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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Location Identifiers, Metadata, and Map for Field Measurements at the East-Taylor Watershed Community Observatory, Colorado, USA (Version 3.3)

This dataset contains identifiers, metadata, and a map of the locations where field measurements have been conducted at the East-Taylor Watershed Community Observatory located in the Upper Colorado River Basin, United States. This is version 3.3 of the dataset and replaces the prior version 3.2 (see below for details on changes between the versions). Dataset description: The East River-Taylor Watershed is the primary field site of the Watershed Function Scientific Focus Area (WFSFA) and the Rocky Mountain Biological Laboratory. Researchers from several institutions generate highly diverse hydrological, biogeochemical, climate, vegetation, geological, remote sensing, and model data at the East-Taylor Watershed in collaboration with the WFSFA. Thus, the purpose of this dataset is to maintain an inventory of the field locations and instrumentation to provide information on the field activities in the East-Taylor Watershed and coordinate data collected across different locations, researchers, and institutions. The dataset contains (1) a README file with information on the various files, (2) three csv files describing the metadata collected for each surface point location, plot and region registered with the WFSFA, (3) csv files with metadata and contact information for each surface point location registered with the WFSFA, (4) a csv file with with metadata and contact information for plots, (5) a csv file with metadata for geographic regions and sub-regions within the watershed, (6) a compiled xlsx file with all the data and metadata which can be opened in Microsoft Excel, (7) a kml map of the locations plotted in the watershed which can be opened in Google Earth, (8) a jpg image of the kml map which can be viewed in any photo viewer, and (9) a zipped file with the registration templates used by the SFA team to collect location metadata. The zipped template file contains two csv files with the blank templates (point and plot), two csv files with instructions for filling out the location templates, and one compiled xlsx file with the instructions and blank templates together. Additionally, the templates in the xlsx include drop down validation for any controlled metadata fields. Persistent location identifiers (Location_ID) are determined by the WFSFA data management team and are used to track data and samples across locations. Dataset uses: This location metadata is used to update the Watershed SFA’s publicly accessible Field Information Portal (an interactive field sampling metadata exploration tool; https://wfsfa-data.lbl.gov/watershed/), the kml map file included in this dataset, and other data management tools internal to the Watershed SFA team. Version Information: The latest version of this dataset publication is version 3.3. This version contains 167 new point locations, 1 new plot, and 2 new geographic regions. Overall, there are a total of 1439 point locations, 75 plots, and 54 geographic regions. Additionally, the kml map of locations and image now includes two boundaries (Upper Ohio Creek (UO) and Carbon Creek (CA)) outside of the East River watershed (USGS HUC-10) and accompanying stream network that represents areas of focus. Refer to methods for further details on the version history. This dataset will be updated on a periodic basis with new measurement location information. Researchers interested in having their East-Taylor Watershed measurement locations added to this list should reach out to the WFSFA data management team at wfsfa-data@googlegroups.com. Acknowledgments: Please cite this dataset if using any of the location metadata in other publications or derived products. If using the location metadata for the 2018 NEON hyperspectral campaign, additionally cite Chadwick et al. (2020). doi:10.15485/1618130. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2020

Aligned FTICR-MS, Respiration, and Biochemical Transformation Data from Columbia River Sediment Incubations Associated with: “Carbon Limitation Leads to Thermodynamic Regulation of Aerobic Metabolism”

Columbia River hyporheic zone sediments from the Hanford Site 300 Area in eastern Washington were incubated in a full factorial design with different organic matter (OM) amendments. The aim of the experiment was to test the influence of OM thermodynamics on aerobic respiration across different organic carbon pools and concentrations. This dataset is comprised of (1) a csv with high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory), (2) a csv with sample IDs, replicates, amendments, dissolved oxygen (DO) measurements, and sampling time points, (3) a csv with sample IDs, replicates, respiration rates, FTICR summary metrics, and relative abundance of chemical classes; and (4) a csv with the number of chemical transformations in each sample replicate (microcosm). The data are associated with the publication “Carbon Limitation Leads to Thermodynamic Regulation of Aerobic Metabolism” published in ES&T Letters (Garayburu-Caruso et al., 2020). Please use the data package’s DOI to cite the data package. We ask that you acknowledge the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) Subsurface Biogeochemical Research (SBR) program when using the data. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include data package authors as co-authors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Data for "Soil carbon dynamics during drying vs. rewetting: Importance of antecedent moisture conditions"

