WHONDRS River Corridor Dissolved Oxygen, Temperature, Sediment Aerobic Respiration, Grain Size, and Water Chemistry from Machine-Learning-Informed Sites across the Contiguous United States (v2)

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, 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-20230802T190226889
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 samples will continue to be collected across the CONUS through 2023 and possibly beyond. This data package will be updated semi-regularly with newly generated data. 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) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (5) total nitrogen data and averages; (6) sediment grain size data; (7) sediment iron (II) data and averages; (8) miniDOT dissolved oxygen and temperature summary data; (9) sediment incubation respiration rate data and averages; (10) normalized respiration rate data and averages; (11) miniDOT installation methods; (12) field protocols; (13) readme; (14) methods codes; (15) international geo-sample number (IGSN) mapping file; (16) a subfolder with miniDOT dissolved oxygen and temperature data and plots; and (17) a subfolder with sediment incubation respiration data, scripts, and plots. All files are .csv, .pdf, .R, .jpg, .jpeg, .png, .mov, .mp4. This data package was originally published in February 2023. It was updated in June 2023. See the change history section in the data package readme for more details. Site T42 was mislabeled as T41. This error will be fixed when this data package is next updated and this note will be removed at that time.