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At least 667 records · Page 37

Diatom influence on the production characteristics of hydrate-bearing sediments: Examples from Ulleung Basin, offshore South Korea

The Ulleung Basin Gas Hydrate field expeditions in 2007 (UBGH1) and 2010 (UBGH2) sought to assess the Basin's gas hydrate resource potential. Coring operations in both expeditions recovered evidence of gas hydrate, primarily as fracture-filling (or vein type) morphologies in mainly silt-sized, fine-grained sediment, but also as pore-occupying hydrate in the coarser-grained layers of interbedded sand and fine-grained systems. A commonality across many of these occurrences is the presence of diatoms in the fine-grained sediment. Here we tested fine-grained sediment (median grain size <12.5 μm) associated with hydrate occurrences at four UBGH2 sites (UBGH2-2-2, UBGH2-3, UBGH2-6 and UBGH2-11) to investigate potential impacts of diatoms on efforts to extract methane from hydrate, or to tap hydrocarbon reservoirs beneath hydrate-bearing sediment. Two key considerations are: the extent to which diatoms control sediment mechanical properties, and the extent to which pore-water freshening, which occurs as gas hydrate breaks down during resource extraction, alters the diatom control on sediment mechanical properties. We conducted experiments to measure sediment index properties, sedimentation behavior and compressibility to address these considerations. We relied on scanning electron microscope (SEM) imagery and X-ray powder diffraction (XRD) to characterize the sediment mineralogy. Our high-level findings are that at the ~20–45% (by volume) diatom concentrations observed at these UBGH2 sites, sediment compressibility increases with diatom content, but diatoms only appear to increase porosity and permeability at the highest diatom concentration (~45%). Our measurements suggest in situ compression indices of 0.35–0.55 and permeabilities on the order of 0.01milliDarcies (1 × 10 -17 m 2 ) can be anticipated at these sites. Importantly, these properties are not expected to vary significantly upon pore water freshening that accompanies gas hydrate dissociation during production.

58 GEOSCIENCES↗

How do Hydrological Variability and Human Activities Control the Spatiotemporal Changes of Riverine Nitrogen Export in the Upper Mississippi River Basin?

Excessive nitrogen export from agricultural watersheds remains a critical water quality challenge, with the Upper Mississippi River Basin (UMRB) significantly contributing to downstream eutrophication and hypoxia in the Gulf. This study investigates the spatiotemporal dynamics of riverine nitrate plus nitrite (NO 3 − + NO 2 − -N) export across the UMRB at high spatial resolution (12-digit Hydrologic Unit Codes or HUC12 subwatershed scale) during 2001−2020 and quantifies the effects of anthropogenic activities and hydrological variability on riverine NO 3 − + NO 2 − -N export changes in the region between 2001−2005 and 2016−2020. Our results revealed hotspots of substantial increases in NO 3 − + NO 2 − -N yields across the UMRB, with distinct regional patterns in driving factors. Over the entire UMRB, NO 3 − + NO 2 − -N yields increased by 9.7 kg/ha/yr on average from 2001−2005 to 2016−2020, with anthropogenic activities contributing 4.8 kg/ha/yr and hydrological variability contributing 4.9 kg/ha/yr. The northern and western UMRB had combined influences from both anthropogenic activities and hydrological variability, while the east-central regions had predominantly hydrologically driven changes. Agricultural sources, including fertilizer, manure, and biological nitrogen fixation, collectively contributed over 80% of NO 3 − + NO 2 − -N loading throughout the basin. Furthermore, this framework for disentangling human and hydrological impacts provides critical insights for developing effective and targeted watershed management strategies to reduce nutrient losses and improve water quality.

54 ENVIRONMENTAL SCIENCES↗

Can we rely on drought–ending “miracles” in the Colorado River Basin?

