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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1977

Volcanism of the Eastern Snake River Plain, Idaho: A comparative planetary geology-guidebook

The Planetary Geology Field Conference on the central Snake River Plain was conceived and developed to accomplish several objectives. Primarily, field conferences are sponsored by the National Aeronautics and Space Administration to draw attention to aspects of terrestrial geology that appear to be important in interpreting the origin and evolution of extraterrestrial planetary surfaces. Another aspect is to present results of recent research in a region. A final objective of this conference is to bring together investigators of diverse backgrounds who share a common interest in the Snake River Plain. The Snake River Plain appears to be similar in surface morphology to many volcanic regions on the Moon, Mars, and possibly Mercury. Therefore, the Snake River Plain, in combination with the relatively good state of preservation, the lack of forests or other heavy vegetation, and the good network of jeep trails, is an area nearly ideal for analog studies.

Greeley, R.↗

DOE OSTI2025

Source apportionment of aerosols at the White River IMPROVE site near the SAIL site

This data set contains source apportionment results at the White River IMPROVE site (39.1536, -106.8209), which is about 30 km north of the Surface Atmosphere Integrated Field Laboratory (SAIL) Campaign site. The IMPROVE network (Malm et al. 1994) collected 24-hour aerosol filter samples every three days over several decades at this site. Chemical concentrations in the PM2.5 fraction of 19 elements (Al, As, Br, Ca, Cl, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Se, Si, Ti, V, and Zn), along with nitrate, sulfate, elemental carbon (EC), organic carbon (OC), and calculated coarse mass concentrations (PM10−PM2.5 mass concentrations), from 2014 to 2023, were used as input for the PMF analysis. PMF was performed using EPA PMF 5.0 (Norris et al. 2014). A five-factor solution was chosen as the optimal solution. These factors were identified as coarse dust, fine dust, biomass burning, sulfate-dominated, and nitrate-dominated sources. This data set is useful for understanding aerosol sources and their long-term variability near this region.

biomass burning↗

NASA NTRS1987

Analysis of Eocene depositional environments - Preliminary TM and TIMS results, Wind River Basin, Wyoming

Both Landsat TM and aircraft Thermal IR Multispectral Scanner (TIMS) data have been used to map the lithofacies of the Wind River Basin's Eocene physical and biological environments. Preliminary analyses of these data have furnished maps of a fault contact boundary and a complex network of fluvial ribbon channel sandstones. The synoptic view thereby emerging for Eocene fluvial facies clarifies the relationships of ribbon channel sandstones to fossil-bearing overbank/floodplain facies and certain peleosols. The utility of TM and TIMS data is thereby demonstrated.

Stucky, Richard K.↗

DOE OSTI2023

Uncertainty quantification of machine learning models to improve streamflow prediction under changing climate and environmental conditions

Machine learning (ML) models, and Long Short-Term Memory (LSTM) networks in particular, have demonstrated remarkable performance in streamflow prediction and are increasingly being used by the hydrological research community. However, most of these applications do not include uncertainty quantification (UQ). ML models are data driven and can suffer from large extrapolation errors when applied to changing climate/environmental conditions. UQ is required to quantify the influence of data noises on model predictions and avoid overconfident projections in extrapolation. In this work, we integrate a novel UQ method, called PI3NN, with LSTM networks for streamflow prediction. PI3NN calculates Prediction Intervals by training 3 Neural Networks. It can precisely quantify the predictive uncertainty caused by the data noise and identify out-of-distribution (OOD) data in a non-stationary condition to avoid overconfident predictions. We apply the PI3NN-LSTM method in the snow-dominant East River Watershed in the western US and in the rain-driven Walker Branch Watershed in the southeastern US. Results indicate that for the prediction data which have similar features as the training data, PI3NN precisely quantifies the predictive uncertainty with the desired confidence level; and for the OOD data where the LSTM network fails to make accurate predictions, PI3NN produces a reasonably large uncertainty indicating that the results are not trustworthy and should avoid overconfidence. PI3NN is computationally efficient, robust in performance, and generalizable to various network structures and data with no distributional assumptions. It can be broadly applied in ML-based hydrological simulations for credible prediction.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2011

