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At least 721 records · Page 40

Two (or more) for one: Identifying classes of household energy- and water-saving measures to understand the potential for positive spillover

A key component of behavior-based energy conservation programs is the identification of target behaviors. A common approach is to target behaviors with the greatest energy-saving potential. The concept of behavioral spillover introduces further considerations, namely that adoption of one energy-saving behavior may increase (or decrease) the likelihood of other energy-saving behaviors. This research aimed to identify and describe household energy- and water-saving measure classes within which positive spillover is likely to occur (e.g., adoption of energy-efficient appliances may correlate with adoption of water-efficient appliances), and explore demographic and psychographic predictors of each. Nearly 1,000 households in a California city were surveyed and asked to report whether they had adopted 75 different energy- and/or water-saving measures. Principal Component Analysis and Network Analysis based on correlations between adoption of these diverse measures revealed and characterized eight water-energy-saving measure classes: Water Conservation, Energy Conservation, Maintenance and Management, Efficient Appliance, Advanced Efficiency, Efficient Irrigation, Green Gardening, and Green Landscaping. Understanding these measure classes can help guide behavior-based energy program developers in selecting target behaviors and designing interventions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Walker Branch Watershed: Daily Stream Metabolism and Organic Carbon Spiraling Metrics in the West Fork of Walker Branch, Tennessee, USA, 2004-2010

This dataset contains daily metabolism estimates of gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP), in addition to organic carbon spiraling length (SOC) and mineralization velocity (VfOC) estimates at the West Fork of Walker Branch, a small headwater stream, in the Walker Branch Watershed, Tennessee, USA. Observations were made from 2004-2010 (2004-01-01 to 2010-12-31). These data were generated to assess seasonal and interannual variability in metabolism and organic carbon spiraling and to explore potential driver variables, as analyses of intra- and interannual variability in metabolism and organic carbon spiraling are currently limited, leaving knowledge gaps in the driving mechanisms of and future changes to stream metabolism and carbon processing under climate change. Additionally, measurements of discharge (Q), stream width, stream- and canopy-level photosynthetically active radiation (PAR), water temperature, and precipitation from this time frame are included. This dataset contains one data file in comma separated (*.csv) format.

54 ENVIRONMENTAL SCIENCES↗

Nutrient and carbon concentrations in dated soil cores at US-OWC Ameriflux wetland site (OWC NERR)

Soil cores were sampled at the Old Woman Creek (OWC) National Estuarine Research Reserve at the south shore of Lake Erie, near Huron, Ohio, USA. OWC is a temperate mineral soil marsh. We dated the soil cores using lead isotope analysis and measured the concentrations of carbon and nutrients (nitrogen, phosphorus) throughout the core depths. We analyzed 36 cores, sampled along three transects at areas of the wetland with different hydrological regimes. Each transect included three coring sites at different water depth categories (shallow, intermediate deep) with four core samples per coring site. The data can be used to determine the carbon sequestration rates and nutrient accumulation rates, at multiple locations throughout OWC wetland.Dataset, in csv format, with data variables in columns, and different cores and core depths slices in rows, includes results from 36 sediment cores (0-30 cm depth) taken at 9 locations (4 replicates at each location) along 3 gradients of water depth (shallow, intermediate, deep), each at a different hydrologic location (outflow, backflow, middle). At each depth slice within a core, we provide depth, date (using 210Pb), bulk density, and the concentrations of carbon, nitrogen, phosphorus, d13C, and d15N.

