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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Data and Code for 'GHG Mitigation and Land Use Change Implications of Sustainable Aviation Fuel in the United States'

BEPAM, Biofuel and Environmental Policy Analysis Model, models the agricultural sector and determines economically optimal land-use and feedstock mix at the US scale by maximizing the sum of agricultural sector consumers’ and producers’ surplus subject to various resource balances, land availability, and technological constraints under a range of biomass prices, from zero to $140 Mg-1 over the 2016-2030 period. Here BEPAM is used to model SAF production using energy crops and crop residues. BEPAM uses the GAMS format and uses yield and GHG balance projections from the biogeochemical model, DayCent.

09 BIOMASS FUELS↗
NASA NTRS2005

Development of an Optimal Water Allocation Decision Tool for the Major Crops During the Water Deficit Period in the Southeast U.S.

We developed a dynamic model to optimize irrigation application in three major crops (corn, cotton and peanuts) grown in the Southeast USA. Water supply amount is generated from an engineering model which is then combined with economic models to find the optimal amount of irrigation water to apply on each crop field during the six critical water deficit weeks in summer. Results indicate that water is applied on the crop with the highest marginal value product of irrigation. Decision making tool such as the one developed here would help farmers and policy makers to find the maximum profitable solution when water shortage is a serious concern.

Paudel, Krishna P.↗
NASA NTRS1982

Application of future remote sensing systems to irrigation

Area estimates of irrigated crops and knowledge of crop type are required for modeling water consumption to assist farmers, rangers, and agricultural consultants in scheduling irrigation for distributed management of crop yields. Information on canopy physiology and soil moisture status on a spatial basis is potentially available from remote sensors, so the questions to be addressed relate to: (1) timing (data frequency, instantaneous and integrated measurement); and scheduling (widely distributed spatial demands); (2) spatial resolution; (3) radiometric and geometric accuracy and geoencoding; and (4) information/data distribution. This latter should be overnight, with no central storage, onsite capture, and low cost.

Miller, L. D.↗
NASA NTRS2017

Representing Water Scarcity in Future Agricultural Assessments

Globally, irrigated agriculture is both essential for food production and the largest user of water. A major challenge for hydrologic and agricultural research communities is assessing the sustainability of irrigated croplands under climate variability and change. Simulations of irrigated croplands generally lack key interactions between water supply, water distribution, and agricultural water demand. In this article, we explore the critical interface between water resources and agriculture by motivating, developing, and illustrating the application of an integrated modeling framework to advance simulations of irrigated croplands. We motivate the framework by examining historical dynamics of irrigation water withdrawals in the United States and quantitatively reviewing previous modeling studies of irrigated croplands with a focus on representations of water supply, agricultural water demand, and impacts on crop yields when water demand exceeds water supply. We then describe the integrated modeling framework for simulating irrigated croplands, which links trends and scenarios with water supply, water allocation, and agricultural water demand. Finally, we provide examples of efforts that leverage the framework to improve simulations of irrigated croplands as well as identify opportunities for interventions that increase agricultural productivity, resiliency, and sustainability.

Irrigated Agriculture; Crop Model; Hydrologic Mode↗
NASA NTRS1990

Using Landsat to provide potato production estimates to Columbia Basin farmers and processors

A summary of project activities relative to the estimation of potato yields in the Columbia Basin is given. Oregon State University is using a two-pronged approach to yield estimation, one using simulation models and the other using purely empirical models. The simulation modeling approach has used satellite observations to determine key dates in the development of the crop for each field identified as potatoes. In particular, these include planting dates, emergence dates, and harvest dates. These critical dates are fed into simulation models of crop growth and development to derive yield forecasts. Two empirical modeling approaches are illustrated. One relates tuber yield to estimates of cumulative intercepted solar radiation; the other relates tuber yield to the integral under the GVI curve.

