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Fairfax County Monitoring Network 2007 - 2022: Annual Loads, Regression Models, and Ancillary Data

March 18, 2025
Nitrogen (N), phosphorus (P), and suspended sediment (SS) loads in Fairfax County, Virginia streams were calculated using monitoring data from 5 intensively monitored watersheds for the period from water year (October - September) 2008 through 2022. Nutrient (N and P) and SS loads were computed using a surrogate (multiple-linear regression) approach with lab analyzed N, P, and SS samples as the response variable and basic water-quality parameters (e.g. turbidity, specific conductance, water temperature, pH), streamflow, a baseflow separation Boolean term, and time and seasonal terms as predictor (surrogate) variables. Load results represent the mass of N, P, and SS exported from each of the monitored Fairfax County watersheds. Calibration data, high-frequency surrogate timeseries, model coefficients, and model diagnostics are provided for each unique station-constituent model. Annual, monthly, and sub-hourly estimates of load are provided for the following constituents: SS, total N, total P, total dissolved N, total dissolved P, total particulate N, total particulate P, nitrate plus nitrite, total Kjeldahl nitrogen, dissolved total Kjeldahl nitrogen, and orthophosphate. Streamflow and climate are important drivers of water-quality conditions; therefore, a dataset is provided describing stream flashiness, rainfall, and air temperature. Concentrations of N, P, and SS collected from 20 monitored streams also are provided.
 
This data release contains 10 comma-delimited (.csv) files with corresponding data dictionary files (.csv) and one file containing R code to generate 15-minute interval estimates of load.
• Annual_Loads.csv contains annual load, yield, streamflow volume, and streamflow yield in imperial and SI units
• Monthly_Loads.csv contains monthly load, yield, streamflow volume and streamflow yield in imperial and SI units
• UV_Loads_Concentrations contains 15-minute interval estimates of concentration and load in imperial and SI units.
• Annual_Loads_Flow.csv contains annual load and yield apportioned by the mass transported during either baseflow or stormflow hydrologic conditions, in imperial and SI units
• Concentrations.csv contains nutrient and suspended sediment concentrations from 20 monitoring stations collected each month from 2008 through 2022.
• Calibration.csv contains all data used in the calibration of surrogate regression models for the computation of N, P, and concentration and load. Each station-constituent model can be executed with this file and the FFX_loadest.R code.
• Surrogate.csv contains 15-minute interval measures of streamflow, water-quality parameters, and a Boolean baseflow separation identifier “BASE.” These data were used to compute the 15-minute interval measurements of N, P, and SS concentration and load using the models provided in the FFX_loadest.R file and provided in the UV_Loads_Concentrations.csv.
• Coefficients.csv contains model coefficients for each station-constituent specific load model.
• Diagnostics.csv contains diagnostics to evaluate the performance of each individual constituent-station model. Diagnostics include residuals, influence, leverage, actual and predicted values, and each model bias correction factor for retransforming from log to linear units.
• Climate.csv contains data describing a suite of mean annual hydrologic and climate metrics
• FFX_Loadest.R contains the R code to run each model using the Calibration.csv and Surrogate.csv files.
For each file entity and attributes are described in data.dictionary.csv that shares the same name.
 
A README text file is also attached, which contains descriptions of each data table and supplementary information. 
Publication Year 2025
Title Fairfax County Monitoring Network 2007 - 2022: Annual Loads, Regression Models, and Ancillary Data
DOI 10.5066/P1NTROI6
Authors Aaron J Porter
Product Type Data Release
Record Source USGS Asset Identifier Service (AIS)
USGS Organization Virginia and West Virginia Water Science Center
Rights This work is marked with CC0 1.0 Universal
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