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At least 127 records · Page 7

Planting miscanthus instead of row crops may increase the productivity and economic performance of farmed potholes

Abstract Climate change projections indicate that precipitation events in the central United States are expected to become more intense, more frequent in the spring, and less frequent in the summer. Such a precipitation shift could adversely impact crop yields, especially in subfield areas known as farmed potholes, which are highly susceptible to flooding and ponding, and crop death is more likely to occur, particularly early in the growing season. This suggests that planting alternative crops, such as more flood tolerant perennials, in these areas may be a more profitable option. Using observations of crop growth and yield along with ponding depth of a specific field and farmed pothole in the central United States, we developed a spatially explicit version of the agroecosystem model Agro‐IBIS to estimate water depth and crop yield. After evaluating the model, we conducted a case study for a specific farmed pothole with a range of future precipitation scenarios with Agro‐IBIS to simulate the effects of contemporary (2002–2016) and future precipitation on a conventional corn/soybean ( Zea mays L. and Glycine max Merr.) rotation and an alternative perennial miscanthus ( Miscanthus × giganteus Greef et Deu.) cropping system. The depth and frequency of ponding increased under most future precipitation scenarios. The corn/soybean rotation had greater total loss (i.e., no yield) on average (>30%) for all scenarios in comparison to miscanthus (<10%). Under one future precipitation scenario with increased spring precipitation, both the corn/soybean rotation and miscanthus simulations showed an increase in yield. A simple budget analysis indicated that it is more profitable to plant miscanthus instead of corn or soybeans where yields in farmed potholes are consistently poor. Our findings show that potholes can be individually modeled, and their influence on yield can be quantified for use in future management decisions dictated by change in climate.

54 ENVIRONMENTAL SCIENCES↗

Comparative nutrient drawdown capacities of farmed kelps and implications of metabolic strategy and nutrient source

Abstract Seaweed aquaculture, particularly kelp farming, is a popular topic as a potential solution for mitigating anthropogenic pollutants and enhancing coastal drawdown of carbon and nitrogen. Using a common garden approach, this study evaluated nutrient drawdown capacities of Alaria marginata (ribbon kelp) and Saccharina latissima (sugar kelp) across four commercial kelp farms in Southeast and Southcentral Alaska. Our findings show that A. marginata exhibited ~30% more carbon and 21% more nitrogen content compared to S. latissima . These results demonstrate the potential for A. marginata to serve as a more efficient species for nutrient drawdown into farmed kelp tissues (per unit biomass) for consideration of potential mitigative actions. The efficacy of this drawdown is likely to be driven by the careful pairing of kelp species with farming environment. Temporally, there was a noted increase in carbon content and a decline in nitrogen content from March to May for both species, consistent with known seasonal nutrient dynamics in coastal waters. Notably, differences in the carbon stable isotope signatures (δ 13 C) between the kelps may hint at variations in metabolic pathways and nutrient sourcing, particularly concerning the preferential assimilation of CO 2 versus , and highlight the need for further work on this topic for applied macroalgal research.

Stephens, Tiffany↗

Wcomp (Wind Farm Wake Comparison Framework) [SWR-23-72]

The Wind Farm Wake Comparison Framework (Wcomp) is a software tool to facilitate the comparison of a specific collection of wind farm wake modeling tools: Python-based, steady-state, analytical wake modeling utilities. Wcomp integrates another software project, windIO, to create a consistent method for describing a wind farm flow control problem. Additionally, a data structure is included to represent the outputs a wind farm flow control simulation. Well-described interfaces allow existing wake modeling tools to plug into this framework.

Mudafort, Rafael↗

Evaluation of the Fitch Wind-Farm Wake Parameterization with Large-Eddy Simulations of Wakes Using the Weather Research and Forecasting Model

Abstract Wind-farm parameterizations in weather models can be used to predict both the power output and farm effects on the flow; however, their correctness has not been thoroughly assessed. We evaluate the wind-farm parameterization of the Weather Research and Forecasting Model with large-eddy simulations (LES) of the wake performed with the same model. We study the impact on the velocity and turbulence kinetic energy (TKE) of inflow velocity, roughness, resolution, number of turbines (one or two), and inversion height and strength. We compare the mesoscale with the LES by spatially averaging the LES within areas correspondent to the mesoscale horizontal spacing: one covering the turbine area and two downwind. We find an excellent agreement of the velocity within the turbine area between the two types of simulations. However, within the same area, we find the largest TKE discrepancies because in mesoscale simulations, the turbine-added TKE has to be highest at the turbine position to be advected downwind. Within the downwind areas, differences between velocities increase as the wake recovers faster in the LES, whereas for the TKE both types of simulations show similar levels. From the various configurations, the impact of inversion height and strength is small for these heights and inversion levels. The highest impact for the one-turbine simulations appears under the low-speed case due to the higher thrust, whereas the impact of resolution is low for the large-eddy simulations but high for the mesoscale simulations. Our findings demonstrate that higher-fidelity simulations are needed to validate wind-farm parameterizations.

