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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Blue Rock CropSpanPV - Low Cost Racking for Agricultural Solar Photovoltaics

In this work, a total of four solar panel layouts, applied to Agrivoltaics, are investigated. This study presents two hypotheses: 1. Prefabrication - Lower total cost can be achieved by constructing a pre-assembled, pre-wired solar array in a factory, with automation, then rapidly deploying it in the field. 2. Tension Structures - Using tension structures in a way to suspend an overhead solar array also reduces costs when compared to conventional support methods. Designs are presented for frames to hold the panels. Configurations are advanced to connect the frames into arrays. Supports and foundations to hold the arrays in the desired layout are calculated, selected and presented. Cost models are prepared for the four layouts, which include definition of the business enterprise, the manufacturing operation, and the required facility for production at scale. Cost models include, detail material and task/labor take-offs for both manufacturing and installation. Comparisons with conventional system adapted to Agrivoltaics reveal that the two hypotheses do not hold true. A prefabricated array requires additional material that is not needed in the base system and the cost of this additional material is not outweighed by the cost savings of reduced field installation. The cost of wire rope for a tension structure does result in an economy of material, however, the cost of end connections and tensioning devices adds significantly to the cost of the overall tension structure. Foundation loads with tension structures, especially the large wind uplift seen with a fixed tilt solar array, impose significant constraints and high costs. The following conclusions are recommended for further consideration: 1. Best Case Agrivoltaic Configuration - The best value/lowest cost configuration for agrivoltaics is the installation of solar panels mounted on a single axis tracker in either a 2-in-portrait or 2-in landscape arrangement. This is useful for grazing lands and for staple crops which require high light levels. These applications represent the vast majority of the potential agrivoltaic market. Important elements in this configuration are the specific geometric layout coordinated with the various field operations and a control system linked between the farm equipment and single axis tracker. The control system is to monitor location and orientation, then actively tilt the solar panels or brake the field equipment to provide clearance and avoid collisions. 2. Long Span Applications - The use of tension structures for an overhead fixed tilt array is beneficial where long spans are a necessity, especially where the base support in the project location has consolidated rock near the surface or some other solid structure. One application is spanning wide irrigation canals. Another may be as an installation at the top deck of parking structures. 3. Direct Ground Mount Configuration – Having skids at the base of a pre-fabricated array that extend when the array is deployed, could be a successful design. This could be a useful strategy for dense, flat, ground-mount configurations like that employed by a couple of successful commercial operations (5G Maverick and Erthos). Arrays would be orientated north and south, deployed very low on prepared grade. Arrays would be aligned closely next to each other and anchored with small ground screws or simply with ballast. This same product arrangement could be very useful for rapid deployment and set-up of solar arrays for temporary deployments, disaster response and the military operations

14 SOLAR ENERGY↗
NASA NTRS1981

Applications systems verification and transfer project. Volume 7: Cost/benefit analysis for the ASVT on operational applications of satellite snow-cover observations

The results of the OASSO ASVT's were used to estimate the benefits accruing from the added information available from satellite snowcover area measurement. Estimates of the improvement in runoff prediction due to addition of SATSCAM were made by the Colorado ASVT personnel. The improvement estimate is 6-10%. Data were applied to subregions covering the Western States snow area amended by information from the ASVT and other watershed experts to exclude areas which are not impacted by snowmelt runoff. Benefit models were developed for irrigation and hydroenergy uses. The benefit/cost ratio is 72:1. Since only two major benefit contributors were used and since the forecast improvement estimate does not take into account future satellite capabilities these estimates are considered to be conservative. The large magnitude of the benefit/cost ratio supports the utility and applicability of SATSCAM.

