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At least 469 records · Page 26

AmeriFlux US-MN2 Morris: Corn-Soybean-Wheat with Cover Crops, Minimal Tillage

This is the AmeriFlux version of the carbon flux data for the site US-MN2 Morris: Corn-Soybean-Wheat with Cover Crops, Minimal Tillage. Site Description - Cropland, 3-year rotation (corn-soybean-wheat), cover crops (winter camelina and pennycress), minimum tillage, nutrient management by soil tests, uniform pest management, tile drainage

Helseth, Christina↗

AmeriFlux US-MN3 Morris: Corn-Soybean, Conventional Tillage

This is the AmeriFlux version of the carbon flux data for the site US-MN3 Morris: Corn-Soybean, Conventional Tillage. Site Description - Cropland, 2-year rotation (corn-soybean), conventional (deep rip) tillage, uniform nutrient management, uniform pest management, tile drainage

Helseth, Christina↗

AmeriFlux FLUXNET-1F US-MN1 Morris: Corn-Soybean with Cover Crops, Strip Tillage

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MN1 Morris: Corn-Soybean with Cover Crops, Strip Tillage. This is the FLUXNET version of the carbon flux data for the site US-MN1 Morris: Corn-Soybean with Cover Crops, Strip Tillage produced by applying the standard ONEFlux (1F) software. Site Description - Cropland, 2-year rotation (corn-soybean), strip tillage with winter cover crops (annual rye), nutrient management by soil tests, uniform pest management, tile drainage

Helseth, Christina [USDA-ARS LTAR]↗

AmeriFlux FLUXNET-1F US-MN2 Morris: Corn-Soybean-Wheat with Cover Crops, Minimal Tillage

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MN2 Morris: Corn-Soybean-Wheat with Cover Crops, Minimal Tillage. This is the FLUXNET version of the carbon flux data for the site US-MN2 Morris: Corn-Soybean-Wheat with Cover Crops, Minimal Tillage produced by applying the standard ONEFlux (1F) software. Site Description - Cropland, 3-year rotation (corn-soybean-wheat), cover crops (winter camelina and pennycress), minimum tillage, nutrient management by soil tests, uniform pest management, tile drainage

Helseth, Christina [USDA-ARS LTAR]↗

AmeriFlux FLUXNET-1F US-MN3 Morris: Corn-Soybean, Conventional Tillage

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MN3 Morris: Corn-Soybean, Conventional Tillage. This is the FLUXNET version of the carbon flux data for the site US-MN3 Morris: Corn-Soybean, Conventional Tillage produced by applying the standard ONEFlux (1F) software. Site Description - Cropland, 2-year rotation (corn-soybean), conventional (deep rip) tillage, uniform nutrient management, uniform pest management, tile drainage

Helseth, Christina [USDA-ARS LTAR]↗

AmeriFlux FLUXNET-1F US-xSP NEON Soaproot Saddle (SOAP)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xSP NEON Soaproot Saddle (SOAP). This is the FLUXNET version of the carbon flux data for the site US-xSP NEON Soaproot Saddle (SOAP) produced by applying the standard ONEFlux (1F) software. Site Description - The Soaproot Saddle is a complex terrain of coarse hills, steep slopes and narrow drainages. With an elevation of 3274 - 4537’ this site encompasses 1438 acres of mixed conifer forests that are experiencing high levels of mortality due to native Pine beetles. At the core of this site stands a 171’ tall flux tower that collects physical and chemical properties of atmosphere and related process. Soaproot Saddle also hosts an array of sensor measurements along with field observations collected by highly trained NEON staff. The automated instrument measurements and some of the terrestrial observational safor this field site are colocted with NEON's aquatic site, Upper Big Creek, which is located just north of Soaproot Saddle's site boundaries.

