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This data set includes WRTDS nutrient flux trend results and the values of daily streamflow trend results displayed in the Quantile-Kendall plots. For 1995-2015 nutrient trends, the method of generalized flow normalization (FNG) was used which explicitly addresses non-stationary streamflow conditions. For 2005-2015 nutrient trends, the WRTDS trend analyses used the method of stationary flow normalization (FNS) because streamflow nonstationarity is difficult to assess over this shorter duration time frame. The 1995-2015 annual nutrient trends were determined for all five nutrient parameters (TP, SRP, TN, NO23, TKN), and monthly trends were evaluated only for SRP. The 2005-2015 annual nutrient trends were determined...
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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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Data provided in this release support the findings in Choquette et al. (2019), utilizing methods for evaluating water-quality and daily-streamflow trends described also in Hirsch and DeCicco (2015 and 2018a) and Hirsch (2018). The trend results and model-input data focus on 10 locations in the Lake Erie watershed that have long-term (20 or more years) water-quality and streamflow monitoring records. The trend results include the years 1987 through 2016 or specified sub-periods during this time frame. The model-input data records spanned the time period 1974 through 2016 although record lengths varied by site, data type, and trend analysis. The water-quality records were provided by the National Center for Water...
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For about 10 years, the U.S. Geological Survey (USGS) has monitored water quality and streamflow in three agricultural drainage ditches in an effort to evaluate the influence of best management practices on water quality. These ditches are small tributaries to oxbow lakes located in the Mississippi Alluvial Plain of northwestern Mississippi--two sites (LWSR and LWT2) drain to Lake Washington and one site (BLT1) drains to Bee Lake. Streamflow was intermittent at these sites and the ditches were dry much of the year. When streamflow was present, flows were measured on 15-minute intervals and water-quality samples were collected over the course of the flow event using an automated sampler. These datasets were aggregated...
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This data set contains U.S. Geological Survey (USGS) streamgage matching results in tabular format for water-quality sites retrieved from the Water Quality Portal for the Delaware River Basin. The table contains a list of water-quality sites joined to USGS streamgages where the water-quality site and USGS streamgage are located on the same stream, as represented by the National Hydrography Dataset Plus (NHDPlus) "LevelPathID" attribute. The file represents a one-to-many relationship: each water-quality site, as represented by the unique identifier, "MonitoringLocationIdentifier", is joined to anywhere from zero streamgages (not on same stream as any gage; the gage info columns are NA) to one or more streamgages...
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This data release contains a 17-year record (2005-2022) of discrete chlorophyll data from inland waters, collected from across the nation and territories. These data are from discrete samples (collected in the field and analyzed in the laboratory) from plankton (suspended algae) and periphyton (benthic algae) from lakes, streams, rivers, reservoirs, canals, and other sites. These data are gathered to support process and remote sensing modeling and prediction of Harmful Algal Blooms (HABs). The chlorophyll data were compiled from the Water Quality Portal (WQP) and USGS National Water Quality Lab (NWQL). Data for uncorrected chlorophyll a, corrected chlorophyll a, and pheophytin from EPA Methods 445 and 446 are included...
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Datasets of suspended sediment concentration and percent fines, sampling information, and daily streamflow data were compiled and harmonized for 16 sites to better understand sediment transport and delivery in the Lower Mississippi and Atchafalaya Rivers. The compiled data were harmonized by removing unnecessary columns, screening data for laboratory or sampling issues, creating consistent entries for character columns, and dropping irrelevant data, among other steps. Fourteen of the sites are in the Lower Mississippi-Atchafalaya River Basin with two additional sites on the Middle Mississippi and Ohio Rivers. Suspended sediment concentration (total, all size fractions) and percent fines for multiple size fractions...
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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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Jointly managed by multiple states and the federal government, there are many ongoing efforts to characterize and understand water quality in the Delaware River Basin (DRB). Many State, Federal and non-profit organizations have collected surface-water-quality samples across the DRB for decades and many of these data are available through the National Water Quality Monitoring Council's Water Quality Portal (WQP). For this data release, WQP data in the DRB were harmonized, meaning that they were processed to create a clean and readily usable dataset. The harmonization process included the synthesis of parameter names and fractions, the condensation of remarks and other data qualifiers, the resolution of duplicate...
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This data set includes WRTDS nutrient flux trend results and the values of daily streamflow trend results displayed in the Quantile-Kendall plots. For 1995-2015 nutrient trends, the method of generalized flow normalization (FNG) was used which explicitly addresses non-stationary streamflow conditions. For 2005-2015 nutrient trends, the WRTDS trend analyses used the method of stationary flow normalization (FNS) because streamflow nonstationarity is difficult to assess over this shorter duration time frame. The 1995-2015 annual nutrient trends were determined for all five nutrient parameters (TP, SRP, TN, NO23, TKN), and monthly trends were evaluated only for SRP. The 2005-2015 annual nutrient trends were determined...
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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...
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In 1991, the U.S. Geological Survey (USGS) began a study of more than 50 major river basins across the Nation as part of the National Water-Quality Assessment (NAWQA) project. One of the major goals of the NAWQA project was to determine how river water quality has changed over time. To support that goal, long-term consistent and comparable monitoring has been conducted by the USGS on streams and rivers throughout the Nation. Outside of the NAWQA project, the USGS and other Federal, State, and local agencies also have collected long-term water-quality data to support their own assessments of changing water quality. In 2017, data from these multiple sources were combined to support one of the most comprehensive assessments...
