The total concentration of dissolved constituents in water is routinely quantified by measurements of salinity or total dissolved solids (TDS). However, salinity and TDS are operationally defined by their analytical methods and are not equivalent for most waters. Furthermore, multiple methods are available to determine salinity and TDS, and these methods have inherent differences. TDS is defined as the mass of anhydrous residue remaining in a sample vessel after evaporation and subsequent oven drying at a defined temperature. Salinity is a measure of the mass of dissolved salts in a given mass of solution. In addition, there are approaches that quantify the total solute (TS) concentration, including gases. PHREECI was utilized to rapidly calculate salinity, TDS, and TS of 6,391 surface water samples from 523 sites using eight different approaches. PHREEQCI is a widely used geochemical computer program that can be used to calculate chemical speciation and specific conductance of a natural water sample from its chemical composition (Charlton and Parkhurst, 2002; Parkhurst and Appelo, 1999; McCleskey, 2018). The PHREECI input files and water-quality data utilized in this study are presented here. PHREEQCI can be obtained at https://www.usgs.gov/software/phreeqc-version-3 File information: PHREEQCI_Salinity.txt contains a script used to calculate salinity, TDS, and TS using eight different approaches. The file contains a script that generates a text file containing all the calculated parameters (Salinity.out) including calculated specific conductance (McCleskey and others, 2012; McCleskey, 2018), salinity (4 methods), TDS (1 method), and TS (1 method), and the Practical Salinity Scale (2methods). In addition, a QAQC graph is created (McCleskey, 2018). Notes for creating input files and running the PHREEQCI input script: (1) The field measured specific conductance (in microSiemens per centimeter at 25 °C) must be listed under the “Description” character field because PHREEQCI does not have a “Defined Heading” for specific conductance in the SOLUTION_SPREAD block. (2) The Bounds.TSV file must be in the same file folder as the input file for the QAQC bounds to be included on the specific conductance imbalance versus charge balance graph. (3) PHREEQCI was run using the wateq4f.dat thermodynamic database. Bounds.TSV is a tab separated file used to create the QAQC bounds in the specific conductance imbalance versus charge balance graph (McCleskey and others, 2012a). The file must be in the same file folder as the input file for the QAQC bounds to be included on the specific conductance imbalance versus charge balance graph. The bounds are set at ±15% for both specific conductance imbalance and charge balance. PHREEQCI_SalinityInput.pqi is an example PHREEQCI input file. The solutions are 6,391 surface water samples where the water-quality data were obtained from the Water Quality Portal (https://www.waterqualitydata.us/). PHREEQCI_SalinityOutput.pqo is the PHREEQCI output file created using PHREEQCI_SalinityInput.pqi. Salinity.txt is a text file that is generated by PHREEQCI that contains the calculated electrical conductivity (EC_Calc); the specific conductance using the non-linear (SC_nlf) temperature compensation factors (McCleskey, 2018); milliequivalents (meq) of Ca, Mg Na, K Cl, SO4, NO3, F, Al, Sr, Ba, Fe, Mn, Zn Br, Li, and inorganic carbon (C); total meq of the cations (Cat) and anions (An); the percent of the of the total meq due to Ca, Mg Na, K Cl, SO4, NO3, F, Al, Sr, Ba, Fe, Mn, Zn, Br, Li, and C; water type (WT) based on major ions (0 = mixed, 1 = Cl rich, 2 = carbonate rich, 3 = CaSO4 rich, and 4 = Na2SO4 rich), salinity (S) in mg/L based on a specific conductance-water type method (S_SCWT_mg/L); S in mg/L based on speciated solute concentrations (S_spec_mg/L); S in mg/L based on unspeciated solute concentrations (S_unspec_mg/L); S in mg/L based on speciated silica (S_Si_mg/L); total solutes, including CO2(g), in mg/L