Network), NEON (National Ecological Observatory [N↗

Fluid – Fluid Interfacial Area and Its Impact on Relative Permeability - A Pore Network Modeling Study

Abstract Relative permeability (kr) is commonly modeled as an empirical function of phase saturation. Although current empirical models can provide a good match of one or two measured relative permeabilities using saturation alone, they are unable to predict relative permeabilities well when there is hysteresis or when physical properties such as wettability change. Further, current models often result in relative permeability discontinuities that can cause convergence and accuracy problems in simulation. To overcome these problems, recent research has modeled relative permeability as a state function of both saturation (S) and phase connectivity (X). Pore network modeling (PNM) data, however, shows small differences in relative permeability for the same S-X value when approached from a different flow direction. This paper examines the impact of one additional Minkowski parameter (Mecke and Arns, 2005), the fluid-fluid interfacial area, on relative permeability to identify if that satisfactorily explains this discrepancy. We calculate the total fluid-fluid interfacial areas (IA) during two-phase (oil/water) flow in porous media using pore network modeling. The area is calculated from PNM simulations using the areas associated with corners and throats in pore elements of different shapes. The pore network is modeled after a Bentheimer sandstone, using square, triangular, and circular pore shapes. Simulations were conducted for numerous primary drainage and imbibition cycles at a constant contact angle of 0° for the wetting phase. Simultaneous measurements of capillary pressure, relative permeability, saturation, and phase connectivity are made for each displacement. Fluid-fluid interfacial area is calculated from the PNM capillary pressure, the fluid location in the pore elements, and the pore element dimensional data. The results show that differences in the relative permeability at the same (S,X) point is explained well by differences in the fluid-fluid interfacial area (IA). That is, for a larger change in IA at these intersection points, the permeability difference is greater. That difference in relative permeability approaches zero as the difference in IA approaches zero. This confirms that relative permeability can be modeled better as a unique function of S, X, and IA. The results also show that an increase in IA restricts flow decreasing the nonwetting (oil) phase permeability. This decrease is caused by an increase in the throat area fraction compared to the corner area as the total area IA increases. The wetting phase relative permeability, however, shows the inverse trend, in that its relative permeability is greater when IA becomes larger owing to a greater fraction of the total area associated with the corners. The area IA, however, impacts the nonwetting phase relative permeability more than the wetting phase relative permeability. Corner flow improves the wetting phase relative permeability because the wetting phase is continuous there. Finally, a sensitivity analysis shows that relative permeability a is more sensitive to change in S than they are for IA for the case studied implying that if only two parameters are used to model relative permeability it is better to choose S and X.

Engineering↗

Analysis of the performance of different culvert boundary conditions in 2D shallow flow models

Culverts allow roads to safely traverse small streams or drainage ditches, and their proper design is critical to ensure a safe and reliable transportation network. A correct modelization of these hydraulic structures becomes crucial in the assessment of flood footprints or discharge peak estimation in a risk evaluation plan. The question of how to include culverts comes up frequently when assembling a hydraulic model that requires the presence of as many singular elements as possible. In this work, three different culvert integrations with the surface domain are studied and compared in the context of a 2D shallow water (SW) model. All of them are based on the Federal Highway Administration (FHWA) formulation for the culvert discharge estimation but differ in complexity and in the interaction with the numerical model for surface flow, some of them as internal boundary conditions. Several steady and unsteady validation test cases are presented and the numerical results are compared with the predictions from HEC-RAS 1D and HY-8 software. Furthermore, the culvert area, shape and their sensitivity to the 2D computational mesh is also analyzed.

