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The newly developed dataset, CAMELS-Chem, compiles USGS water chemistry and instantaneous discharge from 1980 through 2014 in 493 headwater catchments. It includes common stream water chemistry related constituents, as well as an overlapping set of annual wet deposition load from the National Atmospheric Deposition Program.

camels-dataset water-quality dissolved-oxygen watershed-chemistry

camels-chem-do-dataset's Introduction

CAMELS-Chem DO dataset

The CAMELS-Chem dataset is developed by the Nevada Mountain Ecohydrology Lab (https://naes.unr.edu/harpold/) led by Adrian A. Harpold (@NV_Mtn_Ecohydro) at University of Neveda, Reno. It builds a stream chemistry database that supplements to the Catchment Attribute for Large Sample Studies (CAMESLS) database (Addor et al., 2017; Newman et al., 2015).

The newly developed dataset, CAMELS-Chem, compiles USGS water chemistry and instantaneous discharge from 1980 through 2014 in 493 headwater catchments. It includes common stream water chemistry related constituents (pH, water temperature, dissolved oxygen, Na, K, Ca, Mg, Al, Cl, NO3, SO4, Si, HCO3, organic nitrogen, total nitrogen, dissolved organic carbon, total organic carbon, and etc), as well as an overlapping set of annual wet deposition load from the National Atmospheric Deposition Program (Br, Ca, Cl, H, K, Mg, N, Na, NH4, NO3, SO4).

This page includes the DO records from the CAMELS-Chem database used in Zhi et al., 2021. The entire database will be available when the CAMELS-Chem manuscript is published (Sterle et al., in preparation).

Study site: Coal Creek Watershed

Reference:

  • Zhi, W., Feng, D., Tsai, W. P., Sterle, G., Harpold, A., Shen, C., & Li, L. (2021). From Hydrometeorology to River Water Quality: Can a Deep Learning Model Predict Dissolved Oxygen at the Continental Scale?. Environmental Science & Technology, doi: 10.1021/acs.est.0c06783

  • Sterle, G., Perdrial, J.N., Li, L., Adler, T., Underwood, K., Rizzo, D., Wen, H., Addor, N., Newman, A. and Harpold, A., Augmenting CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) with Atmospheric and Stream Water Chemistry Data (in preparation).

  • Addor, N., Newman, A.J., Mizukami, N. and Clark, M.P., 2017. The CAMELS data set: catchment attributes and meteorology for large-sample studies. Hydrology and Earth System Sciences (HESS), 21(10), pp.5293-5313.

  • Newman, A.J., Clark, M.P., Sampson, K., Wood, A., Hay, L.E., Bock, A., Viger, R.J., Blodgett, D., Brekke, L., Arnold, J.R. and Hopson, T., 2015. Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance. Hydrology and Earth System Sciences (HESS), 19(1), p.209.

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