Source record↗
NASA NTRS2022

Improved representation of agricultural land use and crop management for large-scale hydrological impact simulation in Africa using SWAT+

To date, most regional and global hydrological models either ignore the representation of cropland or consider crop cultivation in a simplistic way or in abstract terms without any management practices. Yet, the water balance of cultivated areas is strongly influenced by applied management practices (e.g. planting, irrigation, fertilization, and harvesting). The SWAT+ (Soil and Water Assessment Tool) model represents agricultural land by default in a generic way, where the start of the cropping season is driven by accumulated heat units. However, this approach does not work for tropical and subtropical regions such as sub-Saharan Africa, where crop growth dynamics are mainly controlled by rainfall rather than temperature. In this study, we present an approach on how to incorporate crop phenology using decision tables and global datasets of rainfed and irrigated croplands with the associated cropping calendar and fertilizer applications in a regional SWAT+ model for northeastern Africa. We evaluate the influence of the crop phenology representation on simulations of leaf area index (LAI) and evapotranspiration (ET) using LAI remote sensing data from Copernicus Global Land Service (CGLS) and WaPOR (Water Productivity through Open access of Remotely sensed derived data) ET data, respectively. Results show that a representation of crop phenology using global datasets leads to improved temporal patterns of LAI and ET simulations, especially for regions with a single cropping cycle. However, for regions with multiple cropping seasons, global phenology datasets need to be complemented with local data or remote sensing data to capture additional cropping seasons. In addition, the improvement of the cropping season also helps to improve soil erosion estimates, as the timing of crop cover controls erosion rates in the model. With more realistic growing seasons, soil erosion is largely reduced for most agricultural hydrologic response units (HRUs), which can be considered as a move towards substantial improvements over previous estimates. We conclude that regional and global hydrological models can benefit from improved representations of crop phenology and the associated management practices. Future work regarding the incorporation of multiple cropping seasons in global phenology data is needed to better represent cropping cycles in areas where they occur using regional to global hydrological models.

crop phenology↗
NASA NTRS1996

Development of a Land Use Mapping and Monitoring Protocol for the High Plains Region: A Multitemporal Remote Sensing Application

The purpose of this project was to develop a practical protocol that employs multitemporal remotely sensed imagery, integrated with environmental parameters to model and monitor agricultural and natural resources in the High Plains Region of the United States. The value of this project would be extended throughout the region via workshops targeted at carefully selected audiences and designed to transfer remote sensing technology and the methods and applications developed. Implementation of such a protocol using remotely sensed satellite imagery is critical for addressing many issues of regional importance, including: (1) Prediction of rural land use/land cover (LULC) categories within a region; (2) Use of rural LULC maps for successive years to monitor change; (3) Crop types derived from LULC maps as important inputs to water consumption models; (4) Early prediction of crop yields; (5) Multi-date maps of crop types to monitor patterns related to crop change; (6) Knowledge of crop types to monitor condition and improve prediction of crop yield; (7) More precise models of crop types and conditions to improve agricultural economic forecasts; (8;) Prediction of biomass for estimating vegetation production, soil protection from erosion forces, nonpoint source pollution, wildlife habitat quality and other related factors; (9) Crop type and condition information to more accurately predict production of biogeochemicals such as CO2, CH4, and other greenhouse gases that are inputs to global climate models; (10) Provide information regarding limiting factors (i.e., economic constraints of pumping, fertilizing, etc.) used in conjunction with other factors, such as changes in climate for predicting changes in rural LULC; (11) Accurate prediction of rural LULC used to assess the effectiveness of government programs such as the U.S. Soil Conservation Service (SCS) Conservation Reserve Program; and (12) Prediction of water demand based on rural LULC that can be related to rates of draw-down of underground water supplies.

Price, Kevin P.↗
DOE OSTI2020

Simulated Biomass Sorghum GHG Reduction Potential is Similar to Maize

Policy support for cellulosic biofuels is contingent on their achieving much greater reductions in life-cycle greenhouse gas emissions than corn starch ethanol. Biomass sorghum has been suggested as a genetically and agronomically tractable feedstock species to augment near-term cellulosic feedstock production. This study used DayCent modeling to investigate biomass sorghum production emissions relative to corn with and without stover utilization at 3,265 across the rainfed United States. Sorghum produced greater average feedstock dry matter (15.6±1.4 vs. 14.8±2.2 Mg ha -1 yr -1 ) and slightly lower estimated ethanol energy yields (10.6±1.0 vs. 11.8±2.9 MJ m -2 yr -1 ) as corn grain with 75% stover collection. The high biomass removals in both the sorghum and corn stover scenarios led to soil organic carbon losses on 90% and 100% of sites, respectively. Average feedstock production emissions intensities were similar between sorghum and corn with 75% stover removal (17.6±2.8 vs. 18.8±3.0 g CO 2 e MJ -1 ), but were notably lower under sorghum for sites in the southwestern study region (13.6±3.0 vs. 22.5±3.1 g CO 2 e MJ -1 ). Futhermore, these results suggest that biomass sorghum produces cellulosic feedstock with similar emissions to corn grain and at current yield levels is unlikely to meet the Renewable Fuel Standard emissions reduction threshold for cellulosic biofuels.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Demonstration of Fluid Dynamics for Plant Growing Systems in Varied Gravity Environments Through Scaled Capillary Models