This dataset contains data used for the paper "Soil carbon dynamics during drying vs. rewetting: importance of antecedent moisture conditions". The Related References field will be updated with a full citation when available.Soil moisture influences soil carbon dynamics, including microbial growth and respiration. The response of such ‘soil respiration’ to moisture changes is generally assumed to be linear and reversible, i.e. to depend only on the current moisture state. Current models thus do not account for antecedent soil moisture conditions when determining soil respiration or the available substrate pool. We conducted a laboratory incubation to determine how the antecedent conditions of drought and flood influenced soil organic matter (SOM) chemistry, bioavailability, and respiration. We sampled soils from an upland coastal forest, Beaver Creek, WA USA, and subjected them to drying and rewetting treatments. For the drying treatment, field moist soils were saturated and then dried to 75, 50, 35, and 5 % saturation. In the rewetting treatment, field moist soils were air-dried and then rewet to 35, 50, 75, and 100 % saturation. We measured respiration and water extractable organic carbon (WEOC) concentrations and used 1H-NMR and FT-ICR-MS to characterize the WEOC pool across the treatments. The drying vs. wetting treatment strongly influenced SOM bioavailability, as rewet soils (with antecedent drought) had greater WEOC concentrations and respiration fluxes compared to the drying soils (with antecedent flood). In addition, air-dry soils had the highest WEOC concentrations, and the NMR-resolved peaks showed a strong contribution of protein groups in these soils. Both NMR and FT-ICR-MS analyses indicated increased contribution of complex aromatic groups/molecules in the rewet soils, compared to the drying soils. We suggest that drying introduced organic matter into the WEOC pool via desorption of aromatic molecules and/or by microbial cell lysis, and this stimulated microbial mineralization rates. Our work indicates that even short-term shifts in antecedent moisture conditions can strongly influence soil C dynamics at the core scale. The predictive uncertainties in current soil models may be reduced by a more accurate representation of soil water and C persistence that includes a mechanistic and quantitative understanding of the impact of antecedent moisture conditions.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv and .txt format, which can be accessed and processed using MS Excel or R. NMR data are provided as raw output data (accessed in Bruker TopSpin or MestreNova) as well as the MestreNova-processed files. This archive can also be accessed on GitHub at https://github.com/kaizadp/hysteresis_and_soil_carbon (DOI: 10.5281/zenodo.4432885).

1H-NMR↗
DOE OSTI2021

Data for "Soil texture and environmental conditions influence the biogeochemical responses of soils to drought and flooding"

This dataset contains data used for the paper "Soil texture and environmental conditions influence the biogeochemical responses of soils to drought and flooding". The Related References field will be updated with a full citation when available.Climate change is intensifying the global water cycle, with increased frequency of drought and flood. Water is an important driver of soil carbon dynamics, and it is crucial to understand how moisture disturbances will affect carbon availability and fluxes in soils. Here we investigate the role of water in substrate-microbe connectivity and soil carbon cycling under extreme moisture conditions. We collected soils from Alaska, Florida, and Washington USA, and incubated them under Drought and Flood conditions. Drought had a stronger effect on soil respiration, pore-water carbon, and microbial community composition than flooding. Soil response was not consistent across sites, and was influenced by site-level pedological and environmental factors. Soil texture and porosity can influence microbial access to substrates through the pore network, driving the chemical response. Further, the microbial communities are adapted to the historic stress conditions at their sites and therefore show site-specific responses to drought and flood.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv and .txt format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/kaizadp/TES_3Soils_2021 (DOI: 10.5281/zenodo.4792655).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Data from : "Warming promotes loss of subsoil carbon through accelerated degradation of plant-derived organic matter". Blodgett warming experiment

This dataset contains data used for the paper: Warming promotes loss of subsoil carbon through accelerated degradation of plant-derived organic matter. Soil Biology and Biochemistry 156, 108185. doi:10.1016/j.soilbio.2021.108185On April 2018 (after 4.5 years of warming), we collected O-horizon (organic horizon) material and soil core down to 90 cm depth from a whole-soil warming experiment in a mixed-coniferous temperate forest, located at the University of California Blodgett experimental forest in the foothills of the Sierra Nevada, CA USA. The goal was to assess how 4.5 years of +4 °C whole-soil warming affected the quantity and quality of soil organic matter. Cores were collected from 6 experimental plots (three replicated blocks); samples were collected in 10 cm increments from 0 to 90 cm depth.This dataset contains a compressed (.zip) archive of the data used for this manuscript. The dataset includes files in .xlsx format, which can be accessed and processed using MS Excel or R. Carbon and nitrogen concentrations, as well as stable carbon isotope composition ((δ13C) and solvent extractable lipid biomarker (alkanoic acids and alkanes) data are provided as processed data files. Diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy data are provided as raw output and processed data files.The dataset files "Blodgett_warming_Data" and "Blodgett_warming_raw_data.xlsx" were updated on July 7, 2021. The following updates were made: (1) specification of the units of measurements in the dataset (the unit of measurement was missing in some parameters) and (2) the column name "pulled depth" was changed to "pooled depth" in the updated data files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Raw Data published in PeerJ, 2020 for Lower Subalpine needle decomposition field study 2017-2018

