Jeff G. Chanat
Jeff Chanat is a hydrologist at the Virginia and West Virginia Water Science Center.
Science and Products
Data to support Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies
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...
Climate, Landscape, and Water-Quality Metrics for Selected Watersheds in Fairfax County, Virginia, 2007-2018
This data release documents spatiotemporal water-quality, landscape, and climatic conditions in Fairfax County, Virginia from 2007 through 2018. These data were used to evaluate the water-quality and ecological condition of 20 Fairfax County watersheds monitored since 2007. Data include measures of water-quality, precipitation, air temperature, land use, land cover, wastewater and...
CAST Data Input Disaggregation from County and Land-River Segment Scale to National Hydrography Dataset Plus, Version 1.1
The detrimental effects of excess nutrients and sediment entering the Chesapeake Bay estuary from its watersheds have necessitated regulatory actions. Federally-mandated reductions are apportioned to bay jurisdictions based on the U.S. Environmental Protection Agency's Chesapeake Bay Time-Variable Watershed Model (CBPM). The Chesapeake Assessment Scenario Tool (CAST version CAST-19; cast...
Inputs and Selected Predictions of a Differential Spatially Referenced Regression Model for 20-year Changes in Total Nitrogen in the Chesapeake Bay Watershed
The core equations of the SPARROW model (Schwarz and others, 2006) were implemented in differential form using the R programming language (R Core Team, 2017), as the basis of a tool for empirically relating a regional pattern of changes in constituent flux, over a multi-year period, to spatially referenced changes in explanatory variables over the same period. A pilot implementation was...
Multidecadal Streamflow Trends and Ecological Flow Statistics at USGS Monitoring Stations within the Chesapeake Bay Watershed (1940-2018)
The hydrologic regime of rivers and streams is a major determinant of habitat quality for fish and aquatic invertebrates. Long-term streamflow data were compiled and multidecadal streamflow trends and ecological flow (EFlow) statistics were calculated in support of the United States Geological Survey (USGS) Chesapeake Bay Science Initiative toward understanding fish habitat and health in...
Nitrogen, Phosphorus, and Suspended-Sediment Loads and Trends measured at the Chesapeake Bay Nontidal Network Stations: Water Years 1985-2014
Nitrogen, phosphorus, and suspended-sediment loads, and changes in loads, in 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 2014. Nutrient and suspended-sediment loads and changes in loads were determined by applying a weighted regression approach called WRTDS...
Filter Total Items: 16
Evaluating water-quality trends in agricultural watersheds prioritized for management-practice implementation
Many agricultural watersheds rely on the voluntary use of management practices (MPs) to reduce nonpoint source nutrient and sediment loads; however, the water-quality effects of MPs are uncertain. We interpreted water-quality responses from as early as 1985 through 2020 in three agricultural Chesapeake Bay watersheds that were prioritized for MP implementation, namely, the Smith Creek...
Authors
James S. Webber, Jeffrey G. Chanat, John Clune, Olivia Devereux, Natalie Celeste Hall, Robert D. Sabo, Qian Zhang
Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies
Large multi-site trend studies provide an opportunity to evaluate progress of waterbodies towards water-quality goals across broad geographic areas. Such studies often aggregate the results of site-specific models and thus contend with evaluating each model for appropriate fit and statistical assumptions. We explored the use of four traditional machine learning models (logistic...
Authors
Jennifer C. Murphy, Jeffrey G. Chanat
Integrated water resources trend assessments: State of the science, challenges, and opportunities for advancement
Water is vital to human life and healthy ecosystems. Here we outline the current state of national-scale water resources trend assessments, identify key gaps, and suggest advancements to better address critical issues related to changes in water resources that may threaten human development or the environment. Questions like, “Do we have less suitable drinking water now than we had 20...