NREPS Applications for Water Supply and Management in California and Tennessee

Management of water resources is a balancing act between temporally and spatially limited sources and competitive needs which can often exceed the supply. In order to manage water resources over a region such as the San Joaquin Valley or the Tennessee River Valley, it is pertinent to know the amount of water that has fallen in the watershed and where the water is going within it. Since rain gauge networks are typically sparsely spaced, it is typical that the majority of rainfall on the region may not be measured. To mitigate this under-sampling of rainfall, weather radar has long been employed to provide areal rainfall estimates. The Next-Generation Weather Radars (NEXRAD) make it possible to estimate rainfall over the majority of the conterminous United States. The NEXRAD Rainfall Estimation Processing System (NREPS) was developed specifically for the purpose of using weather radar to estimate rainfall for water resources management. The NREPS is tailored to meet customer needs on spatial and temporal scales relevant to the hydrologic or land-surface models of the end-user. It utilizes several techniques to mitigate artifacts in the NEXRAD data from contaminating the rainfall field. These techniques include clutter filtering, correction for occultation by topography as well as accounting for the vertical profile of reflectivity. This presentation will focus on improvements made to the NREPS system to map rainfall in the San Joaquin Valley for NASA s Water Supply and Management Project in California, but also ongoing rainfall mapping work in the Tennessee River watershed for the Tennessee Valley Authority and possible future applications in other areas of the continent.

Gatlin, P.↗

DOE OSTI2024

3D Quantification of Pore Networks and Anthropogenic Carbon Mineralization in Stacked Basalt Reservoirs

Basalt formations are promising candidates for the geologic storage of anthropogenic CO 2 due to their storage capacity, porosity, permeability, and reactive geochemical trapping ability. The Wallula Basalt Carbon Storage Pilot Project demonstrated that supercritical CO 2 injected into >800 m deep Columbia River Basalt Group stacked reservoir flow tops mineralizes to ankerite-siderite-aragonite on month-year timescales, with 60% of the 977 metric tonnes of CO 2 converted within two years. The potential impacts of mineral precipitation and consequent changes on rock porosity, pore structure, pore size, and pore size distributions have likely been underestimated hitherto. Herein, we address these knowledge gaps using X-ray Micro Computed Tomography (XMT) to evaluate the pore network architecture of sidewall cores recovered two years after CO 2 injection. In the present study, we performed a detailed quantitative analysis of the CO 2 -reacted basalt cores by XMT imaging. Reconstructed 3D images were analyzed to study the distribution and volumetric details of porosity and carbonate nodules in the cores along with the various other phases, providing insight into paragenesis and carbonate growth mechanisms, including mineralogic/chemical zonation. Finally, these findings are being used to parametrize multiphase reactive transport models to predict the fate and transport of subsurface CO 2 , enabling scale-up to commercial-scale geologic carbon storage in basalts and other reactive mafic-ultramafic formations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Laboratory time series moisture manipulative experiment from sediment across the contiguous US: time series aerobic respiration and geochemistry (v2)

This dataset supports a broader study examining the effects of wetting and drying on hyporheic zone respiration across the contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata (including qualitative information on instream and river corridor characteristics). Samples were collected as part of the WHONDRS CONUS-Scale Model-Sample Study (CM). This study was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. The data package associated with the CM study is available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689. CM sampling began in April 2022 and ended in October 2023. This study uses subsamples from a subset of CM samples collected between June 2022 and June 2023. The original field samples were labeled as CM_###. Subsequent subsamples for this study were labeled as EC_###. The labels from the field samples and the EC subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EC_001 is a subsample from CM_001). See the critical details section below for more details on sample naming. This data package was originally published in August 2024. It was updated in February 2026 (v2; new and modified files). See the change history section in the readme for more details. For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) field protocol; and a (6) a subfolder with sediment sample data from the incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) adenosine triphosphate (ATP); (4) percent carbon and nitrogen; (5) effect size; (6) iron (II); (7) gravimetric moisture; (8) respiration rates and raw dissolved oxygen values; (9) specific conductance; (10) pH; (11) temperature; (12) a summary containing median values of each data type for each treatment (wet and dry); (13) methods codes; (14) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla FTICR-MS data. This folder contains three subfolders, one containing the sediment .xml data files, one containing the sediment CoreMS output files, the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .ref, or .xml.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

A Ground-Based Network for Improved Validation of Satellite Carbon Dioxide and Methane Observations Over the Eastern United States

