Christopher T Green, Ph.D.
Christopher Green is a Research Hydrologist with the USGS Water Resources Mission Area.
Research Interests
- Flow and reactive transport in complex geological media
- Nitrogen cycling and fluxes in groundwater in agricultural areas
- Flow and solute transport in the unsaturated zone
- Gas transport in the unsaturated zone
- Effects of biofuels crops on groundwater quality
Science and Products
Histogram-based gradient boosted regression tree model of mean ages of shallow well samples in the Great Lakes Basin, USA
Green and others (2021) developed a gradient boosted regression tree model to predict the mean groundwater age, or travel time, for shallow wells across a portion of the Great Lakes basin in the United States. Their study applied machine learning methods to predict ages in wells using well construction, well chemistry, and landscape characteristics. For a dataset of age tracers in 961 water sample
Multivariate regression model for predicting oxygen reduction rates in groundwater for the State of Wisconsin
A multivariate regression model was developed to predict zero-order oxygen reduction rates (mg/L/yr) in aquifers across the State of Wisconsin. The model used a combination of dissolved oxygen concentrations and mean groundwater ages estimated with sampled age tracers from wells in the U.S. Geological Survey National Water Information System and previously published project reports from state agen
Compiled age tracer and redox chemistry data for the State of Wisconsin, 1987-2009
This data set was compiled to support the development of a model of oxygen reduction rates in Wisconsin groundwater wells; a model which is part of a Groundwater Nitrate Decision Support Tool for Wisconsin. Data were compiled from previously published studies with data collection from 1987 to 2009. Only data describing redox condition, groundwater age, depth to water, and well construction were co
Data to support a Groundwater Nitrate Decision Support Tool for Wisconsin
A Groundwater Nitrate Decision Support Tool (GW-NDST) for wells in Wisconsin was developed to assist resource managers with assessing how legacy and possible future nitrate leaching rates, combined with groundwater lag times and potential denitrification, influence nitrate concentrations in wells (Juckem et al. 2024). Running and using the GW-NDST software involves downloading the software code (v
Soil sample data for four uranium mine sites, Mohave County, Arizona, April and November 2018
This U.S. Geological Survey data release is a spreadsheet containing soil-profile measurements of ambient spring and fall water-potential and water-content conditions, and physical and chemical properties for four mine sites, Mohave County, Arizona, April and November 2018. The four mines sampled in both April and November were Kanab North (native soil and reclaimed soil), EZ2 (native soil), Arizo
Data Release for Metamodeling and Mapping of Nitrate Flux in the Unsaturated Zone and Groundwater, Wisconsin, USA
Widespread nitrate contamination of groundwater in agricultural areas poses a major challenge to sustainable water resources. Efficient analysis of nitrate fluxes across large regions also remains difficult. This study introduces a method of characterizing nitrate transport processes continuously across regional unsaturated zones and groundwater based on surrogate, machine-learning metamodels of a
Filter Total Items: 45
Design and calibration of a nitrate decision support tool for groundwater wells in Wisconsin, USA
This paper describes development of a nitrate decision support tool for groundwater wells (GW-NDST) that combines nitrate leaching and groundwater lag-times to compute well concentrations. The GW-NDST uses output from support models that simulate leached nitrate, groundwater age distributions, and nitrate reduction rates. The support models are linked through convolution to simulate nitrate transp
Authors
Paul F. Juckem, Nicholas Corson-Dosch, Laura A. Schachter, Christopher Green, Kelsie M. Ferin, Eric G. Booth, Christopher J. Kucharik, Brian P. Austin, Leon J. Kauffman
Knowledge gaps and opportunities in water-quality drivers of aquatic ecosystem health
This report identifies key scientific gaps that limit our ability to predict water quality effects on health of aquatic ecosystems and proposes approaches to address those gaps. Topics considered include (1) coupled nutrient-carbon cycle processes and related ecological-flow-regime drivers of ecosystem health, (2) anthropogenic and geogenic toxin bioexposure, (3) fine sediment drivers of aquatic e
Knowledge gaps and opportunities for understanding water-quality processes affecting water availability for beneficial uses
This report describes scientific gaps that limit our ability to predict water-quality effects on water availability for beneficial uses across the United States. Water-quality constituents considered in the report include salinity, geogenic constituents, contaminants of emerging concern, and nitrogen. For each constituent, there is a selection of scientific gaps, approaches, and outcomes to help g