Unexpected and large spring precipitation events in the Colorado River Basin (CRB) that significantly alleviated an otherwise severe water shortage have been observed for over a century, such as the “Miracle May” of 2015. Although these events are often termed as “drought-busting” or “miracle events” by water managers and the media, they have not been extensively researched or characterized. In this collaborative study with water managers across the CRB, we propose a definition for these hard-to-predict, ultra-high precipitation events occurring during the late-snow or snowmelt season. This characterization provides a framework for quantifying the frequency and intensity of extreme dry-to-wet springtime transitions. Despite limitations of climate model simulations due to uncertainties and the inhomogeneous qualities, our findings suggest that such transitions may become less frequent and less intense in a warming climate. Finally, in view of the potentially wetter but less-snowy climate in the basin, the need for future research to more quantitatively assess these “miracle events” is emphasized.

54 ENVIRONMENTAL SCIENCES↗

Appalachian Basin Play Fairway Analysis: Thermal Quality Analysis in Low-Temperature Geothermal Play Fairway Analysis (GPFA-AB)

This collection of files are part of a larger dataset uploaded in support of Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB). Phase 1 of the GPFA-AB project identified potential Geothermal Play Fairways within the Appalachian basin of Pennsylvania, West Virginia and New York. This was accomplished through analysis of 4 key criteria: thermal quality, natural reservoir productivity, risk of seismicity, and heat utilization. Each of these analyses represent a distinct project task, with the fifth task encompassing combination of the 4 risks factors. Supporting data for all five tasks has been uploaded into the Geothermal Data Repository node of the National Geothermal Data System (NGDS). This submission comprises the data for Thermal Quality Analysis (project task 1) and includes all of the necessary shapefiles, rasters, datasets, code, and references to code repositories that were used to create the thermal resource and risk factor maps as part of the GPFA-AB project. The identified Geothermal Play Fairways are also provided with the larger dataset. Figures (.png) are provided as examples of the shapefiles and rasters. The regional standardized 1 square km grid used in the project is also provided as points (cell centers), polygons, and as a raster. Two ArcGIS toolboxes are available: 1) RegionalGridModels.tbx for creating resource and risk factor maps on the standardized grid, and 2) ThermalRiskFactorModels.tbx for use in making the thermal resource maps and cross sections. These toolboxes contain item description documentation for each model within the toolbox, and for the toolbox itself. This submission also contains three R scripts: 1) AddNewSeisFields.R to add seismic risk data to attribute tables of seismic risk, 2) StratifiedKrigingInterpolation.R for the interpolations used in the thermal resource analysis, and 3) LeaveOneOutCrossValidation.R for the cross validations used in the thermal interpolations. Some file descriptions make reference to various 'memos'. These are contained within the final report submitted October 16, 2015. Each zipped file in the submission contains an 'about' document describing the full Thermal Quality Analysis content available, along with key sources, authors, citation, use guidelines, and assumptions, with the specific file(s) contained within the .zip file highlighted. UPDATE: Newer version of the Thermal Quality Analysis has been added here: https://gdr.openei.org/submissions/879 (Also linked below) Newer version of the Combined Risk Factor Analysis has been added here: https://gdr.openei.org/submissions/880 (Also linked below)

15 GEOTHERMAL ENERGY↗

Tularosa Basin Play Fairway: Weights of Evidence Models

These models are related to weights of evidence play fairway anlaysis of the Tularosa Basin, New Mexico and Texas. They were created through Spatial Data Modeler: ArcMAP 9.3 geoprocessing tools for spatial data modeling using weights of evidence, logistic regression, fuzzy logic and neural networks. It used to identify high values for potential geothermal plays and low values. The results are relative not only within the Tularosa Basin, but also throughout New Mexico, Utah, Nevada, and other places where high to moderate enthalpy geothermal systems are present (training sites).

