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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Regenerative Life Support Systems Test Bed performance - Lettuce crop characterization

Two crops of lettuce (Lactuca sativa cv. Waldmann's Green) were grown in the Regenerative Life Support Systems (RLSS) Test Bed at NASA's Johnson Space Center. The RLSS Test Bed is an atmospherically closed, controlled environment facility for the evaluation of regenerative life support systems using higher plants. The chamber encloses 10.6 m 2 of growth area under cool-white fluorescent lamps. Lettuce was double seeded in 480 pots, each containing about 250 cm 3 of calcined-clay substrate. Each pot was irrigated with half-strength Hoagland's nutrient solution at an average total applied amount of 2.5 and 1.8 liters pot -1 , respectively, over each of the two 30-day crop tests. Average environmental and cultural conditions during both tests were 23°C air temperature, 72% relative humidity, 1000 ppm carbon dioxide (CO 2 ), 16h light/8h dark photoperiod, and 356 μmol m -2 s -1 photosynthetic photon flux. After 30 days from seeding, average yield (g pot -1 ) for the first and second crop tests were 72 and 49 edible (shoot) fresh mass, 3.65 and 2.56 edible dry mass, and 0.44 and 0.45 inedible (root) dry mass, respectively. Averaging over both crop tests, the test bed met the requirements of 2.1 person-days of oxygen production, 2.4 person days of CO 2 removal and 129 person days of potential potable water production. The satisfactory growth of both crops demonstrates the potential of lettuce for air revitalization and water production in a controlled ecological life support system. Differences in crop performance resulting from engineering system effects provides evidence of the resilience of biological systems.

Life support systems↗
NASA NTRS1997

Selection and Characterization of Vegetable Crop Cultivars for use in Advanced Life Support Systems

Cultivar evaluation for controlled environments is a lengthy and multifaceted activity. The chapters of this thesis cover eight steps preparatory to yield trials, and the final step of cultivar selection after data are collected. The steps are as follows: 1. Examination of the literature on the crop and crop cultivars to assess the state of knowledge. 2. Selection of standard cultivars with which to explore crop response to major growth factors and determine set points for screening and, later, production. 3. Determination of practical growing techniques for the crop in controlled environments. 4. Design of experiments for determination of crop responses to the major growth factors, with particular emphasis on photoperiod, daily light integral and air temperature. 5. Developing a way of measuring yield appropriate to the crop type by sampling through the harvest period and calculating a productivity function. 6. Narrowing down the pool of cultivars and breeding lines according to a set of criteria and breeding history. 7. Determination of environmental set points for cultivar evaluation through calculating production cost as a function of set points and size of target facility. 8. Design of screening and yield trial experiments emphasizing efficient use of space. 9. Final evaluation of cultivars after data collection, in terms of production cost and value to the consumer. For each of the steps, relevant issues are addressed. In selecting standards to determine set points for screening, set points that optimize cost of production for the standards may not be applicable to all cultivars. Production of uniform and equivalent- sized seedlings is considered as a means of countering possible differences in seed vigor. Issues of spacing and re-spacing are also discussed.

Langhans, Robert W.↗
NASA NTRS2000

Matching Crew Diet and Crop Food Production in BIO-Plex

This paper matches the BIO-Plex crop food production to the crew diet requirements. The expected average calorie requirement for BIO-Plex is 2,975 Calories per crewmember per day, for a randomly selected crew with a typical level of physical activity. The range of 2,550 to 3,400 Calories will cover about two-thirds of all crews. The exact calorie requirement will depend on the gender composition, individual weights, exercise, and work effort of the selected crew. The expected average crewmember calorie requirement can be met by 430 grams of carbohydrate, 100 grams of fat, and 90 grams of protein per crewmember per day, for a total of 620 grams. Some fat can replaced by carbohydrate. Each crewmember requires only 2 grams of vitamins and minerals per day. Only unusually restricted diets may lack essential nutrients. The Advanced Life Support (ALS) consensus is that BIO-Plex should grow wheat, potato, and soybean, and maybe sweet potato or peanut, and maybe lettuce and tomato. The BIO-Plex Biomass Production System food production and the external food supply must be matched to the crew diet requirement for calories and nutritional balance. The crop production and external supply specifications can each be varied as long as their sum matches the required diet specification. We have wide flexibility in choosing the crops and resupply. We can easily grow one-half the crew calories in one BIO-Plex Biomass Production Chamber (BPC) if we grow only the most productive crops (wheat, potato, and sweet potato) and it we achieve nominal crop productivity. If we assume higher productivity we can grow a wider variety of crops. If we grow one-half of the crew calories, externally supplied foods can easily provide the other half of the calories and balance the diet. We can not grow 95 percent of the crew calories in two BPCs at nominal productivity while growing a balanced diet. We produce maximum calories by growing wheat, potato, and peanut.