17 WIND ENERGY↗

AmeriFlux US-CLF Cole Farm

This is the AmeriFlux version of the carbon flux data for the site US-CLF Cole Farm. Site Description - The Cole Farm catchment (0.65km2) is located ~ 4 km southwest of the Shale Hills site, draining orthogonally to a syncline axis of the Wills Creek Formation, a calcareous shale containing interbedded siltstone, sandstone, shaly limestone, and dolomite. Even though the farm adopted no-till practices in the 1970s, the axial channel of Cole Farm flows over a thick (>2.5 m) package of sediment in the valley floor. Soils range in texture from silty clay at the ridge top to sandy loam in the valley floor. Data was collected and funded by the Critical Zone Observatory Network.

Davis, Kenneth J.↗

AmeriFlux FLUXNET-1F US-NC5 NC Butner Farm

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-NC5 NC Butner Farm. This is the FLUXNET version of the carbon flux data for the site US-NC5 NC Butner Farm produced by applying the standard ONEFlux (1F) software. Site Description - The US-NC5 flux tower is located within an 80-year-old mixed pine-hardwood forest at the Umstead Research Farm in Butner, North Carolina. The northern section of this 20-hectare Fall Lake Watershed of the Neuse River Basin in the Piedmont of North Carolina, USA. The Northern portion is currently a managed cattle farm, which is slated for expansion—necessitating forest clearing in the flux site. To establish a reference baseline, a year-long, all-season eddy covariance flux monitoring campaign will be conducted from April 2025 to March 2026. This effort aims to capture the carbon flux dynamics of the mature forest ecosystem prior to a planned land-use conversion. The site will be transitioned into a silvopasture, maintained through prescribed burning and cattle grazing to promote an open-canopy watershed structure. Flux measurements will continue after the conversion.

Sun, Ge [USDA Forest Service]↗

Analysis of Air-Purifying Respirator (APR) and Powered Air-Purifying Respirator (PAPR) Cartridge Performance Testing on a Hanford AX Tank Farm Exhauster Slipstream Volume 2: Raw Analytical Data

As the Tank Operations Contractor for U.S. Department of Energy operations at the Hanford site in Washington State, Washington River Protection Solutions (WRPS) is responsible for managing highly radioactive wastes stored in tanks at Hanford. To protect workers at Hanford Tank Farms, WRPS tests air-purifying respirator (APR) and powered air-purifying respirator (PAPR) chemical cartridges commonly used at the tank farms. The tests were conducted to determine the period of time the cartridges would provide adequate performance for APRs and PAPRs when workers are exposed to a mixture of Chemicals of Potential Concern (COPC) from any vapors exiting headspaces in the storage tanks. Occupational Safety and Health Administration (OSHA) Standard 29 Code of the Federal Regulations (CFR) 1910.134(d)(3)(iii)(b)(2) specifies that for protection against gases and vapors, employers shall implement a schedule for cartridges to ensure that change-outs occur before the end of service life. The change schedule can be based on objective information or data that ensures cartridge change-outs occur before the end of their service life. The primary function of the WRPS Cartridge Test Program is to obtain objective data to determine service lives for the APR and PAPR cartridges used at Hanford Tank Farms. WRPS contracted with Pacific Northwest National Laboratory to analyze the test data and offer an independent analysis and any recommendations. This report summarizes data analysis of APR and PAPR cartridge testing on a vapor slipstream from the Hanford AX tank farm exhauster. Volume 1 of this report documents the testing, data analysis, results, conclusions, and recommendations resulting from the cartridge testing on AX exhauster slipstream vapors. Volume 2 provides an introduction to the raw data, including analytical laboratory analysis results that supported the analysis and conclusions documented in Volume 1.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Coupled wave-current modeling for hydrodynamic load analysis of macroalgae cultivation farms