54 ENVIRONMENTAL SCIENCES↗

Pyrogenic Organic Matter Laboratory Experiment: Aerobic Respiration and Geochemistry from Variably Inundated Stream Sediments (v3)

This dataset supports a broader study examining the effects of variable inundation and pyrogenic organic matter on ecosystem respiration. The dataset provides data generated from a laboratory batch experiment investigating the interaction between variable inundation conditions (wet and dry sediment) and pyrogenic organic matter (burned and unburned treatments). The contents include time series dissolved oxygen, sediment geochemistry data, and field metadata (including qualitative information on instream and river corridor characteristics). This data package was originally published in November 2025. It was updated in April 2026 (v2; new and modified files) and May 2026 (v3; modified files). See the change history section in the readme for more details For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) international generic sample number (IGSN) mapping file; (5) readme; (6) field protocol; (7) sample name metadata; (8) an environmental context picture for the dry and inundated sampling locations; and (9) a subfolder with sample data from the sediment incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) gravimetric moisture; (4) partial pressure and production rates of carbon dioxide, methane, and nitrous oxide; (5) field wet sediment mass, dry sediment mass, water mass, and field wet sediment volume in incubation and sediment NPOC/TN vials; (6) methods codes; (7) respiration rates, pH, and temperature from after the incubation, raw time series dissolved oxygen and temperature, and a subfolder containing associated plots and scripts; (8) ions; (9) FTICR-MS methods; and (10) a subfolder of 12 Tesla (12T) FTICR-MS data. This folder contains the CoreMS processed data and three subfolders, one containing the .xml files, one containing the CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .html, .Rmd, .py, .cal, .json, or .jpg.

54 ENVIRONMENTAL SCIENCES↗

Changes in soil water content and lateral flow exert large effects on soil thermal dynamics across Alaskan landscapes

Both lateral surface and subsurface water flow affect soil moisture dynamics, yet most land surface models only solve subsurface water movement vertically. Here, we use a 3D ecosystem model that considers both land surface and subsurface hydrologic processes to simulate soil moisture, which is then used to drive a 1-D vertical soil thermal model to simulate the soil moisture effects on soil thermal dynamics in central Alaska. Our coupled model improves soil temperature (ST) estimates by 43.5% in comparison with observational data. Soil moisture has little effect on ST during the wet season (-1.5%) and a substantial influence during the dry season (60%). Spatially, water lateral flow has significant impacts on both soil moisture and ST, causing model estimates for thawed areas in the transition season to increase by ~10% in the study area. Our results highlight the importance of considering dynamical soil moisture, as well as lateral flow effects, on soil thermal dynamics in permafrost regions.

54 ENVIRONMENTAL SCIENCES↗

Insights into the Reactivity of Brookite TiO 2 Nanorods in Liquid Water from Ab Initio Molecular Dynamics Simulations

Brookite TiO 2 , a rare natural polymorph of TiO 2 , has been reported to be an excellent photocatalyst for the production of hydrogen from water and aqueous alcohol solutions, especially when it is reduced and synthesized in the form of nanorods. Here, we investigate the reactivity of stoichiometric and reduced brookite nanorods in liquid water using ab initio molecular dynamics and hybrid density functional theory calculations. Our simulations show a much higher water dissociation fraction on reduced nanorods than on stoichiometric ones, with an accumulation of the resulting bridging hydroxyls (O br H) and terminal hydroxyls (Ti –OH) on different facets of the nanorod. ObrH groups accumulate preferentially on low-energy (210) facets, where they are stabilized by adjacent reduced Ti (Ti 3+ ) sites, while Ti –OH groups prefer to form at the four-fold coordinated Ti atoms on high-energy (010) facets. This hydroxylation pattern also favors the spatial localization of excited holes on the (010) facets. This coupling between water-induced surface chemistry and charge separation underpins the enhanced photocatalytic activity of brookite nanorods, providing useful information for the design of more efficient TiO2-based nanostructures for solar-driven hydrogen evolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data and scripts associated with a manuscript on residence time distribution simulation in two 10-kilometer long river sections

