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At least 91 records · Page 5

A coupled hydrologic-agroeconomic modeling framework to evaluate adaptive irrigation strategies under groundwater withdrawal restrictions

Growing groundwater scarcity requires integrated tools to capture interactions among hydrology, agricultural production, markets, and land use. This study presents an iterative modeling framework that couples hydrologic, crop-yield, and economic models to capture two-way feedback among water availability, agricultural production, and market responses under groundwater constraints. The primary goal of this paper is to describe the methodological development of the coupled framework and demonstrate the significance of iterative model interaction. Applied to the western United States, we evaluated adaptive responses to restricting groundwater use beyond recharge levels, represented through changes in irrigation management and expansion or shrinkage of crop markets through land reallocation. Results demonstrate that the iterative coupling converges to stable equilibrium responses within 10 iterations. At equilibrium, deficit irrigation emerges as the dominant adaptation strategy in California, with irrigation levels stabilizing at approximately 70% of full irrigation demand, while Arizona and New Mexico experience stronger yield sensitivities. Early iterations produce commodity price increases of up to 10% for fruit and vegetable crops; however, these responses moderate as land allocation and production patterns adjust across regions. Deficit irrigation and spatial reallocation of irrigated land partially offset production losses, with variability observed across different states: California maintains yields primarily via deficit irrigation, whereas Arizona and New Mexico will rely mainly on reducing irrigated area to absorb the shock. By capturing feedback between biophysical and economic processes, this approach highlights how irrigation strategies and land-use decisions evolve under water stress and provides a transferable platform for evaluating water management policies.

54 ENVIRONMENTAL SCIENCES↗

Linking Hydrobiogeochemical Processes and Management Techniques to Close Nutrient Loops in an Arid River

In this study, we explore opportunities to optimize food-energy-water (FEW) resources by closing nutrient loops in arid-land rivers. Specifically, we evaluate source and sink behavior of nitrogen as nitrate (NO 3 -N) in three characteristic channels in the Middle Rio Grande Basin (Delivery and Drain channels associated with agriculture and the main channel of the Rio Grande). All three channels are located downstream of a large wastewater treatment plant that is the main contributor of nutrients to this reach of the Rio Grande. We used a mass balance approach paired with stable isotope analysis to determine sources and processing of NO 3 -N within the channels over time (a year) and through space (along ~15 to 50 km reaches). Results indicated the growing season was an important period of sink behavior for the Delivery channel and the Rio Grande, but the Drain channel was a year-round source. Stable isotope analysis of 15 N and 18 O found a distinct nitrate signature in the Drain associated with biological processing, as well as Rio Grande sites impacted by agricultural outflow, but no equivalent signature was present in the Delivery channel. Based on our findings, we provide recommendations to help close nutrient loops in the study system and analogous aridland irrigation networks by 1) minimizing loss during the transfer of nutrients from wastewater facilities to agricultural areas, and 2) minimizing enrichment to downstream aquatic ecosystems by sequestering nutrients that escape the nutrient loop.

54 ENVIRONMENTAL SCIENCES↗

Transforming the Future of Marine Aquaculture: A Circular Economy Approach

By mid-century, society will need to significantly intensify the output of its food production system while simultaneously reducing that system’s detrimental impacts on climate, land use, freshwater resources, and biodiversity. This will require finding alternatives to carbon emissions-intensive agriculture, which provides the backbone of today’s global food production system. Here, we explore the hypothesis that marine algae-based aquaculture can help close the projected gap in society’s future nutritional demands while simultaneously improving environmental sustainability. Food production from marine algae-based aquaculture has the potential to contribute more than the total global protein demand projected for 2050, which ranges from 263.8 Mt/yr to 286.5 Mt/yr. It also offers important nutritional and environmental sustainability advantages relative to terrestrial agriculture. Marine algae can provide a better source of high-quality nutritional protein, essential amino acids, and other micronutrients relative to terrestrial plants. In addition, because marine algae do not require soil, irrigation, and the open application of fertilizer, their cultivation does not need to compete with agriculture for arable land and freshwater nor does it lead to fertilizer runoff and downstream eutrophication. Furthermore, by reducing agriculture’s demand for arable land and freshwater, marine algae-based aquaculture can reduce the pressure for deforestation, potentially leading to globally significant reductions in carbon emissions and biodiversity loss.

