2020 ESA Annual Meeting (August 3 - 6)

PS 48 Abstract - Augmenting CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) with atmospheric and stream water chemistry data

Gary Sterle1, Julia N. Perdrial2, Thomas Adler2, Kristen Underwood3, Donna M. Rizzo3, Hang Wen4, Li Li5 and Adrian Harpold1, (1)Natural Resources and Environmental Science, University of Nevada, Reno, NV, (2)Geology, University of Vermont, Burlington, VT, (3)Civil and Environmental Engineering, University of Vermont, Burlington, VT, (4)Civil and Environmental Engineering, Pennsylvania State University, University Park, PA, (5)Civil and Environmental Engineering, Penn State University, University Park, PA
Background/Question/Methods: The increasing availability of hydrochemical datasets at continental scales has the potential to transform scientific insights that have often focused on detailed knowledge of a single catchment. Integration of stream chemistry with hydrology, hydroclimatology, and local physiography (e.g. vegetation, geology, topography) has led to numerous scientific advances over the last several decades. This newly created dataset was derived using a set of advanced data collection tools and entailed three main phases: 1) data acquisition; 2) loading the data into a data warehouse; 3) collation and computation of final data products for publishing. Data acquisition was accomplished using Extract, Transform and Load (ETL) methodology. ETL methodology is a process that extracts the data from different source systems, then transforms the data (applying calculations, date formatting, etc.) and finally loads the data into the Data Warehouse system. The ETL engine used the USGS National Water Information System database where we acquired all available biological data for each of the 493 watersheds. To enrich the dataset, a discharge dataset was obtained which comprised hourly and daily discharge data for each gauge ID.

Results/Conclusions: We pair atmospheric deposition and water chemistry related information with the existing CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) dataset. The newly developed dataset, CAMELS-Chem, is comprised of U.S. Geological Survey water chemistry and instantaneous discharge over the period from 1980 through 2014 in 493 headwater catchments. The CAMEL-Chem dataset includes common stream water chemistry related constituents (Ca2, Na, K, Mg2 and Al3, Cl-, NO3-, SO₄²-, Si, N, total Nitrogen, HCO3, dissolved oxygen, pH, Dissolved Organic Carbon (DOC), Total Organic Carbon (TOC), and water temperature), 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). We release a paired instantaneous discharge (and mean daily discharge) record for all chemistry samples and publish the full 15-minute discharge dataset for all catchments where it is available. Together, this body of work shows the potential value of compiling long-term stream water chemistry datasets in combination with stream discharge and other catchment properties.