WHONDRS River Corridor Dissolved Oxygen, Temperature, Sediment Aerobic Respiration, Grain Size, and Water Chemistry from Machine-Learning-Informed Sites across the Contiguous United States (v3)

Forbes, Brieanne; Barnes, Morgan; Boehnke, Brandon T.; Chen, Xingyuan; Cornwell, Kali; Delgado, Dillman; Fulton, Stephanie G.; Garayburu-Caruso, Vanessa A.; Gary, Stefan; Goldman, Amy E.; Gonzalez, Brianna I.; Grieger, Samantha; Hammond, Glenn E.; Jiang, Peishi; Kaufman, Matthew H.; Laan, Maggi; Li, Bing; Li, Zhi; McKever, Sophia A.; Mudunuru, Maruti K.; Muller, Katherine A.; Myers-Pigg, Allison; Otenburg, Opal; Pelly, Aaron; Peta, Kelsey; Powers-McCormack, Beck; Regier, Peter; Renteria, Lupita; Roebuck, Alan; Scheibe, Timothy D.; Son, Kyongho; Torgeson, Joshua M.; Stegen, James C.; WHONDRS Consortium, The

doi:10.15485/1923689

Title: WHONDRS River Corridor Dissolved Oxygen, Temperature, Sediment Aerobic Respiration, Grain Size, and Water Chemistry from Machine-Learning-Informed Sites across the Contiguous United States (v3)

Dataset
Other Related Research

Abstract

This dataset supports a broader study examining hyporheic zone respiration rates to improve predictive models at a contiguous United States (CONUS) scale. The CONUS-Scale Model-Sample Study (CM) was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. New machine learning models are created every month to guide sampling locations. Data from the resulting samples are used to test and rebuild the machine learning models for the next round of sampling guidance. Sampling began in April 2022 and ended in October 2023 In addition to widely distributed CONUS sites, a more spatially focused sampling occurred in the Yakima River Basin, WA in summer 2022. Data from this more spatially intensive sampling occurred under the label “Second Spatial Study (SSS)” and were also included in the machine learning models. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected samples and data for SSS. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. Data from CM andmore »« less

Authors:

;

; Cornwell, Kali;

;

; Gonzalez, Brianna I.; Grieger, Samantha;

;

; Li, Zhi; McKever, Sophia A.;

Pacific Northwest National Laboratory
Parallel Works
Gram Northwest

Publication Date:: Fri Feb 03 00:00:00 EST 2023

Research Org.:: Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) (United States)

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES

Keywords:: River corridor; Freshwater; Hydrology; Hydraulic exchange; River; Stream; Watershed; Catchment; Biogeochemistry; Hydrobiogeochemical function ; Hyporheic zone; ModEx; Model-experiment iteration; ICON; ML; Mechanistic model; Machine learning; ESS-DIVE Water-Soil-Sediment Chemistry Reporting Format; ESS-DIVE Location Metadata Reporting Format; ESS-DIVE Sample ID and Metadata Reporting Format; ESS-DIVE Hydrologic Monitoring Reporting Format; ESS-DIVE CSV File Formatting Guidelines Reporting Format; ESS-DIVE File Level Metadata Reporting Format; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER; DO; Percent Saturation; Aerobic respiration rate; Sediment grain size ; Dissolved organic carbon; Non-purgeable organic carbon; Total nitrogen; Iron (II); Sediment surface area; Specific surface area; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > WATER QUALITY/WATER CHEMISTRY > WATER CHARACTERISTICS > WATER TEMPERATURE; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > WATER QUALITY/WATER CHEMISTRY > GASES > DISSOLVED OXYGEN; EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > RESPIRATION RATE; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > WATER QUALITY/WATER CHEMISTRY > WATER CHARACTERISTICS > NITROGEN COMPOUNDS; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > WATER QUALITY/WATER CHEMISTRY > NUTRIENTS > NITROGEN COMPOUNDS; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > WATER QUALITY/WATER CHEMISTRY > NUTRIENTS > NITROGEN

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OSTI Identifier:: 1923689

DOI:: https://doi.org/10.15485/1923689

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Citation Formats


                    Forbes, Brieanne, Barnes, Morgan, Boehnke, Brandon T., Chen, Xingyuan, Cornwell, Kali, Delgado, Dillman, Fulton, Stephanie G., Garayburu-Caruso, Vanessa A., Gary, Stefan, Goldman, Amy E., Gonzalez, Brianna I., Grieger, Samantha, Hammond, Glenn E., Jiang, Peishi, Kaufman, Matthew H., Laan, Maggi, Li, Bing, Li, Zhi, McKever, Sophia A., Mudunuru, Maruti K., Muller, Katherine A., Myers-Pigg, Allison, Otenburg, Opal, Pelly, Aaron, Peta, Kelsey, Powers-McCormack, Beck, Regier, Peter, Renteria, Lupita, Roebuck, Alan, Scheibe, Timothy D., Son, Kyongho, Torgeson, Joshua M., Stegen, James C., and WHONDRS Consortium, The. WHONDRS River Corridor Dissolved Oxygen, Temperature, Sediment Aerobic Respiration, Grain Size, and Water Chemistry from Machine-Learning-Informed Sites across the Contiguous United States (v3).  United States: N. p., 2023. 
        Web.  doi:10.15485/1923689.