59 BASIC BIOLOGICAL SCIENCES↗

Separating Oil-Water Mixtures Using Bump Arrays

Particle separation is an important process step across many fields. One technique being applied for separating solids such as blood components or sand particles from carrier fluids is the use of arrays of aligned posts called deterministic lateral arrays to bump particles to one side in the flow stream to enhance separation. This technique may be useful for separation of deformable particles. The ability to efficiently separate two-phase industrial (oil/water) mixtures is key for future use of valuable resources. Over 1 trillion gallons of petroleum production water could be reclaimed annually for reuse in the drought-ridden western US states. The ability to reclaim this petroleum production water may be critical for the Central High Plains (Colorado, Kansas, Oklahoma, Texas, and New Mexico). Trends in just the High Plains area already lost 20 to 25% of the irrigated farming area due to insufficient ground water storage to irrigate, and farmland losses are expected to grow to 40%. Proving this technology is key to reuse of petroleum production water for crop irrigation or to replace water from currently failing aquifers in rich agricultural lands of the Central High Plains. We conducted experiments applying mesofluidic separation for flowing two-phase (oil/water) mixtures. Experiments were conducted using oils of differing viscosities with water as the carrier fluid; separation was achieved over a range of oil-water concentrations. We describe the results of these experiments in this paper.

oil-water separation, micelle, droplet separation,↗

Farm Practice Typologies as a Strategy for Management-Relevant Land Use and Land Cover Mapping in the Great Lakes Region (Version 1) [Dataset]

Dataset overview and development This dataset provides spatially explicit agricultural land-use and land-management typologies developed for the Great Lakes Region (GLR) at the farm-parcel level. The typologies were designed to characterize not only the land-use and land-cover (LULC) associated with individual agricultural farm parcels, but also the land-management practices (LMPs), including irrigation, tile drainage, and conservation easements, occurring within those parcels and how these characteristics change through time. The dataset contains four related typology products: Annual integrated typology – describes the combined LULC and land-management characteristics for each farm parcel for individual years. LULC transition typology – describes the temporal pattern of LULC change for each farm parcel across the study period (2008-2023). LMP trend typology – describes the temporal pattern in the occurrence of LMPs for each farm parcel across the study period. Multi-year integrated typology – combines the LULC transition typology and LMP trend typology to provide an integrated characterization of long-term land-use and management patterns. Purpose of the dataset The purpose of these products is to provide a management-relevant integrated and consistent framework for evaluating the spatial and temporal organization of agricultural landscapes across the GLR. The resulting typologies can: support landscape-scale environmental and land-use analysis; provide spatial information relevant to land-management strategies, conservation planning, policy development, and program evaluation; characterize spatial patterns of agricultural land use and management; examine changes in agricultural landscapes through time; and identify persistent, transitional, and changing agricultural systems. Please refer to the README file provided in Files for more details.

Agriculture↗

InSPIRE 2.0 (Final Technical Report)

Co-locating solar projects and agriculture can provide mutual benefits to local farmers (e.g., dual revenue streams, increased yields from pollinator services, irrigation reductions) and to the solar projects (e.g., reduced timeline/costs for installation and O&M, expanded market, increased PV efficiency from a cooler, vegetated microclimate). While prior work sought to demonstrate the feasibility of agricultural co-location (or "agrivoltaic") opportunities, there is a fundamental gap in data available to developers, landowners, and state agencies that prevents widespread deployment of these mutually beneficial practices. This project addressed this gap by (1) establishing a stakeholder research working group composed of multi-sector industry leaders and academics to provide guidance and assist with outreach; (2) undertaking targeted field-based research projects evaluating solar and agriculture co-location tradeoffs; (3) conducting analysis and modeling studies that complement the field-based research; and (4) developing a data portal to consolidate all data on this topic in one location.

14 SOLAR ENERGY↗

Estimation of Corn Latent Heat Flux from High Resolution Thermal Imagery

Crop evapotranspiration (ET), which is directly related to latent heat flux, is also a key indicator in determining the water status of crops. In order to estimate the latent heat flux, two-source energy balance (TSEB) models have been developed for thermal imagery from satellite platforms. However, because of the coarse resolution of thermal sensors on the satellite, distinguishing soil and vegetation is difficult which complicates the calculation process and introduces errors in latent heat estimates. In this research, high-resolution thermal datasets (0.05 m) and corresponding RGB datasets (0.03 m) were used for calculating crop latent heat flux using an adapted TSEB model. The RGB datasets were used for supervised classification of soil and vegetation, and the classification results were then used to filter the thermal mosaics to separate vegetation and soil temperatures. The vegetation temperature is used for calculating latent heat flux and the results are validated against the ground reference measurements of latent heat using a handheld porometer. The objective of this research is to introduce a workflow including an adapted TSEB model which is customized for high resolution thermal images from unmanned aircraft systems (UAS) to estimate the latent heat flux of row crops in agricultural fields. Nine dates of data collection in 2018 and 2020 have been evaluated and the root mean square error (RMSE) varies between 16 to 106 W/m2 depending on the days after planting (DAP) and the time of measurement for each day. The results indicate that the workflow introduced here is able to provide estimates of instantaneous latent heat flux (evapotranspiration) measurements for row crops in agricultural fields which will enable people to make reliable decisions related to irrigation scheduling.