This data package contains text files that describe geochemical measurements collected from 2017-2018 during isolated conifer needle decomposition field studies at the Lower Subalpine region of Washington Gulch in Crested Butte, CO. The files within include total carbon and nitrogen (CN) content and fourier-transform infrared spectroscopy (FTIR) results for the initial needles collected in 2016 and after decomposition in October 2018. DI water extractions were conducted with the initial harvested needles in 2016 to determine extractable dissolved organic carbon (DOC), total nitrogen (TN), UV absorbance at 254 nm (UV254), and specific UV absorbance (SUVA). This dataset also includes soil extractable DOC, TN, nitrate, nitrite, ammonium, total organic nitrogen (TON), and pH results from soil collections in 2017. Soil porewater results for DOC, TN, UV254, and SUVA analyses at 15 cm soil depth are also provided from 2017-2018. Gas flux raw data provides CO2, CH4, N2O, and NH3 measurements above needle decomposition over the two study years. Finally, soil samples for microbial DNA extractions were collected from the upper soil depth. This raw data is available in the NCBI SRA database under SRA accession number PRJNA605259. These datasets were generated to investigate the isolated decomposition of spruce and lodgepole conifer needles. The goal of this work was to understand how needle litter impacts terrestrial biogeochemical carbon and nitrogen cycling. Results from this work is detailed in the reference paper "A comparison of lodgepole and spruce needle chemistry impacts on terrestrial biogeochemical processes during isolated needle decomposition. DOI: 10.7717/peerj.9538."

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Raw Data published in PeerJ, 2021 for Crested Butte decomposition field study 2017-2019.

This data package contains text files that describe geochemical measurements collected from 2017-2019 during isolated conifer needle decomposition field studies in Crested Butte, Colorado. The geochemical measurements were collected across three elevations (2,800–3,500 m) ranging from montane to subalpine ecoregions. The data sets within include total carbon and nitrogen content and fourier-transform infrared spectroscopy (FTIR) results for the initial needles collected in 2016 and after decomposition in 2019. Data collection results from August 2020 are also included from when the experimental plots were removed to understand final concentrations of soil extractable carbon and nitrogen content as well as mass balances from litter bag deployments. Soil porewater results are also provided from 2017-2019 for DOC, TN, UV254, and specific UV absorbance (SUVA) analyses at 15 cm soil depth. Gas flux raw data provides CO2, CH4, N2O, and NH3 measurements above needle decomposition over the three study years. Finally, soil samples for microbial DNA extractions were collected from the upper soil depth. This raw data is available in the NCBI SRA database under SRA accession numbers PRJNA605259 and PRJNA715914. These data sets were generated to investigate the isolated decomposition of spruce and lodgepole conifer needles. The goal of this work was to determine the roles of elevation, soil type, seasonal changes in soil moisture, and snowmelt timing on litter decomposition processes. Results from this work are detailed in the reference paper "Effect of elevation, season and accelerated snowmelt on biogeochemical processes during isolated conifer needle litter decomposition. DOI: 10.7717/peerj.11926."

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Water Level Data from Wells PLM1 and PLM6 for the East River Watershed, Colorado

This dataset (Williams et al., 2020) contains the original un-QA/QC-ed water level data for PLM1 and PLM6 and has been obsoleted. The data contained within this dataset is not to be used. Refer to Faybishenko et al., 2022 (DOI: 10.15485/1866836) for the latest QA/QC-ed data available via ESS-DIVE.This data set contains water level data for the PLM1 and PLM6 wells. PLM1 and PLM6 are location identifiers used by the Watershed Function SFA project for two groundwater monitoring wells along an elevation gradient located along the lower montane life zone of a hillslope near the Pumphouse location. These wells used to monitor subsurface water and carbon inventories and fluxes at the East River Watershed, Colorado, USA. Complete metadata information on the PLM1 and PLM6 wells are available in the related data package reference Varadharajan C, et al (2020). https://doi.org/10.15485/1660962.Data are reported in .csv files per well. The latitude and longitude of each location are given in a file called locations.csv. These data are used for determining the seasonally dependent flow of groundwater under the PLM hillslope. The downslope flow of groundwater in combination with data on groundwater chemistry can be used to estimate rates of solute export from the hillslope to the floodplain and river.These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Model, data, and code for paper "Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x"

