Sydney S Foks
Sydney Foks is a hydrologist with the USGS Water Resources Mission Area.
Sydney Foks is a hydrologist with the Analysis and Prediction Branch of the Integrated Modeling and Prediction Division - Water Mission Area.
Education
Colorado School of Mines, Golden, CO Hydrology M.S. 2015
Western Washington University, Bellingham, WA Geology B.S. 2011
Professional Appointments
Hydrologist, Integrated Modeling and Prediction Division, USGS, Denver, CO (2018-current)
Hydrologist, Laboratory and Analytical Services Division, USGS, Boulder, CO (2017-2018)
Hydrologist, National Research Program, USGS, Boulder, CO (2015-2017)
Research Assistant, Colorado School of Mines, Golden, CO (2014-2015)
Program Assistant, Colorado State University, Fort Collins, CO (2013-2014)
Student Trainee - Hydrology, National Research Program, USGS, Boulder, CO (2012-2015)
National Association of Geoscience Teachers (NAGT) Student Trainee, National Research Program, USGS, Boulder, CO (2012)
Geologist Intern, CH2M Hill Plateau Remediation Company, U.S. Department of Energy Hanford Site, Richland, WA (2010)
Science and Products
Daily streamflow performance benchmark defined by the standard statistical suite (v1.0) for the National Water Model Retrospective (v2.1) at benchmark streamflow locations (ver. 2.0, December 2022)
This data release contains the standard statistical suite (version 1.0) daily streamflow performance benchmark results for the National Water Model Retrospective (v2.1) at streamflow benchmark locations (version 1.0) as defined by Foks and others (2022). Modeled hourly timesteps were converted to mean daily timesteps. Model error was determined by evaluating predicted daily mean streamflow versus
Daily streamflow performance benchmark defined by the standard statistical suite (v1.0) for the National Hydrologic Model application of the Precipitation-Runoff Modeling System (v1 byObs Muskingum) at benchmark streamflow locations in the conterminous Un
This data release contains the standard statistical suite (version 1.0) daily streamflow performance benchmark results for the National Hydrologic Model Infrastructure application of the Precipitation-Runoff Modeling System (NHM-PRMS) version 1 "byObs" calibration with Muskingum routing computed at streamflow benchmark locations defined by Foks and others (2022). Model error was determined by eval
Daily streamflow performance benchmark defined by D-score (v0.1) for the National Hydrologic Model application of the Precipitation-Runoff Modeling System (v1 byObs Muskingum) at benchmark streamflow locations
This data release contains the D-score (version 0.1) daily streamflow performance benchmark results for the National Hydrologic Model Infrastructure application of the Precipitation-Runoff Modeling System (NHM) version 1 "byObs" calibration with Muskingum routing computed at streamflow benchmark locations (version 1) as defined by Foks and others (2022). Model error was determined by evaluating pr
Streamflow benchmark locations for hydrologic model evaluation within the conterminous United States (cobalt gages)
A list of stream gages within the conterminous United States that will serve as the initial list of sites (version 1.0) used for streamflow benchmarking of hydrologic models. Sites within this list were chosen based on their presence in the GAGES-II dataset, their availability of modeled streamflow data from the most recent version of the National Hydrologic Model application of Precipitation-Runo
Monthly estimates of natural baseflow for 15,866 stream reaches, defined by the National Hydrography Dataset Plus Version 2.0 (NHDPlusV2), in the Delaware River Basin for the period 1950-2015
This metadata record describes monthly estimates of natural baseflow for 15,866 stream reaches, defined by the National Hydrography Dataset Plus Version 2.0 (NHDPlusV2), in the Delaware River Basin for the period 1950-2015. A statistical machine learning technique - random forest modeling (Liaw and Wiener, 2018; R Core Team, 2020) - was applied to estimate natural flows using about 150 potential p
Geospatial Fabric for National Hydrologic Modeling, version 1.1
This U.S. Geological Survey (USGS) data release consists of two hydrographic datasets with spatial modeling units consistent with the National Hydrologic Model (NHM) Geospatial Fabric for National Hydrologic Modeling (abbreviated within this document as GFv1, Viger and Bock, 2014). The two datasets found as subpages to this landing page are 1) the GIS (geographic information system) features of th
