SEARCH · Engineering Papers

Results for “root productivity”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Improved Peatland Hydrology and L-Band Microwave Radiative Transfer Modeling in Version 7 of the SMAP Level-4 Soil Moisture Data Assimilation Product

The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides global, 9-km resolution, 3-hourly surface (0-5 cm) and root-zone (0-100 cm) soil moisture from April 2015 to present with a mean latency of 2.5 days from the time of observation. The L4_SM estimates are derived from the assimilation of SMAP L-band (1.4 GHz) brightness temperature (Tb) observations into the NASA Catchment land surface model. The recently released Version 7 of L4_SM comprises two key advances. First, the Catchment model now includes the recently developed PEATCLSM hydrology module for peatlands and uses an updated global map of peatlands. Second, revised parameters are used in the L-band radiative transfer model that converts the simulated soil moisture and temperature estimates into Tb predictions for use in the radiance-based L4_SM analysis. Specifically, the L-band scattering albedo, soil roughness, and vegetation opacity climatology are obtained from the SMAP Level-2 dual-channel soil moisture retrieval product. In this presentation, we examine the improvements gained with the model and parameter changes. In peatlands, the dynamics of water table depth, surface soil moisture and evapotranspiration are considerably improved in L4_SM Version 7 over Version 6 when evaluated against in situ measurements. These improvements are also manifested in smaller Tb observation-minus-forecast residuals.

SMAP↗

NASA NTRS1988

Early wrong-way response occurs in orthogravitropism of maize roots treated with lithium

Application of lithium ions to tips of roots of Zea mays L. cv. Silver Queen shifts the direction of initial orthogravitropic curvature from downward to upward. The production of this putatively incidental perturbation of orthogravitropic bending kinetics by a pharmacological agent might provide insight into both ortho- and plagiogravitropism. Additionally, the protocol of the experiments bears on recent claims that mucilage external to the root cap plays an essential role in gravitropism. External mucilage was removed before roots were stimulated, yet they reached about 50 degrees gravitropic curvature in an hour.

Non-NASA Center↗

NASA NTRS1985

Liquid fuel spray processes in high-pressure gas flow

Atomization of single liquid jets injected downstream in high pressure and high velocity airflow was investigated to determine the effect of airstream pressure on mean drop size as measured with a scanning radiometer. For aerodynamic - wave breakup of liquid jets, the ratio of orifice diameter D sub o to measured mean drop diameter D sub m which is assumed equal to D sub 32 or Sauter mean diameter, was correlated with the product of the Weber and Reynolds numbers WeRe and the dimensionless group G1/square root of c, where G is the gravitational acceleration, 1 the mean free molecular path, and square root of C the root mean square velocity, as follows; D sub o/D sub 32 = 1.2 (WeRe) to the 0.4 (G1/square root of c) to the 0.15 for values of WeRe 1 million and an airstream pressure range of 0.10 to 2.10 MPa.

Ingebo, R. D.↗

NASA NTRS1986

Liquid fuel spray processes in high-pressure gas flow

Ingebo, R. D.↗

NASA NTRS1994

Completing below-ground carbon budgets for pastures, recovering forests, and mature forests of Amazonia

The objective of this grant was to complete below-ground carbon budgets for pastures and forest soils in the Amazon. Profiles of radon and carbon dioxide were used to estimate depth distribution of CO2 production in soil. This information is necessary for determining the importance of deep roots as sources of carbon inputs. Samples were collected for measuring root biomass from new research sites at Santana de Araguaia and Trombetas. Soil gases will be analyzed for CO2 and (14)CO2, and soil organic matter will be analyzed for C-14. Estimates of soil texture from the RADAMBRASIL database were merged with climate data to calculate soil water extraction by forest canopies during the dry season. In addition, a preliminary map of areas where deep roots are needed for deep soil water was produced. A list of manuscripts and papers prepared during the reporting periods is given.

Davidson, Eric A.↗

NASA NTRS1998

Protocol Development for the NASA-JSC Lunar-Mars Life Support Test Project (LMLSTP) Phase 3 Project: A Report on Baseline Studies at KSC for Continuous Salad Production

The Phase 3 Lunar-Mars Life Support Test Project (LMLSTP) was conducted in a 20-foot chamber at Johnson Space Center. The overall objective of the Phase 3 project was to conduct a 90-day regenerative life support system test involving 4 human subjects to demonstrate an integrated biological and physicochemical life support system. A secondary objective of the Phase 3 LMLSTP was to demonstrate the ability to produce salad-type vegetable by integration of a small benchtop growth chamber located within the crew habitat area. This small chamber, commercially manufactured as the Controlled Environment Research Ecosystem (CERES 2010(TM)), functioned as a means to continuously provide fresh lettuce crops for crew members. The CERES 2010(TM) growth chamber utilized hardware components developed for effective plant biomass production in spaceflight applications. These components included: (1) LED lighting; (2) Astroculture(TM) Root Trays; and (3) Zeoponic media. In planning for the LMLSTP Phase 3, a request was put forward for KSC scientists to generate a protocol for successful continuous planting, culturing, and harvesting of the salad-crop, lettuce. By conducting baseline tests with components of the CERES 2010(TM), a protocol was developed.

