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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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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Overview of Two Decision-Support Systems for Viticulture

Sustainable water management is one of the most challenging issues of our time, especially in the arid western U.S. Adequate water supplies are crucial to maintaining the health of communities, rivers, and wildlife, and nothing is more important to agriculture’s ability to produce food for the world’s growing population. Maximizing the benefits of our water supplies requires careful measurement of their availability and use. For irrigated agriculture, satellite-based estimates of evapotranspiration (ET) provide a measure of the water used to grow food — the biggest share of water consumption in most arid environments around the world. However, access to ET data has been limited and expensive, keeping it out of the hands of most water users and decision-makers. OpenET provides open, easily accessible satellite-based ET data for water management support. The OpenET collaborative includes leading national and international experts in remote sensing of ET, cloud computing, and water policy, partnered with nationally recognized web development teams and leaders in the western agriculture and water management communities. The system can be accessed at https://openetdata.org/.

Overview↗
NASA NTRS2024

Substrate Matters: Ionic Silver Alters Lettuce Growth, Nutrient Uptake, and Root Microbiome in a Hydroponics System

Ionic silver (Ag+) is being investigated as a residual biocide for use in NASA spacecraft potable water systems on future crewed missions. This water will be used to irrigate future spaceflight crop production systems. We have evaluated the impact of three concentrations (31 ppb, 125 ppb, and 500 ppb) of ionic silver biocide solutions on lettuce in an arcillite (calcinated clay particle substrate) and hydroponic (substrate-less) growth setup after 28 days. Lettuce plant growth was reduced in the hydroponic samples treated with 31 ppb silver and severely stunted for samples treated at 125 ppb and 500 ppb silver. No growth defects were observed in arcillite-grown lettuce. Silver was detectable in the hydroponic-grown lettuce leaves at each concentration but was not detected in the arcillite-grown lettuce leaves. Specifically, when 125 ppb silver water was applied to a hydroponics tray, Ag+ was detected at an average amount of 7 μg/g (dry weight) in lettuce leaves. The increase in Ag+ corresponded with a decrease in several essential elements in the lettuce tissue (Ca, K, P, S). In the arcillite growth setup, silver did not impact the plant root zone microbiome in terms of alpha diversity and relative abundance between treatments and control. However, with increasing silver concentration, the alpha diversity increased in lettuce root samples and in the water from the hydroponics tray samples. The genera in the hydroponic root and water samples were similar across the silver concentrations but displayed different relative abundances. This suggests that ionic silver was acting as a selective pressure for the microbes that colonize the hydroponic water. The surviving microbes likely utilized exudates from the stunted plant roots as a carbon source. Analysis of the root-associated microbiomes in response to silver showed enrichment of metagenomic pathways associated with alternate carbon source utilization, fatty-acid synthesis, and the ppGpp (guanosine 3′-diphosphate 5′-diphosphate) stringent response global regulatory system that operates under conditions of environmental stress. Nutrient solutions containing Ag+ in concentrations greater than 31 ppb in hydroponic systems lacking cation-exchange capacity can severely impact crop production due to stunting of plant growth.

lettuce↗
NASA NTRS2024

Terrestrial Water Storage in 2023

Global terrestrial water storage (TWS) anomalies reached a record low of –9.94 cm in 2023, decreasing 0.80 cm from 2022. These reductions largely reflect ongoing TWS losses from glacial melt and groundwater use for irrigation, offset by gains in central and eastern Antarctica and La Niña-related tropical wetting.

Bailing Li↗
NASA NTRSDate not supplied

The Global Water Monitor: Lake, Wetland, and River Reach Monitoring for Resource Management and Hazard Observation

