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The datasets provided here are the input data used to run the Seasonal Kendall Trend (SKT) tests and Weighted Regressions on Time, Discharge, and Season (WRTDS) models. SKT tests use "annualSamplingFreqs_allSites.csv" and "wqData_screenedSitesAll.csv" which includes, for all site-parameter combinations, information on annual sampling frequencies and the screened water-quality data, respectively. The WRTDS models use "DRB.wqdata.20200521.csv", "DRB.flow.20200610.zip", and "DRB.info.20200521.csv" for calibration which includes, for all site-parameter combinations, the water-quality data, streamflow data (as separate .csv files for each site), model specifications and site information, respectively. The multisource...
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This data release contains one dataset and one model archive in support of the journal article, "Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies," by Jennifer C. Murphy and Jeffrey G. Chanat. The model archive contains scripts (run in R) to reproduce the four machine learning models (logistic regression, linear and quadratic discriminant analysis, and k-nearest neighbors) trained and tested as part of the journal article. The dataset contains the estimated probabilities for each of these models when applied to a training and test dataset.
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The datasets provided here are the output from the Seasonal Kendall Trend (SKT) test and Weighted Regressions on Time, Discharge, and Season (WRTDS) model that characterize changes in water quality in rivers and streams across the Delaware River Basin. SKT results are compiled in "skt_out.csv" for all combinations of site, water-quality parameter, and trend period. WRTDS results are compiled in four datasets. If unspecified, generalized flow normalization (GFN) results are reported. Stationary flow normalization (SFN) results are indicated in the datasets. "wrtds_out_annResults.csv" contains the annual estimates of mean concentration and load and GFN and SFN estimates by site and parameter for the entire calibration...
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This data release provides water-quality trends for rivers and streams in the Delaware River Basin determined using the Weighted Regressions on Time, Discharge, and Season (WRTDS) model and the Seasonal Kendall Trend (SKT) test. Sixteen water-quality parameters were assessed, including nutrients (ammonia, nitrate, filtered orthophosphate, total nitrogen, total phosphorus, and unfiltered orthophosphate), major ions (calcium, chloride, magnesium, potassium, sodium, and sulfate), salinity indicators (total dissolved solids and specific conductance), and sediment (total suspended solids and suspended sediment concentration). The child items include the input and output data used in the modeling and testing of water-quality...
This data release includes estimates of annual and monthly mean concentrations and fluxes for nitrate plus nitrite, orthophosphate and suspended sediment for nine sites in the Mississippi River Basin (MRB) produced using the Weighted Regressions on Time, Discharge, and Season (WRTDS) model (Hirsch and De Cicco, 2015). It also includes a model archive (R scripts and readMe file) used to retrieve and format the model input data and run the model. Input data, including discrete concentrations and daily mean streamflow, were retrieved from the National Water Quality Network (https://doi.org/10.5066/P9AEWTB9). Annual and monthly estimates range from water year 1975 through water year 2019 (i.e. October 1, 1974 through...


    map background search result map search result map Water-quality trends for rivers and streams in the Delaware River Basin using Weighted Regressions on Time, Discharge, and Season (WRTDS) models, Seasonal Kendall Trend (SKT) tests, and multisource data, Water Year 1978-2018 Water-quality trends for rivers and streams in the Delaware River Basin using Weighted Regressions on Time, Discharge, and Season (WRTDS) models, Seasonal Kendall Trend (SKT) tests, and multisource data, Water Year 1978-2018 (input data) Water-quality trends for rivers and streams in the Delaware River Basin using Weighted Regressions on Time, Discharge, and Season (WRTDS) models, Seasonal Kendall Trend (SKT) tests, and multisource data, Water Year 1978-2018 (output data) Data to Incorporate Water Quality Analysis into Navigation Assessments as Demonstrated in the Mississippi River Basin Data to support Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies Water-quality trends for rivers and streams in the Delaware River Basin using Weighted Regressions on Time, Discharge, and Season (WRTDS) models, Seasonal Kendall Trend (SKT) tests, and multisource data, Water Year 1978-2018 Water-quality trends for rivers and streams in the Delaware River Basin using Weighted Regressions on Time, Discharge, and Season (WRTDS) models, Seasonal Kendall Trend (SKT) tests, and multisource data, Water Year 1978-2018 (input data) Water-quality trends for rivers and streams in the Delaware River Basin using Weighted Regressions on Time, Discharge, and Season (WRTDS) models, Seasonal Kendall Trend (SKT) tests, and multisource data, Water Year 1978-2018 (output data) Data to Incorporate Water Quality Analysis into Navigation Assessments as Demonstrated in the Mississippi River Basin Data to support Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies