The Maumee River transports huge loads of nitrogen (N) and phosphorus (P) to Lake Erie. The increased concentrations of N and P are causing eutrophication of the lake, creating hypoxic zones, and contributing to phytoplankton blooms. It is hypothesized that the P loads are a major contributor to harmful algal blooms that occur in the western basin of Lake Erie, particularly in summer. The Maumee River has been identified by the United States Environmental Protection Agency as a priority watershed where action needs to be taken to reduce nutrient loads. This study quantified rates of biogeochemical processes affecting downstream flux of N and P by 1) measuring indices of potential sediment P retention and 2) measuring nitrification and ambient and potential denitrification throughout the Maumee River Basin. Data generated from this project will inform models that estimate P retention and N removal potential in the basin and watershed models that simulate the effects of different conservation practices on the landscape.

The Maumee River transports huge loads of nitrogen (N) and phosphorus (P) to Lake Erie. The increased concentrations of N and P are causing eutrophication of the lake, creating hypoxic zones, and contributing to phytoplankton blooms. It is hypothesized that the P loads are a major contributor to harmful algal blooms that occur in the western basin of Lake Erie, particularly in summer. The Maumee River has been identified by the United States Environmental Protection Agency as a priority watershed where action needs to be taken to reduce nutrient loads. This study quantified rates of biogeochemical processes affecting downstream flux of N and P by 1) measuring indices of potential sediment P retention and 2) measuring nitrification and ambient and potential denitrification throughout the Maumee River Basin. Data generated from this project will inform models that estimate P retention and N removal potential in the basin and watershed models that simulate the effects of different conservation practices on the landscape.

The Maumee River transports huge loads of nitrogen (N) and phosphorus (P) to Lake Erie. The increased concentrations of N and P are causing eutrophication of the lake, creating hypoxic zones, and contributing to phytoplankton blooms. It is hypothesized that the P loads are a major contributor to harmful algal blooms that occur in the western basin of Lake Erie, particularly in summer. The Maumee River has been identified by the United States Environmental Protection Agency as a priority watershed where action needs to be taken to reduce nutrient loads. This study quantified rates of biogeochemical processes affecting downstream flux of N and P by 1) measuring indices of potential sediment P retention and 2) measuring nitrification and ambient and potential denitrification throughout the Maumee River Basin. Data generated from this project will inform models that estimate P retention and N removal potential in the basin and watershed models that simulate the effects of different conservation practices on the landscape.

The Fox River transports elevated loads of nitrogen and phosphorus to Lake Michigan. The increased concentration of N and P causes eutrophication of the lake, creating hypoxic zones and damaging the lake ecosystem.To decrease loading, best management practices (BMPs) have been implemented in the uplands of the basin. Little work has been done, however, to reduce nutrient concentrations in the river. Rivers are capable of removing nutrients through biotic uptake and sediment burial and are able to remove N through denitrification. Identifying and managing these locations of increased nutrient cycling known as “hot spots” may be another mechanism for nutrient mitigation.Our objective was to identify hot spots of N and P cycling in the Fox River basin. We measured rates of specific biogeochemical processes (e.g. ambient and potential denitrification, and sediment phosphorus uptake and release) at sites that had varying mixed land use. We also measured variables that are known to affect nitrogen and phosphorus cycling. Models were created to estimate how land use type and BMP coverage can effect the capacity of the Fox River and its tributaries to retain and cycle N and P.

The Fox River transports elevated loads of nitrogen and phosphorus to Lake Michigan. The increased concentration of N and P causes eutrophication of the lake, creating hypoxic zones and damaging the lake ecosystem.To decrease loading, best management practices (BMPs) have been implemented in the uplands of the basin. Little work has been done, however, to reduce nutrient concentrations in the river. Rivers are capable of removing nutrients through biotic uptake and sediment burial and are able to remove N through denitrification. Identifying and managing these locations of increased nutrient cycling known as “hot spots” may be another mechanism for nutrient mitigation.Our objective was to identify hot spots of N and P cycling in the Fox River basin. We measured rates of specific biogeochemical processes (e.g. ambient and potential denitrification, and sediment phosphorus uptake and release) at sites that had varying mixed land use. We also measured variables that are known to affect nitrogen and phosphorus cycling. Models were created to estimate how land use type and BMP coverage can effect the capacity of the Fox River and its tributaries to retain and cycle N and P.