Large-scale cultivation of macroalgae is one of the most promising biofuel sources that could reduce our consumption of fossil fuels and would be particularly economically competitive when grown for the co-production of additional goods such as food and textiles. Current production of biofuel from algal biomass is limited by labor costs and lack of data on potential impacts of cultivation and harvesting on marine and coastal environments as well as a comprehensive characterization of the impact of environmental conditions on macroalgal feedstock and their bioproduct and biofuel yield and quality. Awarded by the United States (U.S.) Department of Energy Advanced Research Projects Agency-Energy (ARPA-E) Macroalgae Research Inspiring Novel Energy Resources (MARINER) program, which seeks to enable the U.S. as a global leader in the production of marine biomass, the Marine Biological Laboratory (MBL) has been developing a test system for tropical seaweed cultivation in the Gulf of Mexico and the Caribbean. An integral step in designing macroalgae cultivation farms is to adequately characterize the hydrodynamic climate at potential growth sites. In regions like the Gulf of Mexico and the Caribbean, which are highly exposed to tropical cyclones, it is critical to not only consider the day-to-day hydrodynamic conditions but to also assess the risk of extreme sea states to ensure the survivability of future macroalgae farms. Under these considerations, the Pacific Northwest National Laboratory (PNNL) is providing modeling support for MBL to inform the design and siting of the farm systems that have been proposed for their ARPA-E MARINER project. This report describes the development of a high-resolution coupled storm surge and wave model to simulate the hydrodynamics and wave climate at proposed macroalgae cultivation sites selected by MBL in Florida and Puerto Rico. Model results, including model validation, water level, current distributions, and sea states, are discussed for both selected sites in Florida and Puerto Rico coast. These simulations provide an accurate insight into the hydrodynamic conditions that a macroalgae farm is likely to experience during its operational lifetime, including current information to support fine-scale hydrodynamic load modeling, risk analysis and system design.

09 BIOMASS FUELS↗

Are long-term climate projections useful for on-farm adaptation decisions?

The current literature on climate services for farmers predominantly focuses on seasonal forecasts, with an assumption that longer-term climate projections may not be suitable for informing farming decisions. In this paper, we explore whether certain types of long-term climate projections may be useful for some specific types of farming decisions. Through interviews with almond tree crop farmers and farm advisors in California, we examine how farmers perceive the utility and accuracy levels of long-term climate projections and identify the types of projections that they may find useful. The interviews revealed that farmers often perceive long-term climate projections as an extension of weather forecasts, which can lead to their initial skepticism of the utility of such information. However, we also found that when farmers were presented with long-term trends or shifts in crop-specific agroclimatic metrics (such as chill hours or summer heat), they immediately perceived these as valuable for their decision-making. Hence, the manner in which long-term projections are framed, presented, and discussed with farmers can heavily influence their perception of the potential utility of such projections. The iterative conversations as part of the exploratory interview questions, served as a tool for “ joint construction of meaning” of complex and ambiguous terms such as “long-term climate projections,” “long-term decisions” and “uncertainty.” This in-turn supported a joint identification (and understanding) of the types of information that can potentially be useful for on-farm adaptive decisions, where the farmer and the interviewer both improvise and iterate to find the best types of projections that fit specific decision-contexts. Overall, this research identifies both the types of long-term climate information that farmers may consider useful, and the engagement processes that are able to effectively elicit farmers' long-term information needs.

Jagannathan, Kripa↗

Engineering A Low-Cost Kelp Aquaculture System for Community-Scale Seaweed Farming at Nearshore Exposed Sites via User-Focused Design Process

For over 50 years, government fishery agencies have recognized the need to transition excess fishing capacity in coastal waters to aquaculture. For the most part, investment strategies to move wild capture and harvest efforts into aquaculture have failed since the technology and capital expense for entry, such as large fish pens, was not conducive for acceptance. In contrast, low trophic level aquaculture of shellfish and seaweeds is suitable as an addition to the livelihoods of seasonal fishing communities and to those displaced by fishery closures, especially if vessels and gear can be designed around existing fishing infrastructures, thus allowing fishers to maintain engagement with their primary fishery, while augmenting income via aquaculture. In this study, an inexpensive, lightweight, and highly mobile gear for kelp seaweed farming was developed and tested over a 3-year period in southern Maine, USA. The system was different from existing kelp farming operations used in nearshore waters that use low-scope mooring lines, and heavy, deadweight anchors. Instead, a highly mobile, easy to deploy system using lightweight gear was designed for exposed conditions. The entire system fit into fish tote boxes and was loadable onto a standard pickup truck. The seaweed system had small but efficient horizontal drag embedment anchors connected to a chain catenary and pretensioned with simple subsurface flotation. The system was able to be deployed and removed in less than 4 h by a crew of three using a 10 m vessel and produced a harvest of 12.7 kg/m over an 8-month fall-winter growth period. The target group for this seaweed research and development effort were coastal fishing communities who move seasonally into non-fishing occupations in service industries, such as construction, retail, etc. An economic assessment suggests farmers would realize an 8% return on investment after3 years and $13.50/h greater income as compared to a non-farming off season job at minimum wage. This low-cost seaweed farming system for fall-winter operations fits well into a “livelihood” strategy for fishing families who must work multiple jobs in the offseason when their main fishery is unavailable.