Satellite observations of greenhouse gases (GHGs), notably carbon dioxide and methane, over the Eastern United States, are currently only validated indirectly and/or sporadically. There are only four existing routine, ground-based remote sensing locations in the United States suitable for validation of satellite GHG observations: Edwards and Pasadena, CA, Lamont, OK, and Park Falls, WI as part of the Total Carbon Column Observing Network (TCCON). Among other efforts, e.g. the Network for the Detection of Atmospheric Composition Change (NDACC) and EM27/SUN deployments led by the University of Toronto, the only sites west of the Mississippi River are Park Falls, WI and Toronto, ON. The only remaining validation tools, vicarious calibration and airborne campaigns, are sporadic in space and/or time and thus coincide with only a small subsample of available soundings and conditions. As a result, satellite GHG observations over the east coast of the United States, home to more than half of its population, lack a consistent, widespread means of validation. We describe an ongoing effort to position 8 EM27/SUN spectrometers along the Eastern Seaboard over the next two years. The goals of this effort are to improve both satellite validation and our understanding of human and natural influences on the carbon cycle of the Eastern US, the former enabling the latter. This work is intended to augment past, ongoing, and future inter-agency programs, e.g., the NIST Urban Testbed, routine aircraft and aircore sampling by NOAA, and NASA’s Atmospheric Carbon and Transport (ACT)-America sub-orbital campaign, in particular by offering information on broader time and spatial scales than what is already available while maintaining the high-accuracy constraints of in situ data. We will present early analysis including siting considerations to capture local and/or background conditions and comparison to NASA’s Goddard Earth Observing System (GEOS) modeling and assimilation systems. This includes a 40-day, 3-km horizontal resolution global simulation of early 2020 and a 50-km retrospective analysis of Orbiting Carbon Observatory 2 (OCO-2) observations over 2015-present. Both are valuable tools for analyzing expected and observed signals and are useful boundary conditions for yet higher-resolution studies.

Brad Weir↗

DOE OSTI2021

Influences on Discharge Partitioning on a Large River Delta: Case Study of the Mississippi-Atchafalaya Diversion, 1926-1950

The modern Mississippi River (M.R.) Delta is plumbed by the Mississippi and Atchafalaya rivers, setting water and sediment dispersal pathways for Earth’s fifth-largest river system. The Atchafalaya River’s (A.R.) partial annexation of discharge from the M.R., particularly between 1926 and 1950, prompted warnings of a rapid river avulsion and the construction of the Old River Control Structure to regulate flow. Natural and anthropogenic causes of this discharge annexation are difficult to disentangle. Here, we develop and validate a hydrodynamic model of flow partitioning through the historic channel network. We then isolate how several key changes to the system affected discharge partitioning and stage at the A.R.-M.R. diversion. Simulations show that erosion of the upper A.R. can account for 73% of the water discharge increase. Dredging in the lower A.R. between 1932 and 1950 can account for 35% of the water discharge increase, and was also an important control on shear stress distribution. The lower M.R. was slightly erosional during this period, and therefore hindered the A.R. discharge increase. Significant lacustrine delta deposition in A.R. had little effect on partitioning. These findings highlight the importance of A.R. enlargement processes on avulsion dynamics at this site. Given the essential nature of this river junction to the society, transportation, and commerce of the United States, improved attribution of discharge increases may lead to future management strategies that are broadly impactful.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Trace elements and their isotopes in streams and rivers

The occurrence and speciation of trace elements in streams and rivers are controlled by interconnected hydrogeological, biogeochemical, and anthropogenic factors that include rock weathering, climate, vegetation, and land use within the watershed. This chapter provides a broad overview of trace element abundance, speciation, and mobility in streams and rivers, including an assessment of how trace elements are partitioned into dissolved, colloidal, and particulate phases. We also discuss how trace elements are mobilized into stream networks and transformed during transport. Select isotopic systems are reviewed to provide examples of how isotopic analyses can be used to understand geochemical and anthropogenic processes.

Herndon, Elizabeth [ORNL] (ORCID:0000000291945493)↗

DOE OSTI2021

Application of remote sensing precipitation data and the $\mathrm{CONNECT}$ algorithm to investigate spatiotemporal variations of heavy precipitation: Case study of major floods across Iran (Spring 2019)