Authors
Sarah M. Stackpoole, Gretchen P. Oelsner, Edward G. Stets, Jory Seth Hecht, Zachary Johnson, Anthony J. Tesoriero, Michelle A. Walvoord, Jeffrey G. Chanat, Krista A. Dunne, Phillip J. Goodling, Bruce D. Lindsey, Michael Meador, Sarah Spaulding
Evaluating drivers of hydrology, water quality, and benthic macroinvertebrates in streams of Fairfax County, Virginia, 2007–18
In 2007, the U.S. Geological Survey partnered with Fairfax County, Virginia, to establish a long-term water-resources monitoring program to evaluate the hydrology, water quality, and ecology of Fairfax County streams and the watershed-scale effects of management practices. Fairfax County uses a variety of management practices, policies, and programs to protect and restore its water...
Authors
James S. Webber, Jeffrey G. Chanat, Aaron J. Porter, John D. Jastram
Climate extremes as drivers of surface-water-quality trends in the United States
Surface-water quality can change in response to climate perturbations, such as changes in the frequency of heavy precipitation or droughts, through direct effects, such as dilution and concentration, and through physical processes, such as bank scour. Water quality might also change through indirect mechanisms, such as changing water demand or changes in runoff interaction with organic...
Authors
Karen R. Ryberg, Jeffrey G. Chanat
An approach for decomposing river water-quality trends into different flow classes
A number of statistical approaches have been developed to quantify the overall trend in river water quality, but most approaches are not intended for reporting separate trends for different flow conditions. We propose an approach called FN2Q, which is an extension of the flow-normalization (FN) procedure of the well-established WRTDS (“Weighted Regressions on Time, Discharge, and Season”...
Authors
Qian Zhang, James S. Webber, Doug L. Moyer, Jeffrey G. Chanat
Factors driving nutrient trends in streams of the Chesapeake Bay watershed
Despite decades of effort toward reducing nitrogen and phosphorus flux to Chesapeake Bay, water-quality and ecological responses in surface waters have been mixed. Recent research, however, provides useful insight into multiple factors complicating the understanding of nutrient trends in bay tributaries, which we review in this paper, as we approach a 2025 total maximum daily load (TMDL)...
Authors
Scott Ator, Joel Blomquist, James S. Webber, Jeffrey G. Chanat
Estimation bias in water-quality constituent concentrations and fluxes: A synthesis for Chesapeake Bay rivers and streams
Flux quantification for riverine water-quality constituents has been an active area of research. Statistical approaches are often employed to make estimation for days without observations. One such approach is the Weighted Regressions on Time, Discharge, and Season (WRTDS) method. While WRTDS has been used in many investigations, there is a general lack of effort to identify factors that...
Authors
Qian Zhang, Joel Blomquist, Doug L. Moyer, Jeffrey G. Chanat
Exploring drivers of regional water-quality change using differential spatially referenced regression – A pilot study in the Chesapeake Bay watershed
An understanding of riverine water-quality dynamics in regional mixed-land use watersheds is the foundation for advances in landscape biogeochemistry and informed land management. A differential implementation of the statistical/process-based model SPAtially Referenced Regressions on Watershed attributes (SPARROW; Smith et al., https://doi.org/10.1029/97wr02171) is proposed to...
Authors
Jeffrey G. Chanat, Guoxiang Yang
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...
Authors
Jeffrey G. Chanat, Douglas L. Moyer, Joel D. Blomquist, Kenneth E. Hyer, Michael J. Langland
Evaluation and application of regional turbidity-sediment regression models in Virginia
Conventional thinking has long held that turbidity-sediment surrogate-regression equations are site specific and that regression equations developed at a single monitoring station should not be applied to another station; however, few studies have evaluated this issue in a rigorous manner. If robust regional turbidity-sediment models can be developed successfully, their applications...
Authors
Kenneth Hyer, John D. Jastram, Douglas Moyer, James S. Webber, Jeffrey G. Chanat
Total nutrient and sediment loads, trends, yields, and nontidal water-quality indicators for selected nontidal stations, Chesapeake Bay Watershed, 1985–2011
The U.S. Geological Survey, in cooperation with Chesapeake Bay Program (CBP) partners, routinely reports long-term concentration trends and monthly and annual constituent loads for stream water-quality monitoring stations across the Chesapeake Bay watershed. This report documents flow-adjusted trends in sediment and total nitrogen and phosphorus concentrations for 31 stations in the...