Jones, Harry↗
NASA NTRS2002

Application of Thermal Infrared Remote Sensing for Quantitative Evaluation of Crop Characteristics

Evidence suggests that thermal infrared emittance (TIR) at the field-scale is largely a function of the integrated crop/soil moisture continuum. Because soil moisture dynamics largely determine crop yields in non-irrigated farming (85 % of Alabama farms are non-irrigated), TIR may be an effective method of mapping within field crop yield variability, and possibly, absolute yields. The ability to map yield variability at juvenile growth stages can lead to improved soil fertility and pest management, as well as facilitating the development of economic forecasting. Researchers at GHCC/MSFC/NASA and Auburn University are currently investigating the role of TIR in site-specific agriculture. Site-specific agriculture (SSA), or precision farming, is a method of crop production in which zones and soils within a field are delineated and managed according to their unique properties. The goal of SSA is to improve farm profits and reduce environmental impacts through targeted agrochemical applications. The foundation of SSA depends upon the spatial and temporal characterization of soil and crop properties through the creation of management zones. Management zones can be delineated using: 1) remote sensing (RS) data, 2) conventional soil testing and soil mapping, and 3) yield mapping. Portions of this research have concentrated on using remote sensing data to map yield variability in corn (Zea mays L.) and soybean (Glycine max L.) crops. Remote sensing data have been collected for several fields in the Tennessee Valley region at various crop growth stages during the last four growing seasons. Preliminary results of this study will be presented.

Shaw, J.↗
NASA NTRS1990

Space Data for Crop Management

CROPIX, Inc., formed in 1984 by Frank Lamb, president of the Eastern Oregon Farming Company, monitors primarily potato crops in a 20,000 square mile area of northern Oregon and central Washington. Potatoes are a high value specialty crop that can be more profitable to the farmer if he has advance knowledge of market conditions, knows when to harvest, and when to take it to market. By processing and collecting data collected by the NASA-developed Landsat Earth Resources survey satellites, Lamb is able to provide accurate information on crop acreage and conditions on a more timely basis than the routine estimates by the USDA. CROPIX uses Landsat data to make acreage estimates of crops, and to calculate a field-by-field vegetative index number. CROPIX then distributes to its customers a booklet containing color-coded maps, an inventory of crops, plus data and graphs on crop conditions and other valuable information.

Source record↗
NASA NTRS2002

Advanced Life Support Food Subsystem Salad Crop Requirements

As the National Aeronautics and Space Administration (NASA) begins to look towards longer duration space flights, the importance of fresh foods and varied menu choices increases. Long duration space missions require development of both a Transit Food System and a Lunar or Planetary Food System. These two systems are intrinsically different since the first one will be utilized in the transit vehicle in microgravity conditions while the second will be used in conditions of partial gravity (hypogravity). The Transit Food System will consist of prepackaged food of extended shelf life. Microgravity imposes significant limitations on the ability of the crew to handle food and allows only for minimal processing. Salad crops will be available for the planetary mission. Supplementing the transit food system with salad crops is also being considered. These crops will include carrots, tomatoes, lettuce, radish, spinach, chard, cabbage, and onion. The crops will be incorporated in the menu along with the prepackaged food. The fresh tasting salad crops will provide variety, texture, and color in the menu. This variety should provide increased psychological benefit. Preliminary studies on spinach, tomatoes, and bok choy have been completed. Sensory and analytical tests, including color and moisture were conducted on the chamber grown crops and compared to store bought spinach, tomatoes, and bok choy. Preliminary studies of the appropriate serving sizes and number of servings per week have also been conducted.