In recent years, the number of floods following unprecedented rainfall events have increased in Iran during early spring (March 21st to April 20th, referred to in Iran as the month of “Farvadin”). While numerous studies have addressed changes in climate extremes and precipitation trends at different temporal scales from daily to annual across the country, analyses of short-duration and heavy precipitation, especially during recent years, are rarely considered. Furthermore, most studies investigate the variations in extremes and total precipitation using a limited number of synoptic weather stations across Iran. Here this study assesses the variations in heavy precipitation (precipitation with intensities greater than or equal to 3 mm/3 h) at 0.04° spatial and 3-hourly temporal resolution during the month of Farvardin. In addition, the effect of atmospheric river conditions over Iran and their possible link to intensifying heavy precipitation is explored. For this purpose, the CONNected-objECT (CONNECT) algorithm is applied on a precipitation dataset, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), and an Integrated Water Vapor Transport (IVT) dataset from the NASA Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2). The results suggest that the increase in the number of floods in recent years is related to the increase in the intensity and volume of heavy precipitation events, although the frequency and duration of heavy precipitation events have not changed significantly. Furthermore, the results show that atmospheric river conditions over the country are present during the same window as each year’s most extreme events. It is found that 8 out of 13 of the largest ARs over Iran come from moisture plumes with pathways over the African and Red Sea.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Predicting turbulent wake flow of marine hydrokinetic turbine arrays in large-scale waterways via physics-enhanced convolutional neural networks

We present a physics-enhanced convolutional neural network (PECNN) algorithm for reconstructing the mean flow and turbulence statistics in the wake of marine hydrokinetic (MHK) turbine arrays installed in large-scale meandering rivers. The algorithm embeds the mass and momentum conservation equations into the loss function of the PECNN algorithm to improve the physical realism of the reconstructed flow fields. The PECNN is trained using large eddy simulation (LES) results of the wake flow of a single row of turbines in a virtual meandering river. Subsequently, the trained PECNN is applied to predict the wake flow of MHK turbines with arrangements and positionings different than those considered during the training process. The PECNN predictions are validated using the results of separately performed LES. The results show that the PECNN algorithm can accurately predict the wake flow of MHK turbine farms at a small fraction of the cost of LES. The PECNN can improve the accuracy by around 1% and reduce the physical constraint indices by around 50% compared to the CNN without physical constraints. This work underscores the potential of PECNN to develop reduced-order models for control co-design and optimization of MHK turbine arrays in natural riverine environments.

Mechanics↗

NASA NTRS2008

The Citizens and Remote Sensing Observational Network (CARSON) Guide: Merging NASA Remote Sensing Data with Local Environmental Awareness

"Citizen science" generally refers to observatoinal research and data collection conducted by non-professionals, commonly as volunteers. In the environmental science field, citizen scientists may be involved with local nad regional issues such as bird and wildlife populations, weather, urban sprawl, natural hazards, wetlands, lakes and rivers, estuaries, and a spectrum of public health concerns. Some citizen scientists may be primarily motivated by the intellectual challenge of scientific observations. Citizen scientists may now examine and utilize remote-sensing data related to their particular topics of interest with the easy-to-use NASA Web-based tools Giovanni and NEO, which allow exploration and investigation of a wide variety of Earth remote sensing data sets. The CARSON (Citizens and Remote Sensing Observational Network) Guide will be an online resource consisting of chapters each demonstrating how to utilize Giovanni and NEO to access and analyze specific remote-sensing data. Integrated in each chapter will be descriptions of methods that citizen scientists can employ to collect, monitor, analyze, and share data related to the chapter topic which pertain to environmental and ecological conditions in their local region. A workshop held in August 2008 initiated the development of prototype chapters on water quality, air quality, and precipitation. These will be the initial chapters in the first release of the CARSON Guide, which will be used in a pilot project at the Maryland Science Center in spring 2009. The goal of the CARSON Guide is to augment and enhance citizen scientist environmental research with NASA satellite data by creating a participatory network consisting of motivated individuals, environmental groups and organizations, and science-focused institutions such as museuma and nature centers. Members of the network could potentially interact with government programs, academic research projects, and not-for-profit organizations focused on environmental issues.

Acker, James↗

DOE OSTI2023

Supporting Advancement in Weather and Water Prediction in the Upper Colorado River Basin: The SPLASH Campaign

Water is a critical resource that causes significant challenges to inhabitants of the western United States. These challenges are likely to intensify as the result of expanding population and climate-related changes that act to reduce runoff in areas of complex terrain. To better understand the physical processes that drive the transition of mountain precipitation to streamflow, the National Oceanic and Atmospheric Administration has deployed suites of environmental sensors throughout the East River watershed of Colorado as part of the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH). This includes surface-based sensors over a network of five different observing sites, airborne platforms, and sophisticated remote sensors to provide detailed information on spatiotemporal variability of key parameters. With a 2-yr deployment, these sensors offer detailed insight into precipitation, the lower atmosphere, and the surface, and support the development of datasets targeting improved prediction of weather and water. Initial datasets have been published and are laying a foundation for improved characterization of physical processes and their interactions driving mountain hydrology, evaluation and improvement of numerical prediction tools, and educational activities. SPLASH observations contain a depth and breadth of information that enables a variety of atmospheric and hydrological science analyses over the coming years that leverage collaborations between national laboratories, academia, and stakeholders, including industry.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

