CAMELS-Chem: augmenting CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) with atmospheric and stream water chemistry data

CAMELS-Chem: augmenting CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) with atmospheric and stream water chemistry data

Large sample datasets are transforming the catchment sciences, but there are few off-the-shelf stream water chemistry datasets with complementary atmospheric deposition, streamflow, meteorology, and catchment physiographic attributes. The existing CAMELS (Catchment Attributes and Meteorology for Lar...

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Bibliographic Details
Published in:Hydrology and earth system sciences Vol. 28; no. 3; pp. 611 - 630
Main Authors: Sterle, Gary, Perdrial, Julia, Kincaid, Dustin W, Underwood, Kristen L, Rizzo, Donna M, Haq, Ijaz Ul, Li, Li, Lee, Byung Suk, Adler, Thomas, Wen, Hang, Middleton, Helena, Harpold, Adrian A
Format: Journal Article
Language:English
Published: Katlenburg-Lindau Copernicus GmbH 13-02-2024
Copernicus Publications
Subjects:
Analysis
Archives & records
Calcium
Camelids
Camels
Catchment area
Catchments
Chemistry
Constituents
Datasets
Deposition
Dissolved organic carbon
Dissolved oxygen
Geological surveys
Geology
Hydrology
Hypotheses
Information systems
Interdisciplinary aspects
Land cover
Magnesium
Meteorology
Organic carbon
Oxygen
Parameter estimation
Relational data bases
Rivers
Sample size
Stream discharge
Stream flow
Stream water
Streamflow
Topography
Total organic carbon
Trend analysis
Water
Water chemistry
Water discharge
Water quality
Water temperature
Watersheds
United States > US
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Description
Summary:Large sample datasets are transforming the catchment sciences, but there are few off-the-shelf stream water chemistry datasets with complementary atmospheric deposition, streamflow, meteorology, and catchment physiographic attributes. The existing CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) dataset includes data on topography, climate, streamflow, land cover, soil, and geology across the continental US. With CAMELS-Chem, we pair these existing attribute data for 516 catchments with atmospheric deposition data from the National Atmospheric Deposition Program and water chemistry and instantaneous discharge data from the US Geological Survey over the period from 1980 through 2018 in a relational database and corresponding dataset. The data include 18 common stream water chemistry constituents: Al, Ca, Cl, dissolved organic carbon, total organic carbon, HCO3, K, Mg, Na, total dissolved N, total organic N, NO3, dissolved oxygen, pH (field and lab), Si, SO4, and water temperature. Annual deposition loads and concentrations include hydrogen, NH4, NO3, total inorganic N, Cl, SO4, Ca, K, Mg, and Na. We demonstrate that CAMELS-Chem water chemistry data are sampled effectively across climates, seasons, and discharges for trend analysis and highlight the coincident sampling of stream constituents for process-based understanding. To motivate their use by the larger scientific community across a variety of disciplines, we show examples of how these publicly available datasets can be applied to trend detection and attribution, biogeochemical process understanding, and new hypothesis generation via data-driven techniques.
ISSN:1607-7938
1027-5606
1607-7938
DOI:10.5194/hess-28-611-2024