This data package is associated with the publication “On the Transferability of Residence Time Distributions in Two 10-km Long River Sections with Similar Hydromorphic Units” submitted to the Journal of Hydrology (Bao et al. 2024).Quantifying hydrologic exchange fluxes (HEFs) at the stream-groundwater interface, along with their residence time distributions (RTDs) in the subsurface, is crucial for managing water quality and ecosystem health in dynamic river corridors. However, directly simulating high-spatial resolution HEFs and RTDs can be a time-consuming process, particularly for watershed-scale modeling. Efficient surrogate models that link RTDs to hydromorphic units (HUs) may serve as alternatives for simulating RTDs in large-scale models. One common concern with these surrogate models, however, is the transferability of the relationship between the RTDs and HUs from one river corridor to another. To address this, we evaluated the HEFs and the resulting RTD-HU relationships for two 10-kilometer-long river corridors along the Columbia River, using a one-way coupled three-dimensional transient surface-subsurface water transport modeling framework that we previously developed. Applying this framework to the two river corridors with similar HUs allows for quantitative comparisons of HEFs and RTDs using both statistical tests and machine learning classification models. This data package includes the model inputs files and the simulation results data. This data package contains 10 folders. The modeling simulation results data are in the folders 100H_pt_data and 300area_pt_data, for the study domain Hanford 100H and 300 area respectively. The remaining eight folders contain the scripts and data to generate the manuscript figures. The file-level metadata file (Bao_2024_Residence_Time_Distribution _flmd.csv) includes a list of all files contained in this data package and descriptions for each. The data dictionary file (Bao_2024_Residence_Time_Distribution _dd.csv) includes column header definitions and units of all tabular files.

54 ENVIRONMENTAL SCIENCES↗

Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)"