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                    Forbes, Brieanne, Barnes, Morgan, Boehnke, Brandon T., Chen, Xingyuan, Cornwell, Kali, Delgado, Dillman, Fulton, Stephanie G., Garayburu-Caruso, Vanessa A., Gary, Stefan, Goldman, Amy E., Gonzalez, Brianna I., Grieger, Samantha, Hammond, Glenn E., Jiang, Peishi, Kaufman, Matthew H., Laan, Maggi, Li, Bing, Li, Zhi, McKever, Sophia A., Mudunuru, Maruti K., Muller, Katherine A., Myers-Pigg, Allison, Otenburg, Opal, Pelly, Aaron, Peta, Kelsey, Powers-McCormack, Beck, Regier, Peter, Renteria, Lupita, Roebuck, Alan, Scheibe, Timothy D., Son, Kyongho, Torgeson, Joshua M., Stegen, James C., & WHONDRS Consortium, The. WHONDRS River Corridor Dissolved Oxygen, Temperature, Sediment Aerobic Respiration, Grain Size, and Water Chemistry from Machine-Learning-Informed Sites across the Contiguous United States (v3).  United States.  doi:https://doi.org/10.15485/1923689

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                    Forbes, Brieanne, Barnes, Morgan, Boehnke, Brandon T., Chen, Xingyuan, Cornwell, Kali, Delgado, Dillman, Fulton, Stephanie G., Garayburu-Caruso, Vanessa A., Gary, Stefan, Goldman, Amy E., Gonzalez, Brianna I., Grieger, Samantha, Hammond, Glenn E., Jiang, Peishi, Kaufman, Matthew H., Laan, Maggi, Li, Bing, Li, Zhi, McKever, Sophia A., Mudunuru, Maruti K., Muller, Katherine A., Myers-Pigg, Allison, Otenburg, Opal, Pelly, Aaron, Peta, Kelsey, Powers-McCormack, Beck, Regier, Peter, Renteria, Lupita, Roebuck, Alan, Scheibe, Timothy D., Son, Kyongho, Torgeson, Joshua M., Stegen, James C., and WHONDRS Consortium, The. 2023.  
"WHONDRS River Corridor Dissolved Oxygen, Temperature, Sediment Aerobic Respiration, Grain Size, and Water Chemistry from Machine-Learning-Informed Sites across the Contiguous United States (v3)".  United States.  doi:https://doi.org/10.15485/1923689.  https://www.osti.gov/servlets/purl/1923689. Pub date:Fri Feb 03 00:00:00 EST 2023

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@article{osti_1923689,

  title        = {WHONDRS River Corridor Dissolved Oxygen, Temperature, Sediment Aerobic Respiration, Grain Size, and Water Chemistry from Machine-Learning-Informed Sites across the Contiguous United States (v3)},

  author       = {Forbes, Brieanne and Barnes, Morgan and Boehnke, Brandon T. and Chen, Xingyuan and Cornwell, Kali and Delgado, Dillman and Fulton, Stephanie G. and Garayburu-Caruso, Vanessa A. and Gary, Stefan and Goldman, Amy E. and Gonzalez, Brianna I. and Grieger, Samantha and Hammond, Glenn E. and Jiang, Peishi and Kaufman, Matthew H. and Laan, Maggi and Li, Bing and Li, Zhi and McKever, Sophia A. and Mudunuru, Maruti K. and Muller, Katherine A. and Myers-Pigg, Allison and Otenburg, Opal and Pelly, Aaron and Peta, Kelsey and Powers-McCormack, Beck and Regier, Peter and Renteria, Lupita and Roebuck, Alan and Scheibe, Timothy D. and Son, Kyongho and Torgeson, Joshua M. and Stegen, James C. and WHONDRS Consortium, The},

  abstractNote = {This dataset supports a broader study examining hyporheic zone respiration rates to improve predictive models at a contiguous United States (CONUS) scale. The CONUS-Scale Model-Sample Study (CM) was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. New machine learning models are created every month to guide sampling locations. Data from the resulting samples are used to test and rebuild the machine learning models for the next round of sampling guidance. Sampling began in April 2022 and ended in October 2023 In addition to widely distributed CONUS sites, a more spatially focused sampling occurred in the Yakima River Basin, WA in summer 2022. Data from this more spatially intensive sampling occurred under the label “Second Spatial Study (SSS)” and were also included in the machine learning models. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected samples and data for SSS. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. Data from CM and SSS were collected using the same methods. Other data types collected from SSS that were not part of CM were published in a separate data package (https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566). This dataset is comprised of two folders with field photos and videos and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocols; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) total nitrogen data and averages; (3) sediment grain size data; (4) sediment iron (II) data and averages; (5) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation vial; (6) sediment incubation respiration rate data and averages; (7) normalized respiration rate data and averages; (8) methods codes; (9) sediment specific surface area; and (10) a subfolder with sediment incubation respiration data, scripts, and plots. The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .jpg, .jpeg, .png, .mov, or .mp4.This data package was originally published in February 2023. It was updated in June 2023 (v2; new and modified files) and again in December 2023 (v3; new and modified files). See the change history section in the readme for more details.},

  doi          = {10.15485/1923689},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri Feb 03 00:00:00 EST 2023},

  month        = {Fri Feb 03 00:00:00 EST 2023}

}

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DOI: https://doi.org/10.15485/1923689

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