The development of reliable and bioregenerative crop growth production systems is vital for human exploration into deep space. As humans prepare for space travel beyond LEO, scientists need to find a way to provide reliable and adequate water delivery for all stages of the plant's life cycle. Past production systems struggled with this and often led to overwatering in the system. To better understand this issue, NASA's Plant Water Management (PWM) experiments were able to model fluid flow through granular substrates, specifically a clay-based material arcilite, in 0-G. The PWM study can help researchers to predict fluid flow through the systems, however their model only works for an arcilite based system and was unable to account for different stages of plant growth. For future missions, payload requirements to support crop production system will need to be limited, leading to the use of in situ resources. This project aims to validate the PWM experiments as well as incorporate various materials into the design for growth systems. To meet these objectives, a series of terrestrial experiments will be deployed to mimic all gravities. By modifying the material, fluid, and size of the test subjects, the effect of Earth's gravity can be minimized. This project will aid researchers in the design of future crop production systems for surface missions by creating a refined model that can be used at all stages of plant growth and utilize in situ resources.

Plant Biology↗
DOE OSTI2025

Fully‐Printed Ion Sensor Arrays for Measuring Agricultural Nitrogen and Potassium Concentrations Using Nernstian and AI Models

Abstract The chemical composition of growing media is a key factor for plant growth, impacting agricultural yield and sustainability. However, there is a lack of affordable chemical sensors for ubiquitous nutrient ion monitoring in agricultural applications. This work investigates using fully printed ion‐sensor arrays to measure the concentrations of nitrate, ammonium, and potassium in mixed‐electrolyte media. Ion sensor arrays composed of nitrate, ammonium, and potassium ion‐selective electrodes and a printed silver‐silver chloride (Ag/AgCl) reference electrode are fabricated and characterized in aqueous solutions in a range of concentrations that encompass what is typical for agricultural growing media (0.01 m m –1 m ). The sensors are also tested in mixed‐electrolyte solutions of NaNO 3 , NH 4 Cl, and KCl of varying concentrations, and the recorded potentials are input into Nernstian and artificial neural network models to compare the prediction accuracy of the models against ground truth. The artificial neural network models demonstrated higher accuracy over the Nernstian model, and the model using only ion‐sensor inputs is 7.5% more accurate than the Nernstian model under the same conditions. By enabling more precise and efficient fertilizer application, these sensor arrays coupled to computational models can help increase crop yields, optimize resource use, and reduce environmental impact.

Goodrich, Payton [University of California Berkele↗
DOE OSTI2024

Halophytes and heavy metals: A multi‐omics approach to understand the role of gene and genome duplication in the abiotic stress tolerance of Cakile maritima

Abstract Premise The origin of diversity is a fundamental biological question. Gene duplications are one mechanism that provides raw material for the emergence of novel traits, but evolutionary outcomes depend on which genes are retained and how they become functionalized. Yet, following different duplication types (polyploidy and tandem duplication), the events driving gene retention and functionalization remain poorly understood. Here we usedCakile maritima, a species that is tolerant to salt and heavy metals and shares an ancient whole‐genome triplication with closely related salt‐sensitive mustard crops (Brassica), as a model to explore the evolution of abiotic stress tolerance following polyploidy. Methods Using a combination of ionomics, free amino acid profiling, and comparative genomics, we characterize aspects of salt stress response inC. maritimaand identify retained duplicate genes that have likely enabled adaptation to salt and mild levels of cadmium. Results Cakile maritimais tolerant to both cadmium and salt treatments through uptake of cadmium in the roots. Proline constitutes greater than 30% of the free amino acid pool inC. maritimaand likely contributes to abiotic stress tolerance. We find duplicated gene families are enriched in metabolic and transport processes and identify key transport genes that may be involved inC. maritimaabiotic stress tolerance. Conclusions These findings identify pathways and genes that could be used to enhance plant resilience and provide a putative understanding of the roles of duplication types and retention on the evolution of abiotic stress response.

