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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

AmeriFlux FLUXNET-1F US-Ne2 Mead - irrigated maize-soybean rotation site

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Ne2 Mead - irrigated maize-soybean rotation site. This is the FLUXNET version of the carbon flux data for the site US-Ne2 Mead - irrigated maize-soybean rotation site produced by applying the standard ONEFlux (1F) software. Site Description - The study site is one of three fields (all located within 1.6 km of each other) at the University of Nebraska Eastern Nebraska Research, Extension and Education Center near Mead, Nebraska. This site is irrigated with a center pivot system. Prior to the initiation of the study, the irrigated site had a 10-yr history of maize-soybean rotation under no-till management. A tillage operation (disking) was done just prior to the 2001 planting to homogenize the top 0.1 m of soil, incorporate P and K fertilizers, as well as previously accumulated surface residues. Since this tillage operation, the site has been under no-till management in a maize-soybean rotation (maize odd years and soybean even years). There was a brief period due to an intercomparison study from 2010 to 2013 when fall conservation tillage was performed and maize (not soybean) was planted in 2010 and 2012. The management reverted to a strictly no-till maize-soybean crop rotation after 2014.

Suyker, Andy [University of Nebraska - Lincoln]↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-RC4 Moscow Mountain on-farm site

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-RC4 Moscow Mountain on-farm site. This is the FLUXNET version of the carbon flux data for the site US-RC4 Moscow Mountain on-farm site produced by applying the standard ONEFlux (1F) software. Site Description - The Moscow Mountain On-farm site operated 2012-2016 as part of a cluster of 5 towers (RC1 to RC5) operated for the Regional Approaches to Climate Change (REACCH) USDA-supported research project. The site is located in the high precipitation agroecological zone of the Columbia Plateau’s dryland cropping region, near Moscow, Idaho. The site was managed with conventional (reduced) tillage. The crop rotation was spring barley, spring field peas, winter wheat, and spring wheat. Soils are silt loam mollisols including the Latahco, Thatuna, Southwick, and Larkin soil series. The site topography is sloping and is situated within the rolling hills of the Palouse region.

Chi, Jinshu [The Hong Kong University of Science a↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-RC5 Moses Lake on-farm site

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-RC5 Moses Lake on-farm site. This is the FLUXNET version of the carbon flux data for the site US-RC5 Moses Lake on-farm site produced by applying the standard ONEFlux (1F) software. Site Description - The Moses Lake On-farm site operated 2013-2015 as part of a cluster of 5 towers (RC1 to RC5) operated for the Regional Approaches to Climate Change (REACCH) USDA-supported research project. The field was a half-circle irrigated plot with the irrigation pivot located on the edge of the field and the flux tower located next to the center of the pivot. The field was in wheat from tower establishment in June 2013 to harvest in August 2013. A cover crop of arugula and mustard was grown from August to October 2013. Potatoes were grown April to August 2014 and wheat (a spring cultivar planted in fall) was grown October 2014 to June 2015. Soils are coarse sandy loam mollisols in the Timmerman series. The site topography is flat.

Chi, Jinshu [The Hong Kong University of Science a↗
DOE OSTI2026

AmeriFlux FLUXNET-1F CA-TPA Ontario Turkey Point Observatory Agricultural Site

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-TPA Ontario Turkey Point Observatory Agricultural Site. This is the FLUXNET version of the carbon flux data for the site CA-TPA Ontario Turkey Point Observatory Agricultural Site produced by applying the standard ONEFlux (1F) software. Site Description - This agricultural flux tower site is located about 15 km southwest of Simcoe in southern Ontario, Canada. It was planted with corn (Zea mays) in 2020 and 2021, sweet potato (Ipomoea batatas) in 2022 and tobacco (Nicotiana tabacum) in 2023. The site is part of Turkey Point Environmental Observatory (TPEO). The establishment of the agricultural site has allowed TPEO to become representative of the major biomes in the Great Lakes region, encompassing coniferous and deciduous forests, as well as agricultural crops. The soil at this agricultural site is well-drained fine sandy loam. The area has a humid continental climate and has one of the longest-growing seasons in Canada with at least 150–160 frost-free days in a year.

Arain, M. Altaf [McMaster University]↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-Ne3 Mead - rainfed maize-soybean rotation site

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Ne3 Mead - rainfed maize-soybean rotation site. This is the FLUXNET version of the carbon flux data for the site US-Ne3 Mead - rainfed maize-soybean rotation site produced by applying the standard ONEFlux (1F) software. Site Description - The study site is one of three fields (all located within 1.6 km of each other) at the University of Nebraska Agricultural Research and Development Center near Mead, Nebraska. While the other two sites are equipped with irrigation systems, this site relies on rainfall. A tillage operation (disking) was done just prior to the 2001 planting to homogenize the top 0.1 m of soil, incorporate P and K fertilizers, as well as previously accumulated surface residues. Since initiation of the study in 2001, this site has been under a strictly no-till, maize-soybean rotation (maize odd years and soybean even years).