15 GEOTHERMAL ENERGY↗

Appalachian Basin Play Fairway Analysis Gravity, Magnetics, and Earthquake Data

This archived dataset contains magnetic and gravity imaging data for the Appalachian Basin, compiled using Poisson Wavelet Multiscale Edge Detection, referred to as 'worm' for brevity, and stored in a PostGIS database, along with shapefiles and CSVs of relevant data. The archive also includes regional earthquake data going back to 1973 and relevant world stress map data. These data are used in estimating the seismic hazards (both natural and induced) for candidate direct use geothermal locations in the Appalachian Basin Play Fairway Analysis by Jordan et al. (2015).

15 GEOTHERMAL ENERGY↗

Appalachian Basin Play Fairway Analysis: Revised 2016 Combined Risk Factor Analysis

This submission contains information used to compute the combined risk factors for deep geothermal energy opportunities in the Appalachian Basin, in the context of a the Play Fairway Analysis project. The risk factors are sedimentary rock reservoir quality, thermal resource quality, potential for induced seismicity, and utilization for direct-use heating of neighborhoods. The methods used to combine the risk factors included taking the average, the geometric mean, and the minimum of the four risk factors. Combined risk maps are provided for three different sedimentary rock reservoir metrics. Combined risk maps are also provided for the three geologic risk factors alone (thermal, reservoir, and seismic), and for the three risk factors that exclude reservoir quality (utilization, seismicity, and thermal qualities). The 2015 data submission should be visited to obtain associated shapefiles, which include: 1) definition of the High and Medium priority play fairways (Inner_Fairway, and Outer_Fairway), 2) definition of the US Census Places (usCensusPlaces), 3) places (cities) of interest in the region (Places_of_Interest) identified as geothermal play fairways, 4) the point centers of the raster cells (Raster_Center_Locations), and 5) locations of industries and special-use communities (e.g., colleges and military bases) identified as low temperature heat users (Industries). The 2015 submission also includes: 1) a methodology memo that explains how the risk factors were combined (GPFA-AB_combining_risk_factors.pdf), 2) the earthquake-based seismic risk map, and 3) supporting information with details of the calculations or processing used in generating these data files. More details on each file are given in the spreadsheet "list_of_contents.xlsx" in the folder "Supporting_Information". Code used to calculate values is available at https://github.com/calvinwhealton/geothermal_pfa under the folder "combining_metrics". Note that the 2016 code is currently under the branch named "combining_metrics_2016" in the folder called "combining_metrics". This branch may be merged with the master branch in the future. Many files contained within this submission update and replace the indicated files contained in: Cornell University. (2015). Risk Factor Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB) [data set]. Retrieved from https://gdr.openei.org/submissions/622. doi:10.15121/1261942

15 GEOTHERMAL ENERGY↗

Appalachian Basin Temperature-Depth Maps and Structured Data in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy

This dataset contains shapefiles and rasters that summarize the results of a stochastic analysis of temperatures at depth in the Appalachian Basin states of New York, Pennsylvania, and West Virginia. This analysis provides an update to the temperature-at-depth maps provided in the Geothermal Play Fairway Analysis of the Appalachian Basin (GPFA-AB) Thermal Quality Analysis (GDR repository 879: https://gdr.openei.org/submissions/879). This dataset improves upon the GPFA-AB dataset by considering several additional uncertainties in the temperature-at-depth calculations, including geologic properties and thermal properties. A Monte Carlo analysis of these uncertain properties and the GPFA-AB estimated surface heat flow was used to predict temperatures at depth using a 1-D heat conduction model. In this data submission, temperatures are provided for depths from 1-5 km in 0.5 km increments. The mean, standard deviation, and selected quantiles of temperatures at these depths are provided as shapefiles with attribute tables that contain the data. Rasters are provided for the mean and standard deviation data. Figures and maps that summarize the data are also provided. For the pixel corresponding to Cornell University, Ithaca, NY, a .csv file containing the 10,000 temperature-depth profiles estimated from the Monte Carlo analysis is provided. These data are summarized in a figure containing violin plots that illustrate the probability of obtaining certain temperatures at depths below Cornell.