Water quality and gas fluxes of Interior Alaska (2014-2018)
This product consists of multiple tabular datasets and associated metadata of water quality information related to rivers, streams, and lakes in the Yukon River watershed between 2014 and 2018. This data release is apart of the National Aeronautics and Space Administration (NASA) funded Arctic-Boreal Vulnerability Experiment (ABoVE) and is an assessment of water quality and greenhouse gas fluxes w
Daily-timestep and monthly-timestep estimates of baseflow at 49 reference stream gages located within 25 miles of the Delaware River basin watershed boundary for the years 1950 through 2015
This USGS data release contains daily-timestep and monthly-timestep estimates of baseflow at 49 reference stream gages located within 25 miles of the Delaware River basin watershed boundary. Estimates are provided for the available period of record of streamflow data at each site between 1950 and 2015. A two-parameter recursive digital filter was used to estimate baseflow at the selected stream ga
National Hydrologic Model Alaska Domain parameter database, version 1
This data release contains input data for hydrologic simulations of the Alaska Domain application of the U.S. Geological Survey (USGS) Precipitation Runoff Modelling System (PRMS) as implemented in the National Hydrologic Model (NHM) infrastructure (Regan and others, 2018). The NHM Alaska Domain parameter database consists of 114 parameter files in ASCII format (CSV), two files needed to run the A
Geospatial Fabric for the National Hydrologic Model Alaska Domain, version 1
This metadata record documents a geospatial dataset for the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS) used to drive the National Hydrologic Model (NHM). The Alaska Geospatial Fabric v1 is the spatial representation of the hydrologic response units (HRUs) used for the PRMS NHM Alaska domain. These HRUs were generated using the twelve-digit Hydrologic Unit Code (HUC12) water
Base flow estimation via optimal hydrograph separation at CONUS watersheds and comparison to the National Hydrologic Model - Precipitation-Runoff Modeling System by HRU calibrated version
Optimal hydrograph separation (OHS) is a two-component, hydrograph separation method that uses a two-parameter, recursive digital filter (RDF) constrained via chemical mass balance to estimate the base flow contribution to a stream or river (Rimmer and Hartman, 2014; Raffensperger et al., 2017). A recursive digital filter distinguishes between high-frequency and low-frequency discharge data within
Water quality, quantity, and gas fluxes of the Upper Mississippi River basin (WY 2012-2016)
This product consists of one tabular dataset and associated metadata of water quality information related to rivers, streams, and reservoirs in the Upper Mississippi River watershed between 2012 and 2016. This data release is a part of a national assessment of freshwater aquatic carbon fluxes. Data consist of organic and inorganic carbon related species, carbon dioxide and methane gas fluxes calcu
Benchmarking high-resolution hydrologic model performance of long-term retrospective streamflow simulations in the contiguous United States
Because use of high-resolution hydrologic models is becoming more widespread and estimates are made over large domains, there is a pressing need for systematic evaluation of their performance. Most evaluation efforts to date have focused on smaller basins that have been relatively undisturbed by human activity, but there is also a need to benchmark model performance more comprehensively, including
Authors
Erin Towler, Sydney Foks, Aubrey L Dugger, Jesse E. Dickinson, Hedeff I. Essaid, David Gochis, Roland J. Viger, Yongxin Zhang
Dissolved carbon export by large river systems is influenced by source area heterogeneity
Rivers and streams export inorganic and organic carbon derived from contributing landscapes and so downstream carbon fluxes are important quantitative indicators of change in ecosystem function and for the full accounting of terrestrial carbon budgets. Carbon concentration-discharge (C-Q) relationships in rivers provide important information about carbon source and behavior in watersheds and are u
Authors
Edward G. Stets, Robert G. Striegl, Kimberly Wickland, Mark Dornblaser, Sydney Foks
Mean squared error, deconstructed