Suyker, Andy [University of Nebraska - Lincoln]↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-Ho3 Howland Forest (harvest site)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Ho3 Howland Forest (harvest site). This is the FLUXNET version of the carbon flux data for the site US-Ho3 Howland Forest (harvest site) produced by applying the standard ONEFlux (1F) software. Site Description - Closed conifer forest, minimal disturbance. References: Fernandez et al. (1993), Canadian Journal of Soil Science 73 317-328. Hollinger et al. (1999), Global Change Biology 5: 891-902. Savage KE, Davidson EA (2001), Global Biogeochemical Cycles 15 337-350. Scott et al. (2004), Environmental Management, Vol. 33, Supplement 1, pp. S9-S22. Hollinger et al. (2004), Global Change Biology 10: 1689-1706.

Ouimette, Andrew [USDA Forest Service]↗
DOE OSTI2021

Arctic Soil Patterns Analogous to Fluid Instabilities: Supporting Data

This dataset characterizes solifluction lobe morphology and spatial patterns using pre-existing LiDAR-derived digital elevation models of 25 sites across Norway with accompanying long term climate data for each site. Data were collected as part of an effort to better understand controls on the formation of solifluction patterns and to test the idea that they are analogous to fluid instabilities. We also provide soil velocity profiles and estimates of effective viscosity from across the world, drawn from literature. They were collected to improve our understanding of the rheology of soliflucting soil. See this article for more information on the theoretical motivation behind this dataset see "Arctic soil patterns analogous to fluid instabilities" (Glade et al., 2021). Data files arranged in a hierarchy and include image files *.tif and *.png, GIS shapefiles and geopackages (*.gpkg), *.csv (with same file as *.xlsx), and *.py (Python scripts readable with a text editor). Files also bundled into *.zip files. Note (2021-10-20): unit corrections made on two files: RR.csv and snowfall.csv. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Integrating Predictions for Improving Defect Classification Accuracy in NDT-based Assessment of Concrete - 20229

There is an increasing need to create predictive models for defect classification in concrete using the output of non-destructive testing (NDT) techniques. Recent advancement of machine-learning algorithms has offered several techniques for developing classification models for different types of data sets. However, the performance of these algorithms is very uncertain, mainly when applied to small and noisy datasets. For example, when human access is limited (e.g., nuclear facility), robot-based NDT is preferred. But compared to manual tests with humans present on site, the data sets are small, and more noise can exist. Therefore, it is imperative to develop new approaches to ensure a consistently high classification accuracy for inadequate data sets. This study explores the classification performance on NDT dataset using classifiers from different machine-learning algorithms, namely k-Nearest Neighbor (kNN), Decision Tree, Naive Bayes, Logistic Regression, and Support Vector Machine (SVM). The authors further integrated the predictions from these classifiers using proposed methods. The integration strategy combines the output of the classifiers based on two different measures, accuracy, and performance (ACC and PERF), using equations such as sum, average, and square-root-of-sums-of-squares (SRSS). Our results reveal varying classification accuracies across individual classifiers with different misclassifications across the test data set. The integration strategy provided significant improvement in the classification accuracy compared to the individual classifiers. Furthermore, the results indicate minimal variation across the integration methods as compared to the variation across the individual classifiers. To conclude, prediction integration offers a unique approach for combining the output of multiple classifiers to create redundancies with the potential of achieving high classification performance and improved reliability in predictive models for defect detection in concrete. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Impacts of a Prescribed Fire on Air Quality in Central New Mexico

A short-duration but high-impact air quality event occurred on 28 November 2018 along the Rio Grande Valley of New Mexico. This fire occurred outside the typical wildfire season, and greatly impacted the air quality in Socorro, NM, and the surroundings. Measurements were taken during the event using an aerosol light scattering technique (integrating nephelometer) and a particulate mass concentration monitor (DustTrak PM optical monitor). The instruments sampled the ambient air during the event on the campus of the New Mexico Institute of Mining and Technology in Socorro, New Mexico. The peak values on a 5-min basis of light scattering and the PM mass concentration reached 470 Mm -1 and 270 µg/m 3 , respectively. We examined the meteorological context of the event using local meteorological data and back trajectories using the NOAA HYSPLIT model to determine atmospheric transport and possible sources. Several fires, both prescribed and wildfires, occurred in the region including a prescribed burn at Bosque del Apache National Wildlife Refuge (17 km south-southeast of the receptor site). The data suggest that the prescribed burn at Bosque del Apache was the dominant contributor due to transport evidence and the event’s narrow spatiotemporal extent. The increasing importance of restoring ecosystem function using prescribed fire in wildland fire management will likely lead to more frequent air quality impacts and sets up policy tradeoffs that require a balance between these public goals. This study examines the evidence of the effects of a prescribed fire in a protected wildland area impacting the air quality in a nearby populated area.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Leaf spectra, Feb2016-April2016, PA-SLZ, PA-PNM, PA-BCI: Panama