54 ENVIRONMENTAL SCIENCES↗

Quantifying the effects of varietal types × management on the spatial variability of sorghum biomass across US environments

Abstract Regional‐scale estimations of sorghum biomass production allow identification of optimum genotype×environment×management (G×E×M) combinations for bioenergy generation. The objective of this study was to determine the degree of contributions of G, E, and M toward variability in sorghum biomass in the United States. Using the Agricultural Production Systems sIMulator in a grid computing platform, biomass was simulated for irrigated and rainfed conditions for 30 years across the United States for four sorghum varietal types (grain—GS, sudangrass—SS, photosensitive—PS, and photo‐insensitive—PI). Simulated biomass was assessed by environments clustered using the sum of intercepted solar radiation ( ir ), mean of temperature stress factor ( tp ) and water stress factor ( sw ). Simulated biomass ranged from 5.8 t ha −1 (GS‐rainfed) to 27.5 t ha −1 (PI‐irrigated). Under high‐temperature environments (mean annual temperature = 25°C), rainfed biomass between 40 and 80 days after planting (DAP) was strongly correlated with sw ( r = 0.64–0.86) and irrigated biomass with ir ( r = 0.68–0.81). Under low‐temperature environments (mean annual temperature = 18°C) after 40 DAP, tp and ir had greater effects than sw ( r = 0.55–0.82). Biomass variance was mainly explained by varietal type (50%–76%) in all environments×irrigation combinations, except in the high‐ and mid‐temperature environments under rainfed conditions where rainfall had the major effect (25%–45%). However, when mean temperature during the growing season decreased from 25°C (high environments) to 18°C (low environments), the contribution of mean temperature to biomass variance increased from 7% to 34% (rainfed) and from 4% to 36% (irrigated). Varietal type had the larger interactions with other factors independently of the environment and irrigation. We demonstrated a need to quantify (i) the main G×E×M drivers of biomass variability based on environmental stress factors and (ii) the variance contribution of these drivers on sorghum biomass. Our regional‐scale estimations are key inputs for future robust biomass projections of energy sorghum genotypes integrating G×E×M under climate change scenarios.

Ojeda, Jonathan J.↗

Impact of biochar amendments on soil water and plant uptake dynamics under different cropping systems

Abstract Application of biochar amendments in agricultural systems has received much attention in recent years. In this study, we assess the 5‐year impacts of biochar application on soil water and plant interactions for an irrigated fresh market tomato ( Solanum lycopersicum ) and a rainfed pasture ( Poaceae ) cropping system. In particular, we focus on three varieties of locally produced biochar from agricultural waste materials—almond shell, walnut shell, and almond pruning residues that are pyrolyzed using a mobile pyrolysis unit. We used the soil hydrological model HYDRUS‐1D to explicitly track seasonal and annual soil water fluxes through changes in water retention, drainage, evaporation, and plant water uptake under biochar application. Modeling results show that the application of biochar at 5% increased soil water availability within the top 20 cm for a rainfed system, irrespective of biochar amendment type. This is clearly indicative of higher plant water uptake and greater water use efficiency (WUE) under biochar application. In contrast, a similar biochar amendment for the irrigated system did not affect WUE, instead reducing seasonal soil evaporation loss and thereby reducing irrigation demand. In both cropping systems, year‐to‐year variability in precipitation significantly impacted the total amount of water saved under biochar application with certain amendments retaining more water than others. Given that biochar application increased water retention irrespective of cropping systems, we further used a simple approach to determine yield trade‐off, if any, between control and biochar treatments. Our economic balance clearly demonstrates that the water saved by amending soil with biochar does not offset the yield disparity if compensated with carbon credits and therefore, application of biochar should be actively considered for both its direct and indirect benefits to potential greenhouse gas mitigation (e.g., diverting orchard waste from open burning), water savings, and soil health.

