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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Land Surface Modeling 2.0 for agricultural climate change impact assessments

Focus Area: This white paper addresses DOE AI4ESP focus area #2 by providing a sketch blueprint for a next generation, hybrid AI/process-based global Land Surface Modeling (LSM) framework to improve projections of climate change impacts on the land surface system including agriculture and the hydrological cycle. Science Challenge: Climate change impacts on agriculture are highly uncertain: -50% to +150% global production changes for major grains under high-end climate change, for example. The core challenge in land surface system predictability is the large gap between the scale at which the relevant biological processes act and the scale at which the risks need to be assessed. Conventional empirical and process-based modeling approaches are insufficient. A new multi-scale modeling paradigm which employs AI/ML to learn from new streams of remote sensing data and targeted ’gene-to-global’ simulations is needed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Distributed Wind Guidebook: Agricultural Producers and Rural Small Business Owners

Distributed wind energy technologies generate clean, carbon-free power close to the point of consumption (i.e., close to people and their energy needs). Distributed wind energy can help individuals, farms, businesses, and communities meet their unique goals, such as reducing impacts on climate change, decreasing electricity bills, boosting energy independence or autonomy from the electric grid, and enhancing grid reliability and resilience. This guidebook is designed to support you in (1) deciding if distributed wind energy is right for you, (2) installing a proven wind turbine technology by working with a reputable installer, and (3) setting up your project for success through its lifetime. The information in this guidebook is tailored to rural small businesses and agricultural producers who are interested in exploring distributed wind energy to meet their electricity, resilience, financial, and environmental goals. You will find gray boxes with key topics, definitions, and considerations throughout the guidebook. The report has been adapted from the Distributed Wind Guidebook, which offers a comprehensive view on core aspects of deploying distributed wind energy technologies. In comparison, this edition of the guidebook is designed to offer a more succinct and tailored guidebook for rural small businesses and agricultural producers. For additional detail on any topic presented within this edition, readers are advised to reference the original version of the Distributed Wind Guidebook.

17 WIND ENERGY↗
DOE OSTI2026

Regulatory and Technical Challenges and Barriers to Adoption of Distributed Wind Energy in Agricultural Settings

Distributed wind (DW) energy development can benefit agricultural landowners through the possibility of improved resilience of electrical service from onsite generation and associated economic benefits. DW development currently faces technical and regulatory challenges related to interconnection of projects with distribution or transmission equipment on the main electrical grid. A review was conducted of barriers to adoption for agricultural DW projects and potential roles of various stakeholders in addressing them. One major barrier is that the unique characteristics of wind energy generation such as its variability and intermittency, may require upgrades for the whole power line, which can lead to prohibitive cost burdens on individual interconnection customers. Another barrier is compliance with federal, state, or utility-level regulations that require technology-agnostic, industry-standard equipment that is often not technically realistic for DW projects. DW developers, grid infrastructure owner-operators, regulators, and standards publishers can work together to address these challenges and facilitate DW development.

17 WIND ENERGY↗
DOE OSTI2023

Bioenergy’s Role in Soil Carbon Storage Decarbonizing Transportation, Agriculture, and Industrial Sectors Workshop Summary Report

On March 28–29, 2022, the U.S. Department of Energy’s (DOE) Bioenergy Technologies Office (BETO) hosted the public virtual workshop “Bioenergy’s Role in Soil Carbon Storage.” Given the recent emphasis of the Biden administration on decarbonizing transportation, agriculture, and industrial sectors of the U.S. economy, this workshop examined how decarbonization through enhanced soil carbon storage while growing bioenergy crops is possible by discussing challenges and opportunities that affect soil carbon levels. Stakeholders representing academia, industry, the farming community, agricultural and forestry sectors, municipalities, and federal agencies involved in soil carbon storage participated in this workshop. A series of keynote presentations, plenary presentations, and stakeholder input sessions provided opportunities for sharing knowledge and identifying research and development (R&D) needs for future advances in soil carbon storage in relation to bioenergy crops. This document provides an overview of the content discussed in the presentations, as well as a summary of the stakeholder input received during the session discussions.