Castruccio, P.↗
DOE OSTI2025

Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1

Abstract. Groundwater plays a key role in meeting water demands, supplying over 40 % of irrigation water globally, with this role likely to grow as water demands and surface water variability increase. A better understanding of the future role of groundwater in meeting sectoral demands requires an integrated hydro-economic evaluation of its cost and availability. Yet substantial gaps remain in our knowledge and modeling capabilities related to groundwater availability, recharge, feasible locations for extraction, extractable volumes, and associated extraction costs, which are essential for large-scale analyses of integrated human–water system scenarios, particularly at the global scale. To address these needs, we developed Superwell, a physics-based groundwater extraction and cost accounting model that operates at sub-annual temporal and at the coarsest 0.5° (≈50 km × 50 km) gridded spatial resolution with global coverage. The model produces location-specific groundwater supply–cost curves that provide the levelized cost to access different quantities of available groundwater. The inputs to Superwell include recent high-resolution hydrogeologic datasets of permeability, porosity, aquifer thickness, depth to water table, recharge, and hydrogeological complexity zones. It also accounts for well capital and maintenance costs, as well as the energy costs required to lift water to the surface. The model employs a Theis-based scheme coupled with an amortization-based cost accounting formulation to simulate groundwater extraction and quantify the cost of groundwater pumping. The result is a spatiotemporally flexible, physically realistic, economics-based model that produces groundwater supply–cost curves. We show examples of these supply–cost curves and the insights that can be derived from them across a set of scenarios designed to explore model outcomes. The supply–cost curves produced by the model show that most (90 %) nonrenewable groundwater in storage globally is extractable at costs lower than USD 0.57 m−3, while half of the volume remains extractable at under USD 0.108 m−3. The global unit cost is estimated to range from a minimum of USD 0.004 m−3 to a maximum of USD 3.971 m−3. We also demonstrate and discuss examples of how these cost curves could be used by linking Superwell's outputs with other models to explore coupled human–environmental system challenges, such as water resources planning and management, or broader analyses of multisectoral feedbacks.

Global Change Analysis Model (GCAM)↗
NASA NTRS1992

Estimating high mosquito-producing rice fields using spectral and spatial data

The cultivation of irrigated rice provides ideal larval habitat for a number of anopheline vectors of malaria throughout the world. Anopheles freeborni, a potential vector of human malaria, is associated with the nearly 240,000 hectares of irrigated rice grown annually in Northern and Central California; therefore, this species can serve as a model for the study of rice field anopheline population dynamics. Analysis of field data revealed that rice fields with early season canopy development, that are located near bloodmeal sources (i.e., pastures with livestock) were more likely to produce anopheline larvae than fields with less developed canopies located further from pastures. Remote sensing reflectance measurements of early-season canopy development and geographic information system (GIS) measurements of distanes between rice fields and pastures with livestock were combined to distinguish between high and low mosquito-producing rice fields. Using spectral and distance measures in either a discriminant or Bayesian analysis, the identification of high mosquito-producing fields was made with 85 percent accuracy nearly two months before anopheline larval populations peaked. Since omission errors were also minimized by these approaches, they could provide a new basis for directing abatement techniques for the control of malaria vectors.

Wood, B. L.↗
DOE OSTI2024

Editorial: Water supply sustainability and challenges in Asian megadeltas under global change

Globally, riverine deltas comprise barely 1% of land area, but they support the livelihoods of more than 500 million people (Moorhouse et al., 2021). The Asian megadeltas (e.g., Indus, Bengal, Mekong, Red River, and Yangtze) and their riverine floodplains are the most dynamic economic and environmental systems in the world. These low-lying coastal landforms support surface water bodies and highly productive aquifer systems. However, water resources of the Asian megadeltas are extremely vulnerable to geogenic (e.g., arsenic) and anthropogenic (e.g., bacteria) contamination, increased water salinisation from rising sea levels (Figure 1), and chemicals (e.g., fertilizers, pesticides) from land-use practices (Mukherjee et al., 2024) – all of which are threatening the sustainability of water supply and food security in the region. This Research Topic collection features five original articles that explore water chemistry including arsenic and bacteriological contamination, water salinisation, water-energy-food nexus in irrigated agriculture, and groundwater depletion resulting from irrigation, rapid urbanization, and climate change. Although the Research Topic collection does not include case studies from all the Asian Megadeltas shown in Figure 1, the relevance of multi-hazard driven water risks to all deltaic and river floodplain environments around the world is well-illustrated.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