This data package contains the associated data and scripts for Nagamoto, E., Ombadi, M., Ciulla, F. et al. Widespread drought-driven declines in streamflows and water quality in the Upper Colorado River Basin during 1998-2022. Commun Earth Environ 7, 734 (2026). https://doi.org/10.1038/s43247-026-03890-5. This purpose of this study was to investigate the impact of the 21st century drought on water quantity and quality at catchments throughout the Upper Colorado River Basin (UCRB). We used stream flow, water temperature, specific conductance, air temperature, precipitation, and catchment attribute data for over 200 sites in the UCRB, collected from the National Water Information System using Basin3D (Varadharajan, 2023), GAGESII (Falcone, 2010), and the Google Earth Engine. We identified years of severe drought between 1998 and 2022 using the Standardized Precipitation Evaporation Index (SPEI), then calculated the relative change percentage of the stream flow, water temperature, and specific conductance from drought versus non-drought years. We used the attribute information from GAGESII to investigate what physical traits of catchments are associated streamflow vulnerability (greater relative change) or resilience to drought. We used land cover data from the National Land Cover Database (USGS, 2024) to assess any changes to physical attributes that may not be represented in the static attributes information in GAGESII. To increase data availability, we modeled stream temperature using methods from Willard, 2023. While the study period is water years 1998 to 2022, the raw water quantity and quality data extends to 1950 and the meteorological data extends to 1980. The data and code can be downloaded via the UCRB_drought.zip. Within the zip, the files are organized as follows: - INPUTS: Contains all input data used in UCRB_Drought_Workflow.ipynb - OUTPUTS: Contains all intermediate data created from UCRB_Drought_Workflow.ipynb as well as final products including the calculated Standardized Evapotranspiration Index (SPEI) - climatic_variables: The code used to collect meteorologic data from Google Earth Engine - feature_importance: The code used for the catchment attributes analysis - preprocessing: Code used in UCRB_Drought_Workflow_Preprocessing.ipynb - pyeto: Code used in UCRB_Drought_Workflow_Preprocessing.ipynb - calculations: Code used in UCRB_Drought_Workflow_Impacts.ipynb - plotting: Code used in UCRB_Drought_Workflow_Impacts.ipynb - README.md - UCRB_Drought_Workflow_Preprocessing.ipynb: The code used to prep raw data for the analysis - UCRB_Drought_Workflow_Impact.ipynb: The code which uses the prepped raw data for analysis, and plots all figures - requirements_ucrb-drought_v2.yml: The requirements file to create a virtual environment and Jupyter Lab kernel to run the code The INPUTS folder is organized into the following major directories and sub-directories. The "RDC_WT_SC_RAW" folder contains raw data for streamflow, water temperature, and specific conductance in a ".h5" file. The "NLCD_RAW" folder contains ".csv" files with annual land cover percentages for counties within the UCRB. The "MET_RAW" folder contains a ".csv" file with monthly meteorological data (air temperature and precipitation) for the sites in the UCRB which was obtained from code in the climatic_variables folder. The "GAGESII" folder contains ".csv" files with physical catchment attribute variables for catchments across the country. The "WT_LSTM_data" folder contains ".csv" files with calculated WT (Willard, 2023) and the associated RMSEs. The "Upper_Colorado_River_Basin_Boundary" folder contains geographic data including a shapefile for plotting in the UCRB_Drought_Workflow.ipynb. The "RESERVOIRS_RAW" folder contains ".csv" files for each reservoir in the UCRB with daily reservoir storage. There are also two files in the INPUTS folder that have combined reservoir storage data and reservoir metadata. The OUTPUTS folder is organized into the following major directories and sub-directories. The "RDC_WT_SC_data" folder contains a folder "Water_year" with the associated cleaned data, metadata, and data availability information in ".csv" files, a folder "Median_Relchange" with the relative change comparing drought to non-drought years in ".csv" files, and a folder "Peak95_Min5_Relchange" that has ".csv" files for the relative change in peak (95th %) and minimum (5th %) variables. The "NLCD_data" folder contains the difference in land cover from the beginning to end of the study period and the percentage of the county that is within UCRB bounds can be found in Nagamoto et al (2025)). The "MET_data" folder contains separated monthly air temperature and precipitation data and the calculated PET in ".csv" files. The "SPEI_data" folder contains ".csv" files with calculated SPEI values (one restricted to the study period and the other with information from the entire MET data period). The "Paper_Tables" folder contains two ".csv" files containing site information and data availability and information about the GAGESII trait aggregated categories. The base directory includes the file “flmd.csv” for a list and description of all files and the file “dd.csv” for data dictionaries. Scripts for preprocessing, analysis, and figure generation are located in the associated GitHub repository found at [https://github.com/iNAIADS/drought-impacts/tree/develop/UCRB-drought]. UPDATE 1: Title and code file updated to match submitted manuscript 10-15-2025. UPDATE 2: Code and data files updated to match revised manuscript 3-4-2026. UPDATE 3: Code and data files updated to match revised manuscript 6-7-2026. ** NOTE: DD and FLMD have not been updated yet. UPDATE 4: Added associated Manuscript information and DD and FLMD have been updated. To cite this code, please use the following BibTeX: @misc{nagamoto2025drought, author = {Emily Nagamoto and Fabio Ciulla and Mohammad Ombadi and Jared Willard and Rosemary Carroll and Charuleka Varadharajan}, title = {Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)"}, year = {2025}, doi = {10.15485/2551894}, publisher = {ESS-DIVE Repository}, url = {https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2551894} }

54 ENVIRONMENTAL SCIENCES↗

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↗

Hyporheic hydraulic geometry: Conceptualizing relationships among hyporheic exchange, storage, and water age

Hyporheic exchange is now widely acknowledged as a key driver of ecosystem processes in many streams. Yet stream ecologists have been slow to adopt nuanced hydrologic frameworks developed and applied by engineers and hydrologists to describe the relationship between water storage, water age, and water balance in finite hydrosystems such as hyporheic zones. Here, in the context of hyporheic hydrology, we summarize a well-established mathematical framework useful for describing hyporheic hydrology, while also applying the framework heuristically to visualize the relationships between water age, rates of hyporheic exchange, and water volume within hyporheic zones. Building on this heuristic application, we discuss how improved accuracy in the conceptualization of hyporheic exchange can yield a deeper understanding of the role of the hyporheic zone in stream ecosystems. Although the equations presented here have been well-described for decades, our aim is to make the mathematical basis as accessible as possible and to encourage broader understanding among aquatic ecologists of the implications of tailed age distributions commonly observed in water discharged from and stored within hyporheic zones. Our quantitative description of “hyporheic hydraulic geometry,” associated visualizations, and discussion offer a nuanced and realistic understanding of hyporheic hydrology to aid in considering hyporheic exchange in the context of river and stream ecosystem science and management.