Prioritizing river basins for nutrient studies
Increases in fluxes of nitrogen (N) and phosphorus (P) in the environment have led to negative impacts affecting drinking water, eutrophication, harmful algal blooms, climate change, and biodiversity loss. Because of the importance, scale, and complexity of these issues, it may be useful to consider methods for prioritizing nutrient research in representative drainage basins within a regional or n
Authors
Anthony J. Tesoriero, Dale M. Robertson, Christopher Green, John K. Böhlke, Judson Harvey, Sharon L. Qi
Long short-term memory models to quantify long-term evolution of streamflow discharge and groundwater depth in Alabama
Long short-term memory (LSTM) models have been shown to be efficient for rainfall-runoff modeling, and to a lesser extent, for groundwater depth forecasting. In this study, LSTMs were applied to quantify the spatiotemporal evolution of surface and subsurface hydrographs in Alabama in the Southeastern United States, where water sustainability has not been fully quantified across spatiotemporal scal
Authors
Hossein Gholizadeh, Yong Zhang, Jonathan Frame, Xiufen Gu, Christopher Green
Time-fractional flow equations (t-FFEs) to upscale transient groundwater flow characterized by temporally non-darcian flow due to medium heterogeneity
Upscaling groundwater flow is a fundamental challenge in hydrogeology. This study proposed time-fractional flow equations (t-FFEs) for upscaling long-term, transient groundwater flow and propagation of pressure heads in heterogeneous media. Monte Carlo simulations showed that, with increasing variance and correlation of the hydraulic conductivity (K), flow dynamics gradually deviated from Darcian
Authors
Yuan Xia, Yong Zhang, Christopher Green, Graham Fogg
Machine learning predictions of mean ages of shallow well samples in the Great Lakes Basin, USA
The travel time or “age” of groundwater affects catchment responses to hydrologic changes, geochemical reactions, and time lags between management actions and responses at down-gradient streams and wells. Use of atmospheric tracers has facilitated the characterization of groundwater ages, but most wells lack such measurements. This study applied machine learning to predict ages in wells across a l
Authors
Christopher Green, Katherine Marie Ransom, Bernard T. Nolan, Lixia Liao, Thomas Harter
Co-transport of biogenic nano-hydroxyapatite and Pb(II) in saturated sand columns: Controlling factors and stochastic modeling
Biogenic nano-hydroxyapatite (bio-nHAP) has recently gained great interest in many domains, especially in the remediation of heavy metal-contaminated soil, due to its high reactivity, low cost, and eco-friendly nature. The co-transport and reaction of bio-nHAP with Pb(II) in saturated porous media, however, are not well understood. This work investigated the effects of ionic strength (IS), ionic c
Authors
Dongbao Zhou, Xuan Han, Yong Zhang, Wei Wei, Christopher Green, HongGuang Sun, Chunmiao Zheng
Complexity of groundwater age mixing near a seawater intrusion zone based on multiple tracers and Bayesian inference
Aquifer flow systems near seawater interfaces can be complicated by density-driven flows and the formation of stagnation zones, which inevitably introduces uncertainty into groundwater age-dating. While age-dating has proved effective to understand the seawater intrusion and aquifer salinization process in coastal aquifers, further efforts are needed to propagate model and data uncertainty to the
Authors
YeoJin Ju, Arash Massoudieh, Christopher Green, Kang-Kun Lee, Dugin Kaown
Spatial fingerprinting of biogenic and anthropogenic volatile organic compounds in an arid unsaturated zone
Subsurface volatile organic compounds (VOCs) can pose risks to human and environmental health and mediate biological processes. VOCs have both anthropogenic and biogenic origins, but the relative importance of these sources has not been explored in subsurface environments. This study synthesizes 17 years of VOC data from the Amargosa Desert Research Site (ADRS) with the goal of improving understan
Authors
Christopher Green, Wentai Luo, Christopher H. Conaway, Karl B. Haase, Ronald J. Baker, Brian J. Andraski
Comparison of groundwater age models for assessing nitrate loading, transport pathways, and management options in a complex aquifer system
In an aquifer system with complex hydrogeology, mixing of groundwater with different ages could occur associated with various flow pathways. In this study, we applied different groundwater age estimation techniques (lumped parameter model, and numerical model) to characterize groundwater age distributions and the major pathways of nitrate contamination in the Gosan agricultural field, Jeju Island.