54 ENVIRONMENTAL SCIENCES↗

Integrated Water-Power System Resilience Analysis in a Southeastern Idaho Irrigation District: Minidoka Case Study

This study investigates the joint water–power system resilience of an irrigation district in southeastern Idaho. Irrigation districts face difficulties in the delivery of water to farmers under drought conditions, during equipment failures, or unplanned infrastructure disruptions. The resilience of interconnected water and power systems can be better analyzed and understood through an integrated approach, using a model that connects the dependencies between the two halves of the system. Using a multi-agent system model capturing both water and power system components, as well as their linkages, we capture the interdependencies of these systems and highlight opportunities for improvement when faced with disruptions. Through simulation scenarios, we examine the system resilience using system performance, quantified as the percentage of met demand of the power and water system, when subjected to drought water year, an unforeseen water demand increase, power outage and dam failure. Scenario results indicate that the effects of low flow years are mostly felt in the power system; unexpected increases in water demand marginally impact irrigation system performance; dams and pumps present vulnerabilities of the system, causing substantial unmet demand during disruptions. Noting the interdependencies between the water–power system halves while leveraging an integrated simulation allows for an insightful analysis of the system impacts during disruptions.

13 HYDRO ENERGY↗

An innovative approach for atrazine electrochemical oxidation modelling: Process parameter effect, intermediate formation and kinetic constant assessment

Water reuse for irrigation activities is becoming a crucial worldwide challenge due to the depletion of water sources. Anyway, agricultural drainage can potentially contain dangerous contaminants such as metals, pesticides, and herbicides, including atrazine. To address the need for agriculture wastewater purification, we investigated atrazine removal from simulated wastewater by electro-oxidation using platinum-coated titanium electrodes on a lab-scale experimental apparatus. The effects of electrolyte composition and concentration, i.e. ionic strength and applied current density on atrazine removal, were investigated. The results demonstrated that the electrochemical oxidation of the herbicide occurred through two routes, depending on the presence or absence of oxidizing chlorine species. The generation of intermediates during the treatment was monitored and quantified by evaluating the effect of an inert electrolyte (NaClO 4 ) versus an oxidizable chlorine species (NaCl). In both experimental conditions, five intermediates were identified, including desethyl-atrazine (DEA), hydroxyatrazine (ATZ-OH), desisopropyl-atrazine (DIA) and desethyl-desisopropyl-atrazine (DEDIA). A degradation mechanism and a model for describing hydroxyl radicals and active chlorine species contributions at ATZ oxidation were also proposed. Intermediate evolution profiles suggest that ATZ degradation can be considered as a series–parallel reaction system. Finally, the energy requirement assessment for ATZ removal was carried out. The highest ATZ removal (≅98%) was achieved with NaCl = 0.08 M, J = 60 A/m −2 , and E C = 5.83 kWh m −3 . Results highlight that atrazine removal was improved when an active chlorine species (NaCl) was present in the water solution. Moreover, the addition of chlorine species during electro-oxidation is an energy-saving strategy. Collectively, electro-oxidation technique can be efficiently applied to treat polluted water in order to meet the needs of recycling water quality and reduce resource consumption.

Electro-chemical oxidation↗

CubeSat constellations provide enhanced crop phenology and digital agricultural insights using daily leaf area index retrievals

Satellite remote sensing has great potential to deliver on the promise of a data-driven agricultural revolution, with emerging space-based platforms providing spatiotemporal insights into precision-level attributes such as crop water use, vegetation health and condition and crop response to management practices. Using a harmonized collection of high-resolution Planet CubeSat, Sentinel-2, Landsat-8 and additional coarser resolution imagery from MODIS and VIIRS, we exploit a multi-satellite data fusion and machine learning approach to deliver a radiometrically calibrated and gap-filled time-series of daily leaf area index (LAI) at an unprecedented spatial resolution of 3 m. The insights available from such high-resolution CubeSat-based LAI data are demonstrated through tracking the growth cycle of a maize crop and identifying observable within-field spatial and temporal variations across key phenological stages. Daily LAI retrievals peaked at the tasseling stage, demonstrating their value for fertilizer and irrigation scheduling. An evaluation of satellite-based retrievals against field-measured LAI data collected from both rain-fed and irrigated fields shows high correlation and captures the spatiotemporal development of intra- and inter-field variations. Novel agricultural insights related to individual vegetative and reproductive growth stages were obtained, showcasing the capacity for new high-resolution CubeSat platforms to deliver actionable intelligence for precision agricultural and related applications.