09 BIOMASS FUELS↗
DOE OSTI2022

A Wireless Underground Sensor Network Field Pilot for Agriculture and Ecology: Soil Moisture Mapping Using Signal Attenuation

Wireless Underground Sensor Networks (WUSNs) that collect geospatial in situ sensor data are a backbone of internet-of-things (IoT) applications for agriculture and terrestrial ecology. In this paper, we first show how WUSNs can operate reliably under field conditions year-round and at the same time be used for determining and mapping soil conditions from the buried sensor nodes. We demonstrate the design and deployment of a 23-node WUSN installed at an agricultural field site that covers an area with a 530 m radius. The WUSN has continuously operated since September 2019, enabling real-time monitoring of soil volumetric water content (VWC), soil temperature (ST), and soil electrical conductivity. Secondly, we present data collected over a nine-month period across three seasons. We evaluate the performance of a deep learning algorithm in predicting soil VWC using various combinations of the received signal strength (RSSI) from each buried wireless node, above-ground pathloss, the distance between wireless node and receive antenna (D), ST, air temperature (AT), relative humidity (RH), and precipitation as input parameters to the model. The AT, RH, and precipitation were obtained from a nearby weather station. We find that a model with RSSI, D, AT, ST, and RH as inputs was able to predict soil VWC with an R 2 of 0.82 for test datasets, with a Root Mean Square Error of ±0.012 (m 3 /m 3 ). Hence, a combination of deep learning and other easily available soil and climatic parameters can be a viable candidate for replacing expensive soil VWC sensors in WUSNs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Developing a Decision Support System for Regional Agricultural Nonpoint Salinity Pollution Management: Application to the San Joaquin River, California

Environmental problems and production losses associated with irrigated agriculture, such as salinity, degradation of receiving waters, such as rivers, and deep percolation of saline water to aquifers, highlight water-quality concerns that require a paradigm shift in resource-management policy. New tools are needed to assist environmental managers in developing sustainable solutions to these problems, given the nonpoint source nature of salt loads to surface water and groundwater from irrigated agriculture. Equity issues arise in distributing responsibility and costs to the generators of this source of pollution. This paper describes an alternative approach to salt regulation and control using the concept of “Real-Time Water Quality management”. The approach relies on a continually updateable WARMF (Watershed Analysis Risk Management Framework) forecasting model to provide daily estimates of salt load assimilative capacity in the San Joaquin River and assessments of compliance with salinity concentration objectives at key monitoring sites on the river. The results of the study showed that the policy combination of well-crafted river salinity objectives by the regulator and the application of an easy-to use and maintain decision support tool by stakeholders have succeeded in minimizing water quality (salinity) exceedances over a 20-year study period.

real-time management economics↗
DOE OSTI2026

N 2 Onet: a global collaborative network facilitating advances in measurement, modeling, and mitigation of agricultural soil nitrous oxide emissions

Nitrogen (N) fertilizer supports global food production, but its use and overuse drive emissions of nitrous oxide (N 2 O), a potent and long-lived greenhouse gas. Understanding the drivers of N 2 O fluxes remains elusive, making it difficult to predict emissions in time and space and to develop and evaluate ways to lower emissions through management. Major scientific uncertainties underlying the understanding of the drivers of N 2 O fluxes identified in a workshop of N 2 O emissions experts include poor process-based understanding of controls on soil N 2 O emissions in the field; insufficient data to reduce uncertainty in N 2 O budgets from the field to regional scales, including N 2 O emission measurements and importantly, field-scale N balances; and high uncertainty in model predictions of soil N 2 O emissions across environmental and management conditions. To reduce these uncertainties, we present the concept of N 2 Onet, a global collaborative initiative to accelerate advances in N 2 O measurement, analyses, and mitigation. N 2 Onet will serve as an observational network of supersites with multi-scale measurements; a database hub for N 2 O flux and ancillary data; and a catalyst for community building, information sharing, and training. By coalescing and coordinating the global community of researchers, N 2 Onet will provide a roadmap for reducing N 2 O emissions from agriculture worldwide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Technology pathways for energy- and water-efficient controlled environment agriculture: A review of technologies, implementation pathways, and regional use cases

Controlled Environment Agriculture (CEA) offers high-yield, climate-resilient food production, but high energy and resource demands challenge its sustainability. This paper synthesizes technologies that can improve outcomes across six categories—energy, CO 2 utilization, building envelope, hardware, water, and process—plus colocation strategies. We evaluate 80 technologies and define ten implementation pathways bundling complementary technologies to reduce energy use, optimize water consumption, and minimize emissions. Regional application is demonstrated through five U.S. case studies spanning different climates. A logic framework guides pathway selection for case studies based on climate, infrastructure, and regulatory context, informing context-sensitive technology deployment. Results show energy intensity reductions of 3–55 %, ranging from energy management programs to comprehensive lighting retrofits; water savings of 20–40 % through closed-loop recirculation; and emissions reductions of 3–100 %, with strategic energy management achieving 3–5 % and renewable electricity paired with electrified heating achieving up to 100 %. Text mining revealed that energy, hardware, and process technologies account for 91 % of literature coverage. Water, building envelope, and CO 2 utilization remain underexplored, indicating priorities for future research. This integrative approach to technology assessment supports growers, developers, and policymakers in aligning CEA system design with local conditions, improving resource efficiency and addressing gaps in cross-domain technology coverage.