The Global Water Monitor is a monitoring program offering surface water-related products for lakes, reservoirs, river reaches, and wetlands, https://blueice.gsfc.nasa.gov/gwm. These products are derived from multiple satellite-based altimetry and multispectral imaging platforms. The primary measurements are water level, slope, and extent, derived from a series of NASA and other agency instruments (Sentinel-3,-6, ICESat-2, SWOT, MODIS). The system serves stakeholders, the US Department of Agriculture Foreign Agricultural Service and the US Geological Survey, as well as various international, national, state, and intelligence agencies, engineers, ecologists, and hydrological researchers. Considering the sensitivity of ground-based data and the remote accessibility of many basins, the satellites offer global coverage, accuracy, and continuity of measurements. Observation of storage fluctuations in lakes and reservoirs provides users with knowledge of short and long-term drought conditions that can affect both water and energy resources. Emphasis is on changing climatic conditions, water sharing between nations, and regional stability. Measurements across a wetland complex can assist with efforts to assess hydrological dynamics with a focus on conservation efforts that aid both natural ecology and the sharing of precious water resources – the latter potentially being required in a basin across the municipal, crop irrigation, aquaculture, livestock, and power station spectrum. Observations of river reaches assists in the collection of basic hydraulic information, particularly in gauge-poor regions, for modelling efforts and the estimation of discharge, and at high-latitudes satellite-based river observations serve projects that warn of spring melts and flood hazards. We look at how recent improvements in instrument technology and mission operations are assisting with acquiring true global coverage and cross-validation efforts, and how stakeholders interact with the project in terms of setting requirements, product format, and accessibility methods. Examples show the application of the products across a range of programs, and in addition to meeting operational requirements, how the multi-decadal surface water levels are creating a high-quality timeline of Earth Data Records.

Lakes↗
DOE OSTI2020

Methods and apparatus for gnotobiotic plant growth

The disclosure relates to a plant growth apparatus and related system to grow and maintain plants under controlled biotic conditions, for example to grow axenic (microbe-free) plants, gnotobiotic (defined microbiota) plants, and holoxenic (complex, or undefined microbiota) plants. This system allows aseptic bottom irrigation with water, soluble nutrients, chemicals, and/or microbiota. Plants can be inverted for dipping and/or vacuum infiltration. The system also allows for passive (gravity) drainage, thereby allowing for gas exchange and preventing root anoxia. A variety of plant growth substrates can be used within the plant growth apparatus as a plant growth medium. The plant growth apparatus, containing the growth substrate medium, can be completely flushed via the drainage port to remove potential toxic byproducts of the sterilization processes. The entire system is suitably constructed using autoclavable material.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Proposed Potential Mitigation of Wastewater Disposal Through Treated Produced Water in Bakken Formation

The recent global expansion in the development of unconventional oil and gas assets has also resulted in a tremendous increase in the number of extended horizontal drilling and hydraulic fracturing projects in the Bakken. The United States is presently the largest global crude oil producer, and the Bakken Formation in North Dakota is one of the major contributors to this achievement. However, the wastewater produced from these increased oilfield activities are highly saline (∼170,000 to 350,000 ppm TDS) and no technology currently available can satisfactorily treat it. As a result, more than 90% of wastewater in the Bakken is disposed of by deep injection into disposal wells. However, there are growing environmental and operational concerns about the sustainability and impacts of this approach. Research has shown that cumulative wastewater injection in some areas could increase the chances of earthquakes in those areas. However, if this produced water is efficiently treated, it could be reused in hydraulic fracturing operations or to support coal mining and irrigation activities. All these applications would reduce the need for wastewater injection and reduce the demand for fresh water used in hydraulic fracturing operations across North Dakota. For this purpose, we propose an enhanced supercritical technology we call Supercritical Water Extraction – Enhance Targeted Recovery to handle the issue of high TDS of flowback and produced water in the Bakken.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2022

Semi-automated Design of Artificial Intelligence Earth Science Models

Prediction and observation of water cycles involve not only patterns isolated in space and time, but rather modeling complex spatio-temporal relationships across multiple sources of data and domains. For instance, Evapotranspiration (ET) and Leaf Area Indexes (LAI) are two critical components in DOE’s Energy Exascale Earth System Model (E3SM). Accurate assessments of ET and LAI are critical for understanding hydrological processes, deforestation, crop yield, and irrigation impacts. However, current ET estimates for global simulations are available at very coarse spatial resolution. They are usually derived from satellite data based on broad plant functional types (PFT), which fail to capture the fine-scale variations due to change in vegetation type across the globe. Within this context and in light of the data-model integration challenges highlighted in the EESSD Strategic Plan, the new era of AI model development for geosciences calls for data-driven methods that provide domain scientists with estimations of parameters such as PFT and LAI in an efficient, interpretable, and easy-to-operate manner.