SAIL-Net Raw and Post Corrected POPS Data Fall 2021 - Summer 2023

SAIL-Net is a DOE funded project in the East River Watershed near Crested Butte, Colorado with the goal of advancing our understanding of aerosol-cloud interactions in complex, mountainous regions. Through the deployment of a network of six low cost microphysics nodes in Fall 2021 in the same domain at the SAIL campaign, SAIL-Net provides data on aerosol size distributions, cloud condensation nuclei (CCN), and ice nucleation particles (INP). This network enables the investigation of small-scale variations in complex terrain. Two datasets are provided - one containing raw data and the other containing post-corrected data. The raw dataset provides the raw data recorded from the POPS which were deployed at each of the six sites. These data are organized by site and broken down into daily data files. The six site names used here are: “gothic”, “irwin”, “cbtop”, “cbmid”, “pumphouse”, and “snodgrass”. These data are not cleaned or post-corrected, but some flags have been added. The data are reported at 1 second time resolution. The post-corrected dataset provides the post-corrected and cleaned data recorded from the POPS which were deployed at each of the six sites. This data are also organized by site (same as those found in the raw data) and broken down into daily data files. Unlike the raw POPS data, these data have already been cleaned to remove what we believe are bad values. These data should be ready to use with no cleaning. For a full description of the cleaning and post-correction process, see the readme.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

SAIL-Net CloudPuck CCN Data

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2021

Acoustic Sensor Network for Planetary Exploration

This paper investigates the concept of an acoustic sensor network that can monitor a variety of geophysical processes occurring on other planetary bodies. In many cases sound is naturally omnidirectional and travels at known speeds which depend on the composition and density of the atmosphere. The differences in the time of flight of signals received by a distributed microphone network can be used to locate the source of the sound. We suggest this property is ideal for mobile planetary robots and can be used to expand the exploration envelope considerably by directing camera pointing or rover path planning thus extending beyond line-of-sight exploration. Acoustic signatures have been used in a variety of fields (e.g., sonar, heavy machinery) to identify and catalog sounds associated with a specific vessels and malfunctioning machinery. Our ears have cataloged hundreds of sounds and we continuously use these sounds both consciously and subconsciously to extract information about our surroundings. This paper investigates the use acoustic measurements on other planetary bodies that could be used to characterize specific environmental parameters such as rain droplet size, wind speed, thunder, or dust devil vortex diameter. The paper identified other important sound sources that are thought to occur on other bodies in our solar system include; booming or singing dunes, waves, rivers, streams, fluidfalls, geysers, hurricanes, tornados, ice flow, volcanoes, planetary quakes, avalanche, rock slides and ice cracking. In addition, this paper focused on issues associated with the development of appropriate sensors for the network including the specification of the sensitivity, frequency response, and directional response of each of the microphones in the network in order to aid in localization of sound sources. We also presented our initial development of the transducers for potential mission targets including Mars and Titan and investigated the use of signal processing techniques including windowing, time frequency plots and correlation techniques to resolve phase differences between sensors in the network to aid in localization. We also identified additional benefits of these sensor networks in that they could used as engineering sensors to diagnose mechanical malfunctions on a rover or lander actuators or mechanisms. We also noted that they could also enhance public outreach by adding sound to videos.

Malaska, Mike↗

DOE OSTI2023

WHONDRS River Corridor Sediment and Water Geochemistry and In Situ Sensor Data from Machine-Learning-Informed Sites across the Contiguous United States (v6)

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 were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Sampling began in April 2022 and ended in October 2023. In addition to the 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. Other data types collected from SSS that were not part of CM were published in a separate data package (https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566). This data package was originally published in February 2023. It was updated in June 2023 (v2; new and modified files); December 2023 (v3; new and modified files); June 2024 (v4; new and modified files); April 2024 (v5; new and modified files); and September 2025 (v6; 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. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocols; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) surface water major cations and anions and averages; (4) sediment grain size data; (5) sediment iron (II) data and averages; (6) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment specific surface area; (11) sediment percent carbon and nitrogen; (12) sediment gravimetric moisture and averages; (15) sediment X-ray diffraction (XRD) data; (16) sediment adenosine triphosphate (ATP) and averages; (17) a subfolder with sediment incubation respiration data, scripts, and plots; (18) surface water and sediment FTICR methods; and (19) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS).The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank 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. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