The data package includes data, model, and code that support the analyses and conclusions in the paper titled “modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x”. The primary goal of this paper is to demonstrate that key streamflow properties such as water depth, flow velocity, and dynamic pressure in a natural river at 30-kilometer scale over 5 years can be reliably and efficiently modeled using the computational framework presented in this paper. To support the paper, various data types from remote sensing, field observations, and computational models are used. Specific details are described as follows. Firstly, the river bathymetry data was obtained from a Light Detection and Ranging (LiDAR) survey. This data is then converted to a triangulated surface format, STL, for mesh generation in OpenFOAM. The STL data can be found in Model_Setups/BaseCase_2013To2015/constant/triSurface. The OpenFOAM mesh generated using this STL file can be found in constant/polyMesh. Other model setups, boundary and initial conditions can be found in /system and /0.org under folder BaseCase_2013To2015. A similar data structure can also be found in BaseCase_2018To2019 for the simulations during 2018 and 2019. Secondly, the OpenFOAM simulations need the upstream discharge and water depth information at the upstream boundary to drive the model. These data are generated from a one-dimensional hydraulic model and the data can be found under the folder Model_Setups /1D model Mass1 data. The mass1_65.csv and mass1_191.csv files include the results of the 1D model at the model inlet and outlet, respectively. The Matlab source code Mass1ToOFBC20182019.m is used to convert these data into OpenFOAM boundary condition setups.With the above OpenFOAM model, it can generate data for water surface elevation, flow velocity, and dynamic pressure. In this paper, the water surface elevation was measured at 7 locations during different periods between 2011 and 2019. The exact survey locations (see Fig1_SurveyLocations.txt) can be found in folder Fig_1. The variation of water stage over time at the 7 locations can be found in folder /Observation_WSE. The data type include .txt, .csv, .xlsx, and .mat. The .mat data can be loaded by Matlab.We also measured the flow velocities at 12 cross-sections along the river. At each cross-section, we recorded the x, y locations, depth, three velocity components u,v,w. These data are saved to a Matlab format which can be found under folder /Observation_Velocity and /Fig_1. The relative locations of velocity survey locations to the river bathymetry can be found in Figure 1c.The water stage data at the 7 locations from OpenFOAM, 1D, and 2D hydraulic models are also provided to evaluate the long-term performance of 3D models vs 1D/2D models. The water stage data for the 7 locations from OpenFOAM have been saved to .mat format and can be found in /OpenFOAM_WSE. The water stage data from the 1D model are saved in .csv format and can be found in /Mass1_WSE. The water stage from the 2D model is saved as .mat format and can be found in / Mass2_WSEIn addition, the OpenFOAM model outputs the information of hydrostatic and hydrodynamic pressure. They are saved as .mat format under folder /Fig_11/2013_1. As the files are too large, we only uploaded the data for January 2013. The area of different ratio of dynamic pressure to static pressure for all simulation range, i.e., 2013-2015, are saved to .mat format. They can be found in /Fig_11/PA. Further, the data of wall clock time versus the solution time of the OpenFOAM modeling are also saved to .mat format under folder /Fig_13/LogsMat. In summary, the data package contains seven data types, including .txt, .csv, .xlsx, .dat, .stl, .m, and .mat. The former 4 types can be directly open using a text editor or Microsoft Office. The .mat format needs to be read by Matlab. The Matlab source code .m files need to be run with Matlab. The OpenFOAM setups can be visualized in ParaView. The .stl file can be opened in ParaView or Blender. The data in subfolders Fig_1 to Fig_10 and Fig_12 are copied from the aforementioned data folders to generate specific figures for the paper. A readME.txt file is included in each subfolder to further describe how the data in each folder are generated and used to support the paper.Please use the data package's DOI to cite the data package. Please contact yunxiang.chen@pnnl.gov if you need more data related to the paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Data for: Spatial access and resource limitations control carbon mineralization in soils