Controlled environment agriculture↗
DOE OSTI2024

Soil Sensors in Agriculture: From Unsustainable to Biodegradable

Commercially available bi-metallic temperature sensors have long exploited differential thermal expansions between materials to produce an actuation-induced readout from a bi-metal helix. When dispersed in agricultural land, electronic components are used to transmit information at the cost of an increased environmental footprint. This paper briefly recaps the proposed sensor, which employs a biodegradable bi-material helix composed of a polymer and metal. Proposed polymer sheetings of cellulose acetate and polylactic acid are characterized via TGA, DMA, and DSC to evaluate plasticizer content, shrinkage, and an appropriate sensor work-use range. Finally, the deflection of non-biodegradable bi-polymer strips is quantified for various combinations to determine if bi-polymer deflection is possible.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Minimizing Electric Lighting Use With LASSI Lighting Controls in Controlled Environment Agriculture

The majority of energy use in controlled environment agriculture is typically from electric lighting. Certain lighting controls can help minimize the energy required in these operations. This analysis simulates a greenhouse with different types of lighting controls in different U.S. climates to explore the effects of the lighting controls on energy use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

High precision control and deep learning-based corn stand counting algorithms for agricultural robot

This paper presents high precision control and deep learning-based corn stand counting algorithms for a low-cost, ultra-compact 3D printed and autonomous field robot for agricultural operations. Currently, plant traits, such as emergence rate, biomass, vigor, and stand counting, are measured manually. This is highly labor-intensive and prone to errors. The robot, termed TerraSentia, is designed to automate the measurement of plant traits for efficient phenotyping as an alternative to manual measurements. In this paper, we formulate a Nonlinear Moving Horizon Estimator that identifies key terrain parameters using onboard robot sensors and a learning-based Nonlinear Model Predictive Control that ensures high precision path tracking in the presence of unknown wheel-terrain interaction. Moreover, we develop a machine vision algorithm designed to enable an ultra-compact ground robot to count corn stands by driving through the fields autonomously. The algorithm leverages a deep network to detect corn plants in images, and a visual tracking model to re-identify detected objects at different time steps. We collected data from 53 corn plots in various fields for corn plants around 14 days after emergence (stage V3 - V4). The robot predictions have agreed well with the ground truth with C robot =1.02×C human -0.86 and a correlation coefficient R=0.96. The mean relative error given by the algorithm is -3.78%, and the standard deviation is 6.76%. These results indicate a first and significant step towards autonomous robot-based real-time phenotyping using low-cost, ultra-compact ground robots for corn and potentially other crops.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Using stable isotopes to inform water resource management in forested and agricultural ecosystems

Present and future climatic trends are expected to markedly alter water fluxes and stores in the hydrologic cycle. In addition, water demand continues to grow due to increased human use and a growing population. Sustainably managing water resources requires a thorough understanding of water storage and flow in natural, agricultural, and urban ecosystems. Measurements of stable isotopes of water (hydrogen and oxygen) in the water cycle (atmosphere, soils, plants, surface water, and groundwater) can provide information on the transport pathways, sourcing, dynamics, ages, and storage pools of water that is difficult to obtain with other techniques. However, the potential of these techniques for practical questions has not been fully exploited yet. Here, we outline the benefits and limitations of potential applications of stable isotope methods useful to water managers, farmers, and other stakeholders. We also describe several case studies demonstrating how stable isotopes of water can support water management decision-making. Finally, we propose a workflow that guides users through a sequence of decisions required to apply stable isotope methods to examples of water management issues. We call for ongoing dialogue and a stronger connection between water management stakeholders and water stable isotope practitioners to identify the most pressing issues and develop best-practice guidelines to apply these techniques.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Earth System Model Overestimation of Cropland Temperatures Scales With Agricultural Intensity

Intensive crop growth can modify regional climate by partitioning energy to latent heating through transpiration, cooling growing season temperatures. Recent work shows that cooling associated with agriculture can dampen anthropogenic warming over breadbasket regions. However, it is unknown whether climate models reproduce crop influences on regional climate, and thus the future risk of extreme climate events over global breadbasket regions. Here, we show that models overestimate growing season temperatures and underestimate evapotranspiration (ET) over global croplands, and that these differences increase with cropped area. We trace this warm and dry difference through each model's representation of the surface energy budget, showing that model differences in transpiration, leaf area index, and the ratio of transpiration to total ET drive the overall effect. While the implications of these model deficiencies for future projections are uncertain, they point to the importance of improving representations of crop-climate processes to better assess breadbasket vulnerability to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Enhance indigenous agricultural systems to reduce migration