Cropland mapping; cropland areas; 30-m; Landsat-8;↗
DOE OSTI2024

Representing cropping systems with the MEMS 2 ecosystem model

Abstract Croplands have been the focus of substantial investigation due to their considerable potential for sequestering carbon. Understanding the potential for soil organic carbon (SOC) sequestration and necessary management strategies will be enabled with accurate process‐based models. Accurately representing crop growth and agricultural practices will be critical for realistic SOC modeling. The MEMS 2 model incorporates a current understanding of SOC formation and stabilization, measurable SOC pools, and deep SOC dynamics and is seen as a highly promising tool to inform management intervention for SOC sequestration. Thus far, MEMS 2 has been developed to represent grasslands. In this study, we further developed MEMS 2 to model annual grain crops and common agricultural practices, such as irrigation, fertilization, harvesting, and tillage. Using four Ameriflux sites, we demonstrated an accurate simulation of crop growth and development. Model performance was strong for simulating aboveground biomass (index of agreement [d] range of 0.89–0.98) and green leaf area index (dfrom 0.90 to 0.96) across corn, soybean, and winter wheat. Good agreement with observations was also achieved for net ecosystem CO 2 exchange (dfrom 0.90 to 0.96), evapotranspiration (dfrom 0.91 to 0.94), and soil temperature (dof 0.96), while discrepancy with the available soil water content data remain (dfrom 0.14 to 0.81 at four depths to 100 cm). While we will continue model testing and improvement, MEMS 2 (version 2.14) has now demonstrated its ability to effectively simulate the growth of common grain crops and practices.

Agriculture↗
NASA NTRS2020

CMIP6 Historical Simulations (1850‐2014) with GISS‐E2.1

Simulations of the CMIP6 historical period 1850‐‐2014, characterized by the emergence of anthropogenic climate drivers like greenhouse gases, are presented for different configurations of the NASA Goddard Institute for Space Studies (GISS) Earth System ModelE2.1. The GISS‐E2.1 ensembles are more sensitive to forcing than their CMIP5 predecessors (GISS‐E2), but warm less during recent decades due to reduced total forcing. This forcing reduction is attributed to an increase in longwave opacity in pre‐industrial simulations, resulting in an atmosphere less sensitive to further increases in opacity that result from rising greenhouse gas concentrations. This demonstrates the importance of the base climatology to forcing and forced climate trends. Most model versions match observed temperature trends since 1979 from the ocean to the stratosphere. The choice of ocean model is important to the transient climate response, as found in CMIP5 GISS‐E2: the model that more efficiently exports heat to the deep ocean shows a smaller rise in tropospheric temperature. Model sea level rise over the historical period is traced to excessive drawdown of aquifers to meet irrigation demand with a smaller contribution from thermal expansion. This shows how fully coupled models can provide indirect observational constraints upon forcing, in this case, constraining irrigation rates with observed sea level changes. The overall agreement of GISS‐E2.1 with observed trends is familiar from evaluation of its predecessors, as is the conclusion that these trends are almost entirely anthropogenic in origin.

NASA Goddard Institute for Space Studies (GISS) Ea↗
NASA NTRS1990

An image recorded by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

The airborne visible/infrared imaging spectrometer (AVIRIS) is described, and an example of a false-color image recorded by this device is provided. The AVIRIS is capable of sensing in 209 visible and near-infrared wavebands with an 11km swath and a 20m spatial resolution. Evaluation flights for AVIRIS were made at an altitude of approximately 20km x 10.2km of low-lying and relatively flat irrigated land near Yuba City and Sacramento, California. Raw data were converted from digital numbers to radiance and radiometrically corrected at the NASA Jet Propulsion Laboratory. Notch filtering in the frequency domain of the image was used to remove periodic noise. The illustration of both spatial and spectral properties on the false-color image are explained. AVIRIS is designed to be flown in an ER-2 aircraft and will serve as a test-bed sensor for the High-Resolution Imaging Spectrometer (HIRIS) planned for the Earth Observing System.