This dataset contains data and code used for the paper "Spatial access and resource limitations control carbon mineralization in soils", https://doi.org/10.1016/j.soilbio.2021.108427. Core-scale soil carbon fluxes are ultimately regulated by pore-scale dynamics of substrate availability and microbial access. These are constrained by physicochemical and biochemical phenomena (e.g. spatial access and hydrologic connectivity, physical occlusion, adsorption-desorption with mineral surfaces, nutrient and resource limitations). We conducted an experiment to determine how spatial access and resource limitations influence core-scale water-soluble soil organic matter (SOM) mineralization, and how these are regulated by antecedent moisture conditions. Intact soil cores were incubated at field-moist vs. drought conditions, after which they were saturated from above (to simulate precipitation) or below (to simulate groundwater recharge). Soluble carbon (acetate) and nitrogen (nitrate) forms were added to some cores during the rewetting process to alleviate potential nutrient limitations. Soil respiration was measured during the incubation, after which pore water was extracted from the saturated soils and analyzed for water soluble organic carbon concentrations and characterization. Our results showed that carbon (C) amendments increased the cumulative carbon dioxide (CO2) evolved from the soil cores, suggesting that the soils were C-limited. Drought and rewetting increased soil respiration, and there was a greater abundance of complex aromatic molecules in pore waters sampled from these soils. This newly available substrate appeared to alleviate nutrient limitations on respiration, because there were no further respiration increases with subsequent C and N amendments. We had hypothesized that respiration would be influenced by wetting direction, as simulated precipitation would mobilize C from the surface. However, as a main effect, this response was seen only in the C-amended soils, indicating that surface-C may not have been bioavailable. At the pore scale (pore water samples), drought and the C, N amendments caused a net loss of identified molecules when the soils were rewet from below, whereas wetting from above caused a net increase in identified molecules, suggesting that fresh inputs stimulated the C-and N-limited microbial populations present deeper in the soil profile. Our experiment highlights the complex and interactive role of antecedent moisture conditions, wetting direction, and resource limitations in driving core-scale C fluxes.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/kaizadp/TES_spatial_access_2021 (DOI: 10.5281/zenodo.5522938).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Soil pore network response to freeze-thaw cycles in permafrost aggregates

This dataset contains data used for the paper "Pore network response to freeze-thaw cycles in permafrost aggregates". The Related References field will be updated with a full citation when available.Climate change in Arctic landscapes may increase freeze-thaw frequency within the active layer as well as newly thawed permafrost. A highly disruptive process, freeze-thaw can deform soil pores and alter the architecture of the soil pore network with varied impacts to water transport and retention, redox conditions, and microbial activity. Our objective was to investigate how freeze-thaw cycles impacted the pore network of newly thawed permafrost aggregates to improve understanding of what type of transformations can be expected from warming Arctic landscapes. We measured the impact of freeze-thaw on pore morphology, pore throat diameter distribution, and pore connectivity with X-ray computed tomography (XCT) using six permafrost aggregates with sizes of 2.5 cm3 from a mineral soil horizon (Bw; 28-50 cm depths) in Toolik, Alaska. Freeze-thaw cycles were performed using a laboratory incubation consisting of five freeze-thaw cycles (-10˚C to 20˚C) over five weeks. Our findings indicated decreasing spatial connectivity of the pore network across all aggregates with higher frequencies of singly connected pores following freeze-thaw. Water-filled pores that were connected to the pore network decreased in volume while the overall connected pore volumetric fraction was not affected. Shifts in the pore throat diameter distribution were mostly observed in pore throats ranges of 100 microns or less with no corresponding changes to the pore shape factor of pore throats. Responses of the pore network to freeze-thaw varied with aggregate, suggesting that initial pore morphology may play a role in driving freeze-thaw response. Our research suggests that freeze-thaw alters the microenvironment of permafrost aggregates during the incipient stage of deformation following permafrost thaw, impacting soil properties and function in Arctic landscapes undergoing transition. This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/Erin-Rooney/XCT-freezethaw (DOI: 10.5281/zenodo.5816355).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Advanced Global Atmospheric Gases Experiment (AGAGE) Data

In the ALE/GAGE/AGAGE global network program, continuous high frequency gas chromatographic measurements of four biogenic/anthropogenic gases (methane, CH4; nitrous oxide, N2O; hydrogen, H2; and carbon monoxide, CO) and several anthropogenic gases that contribute to stratospheric ozone destruction and/or to the greenhouse effect have been carried out at five globally distributed sites for several years. The program, which began in 1978, is divided into three parts associated with three changes in instrumentation: the Atmospheric Lifetime Experiment (ALE), which used Hewlett Packard HP5840 gas chromatographs; the Global Atmospheric Gases Experiment (GAGE), which used HP5880 gas chromatographs; and the present Advanced GAGE (AGAGE). AGAGE uses two types of instruments: a gas chromatograph with multiple detectors (GC-MD), and a gas chromatograph with mass spectrometric analysis (GC-MS). Beginning in January 2004, an improved cryogenic preconcentration system (Medusa) replaced the absorption-desorption module in the GC-MS systems at Mace Head and Cape Grim; this provided improved capability to measure a broader range of volatile perfluorocarbons with high global warming potentials. The Medusa GC-MS systems were subsequently used at other AGAGE stations (Trinidad Head, Barbados, American Samoa, Zeppelin, Jungfraujoch, and Goan) after the initial setup at Mace Head and Cape Grim. More information may be found at the AGAGE home page: https://agage.mit.edu/instruments.Compared to the previous version (https://data.ess-dive.lbl.gov/datasets/doi: doi:10.15485/1781803), the latest update (Agage_gcmd_gcms.data.2022_01_03.tar.gz) includes 6 months of new data through the end of September 2020. For a complete list of released compounds and used standard scales, please see “AGAGE_scale_2021_v1.pdf” file. Additional information can also be found on the AGAGE website (https://agage.mit.edu).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