Authors
E.H. Koh, E. Lee, D. Kaown, Christopher Green, D.C. Koh, K.K Lee, S.H. Lee
Stratification of reactivity determines nitrate removal in groundwater
Biogeochemical reactions occur unevenly in space and time, but this heterogeneity is often simplified as a linear average due to sparse data, especially in subsurface environments where access is limited. For example, little is known about the spatial variability of groundwater denitrification, an important process in removing nitrate originating from agriculture and land use conversion. Informati
Authors
Tamara Kolbe, Jean-Raynald de Dreuzy, Benjamin Abbott, Luc Aquilina, Tristan Babey, Christopher Green, Jan Fleckenstein, Thierry Labasque, Anniet M Laverman, Jean Marçais, Stefan Peiffer, Zahra Thomas, Gilles Pinay
GW-NDST software v 1.1.1
This version 1.1.1 release of the Groundwater Nitrate Decision Support Tool (GW-NDST) for Wisconsin supersedes the version 1.1.0 release. This version 1.1.1 release includes updated instructions in the readme file and fixes minor bugs.
GW-NDST software v 1.1.0
Official version 1.1.0 software release of the Groundwater-Nitrate Decision Support Tool (GW-NDST) for Wisconsin. This release (v1.1.0) is matched with and described by Juckem, P.F., Corson-Dosch, N.T., Schachter, L.A., Green, C.T., Ferin, K.M., Booth, E.G., Kucharik, C.J., Austin, B.P., and Kauffman, L.J., 2024, Design and calibration of a Nitrate Decision Support Tool for Groundwater wells in W
NO3GWT version 1.0.0
A groundwater Nitrate Decision Support Tool (GW-NDST) for wells in Wisconsin was developed to assist resource managers with assessing how legacy and possible future nitrate leaching rates, combined with groundwater lag times and potential denitrification, influence nitrate concentrations in wells (Juckem et al. 2024). The GW-NDST was reviewed and approved by the journal via this official USGS appr
Science and Products
Histogram-based gradient boosted regression tree model of mean ages of shallow well samples in the Great Lakes Basin, USA
Green and others (2021) developed a gradient boosted regression tree model to predict the mean groundwater age, or travel time, for shallow wells across a portion of the Great Lakes basin in the United States. Their study applied machine learning methods to predict ages in wells using well construction, well chemistry, and landscape characteristics. For a dataset of age tracers in 961 water sample
Multivariate regression model for predicting oxygen reduction rates in groundwater for the State of Wisconsin
A multivariate regression model was developed to predict zero-order oxygen reduction rates (mg/L/yr) in aquifers across the State of Wisconsin. The model used a combination of dissolved oxygen concentrations and mean groundwater ages estimated with sampled age tracers from wells in the U.S. Geological Survey National Water Information System and previously published project reports from state agen
Compiled age tracer and redox chemistry data for the State of Wisconsin, 1987-2009
This data set was compiled to support the development of a model of oxygen reduction rates in Wisconsin groundwater wells; a model which is part of a Groundwater Nitrate Decision Support Tool for Wisconsin. Data were compiled from previously published studies with data collection from 1987 to 2009. Only data describing redox condition, groundwater age, depth to water, and well construction were co
Data to support a Groundwater Nitrate Decision Support Tool for Wisconsin
A Groundwater Nitrate Decision Support Tool (GW-NDST) for wells in Wisconsin was developed to assist resource managers with assessing how legacy and possible future nitrate leaching rates, combined with groundwater lag times and potential denitrification, influence nitrate concentrations in wells (Juckem et al. 2024). Running and using the GW-NDST software involves downloading the software code (v
Soil sample data for four uranium mine sites, Mohave County, Arizona, April and November 2018
This U.S. Geological Survey data release is a spreadsheet containing soil-profile measurements of ambient spring and fall water-potential and water-content conditions, and physical and chemical properties for four mine sites, Mohave County, Arizona, April and November 2018. The four mines sampled in both April and November were Kanab North (native soil and reclaimed soil), EZ2 (native soil), Arizo