Curran, Paul J.↗
DOE OSTI2024

Vadose zone flushing of fertilizer tracked by isotopes of water and nitrate

Abstract A substantial fraction of nitrogen (N) fertilizer applied in agricultural systems is not incorporated into crops and moves below the rooting zone as nitrate (NO 3 − ). Understanding mechanisms for soil N retention below the rooting zone and leaching to groundwater is essential for our ability to track the fate of added N. We used dual stable isotopes of nitrate (δ 15 N–NO 3 − and δ 18 O–NO 3 − ) and water (δ 18 O–H 2 O and δ 2 H–H 2 O) to understand the mechanisms driving nitrate leaching at three depths (0.8, 1.5, and 3.0 m) of an irrigated corn field sampled every 2 weeks from 2016 to 2020 in the southern Willamette Valley, Oregon, USA. Distinct periods of high nitrate concentrations with lower δ 15 N–NO 3 − values indicated that a portion of that nitrate was from recent fertilizer applications. We used a mixing model to quantify nitrate fluxes associated with recently added fertilizer N versus older, legacy soil N during these “fertilizer signal periods.” Nitrate leached below 3.0 m in these periods made up a larger proportion of the total N leached at that depth (∼52%) versus the two shallower depths (∼13%–16%), indicating preferential movement of recently applied fertilizer N through the deep soil into groundwater. Further, N associated with recent fertilizer additions leached more easily when compared to remobilized legacy N. A high volume of fall and winter precipitation may push residual fertilizer N to depth, potentially posing a larger threat to groundwater than legacy N. Optimizing fertilizer N additions could minimize fertilizer losses and reduce nitrate leaching to groundwater.

Agriculture↗
NASA NTRS2005

Evidence of Urban-Induced Precipitation Variability in Arid Climate Regimes

Water is essential to life in the Earth system. The water cycle components that sustain life are becoming more scarce and polluted. The most recent (1999-2004) drought experienced in the southwestern United States is the seventh worst in the approximately 500-year proxy tree-ring record. As a result, many regions contemplated drought emergencies in which severe water restrictions are implemented. Though larger weather and climate processes likely control drought processes, there is increasing evidence that anthropogenic or human-related activities can significantly alter precipitation processes. Urbanization is an example of anthropogenic forcing. Recent studies continue to provide evidence that urban environments can modify or induce precipitation under a specific set of conditions. Arid and semi-arid regions of the southwestern United States and other parts of the world are rapidly developing and placing greater demands on the environmental system. In the past fifty years, Phoenix has expanded from a predominantly agricultural center to an urbanized region with extent 700 percent larger than its size in the middle of the twentieth century. Riyadh's population grew from about a half million people in 1972 to almost two million by 2000. Saudi Arabia experienced urbanization later than many other countries; in the early 1970s its urban-rural ratio was still about 1:3. By 1990 the ratio had reversed to about 3:l. In the mid-1970s Riyadh's population was increasing by about 10 percent a year. Irrigation also significantly increased between 1972 and 1990 southeast of Riyadh. The study employs a 108-year precipitation historical data record, global climate observing network observations and satellite data to identify possible anomalies in rainfall in and around two major arid urban areas, Phoenix, Arizona and Riyadh, Saudi Arabia. It provides statistically sound evidence that rainfall distribution and magnitude is statistically different in post-urban than in pre-urban (1900-1950) Phoenix. The study hypothesis that a complex interaction between the city landscape, irrigated lands, and nearby mountains have created preferred regions for rainfall development. The study also provides early evidence that rapidly urbanizing parts of the arid Middle East may also be experiencing different precipitation regimes in response to urbanization and irrigation.