Goins, G. D.↗

NASA NTRS2018

The NASA Eulerian Snow on Sea Ice Model (NESOSIM) v1.0: initial model development and analysis

The NASA Eulerian Snow On Sea Ice Model (NESOSIM) is a new, open-source snow budget model that is currentlyconfigured to produce daily estimates of the depth and density of snow on sea ice across the Arctic Ocean throughthe accumulation season. NESOSIM has been developed in a three-dimensional Eulerian framework and includes two(vertical) snow layers and several simple parameterizations (accumulation, wind packing, advection_divergence, blowingsnow lost to leads) to represent key sources and sinks of snow on sea ice. The model is forced with daily inputs of snowfall and near-surface winds (from reanalyses), sea ice concentration (from satellite passive microwave data) and sea ice drift (from satellite feature tracking) during the accumulation season (August through April). In this study, we present the NESOSIM formulation, calibration efforts, sensitivity studies and validation efforts across an Arctic Ocean domain (100 km horizontal resolution). The simulated snow depth and density are calibrated with in situ data collected on drifting ice stations during the 1980s. NESOSIM shows strong agreement with the in situ seasonal cycles of snow depth and density, and shows good (moderate) agreement with the regional snow depth (density) distributions. NESOSIM is run for a contemporary period (2000 to 2015), with the results showing strong sensitivity to the reanalysis derived snowfall forcing data, with the Modern-Era Retrospective analysis for Research and Applications (MERRA) and the Japanese Meteorological Agency 55-year reanalysis (JRA-55) forced snow depths generally higher than ERA-Interim,and the Arctic System Reanalysis (ASR) generally lower. We also generate and force NESOSIM with a consensus "median" daily snowfall dataset from these reanalyses.The results are compared against snow depth estimates derived from NASA's Operation IceBridge (OIB) snow radar data from 2009 to 2015, showing moderate_strong correlations and root mean squared errors of 10 cm depending on the OIB snow depth product analyzed, similar to the comparisons between OIB snow depths and the commonly used modified Warren snow depth climatology. Potential improvements to this initial NESOSIM formulation are discussed in the hopes of improving the accuracy and reliability of these simulated snow depths and densities.

Petty, Alek A.↗

DOE OSTI2022

Modeling Global Carbon Costs of Plant Nitrogen and Phosphorus Acquisition

Abstract Most Earth system models (ESMs) do not explicitly represent the carbon (C) costs of plant nutrient acquisition, which leads to uncertainty in predictions of the current and future constraints to the land C sink. We integrate a plant productivity‐optimizing nitrogen (N) and phosphorus (P) acquisition model (fixation & uptake of nutrients, FUN) into the energy exascale Earth system (E3SM) land model (ELM). Global plant N and P uptake are dynamically simulated by ELM‐FUN based on the C costs of nutrient acquisition from mycorrhizae, direct root uptake, retranslocation from senescing leaves, and biological N fixation. We benchmarked ELM‐FUN with three classes of products: ILAMB, a remotely sensed nutrient limitation product, and CMIP6 models; we found significant improvements in C cycle variables, although the lack of more observed nutrient data prevents a comprehensive level of benchmarking. Overall, we found N and P co‐limitation for 80% of land area, with the remaining 20% being either predominantly N or P limited. Globally, the new model predicts that plants invested 4.1 Pg C yr −1 to acquire 841.8 Tg N yr −1 and 48.1 Tg P yr −1 (1994–2005), leading to significant downregulation of global net primary production (NPP). Global NPP is reduced by 20% with C costs of N and 50% with C costs of NP. Modeled and observed nutrient limitation agreement increases when N and P are considered together ( r 2 from 0.73 to 0.83).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2005

Inflatable Aeroponic System

Aeroponics Internationals (AI) innovation is a self-contained, self-supporting, flexible low mass aeroponic crop production unit with integral environmental systems for the control and delivery of a nutrient mist to the roots. This FLEX Aeroponic System model was developed for commercialization as a result of the NASA SBIR Phase I contract for the research and development of a low-mass, Inflatable Aeroponic System (IAS) for producing pesticide-free lettuces, grains, peppers, tomatoes and other vegetables. The innovation addresses the needs of water and nutrient delivery systems technologies for food production in space. The inflatable nature of the innovation makes it lightweight, allowing it to be deflated so it takes up less volume during transportation and storage. It improves upon AI's current aeroponic system design that uses more rigid structures and takes advantage of vertical inclines to increase bio-mass production by over 600%.