54 ENVIRONMENTAL SCIENCES↗

Collaborative Research: Advancing Arctic Climate Projection Capability at Seasonal to Decadal Scales (Final Technical Report)

The Regional Arctic System Model (RASM) at process resolving configurations has been used to (i) advance understanding of physical processes and feedbacks involved in Arctic amplification and (ii) understand and potentially reduce uncertainty in prediction of arctic climate change at seasonal to decadal scales. RASM consists the atmosphere (Weather and Research Forecasting model, WRF), ocean (Parallel Ocean Program, POP), sea ice (CICE), land hydrology (Variable Infiltration Capacity model, VIC), river routing scheme (RVIC), marine biogeochemistry components and the coupling framework (CPL7). Its domain is pan-Arctic, with the atmosphere and land components configured on a 50-km or 25-km grid and four configurations of the ocean and sea ice components: 1/12°(~9.3km) or 1/48°(~2.4km) and 45 or 60 vertical layers. These RASM configurations have been motivated by the emerging exascale capability for high performance computing to improve model fidelity. The dynamical downscaling of reanalysis allows comparison of RASM results with observations in place and time to: (i) advance system level understanding of physical processes and coupling involved in an event, (ii) optimize model parameter space, (iii) diagnose and reduce model biases and (iv) produce realistic and consistent across all the components initial conditions for predictions and predictability studies, which are all unique capabilities not available in global Earth System Models (ESMs). An evaluation of RASM 1.0 (Cassano et al. 2017) revealed that it had a cold bias over the oceans and a warm bias over land areas due largely to cloud and radiation biases in the model, with too little cloud cover simulated over land and too much cloud cover simulated over sub-polar oceans. This study has motivated an upgrade to WRF version 3.7.1 in RASM and allowed for the inclusion of the radiative impact of convective clouds. A variety of atmospheric physics parameterizations were evaluated against observations (e.g. data from the Arctic Clouds in Summer Experiment (ACSE); Sedlar et al. 2020) to identify an optimal suite of WRF physics options in RASM. The RASM with the optimized WRF physics were used to study the impact of strong mesoscale winds over the ocean around the southern tip of Greenland (DuVivier and Cassano 2016) and their impact on oceanic convection (DuVivier et al. 2017a). Data from the PolarWinds field campaign were used to evaluate WRF boundary layer physics and resolution impacts on the simulation of a Greenland barrier wind event (DuVivier et al. 2017b). The RVIC streamflow routing model has been implemented in RASM to realistically represent high-resolution streamflow processes (Hamman et al. 2017) and to couple the land buoyancy fluxes to the ocean. The RASM-RVIC high-resolution data set of all coastal freshwater fluxes for the Arctic drainage basin and surrounding areas for 1979-2014 was published as a separate product (https://doi.org/10.5281/zenodo.293037). The fidelity of atmospheric momentum transfer to and the response of polar marine Ekman layer in RASM and Community Earth System Model (CESM) was investigated by Roberts et al. (2015). The increased frequency of oceanic flux exchange in CESM, following the RASM guidance, caused a considerable increase in the median inertial ice speed across the Southern Ocean and parts of the Arctic. A comprehensive evaluation of the RASM1.0 atmosphere-ocean-sea ice-land interface was completed by Brunke et al. (2018). RASM was also demonstrated for its capability to simulate extreme events in agreement with observations in space and time (Lee et al. submitted). In particular, the development of three open water events, known as polynyas, have been simulated north of Greenland in February of 2011, 2017 and 2018, in agreement with satellite observations for the past four decades. The optimized RASM sea ice results have been favorably evaluated against satellite observations and a subset of eleven CMIP6 models (Watts et al. submitted). In a complementary project, Jin et al. (2018) have shown that RASM with higher-resolution and new sea-ice processes contributed to lower model errors in sea-ice conditions, concentrations of nutrients and ice algae, in comparison to results from the coarse-resolution (1°) CESM. In two other complementary studies, RASM results were used (i) to explain areas of concentrated use by bowhead whales, the seasonal progression in the use, and the physical environment within those areas (Citta et al. 2015) and (ii) for a synthesis of fall bowhead whales distribution and migration in the Bering-Chukchi-Beaufort (BCB) Sea to investigate whale movements and feeding to the local ocean hydrography and currents (Citta et al. 2018). However, the multi-decadal output from the CESM Large Ensemble yielded unrealistic forcing. Instead, the shorter NCEP CFSv2 9-month forecasts were successfully tested and afforded an increased ensemble size (~30) to demonstrate gains of dynamical downscaling at sub-seasonal to intra-annual time scales. The improved model physics and coupling among RASM model components have yielded more realistic representation of the sea ice cover and consistent across all model components initial conditions. Consequently, RASM demonstrates significant gains compared to simulation of sea ice in the NCEP reanalysis. In addition, RASM 6-month ensemble forecasts yield very realistic sea ice distribution, which demonstrates both significant gains of dynamical downscaling and the continued impact of the initial conditions on forecasts out to 6 months (https://nps.edu/web/rasm/predictions). A follow up study using RASM for dynamical downscaling of the more realistic CESM initialized Decadal Prediction Large Ensemble output is currently ongoing as part of the DOE RGMA HiLAT-RASM project.

