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Input Files and WRTDS Model Output for the two major tributaries of Lake Koocanusa: Discharge

Metadata Updated: July 6, 2024

Canadian discrete water quality data and daily streamflow records were evaluated using the Weighted Regression on Time, Discharge, and Seasons (WRTDS) model implemented with the EGRET R package (Hirsch et al. 2010, Hirsch and De Cicco 2015). Models were used to estimate loads of solutes and evaluate trends for three constituents of interest (selenium, nitrogen, and sulfate). Six models were generated; one model for each of the three constituents of interest, in each of the two major tributaries to Lake Koocanusa: the Kootenay River at Fenwick (BC08NG0009), and the Elk River above Highway 93 Near Elko (BC08NK0003). Data were obtained by downloading data from the British Columbia Water Tool (https://kwt.bcwatertool.ca/surface-water-quality, https://kwt.bcwatertool.ca/streamflow) and Environment Climate Change Canada (https://open.canada.ca/data/en/dataset/c2adcb27-6d7e-4e97-b546-b8ee3d586aa4/resource/7bb8d1ff-f446-494f-8f3d-ad252162eef5?inner_span=True). This data release consists of two input data files and one output file from the EGRET model estimation (eList) which contains the WRTDS model, for each site and constituent. The input datasets include a daily discharge data file and a measured concentration data file. The period of record for the water quality data varies among the constituents and sites. Likewise, the output file time period aligns with the input files and varies among the 6 models. Nitrate in the Elk River at Highway 93 has the longest period of record from 1979 to 2022. Water quality sampling at the Fenwick station was discontinued in 2019, so all models for the Kootenay end after 2019. This data release also contains mass removal data provided by Teck Coal Limited, which were incorporated into a sub-analysis that used the WRTDS selenium model for the Elk River. This child item contains only the discharge files. The WRTDS model was run at a daily time step. Model performance evaluations, including a visual assessment of model fit and residuals and bias correction factors were completed. Model output for each parameter at each site (6 total) is published here in an eLists (.rds file). The format of each eLists is standardized per EGRET processing. See Hirsch and De Cicco (2015) for description of these files. WRTDS_Kalman estimates can also be evaluated by running additional functions with the eLists published. To prevent redundancy they were excluded from this output. For the Kalman models nitrate specified a rho of 0.95 while the other models used the default (0.9). Citations: Hirsch, R.M., and De Cicco, L.A., 2015, User guide to Exploration and Graphics for RivEr Trends (EGRET) and dataRetrieval—R packages for hydrologic data (version 2.0, February 2015): U.S. Geological Survey Techniques and Methods book 4, chap. A10, 93 p., http://dx.doi.org/10.3133/tm4A10. Hirsch, R.M., Moyer, D.L., and Archfield, S.A., 2010, Weighted Regressions on Time, Discharge, and Season (WRTDS), With an Application to Chesapeake Bay River Inputs: Journal of the American Water Resources Association (JAWRA), v. 46, no. 5, 857-880 p., DOI: http://dx.doi.org/10.1111/j.1752-1688.2010.00482.x.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Dates

Metadata Created Date May 31, 2023
Metadata Updated Date July 6, 2024

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date May 31, 2023
Metadata Updated Date July 6, 2024
Publisher U.S. Geological Survey
Maintainer
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Data Last Modified 20230612
Category geospatial
Public Access Level public
Bureau Code 010:12
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Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
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Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
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