Shepherd, J. Marshall↗
NASA NTRS2011

NASA Water Resources Program

With increasing population pressure and water usage coupled with climate variability and change, water issues are being reported by numerous groups as the most critical environmental problems facing us in the 21st century. Competitive uses and the prevalence of river basins and aquifers that extend across boundaries engender political tensions between communities, stakeholders and countries. In addition to the numerous water availability issues, water quality related problems are seriously affecting human health and our environment. The potential crises and conflicts especially arise when water is competed among multiple uses. For example, urban areas, environmental and recreational uses, agriculture, and energy production compete for scarce resources, not only in the Western U.S. but throughout much of the U.S. and also in numerous parts of the world. Mitigating these conflicts and meeting water demands and needs requires using existing water resources more efficiently. The NASA Water Resources Program Element works to use NASA products and technology to address these critical water issues. The primary goal of the Water Resources is to facilitate application of NASA Earth science products as a routine use in integrated water resources management for the sustainable use of water. This also includes the extreme events of drought and floods and the adaptation to the impacts from climate change. NASA satellite and Earth system observations of water and related data provide a huge volume of valuable data in both near-real-time and extended back nearly 50 years about the Earth's land surface conditions such as precipitation, snow, soil moisture, water levels, land cover type, vegetation type, and health. NASA Water Resources Program works closely to use NASA and Earth science data with other U.S. government agencies, universities, and non-profit and private sector organizations both domestically and internationally. The NASA Water Resources Program organizes its projects under five functional themes. I) Streamflow and Flood Forecasting 2) Water Supply and Irrigation (includes evapotranspiration) 3) Drought 4) Water Quality 5) Climate and Water Resources. To maximize this activity NASA Water Resources Program works closely with other government agencies (e.g., the National Oceanic and Atmospheric Administration (NOAA); the U.S. Department of Agriculture (USDA); the U.S. Geological Survey (USGS); the Environmental Protection Agency (EPA), USAID, the Air Force Weather Agency (AFWA)), universities, non-profit national and international organizations, and the private sector. The NASA Water Resources program currently is funding 21 active projects under the functional themes (http://wmp.gsfc.nasa.gov & http://science.nasa.gov/earth-science/applied-sciences/).

Toll, David L.↗
DOE OSTI2022

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↗
NASA NTRS2008

Ongoing Development of NASA's Global Land Data Assimilation System

NASA's Global Land Data Assimilation System (GLDAS) produces global fields of land surface states (e.g., soil moisture and temperature) and fluxes (e.g., latent heat flux and runoff) by driving offline land surface models with observation-based inputs, using the Land Information System (LIS) software. Since production began in 2001, GLDAS has supported more than 100 scientific investigations and applications. Some examples are GEWEX and NASA Energy and Water Cycle Study (NEWS) global water and energy budget analyses, interpretations of hydrologic data derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and forecast model initiation studies at NOAA and NASA. At the same time, the GLDAS team has continued improve results through the development of new modeling and data assimilation techniques. Here we describe several recent and ongoing innovations. These include global implementation of a runoff routing procedure, GRACE data assimilation, advanced snow cover assimilation, and irrigation modeling.

Rodell, Matthew↗
NASA NTRS1982

The feasibility of thermal inertia mapping for detection of perched water tables in semi-arid irrigated lands

The thermal inertia mapping remote sensing technique is evaluated as a potential method for delineating areas of shallow perched water tables and related salinization problems on a regional basis. This method for detecting shallow water tables is based on the existence of significant differences in soil thermal properties between wet and dry soil profiles. Ground observations were conducted at two different test sites in California along the flight line, with one site located in a perched water table area and the other site in a well drained area. Measurements were taken hourly during a four day period (two days before and two days after the flight) for variables such as radiometric, meteorologic, soil moisture and temperature profiles, and surface characteristics. Results indicate that it is not feasible using present apparent thermal inertia remote sensing techniques to reliably delineate regional patterns of very shallow water tables due to the complex environmental system. However, some features within specific fields which may be directly related to the local presence of shallow water tables, such as differences in evaporative cooling due to soil moisture effects between and within fields, can be detected using the thermal inertia technique.