54 ENVIRONMENTAL SCIENCES↗

Computational Analysis of Water Film Thickness During Rain Events for Assessing Hydroplaning Risk Part 2: Rough Road Surfaces

Hydroplaning occurs when a water film forms on a road during a rain event and vehicles are traveling at a speed that does not provide sufficient time for the tires to push the water film out of the tire path. Under these conditions, the tire loses contact with the road and the driver may lose control over the vehicle. The present study is a part of a multiyear research effort aimed at gaining a better understanding of the factors that contribute to hydroplaning risk in order to minimize the occurrence of hydroplaning accidents. Three-dimensional computational fluid dynamics (CFD) analysis was used to investigate the water film thickness on multilane roads, one of the key parameters in evaluating hydroplaning risk. In the first part of the study, water films forming on wide roadways, i.e. multilane highways with 2, 4, and 6 lanes per side, were analyzed, with varying cross slope, longitudinal slope, and rainfall rate. Roadways with and without curbs and drainage were included in the analysis. The analysis in the first part was limited to nearly smooth asphalt or concrete surfaces because the maximum roughness height that can be specified in a CFD model using wall functions to determine shear stress at the road surface boundary is one half the thickness of computational cell layer adjacent to the boundary and the need to resolve the vertical velocity distribution in a thin water film requires cell layers that are a fraction of a millimeter thick. In this part of the study, the analysis was extended to consider the influence of pavement roughness over a range extending up 3.6 mm on the development of water film thickness. Various methods of modeling roughness were investigated and are presented: the roughness height model, a meshed-out geometry of the macrotexture of the pavement, and a porous region model. The computational results were analyzed and compared with experimental measurements performed by Gallaway et al.

42 ENGINEERING↗

Y-12 Groundwater Protection Program Monitoring Well Inspection and Maintenance Plan

This plan describes the systematic approach for: inspecting the physical condition of monitoring wells at Y-12, determining maintenance needs that extend the life of a well, and identifying those wells that no longer meet acceptable monitoring well design or well construction standards and require plugging and abandonment. The inspection and maintenance of groundwater monitoring wells is one of the primary management strategies of the Y-12 Groundwater Protection Program (GWPP) Management Plan, that is, the “proactive stewardship of the extensive monitoring well network at Y-12" (Consolidated Nuclear Security, L.L.C. [CNS], 2018). Effective stewardship, and a program of routine inspections of the physical condition of each monitoring well, ensures that representative water-quality samples and hydrologic data are obtained from the well network and protects the subsurface environment. In accordance with the Y-12 GWPP Monitoring Optimization Plan (MOP) for Groundwater Monitoring Wells at the Y-12 National Security Complex, Oak Ridge, Tennessee (CNS, 2017), the status designation (active or inactive) for each well determines the scope and extent of well inspections and maintenance activities. This plan, in conjunction with the above document, formalizes the GWPP approach to focus available resources on monitoring wells which provide the most useful data, and for that reason the GWPP inspects and performs maintenance on the wells sampled by the GWPP. This plan applies to groundwater monitoring wells installed at Y-12 and the related waste management facilities located within the three hydrogeologic regimes: (1) the Bear Creek Hydrogeologic Regime (Bear Creek Regime), (2) the Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime), and (3) the Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime). The Bear Creek Regime encompasses the section of Bear Creek Valley (BCV) immediately west of Y-12. The East Fork Regime encompasses most of the Y-12 process, operations, and support facilities in BCV west of Scarboro Road. The Chestnut Ridge Regime is directly south of Y-12 and encompasses a section of Chestnut Ridge that is bounded to the west by a surface drainage feature (Dunaway Branch, located immediately west of Industrial Landfill II) and by Scarboro Road to the east. The GWPP maintains an extensive database of geographic and construction details and related information for the monitoring wells in each hydrogeologic regime in the Updated Subsurface Database for Bear Creek Valley, Chestnut Ridge, and Parts of Bethel Valley on the U.S. DOE Oak Ridge Reservation (CNS, 2019). A detailed description of the hydrogeologic framework at Y-12 can be found in the GWPP Management Plan (CNS, 2018).

