This data release consists of the data used to develop SPAtially Referenced Regression On Watershed(SPARROW) attributes models for estimating loads of total phosphorus and total nitrogen in Tennessee streams. These data support the publication containing the Tennessee SPARROW models results (Hoos and others, 2019) and include model input used in the South Atlantic-Gulf Drainages and Tennessee River Basin (SAGT) nutrient SPARROW models (Hoos and McMahon, 2009; Garcia and others, 2011) as well as model input for river basins in Tennessee not included in the domain of the published SAGT SPARROW models. Also included in this data release are model coefficients, the software required to execute the Tennessee SPARROW models, and the model output for all streams in Tennessee. Each data set is listed in this data release with an accompanying file containing metadata for the dataset. For additional details, please refer to the README.txt file.

This data release consists of the data used to develop SPAtially Referenced Regression On Watershed(SPARROW) attributes models for estimating loads of total phosphorus and total nitrogen in Tennessee streams. These data support the publication containing the Tennessee SPARROW models results (Hoos and others, 2019) and include model input used in the South Atlantic-Gulf Drainages and Tennessee River Basin (SAGT) nutrient SPARROW models (Hoos and McMahon, 2009; Garcia and others, 2011) as well as model input for river basins in Tennessee not included in the domain of the published SAGT SPARROW models. Also included in this data release are model coefficients, the software required to execute the Tennessee SPARROW models, and the model output for all streams in Tennessee. Each data set is listed in this data release with an accompanying file containing metadata for the dataset. For additional details, please refer to the README.txt file.

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.

water quality loadings (nitrogen and phosphorous) from SWAT simulations on different crop expansion scenarios. This dataset is associated with the following publication: Chen, P., Y. Yuan, W. Li, S. LeDuc, T. Lark, X. Zhang, and C. Clark. Assessing the Impacts of Recent Crop Expansion on Water Quality in the Missouri River Basin Using the Soil and Water Assessment Tool. Journal of Advances in Modeling Earth Systems. John Wiley & Sons, Inc., Hoboken, NJ, USA, 13(6): e2020MS002284, (2021).

water quality loadings (nitrogen and phosphorous) from SWAT simulations on different crop expansion scenarios. This dataset is associated with the following publication: Chen, P., Y. Yuan, W. Li, S. LeDuc, T. Lark, X. Zhang, and C. Clark. Assessing the Impacts of Recent Crop Expansion on Water Quality in the Missouri River Basin Using the Soil and Water Assessment Tool. Journal of Advances in Modeling Earth Systems. John Wiley & Sons, Inc., Hoboken, NJ, USA, 13(6): e2020MS002284, (2021).

The primary data set consists of continuous water-quality data (temperature, specific conductance, pH, dissolved oxygen, turbidity, nitrate plus nitrite, and streamflow) from in-situ equipment, and discrete water-quality samples (total nitrogen, total phosphorus, suspended sediment concentration, and suspended sediment sieve diameter) collected during site visits at the USGS streamgage Iroquois River near Foresman, Indiana, April 7, 2015 to July 19, 2018. These continuous and discrete measurements were used to develop regression models which may be used to compute concentrations and loads of total nitrogen and total phosphorus. The secondary data set consists of daily streamflow, daily nitrate, daily turbidity and daily specific conductance values collected continuously by in-situ monitors at Iroquois River near Foresman, Indiana March 20, 2015 to July 19, 2018 which serve as input explanatory variables for the developed regression models to compute total nitrogen and total phosphorus at Iroquois River near Foresman. The tertiary data set for March 20, 2015 to July 19, 2018 is the output data set that was developed by application of the regression models and includes the computed daily mean total nitrogen and total phosphorus concentrations (concentration, upper 95-percent prediction interval, and lower 95-percent prediction interval) and daily mean total nitrogen and total phosphorus loads (load, upper 95-percent prediction interval, and lower 95-percent prediction interval).

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.

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 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.

This data release contains seasonal source-specific estimates of total nitrogen (TN) and total phosphorus (TP) loads from watersheds draining to Washing water of the Salish Sea (Puget Sound region,12,314 e2NHDPlusV2 reaches plus 2 added transfer reaches) using a dynamic SPARROW (Spatially Referenced Regressions on Watershed attributes) model. Input data, output predictions, model control files, and model source code are provided to fully reproduce results. The modeled period was from January 2005 through December 2020 in seasonal time steps, or 64 periods, and the following seasonal definitions were applied: winter includes January, February, and March; spring includes April, May, and June; summer includes July, August, and September; and fall includes October, November, and December.