15 GEOTHERMAL ENERGY↗

CLM simulated data at three FLUXNET sites and three SNOTEL sites in the Colorado River Basin

This data package includes 6 csv files that include Community Land Model (CLM) simulations for three Fluxnet sites (i.e., US-NR1, US-GLE and US-VCM) and three SNOTEL sites (i.e., ER-BT, ER-SP and ER-PK) in the Upper Colorado River Basin area. Data inputs include meteorological forcing data (obtained from Fluxnet and SNOTEL databases) and CLM-simulated evapotranspiration (ET) data from 2005 to 2016. These datasets support the development of subseasonal regime approach based on statistics driven Hidden Markov Model to assess intra- and inter-annual variability of ET, which improves our understanding of climate change's impacts on water resources and ecosystem dynamics in the Colorado River Basin.

54 ENVIRONMENTAL SCIENCES↗

Data and Scripts associated with a manuscript on ecosystem responses to wildfires in the Columbia River Basin

This data package is associated with the publication “Ecosystem leaf area, gross primary production, and evapotranspiration responses to wildfire in the Columbia River Basin” submitted to Biogeosciences (Shi et al., 2024; doi: 10.22541/au.171053013.30286044/v1). In this research, data products, leaf area index (LAI), gross primary production (GPP), and evapotranspiration (ET), from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to quantify the resistance and resilience of different ecosystem types in the Columbia River Basin (CRB). A machine learning algorithm, random forest (RF), was used to examine the impacts of precipitation, vapor pressure deficit (VPD), and burn severity from Monitoring Trends in Burn Severity (MTBS) on ecosystem resilience. The data package includes the processed MODIS data products, precipitation, VPD, and burn severity in 138 fire regions in CRB and the input files for RF model training. This data package includes six folders. The MODIS products are included in three MODIS_* folders with shell scripts for data clipping and *ncl files for data processing: (1) “/MODIS_LAI_CRB”; (2) “/MODIS_GPP_CRB”; and (3) “/MODIS_ET_CRB”. All the processed data for each fire event are NetCDF formatted. The MTBS burn severity data and the shell and *ncl scripts used for data processing are in the folder named (4) “MTBS_fire”. The ERA meteorological fields and the data processing scritps are in (5) “ERA_Var_CR”. All the scripts for figure development are in the format of *ncl and in the folder (6) “paper_scripts”. See the file ending in “flmd.csv” for a list of all files contained in this data package and descriptions for each. Tabular column headers and units are described in the data dictionary file ending in “dd.csv”.

54 ENVIRONMENTAL SCIENCES↗

Illinois Basin Coal Wells

Data described of the Illinois Basin Coal Wells from the Technical Report: Paronish, T.; Crandall, D.; Jarvis, K.; Workman, S.; Pohl, M.; Drosche, J.; Mckisic, T.; McLaughlin P.; Freidberg, J.; Delpomdor F. Computed Tomography Scanning and Petrophysical Measurements of Illinois Basin Coal Wells; DOE/NETL-2024/XXX; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2024; p 59.

Coal↗

Characteristics of KE Basin Sludge Samples Archived in the RPL - 2007

Samples of sludge were collected from the K East fuel storage basin (KE Basin) floor, contiguous pits (Weasel Pit, North Load Out Pit, Dummy Elevator Pit, and Tech View Pit), and fuel storage canisters between 1995 and 2003 for chemical and radionuclide concentration analysis, physical property determination, and chemical process testing work. Because of the value of the sludge in this testing and because of the cost of obtaining additional fresh samples, an ongoing program of sludge preservation has taken place with the goals to track the sludge identities and preserve, as well as possible, the sludge composition by keeping the sludge in sealed jars and maintaining water coverage on the sludge consistent with the controlling Fluor Hanford (FH) Sampling and Analysis plans and FH contracts with the Pacific Northwest National Laboratory (PNNL). This work was originally initiated to provide material for planned hydrothermal treatment testing in accordance with the test plan for the Sludge Treatment Project (STP) corrosion process chemistry follow on testing (Delegard et al. 2007). Although most of the planned hydrothermal testing was canceled in July 2007 (as described in the forward of Delegard et al. 2007), sample consolidation and characterization was continued to identify a set of well-characterized sludge samples that are suited to support evolving STP initiatives. The work described in the letter was performed by the PNNL under the direction of the Sludge Treatment Project, managed by Fluor Hanford.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Identifying and Mitigating Potential Nutrient and Sediment Hot Spots under a Future Scenario in the Missouri River Basin