Perchonok, Michele H.↗
NASA NTRS2016

How Universal is the Relationship Between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment

Leaf Area Index (LAI) is a key variable that bridges remote sensing observations to the quantification of agroecosystem processes. In this study, we assessed the universality of the relationships between crop LAI and remotely sensed Vegetation Indices (VIs). We first compiled a global dataset of 1459 in situ quality-controlled crop LAI measurements and collected Landsat satellite images to derive five different VIs including Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), two versions of the Enhanced Vegetation Index (EVI and EVI2), and Green Chlorophyll Index (CI(sub Green)). Based on this dataset, we developed global LAI-VI relationships for each crop type and VI using symbolic regression and Theil-Sen (TS) robust estimator. Results suggest that the global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. These relationships explain more than half of the total variance in ground LAI observations (R2 greater than 0.5), and provide LAI estimates with RMSE below 1.2 m2/m2. Among the five VIs, EVI/EVI2 are the most effective, and the crop-specific LAI-EVI and LAI-EVI2 relationships constructed by TS, are robust when tested by three independent validation datasets of varied spatial scales. While the heterogeneity of agricultural landscapes leads to a diverse set of local LAI-VI relationships, the relationships provided here represent global universality on an average basis, allowing the generation of large-scale spatial-explicit LAI maps. This study contributes to the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

Vegetation Index↗
NASA NTRS2017

Temperature Increase Reduces Global Yields of Major Crops in Four Independent Estimates

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multi-method analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.

Zhao, Chuang↗
NASA NTRS2018

Spatially-Explicit Monitoring of Crop Photosynthetic Capacity Through the Use of Space-Based Chlorophyll Fluorescence Data

Plant functional traits such as photosynthetic capacity are critical parameters for terrestrial biosphere models. However, their spatial and temporal characteristics are still poorly represented. In this study, we used satellite observations of sun-induced fluorescence (SIF) to estimate top-of-canopy photosynthetic capacity (maximum carboxylation rate, V(sub cmax) at a reference temperature of 25 deg C) for crops, which was in turn utilized to simulate regional gross primary production (GPP). We first estimate the key parameter, V(sub cmax), in the widely-used FvCB photosynthesis model using field measurements of CO2 and water fluxes during 2007-2012 at seven crop eddy covariance flux sites over the US Corn Belt. The results showed that satellite far-red SIF retrievals have a stronger link to V(sub cmax) at the seasonal scale (R(squared)=0.70 for C4 and R(squared)=0.63 for C3 crop) as compared with widely-used vegetation indices. We calibrate an empirical model linking V(sub cmax) with SIF that was used to estimate spatially and temporally varying crop V(sub cmax) for the US Corn Belt region. The resulting V(sub cmax) maps are used together with meteorological data from MERRA reanalysis data and vegetation structural parameters derived from the satellite- based spectral reflectance data to constrain the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) balance model in order to estimate regional crop GPP. Our results show a substantial improvement in the seasonal and spatial patterns of cropland GPP when compared with crop yield inventory data. The evaluation with tall tower atmospheric CO2 measurements further supports our estimation of spatiotemporal V(sub cmax) from space-borne SIF. Considering that SIF has a direct link to photosynthetic activity, our findings highlight the potential to infer regional V(sub cmax) using remotely sensed SIF data and to use this information for a better quantification of regional cropland carbon cycles.

Drought↗
DOE OSTI2026

Life cycle analysis of dedicated energy crops for fuel production in the United States