Changes in social and environmental conditions in the Western Highlands of Guatemala undermine food security and job opportunities. Here, we describe how targeted assistance can build upon traditional agricultural systems to increase adaptive capacity, improve nutrition, provide jobs and thereby reduce pressures to migrate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Hydrologic response of artificially drained agricultural watersheds: insights from high-resolution integrated surface/subsurface simulations

Artificial drainage systems comprising subsurface networks of perforated pipes (tile drains) and engineered surface ditches are widely used to remove excess water from poorly drained agricultural regions. Artificial drainage lowers the water table by design but also has inadvertent effects on the watershed-scale hydrologic response with important implications for flood risk and nutrient exports. We investigated the effects of tile drains on watershed-scale hydrologic response in the Portage River, OH, Watershed using a high-resolution physically based integrated surface/subsurface hydrology model with recently developed capabilities to represent artificial drainage. Tile drains were found to enhance streamflow during times of low flow, generally consistent with previous studies. Streamflow flashiness was found to have a non-monotonic dependence on tile spacing with a minimum at intermediate spacings (∼50 m). Flashiness and the event hydrographs for small tile spacing were similar to the situation with no tiles, but flow paths from farm to stream were very different for those two end member cases, emphasizing the limitations of the stream hydrograph in characterizing hydrologic response. For typical tile spacings, peak flow can either be enhanced or attenuated by the presence of tiles, depending on the size of the event and the antecedent meteorological conditions. Tiles enhance peak flow when the event is below a threshold of ∼25 mm or when events arrive in dry conditions. Peak flow is reduced by tiles when events are large and arrive in conditions that are not overly dry. The dependence on event size and antecedent conditions is explained by differences in available storage and flow paths to the streams. These results provide additional insights into how tile drainage modulates event-scale hydrologic response, an important control on flood generation mechanisms and nutrient exports.

agricultural watershed↗
DOE OSTI2025

Evaluating opportunity for distributed wind energy in rural and agricultural areas

Wind energy is among the most mature renewable energy technologies, accounting for 11% of the current US electricity generation in 2024, with the lowest average levelized cost. While it is known that substantial opportunity exists for further development, a key question has been where wind energy is best suited compared to other technologies. This study leverages an immense dataset of parcel-resolved technoeconomic potential for the contiguous United States, focusing on distributed wind (DW) energy—a configuration where one or more turbines, typically 30–60 m in height are used to satisfy nearby energy needs. The analysis is conducted at multiple spatial scales and considers land use, crop land, census, and incentive program data to determine the most opportune areas for market development. The results show that rural, agricultural and residential areas are most suited to DW. Connection type (in front of, or behind the meter) and regulations determine the best application, while siting constraints, economics, demand and the wind resource determines the optimal size of turbine.

17 WIND ENERGY↗
DOE OSTI2020

Carbon flow through energycane agroecosystems established post-intensive agriculture

As part of an integrated energy and climate system, biomass production for bioenergy based on the tropical perennial C4 grass energycane can both offset fossil fuels and store soil carbon (C). We measured energycane yields, root biomass, soil C pools, and soil C stocks in a 4 year field trial and modeled C flow from plants to soils in the surface layer of no-till energycane planted after more than a century of intensive sugarcane agriculture. Aboveground yields ranged from 16.7 to 19.0 Mg C/ha over the 4 year trial. Although total C stocks did not significantly differ in the surface layer (approx. 0–20 cm) during the study, C in free and occluded light fractions decreased, whereas C in the mineral-rich dense fraction increased over 4 years. Belowground system inputs, estimated from measurements and informed by convergence in the final soil fraction model, were set to 2.5 Mg C ha -1 year -1 . With this input value, we estimated that surface soils retained photosynthetically fixed C predominantly within the mineral-associated organic matter pool for a mean and median transit time of 177 and 110 years, respectively. Although we did not model C flow to deep soil layers (approx. 0–100 cm), observed C accumulation (11.4 Mg C ha -1 year -1 ) and root growth down to 120 cm suggest that soil processes and resulting C sequestration at the surface are likely to persist deeper into the soil profile. Energycane, as a strong candidate for climate change mitigation and land degradation remediation, showed high biomass yields and allocation of resources to roots, with sequestered soil C expected to persist for over a century.

09 BIOMASS FUELS↗