Release notes
This application will update with new short-term nontidal network data as results are available. Visit the USGS Nontidal Network web page for additional information or to access the data used in the application.
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July 2020 - initial release, 2009-2018 water year results
About this tool
The nontidal network mapper shares the short-term water-year nutrient and suspended-sediment load and trend results for the Chesapeake Bay Program’s non-tidal network (Figure 1).
Data collected from the 123 nontidal network stations are analyzed by the U.S. Geological Survey every two years and are used to quantify the changes in nutrient (primarily nitrogen and phosphorus) and suspended-sediment loads. The results are used by the Chesapeake Bay Program partnership to help assess response in nontidal rivers and streams to nutrient and sediment reduction efforts.
The mapper provides the primary findings for nitrogen, phosphorus, and sediment trends and gives the user tools to further examine the results for river basins and individual sites.
Tool features
For each constituent (total nitrogen, total phosphorus, and suspended-sediment), interactive maps, graphs, and query tools allow users to view both site-specific load, trend, and yield information as well as patterns across the Chesapeake Bay or its major watersheds.
Related Content
USGS develops tool to further examine nutrient and sediment trends in the Chesapeake Bay Watershed
River Input Monitoring
Nitrogen, phosphorus, and suspended-sediment loads and trends measured at the Chesapeake Bay Nontidal Network stations: Water years 1985-2018 (ver. 2.0, May 2020)
Application of a Weighted Regression Model for Reporting Nutrient and Sediment Concentrations, Fluxes, and Trends in Concentration and Flux for the Chesapeake Bay Nontidal Water-Quality Monitoring Network, Results Through Water Year 2012
A bootstrap method for estimating uncertainty of water quality trends
User guide to Exploration and Graphics for RivEr Trends (EGRET) and dataRetrieval: R packages for hydrologic data
Comparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed
Weighted regressions on time, discharge, and season (WRTDS), with an application to Chesapeake Bay River inputs
Load and trend results would not be possible without the ongoing monitoring and program support of our partners.
Related Content
- Science
USGS develops tool to further examine nutrient and sediment trends in the Chesapeake Bay Watershed
The U.S. Geological Survey (USGS) has developed the nontidal network mapper to share the short-term (2009-2018) water-year nutrient and suspended-sediment load and trend results for the Chesapeake Bay Program’s (CBP) non-tidal network (NTN). The network is a cooperative effort by USGS, the U.S. Environmental Protection Agency (USEPA), and agencies in the states of the Chesapeake watershed and the...River Input Monitoring
The objective of this study is to provide concentrations and estimates of loads and trends of suspended solids, nitrogen, phosphorus, and other selected constituents at the James, Rappahannock, Appomattox, Pamunkey, and Mattaponi Rivers. - Data
Nitrogen, phosphorus, and suspended-sediment loads and trends measured at the Chesapeake Bay Nontidal Network stations: Water years 1985-2018 (ver. 2.0, May 2020)
Nitrogen, phosphorus, and suspended-sediment loads, and changes in loads, in major rivers across the Chesapeake Bay watershed have been calculated using monitoring data from the Chesapeake Bay Nontidal Network (NTN) stations for the period 1985 through 2018. Nutrient and suspended-sediment loads and changes in loads were determined by applying a weighted regression approach called WRTDS (Weighted - Publications
Application of a Weighted Regression Model for Reporting Nutrient and Sediment Concentrations, Fluxes, and Trends in Concentration and Flux for the Chesapeake Bay Nontidal Water-Quality Monitoring Network, Results Through Water Year 2012
In the Chesapeake Bay watershed, estimated fluxes of nutrients and sediment from the bay’s nontidal tributaries into the estuary are the foundation of decision making to meet reductions prescribed by the Chesapeake Bay Total Maximum Daily Load (TMDL) and are often the basis for refining scientific understanding of the watershed-scale processes that influence the delivery of these constituents to tA bootstrap method for estimating uncertainty of water quality trends
Estimation of the direction and magnitude of trends in surface water quality remains a problem of great scientific and practical interest. The Weighted Regressions on Time, Discharge, and Season (WRTDS) method was recently introduced as an exploratory data analysis tool to provide flexible and robust estimates of water quality trends. This paper enhances the WRTDS method through the introduction oUser guide to Exploration and Graphics for RivEr Trends (EGRET) and dataRetrieval: R packages for hydrologic data
Evaluating long-term changes in river conditions (water quality and discharge) is an important use of hydrologic data. To carry out such evaluations, the hydrologist needs tools to facilitate several key steps in the process: acquiring the data records from a variety of sources, structuring it in ways that facilitate the analysis, processing the data with routines that extract information about chComparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed
Nutrient and sediment fluxes and changes in fluxes over time are key indicators that water resource managers can use to assess the progress being made in improving the structure and function of the Chesapeake Bay ecosystem. The U.S. Geological Survey collects annual nutrient (nitrogen and phosphorus) and sediment flux data and computes trends that describe the extent to which water-quality conditiWeighted regressions on time, discharge, and season (WRTDS), with an application to Chesapeake Bay River inputs
A new approach to the analysis of long‐term surface water‐quality data is proposed and implemented. The goal of this approach is to increase the amount of information that is extracted from the types of rich water‐quality datasets that now exist. The method is formulated to allow for maximum flexibility in representations of the long‐term trend, seasonal components, and discharge‐related component - Partners
Load and trend results would not be possible without the ongoing monitoring and program support of our partners.