Dedicated energy crops are promising feedstocks to make biofuels including jet fuels. This study applies life cycle analysis (LCA) to estimate direct well-to-wake (WTW) greenhouse gas (GHG) emissions (g CO 2 e/MJ) for jet fuel derived from five energy crops-biomass sorghum, miscanthus, switchgrass, poplar, and willow-via Fischer-Tropsch-to-Jet (FTJ) and Ethanol-to-Jet (ETJ) pathways. The WTW boundary includes direct emissions from biomass production, fuel production, and fuel combustion. The R&D GREET model is expanded to conduct the LCA, using national average biomass yields and farming inputs from the 2023 Billion-Ton Study. In addition, this study estimates emissions from market-mediated effects, including induced land-use change, induced other crop (non-feedstock) production changes, and induced livestock production changes using global economic and emissions factor models. On a per-dry U.S. ton basis, cultivation and harvest emissions are lowest for willow (51,565 g CO 2 e) and highest for biomass sorghum (104,488 g CO 2 e). Per-acre results show similarly high emissions for sorghum and lowest values for poplar and willow. Direct WTW emissions are substantially lower for FTJ (biomass sorghum: 5.5; miscanthus: 10.3; switchgrass: 11.7; poplar: 11.9; and willow: 8.7 g CO 2 e/MJ) than ETJ (33.2; 33.8; 34.8; 36.2; and 31.7 g CO 2 e/MJ, respectively). When market-mediated emissions are included, miscanthus exhibits the lowest total emissions across energy crop pathways. Although results are sensitive to modeling assumptions, they indicate that high-yielding perennial and woody crops, particularly when planted on marginal land, could significantly reduce WTW emissions for bio-jet fuels by combining low direct emissions with soil carbon gains and favorable market-mediated effects.

Billion-Ton Study↗
NASA NTRS2021

Strong Regional Influence of Climatic Forcing Datasets on Global Crop Model Ensembles

We present results from the Agricultural Model Intercomparison and Improvement Project (AgMIP) Global Gridded Crop Model Intercomparison (GGCMI) Phase I, which aligned 14 global gridded crop models (GGCMs) and 11 climatic forcing datasets (CFDs) in order to understand how the selection of climate data affects simulated historical crop productivity of maize, wheat, rice and soybean. Results show that CFDs demonstrate mean biases and differences in the probability of extreme events, with larger uncertainty around extreme precipitation and in regions where observational data for climate and crop systems are scarce. Countries where simulations correlate highly with reported FAO national production anomalies tend to have high correlations across most CFDs, whose influence we isolate using multi-GGCM ensembles for each CFD. Correlations compare favorably with the climate signal detected in other studies, although production in many countries is not primarily climate-limited (particularly for rice). Bias-adjusted CFDs most often were among the highest model-observation correlations, although all CFDs produced the highest correlation in at least one top-producing country. Analysis of larger multi-CFD-multi-GGCM ensembles (up to 91 members) shows benefits over the use of smaller subset of models in some regions and farming systems, although bigger is not always better. Our analysis suggests that global assessments should prioritize ensembles based on multiple crop models over multiple CFDs as long as a top-performing CFD is utilized for the focus region.

Agricultural Model Intercomparison and Improvement↗
NASA NTRS2022

Global Gridded Crop Models Underestimate Yield Responses to Droughts and Heatwaves

Extreme events can lead to crop yield declines, resulting in financial losses and threats to food security, and the frequency and intensity of such events is projected to increase. As global gridded crop models (GGCMs) are commonly used to assess climate change impacts on agricultural yields, there is a need to understand whether these models are able to reproduce the observed yield declines. We evaluated 13 GGCMs from the Inter-Sectoral Impact Model Intercomparison Project and compared observed and simulated impact of past droughts and heatwaves on yields for four crops (maize, rice, soy, wheat). We found that most models detect but underestimate the impact of droughts and heatwaves on yield. Specifically, the drought signal was detected by 12 of 13 models for maize and all models for wheat, while the heat signal was detected by eleven models for maize and six models for wheat. To investigate whether the difference between simulated and observed yield declines is due to a misrepresentation of simulated exposure to heat or water scarcity (i.e. misrepresentation of growing season), we analysed the relationship between average discrepancies between observed and simulated yield losses, and average simulated exposure to extreme weather conditions across all crop models. We found a positive correlation between simulated exposure to heat and model performance for heatwaves, but found no correlation for droughts. This suggests that there is a systematic underestimation of yield responses to heat and drought and not only a misrepresentation of exposure. Assuming that performance for the past indicates models' capacity to project future yield impacts, models likely underestimate future yield decline from climate change. High-quality temporally and spatially resolved observational data on growing seasons will be highly valuable to further improve crop models' capacity to adequately respond to extreme weather events.

extreme events↗
DOE OSTI2025

Rhizosphere Microbiome Diversity Potentially Supports Robust Nature of Field Pennycress ( Thlaspi arvense L.) in Dryland Cropping Systems of Eastern Washington

