Articles | Volume 28, issue 3
https://doi.org/10.5194/hess-28-611-2024
https://doi.org/10.5194/hess-28-611-2024
Research article
 | 
13 Feb 2024
Research article |  | 13 Feb 2024

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

Gary Sterle, Julia Perdrial, Dustin W. Kincaid, Kristen L. Underwood, Donna M. Rizzo, Ijaz Ul Haq, Li Li, Byung Suk Lee, Thomas Adler, Hang Wen, Helena Middleton, and Adrian A. Harpold

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Cited articles

Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017. 
Adler, T., Underwood, K. L., Rizzo, D. M., Harpold, A., Sterle, G., Li, L., Wen, H., Stinson, L., Bristol, C., Stewart, B., Lini, A., Perdrial, N., and Perdrial, J. N.: Drivers of Dissolved Organic Carbon Mobilization From Forested Headwater Catchments: A Multi Scaled Approach, Front. Water, 3, https://doi.org/10.3389/frwa.2021.578608, 2021. 
Alvarez-Garreton, C., Mendoza, P. A., Boisier, J. P., Addor, N., Galleguillos, M., Zambrano-Bigiarini, M., Lara, A., Puelma, C., Cortes, G., Garreaud, R., McPhee, J., and Ayala, A.: The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – Chile dataset, Hydrol. Earth Syst. Sci., 22, 5817–5846, https://doi.org/10.5194/hess-22-5817-2018, 2018. 
Anderson, I., Hanley, J. P., M. Rizzo, D., Huston D. R., and Dewoolkar, M. M.: Evaluating Damage to Vermont Bridges by Hurricane Irene with Multivariate Bridge Inspection and Stream Hydrogeologic Data, J. Bridge. Eng., 25, 04020083, https://doi.org/10.1061/(ASCE)BE.1943-5592.0001603, 2020. 
Arora, B., Kuppel, S., Wellen, C., Oswald, C., Groh, J., Payandi-Rolland, D., Stegen, J., and Coffinet, S.: Building Cross-Site and Cross-Network collaborations in critical zone science, J. Hydrol., 618, 129248, https://doi.org/10.1016/j.jhydrol.2023.129248, 2023. 
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Short summary
We develop stream water chemistry to pair with the existing CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) dataset. The newly developed dataset, termed CAMELS-Chem, includes common stream water chemistry constituents and wet deposition chemistry in 516 catchments. Examples show the value of CAMELS-Chem to trend and spatial analyses, as well as its limitations in sampling length and consistency.
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