54 ENVIRONMENTAL SCIENCES↗

FTICR-MS Data from Multi-continent River Water and Sediment and from Coastal River Fresh and Saline Sediment Associated with: “Dissolved Organic Matter Functional Trait Relationships are Conserved Across Rivers”

This data package is associated with the publication “Dissolved Organic Matter Functional Trait Relationships are Conserved Across Rivers” submitted to PNAS (Stegen et al., 2023). The study aims to understand large-scale spatial structure of the dissolved organic matter (DOM) thermodynamic traits and inter-trait relationships by investigating (1) river water and sediments collected along 97 rivers spanning 3 continents and (2) coastal sediment collected from fresh and saline locations in Pacific and Gulf/Atlantic rivers. Sediment extracts and water samples were analyzed using ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). This dataset is comprised of three folders (1) Coastal, (2) WHONDR_S19S, and (3) Data_Dictionaries. Coastal contains (1) a subfolder with processed FTICR-MS data as csv files and sample collection metadata, (2) a subfolder with R scripts used to process the data and create associated figures, (3) a subfolder with the raw, unprocessed FTICR-MS data as .xml files, and (4) a readme file with more information about the dataset and instructions for using Formularity (https://omics.pnl.gov/software/formularity). WHONDRS_S19S contains (1) a csv file with processed FTICR data, (2) a csv with sample collection metadata, (3) a csv with sample geospatial data, (4) a csv with simulated lambda model outputs, (5) a subfolder with R scripts used to process the data and create associated figures, and (6) a readme file with more information regarding WHONDRS raw FTICR data and processing scripts. Data_Dictionaries contains data dictionaries for each csv file in the data package. The 97 global river corridors were part of a WHONDRS (https://whondrs.pnnl.gov) study. The raw, unprocessed FTICR-MS data with additional data can be found at doi:10.15485/1729719 for sediments and doi:10.15485/1603775 for water. This data package contains the processed data used in the associated manuscript. The coastal data has not been previously published, and this data package contains both the raw and processed data. Version 3 of this data package published February 2023 includes updates to the title of the manuscript, additional data and data dictionary and updated scripts linked to new analysis.

54 ENVIRONMENTAL SCIENCES↗

Declining Reservoir Reliability and Increasing Reservoir Vulnerability: Long-Term Observations Reveal Longer and More Severe Periods of Low Reservoir Storage for Major United States Reservoirs

Hydrological drought is a pervasive and reoccurring challenge in managing water resources. Reservoirs are critical for lessening the impacts of drought on water available for many uses. We use a novel and generalized approach to identify periods of unusually low reservoir storage—via comparisons to operational rule curves and historical patterns—to investigate how droughts affect storage in 250 reservoirs across the conterminous U.S. (CONUS). We find that the maximum amount of water stored in reservoirs is decreasing, and that periods of unusually low storage are becoming longer, more severe, and more variable in (a) western and central CONUS reservoirs, and (b) reservoirs with primarily over-year storage. Results suggest that reservoir storage has become less reliable and more vulnerable to larger deviations from desired storage patterns. These changes have coincided with ongoing shifts to the hydroclimate of CONUS, and with sedimentation further reducing available reservoir storage.