ABSTRACT Field pennycress ( Thlaspi arvense L.) is an annual in the Brassicaceae family and is currently being developed as an oilseed intermediate crop suitable for renewable biodiesel and jet fuel. It displays many desirable characteristics for this role including cold tolerance, a rapid life cycle, and a seed fatty acid profile conducive to bioenergy generation. These traits make field pennycress favorable for winter oilseed cultivation in the inland Pacific Northwest (iPNW). Simultaneously, intermediate crops are an increasingly recognized component of both agronomic sustainability and soil health management. Intermediate crops enhance soil microbial diversity, which benefits both soil and plant health. To understand the impact of field pennycress on soil microbial diversity, two natural accessions and seven experimental accessions were grown at three sites in Eastern Washington. Aboveground biomass and rhizosphere soil were then collected. Soil genomic DNA was extracted from rhizosphere samples and used to generate an amplicon library for bacterial (16S) and fungal (ITS) rRNA sequences. The resulting libraries were analyzed in QIIME2, which revealed that not only did the fad2 deficient line from the Spring32‐10 background have significantly increased aboveground biomass production compared to other pennycress genotypes, but also displayed significantly higher β‐diversity in the rhizosphere community specifically at the site experiencing the driest conditions. ANCOM analysis showed that multiple sequences similar to beneficial plant and soil health enhancing organisms such as Trichoderma spirale , Pseudomonas spp., and Methylobacterium goesingense were found to be enriched in the microbiome of the fad2 Spring32‐10 background also at that site. To add additional context to rhizosphere community data, root exudates from two pennycress genotypes were captured in magenta boxes and analyzed using HPLC. Future work will expand our understanding of the mechanisms by which field pennycress creates diversity in the rhizosphere, thus expanding our ability to cultivate this crop in the iPNW.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Bioenergy Cropping Reduces the Spatiotemporal Scaling of Soil Bacterial Biodiversity

Widespread bioenergy cropping can transform landscapes, strongly affecting biodiversity. However, the impact of bioenergy cropping on the spatiotemporal scaling of soil biodiversity remains virtually unknown, despite its profound implications for the functioning of the ecological community. Here, we investigated how bioenergy cropping influenced the spatiotemporal scaling of soil bacterial biodiversity in marginal soils (sandy loam and clay loam soils) in Oklahoma, USA. We detected strong, significant species-time-area relationships (STARs) and phylogenetic-time-area relationships (PTARs) in bacterial communities and their lineages, suggesting that STARs and PTARs exist in microbial ecology within the studied system. Also, spatiotemporal scaling rates (the slopes of STAR and PTAR models) varied substantially among bacterial lineages and were positively correlated with their 16S rRNA gene copy numbers, a genomic trait indicative of microbial growth potentials. Strikingly, bioenergy cropping significantly reduced spatiotemporal scaling rates by 6.8%-14.1%, with a more pronounced reduction observed in sandy loam soils, where those rates were significantly lower than in clay loam soils. The heterogeneity of soil phosphorus and carbon resulted in variations in bacterial spatiotemporal scaling rates. Collectively, our findings suggest that bioenergy cropping may alleviate rapid shifts in soil biodiversity across space and time, thereby stabilizing soil biodiversity and supporting its role as part of sustainable land management and climate mitigation strategies.

bacterial diversity↗
DOE OSTI2023

Carbon mitigation payments can reduce the riskiness of bioenergy crop production

Abstract Perennial bioenergy crops provide substantial carbon mitigation benefits but have risky returns. We couple economic analysis with a biogeochemical model (DayCent) to examine the effect of carbon mitigation payments on the spatially varying bioenergy crop returns and risk profiles relative to conventional crops across the rainfed United States. These payments increase the likelihood of positive profit in the Midwest for miscanthus and southern states for switchgrass. At low biomass prices, these payments make bioenergy crops appealing to risk‐averse farmers. At moderate biomass prices, these payments make bioenergy crops appealing to all farmers regardless of risk preference.