54 ENVIRONMENTAL SCIENCES↗

Evaluating the Long-Term Ecological Responses to Riparian Ecosystem Restoration at the Fort Benning, Georgia Military Installation

Riparian and instream restorations are commonly implemented to improve ecosystem condition. However, very few restoration activities are monitored for multiple years to assess long-term effectiveness. At the Department of Defense’s Fort Benning Military Installation (FBMI) in west-central Georgia, two experimental restoration projects (ephemeral drainage revitalization and instream habitat augmentation [i.e., coarse woody debris (CWD) additions]) were implemented ~14 years ago with the goal of reducing environmental impacts of military training activities. A SERDP project found that instream restoration improved some aspects of ecosystem function and community structure but not others. The objective of the current study was to re-evaluate the effect of these restoration practices on stream ecosystem processes ~14 years after implementation.

54 ENVIRONMENTAL SCIENCES↗

Source Physics Experiment: Rock Valley Interferometric Synthetic Aperture RADAR Earthquake Detection Study

Seismic signals from 1993 show a series of magnitude (Mw) 3.7 or less seismic events in Rock Valley on the Nevada National Security Site (NNSS). Historic synthetic aperture radar images of that location were found that could provide interferometric synthetic aperture radar (InSAR) measures of the ground height during 1993. Given this historic SAR imagery, we explore answering the question if ground movement from the 1993 Rock Valley earthquake activity could be sensed by remote sensing means. Finding earthquake surface movement would assist in locating the Rock Valley fault and the 1993 earthquake hypocenter where the Source Physics Experiment Phase III series of experiments will be conducted. In this report, we show that InSAR can sense very small height differences, and for the European Radar Satellite-1 InSAR collections during 1992 and 1993 over Rock Valley earth surface movements were measured with 8 mm uplift and 12.5 mm subsidence over isolated areas. One of these earth movement areas coincides with an InSAR image pair coherence drop between March 5, 1993 and June 18, 1993. The coherence drop is over an approximately 13 square km area south southeast of Skull Mountain centered at 36° 43' 30" N latitude and 116° 05' 00" W longitude. Measured small surface movement and a loss of InSAR coherence may be caused by the series of earthquakes. The location of these InSAR detections may also coincide with water drainage or erosion displacement. There are no records to disambiguate the earthquake and erosion earth surface motion possibilities. Therefore, the InSAR findings of earth surface movement by InSAR are inconclusive.