Ezra, C. E.↗
DOE OSTI2021

Understanding Multilevel Selection May Facilitate Management of Arbuscular Mycorrhizae in Sustainable Agroecosystems

Studies in natural ecosystems show that adaptation of arbuscular mycorrhizal (AM) fungi and other microbial plant symbionts to local environmental conditions can help ameliorate stress and optimize plant fitness. This local adaptation arises from the process of multilevel selection, which is the simultaneous selection of a hierarchy of groups. Studies of multilevel selection in natural ecosystems may inform the creation of sustainable agroecosystems through developing strategies to effectively manage crop microbiomes including AM symbioses. Field experiments show that the species composition of AM fungal communities varies across environmental gradients, and that the biomass of AM fungi and their benefits for plants generally diminish when fertilization and irrigation eliminate nutrient and water limitations. Furthermore, pathogen protection by mycorrhizas is only important in environments prone to plant damage due to pathogens. Consequently, certain agricultural practices may inadvertently select for less beneficial root symbioses because the conventional agricultural practices of fertilization, irrigation, and use of pesticides can make these symbioses superfluous for optimizing crop performance. The purpose of this paper is to examine how multilevel selection influences the flow of matter, energy, and genetic information through mycorrhizal microbiomes in natural and agricultural ecosystems, and propose testable hypotheses about how mycorrhizae may be actively managed to increase agricultural sustainability.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2020

Central Valley Water Resources: Improving California Groundwater Assessments using GRACE and InSAR Datasets for Water Resource Management

California’s Central Valley is one of the most productive agricultural areas in the world, producing approximately $20 billion in crops annually. The recent California droughts of 2007-2010 and 2012-2019 resulted in increased groundwater pumping in the Central Valley to adequately irrigate farmland. Overdrafting of the Central Valley aquifer results in groundwater depletion, land subsidence, and permanent loss of groundwater storage. In 2014, depletion of groundwater led the state of California to enact the Sustainable Groundwater Management Act (SGMA),requiring critically overdrafted, high, and medium priority sub-basins to reach sustainable levels of groundwater pumping and recharge by 2042. SGMA allows local Groundwater Sustainability Agencies (GSAs) the authority to create Groundwater Sustainability Plans (GSPs) at the sub-basin level. To assist California’s Department of Water Resources (DWR), this project quantified groundwater change and land subsidence in Central Valley sub-basins with sparse or unreliable well and Geographic Positioning Systems (GPS) data. This was done using NASA’s Gravity Recovery and Climate Experiment (GRACE), GRACE FollowOn (GRACE-FO), and interferograms derived from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) and Advanced Land Observing Satellite 2 (ALOS-2)Phased Array L-band Synthetic Aperture Radar 2 (PALSAR-2). Time series of the GRACE and InSAR data were compared with well and GPS data in data-dense sub-basins to determine the feasibility of these datasets for groundwater storage and subsidence monitoring. We found that GRACE and InSAR data are effective tools for determining groundwater change and land subsidence and can be used on their own to monitor sub-basins in the absence of well and GPS data

Water Resources↗
NASA NTRS2021

A High-Resolution Land Data Assimilation System Optimized for the Western United States

The Western Land Data Assimilation System (WLDAS) is a custom instance of the NASA Land Information System that combines land surface parameters, meteorological forcing data, and satellite products within a land surface model to produce daily estimates of the water and energy budget variables for the western United States. WLDAS was configured through discussions with partners, with the goal of groundwater sustainability planning for the state of California in mind. The publicly available output dataset has a 1-km grid resolution and spans 1979–present, which makes it suitable for water resources assessments. The data are also able to contextualize the recent drought events in California. Assimilation of Leaf Area Index, which is demonstrated herein to improve simulation over agricultural areas in California, specifically in terms of evapotranspiration in irrigation regions, will be included along with other data assimilation in subsequent releases of WLDAS.

land surface modeling↗