QA/QC-ed Groundwater Level Time Series in PLM-1 and PLM-6 Monitoring Wells, East River, Colorado (2016-2022)

This data set contains QA/QC-ed (Quality Assurance and Quality Control) water level data for the PLM1 and PLM6 wells. PLM1 and PLM6 are location identifiers used by the Watershed Function SFA project for two groundwater monitoring wells along an elevation gradient located along the lower montane life zone of a hillslope near the Pumphouse location at the East River Watershed, Colorado, USA. These wells are used to monitor subsurface water and carbon inventories and fluxes, and to determine the seasonally dependent flow of groundwater under the PLM hillslope. The downslope flow of groundwater in combination with data on groundwater chemistry (see related references) can be used to estimate rates of solute export from the hillslope to the floodplain and river. QA/QC analysis of measured groundwater levels in monitoring wells PLM-1 and PLM-6 included identification and flagging of duplicated values of timestamps, gap filling of missing timestamps and water levels, removal of abnormal/bad and outliers of measured water levels. The QA/QC analysis also tested the application of different QA/QC methods and the development of regular (5-minute, 1-hour, and 1-day) time series datasets, which can serve as a benchmark for testing other QA/QC techniques, and will be applicable for ecohydrological modeling. The package includes a Readme file, one R code file used to perform QA/QC, a series of 8 data csv files (six QA/QC-ed regular time series datasets of varying intervals (5-min, 1-hr, 1-day) and two files with QA/QC flagging of original data), and three files for the reporting format adoption of this dataset (InstallationMethods, file level metadata (flmd), and data dictionary (dd) files).QA/QC-ed data herein were derived from the original/raw data publication available at Williams et al., 2020 (DOI: 10.15485/1818367). For more information about running R code file (10.15485_1866836_QAQC_PLM1_PLM6.R) to reproduce QA/QC output files, see README (QAQC_PLM_readme.docx). This dataset replaces the previously published raw data time series, and is the final groundwater data product for the PLM wells in the East River. Complete metadata information on the PLM1 and PLM6 wells are available in a related dataset on ESS-DIVE: Varadharajan C, et al (2022). https://doi.org/10.15485/1660962. These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales. 2022/09/09 Update: Converted data files using ESS-DIVE’s Hydrological Monitoring Reporting Format. With the adoption of this reporting format, the addition of three new files (v1_20220909_flmd.csv, V1_20220909_dd.csv, and InstallationMethods.csv) were added. The file-level metadata file (v1_20220909_flmd.csv) contains information specific to the files contained within the dataset. The data dictionary file (v1_20220909_dd.csv) contains definitions of column headers and other terms across the dataset. The installation methods file (InstallationMethods.csv) contains a description of methods associated with installation and deployment at PLM1 and PLM6 wells. Additionally, eight data files were re-formatted to follow the reporting format guidance (er_plm1_waterlevel_2016-2020.csv, er_plm1_waterlevel_1-hour_2016-2020.csv, er_plm1_waterlevel_daily_2016-2020.csv, QA_PLM1_Flagging.csv, er_plm6_waterlevel_2016-2020.csv, er_plm6_waterlevel_1-hour_2016-2020.csv, er_plm6_waterlevel_daily_2016-2020.csv, QA_PLM6_Flagging.csv). The major changes to the data files include the addition of header_rows above the data containing metadata about the particular well, units, and sensor description. 2023/01/18 Update: Dataset updated to include additional QA/QC-ed water level data up until 2022-10-12 for ER-PLM1 and 2022-10-13 for ER-PLM6. Reporting format specific files (v2_20230118_flmd.csv, v2_20230118_dd.csv, v2_20230118_InstallationMethods.csv) were updated to reflect the additional data. R code file (QAQC_PLM1_PLM6.R) was added to replace the previously uploaded HTML files to enable execution of the associated code. R code file (QAQC_PLM1_PLM6.R) and ReadMe file (QAQC_PLM_readme.docx) were revised to clarify where original data was retrieved from and to remove local file paths.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The impact of freeze-thaw history on soil carbon response to experimental freeze-thaw cycles

