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)

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 mod...

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Bibliographic Details
Main Authors: Brieanne Forbes, Morgan Barnes, Brandon T. Boehnke, Xingyuan Chen, Kali Cornwell, Dillman Delgado, Stephanie G. Fulton, Vanessa A. Garayburu-Caruso, Stefan Gary, Amy E. Goldman, Brianna I. Gonzalez, Samantha Grieger, Glenn E. Hammond, Peishi Jiang, Matthew H. Kaufman, Maggi Laan, Bing Li, Zhi Li, Sophia A. McKever, Maruti K. Mudunuru, Katherine A. Muller, Allison Myers-Pigg, Opal Otenburg, Aaron Pelly, Kelsey Peta, Beck Powers-McCormack, Peter Regier, Lupita Renteria, Alan Roebuck, Timothy D. Scheibe, Kyongho Son, Joshua M. Torgeson, James C. Stegen, The WHONDRS Consortium
Format: Dataset
Language:unknown
Published: ESS-DIVE: Deep Insight for Earth Science Data 2023
Subjects:
ML
DO
Online Access:https://search.dataone.org/view/ess-dive-e976198fe417dbb-20231221T233104619
Description
Summary: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 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. 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.