54 ENVIRONMENTAL SCIENCES↗

Wetland Soil Characterization and Methane Production Impacted by Nickel Addition, Argonne and Tims Branch Wetlands, September and October 2020

Abstract:Freshwater wetland soils are foci of biogeochemical cycling as they serve as key sources of methane to the atmosphere. An array of metalloenzymes is essential to anaerobic microbial carbon transformations. Nickel is notably recognized as playing key roles in the enzymatic pathways of methanogenesis. Low availability of trace metals limits microbial element cycling in laboratory studies, but the occurrence of such limitations in natural subsurface aquatic systems is poorly understood. Microcosm incubation studies were carried out using two distinct wetland soils, one from a marsh wetland and the second from a riparian wetland, to explore the effect of dissolved Ni concentrations on methane production. Data are provided for wetland soil characterization and soil incubation experiments using materials from marsh wetlands at Argonne National Laboratory and riparian wetlands in the Tims Branch watershed at Savannah River National Laboratory. The characterization data consists soil carbon, nitrogen, sulfur, and iron contents plus as well as the solid-phase concentrations of copper, nickel, cobalt, and zinc, bioessential trace metals that may limits microbial metabolic process if they have low availability. The data for the soil incubation experiments include fluid pH, fluid dissolved trace metal concentrations, and cumulative methane production. Three soil incubations are reported: marsh wetland soil with increasing nickel addition, marsh wetland soil in sulfate-free water with increasing nickel addition, and riparian wetland soil with increasing nickel addition. All data are provided in text-based CSV format with header sections indicating the data contained in each file and the corresponding units. Note that "u" is used in place of Greek lower case mu to indicate the micro prefix on units. A Table of Contents file (Yan_Soil_Incubations_2020_TOC.txt) provides an index for the data contained in the individual files.

54 ENVIRONMENTAL SCIENCES↗

U.S. Indirect and Direct Potable Water Reuse Systems (2020)

Collection of proposed, operating, demonstration, and pilot study potable reuse systems across the U.S. as of 2020. Information includes project name, location, augmentation type, capacity, year operational, treatment train, and source water type. References are included in this submission. As potable reuse facilities undergo expansions or upgrades, treatment trains and capacities are subject to change. Operational status may also change. Treatment trains listed are reported to the detail that the source provides. Type and doses of chemical post-treatment or chlorination is often not specified. Please see README section in spreadsheet for definitions of acronyms used.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Uptake and speciation of trace metal inputs to Wetland Soils from Illinois and South Carolina and Stream Sediments from Tennessee

Metals occur in all ecosystems, although their concentrations vary depending on their natural geologic conditions and surrounding human activities. In addition to metals intrinsically present from the geology of a particular system, metals can enter environmental systems from a wide variety of natural and anthropogenic sources, such as sediment re-suspension, mining operations, industrial processes, agricultural activities, and atmospheric deposition. While metals can be toxic at high concentrations, some metals serve as essential micronutrients for biogeochemical processes. Metal transport and availability in engineered and natural water systems depend on processes of adsorption/desorption, oxidation/reduction, dissolution/precipitation, and ligand complexation. Insights into the speciation of metals and their bioavailability will also help advance understanding of the roles of metals in the biogeochemical cycling of nutrients. We conducted batch experiments under anoxic conditions on soils and sediments collected from three different natural aquatic systems to understand their response to influxes of dissolved Cu, Ni and Zn. While soils and sediments from all sites could strongly bind added trace metals, there were substantial differences in trace metal uptake trends between different sites, especially for Cu. There was no distinct correlation between trace metal uptake and the total organic matter, iron, and sulfur content present in the samples. X-ray absorption spectroscopy indicated that the speciation of the freshly added metals taken up by the solids differs substantially from the speciation of the metals originally present in unamended samples. Cu sulfides dominated speciation at low loadings (1 µmol/g), whereas complexation to thiol groups and formation of metallic Cu governed speciation at high loadings (10 µmol/g). For Ni and Zn, adsorption to mineral surfaces and organic matter governed their speciation in materials from most sites. This study suggests that the background speciation of metals in natural aquatic systems is a poor predictor of the speciation and lability of metals introduced to terrestrial aquatic systems from anthropogenic or natural processes. Our findings imply that geochemical processes controlling trace metal speciation may vary considerably with metal loading in different natural systems. Data are provided for marsh wetland soils at Argonne National Laboratory (Marsh 1 and Marsh 2), riparian wetland soils (Riparian 1 and Riparian 2) in the Tims Branch watershed at Savannah River National Laboratory, and stream bed sediments (Stream 1 and Stream 2) from East Fork Poplar Creek near Oak Ridge National Laboratory. Data package includes the results of trace metal uptake experiments conducted on the selected sites for determining their capacity to immobilize metals under different loadings. XANES spectra for Cu, Ni, ad Zn at different loadings are included in the package. The abundance of different trace metal species obtained using linear combination fitting in ATHENA are also included in the data.