Authors
Michael J. Langland, Joel D. Blomquist, Douglas Moyer, Kenneth Hyer, Jeffrey G. Chanat
Science and Products
Data to support Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies
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...
Climate, Landscape, and Water-Quality Metrics for Selected Watersheds in Fairfax County, Virginia, 2007-2018
This data release documents spatiotemporal water-quality, landscape, and climatic conditions in Fairfax County, Virginia from 2007 through 2018. These data were used to evaluate the water-quality and ecological condition of 20 Fairfax County watersheds monitored since 2007. Data include measures of water-quality, precipitation, air temperature, land use, land cover, wastewater and...
CAST Data Input Disaggregation from County and Land-River Segment Scale to National Hydrography Dataset Plus, Version 1.1
The detrimental effects of excess nutrients and sediment entering the Chesapeake Bay estuary from its watersheds have necessitated regulatory actions. Federally-mandated reductions are apportioned to bay jurisdictions based on the U.S. Environmental Protection Agency's Chesapeake Bay Time-Variable Watershed Model (CBPM). The Chesapeake Assessment Scenario Tool (CAST version CAST-19; cast...
Inputs and Selected Predictions of a Differential Spatially Referenced Regression Model for 20-year Changes in Total Nitrogen in the Chesapeake Bay Watershed
The core equations of the SPARROW model (Schwarz and others, 2006) were implemented in differential form using the R programming language (R Core Team, 2017), as the basis of a tool for empirically relating a regional pattern of changes in constituent flux, over a multi-year period, to spatially referenced changes in explanatory variables over the same period. A pilot implementation was...
Multidecadal Streamflow Trends and Ecological Flow Statistics at USGS Monitoring Stations within the Chesapeake Bay Watershed (1940-2018)
The hydrologic regime of rivers and streams is a major determinant of habitat quality for fish and aquatic invertebrates. Long-term streamflow data were compiled and multidecadal streamflow trends and ecological flow (EFlow) statistics were calculated in support of the United States Geological Survey (USGS) Chesapeake Bay Science Initiative toward understanding fish habitat and health in...
Nitrogen, Phosphorus, and Suspended-Sediment Loads and Trends measured at the Chesapeake Bay Nontidal Network Stations: Water Years 1985-2014
Nitrogen, phosphorus, and suspended-sediment loads, and changes in loads, in 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 2014. Nutrient and suspended-sediment loads and changes in loads were determined by applying a weighted regression approach called WRTDS...
Filter Total Items: 16
Evaluating water-quality trends in agricultural watersheds prioritized for management-practice implementation
Many agricultural watersheds rely on the voluntary use of management practices (MPs) to reduce nonpoint source nutrient and sediment loads; however, the water-quality effects of MPs are uncertain. We interpreted water-quality responses from as early as 1985 through 2020 in three agricultural Chesapeake Bay watersheds that were prioritized for MP implementation, namely, the Smith Creek...
Authors
James S. Webber, Jeffrey G. Chanat, John Clune, Olivia Devereux, Natalie Celeste Hall, Robert D. Sabo, Qian Zhang
Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies
Large multi-site trend studies provide an opportunity to evaluate progress of waterbodies towards water-quality goals across broad geographic areas. Such studies often aggregate the results of site-specific models and thus contend with evaluating each model for appropriate fit and statistical assumptions. We explored the use of four traditional machine learning models (logistic...
Authors
Jennifer C. Murphy, Jeffrey G. Chanat
Integrated water resources trend assessments: State of the science, challenges, and opportunities for advancement
Water is vital to human life and healthy ecosystems. Here we outline the current state of national-scale water resources trend assessments, identify key gaps, and suggest advancements to better address critical issues related to changes in water resources that may threaten human development or the environment. Questions like, “Do we have less suitable drinking water now than we had 20...
Authors
Sarah M. Stackpoole, Gretchen P. Oelsner, Edward G. Stets, Jory Seth Hecht, Zachary Johnson, Anthony J. Tesoriero, Michelle A. Walvoord, Jeffrey G. Chanat, Krista A. Dunne, Phillip J. Goodling, Bruce D. Lindsey, Michael Meador, Sarah Spaulding
Evaluating drivers of hydrology, water quality, and benthic macroinvertebrates in streams of Fairfax County, Virginia, 2007–18
In 2007, the U.S. Geological Survey partnered with Fairfax County, Virginia, to establish a long-term water-resources monitoring program to evaluate the hydrology, water quality, and ecology of Fairfax County streams and the watershed-scale effects of management practices. Fairfax County uses a variety of management practices, policies, and programs to protect and restore its water...