Using the Soil and Water Assessment Tool (SWAT) for large-scale watershed modeling could be useful for evaluating the quality of the water in regions that are dominated by nonpoint sources in order to identify potential “hot spots” for which mitigating strategies could be further developed. An analysis of water quality under future scenarios in which changes in land use would be made to accommodate increased biofuel production was developed for the Missouri River Basin (MoRB) based on a SWAT model application. The analysis covered major agricultural crops and biofuel feedstock in the MoRB, including pasture land, hay, corn, soybeans, wheat, and switchgrass. The analysis examined, at multiple temporal and spatial scales, how nitrate, organic nitrogen, and total nitrogen; phosphorus, organic phosphorus, inorganic phosphorus, and total phosphorus; suspended sediments; and water flow (water yield) would respond to the shifts in land use that would occur under proposed future scenarios. The analysis was conducted at three geospatial scales: (1) large tributary basin scale (two: Upper MoRB and Lower MoRB); (2) regional watershed scale (seven: Upper Missouri River, Middle Missouri River, Middle Lower Missouri River, Lower Missouri River, Yellowstone River, Platte River, and Kansas River); and (3) eight-digit hydrologic unit (HUC-8) subbasin scale (307 subbasins). Results showed that subbasin-level variations were substantial. Nitrogen loadings decreased across the entire Upper MoRB, and they increased in several subbasins in the Lower MoRB. Most nitrate reductions occurred in lateral flow. Also at the subbasin level, phosphorus in organic, sediment, and soluble forms was reduced by 35%, 45%, and 65%, respectively. Suspended sediments increased in 68% of the subbasins. The water yield decreased in 62% of the subbasins. In the Kansas River watershed, the water quality improved significantly with regard to every nitrogen and phosphorus compound. The improvement was clearly attributable to the conversion of a large amount of land to switchgrass. The Middle Lower Missouri River and Lower Missouri River were identified as hot regions. Further analysis identified four subbasins (10240002, 10230007, 10290402, and 10300200) as being the most vulnerable in terms of sediment, nitrogen, and phosphorus loadings. Overall, results suggest that increasing the amount of switchgrass acreage in the hot spots should be considered to mitigate the nutrient loads. The study provides an analytical method to support stakeholders in making informed decisions that balance biofuel production and water sustainability.

land use change↗

488-1D Ash Basin closure cap help modeling- Microdrain® liner option

At the request of Area Completion Engineering and in support of the 488-1D Ash Basin closure, the Savannah River National Laboratory (SRNL) performed hydrologic simulations of the revised 488-1D Ash Basin closure cap design using the Hydrologic Evaluation of Landfill Performance (HELP) model. The revised design substitutes a MicroDrain Liner®—60-mil low-density polyethylene geomembrane structurally integrated with 130-mil drainage layer—for the previously planned drainage/barrier system—300-mil geosynthetic drainage layer (GDL), 300-mil geosynthetic clay liner (GCL), and 6-inch common fill soil layer. For a 25-year, 24-hour storm event, HELP model v3.07 was employed to (1) predict the peak maximum daily hydraulic head for the geomembrane layer, and (2) ensure that South Carolina Department of Health and Environmental Control (SCDHEC) requirements for the barrier layer (i.e., ≤ 12 inches hydraulic head on top of a barrier having a saturated hydraulic conductivity ≤ 1.0E-05 cm/s) will not be exceeded. A 25-year, 24-hour storm event at the Savannah River Site (SRS) is 6.1 inches rainfall (Weber 1998). HELP model v3.07 results based upon the new planned cap design suggest that the peak maximum daily hydraulic head on the geomembrane barrier layer will be 0.15 inches for a minimum slope equal to 3%, which is two orders of magnitude below the SCDHEC upper limit of 12 inches.

