, which is based on concentration data from USGS site 07373420, Mississippi River near St. Francisville, LA, and the discharge data are the sum of US Army Corps of Engineers Sites 01100 (Tarbert Landing) and 02600 (Old River Outflow) . Output dataset has the annual WRTDS estimates for time period 1975 to 2017 for all six constituents.

This dataset consists of input and output datasets for estimating trends in river loads using the Weighted Regressions on Time Season and Discharge (WRTDS) model. The input datasets includes a discharge datafile and concentration datafiles for 6 water quality constituents: Total Phosphorus, Total Nitrogen, Nitrate plus Nitrite, Ammonium, Orthophosphate and Suspended Sediment. The period of record for the water quality data is from 1975 to 2017. The concentration and discharge data are for one site, the Mississippi River Outflow site, which is based on concentration data from USGS site 07373420, Mississippi River near St. Francisville, LA, and the discharge data are the sum of US Army Corps of Engineers Sites 01100 (Tarbert Landing) and 02600 (Old River Outflow) . Output dataset has the annual WRTDS estimates for time period 1975 to 2017 for all six constituents.

This dataset consists of input and output datasets for estimating trends in river loads using the Weighted Regressions on Time Season and Discharge (WRTDS) model. The input datasets includes a discharge datafile and concentration datafiles for 6 water quality constituents: Total Phosphorus, Total Nitrogen, Nitrate plus Nitrite, Ammonium, Orthophosphate and Suspended Sediment. The period of record for the water quality data is from 1975 to 2017. The concentration and discharge data are for one site, the Mississippi River Outflow site, which is based on concentration data from USGS site 07373420, Mississippi River near St. Francisville, LA, and the discharge data are the sum of US Army Corps of Engineers Sites 01100 (Tarbert Landing) and 02600 (Old River Outflow) . Output dataset has the annual WRTDS estimates for time period 1975 to 2017 for all six constituents.