Pelt, Jennifer Van↗

NASA NTRS1996

Methodology for Physics and Engineering of Reliable Products

Physics of failure approaches have gained wide spread acceptance within the electronic reliability community. These methodologies involve identifying root cause failure mechanisms, developing associated models, and utilizing these models to inprove time to market, lower development and build costs and higher reliability. The methodology outlined herein sets forth a process, based on integration of both physics and engineering principles, for achieving the same goals.

failure analysis electronics reliability PACT (pre↗

DOE OSTI2023

Regional biogeography versus intra-annual dynamics of the root and soil microbiome

Abstract Background Root and soil microbial communities constitute the below-ground plant microbiome, are drivers of nutrient cycling, and affect plant productivity. However, our understanding of their spatiotemporal patterns is confounded by exogenous factors that covary spatially, such as changes in host plant species, climate, and edaphic factors. These spatiotemporal patterns likely differ across microbiome domains (bacteria and fungi) and niches (root vs. soil). Results To capture spatial patterns at a regional scale, we sampled the below-ground microbiome of switchgrass monocultures of five sites spanning > 3 degrees of latitude within the Great Lakes region. To capture temporal patterns, we sampled the below-ground microbiome across the growing season within a single site. We compared the strength of spatiotemporal factors to nitrogen addition determining the major drivers in our perennial cropping system. All microbial communities were most strongly structured by sampling site, though collection date also had strong effects; in contrast, nitrogen addition had little to no effect on communities. Though all microbial communities were found to have significant spatiotemporal patterns, sampling site and collection date better explained bacterial than fungal community structure, which appeared more defined by stochastic processes. Root communities, especially bacterial, were more temporally structured than soil communities which were more spatially structured, both across and within sampling sites. Finally, we characterized a core set of taxa in the switchgrass microbiome that persists across space and time. These core taxa represented < 6% of total species richness but > 27% of relative abundance, with potential nitrogen fixing bacteria and fungal mutualists dominating the root community and saprotrophs dominating the soil community. Conclusions Our results highlight the dynamic variability of plant microbiome composition and assembly across space and time, even within a single variety of a plant species. Root and soil fungal community compositions appeared spatiotemporally paired, while root and soil bacterial communities showed a temporal lag in compositional similarity suggesting active recruitment of soil bacteria into the root niche throughout the growing season. A better understanding of the drivers of these differential responses to space and time may improve our ability to predict microbial community structure and function under novel conditions.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2017

Version 3 of the SMAP Level 4 Soil Moisture Product

The NASA Soil Moisture Active Passive (SMAP) Level 4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root zone (0-100 cm) soil moisture as well as related land surface states and fluxes from 31 March 2015 to present with a latency of 2.5 days. The ensemble-based L4_SM algorithm is a variant of the Goddard Earth Observing System version 5 (GEOS-5) land data assimilation system and ingests SMAP L-band (1.4 GHz) Level 1 brightness temperature observations into the Catchment land surface model. The soil moisture analysis is non-local (spatially distributed), performs downscaling from the 36-km resolution of the observations to that of the model, and respects the relative uncertainties of the modeled and observed brightness temperatures. Prior to assimilation, a climatological rescaling is applied to the assimilated brightness temperatures using a 6 year record of SMOS observations. A new feature in Version 3 of the L4_SM data product is the use of 2 years of SMAP observations for rescaling where SMOS observations are not available because of radio frequency interference, which expands the impact of SMAP observations on the L4_SM estimates into large regions of northern Africa and Asia. This presentation investigates the performance and data assimilation diagnostics of the Version 3 L4_SM data product. The L4_SM soil moisture estimates meet the 0.04 m3m3 (unbiased) RMSE requirement. We further demonstrate that there is little bias in the soil moisture analysis. Finally, we illustrate where the assimilation system overestimates or underestimates the actual errors in the system.

GEOS-↗

NASA NTRS2021

Extensive Characterization of Aerosol Optical Properties and Chemical Component Concentrations: Application of the GRASP/Component Approach to Long-term AERONET Measurements