Data Release for Metamodeling and Mapping of Nitrate Flux in the Unsaturated Zone and Groundwater, Wisconsin, USA
Widespread nitrate contamination of groundwater in agricultural areas poses a major challenge to sustainable water resources. Efficient analysis of nitrate fluxes across large regions also remains difficult. This study introduces a method of characterizing nitrate transport processes continuously across regional unsaturated zones and groundwater based on surrogate, machine-learning metamodels of a
Filter Total Items: 45
Design and calibration of a nitrate decision support tool for groundwater wells in Wisconsin, USA
This paper describes development of a nitrate decision support tool for groundwater wells (GW-NDST) that combines nitrate leaching and groundwater lag-times to compute well concentrations. The GW-NDST uses output from support models that simulate leached nitrate, groundwater age distributions, and nitrate reduction rates. The support models are linked through convolution to simulate nitrate transp
Authors
Paul F. Juckem, Nicholas Corson-Dosch, Laura A. Schachter, Christopher Green, Kelsie M. Ferin, Eric G. Booth, Christopher J. Kucharik, Brian P. Austin, Leon J. Kauffman
Knowledge gaps and opportunities in water-quality drivers of aquatic ecosystem health
This report identifies key scientific gaps that limit our ability to predict water quality effects on health of aquatic ecosystems and proposes approaches to address those gaps. Topics considered include (1) coupled nutrient-carbon cycle processes and related ecological-flow-regime drivers of ecosystem health, (2) anthropogenic and geogenic toxin bioexposure, (3) fine sediment drivers of aquatic e
Knowledge gaps and opportunities for understanding water-quality processes affecting water availability for beneficial uses
This report describes scientific gaps that limit our ability to predict water-quality effects on water availability for beneficial uses across the United States. Water-quality constituents considered in the report include salinity, geogenic constituents, contaminants of emerging concern, and nitrogen. For each constituent, there is a selection of scientific gaps, approaches, and outcomes to help g
Prioritizing river basins for nutrient studies
Increases in fluxes of nitrogen (N) and phosphorus (P) in the environment have led to negative impacts affecting drinking water, eutrophication, harmful algal blooms, climate change, and biodiversity loss. Because of the importance, scale, and complexity of these issues, it may be useful to consider methods for prioritizing nutrient research in representative drainage basins within a regional or n
Authors
Anthony J. Tesoriero, Dale M. Robertson, Christopher Green, John K. Böhlke, Judson Harvey, Sharon L. Qi
Long short-term memory models to quantify long-term evolution of streamflow discharge and groundwater depth in Alabama
Long short-term memory (LSTM) models have been shown to be efficient for rainfall-runoff modeling, and to a lesser extent, for groundwater depth forecasting. In this study, LSTMs were applied to quantify the spatiotemporal evolution of surface and subsurface hydrographs in Alabama in the Southeastern United States, where water sustainability has not been fully quantified across spatiotemporal scal
Authors
Hossein Gholizadeh, Yong Zhang, Jonathan Frame, Xiufen Gu, Christopher Green
Time-fractional flow equations (t-FFEs) to upscale transient groundwater flow characterized by temporally non-darcian flow due to medium heterogeneity
Upscaling groundwater flow is a fundamental challenge in hydrogeology. This study proposed time-fractional flow equations (t-FFEs) for upscaling long-term, transient groundwater flow and propagation of pressure heads in heterogeneous media. Monte Carlo simulations showed that, with increasing variance and correlation of the hydraulic conductivity (K), flow dynamics gradually deviated from Darcian
Authors
Yuan Xia, Yong Zhang, Christopher Green, Graham Fogg
Machine learning predictions of mean ages of shallow well samples in the Great Lakes Basin, USA
The travel time or “age” of groundwater affects catchment responses to hydrologic changes, geochemical reactions, and time lags between management actions and responses at down-gradient streams and wells. Use of atmospheric tracers has facilitated the characterization of groundwater ages, but most wells lack such measurements. This study applied machine learning to predict ages in wells across a l