As science becomes increasingly cross-disciplinary and scientific models become increasingly cross-coupled, standardized practices of model evaluation are more important than ever. For normally distributed data, mean squared error (MSE) is ideal as an objective measure of model performance, but it gives little insight into what aspects of model performance are “good” or “bad.” This apparent weakne
Authors
Timothy O. Hodson, Thomas M. Over, Sydney Foks
Stream dissolved organic matter in permafrost regions shows surprising compositional similarities but negative priming and nutrient effects
Permafrost degradation is delivering bioavailable dissolved organic matter (DOM) and inorganic nutrients to surface water networks. While these permafrost subsidies represent a small portion of total fluvial DOM and nutrient fluxes, they could influence food webs and net ecosystem carbon balance via priming or nutrient effects that destabilize background DOM. We investigated how addition of biolab
Authors
Ethan Wologo, Sarah Shakil, Scott Zolkos, Sadie R. Textor, Stephanie Ewing, Jane Klassen, Robert G. M. Spencer, David C. Podgorski, Suzanne E. Tank, Michelle Baker, Jonathan A. O'Donnell, Kimberly P. Wickland, Sydney Foks, Jay P. Zarnetske, Joseph Lee-Cullin, Futing Liu, Yuanhe Yang, Pirkko Kortelainen, Jaana Kolehmainen, Joshua F. Dean, Jorien E. Vonk, Robert M. Holmes, Gilles Pinay, Michaela M. Powell, Jansen Howe, Rebecca J. Frei, Samuel P. Bratsman, Benjamin W. Abbott
Estimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models
Optimal hydrograph separation (OHS) uses a two-parameter recursive digital filter that applies specific conductance mass-balance constraints to estimate the base flow contribution to total streamflow at stream gages where discharge and specific conductance are measured. OHS was applied to U.S. Geological Survey (USGS) stream gages across the conterminous United States to examine the range/distribu
Authors
Sydney Foks, Jeff P. Raffensperger, Colin A. Penn, Jessica M. Driscoll
Influence of climate on alpine stream chemistry and water sources
The resilience of alpine/subalpine watersheds may be viewed as the resistance of streamflow or stream chemistry to change under varying climatic conditions, which is governed by the relative size (volume) and transit time of surface and subsurface water sources. Here, we use end‐member mixing analysis in Andrews Creek, an alpine stream in Rocky Mountain National Park, Colorado, from water year 199
Authors
Sydney Foks, Edward G. Stets, Kamini Singha, David W. Clow
Hydrologic Model Evaluation and Time-Series Tools (HyMETT) R-package
Hydrologic Model and Evaluation Time-series Tools (HyMETT) software facilitates the analysis and evaluation of hydrologic model output and time-series data with functions focused on comparison of modeled and observed data, period-of-record statistics, and trends.
Science and Products
Daily streamflow performance benchmark defined by the standard statistical suite (v1.0) for the National Water Model Retrospective (v2.1) at benchmark streamflow locations (ver. 2.0, December 2022)
This data release contains the standard statistical suite (version 1.0) daily streamflow performance benchmark results for the National Water Model Retrospective (v2.1) at streamflow benchmark locations (version 1.0) as defined by Foks and others (2022). Modeled hourly timesteps were converted to mean daily timesteps. Model error was determined by evaluating predicted daily mean streamflow versus
Daily streamflow performance benchmark defined by the standard statistical suite (v1.0) for the National Hydrologic Model application of the Precipitation-Runoff Modeling System (v1 byObs Muskingum) at benchmark streamflow locations in the conterminous Un
This data release contains the standard statistical suite (version 1.0) daily streamflow performance benchmark results for the National Hydrologic Model Infrastructure application of the Precipitation-Runoff Modeling System (NHM-PRMS) version 1 "byObs" calibration with Muskingum routing computed at streamflow benchmark locations defined by Foks and others (2022). Model error was determined by eval
Daily streamflow performance benchmark defined by D-score (v0.1) for the National Hydrologic Model application of the Precipitation-Runoff Modeling System (v1 byObs Muskingum) at benchmark streamflow locations
This data release contains the D-score (version 0.1) daily streamflow performance benchmark results for the National Hydrologic Model Infrastructure application of the Precipitation-Runoff Modeling System (NHM) version 1 "byObs" calibration with Muskingum routing computed at streamflow benchmark locations (version 1) as defined by Foks and others (2022). Model error was determined by evaluating pr