This data release contains total dissolved solids (TDS) concentrations and specific conductance (SC) measurements collected at surface-water monitoring locations and groundwater monitoring wells within the Upper Colorado River Basin (UCRB) between 1894 and 2022. Discrete TDS and SC results were obtained from the Water Quality Portal (WQP). Continuous SC monitoring results were obtained from the USGS National Water Information System (NWIS). The data set includes 127,294 TDS results that were collected at 12,339 sites between 1900 and 2022, and 705,918 SC results that were collected at 19,630 sites between 1894 and 2022. The SC results represented 244,784 discrete measurements at 19,625 sites and 461,134 mean daily values from continuous monitoring at 193 sites. The data retrieved from the WQP were harmonized to create a standardized and readily usable dataset. The harmonization process included the synthesis of parameter names and fractions, the reconciliation of remarks and other data qualifiers, the resolution of duplicate records, and basic checks of the data quality. The harmonized results at 230 sites were selected for additional data processing because those sites were potential calibration targets for TDS watershed modeling for the UCRB using the USGS Spatially Referenced Regression on Watershed attributes (SPARROW) model. The 230 sites met the minimum criteria for the number and seasonal distribution of samples, the length of the sampling period, and the amount of overlap with the streamflow record at a nearby gage. The measured TDS concentrations at those sites were supplemented with estimated TDS concentrations that were determined from relations between measured TDS and SC results within the UCRB. A site-specific regression of TDS on SC was used to estimate TDS from SC at 143 sites, while a regional conversion factor between TDS and SC was used to estimate TDS from SC at 87 sites. The final TDS data for the 230 sites included 50,003 measured values from the WQP, 378,147 values estimated using the equation from a site-specific regression of TDS on SC (with 350,840 based on mean daily SC values), and 30,880 values estimated using a regional median ratio between TDS and SC.

Groundwater salinity impacts water quality and limits usability for drinking, irrigation, and industrial purposes where salinity is high. Salinity is a measure of the mass of dissolved salts in a given volume of solution and is closely related to the concentration of Total Dissolved Solids (TDS) as well as the ability of water to conduct electricity, or specific conductance (SC) (McCleskey and others, 2025). The relationship between salinity, TDS, and SC are controlled by the major ion composition of groundwater, or hydrochemical facies. Hydrochemical facies represent the chemical reactions between groundwater and the surrounding geology and correlate with depth (Stackelberg and others, 2025). Thus, understanding the hydrochemical facies and salinity of groundwater is crucial for effective water resource management. This data release documents groundwater data and calculations (scripted workflow written in Python) that uses the hydrochemical facies of groundwater, in conjunction with measurements of specific conductance, to accurately estimate the salinity of groundwater for the continental United States (CONUS). Additionally, TDS can be calculated several ways. TDS can be measured directly following U.S. Geological Survey (USGS) residual on evaporation method 70300 or by utilizing a summation of constituents (TDSsoc) USGS method 70301. The TDSsoc method sums the concentrations, in milligrams per liter (mg/L) for the following major constituents: Ca, Mg, Na, K, Cl, SO4, NO3, CO3, and SiO2. The data sources include dissolved solids data from a brackish groundwater assessment (Qi and others, 2017), produced waters geochemical data, (Blondes and others, 2023), state groundwater-quality data from the Safe Drinking Water Information System (SDWIS) contained within the workflow, and preprocessed groundwater-quality data retrieved from the National Water Quality Portal (WQP), also contained within the workflow. The files contained herein document the scripted Python workflow to retrieve necessary water-quality datasets from the internet, process the data, calculate alkalinity, and assign water type categories. Outputs from this workflow are documented in the Child Item titled 2) Results of salinity calculations and assigned water type category - ScienceBase-Catalog.