54 ENVIRONMENTAL SCIENCES↗

AmeriFlux FLUXNET-1F US-Ne3 Mead - rainfed maize-soybean rotation site

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Ne3 Mead - rainfed maize-soybean rotation site. This is the FLUXNET version of the carbon flux data for the site US-Ne3 Mead - rainfed maize-soybean rotation site produced by applying the standard ONEFlux (1F) software. Site Description - The study site is one of three fields (all located within 1.6 km of each other) at the University of Nebraska Agricultural Research and Development Center near Mead, Nebraska. While the other two sites are equipped with irrigation systems, this site relies on rainfall. A tillage operation (disking) was done just prior to the 2001 planting to homogenize the top 0.1 m of soil, incorporate P and K fertilizers, as well as previously accumulated surface residues. Since initiation of the study in 2001, this site has been under a strictly no-till, maize-soybean rotation (maize odd years and soybean even years).

Suyker, Andy [University of Nebraska - Lincoln]↗

Attention-based convolutional capsules for evapotranspiration estimation at scale

Evapotranspiration (ET) measures the amount of water lost from the Earth's surface to the atmosphere and is an integral metric for both agricultural and environmental sciences. Understanding and quantifying ET is critical for achieving effective management of freshwater and irrigation systems. However, current ET estimation models suffer from a trade-off between accuracy and spatial coverage. In this study, we introduce our model Quench, a neural network architecture that achieves highly-accurate ET estimates over large continuous spatial extents. Quench uses our novel Attention-Based Convolutional Capsule for its neural network layers to identify areas of focus and efficiently extract ET information from satellite imagery. Benchmarks that profile our model's performance show substantive improvements in accuracy, with up to 128% increase in accuracy compared to traditional convolutional-based and process-based models. Finally, Quench also demonstrates consistent model performance over high geospatial variability and a diverse array of regions, seasons, climates, and vegetations.

54 ENVIRONMENTAL SCIENCES↗

A coupled equilibrium boundary layer model with stable water isotopes and its application to local water recycling

The contribution of evapotranspiration (ET) to regional precipitation, known as “local water recycling”, is a key process in the water cycle that can affect water management. However, the amount of planetary boundary layer (PBL) moisture that arises from ET is highly uncertain due to complex atmosphere and land surface conditions. In this study, an idealized two-layer equilibrium boundary layer model was coupled with a stable water isotope module including HDO and H 2 18 O to constrain PBL growing season water transport processes. The model was validated using turbulent heat fluxes and isotope ratios of water vapor (δ m ) and precipitation (δ P ) measured at a cropland site and a nearby tall tower in the Upper Midwest, United States. The results show that the PBL equilibrium features of δ m and δ P are well-constrained by thermal and moisture equilibrium in the PBL. For this study region, the summer values of rain evaporation fraction (f) and local water recycling ratio (LRR) are estimated to be 0.09 and 0.29 ± 0.12, respectively. The summer LRR values for the years 2006–2010 were 0.35, 0.36, 0.17, 0.29, and 0.29, respectively. The small value of LRR in 2008 corresponded to a drought condition with the lowest precipitation and second lowest ET among the five years. The summer magnitude of the amount effect is –2.8‰ (mm day –1 ) –1 and –0.8‰ (mm day –1 ) –1 for HDO and H 2 18 O, respectively. The local water recycling is identified as a significant factor influencing the continental isotope effect. Cropland has likely changed the regional LRR by –7.6 to 19.5% under different pre-agriculture land use scenarios. In conclusion, the feedback processes revealed here indicate that local water recycling is expected to be weakened under drought conditions, but it will be enhanced if irrigation is applied more intensely with more frequent drought events as the climate continues to warm.

54 ENVIRONMENTAL SCIENCES↗

Zero-Power Wireless Infrared Digitizing Sensors for Large Scale Energy-Smart Farm

This project, funded by ARPA-E and led by Northeastern University, developed zeropower infrared digitizing sensors to optimize irrigation and enhance crop yields. Traditional water stress detection methods are costly and require frequent maintenance, limiting their effectiveness. Our research identified shortwave infrared (SWIR) transmittance as the most reliable indicator of plant water stress and developed plasmonically enhanced micromechanical photoswitches (PMPs) that operate with minimal power. The sensors offer low-cost, large-scale deployment, auto-calibration across different crops, and a 10-year battery life, significantly reducing maintenance costs. The system achieved 4x greater accuracy than conventional soil moisture sensors while ensuring economic feasibility. By enabling precision irrigation, this technology conserves water, enhances crop productivity, and lowers operational costs, making it a scalable solution for sustainable agriculture and global food security.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