Streamflow benchmark locations for hydrologic model evaluation within the conterminous United States (cobalt gages)
A list of stream gages within the conterminous United States that will serve as the initial list of sites (version 1.0) used for streamflow benchmarking of hydrologic models. Sites within this list were chosen based on their presence in the GAGES-II dataset, their availability of modeled streamflow data from the most recent version of the National Hydrologic Model application of Precipitation-Runo
Monthly estimates of natural baseflow for 15,866 stream reaches, defined by the National Hydrography Dataset Plus Version 2.0 (NHDPlusV2), in the Delaware River Basin for the period 1950-2015
This metadata record describes monthly estimates of natural baseflow for 15,866 stream reaches, defined by the National Hydrography Dataset Plus Version 2.0 (NHDPlusV2), in the Delaware River Basin for the period 1950-2015. A statistical machine learning technique - random forest modeling (Liaw and Wiener, 2018; R Core Team, 2020) - was applied to estimate natural flows using about 150 potential p
Geospatial Fabric for National Hydrologic Modeling, version 1.1
This U.S. Geological Survey (USGS) data release consists of two hydrographic datasets with spatial modeling units consistent with the National Hydrologic Model (NHM) Geospatial Fabric for National Hydrologic Modeling (abbreviated within this document as GFv1, Viger and Bock, 2014). The two datasets found as subpages to this landing page are 1) the GIS (geographic information system) features of th
Water quality and gas fluxes of Interior Alaska (2014-2018)
This product consists of multiple tabular datasets and associated metadata of water quality information related to rivers, streams, and lakes in the Yukon River watershed between 2014 and 2018. This data release is apart of the National Aeronautics and Space Administration (NASA) funded Arctic-Boreal Vulnerability Experiment (ABoVE) and is an assessment of water quality and greenhouse gas fluxes w
Daily-timestep and monthly-timestep estimates of baseflow at 49 reference stream gages located within 25 miles of the Delaware River basin watershed boundary for the years 1950 through 2015
This USGS data release contains daily-timestep and monthly-timestep estimates of baseflow at 49 reference stream gages located within 25 miles of the Delaware River basin watershed boundary. Estimates are provided for the available period of record of streamflow data at each site between 1950 and 2015. A two-parameter recursive digital filter was used to estimate baseflow at the selected stream ga
National Hydrologic Model Alaska Domain parameter database, version 1
This data release contains input data for hydrologic simulations of the Alaska Domain application of the U.S. Geological Survey (USGS) Precipitation Runoff Modelling System (PRMS) as implemented in the National Hydrologic Model (NHM) infrastructure (Regan and others, 2018). The NHM Alaska Domain parameter database consists of 114 parameter files in ASCII format (CSV), two files needed to run the A
Geospatial Fabric for the National Hydrologic Model Alaska Domain, version 1
This metadata record documents a geospatial dataset for the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS) used to drive the National Hydrologic Model (NHM). The Alaska Geospatial Fabric v1 is the spatial representation of the hydrologic response units (HRUs) used for the PRMS NHM Alaska domain. These HRUs were generated using the twelve-digit Hydrologic Unit Code (HUC12) water
Base flow estimation via optimal hydrograph separation at CONUS watersheds and comparison to the National Hydrologic Model - Precipitation-Runoff Modeling System by HRU calibrated version
Optimal hydrograph separation (OHS) is a two-component, hydrograph separation method that uses a two-parameter, recursive digital filter (RDF) constrained via chemical mass balance to estimate the base flow contribution to a stream or river (Rimmer and Hartman, 2014; Raffensperger et al., 2017). A recursive digital filter distinguishes between high-frequency and low-frequency discharge data within
Water quality, quantity, and gas fluxes of the Upper Mississippi River basin (WY 2012-2016)