St-Gelais, Adam T.↗

Wind farm structural response and wake dynamics for an evolving stable boundary layer: computational and experimental comparisons

Abstract. The wind turbine design process requires performing thousands of simulations for a wide range of inflow and control conditions, which necessitates computationally efficient yet time-accurate models, especially when considering wind farm settings. To this end, FAST.Farm is a dynamic-wake-meandering-based mid-fidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. This work is an extension of a study that addressed constructing a diurnal cycle evolution based on experimental data (Quon, 2024). Here, this inflow is used to validate the turbine structural and wake-meandering response between experimental data, FAST.Farm simulation results, and high-fidelity large-eddy simulation results from the coupled Simulator fOr Wind Farm Applications (SOWFA)–OpenFAST tool. The validation occurs within the nocturnal stable boundary layer when corresponding meteorological and turbine data are available. To this end, we compared the load results from FAST.Farm and SOWFA–OpenFAST to multi-turbine measurements from a subset of a full-scale wind farm. Computational predictions of blade-root and tower-base bending loads are compared to 10 min statistics of strain gauge measurements during 3.5 h of the evolving stable boundary layer, generally with good agreement. This time period coincided with an active wake-steering campaign of an upstream turbine, resulting in time-varying yaw positions of all turbines. Wake meandering was also compared between the computational solutions, generally with excellent agreement. Simulations were based on a high-fidelity precursor constructed from inflow measurements and using state-of-the-art mesoscale-to-microscale coupling.

17 WIND ENERGY↗

Induced Markov chain for wind farm generation forecasting

Systems and methods for forecasting power generation in a wind farm are disclosed. The systems and methods utilize an induced Markov chain model to generate a forecast of power generation of the wind farm. The forecast is at least one of a point forecast or a distributional forecast. Additionally, the systems and methods modify at least one of: (i) a generation of electricity at a power plant coupled to a common power grid as the wind farm; or (ii) a distribution of electricity in the common power grid based on the forecast of power generation of the wind farm. In an exemplary approach, utilizing the induced Markov chain model to generate the forecast may include determining a series of time adjacent power output measurements based on historical wind power measurements and calculating a time series of difference values based on the series of time adjacent power output measurements.

17 WIND ENERGY↗

Solar Farm’s Microclimates Effects: Predicting Abundance and Visiting Frequency of Pollinators

The solar farm is garnering attention for its contribution to ecosystem services, particularly in supporting pollinators. Although numerous studies have focused on the distinct microclimates of solar farms, there has been limited effort to validate and model the impact of these conditions on insects [1]. To effectively evaluate and leverage the ecosystem services from solar farms in policymaking, understanding how insects react to microclimate variations in diverse designs and management methods is essential. This study aims to validate and model the impact of temperature and shade at solar farms on pollinator populations and their frequency of pollination as well as compare the potential for increased pollination under different types of panels within a solar grazing setup.

Chung, Hyun Yong↗

Evaluating Liquid Waste Transfers and their Impacts to the SRS Tank Farm to Support Operations and Closure

The Liquid Waste (LW) contractor at the Savannah River Site, Savannah River Mission Completion (SRMC), supports the storage, processing, and safe disposition of legacy, radioactive liquid waste. The LW Tank Farms contain approximately 127 million liters (33.5 million gallons) of liquid waste within 43 active, underground waste tanks. To meet mission critical milestones for the closure of waste tanks and processing of 34 million liters (9 million gallons) of salt waste per year by the LW Salt Waste Processing Facility (SWPF), an increase in Tank Farm operations, including waste tank transfers, is required. Waste is compiled in salt and sludge batches in the Tank Farms and transferred to SWPF and the Defense Waste Processing Facility (DWPF) for treatment. All waste tank transfers, such as waste removal and batch compilation transfers, must be pre-evaluated to ensure Documented Safety Analysis (DSA) requirements are met via Evaluated Transfer Approval Forms (ETAFs). Facility conditions and configurations may change as a result of a waste transfer. These changes must be reflected in the Tank Farms Emergency Response Datasheet (ERD), which contains data utilized for operation and emergency situations.