The goal of this study was to develop a suite of inter-related water quality monitoring approaches capable of modeling and estimating the spatial and temporal gradients of particulate and dissolved total mercury (THg) concentration, and particulate and dissolved methyl mercury (MeHg), concentration, in surface waters across the Sacramento / San Joaquin River Delta (SSJRD). This suite of monitoring approaches included: a) data collection at fixed continuous monitoring stations (CMS) outfitted with in-situ sensors, b) spatial mapping using boat-mounted flow-through sensors, and c) satellite-based remote sensing. The focus of this specific Child Page is to present laboratory measured spectral data associated with discrete surface water samples collected as part of both the CMS and boat mapping sampling efforts. All laboratory-based measurement presented herein were conducted by the U.S. Geological Survey (USGS) Organic Matter Research Laboratory (OMRL) in Sacramento, Calif. The machine-readable (comma separated value, *.csv) files presented herein include spectral data collected using two different instruments: 1) Laboratory-based absorbance and fluorescence measurements on filtered water using an Aqualog (Hansen and others, 2018) and 2) Laboratory-based absorption measurements using a Varian Cary spectrophotometer on particulate samples collected on glass fiber filters (Kishino and others, 1985; Roesler, 1998). The reported spectral data includes: 1) fluorescence intensities across a wide range of excitation (240 to 800 nm) and emission (250 to 800 nm) wavelengths expressed as an excitation-emission matrix (EEM), 2) absorbance of light (from 239 nm to 800 nm) due to dissolved and colloidal substances, and 3) absorption coefficients (from 350 nm to 715 nm) for particulates using the quantitative filter technique (QFT).

Measurements of Total Dissolved Solids (TDS) collected at Delta Mendota Canal At Bass Avenue. Currently collected twice a year, previously collected quarterly. Access further information for this data set by contacting Bureau of Reclamation, California-Great Basin Region, Environmental Affairs Division (CGB-157). See ResultAttributes for STAFF_GAUGE, SMPL_DEPTH, SMPL_CATEGORY_NAME, METHOD_CODE, RESULT_RL, RESULT_RL-UNIT_STD_NAME, RESULT_MDL, RESULT_MDL-UNIT_STD_NAME, USBR_QA_SUBTYPE_NAME, USBR_QULFR_DESCRIPTION. STAFF_GAUGE is the water height in decimal feet measured by gauge (e.g., 15.2). SMPL_DEPTH is the vertical depth at which sample is collected (e.g., 0 - 15 cm). For water samples: depth below water/air interface. For sediment and soil samples: depth below water/solid or air/solid interface. SMPL_CATEGORY_NAME is the category type of sample (e.g., Composite). METHOD_CODE is the name of method used to obtain result (e.g., EPA 200.8). RESULT_RL is the result reporting limit (accounting for dilution) (e.g., 0.02). RESULT_RL-UNIT_STD_NAME is the unit associated with RESULT_RL (e.g., mg/L). RESULT_MDL is the result method detection limit (e.g., 0.007). RESULT_MDL-UNIT_STD_NAME is the unit associated with RESULT_MDL (e.g., mg/L). USBR_QA_SUBTYPE_NAME is the quality control type of the sample (e.g., USBR_BLANK_SPIKE). USBR_QULFR_DESCRIPTION is the quality assurance description (if any) (e.g., Result may have a high bias.).

The dataset consists of two spreadsheets of data for water samples of varying salinity. One spreadsheet contains measured concentrations of nutrients in filtered water samples that were corrected for salinity effects when necessary, and measured concentrations of nutrients spiked into environmental samples or blank water that were corrected for salinity effects when necessary. The second spreadsheet contains measured concentrations of ammonia and silica in filtered water samples without the salinity correction applied, and measured concentrations of ammonia and silica spiked into environmental samples or blank water without the salinity correction applied.

These data were compiled to quantify the role of Lake Powell in modulating salinity and reducing overall salt flux from the Upper Colorado River Basin downstream. In addition, these data were used to infer summertime calcite precipitation in Lake Powell (the major proposed sink for salt within the system). The Lake Powell Calcium Magnesium data contains summertime surface water calcium and magnesium concentrations along three transects that span the two major inflows to Lake Powell and the region of Lake Powell closest to the dam. The Modeled Salinity data was used to compare measured total dissolved solid concentrations at Lees Ferry to the instantaneous flow-weighted concentration of total dissolved solid entering the reservoir at any given time. The NWIS-Weighted Inflow Salinity data was used to compare total dissolved salt concentrations made by the Lake Powell Water Quality Monitoring Program to those inferred from upstream gaged sites contained in the National Water Information System. The WRTDS-Output Mass Balance data presents annual mass balance estimates for total dissolved solids, sulfate, bicarbonate, calcium, and chloride in Lake Powell including raw results from Weighted Regressions on Time, Discharge and Season (WRTDS) modeling and estimates of changes in annual reservoir storage.