This product consists of one tabular dataset and associated metadata of water quality information related to rivers, streams, and reservoirs in the Upper Mississippi River watershed between 2012 and 2016. This data release is a part of a national assessment of freshwater aquatic carbon fluxes. Data consist of organic and inorganic carbon related species, carbon dioxide and methane gas fluxes calcu
Benchmarking high-resolution hydrologic model performance of long-term retrospective streamflow simulations in the contiguous United States
Because use of high-resolution hydrologic models is becoming more widespread and estimates are made over large domains, there is a pressing need for systematic evaluation of their performance. Most evaluation efforts to date have focused on smaller basins that have been relatively undisturbed by human activity, but there is also a need to benchmark model performance more comprehensively, including
Authors
Erin Towler, Sydney Foks, Aubrey L Dugger, Jesse E. Dickinson, Hedeff I. Essaid, David Gochis, Roland J. Viger, Yongxin Zhang
Dissolved carbon export by large river systems is influenced by source area heterogeneity
Rivers and streams export inorganic and organic carbon derived from contributing landscapes and so downstream carbon fluxes are important quantitative indicators of change in ecosystem function and for the full accounting of terrestrial carbon budgets. Carbon concentration-discharge (C-Q) relationships in rivers provide important information about carbon source and behavior in watersheds and are u
Authors
Edward G. Stets, Robert G. Striegl, Kimberly Wickland, Mark Dornblaser, Sydney Foks
Mean squared error, deconstructed
As science becomes increasingly cross-disciplinary and scientific models become increasingly cross-coupled, standardized practices of model evaluation are more important than ever. For normally distributed data, mean squared error (MSE) is ideal as an objective measure of model performance, but it gives little insight into what aspects of model performance are “good” or “bad.” This apparent weakne
Authors
Timothy O. Hodson, Thomas M. Over, Sydney Foks
Stream dissolved organic matter in permafrost regions shows surprising compositional similarities but negative priming and nutrient effects
Permafrost degradation is delivering bioavailable dissolved organic matter (DOM) and inorganic nutrients to surface water networks. While these permafrost subsidies represent a small portion of total fluvial DOM and nutrient fluxes, they could influence food webs and net ecosystem carbon balance via priming or nutrient effects that destabilize background DOM. We investigated how addition of biolab
Authors
Ethan Wologo, Sarah Shakil, Scott Zolkos, Sadie R. Textor, Stephanie Ewing, Jane Klassen, Robert G. M. Spencer, David C. Podgorski, Suzanne E. Tank, Michelle Baker, Jonathan A. O'Donnell, Kimberly P. Wickland, Sydney Foks, Jay P. Zarnetske, Joseph Lee-Cullin, Futing Liu, Yuanhe Yang, Pirkko Kortelainen, Jaana Kolehmainen, Joshua F. Dean, Jorien E. Vonk, Robert M. Holmes, Gilles Pinay, Michaela M. Powell, Jansen Howe, Rebecca J. Frei, Samuel P. Bratsman, Benjamin W. Abbott
Estimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models
Optimal hydrograph separation (OHS) uses a two-parameter recursive digital filter that applies specific conductance mass-balance constraints to estimate the base flow contribution to total streamflow at stream gages where discharge and specific conductance are measured. OHS was applied to U.S. Geological Survey (USGS) stream gages across the conterminous United States to examine the range/distribu
Authors
Sydney Foks, Jeff P. Raffensperger, Colin A. Penn, Jessica M. Driscoll
Influence of climate on alpine stream chemistry and water sources
The resilience of alpine/subalpine watersheds may be viewed as the resistance of streamflow or stream chemistry to change under varying climatic conditions, which is governed by the relative size (volume) and transit time of surface and subsurface water sources. Here, we use end‐member mixing analysis in Andrews Creek, an alpine stream in Rocky Mountain National Park, Colorado, from water year 199
Authors
Sydney Foks, Edward G. Stets, Kamini Singha, David W. Clow
Hydrologic Model Evaluation and Time-Series Tools (HyMETT) R-package
Hydrologic Model and Evaluation Time-series Tools (HyMETT) software facilitates the analysis and evaluation of hydrologic model output and time-series data with functions focused on comparison of modeled and observed data, period-of-record statistics, and trends.