Ambrozio Dias, Philipe↗
DOE OSTI2022

Multi-Level Impacts of Extreme Climate-Related Events on Food Supply Chain: Idaho Potato's Case Study

Background: The world is experiencing frequent extreme weather events like droughts, floods, snowstorms, and shifting of seasons due to climate change. Increasing frequencies and severity of these extreme weather events threaten food security because agriculture is extremely vulnerable to climate change. Higher temperature reduces overall yields of the desirable crops but proliferates weeds and harmful pests. Current data shows that every year U.S. farmers spend more than 11 billion USD to fight weeds and this number is expected to rise in the coming years due to climate change. Due to droughts, the water required for irrigation is becoming scarcer. Since many areas are becoming climatically unusable for crop production, the amount of farmland area is shrinking rapidly. In addition, changes in precipitation patterns are causing crop failures and negatively impacting expected yields. In this study, we investigated how different extreme climate events impact different stages of a food supply chain. Approach: As a case study, we chose Idaho’s potato supply chain (SC). Idaho is the top potato producing state in the U.S. and contributes around 30% of the nation’s potato production. Using the agent-based modeling (ABM) approach, we developed a multi-echelon potato supply chain computer simulation model with six types of agents – seed producers, farmers, shippers, processors, retailers, and logistics companies. In addition to the baseline scenario, we developed two additional climate-related disruption events – drought and snowstorm. We investigated how each of these disruption events impacts different stakeholders across the supply chain in terms of revenue and some other key performance metrics such as lead time, food waste, number of delayed orders, and order fulfillment rate. Results: Extreme climate events not only impact the growers but there is also cascading ripple effects downstream of the supply chain. The methodology developed in this study could be applied to other food and agricultural SC to understand the vulnerabilities of the different links. The findings would potentially help to adopt new policies for the well-being of the overall SC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

2022 Prototype Manufacture and Installation Awardee: Sonsight Wind

The Sonsight Wind 3.5-kilowatt (kW) prototype turbine is designed to compete with solar power, meeting energy needs for a wide range of smaller-scale applications, such as powering individual homes and irrigation systems on farms and ranches in remote areas. The technology's innovative high-torque, low-rotations-per-minute generator permits the use of longer blades that, at moderate wind speed sites, generate the energy of a 5-kW turbine with lower thrust forces than similarly rated turbines. The 3.5-kW turbine is projected to ofer greater durability at a signifcantly lower levelized cost of energy. Sonsight Wind advanced the development of the prototype with a previous Competitiveness Improvement Project (CIP) funding award.

competitiveness improvement project↗
DOE OSTI2026

Pixel-Registered Multimodal Synchrotron XRF and FTIR Microscopies Reveal Salinity Stress Response Mechanisms in Pistachio

Background: Salinity is a major abiotic stress that negatively affects nearly all plant species at all stages of growth. Drought and poor-quality irrigation cause high soil salinity and salt accumulation via evaporation, reducing crop productivity. Despite its critical importance, the spatial localization of salt ions and associated biochemical changes within plants experiencing high salinity remains largely unknown. In this study, we developed a multimodal imaging pipeline to understand the impact of salinity on the pistachio rootstock UCB-1 (Pistacia atlantica x Pistacia integerrima). We directly link biochemical fingerprints in stem tissue architecture with salt ion localization to provide insights into the strategies pistachio uses to tolerate salinity. Results: We observed that Pistacia spp. exposed to high salt conditions accumulated Ca, Si, Cl, Al and Mg as hotspots within the pith, compared to the control (of which only Ca and Al co-locate). In contrast, there was a decrease in K between the control and salinity treatment. Hotspots of amide I and II were present in the cortex and pith of the salinity treated sample. Additionally, the salinity treatment resulted in an increased abundance of pectin and carbohydrates within the pith compared to the control, and the abundance of esters/carboxylic acid was greater in the salinity treatment. Conclusions: We determined that Cl and K, S and P, and biochemical components polysaccharide and pectin, esters and carboxylic acid, amide I and cellulose are the strongest drivers of salinity- treatment induced variability. In the cortex and phloem/xylem, a negative K-Ca correlation decreases in the salinity treatment. Several hotspots of elements and amide I (proteins) appear under salinity treatment, particularly in the cortex, suggesting an increase in the production of stress-related proteins (in response to high Cl) and/or structural proteins (i.e. Ca). Together, these results indicate that pistachio responds to salinity through ion compartmentalization coupled with a targeted biochemical adjustment, rather than a broadscale tissue-wide response. Overall, these novel, spatially resolved pixel-registered multimodal imaging data provide an enabling platform to understand the mechanisms of salinity tolerance in Pistacia spp and can be broadly applied to studying stress-related phenotype response in various plant tissues.

