Total Nitrogen (TN) rloadest models were developed to compute TN flux at School Branch at three USGS monitoring stations: School Branch at Maloney Road near Brownsburg, Indiana (03353415); School Branch at CR750N at Brownsburg, Indiana (03353420); and School Branch at Noble Drive at Brownsburg, Indiana (03353430). Frequently, TN models developed in rloadest regress discrete TN concentrations against concurrent daily mean streamflow values. However, due to the flashy nature of streamflows on School Branch, the developed TN models regressed discrete TN concentrations against the closest unit-value (15-minute) streamflows. Once TN flux models were calibrated, unit-value streamflows were used to estimate average TN fluxes for selected time periods, which in turn were used to compute loads. This data release contains calibration data sets and R code used to create regression models for estimating daily flux of total nitrogen and summary information for the models for each site.

The primary data sets consist 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 School Branch at CR750N at Brownsburg, Indiana, November 17, 2015 to February 6, 2019. The continuous and discrete measurements were used to develop regression models which may be used to compute concentrations and loads of suspended sediment, total nitrogen, and total phosphorus. The secondary data sets consist of daily streamflow, daily turbidity, daily specific conductance, and daily nitrate plus nitrite values collected continuously by in-situ monitors at School Branch at CR750N at Brownsburg, Indiana June 23, 2015 to February 6, 2019 which serve as input explanatory variables for the developed regression models to compute suspended sediment, total nitrogen, and total phosphorus at School Branch at CR750N at Brownsburg. The tertiary data sets for June 23, 2015 to February 6, 2019 are the output data sets that were developed by application of each regression model and include the computed daily mean constituent concentrations (with upper 95-percent prediction interval, and lower 95-percent prediction interval) and daily mean constituent loads (with upper 95-percent prediction interval, and lower 95-percent prediction interval).

The primary data sets consist 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 School Branch at CR750N at Brownsburg, Indiana, November 17, 2015 to February 6, 2019. The continuous and discrete measurements were used to develop regression models which may be used to compute concentrations and loads of suspended sediment, total nitrogen, and total phosphorus. The secondary data sets consist of daily streamflow, daily turbidity, daily specific conductance, and daily nitrate plus nitrite values collected continuously by in-situ monitors at School Branch at CR750N at Brownsburg, Indiana June 23, 2015 to February 6, 2019 which serve as input explanatory variables for the developed regression models to compute suspended sediment, total nitrogen, and total phosphorus at School Branch at CR750N at Brownsburg. The tertiary data sets for June 23, 2015 to February 6, 2019 are the output data sets that were developed by application of each regression model and include the computed daily mean constituent concentrations (with upper 95-percent prediction interval, and lower 95-percent prediction interval) and daily mean constituent loads (with upper 95-percent prediction interval, and lower 95-percent prediction interval).

This U.S. Geological Survey data release presents tabular daily data on nitrate plus nitrite nitrogen and total nitrogen loads for the Connecticut River at Middle Haddam, Connecticut, from December 6, 2008, to September 30, 2014. The data release contains total nitrogen concentration estimates at 15-minute intervals from December 2011 to September 2014. The data release also includes tabular information on the total nitrogen loads from the Connecticut River at Thompsonville, Connecticut, from October 1, 2008, to September 30, 2014. Load data for each site and constituent include the daily loads and upper and lower 95-percent prediction intervals (where applicable); the method used in the load calculation for each site is also included in this data release.

This U.S. Geological Survey data release presents tabular daily data on nitrate plus nitrite nitrogen and total nitrogen loads for the Connecticut River at Middle Haddam, Connecticut, from December 6, 2008, to September 30, 2014. The data release contains total nitrogen concentration estimates at 15-minute intervals from December 2011 to September 2014. The data release also includes tabular information on the total nitrogen loads from the Connecticut River at Thompsonville, Connecticut, from October 1, 2008, to September 30, 2014. Load data for each site and constituent include the daily loads and upper and lower 95-percent prediction intervals (where applicable); the method used in the load calculation for each site is also included in this data release.

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 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).

As part of the Great Lakes Restoration Initiative, the U.S. Department of Agriculture, Natural Resources Conservation Service; U.S. Environmental Protection Agency; and the U.S. Geological Survey (USGS) have partnered to evaluate agricultural conservation practices focused on nutrient management. Monitoring methods allow for rapid assessment of water-quality changes in response to conservation efforts by focusing on subsurface-tile drainage and direct surface runoff from fields. Estimated daily loads presented within this dataset are from five surface-runoff monitoring stations (USGS station identification number 441624088045601, approximated drainage area of 4.17 hectare; USGS station identification number 441546088082001, approximated drainage area of 11.0 hectare; USGS station identification number 441520880845001, approximated drainage area of 3.20 hectare; USGS station identification number 442119088085501, approximated drainage area of 1.94 hectare; USGS station identification number 442114088085701, approximated drainage area of 10.4 hectare) and one tile-runoff monitoring station (USGS station identification number 441520088045002; approximated drainage area of 2.02 hectare). The monitored fields are row-crop parcels planted in a biennial corn-soybean crop rotation. Best-management practices were applied during part of the monitoring period. Note: Daily load computations are presented directly as they were output from the GCLAS program and do not represent the degree of accuracy of the estimates.

As part of the Great Lakes Restoration Initiative, the U.S. Department of Agriculture, Natural Resources Conservation Service; U.S. Environmental Protection Agency; and the U.S. Geological Survey (USGS) have partnered to evaluate agricultural conservation practices focused on nutrient management. Monitoring methods allow for rapid assessment of water-quality changes in response to conservation efforts by focusing on subsurface-tile drainage and direct surface runoff from fields. Estimated daily loads presented within this dataset are from five surface-runoff monitoring stations (USGS station identification number 441624088045601, approximated drainage area of 4.17 hectare; USGS station identification number 441546088082001, approximated drainage area of 11.0 hectare; USGS station identification number 441520880845001, approximated drainage area of 3.20 hectare; USGS station identification number 442119088085501, approximated drainage area of 1.94 hectare; USGS station identification number 442114088085701, approximated drainage area of 10.4 hectare) and one tile-runoff monitoring station (USGS station identification number 441520088045002; approximated drainage area of 2.02 hectare). The monitored fields are row-crop parcels planted in a biennial corn-soybean crop rotation. Best-management practices were applied during part of the monitoring period. Note: Daily load computations are presented directly as they were output from the GCLAS program and do not represent the degree of accuracy of the estimates.

This data release contains data sets and R code used to create regression models for estimating daily flux of suspended sediment, total nitrogen, and total phosphorus at the Kankakee River at Shelby, IN (05518000) streamgage. The models were developed using discrete water-quality data and concurrent daily streamflow data measured/determined at the streamgage for the period January 2016 through May 2018. Also, included is a daily streamflow input data set and daily flux output data sets that were developed by application of the regression models. The USGS rloadest package was used to develop the regression models and flux estimates. Summary information for the models for each constituent are included in this data release.