This dataset contains data used for the paper "The impact of freeze-thaw history on soil carbon response to experimental freeze-thaw cycles". The Related References field will be updated with a full citation when available.Freeze-thaw is a disturbance process in cold regions where permafrost soils are becoming vulnerable to temperature fluctuations above 0˚C. Freeze-thaw alters soil physical and biogeochemical properties with implications for carbon persistence and emissions in Arctic landscapes. We examined whether different freeze-thaw histories in two soil systems led to contrasting biogeochemical responses under a laboratory-controlled freeze-thaw incubation. We investigated controls on soil organic matter (SOM) composition through Fourier-transform ion cyclotron resonance mass spectroscopy (FT-ICR-MS) to identify nominal carbon oxidation states and relative abundances of aliphatic-type carbon molecules in both surface and subsurface soils. Soil cores (~ 60 cm-depth) were sampled from two sites in Alaskan permafrost landscapes with different in situ freeze-thaw characteristics: Healy (>40 freeze-thaw cycles annually) and Toolik (<150 freeze-thaw cycles annually). FT-ICR-MS was coupled with in situ temperature data and soil properties (i.e., soil texture, mineralogy) to assess (1) differences in SOM composition associated with previous freeze-thaw history and (2) sensitivity to experimental freeze-thaw in the extracted cores. Control (freeze-only) samples showed greater carbon oxidation in Healy soils compared with Toolik, even in lower mineral horizons where freeze-thaw history was comparable across both sites. Healy showed the most loss of carbon compounds following experimental freeze-thaw in the lower mineral depths, including a decrease in aliphatics. Toolik soils responded more slowly to freeze-thaw as shown by intermediary carbon oxidation distributed across multiple carbon compound classes. Variations in the response of permafrost carbon chemistry to freeze-thaw is an important factor for predicting changes in soil function as permafrost thaws in high northern latitudes.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/Erin-Rooney/FTC-FTICR (DOI 10.5281/zenodo.6533064).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Water Quality Parameters at the Elkhorn Slough National Estuarine Research Reserve (ESNERR)

The following dataset includes water quality and meteorological forcing data between 2003 and 2019 across four Elkhorn Slough National Estuarine Research Reserve (ESNERR) stations. The data are monthly averaged and include orthophosphate, ammonium, Nitrite, Nitrate, Nitrite + Nitrate, Chlorophyll, Temperature of water, Specific Conductance, Salinity, Dissolved Oxygen, Air Temperature and Precipitation. The data were compiled for wavelet and other statistical analyses. All data included herein are associated with the following manuscript: Venkatesh*, S., B. Arora, D. Dwivedi, S. Vezhaperambu, M. V. Ramesh (2021), Temporal Variability of Water Quality Parameters at the Elkhorn Slough Estuary using Wavelets, IEEE Proceedings on 6th International Conference for Convergence in Technology, DOI:10.1109/I2CT51068.2021.9418159.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Model Inputs, Outputs, and Scripts associated with: “Spatial microbial respiration variations in the hyporheic zones within the Columbia River Basin”

This data package is associated with the publication “Spatial microbial respiration variations in the hyporheic zones within the Columbia River Basin” published in the Journal of Geophysical Research: Biogeosciences (Son et al. 2022) available at doi: 10.1029/2021JG006654. This data package includes the key model inputs/outputs of the river corridor model for the Columbia River Basin (CRB) and the model source codes, which were used in the manuscript. The model is a carbon-nitrogen-coupled river corridor model (RCM), and the model is used to quantify hyporheic zone (HZ) aerobic and anaerobic respiration at the NHDPLUS stream reach scales. The RCM used in this study combines empirical substrate models derived from observations and three microbially driven reactions to compute respiration of the HZ for each National Hydrography Dataset (NHD) reach within the CRB. The reactions in HZs of each NHD reach include anaerobic respiration and two-step anaerobic respiration via denitrification. Our HZ respiration estimates are limited to the lotic (or flowing) stream/river systems, and do not account for the respiration process in water column. Note that the RCM only simulates the HZ’s contribution to the dissolved carbon dioxide (CO2) concentrations in the streams, and the CO2 emissions to the atmosphere are not modelled. The model computes at hourly timesteps because of the fast reaction rates. The key input data of the model are exchange flux, residence time, and stream solute (dissolved organic carbon (DOC), dissolved oxygen (DO), and nitrate concentrations). These inputs are constant over time and represent long-term averaged values.This modeling framework successfully quantified HZ respiration components over multiple scales. It revealed key mechanisms driving the spatial variation of HZ aerobic and anaerobic respiration in reaches with varying hydrologic and substrate conditions. Thus, this modeling study offers a testing hypothesis in different river system (e.g., climate and biomes) for the HZ respiration processes, and can be used as a sampling design tool for large-scale HZ experimental studies.This dataset contains five folders: (1) model_inputs, (2) model_outputs, (3) Rscripts, (4) figures, and (5) model_codes. It also contains a readme, file level metadata (FLMD), and data dictionary (dd). Please see the FLMD for a list of all the files contained in this data package and descriptions for each. The model_inputs folder contains the model inputs used to drive the model simulations. The model_outputs folder contains key model output files from the river corridor model. The Rscripts folder contains the Rscripts for pre- and post- processing model results. The figures folder contains the raw figures associated with the manuscript. The model_codes folder includes key model source codes/input files. All files are .jpg, .jpeg, .out, .e, .od, .dat, .sub, .F90, .0, .R, .sbx, .cpg, .sbn, .shx, .shp, .dbf, .prj, .tfw, .tif, .xml, .pdf, or .csv.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Data and Scripts associated with: “Laboratory evaluation of open source and commercial electrical conductivity sensor precision and accuracy”