Authors
James S. Webber, Jeffrey G. Chanat, Aaron J. Porter, John D. Jastram
Climate extremes as drivers of surface-water-quality trends in the United States
Surface-water quality can change in response to climate perturbations, such as changes in the frequency of heavy precipitation or droughts, through direct effects, such as dilution and concentration, and through physical processes, such as bank scour. Water quality might also change through indirect mechanisms, such as changing water demand or changes in runoff interaction with organic...
Authors
Karen R. Ryberg, Jeffrey G. Chanat
An approach for decomposing river water-quality trends into different flow classes
A number of statistical approaches have been developed to quantify the overall trend in river water quality, but most approaches are not intended for reporting separate trends for different flow conditions. We propose an approach called FN2Q, which is an extension of the flow-normalization (FN) procedure of the well-established WRTDS (“Weighted Regressions on Time, Discharge, and Season”...
Authors
Qian Zhang, James S. Webber, Doug L. Moyer, Jeffrey G. Chanat
Factors driving nutrient trends in streams of the Chesapeake Bay watershed
Despite decades of effort toward reducing nitrogen and phosphorus flux to Chesapeake Bay, water-quality and ecological responses in surface waters have been mixed. Recent research, however, provides useful insight into multiple factors complicating the understanding of nutrient trends in bay tributaries, which we review in this paper, as we approach a 2025 total maximum daily load (TMDL)...
Authors
Scott Ator, Joel Blomquist, James S. Webber, Jeffrey G. Chanat
Estimation bias in water-quality constituent concentrations and fluxes: A synthesis for Chesapeake Bay rivers and streams
Flux quantification for riverine water-quality constituents has been an active area of research. Statistical approaches are often employed to make estimation for days without observations. One such approach is the Weighted Regressions on Time, Discharge, and Season (WRTDS) method. While WRTDS has been used in many investigations, there is a general lack of effort to identify factors that...
Authors
Qian Zhang, Joel Blomquist, Doug L. Moyer, Jeffrey G. Chanat
Exploring drivers of regional water-quality change using differential spatially referenced regression – A pilot study in the Chesapeake Bay watershed
An understanding of riverine water-quality dynamics in regional mixed-land use watersheds is the foundation for advances in landscape biogeochemistry and informed land management. A differential implementation of the statistical/process-based model SPAtially Referenced Regressions on Watershed attributes (SPARROW; Smith et al., https://doi.org/10.1029/97wr02171) is proposed to...
Authors
Jeffrey G. Chanat, Guoxiang Yang
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...
Authors
Jeffrey G. Chanat, Douglas L. Moyer, Joel D. Blomquist, Kenneth E. Hyer, Michael J. Langland
Evaluation and application of regional turbidity-sediment regression models in Virginia
Conventional thinking has long held that turbidity-sediment surrogate-regression equations are site specific and that regression equations developed at a single monitoring station should not be applied to another station; however, few studies have evaluated this issue in a rigorous manner. If robust regional turbidity-sediment models can be developed successfully, their applications...
Authors
Kenneth Hyer, John D. Jastram, Douglas Moyer, James S. Webber, Jeffrey G. Chanat
Total nutrient and sediment loads, trends, yields, and nontidal water-quality indicators for selected nontidal stations, Chesapeake Bay Watershed, 1985–2011
The U.S. Geological Survey, in cooperation with Chesapeake Bay Program (CBP) partners, routinely reports long-term concentration trends and monthly and annual constituent loads for stream water-quality monitoring stations across the Chesapeake Bay watershed. This report documents flow-adjusted trends in sediment and total nitrogen and phosphorus concentrations for 31 stations in the...
Authors
Michael J. Langland, Joel D. Blomquist, Douglas Moyer, Kenneth Hyer, Jeffrey G. Chanat