54 ENVIRONMENTAL SCIENCES↗

Biogeochemistry of Pond B (Savannah River Site, South Carolina, USA): Water column and Sediments

Pond B at Savannah River Site (SRS, South Carolina) is a monomictic reservoir that received SRS R reactor cooling water from 1961–1964. Previous studies conducted between the 1980s–1990s on the water column and sediments of Pond B measured trace amounts of Pu (33 MBq 238Pu and 430 MBq 239,240Pu), 241Am, and 137Cs. Since then, the pond has been relatively isolated and the radionuclide concentrations have not been monitored over time. Herein, about 30 years after the last publication on Pond B, we are re-evaluating the geochemistry and radionuclide distribution within Pond B at five locations along a horizontal transect from the inlet to outlet. In addition, we are conducting the first analysis of the microbial community composition. This data package consists of water column measurements (1) using a multi-probe sonde, (2) plutonium isotopes and total concentrations, (3) total organic/inorganic carbon concentrations, (4) trace metals and major ions concentrations, and (6) microbial community composition. Sediment measurements include (1) plutonium isotopes and total concentrations and (2) microbial community composition.For sediment core and porewater, please see other Pond B data package (ess-dive-60d2352a4495472-20200615T203925174).The data in this package will be submitted for peer review in 2023.