Peterson, Shelby R.↗

Assessment of Water Quality in Indo-Gangetic Plain of South-Eastern Asia under Organic vs. Conventional Rice Farming

Water contamination is often reported in agriculturally intensive areas such as the Indo-Gangetic Plain (IGP) in south-eastern Asia. We evaluated the impact of the organic and conventional farming of basmati rice on water quality during the rainy season (July to October) of 2011 and 2016 at Kaithal, Haryana, India. The study area comprised seven organic and seven conventional fields where organic farming has been practiced for more than two decades. Water quality parameters used for drinking (nitrate, NO 3 ; total dissolved solids (TDS); electrical conductivity (EC) pH) and irrigation (sodium adsorption ratio (SAR) and residual sodium carbonate (RSC)) purposes were below permissible limits for all samples collected from organic fields and those from conventional fields over the long-term (~15 and ~20 years). Importantly, the magnitude of water NO 3 contamination in conventional fields was approximately double that of organic fields, which is quite alarming and needs attention in future for farming practices in the IGP in south-eastern Asia.

54 ENVIRONMENTAL SCIENCES↗

Large eddy simulation of wind farm performance in horizontally and vertically staggered layouts

This numerical investigation employs Large Eddy Simulation (LES) coupled with Actuator Disk Model (ADM) to evaluate wind farm layout optimization strategies. The study presents a systematic analysis of aligned, horizontal staggering, vertical staggering, and mixed (combination of horizontal and vertical) staggering configurations, aiming to establish optimal design parameters for enhanced power production. The investigation examines key performance metrics including mean velocity distributions, turbulence intensity characteristics, and power generation efficiency. Results demonstrate better performance of both horizontal and vertical staggering patterns compared to conventional aligned configurations, with horizontal staggering exhibiting notably higher power output than vertical arrangements. Our findings also suggest that mixed configurations, incorporating both horizontal and vertical staggering, can offer optimal performance characteristics. As a result, this research advances the understanding of wake interactions in complex wind farm layouts and provides design guidelines for maximizing wind farm power generation efficiency through strategic turbine positioning.

17 WIND ENERGY↗

Conceptual Design and Rationale for a New Agrivoltaics Concept: Pastured-Raised Rabbits and Solar Farming

Land-use conflicts created by the growth of solar photovoltaics (PV) can be mitigated by applying the concept of agrivoltaics, that is, the co-development of land for both PV and agricultural purposes, to commercial-scale solar installations. In this study, we present a conceptual design for a novel agrivoltaic system based on pasture-fed rabbit farming and provide the technical, environmental and economic analyses to demonstrate the viability of the concept. Included in our analysis are the economic advantages to the PV operator of grazing rabbits at a density sufficient to control vegetative growth, thus reducing the economic and environmental costs of mowing; the dual-revenue stream from the sale of both rabbits and electricity, contrasted with estimates of the capital-investment costs for rabbits co-located with, and also independent of, PV; and the economic value to the rabbit farmer of higher colony-growth rates (made possible by the shading and predator protection provided by the PV arrays and of reduced fencing costs, which are the largest capital cost, by being able to leverage the PV systems for rabbit fencing. We also provide an environmental analysis that suggests that rabbit-PV farming is a pathway to a measurable reduction in agriculturally-generated greenhouse-gas emissions. Here, our calculations indicate that the co-location of solar and rabbit farms is a viable form of agrivoltaics, increasing overall site revenue by 2.5%-24.0% above projected electricity revenue depending on location and rental/ownership of rabbits, while providing a high-value agricultural product that, on a per weight basis, has significantly less environmental impact than cattle.

14 SOLAR ENERGY↗

Control co-design under uncertainty for offshore wind farms: Optimizing grid integration, energy storage, and market participation

Offshore wind farms (OWFs) are set to significantly contribute to global decarbonization efforts. Developers often use a sequential approach to optimize design variables and market participation for grid-integrated offshore wind farms. However, this method can lead to sub-optimal system performance, and uncertainties associated with renewable resources are often overlooked in decision-making. Here, this paper proposes a control co-design approach, optimizing design and control decisions for integrating OWFs into the power grid while considering energy market and primary frequency market participation. Additionally, we introduce optimal sizing solutions for energy storage systems deployed onshore to enhance revenue for OWF developers over time. This framework addresses uncertainties related to wind resources and energy prices. We analyze five U.S. west-coast offshore wind farm locations and potential interconnection points, as identified by the Bureau of Ocean Energy Management (BOEM). Results show that optimized control co-design solutions can increase market revenue by 3.2% and provide flexibility in managing wind resource uncertainties.

Control Co-design↗