58 GEOSCIENCES↗

488-1D Ash basin closure cap help modeling-Microdrain® liner option

At the request of Area Completion Engineering and in support of the 488-1D Ash Basin closure, the Savannah River National Laboratory (SRNL) performed hydrologic simulations of the revised 488-1D Ash Basin closure cap design using the Hydrologic Evaluation of Landfill Performance (HELP) model. The revised design substitutes a MicroDrain Liner®—50-mil linear low-density polyethylene geomembrane structurally integrated with 130-mil drainage layer—for the previously planned drainage/barrier system—300-mil geosynthetic drainage layer (GDL), 300-mil geosynthetic clay liner (GCL), and 6-inch common fill soil layer. For a 25-year, 24-hour storm event, HELP model v3.07 was employed to (1) predict the peak maximum daily hydraulic head for the geomembrane layer, and (2) ensure that South Carolina Department of Health and Environmental Control (SCDHEC) requirements for the barrier layer (i.e., ≤ 12 inches hydraulic head on top of a barrier having a saturated hydraulic conductivity ≤ 1.0E-05 cm/s) will not be exceeded. A 25-year, 24-hour storm event at the Savannah River Site (SRS) is 6.1 inches rainfall (Weber 1998). HELP model v3.07 results based upon the new planned cap design suggest that the peak maximum daily hydraulic head on the geomembrane barrier layer will be 0.179 inches for a minimum slope equal to 3%, which is approximately two orders of magnitude below the SCDHEC upper limit of 12 inches.

54 ENVIRONMENTAL SCIENCES↗

L-Basin microbial monitoring program - evaluation of 20 years of monitoring

This report summarizes the results from over 20-years’ of activities for microbial monitoring of the bulk water, floc analysis, and test coupon surfaces for the Savannah River Site L Basin. The Microbial Monitoring Program provides important information for the characterization of overall water quality as it impacts the continued safe storage of spent nuclear fuel in L Basin. The potential impacts to fuel storage are: 1) microbial-influenced corrosion of the fuel; and 2) biofouling of the fuel storage systems.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Enhanced Recovery Opportunities in the Appalachian Basin

The Midwest Regional Carbon Sequestration Partnership (MRCSP) has incorporated the work of geologic research teams (Geoteams) in its regional characterization, project planning and carbon dioxide (CO2) injection implementation work since the partnership was established by the U.S. Department of Energy (DOE) in 2003. Over this 16-year period, the cohort of Geoteams has grown from five to ten states and has contributed to the characterization of geologic sequestration opportunities, refinement of reservoir and seal data, and supported injection efforts through both predictive and post-injection assessments. The Appalachian Basin Geoteam consists of geologists from the state geological surveys of Kentucky, Maryland, New York, Ohio, Pennsylvania, and West Virginia. Pennsylvania and West Virginia led the research related to enhanced recovery opportunities in oil and gas fields, while Kentucky led the work associated with enhanced gas recovery (EGR) opportunities in organic-rich shales. The Appalachian Basin Geoteam evaluated reservoirs amenable to CO2-EOR and EGR using a combination of data sources and technical approaches. The Geoteam characterized the subsurface geology of the area in stepwise fashion, starting with existing geologic maps and fields/pools data generated as part of previous MRCSP regional characterization research. With this data, the Geoteam correlated stratigraphy and generated cross sections to delineate the extent, depths and thicknesses of those formations that may serve as reservoirs for either miscible or immiscible enhanced recovery projects. In addition, the team prepared structure and isopach maps for prospective formations, as well as assessments of gross and net porosity of these units. Once prospective localities were identified, the Geoteam selected a short list of oil fields in each of the three states for assessment for case study preparation.

01 COAL, LIGNITE, AND PEAT↗