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This data release contains annual estimates of suspended-sediment concentration and load for the Mississippi River, St. Francisville site and the Atchafalaya River, Melville site from 1980-2015. Annual estimates and flow-normalized estimates were generated using the Weighted Regressions on Time, Season and Discharge (WRTDS) model. Input data for the model included suspended-sediment concentrations publicly available from the U.S. Geological Survey (USGS)'s National Water Information System (U.S. Geological Survey, 2016) and daily-mean streamflow estimates from the Army Corps of Engineers (2016) and USGS. These annual concentrations and loads are used to support trend analyses and provide estimates of sediment availability...
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In 1991, the U.S. Geological Survey (USGS) began a study of more than 50 major river basins across the Nation as part of the National Water-Quality Assessment (NAWQA) project. One of the major goals of the NAWQA project was to determine how river water quality has changed over time. To support that goal, long-term consistent and comparable monitoring has been conducted by the USGS on streams and rivers throughout the Nation. Outside of the NAWQA project, the USGS and other Federal, State, and local agencies also have collected long-term water-quality data to support their own assessments of changing water quality. In 2017, data from these multiple sources were combined to support one of the most comprehensive assessments...
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Jointly managed by multiple states and the federal government, there are many ongoing efforts to characterize and understand water quality in the Delaware River Basin (DRB). Many State, Federal and non-profit organizations have collected surface-water-quality samples across the DRB for decades and many of these data are available through the National Water Quality Monitoring Council's Water Quality Portal (WQP). In this data release, WQP data in the DRB were harmonized, meaning that they were processed to create a clean and readily usable dataset. This harmonization processing included the synthesis of parameter names and fractions, the condensation of remarks and other data qualifiers, the resolution of duplicate...
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Trends in nutrient fluxes and streamflow for selected tributaries in the Lake Erie watershed were calculated using monitoring data at 10 locations. Trends in flow-normalized nutrient fluxes were determined by applying a weighted regression approach called WRTDS (Weighted Regression on Time, Discharge, and Season). Site information and streamflow and water-quality records are contained in 3 zipped files named as follows: INFO (site information), Daily (daily streamflow records), and Sample (water-quality records). The INFO, Daily (flow), and Sample files contain the input data, by water-quality parameter and by site as .csv files, used to run trend analyses. These files were generated by the R (version 3.1.2) software...
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...
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Harmful algal blooms (HABs) are overgrowths of algae or cyanobacteria in water and can be harmful to humans and animals directly via toxin exposure or indirectly via changes in water quality and related impacts to ecosystems services, drinking water characteristics, and recreation. While HABs occur frequently throughout the United States, the driving conditions behind them are not well understood, especially in flowing waters. In order to facilitate future model development and characterization of HABs in the Illinois River Basin, this data release publishes a synthesized and cleaned collection of HABs-related water quality and quantity data for river and stream sites in the basin. It includes nutrients, major ions,...


    map background search result map search result map Annual estimates of suspended-sediment concentration and load to support trend analysis on the Mississippi River and Atchafalaya River, 1980-2015 Hydrologic event-based water-quality and streamflow data for three oxbow tributaries in northwestern Mississippi, 2007-2016 Nutrient and streamflow model-input data (1974-2016) and trend results (1987-2016) for selected Lake Erie tributaries Nutrient and streamflow model-input data Lake Erie Tributaries: Nutrient and streamflow trend results Nutrient and streamflow trend results Multisource surface-water-quality data and U.S. Geological Survey streamgage match for the Delaware River Basin Multisource surface-water-quality data for the Delaware River Basin U.S. Geological Survey streamgage matching results for water-quality sites of the Delaware River Basin 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 Water-quality and streamflow datasets used in Weighted Regressions on Time, Discharge, and Season (WRTDS) models to determine trends in the Nation’s rivers and streams, 1972-2017 Water-quality and streamflow datasets used in Weighted Regressions on Time, Discharge, and Season (WRTDS) models to determine trends in the Nation’s rivers and streams, 1972-2017 (output data) Datasets of Suspended Sediment Concentration and Percent Fines (1973–2021), Sampling Information (1973–2021), and Daily Streamflow (1928–2021) for Sites in the Lower Mississippi and Atchafalaya Rivers to Support Analyses of Sediment Transport and Delivery Harmonized discrete and continuous water quality data in support of modeling harmful algal blooms in the Illinois River Basin, 2005 - 2020 A national harmonized dataset of discrete chlorophyll from lakes and streams (2005-2022) Data to support Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies Hydrologic event-based water-quality and streamflow data for three oxbow tributaries in northwestern Mississippi, 2007-2016 Annual estimates of suspended-sediment concentration and load to support trend analysis on the Mississippi River and Atchafalaya River, 1980-2015 Multisource surface-water-quality data and U.S. Geological Survey streamgage match for the Delaware River Basin Multisource surface-water-quality data for the Delaware River Basin U.S. Geological Survey streamgage matching results for water-quality sites of the Delaware River Basin Nutrient and streamflow model-input data (1974-2016) and trend results (1987-2016) for selected Lake Erie tributaries Nutrient and streamflow model-input data Lake Erie Tributaries: Nutrient and streamflow trend results Nutrient and streamflow trend results 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) Harmonized discrete and continuous water quality data in support of modeling harmful algal blooms in the Illinois River Basin, 2005 - 2020 Datasets of Suspended Sediment Concentration and Percent Fines (1973–2021), Sampling Information (1973–2021), and Daily Streamflow (1928–2021) for Sites in the Lower Mississippi and Atchafalaya Rivers to Support Analyses of Sediment Transport and Delivery 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 and streamflow datasets used in Weighted Regressions on Time, Discharge, and Season (WRTDS) models to determine trends in the Nation’s rivers and streams, 1972-2017 (output data) Water-quality and streamflow datasets used in Weighted Regressions on Time, Discharge, and Season (WRTDS) models to determine trends in the Nation’s rivers and streams, 1972-2017 A national harmonized dataset of discrete chlorophyll from lakes and streams (2005-2022)