FTIR spectromicroscopy↗
DOE OSTI2023

Contesting with the Ganges Water Machine in South Asia: Theory versus Reality

Recently, there has been much interest in how to manage the water resources of the Ganges River Basin (GRB), the cradle of Asian civilization, currently supporting >500 million people. This also includes cleaning up the Ganges river, regarded as one of the most polluted mega-rivers of the world. Historically, the transboundary Ganges river and its tributaries, flowing through India, Nepal, and Bangladesh, have become extensively polluted and disrupted, mostly because of river engineering and increased discharge of industrial and urban waste. Compounding the problem, in the past few decades, intense groundwater abstraction from the GRB aquifers has led to unprecedented groundwater level depletion in some locations. At present, the GRB groundwater levels are strongly influenced by depth-dependent abstraction, which is predicted to intensify in the future, given the increasing water demand. Therefore, with impending climate change, designing the coupled river water–groundwater management necessary to meet the goal for sustainable access to clean water for a huge population, has become an arduous challenge.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Temporal Variability in Reservoir Surface Area Is an Important Source of Uncertainty in GHG Emission Estimates

Ebullitive methane (CH 4 ) emissions in lentic ecosystems tend to concentrate at river-lake interfaces and within shallow littoral zones. However, inconsistent definitions of the littoral zone and static representations of the lake or reservoir surface area contribute to major uncertainties in greenhouse gas (GHG) emissions estimates, particularly in reservoirs with large water-level fluctuations. This study examines temporal variation in littoral and total surface areas of US reservoirs and demonstrates how different methods and data sources lead to discrepencies in reservoir GHG emissions at large scales and over time. We also explore variability in remotely sensed water occurrence according to maximum surface area, reservoir purposes, and hydrologic regions. Notably, the largest relative variability in surface area is exhibited by small reservoirs with a maximum surface area <1 km 2 and non-hydroelectric reservoirs. Additionally, we use a case study of measured CH 4 emissions from the southeastern United States (Douglas Reservoir) to illustrate the effects of varying surface area on reservoir-wide GHG estimates. Upscaled CH 4 emissions in Douglas Reservoir differed by nearly two-fold depending on the source of total surface area data and whether estimates accounted for seasonal fluctuations in surface area. During seasonal drawdown in Douglas Reservoir, relative littoral area varies non-linearly; periods of lower pool elevation (and thus larger relative littoral area) likely contribute disproportionately high CH 4 emission rates compared to the commonly sampled summer season when water levels are at full-pool elevation. Improved GHG monitoring and upscaling techniques require accounting for temporal variability in reservoir surface extent and littoral area.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Phyllosphere exudates select for distinct microbiome members in sorghum epicuticular wax and aerial root mucilage

