The U.S. Geological Survey's (USGS) SPAtially Referenced Regressions On Watershed attributes (SPARROW version 2_10) model was used to aid in the interpretation of monitoring data and simulate streamflow and water-quality conditions in streams across the Pacific Region of 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 includes input and output files associated with 2012 SPARROW simulations of streamflow, total nitrogen, total phosphorus and suspended sediment load in streams of the Pacific region. Model construction, calibration and results are described in Wise (2019, https://doi.org/10.3133/sir20195112). First posted - January 6, 2020(available from author) Revised - June 08, 2020

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 Southwestern Region of 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 includes input and output files associated with 2012 SPARROW simulations of streamflow, total nitrogen, total phosphorus and suspended-sediment load in streams of the Southwestern region. Model construction, calibration and results are described in Wise, Anning, and Miller (2019, https://doi.org/10.3133/sir20195106.

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 Southwestern Region of 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 includes input and output files associated with 2012 SPARROW simulations of streamflow, total nitrogen, total phosphorus and suspended-sediment load in streams of the Southwestern region. Model construction, calibration and results are described in Wise, Anning, and Miller (2019, https://doi.org/10.3133/sir20195106.

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 Southeast 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 Southeast region. Model construction, calibration and results are described in Hoos and Roland (2019, https://doi.org/10.3133/sir20195135).

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 Southeast 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 Southeast region. Model construction, calibration and results are described in Hoos and Roland (2019, https://doi.org/10.3133/sir20195135).

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 Southeast 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 Southeast region. Model construction, calibration and results are described in Hoos and Roland (2019, https://doi.org/10.3133/sir20195135).

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 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 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.