58 GEOSCIENCES↗

Predictive Data-driven Platform for Subsurface Energy Production

Subsurface energy activities such as unconventional resource recovery, enhanced geothermal energy systems, and geologic carbon storage require fast and reliable methods to account for complex, multiphysical processes in heterogeneous fractured and porous media. Although reservoir simulation is considered the industry standard for simulating these subsurface systems with injection and/or extraction operations, reservoir simulation requires spatio-temporal “Big Data” into the simulation model, which is typically a major challenge during model development and computational phase. In this work, we developed and applied various deep neural network-based approaches to (1) process multiscale image segmentation, (2) generate ensemble members of drainage networks, flow channels, and porous media using deep convolutional generative adversarial network, (3) construct multiple hybrid neural networks such as convolutional LSTM and convolutional neural network-LSTM to develop fast and accurate reduced order models for shale gas extraction, and (4) physics-informed neural network and deep Q-learning for flow and energy production. We hypothesized that physicsbased machine learning/deep learning can overcome the shortcomings of traditional machine learning methods where data-driven models have faltered beyond the data and physical conditions used for training and validation. We improved and developed novel approaches to demonstrate that physics-based ML can allow us to incorporate physical constraints (e.g., scientific domain knowledge) into ML framework. Outcomes of this project will be readily applicable for many energy and national security problems that are particularly defined by multiscale features and network systems.

58 GEOSCIENCES↗

The Influence of Microbial Priming Effects on the Hydro-bio-geochemistry of Large River Reservoirs

River-tributary confluences, where diverse organic matter (OM) sources mix, are considered aquatic critical zones for biogeochemical cycling. Here we evaluate dissolved OM composition and bioavailability in the mainstem of the Columbia River and three of its tributaries (Snake, Yakima, and Walla Walla rivers) along a hydrologic gradient in the Columbia River drainage basin using a variety of bulk and molecular level measurements. Field replicates and mixtures representing river-tributary confluences were incubated in the dark for 15 days to investigate the response of the microbial community to varying OM quantity/composition. The Columbia, Snake, and Yakima rivers did not differ in dissolved organic carbon (DOC), fluorescent dissolved OM (fDOM), or Chlorophyll-a (Chl-a) concentrations. However, the Walla Walla River had significantly greater DOC, fDOM, and Chl-a concentrations, indicative of greater contributions from algal DOM. FT-ICR-MS spectra for Walla Walla had significantly more peaks corresponding to amino sugars, carbohydrates and proteins while the Columbia River had more peaks for lignin, unsaturated hydrocarbons, and condensed aromatics. When incubated for 15 days in the dark, total DOC did not decrease for any of the river samples. DOC did decrease, however, in a mix representing the confluence of the Columbia and Walla Walla rivers, suggesting the microbial consortia of the Columbia River were primed by the Walla Walla River OM. OM composition was significantly different for several compound classes (e.g., lignin, protein, and tannin) following the incubations of unmixed river and tributary samples. However, the microbial community in the Walla Walla-Columbia mixture appeared to be indiscriminate of the molecular structure of the DOM as the compound class distribution did not change significantly. This provides preliminary evidence that the heterotrophs in river-tributary critical zones remineralize diverse OM structures.

54 ENVIRONMENTAL SCIENCES↗

Economic Extraction, Recovery and Upgrading of Rare Earth Elements from Coal-Based Resources (Final Report)

The overall objective of this project is to produce a rare earth elements product with greater than 8% rare earth elements from coal-based resources using an economically viable and environmentally benign processing methodology. The objective of the coal processing work will be to acquire appropriate coal feed and produce a viable clean coal product, a concentrated REE feed stream, and a pyrite stream (where available) that can be used to enhance leaching. The objective of the bio-oxidation portion of the project is to utilize bacteria to oxidize sulfide minerals and ferrous ions to ferric ions to accelerate leaching and remove the sulfides to prevent future acid mine drainage and related liabilities. The objective of the solution conditioning work is to remove iron and control leaching solution conditions to facilitate extraction of REEs without significant thorium extraction. The objective of the column leaching work is to engineer/model and simulate heap leaching to demonstrate low-cost extraction of REEs from coal-based resources. The objective of the solvent extraction work is to selectively extract and recover through controlled stripping of REEs that are solubilized through leaching. The objective of the precipitation portion of the project is to recover the REEs from the solvent extraction stripping solutions and dry them to achieve the final product of rare earth elements that is > 8 % REEs. The objective of the technical, economic, and environmental analysis is to determine the overall viability of the processing approach that is demonstrated in this project

01 COAL, LIGNITE, AND PEAT↗