This data package is associated with the publication “Laboratory evaluation of open source and commercial electrical conductivity sensor precision and accuracy: How do they compare?” submitted to PLOS ONE and accepted for publication (Fulton, S.G. et al. 2023; doi not yet available).Variation in electrical conductivity (EC) of water is important to reveal environmental disturbance and natural dynamics, including factors such as anthropogenic salinization. This data package supports a study addressing the need for a robust performance assessment of open source (OS) EC sensors. We evaluated the accuracy (mean error, %) and precision (sample standard deviation) of OS EC sensors in the laboratory via comparison to EC calibration standards using three different OS and OS/commercial-hybrid (OS/C) EC sensors and data logger configurations and two commercial (C) EC sensors and data logger configurations. We also evaluated the effect of cable length (7.5 m and 30 m) and sensor calibration on OS sensor accuracy and precision. This data package presents the results from the different testing laboratory configurations. It also includes an R script for statistical analysis of the data and an Arduino IDE file used to calibrate and collect data with the OS Atlas EC sensor. File types are .csv, .pdf, .R, and .ino.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Recent streamflow trends across permafrost basins of North America: Datasets

Climate change impacts, including changing temperatures, precipitation, and vegetation, are widely anticipated to cause major shifts to the permafrost with resulting impacts to hydro-ecosystems across the high latitudes of the globe. However, it is challenging to examine streamflow shifts in these regions owing to a paucity of data, discontinuity of records, and other issues related to data consistency and accuracy. We looked at recent changes in streamflow over 1976-2021 in watersheds affected by varying degrees of permafrost coverage to characterize trends and drivers for a range of watersheds across North America. Data sets are described in detail in the paper associated with this data set, Bennett et al. 2023, Front. Water - Water and Critical Zone, DOI: 10.3389/frwa.2023.1099660.These data contain CSV files of the streamflow, climate, and land surface characteristics for several sites located across the high latitude regions of North America. Both observed and reanalysis data products are provided. These files can be opened using Excel or a text editor, or they can be read, and analyzed in software tools such as Python or R. A brief description of the files is below, and more details can be found in the Methods section.rabpro_stats_north_select_74_55m.csv - This file describes the observed gages used in the analysis.GF31_23_metadat.csv - This file describes the 23 permafrost systems. Columns are as described in rabpro_stats_north_select_74_55m.csv above, with rabpro_id, the id used for the timeseries file mapping in GF31_23_time_series.csv.GF31_23_time_series.csv - This file contains the time series data for the stations described in GF31_23_metadat.csv.GF31_random_reaches_1583.csv - This file describes the 1583 randomly selected permafrost-dominant sites for machine learning analysis.era5_GF31_monthly_vars_random_reaches_1583.csv - This file contains the monthly ERA5 land data for the 1583 randomly selected permafrost-dominant sites.observed.zip: USGS and Hydat station data for the 74 gages analyzed in this study. Monthly, seasonal, and annual streamflow observations for minimum streamflow, mean streamflow, and maximum streamflow. Units are m3/sec. 1975-2022.streamflow_daily_GF31_infilled_1979_2022.csv - infilled daily streamflow data (infilled using GloFAS v 3.1) for 55 gages. Units are m3/sec. 1979-2022.glofas_23.zip - Glofas v3.1 file for the 23 permafrost-dominant gages in the study. Monthly, seasonal, and annual streamflow observations for minimum streamflow, mean streamflow, and maximum streamflow. Units are m3/sec. 1979-2021.glofas_1583.zip - Glofas v3.1 file for the 1583 randomly selected permafrost-dominant gages in the study. Monthly, seasonal, and annual streamflow observations for minimum streamflow, mean streamflow, and maximum streamflow. Units are m3/sec. 1979-2021.

54 ENVIRONMENTAL SCIENCES↗