ABSTRACT:

The CAMELS-Chem dataset is a comprehensive collection of stream water chemistry data, atmospheric deposition data, and catchment attribute data for 516 minimally impacted headwater catchments across the continental United States. The dataset spans a period of 39 years, from 1980 through 2018, and includes 18 common stream water chemistry constituents, such as Al, Ca, Cl, Dissolved Organic Carbon, Total Organic Carbon, HCO3, K, Mg, Na, Total Dissolved Nitrogen, NO3, Dissolved Oxygen, pH, Si, SO4, and water temperature. Additionally, the dataset provides annual wet deposition loads for several key components. The dataset is based on the existing CAMELS dataset, which provides catchment attribute data such as topography, climate, land cover, soil, and geology. In CAMELS-Chem, this catchment attribute data is paired with atmospheric deposition data from the National Atmospheric Deposition Program and water chemistry data and instantaneous discharge from the US Geological Survey. The dataset also includes paired instantaneous and discharge measurements for all chemistry samples.
The catchment attribute data files used in the CAMELS-Chem dataset were downloaded from the CAMELS website (https://ral.ucar.edu/solutions/products/camels

ABSTRACT:

A reference to CZO Catalina-Jemez. A local copy will be created when updates are made to the datasets in the original CZO Catalina-Jemez.

ABSTRACT:

Rivers are integrators of hydrologic responses and catchment activity that are rich in information on watershed processes. Particularly, concentration-discharge (C-Q) relationships produce information on the controls of hydrogeochemical reactions along respective flow paths as a function of the hydrograph. Home to Apsáalooke/Crow people for generations, the Crow reservation is where the Little Bighorn River (LBHR) incises the landscape serving as the cultural bloodline and source of Apsáalooke livelihood. My initial longitudinal survey analyzing grab samples collected in December 2019 and June 2020 showed that the LBHR watershed is dominated by a Ca/Mg sulfate-bicarbonate solution and contains trace level concentrations of U-238, As-75, and up to 25 PFAS compounds. However, the extent to which pollutants may be stored and transported in association with discharge is unclear. Now, this study seeks to expand by identifying the C-Q relationship in the LBHR to understand the connection between seasonal river flows and pollutant flux. Using in situ multiparameter EXO2 sonde devices, high frequency sample collection, and chemical analyses together will contribute to the understanding of the hydrogeochemical behavior of the LBHR. This investigation will provide C-Q insights, foundation of surface water quality, determine those impacts on tribal water uses, and inform tribal water policy.

ABSTRACT:

Sensor time series datasets collected over nine years at a small forested research watershed, W-9, in Vermont, U.S.A. The datasets include (1) a univariate time series of stream stage measured at a 5- minute interval (from which stream discharge is computed), (2) two univariate time series of turbidity and fluorescent dissolved organic matter (FDOM), each measured at a 15-minute interval (using optical Turner Designs Cyclops sensors), and (3) a multi-variate time series of stream stage, turbidity, and FDOM together.

The sensors are positioned below the depth of ice formation and are operated year-round. The data estimate stream fluxes of dissolved and particulate organic carbon (DOC and POC). Turbidity in the water interferes with light transmission needed for the FDOM measurement, so FDOM values are corrected based on the turbidity values. Fluorescence is temperature sensitive, so FDOM values are also adjusted using concurrent water temperature measurements. The stage time series has 231,465 samples, and the turbidity and FDOM time series have 229,620 samples each.

These datasets are private until publicly released by the USGS, and may be available upon request and approval by the USGS.