Authors
Christopher Green, Katherine Marie Ransom, Bernard T. Nolan, Lixia Liao, Thomas Harter
Co-transport of biogenic nano-hydroxyapatite and Pb(II) in saturated sand columns: Controlling factors and stochastic modeling
Biogenic nano-hydroxyapatite (bio-nHAP) has recently gained great interest in many domains, especially in the remediation of heavy metal-contaminated soil, due to its high reactivity, low cost, and eco-friendly nature. The co-transport and reaction of bio-nHAP with Pb(II) in saturated porous media, however, are not well understood. This work investigated the effects of ionic strength (IS), ionic c
Authors
Dongbao Zhou, Xuan Han, Yong Zhang, Wei Wei, Christopher Green, HongGuang Sun, Chunmiao Zheng
Complexity of groundwater age mixing near a seawater intrusion zone based on multiple tracers and Bayesian inference
Aquifer flow systems near seawater interfaces can be complicated by density-driven flows and the formation of stagnation zones, which inevitably introduces uncertainty into groundwater age-dating. While age-dating has proved effective to understand the seawater intrusion and aquifer salinization process in coastal aquifers, further efforts are needed to propagate model and data uncertainty to the
Authors
YeoJin Ju, Arash Massoudieh, Christopher Green, Kang-Kun Lee, Dugin Kaown
Spatial fingerprinting of biogenic and anthropogenic volatile organic compounds in an arid unsaturated zone
Subsurface volatile organic compounds (VOCs) can pose risks to human and environmental health and mediate biological processes. VOCs have both anthropogenic and biogenic origins, but the relative importance of these sources has not been explored in subsurface environments. This study synthesizes 17 years of VOC data from the Amargosa Desert Research Site (ADRS) with the goal of improving understan
Authors
Christopher Green, Wentai Luo, Christopher H. Conaway, Karl B. Haase, Ronald J. Baker, Brian J. Andraski
Comparison of groundwater age models for assessing nitrate loading, transport pathways, and management options in a complex aquifer system
In an aquifer system with complex hydrogeology, mixing of groundwater with different ages could occur associated with various flow pathways. In this study, we applied different groundwater age estimation techniques (lumped parameter model, and numerical model) to characterize groundwater age distributions and the major pathways of nitrate contamination in the Gosan agricultural field, Jeju Island.
Authors
E.H. Koh, E. Lee, D. Kaown, Christopher Green, D.C. Koh, K.K Lee, S.H. Lee
Stratification of reactivity determines nitrate removal in groundwater
Biogeochemical reactions occur unevenly in space and time, but this heterogeneity is often simplified as a linear average due to sparse data, especially in subsurface environments where access is limited. For example, little is known about the spatial variability of groundwater denitrification, an important process in removing nitrate originating from agriculture and land use conversion. Informati
Authors
Tamara Kolbe, Jean-Raynald de Dreuzy, Benjamin Abbott, Luc Aquilina, Tristan Babey, Christopher Green, Jan Fleckenstein, Thierry Labasque, Anniet M Laverman, Jean Marçais, Stefan Peiffer, Zahra Thomas, Gilles Pinay
GW-NDST software v 1.1.1
This version 1.1.1 release of the Groundwater Nitrate Decision Support Tool (GW-NDST) for Wisconsin supersedes the version 1.1.0 release. This version 1.1.1 release includes updated instructions in the readme file and fixes minor bugs.
GW-NDST software v 1.1.0
Official version 1.1.0 software release of the Groundwater-Nitrate Decision Support Tool (GW-NDST) for Wisconsin. This release (v1.1.0) is matched with and described by Juckem, P.F., Corson-Dosch, N.T., Schachter, L.A., Green, C.T., Ferin, K.M., Booth, E.G., Kucharik, C.J., Austin, B.P., and Kauffman, L.J., 2024, Design and calibration of a Nitrate Decision Support Tool for Groundwater wells in W
NO3GWT version 1.0.0
A groundwater Nitrate Decision Support Tool (GW-NDST) for wells in Wisconsin was developed to assist resource managers with assessing how legacy and possible future nitrate leaching rates, combined with groundwater lag times and potential denitrification, influence nitrate concentrations in wells (Juckem et al. 2024). The GW-NDST was reviewed and approved by the journal via this official USGS appr