Phosphorus, nitrogen, and suspended-sediment loads, in 24 U.S. tributaries of the Great Lakes, were calculated using U.S. Geological Survey (USGS) data from the Great Lakes Restoration Initiative (GLRI) monitoring program for the period Oct 2010 through Sept 2020 (USGS water years 2011–2020). Total phosphorus, orthophosphate, particulate phosphorus, total nitrogen, nitrate plus nitrite, ammonium plus ammonia, and suspended-sediment loads and changes in loads were determined by applying a weighted regression approach called WRTDS (Weighted Regression on Time, Discharge, and Season). The load results represent the total mass of nitrogen, phosphorus, and suspended sediment exported downstream at each tributary site. Daily loads were estimated using the WRTDS method with Kalman filtering. To determine the change in loads between the first and last water year in record, the annual load results were flow-normalized to standardize among years with varying flow dynamics. Three primary data tables are provided that describe phosphorus, nitrogen, and suspended-sediment conditions at 24 tributaries across the U.S. Great Lakes watershed: (1) annual results, (2) daily results, and (3) changes results. The annual table is organized by USGS water year (defined as Oct 1–Sept 30). The annual and daily tables also include time-weighted mean concentrations, mean discharge, and yield estimates, the latter being calculated by dividing loads by watershed areas. Descriptions for data tables are provided in the DataDictionary.csv file. Results are also displayed in an interactive web application (https://rconnect.usgs.gov/glritrends). This data release also contains a model archive. The “model_code.zip” file contains the R code and input data to run the models, generate the results, and display the results on a shiny application. The Readme.md file includes instructions of how to run the model and descriptions of all inputs, model arguments, and outputs. Each model (saved as an eList) contains the input data (USGS station information (i.e., site information), daily discharge, and water sample data), model parameters, estimated values, and bootstrapped results. All eLists are archived in the “model_archive” folder, which is organized by sample dataset (i.e., allsamples and midsamples) and are named with the parameter and station number (e.g., NH4_04024000.RData). The RData files used in the shiny application are archived in the “shinydata” folder.

Phosphorus, nitrogen, and suspended-sediment loads, in 24 U.S. tributaries of the Great Lakes, were calculated using U.S. Geological Survey (USGS) data from the Great Lakes Restoration Initiative (GLRI) monitoring program for the period Oct 2010 through Sept 2020 (USGS water years 2011–2020). Total phosphorus, orthophosphate, particulate phosphorus, total nitrogen, nitrate plus nitrite, ammonium plus ammonia, and suspended-sediment loads and changes in loads were determined by applying a weighted regression approach called WRTDS (Weighted Regression on Time, Discharge, and Season). The load results represent the total mass of nitrogen, phosphorus, and suspended sediment exported downstream at each tributary site. Daily loads were estimated using the WRTDS method with Kalman filtering. To determine the change in loads between the first and last water year in record, the annual load results were flow-normalized to standardize among years with varying flow dynamics. Three primary data tables are provided that describe phosphorus, nitrogen, and suspended-sediment conditions at 24 tributaries across the U.S. Great Lakes watershed: (1) annual results, (2) daily results, and (3) changes results. The annual table is organized by USGS water year (defined as Oct 1–Sept 30). The annual and daily tables also include time-weighted mean concentrations, mean discharge, and yield estimates, the latter being calculated by dividing loads by watershed areas. Descriptions for data tables are provided in the DataDictionary.csv file. Results are also displayed in an interactive web application (https://rconnect.usgs.gov/glritrends). This data release also contains a model archive. The “model_code.zip” file contains the R code and input data to run the models, generate the results, and display the results on a shiny application. The Readme.md file includes instructions of how to run the model and descriptions of all inputs, model arguments, and outputs. Each model (saved as an eList) contains the input data (USGS station information (i.e., site information), daily discharge, and water sample data), model parameters, estimated values, and bootstrapped results. All eLists are archived in the “model_archive” folder, which is organized by sample dataset (i.e., allsamples and midsamples) and are named with the parameter and station number (e.g., NH4_04024000.RData). The RData files used in the shiny application are archived in the “shinydata” folder.