54 ENVIRONMENTAL SCIENCES↗

HarDWR - Water Management Area (WMA) Shapefiles

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - No changes v1.0 - Initial public release Description Borders of all Water Management Areas (WMAs) across the 11 western-most states of the coterminous United States are available filtered through a single source. The legal name for this set of boundaries varies state-by-state. The data is provided as two compressed shapefiles. One, stateWMAs, contains data for all 11 states. For 10 of those states, Arizona being the exception, the polygons represent the legal management boundaries used by those states to manage their surface and groundwater resources respectively. WMAs refer to the set of boundaries a particular state uses to manage its water resources. Each set of boundaries was collected from the states individually, and then merged into one spatial layer. The merging process included renaming some columns to enable merging with all other source layers, as well as removing columns deemed not required for followup analysis. The retained columns for each boundary are: basinNum - the state provided unique numerical ID; basinName - the state provided English name of the area, where applicable; state - the state name; and uniID - a unique identifier we created by concatenating the state name, and underscore, and the state numerical ID. Arizona is unique within this collection of states in that surface and groundwater resources are managed using two separate sets of boundaries. During our followup analysis (Grogan et al., in review) we decided to focus on one set of boundaries, those for surface water. This is due to the recommendation of our hydrologists that the surface water boundary set is a more realist representation of how water moves across the landscape, as a few of the groundwater boundaries are based on political and/or economic considerations. Therefore, the Arizona surface WMAs are included within stateWMAs. The Arizona groundwater WMAs are provided as a separate file, azGroundWMAs, as a companion to the first file for completeness and general reference. WMA spatial boundary data sources by state: Arizona: Arizona Surface Water Watersheds; Collected February, 2020; https://gisdata2016-11-18t150447874z-azwater.opendata.arcgis.com/datasets/surface-watershed/explore?location=34.158174%2C-111.970823%2C7.50 Arizona: Arizona Ground Water Basins; Collected February, 2020; https://gisdata2016-11-18t150447874z-azwater.opendata.arcgis.com/datasets/groundwater-basin-2/explore?location=34.158174%2C-111.970823%2C7.50 California: California CalWater 2.2.1; Collected February, 2020; https://www.mlml.calstate.edu/mpsl-mlml/data-center/data-entry-tools/data-tools/gis-shapefile-layers/ Colorado: Colorado Water District Boundaries; Collected February, 2020; https://www.colorado.gov/pacific/cdss/gis-data-category Idaho: Idaho Department of Water Resources (IDWR) Administrative Basins; Collected November, 2015; https://data-idwr.opendata.arcgis.com/datasets/fb0df7d688a04074bad92ca8ef74cc26_4/explore?location=45.018686%2C-113.862284%2C6.93 Montana: Collected June, 2019; Directly contacted Montana Department of Natural Resources and Conservation (DNRC) Office of Information Technology (OIT) Nevada: Nevada State Engineer Admin Basin Boundaries; Collected April, 2020 https://ndwr.maps.arcgis.com/apps/mapviewer/index.html?layers=1364d0c3a0284fa1bcd90f952b2b9f1c New Mexico: New Mexico Office of the State Engineer (OSE) Declared Groundwater Basins; Collected April, 2020 https://geospatialdata-ose.opendata.arcgis.com/datasets/ose-declared-groundwater-basins/explore?location=34.179783%2C-105.996542%2C7.51 Oregon: Oregon Water Resources Department (OWRD) Administrative Basins; Collected February, 2020; https://www.oregon.gov/OWRD/access_Data/Pages/Data.aspx Utah: Utah Adjudication Books; Collected April, 2020; https://opendata.gis.utah.gov/datasets/utahDNR::utah-adjudication-books/explore?location=39.497165%2C-111.587782%2C-1.00 Washington: Washington Water Resource Inventory Areas (WRIA); Collected June, 2017; https://ecology.wa.gov/Research-Data/Data-resources/Geographic-Information-Systems-GIS/Data Wyoming: Wyoming State Engineer's Office Board of Control Water Districts; Collected June, 2019; Directly contacted Wyoming State Engineer's Office

Economics↗

Integrating Contaminant Source Indicators, Water Quality Measures, and Ecotoxicity to Characterize Contaminant Mixtures and Per- and Polyfluoroalkyl Substance (PFAS) Variability in an Urban Watershed

Thousands of chemical contaminants threaten watersheds but are time and cost prohibitive to monitor. Identifying their sources, transport, and ecological risk is limited in heterogeneous urban watersheds. We present an integrative watershed approach using source-specific indicator compounds, common water quality measures, and ecotoxicity assays to examine the distribution of contaminant mixtures in an urbanized watershed. Indicator compound concentrations were temporally and spatially distributed for treated/untreated sewage (sucralose, artificial sweetener), road runoff (diphenyl-guanidine [DPG] and 6PPD-quinone [6PPD-Q], automobile tire additives), and lawncare runoff (aminomethanephosphonic acid (AMPA), major degradant of the herbicide glyphosate). Sucralose was predominately sourced from treated wastewater; measurable concentrations in tributaries indicated raw sewage inputs. DPG and 6PPD-Q concentrations correlated to road density during base flow and were elevated during stormflow. AMPA was measurable spring through fall, especially where lawns were dense. When specific sources dominated flow, water quality measures correlated with wastewater (sulfate, potassium, chloride, and sodium) and road runoff (chromium and lead) indicators. The limited behavioral toxicity observed in exposed zebrafish (Danio rerio) (18%) was not well explained by source-indicators. PFAS concentrations were highly variable spatially but not well explained by our source-specific indicator compounds. Here, more costly compound-specific monitoring may be necessary when multiple sources exist or when unexpected toxicity trends occur.

computer simulations↗