09 BIOMASS FUELS↗
DOE OSTI2026

Enhancing climate-smart crop performance in arid agrivoltaics systems: effects of photovoltaic shading and soil amendments on tepary bean growth, yield, and associated soil microbiome

As climate change expands the world’s arid and semiarid regions, sustainable systems that integrate food and energy production are becoming increasingly critical. Agrivoltaics—co-locating crops with photovoltaic (PV) panels—offers a dual land-use strategy that mitigates environmental stress by shading crops, conserving soil moisture, and enhancing PV efficiency. While climate-smart crops like the tepary bean ( Phaseolus acutifolius ) are well adapted to heat and drought, little is known about how these crops and their associated soil microbiomes respond to the unique microclimates created by PV shading. This study evaluated tepary bean performance and plant–microbial interactions under PV-shade vs. no shade across three soil amendment treatments at two experimental sites. We assessed plant traits including germination, phenology, biomass, height, as well as yield and bean morphology, alongside shifts in soil microbial composition and functional potential. Plants grown under PV-shade were generally taller, with extended reproductive periods and higher yields: 42% of shaded plants produced beans compared to only 8% under full sun. Shaded plants also produced rounder, higher-quality beans, whereas non-shaded plants yielded flatter, less developed beans. Microbial community composition was more strongly influenced by amendment and site conditions than by shading alone. Key microbial taxa (e.g., Glomeromycetes, Desulfobacterota ) and predicted functions (e.g., denitrification, nitrogen-respiration, sulfate reduction) were associated with differences in plant performance. Finally, combining agrivoltaic systems with targeted soil amendments can enhance crop yield and soil microbial functionality—offering a promising strategy for sustainable agriculture in arid landscapes.

14 SOLAR ENERGY↗
DOE OSTI2022

Attributing differences of solar-induced chlorophyll fluorescence (SIF)-gross primary production (GPP) relationships between two C4 crops: corn and miscanthus

There remains limited information to characterize the solar-induced chlorophyll fluorescence (SIF)-gross primary production (GPP) relationship in C4 cropping systems. The annual C4 crop corn and perennial C4 crop miscanthus differ in phenology, canopy structure and leaf physiology. Investigating the SIF-GPP relationships in these species could deepen our understanding of SIF-GPP relationships within C4 crops. Using in situ canopy SIF and GPP measurements for both species along with leaf-level measurements, we found considerable differences in the SIF-GPP relationships between corn and miscanthus, with a stronger SIF-GPP relationship and higher slope of SIF-GPP observed in corn compared to miscanthus. These differences were mainly caused by leaf physiology. For miscanthus, high non-photochemical quenching (NPQ) under high light, temperature and water vapor deficit (VPD) conditions caused a large decline of fluorescence yield (Φ F ), which further led to a SIF midday depression and weakened the SIF-GPP relationship. The larger slope in corn than miscanthus was mainly due to its higher GPP in mid-summer, largely attributed to the higher leaf photosynthesis and less NPQ. Furthermore, our results demonstrated variation of the SIF-GPP relationship within C4 crops and highlighted the importance of leaf physiology in determining canopy SIF behaviors and SIF-GPP relationships.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Observational evidence for groundwater influence on crop yields in the United States

As climate change shifts crop exposure to dry and wet extremes, a better understanding of factors governing crop response is needed. Recent studies identified shallow groundwater—groundwater within or near the crop rooting zone—as influential, yet existing evidence is largely based on theoretical crop model simulations, indirect or static groundwater data, or small-scale field studies. Here, we use observational satellite yield data and dynamic water table simulations from 1999 to 2018 to provide field-scale evidence for shallow groundwater effects on maize yields across the United States Corn Belt. We identify three lines of evidence supporting groundwater influence: 1) crop model simulations better match observed yields after improvements in groundwater representation; 2) machine learning analysis of observed yields and modeled groundwater levels reveals a subsidy zone between 1.1 and 2.5 m depths, with yield penalties at shallower depths and no effect at deeper depths; and 3) locations with groundwater typically in the subsidy zone display higher yield stability across time. We estimate an average 3.4% yield increase when groundwater levels are at optimum depth, and this effect roughly doubles in dry conditions. Groundwater yield subsidies occur ~35% of years on average across locations, with 75% of the region benefitting in at least 10% of years. Overall, we estimate that groundwater-yield interactions had a net monetary contribution of approximately $10 billion from 1999 to 2018. This study provides empirical evidence for region-wide groundwater yield impacts and further underlines the need for better quantification of groundwater levels and their dynamic responses to short- and long-term weather conditions.

60 APPLIED LIFE SCIENCES↗