Phyllosphere exudates create specialized microhabitats that shape microbial community diversity. We explored the microbiome associated with two sorghum phyllosphere exudates, the epicuticular wax and aerial root mucilage. We assessed the microbiome associated with the wax from sorghum plants over two growth stages, and the root mucilage additionally from nitrogen-fertilized and non-fertilized plants. In parallel, we isolated and characterized hundreds of bacteria from wax and mucilage, and integrated data from cultivation-independent and cultivation-dependent approaches to gain insights into exudate diversity and bacterial phenotypes. We found that Sphingomonadaceae and Rhizobiaceae families were the major taxa in the wax regardless of water availability and plant developmental stage to plants. The cultivation-independent mucilage-associated bacterial microbiome contained Erwiniaceae, Flavobacteriaceae, Rhizobiaceae, Pseudomonadaceae, Sphingomonadaceae, and its structure was strongly influenced by sorghum development but only modestly influenced by fertilization. In contrast, the fungal community structure of mucilage was strongly affected by the year of sampling but not by fertilization or plant developmental stage, suggesting a decoupling of fungal-bacterial dynamics in the mucilage. Our bacterial isolate collection from wax and mucilage had several isolates that matched 100% to detected amplicon sequence variants, and were enriched on media that selected for phenotypes including phosphate solubilization, putative diazotrophy, resistance to desiccation, capability to grow on methanol as a carbon source, and ability to grow in the presence of linalool and β-caryophyllene (terpenes in sorghum wax). This work expands our understanding of the microbiome of phyllosphere exudates and supports our long-term goal to translate microbiome research to support sorghum cultivation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The domestic and international implications of future climate for U.S. agriculture in GCAM

Agriculture yields are susceptible to changes in future temperature, precipitation, and other Earth system factors. Future changes to these physical Earth system attributes and their effects on agricultural yields are highly uncertain. United States agricultural producers will be affected by such changes whether they occur domestically or internationally (via international commodity markets). How important to U.S. agriculture are domestic changes due to climate compared to those occurring externally? Here we show that potential direct impacts to United States agriculture have financial impacts on U.S. producers that are roughly similar in magnitude but opposite in sign to impacts on U.S. producers due to changes in other parts of the world. This finding is robust across application of a wide range of potential future crop yield impacts applied to a multi-sector global integrated assessment model. Therefore, when examining country-specific impacts, it is necessary to model both the domestic and international impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

AgroIBIS VSF Farmed Pothole Ponding Model Runs

This data set includes modeled (AgroIBIS-VSF) output of crop yield for miscanthus and a corn/soybean rotation in .nc format. Input includes the precipitation scenarios (.csv) used to generate the runs, and supplemental observed yield monitor data (.csv) from the research area of interest.

Agricultural Hydrology (Drainage, Flooding, Irriga↗
DOE OSTI2021

Comparison of Deterministic and Statistical Models for Water Quality Compliance Forecasting in the San Joaquin River Basin, California

Model selection for water quality forecasting depends on many factors including analyst expertise and cost, stakeholder involvement and expected performance. Water quality forecasting in arid river basins is especially challenging given the importance of protecting beneficial uses in these environments and the livelihood of agricultural communities. In the agriculture-dominated San Joaquin River Basin of California, real-time salinity management (RTSM) is a state-sanctioned program that helps to maximize allowable salt export while protecting existing basin beneficial uses of water supply. The RTSM strategy supplants the federal total maximum daily load (TMDL) approach that could impose fines associated with exceedances of monthly and annual salt load allocations of up to $1 million per year based on average year hydrology and salt load export limits. The essential components of the current program include the establishment of telemetered sensor networks, a web-based information system for sharing data, a basin-scale salt load assimilative capacity forecasting model and institutional entities tasked with performing weekly forecasts of river salt assimilative capacity and scheduling west-side drainage export of salt loads. Web-based information portals have been developed to share model input data and salt assimilative capacity forecasts together with increasing stakeholder awareness and involvement in water quality resource management activities in the river basin. Two modeling approaches have been developed simultaneously. The first relies on a statistical analysis of the relationship between flow and salt concentration at three compliance monitoring sites and the use of these regression relationships for forecasting. The second salt load forecasting approach is a customized application of the Watershed Analysis Risk Management Framework (WARMF), a watershed water quality simulation model that has been configured to estimate daily river salt assimilative capacity and to provide decision support for real-time salinity management at the watershed level. Analysis of the results from both model-based forecasting approaches over a period of five years shows that the regression-based forecasting model, run daily Monday to Friday each week, provided marginally better performance. However, the regression-based forecasting model assumes the same general relationship between flow and salinity which breaks down during extreme weather events such as droughts when water allocation cutbacks among stakeholders are not evenly distributed across the basin. A recent test case shows the utility of both models in dealing with an exceedance event at one compliance monitoring site recently introduced in 2020.

54 ENVIRONMENTAL SCIENCES↗