Plant Sciences↗
NASA NTRS1972

Data processing 1: Advancements in machine analysis of multispectral data

Multispectral data processing procedures are outlined beginning with the data display process used to accomplish data editing and proceeding through clustering, feature selection criterion for error probability estimation, and sample clustering and sample classification. The effective utilization of large quantities of remote sensing data by formulating a three stage sampling model for evaluation of crop acreage estimates represents an improvement in determining the cost benefit relationship associated with remote sensing technology.

Swain, P. H.↗
NASA NTRS1985

Microwave inversion of leaf area and inclination angle distributions from backscattered data

The backscattering coefficient from a slab of thin randomly oriented dielectric disks over a flat lossy ground is used to reconstruct the inclination angle and area distributions of the disks. The disks are employed to model a leafy agricultural crop, such as soybeans, in the L-band microwave region of the spectrum. The distorted Born approximation, along with a thin disk approximation, is used to obtain a relationship between the horizontal-like polarized backscattering coefficient and the joint probability density of disk inclination angle and disk radius. Assuming large skin depth reduces the relationship to a linear Fredholm integral equation of the first kind. Due to the ill-posed nature of this equation, a Phillips-Twomey regularization method with a second difference smoothing condition is used to find the inversion. Results are obtained in the presence of 1 and 10 percent noise for both leaf inclination angle and leaf radius densities.

Lang, R. H.↗
NASA NTRS1986

Influence of forebody cross-sectional shape on wing vortex burst location

A water tunnel study examining the influence of forebody cross section on the position of the wing vortex burst was carried out in the NASA Ames-Dryden water tunnel for a 55-deg cropped delta-wing model. Two of three cross sections investigated were chine-shaped, where the included angle of the chine was either 7.5-deg, representing a rather small side-edge angle, or 90 deg, representing a more moderate design. The third cross section was circular and served as a baseline for comparison. It is found that the 7.5 deg chine cross section generated the strongest forebody vortices of the three configurations and that these strong forebody vortices interacted with the main wing vortices in such a manner as to dramatically delay wing vortex burst position at zero sideslip. If the configuration is sideslipped, large asymmetries in wing vortex burst location may result.

Hall, R. M.↗
NASA NTRS2004

Economic Impact of Water Allocation on Agriculture in the Lower Chattahoochee River Basin

The relative value of irrigation water was assessed for three important crops (corn, cotton, and peanuts) grown in the southeastern United States. A decision tool was developed with the objective of allocating limited available water among competing crops in a manner that would maximize the economic returns to the producers. The methodology was developed and tested for a hypothetical farm located in Henry County, Alabama in the Chattahoochee river basin. Crop yield - soil moisture response functions were developed using Monte Carlo simulated data for cotton, corn, and peanuts. A hydrologic model was employed to simulate runoff over the period of observed rainfall the county to provide inflows to storage facilities that could be used as constraints for the optimal allocation of the available water in the face of the uncertainty of future rainfall and runoff. Irrigation decisions were made on a weekly basis during the critical water deficit period in the region. An economic optimization model was employed with the crop responses, and soil moisture functions to determine the optimum amount of water place on each crop subject to the amount of irrigation water availability and climatic uncertainty. The results indicated even small amounts of irrigation could significantly benefit farmers in the region if applied judiciously. A weekly irrigation sequence was developed that maintained the available water on the crops that exhibited the most significant combination of water sensitivity and cash value.

Limaye, Ashutosh S.↗
NASA NTRS2017

How Can CO2 Help Agriculture in the Face of Climate Change?

Humans are increasing the amount of carbon dioxide (CO2) in the air through CO2 emissions. This is changing the climate, making life harder for many plants in areas that suffer from heat and drought. However, plants need CO2 to grow, and more CO2 can make them grow better. So will plants overall benefit from increased CO2 level or suffer from it? We wanted to test if the positive effect would offset the negative ones. To do so, we used scientific models to calculate future crop production and water use of four important crops all over the world under different scenarios of CO2 emissions and climate change. Our calculations show that although there will be large reductions in crop yield due to climate change over the next century, some crops will still be able to grow well. This is also because crops can grow with less water when CO2 levels are raised.

Delphine, Deryng↗