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 Quality Research (NCWQR; Heidelberg University, Tiffin, Ohio) and the Indiana Department of Environmental Management (IDEM), and streamflow records were provided by the U.S. Geological Survey (USGS). The 10 water-quality trend sites were identified using abbreviated names of the nearby USGS streamgage that provided streamflow data for determining nutrient fluxes at these sites (see Site_map.pdf and Site-summary_table.csv). Trends in flow-normalized nutrient fluxes were determined using the method Weighted Regression on Time, Discharge, and Season (WRTDS) method (Hirsch and DeCicco, 2015, 2018a, and 2018b) and streamflow (discharge) trends were determined using the graphical-statistical method of Quantile-Kendall plots (Hirsch, 2018). The nutrient trend analyses focus on the parameters total phosphorus (TP, as P), soluble reactive phosphorus (SRP, as P), total nitrogen (TN, as N), nitrate plus nitrite (NO23, as N) filtered at NCWQR sites or unfiltered at IDEM sites, and total Kjeldahl nitrogen (TKN, as N). TN was calculated as TKN plus NO23. SRP was monitored at only 6 of the 10 trend sites. Additional information on field and laboratory methods appears in Choquette et al. (2019). The dataset is presented in two parts: 1. Nutrient and Streamflow Model-Input Data 2. Nutrient and Streamflow Trend Results References: Choquette, A.F., Hirsch, R.M., Murphy, J.C., Johnson, L.T., and Confesor, R.B. Jr., 2019, Tracking changes in nutrient delivery to western Lake Erie: approaches to compensate for variability and trends in streamflow: J. of Great Lakes Research, v. 45, no. 1, p. 21-39, https://doi.org/10.1016/j.jglr.2018.11.012. Hirsch, R.M., 2018, Daily streamflow trend analysis: U.S. Geological Survey Office of Water Information Blog, 38 p., at: https://owi.usgs.gov/blog/Quantile-Kendall/. Hirsch, R.M., and De Cicco, L.A., 2015 (revised). User Guide to Exploration and Graphics for RivEr Trends (EGRET) and dataRetrieval: R Packages for Hydrologic Data, Version 2.0, U.S. Geological Survey Techniques Methods, 4-A10. U.S. Geological Survey, Reston, VA., 93 p. (at: http://dx.doi.org/10.3133/tm4A10). Hirsch, R.M., and De Cicco, L.A., 2018a, Guide to EGRET 3.0 Enhancements: at https://cran.r-project.org/web/packages/EGRET/vignettes/Enhancements.html. Hirsch, R.M., and De Cicco, L.A., 2018b, EGRET release 3.0, and EGRETci release 2.0, at: https://cran.r-project.org/ .

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 Quality Research (NCWQR; Heidelberg University, Tiffin, Ohio) and the Indiana Department of Environmental Management (IDEM), and streamflow records were provided by the U.S. Geological Survey (USGS). The 10 water-quality trend sites were identified using abbreviated names of the nearby USGS streamgage that provided streamflow data for determining nutrient fluxes at these sites (see Site_map.pdf and Site-summary_table.csv). Trends in flow-normalized nutrient fluxes were determined using the method Weighted Regression on Time, Discharge, and Season (WRTDS) method (Hirsch and DeCicco, 2015, 2018a, and 2018b) and streamflow (discharge) trends were determined using the graphical-statistical method of Quantile-Kendall plots (Hirsch, 2018). The nutrient trend analyses focus on the parameters total phosphorus (TP, as P), soluble reactive phosphorus (SRP, as P), total nitrogen (TN, as N), nitrate plus nitrite (NO23, as N) filtered at NCWQR sites or unfiltered at IDEM sites, and total Kjeldahl nitrogen (TKN, as N). TN was calculated as TKN plus NO23. SRP was monitored at only 6 of the 10 trend sites. Additional information on field and laboratory methods appears in Choquette et al. (2019). The dataset is presented in two parts: 1. Nutrient and Streamflow Model-Input Data 2. Nutrient and Streamflow Trend Results References: Choquette, A.F., Hirsch, R.M., Murphy, J.C., Johnson, L.T., and Confesor, R.B. Jr., 2019, Tracking changes in nutrient delivery to western Lake Erie: approaches to compensate for variability and trends in streamflow: J. of Great Lakes Research, v. 45, no. 1, p. 21-39, https://doi.org/10.1016/j.jglr.2018.11.012. Hirsch, R.M., 2018, Daily streamflow trend analysis: U.S. Geological Survey Office of Water Information Blog, 38 p., at: https://owi.usgs.gov/blog/Quantile-Kendall/. Hirsch, R.M., and De Cicco, L.A., 2015 (revised). User Guide to Exploration and Graphics for RivEr Trends (EGRET) and dataRetrieval: R Packages for Hydrologic Data, Version 2.0, U.S. Geological Survey Techniques Methods, 4-A10. U.S. Geological Survey, Reston, VA., 93 p. (at: http://dx.doi.org/10.3133/tm4A10). Hirsch, R.M., and De Cicco, L.A., 2018a, Guide to EGRET 3.0 Enhancements: at https://cran.r-project.org/web/packages/EGRET/vignettes/Enhancements.html. Hirsch, R.M., and De Cicco, L.A., 2018b, EGRET release 3.0, and EGRETci release 2.0, at: https://cran.r-project.org/ .

Input and release of phosphate, nitrate, and ammonium measured using stacked ion-exchange resin bags on top of soil in floodplains along Pocomoke River, Maryland, in order to evaluate the effectiveness of floodplain reconnection on water quality functions.