This data package contains leaf spectra data measured on a monthly basis from February to April, 2016. Measurements were taken at the Bosque Protector San Lorenzo (SLZ), Barro Colorado Island (BCI) and Parque Natural Metropolitano (PNM) NGEE Tropics sites in Panama. Data from the BCI site are only available for March, 2016. Within the attached zip file are PDF manuals for instruments used, a guide to data collection protocol, and metadata files, including a PDF containing metadata for the 2016 ENSO gas exchange campaign. Also included is an additional zip file "2016_ENSO_BNL_Leaf_Spectra_Archive.zip" with data in .csv format organized by site. This data was collected as part of the 2016 ENSO campaign. See related datasets (existing and future) for further sample details, leaf water potential data, LMA, and gas exchange and leaf chemistry data. VERSION 2 update. The identification of a species from the PNM site has been corrected as follows: the identification of the tree initially identified as Pseudosamanea guachapele (ALBIED) has been revised to Albizia adinocephala (ALBIAD). The updated data package includes revised data, metadata and protocol documents updated to reflect this change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Bayesian approach to evaluation of soil biogeochemical models

Abstract. To make predictions about the carbon cycling consequences of rising global surface temperatures, Earth system scientists rely on mathematical soil biogeochemical models (SBMs). However, it is not clear which models have better predictive accuracy, and a rigorous quantitative approach for comparing and validating the predictions has yet to be established. In this study, we present a Bayesian approach to SBM comparison that can be incorporated into a statistical model selection framework. We compared the fits of linear and nonlinear SBMs to soil respiration data compiled in a recent meta-analysis of soil warming field experiments. Fit quality was quantified using Bayesian goodness-of-fit metrics, including the widely applicable information criterion (WAIC) and leave-one-out cross validation (LOO). We found that the linear model generally outperformed the nonlinear model at fitting the meta-analysis data set. Both WAIC and LOO computed higher overfitting risk and effective numbers of parameters for the nonlinear model compared to the linear model, conditional on the data set. Goodness of fit for both models generally improved when they were initialized with lower and more realistic steady-state soil organic carbon densities. Still, testing whether linear models offer definitively superior predictive performance over nonlinear models on a global scale will require comparisons with additional site-specific data sets of suitable size and dimensionality. Such comparisons can build upon the approach defined in this study to make more rigorous statistical determinations about model accuracy while leveraging emerging data sets, such as those from long-term ecological research experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The feasibility of MT tipper data to monitor CO2 storage sites

Monitoring carbon storage sites using geophysical techniques is a critical component to the success and safety of storage programs. Currently, the primary methods of monitoring such sites are seismic and, to a much lesser extent, electromagnetics using active sources. The cost of such methods, especially seismic, can be prohibitively expensive. Natural source lectromagnetics, or magnetotellurics (MT), represents a low-cost, and underutilized method with the potential to aid CO2 monitoring efforts. Specifically, the tipper of MT data gives insight to the dimensionality of the subsurface and is able to detect the expansion front of a CO2 plume in a saline reservoir. We analyze the feasibility of using the tipper to monitor two shallow CO2 plumes and conclude that the tipper may be a suitable method for long-term monitoring.<br>

Kohnke, Colton↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-ARM ARM Southern Great Plains site- Lamont

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-ARM ARM Southern Great Plains site- Lamont. This is the FLUXNET version of the carbon flux data for the site US-ARM ARM Southern Great Plains site- Lamont produced by applying the standard ONEFlux (1F) software. Site Description - Central facility tower crop field (winter wheat, corn, soy, alfalfa). The site also has continuous measurements of precise mixing ratios of CO2, CH4, CO, N2O, and isotopic ratio of 13CO2. In addition to 4 m system, there are sonic anemometers at 25 m and 60 m.

Biraud, Sebastien↗
DOE OSTI2022

AmeriFlux FLUXNET-1F CA-NS4 UCI-1964 burn site wet

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-NS4 UCI-1964 burn site wet. This is the FLUXNET version of the carbon flux data for the site CA-NS4 UCI-1964 burn site wet produced by applying the standard ONEFlux (1F) software. Site Description - The UCI-1964 wet site is located in a continental boreal forest, dominated by black spruce trees, within the BOREAS northern study area in central Manitoba, Canada. The site is a member of a chronological series of sites that are representative secondary succession growth stages after large stand replacement fires. Black spruce trees undergo a slow growth process enabling the accurate determination of the chronosequence of stand age disturbance. Additionally, boreal forests make up approximately 25% of forest ecosystems on earth. With both of these in mind, the UCI sites provide an excellent location to study the CO2 exchange between the atmosphere and boreal forest ecosystems as a function of sequential wildfires.

Goulden, Mike↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-ARb ARM Southern Great Plains burn site- Lamont

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-ARb ARM Southern Great Plains burn site- Lamont. This is the FLUXNET version of the carbon flux data for the site US-ARb ARM Southern Great Plains burn site- Lamont produced by applying the standard ONEFlux (1F) software. Site Description - The ARM SGP Burn site is located in the native tallgrass prairies of the USDA Grazinglands Research Laboratory near El Reno, OK. One of two adjacent 35 ha plots, the US-ARb plot was burned on 2005/03/08. The second plot, US-ARc, was left unburned as the control for experimental purposes. Aside from 2005, the region evaded burning activities for at least 15 years. Current disturbances consist of only light grazing activities.

Torn, Margaret↗