A recently developed GRASP/Component approach (GRASP: Generalized Retrieval of Atmosphere and Surface Properties) was applied to AERONET (Aeronet Robotic Network) sun photometer measurements in this study. Unlike traditional aerosol component retrieval, this approach allows the inference of some information about aerosol composition directly from measured radiance, rather than indirectly through the inversion of optical parameters, and has been integrated into the GRASP algorithm. The newly developed GRASP/Component approach was applied to 13 AERONET sites for different aerosol types under the assumption of aerosol internal mixing rules to analyze the characteristics of aerosol components and their distribution patterns. The results indicate that the retrievals can characterize well the spatial and temporal variability of the component concentration for different aerosol types. A reasonable agreement between GRASP BC retrievals and MERRA-2 BC products is found for all different aerosol types. In addition, the relationships between aerosol component content and aerosol optical parameters such as aerosol optical depth (AOD), fine-mode fraction (FMF), absorption Ångström exponent (AAE), scattering Ångström exponent (SAE), and single scattering albedo (SSA) are also analyzed for indirect verifying the reliability of the component retrieval. It was demonstrated the GRASP/Component optical retrievals are in good agreement with AERONET standard products [e.g., correlation coefficient (R) of 0.93–1.0 for AOD, fine-mode AOD (AODF), coarse-mode AOD (AODC) and Ångström exponent (AE); R = ~ 0.8 for absorption AOD (AAOD) and SSA; RMSE (root mean square error) < 0.03 for AOD, AODF, AODC, AAOD and SSA]. Thus, it is demonstrated the GRASP/Component approach can provide aerosol optical products with comparable accuracy as the AERONET standard products from the ground-based sun photometer measurements as well as some additional important inside on aerosol composition.

Xindan Zhang↗

DOE OSTI2022

Soil resistance and recovery during neotropical forest succession

The recovery of soil conditions is crucial for successful ecosystem restoration and, hence, for achieving the goals of the UN Decade on Ecosystem Restoration. Here, we assess how soils resist forest conversion and agricultural land use, and how soils recover during subsequent tropical forest succession on abandoned agricultural fields. Our overarching question is how soil resistance and recovery depend on local conditions such as climate, soil type and land-use history. For 300 plots in 21 sites across the Neotropics, we used a chronosequence approach in which we sampled soils from two depths in old-growth forests, agricultural fields (i.e. crop fields and pastures), and secondary forests that differ in age (1–95 years) since abandonment. We measured six soil properties using a standardized sampling design and laboratory analyses. Soil resistance strongly depended on local conditions. Croplands and sites on high-activity clay (i.e. high fertility) show strong increases in bulk density and decreases in pH, carbon (C) and nitrogen (N) during deforestation and subsequent agricultural use. Resistance is lower in such sites probably because of a sharp decline in fine root biomass in croplands in the upper soil layers, and a decline in litter input from formerly productive old-growth forest (on high-activity clays). Soil recovery also strongly depended on local conditions. During forest succession, high-activity clays and croplands decreased most strongly in bulk density and increased in C and N, possibly because of strongly compacted soils with low C and N after cropland abandonment, and because of rapid vegetation recovery in high-activity clays leading to greater fine root growth and litter input. Furthermore, sites at low precipitation decreased in pH, whereas sites at high precipitation increased in N and decreased in C : N ratio. Extractable phosphorus (P) did not recover during succession, suggesting increased P limitation as forests age. These results indicate that no single solution exists for effective soil restoration and that local site conditions should determine the restoration strategies.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2019

Evaluating the Uncertainty of Terrestrial Water Budget Components over High Mountain Asia

This study explores the uncertainties in terrestrial water budget estimation over High Mountain Asia (HMA) using a suite of uncoupled land surface model (LSM) simulations. The uncertainty in the water balance components of precipitation (P), evapotranspiration (ET), runoff (R), and terrestrial water storage (TWS) is significantly impacted by the uncertainty in the driving meteorology, with precipitation being the most important boundary condition. Ten gridded precipitation datasets along with a mix of model-, satellite-, and gauge-based products, are evaluated first to assess their suitability for LSM simulations over HMA. The datasets are evaluated by quantifying the systematic and random errors of these products as well as the temporal consistency of their trends. Though the broader spatial patterns of precipitation are generally well captured by the datasets, they differ significantly in their means and trends. In general, precipitation datasets that incorporate information from gauges are found to have higher accuracy with low Root Mean Square Errors and high correlation coefficient values. An ensemble of LSM simulations with selected subset of precipitation products is then used to produce the mean annual fluxes and their uncertainty over HMA in P, ET, and R to be 2.11 ± 0.45, 1.26 ± 0.11, and 0.85 ± 0.36 mm per day, respectively. The mean annual estimates of the surface mass (water) balance components from this model ensemble are comparable to global estimates from prior studies. However, the uncertainty/spread of P, ET, and R is significantly larger than the corresponding estimates from global studies. A comparison of ET, snow cover fraction, and changes in TWS estimates against remote sensing-based references confirms the significant role of the input meteorology in influencing the water budget characterization over HMA and points to the need for improving meteorological inputs.

Terrestrial water budget↗

DOE OSTI2023

Deep root activity overprints weathering of petrogenic organic carbon in shale

The oxidation of organic carbon in sedimentary bedrock (petrogenic OC, OC petro ) is increasingly recognized as a potential source of CO 2 to the atmosphere. Recent studies provide evidence for the mobilization and oxidation of OC petro in sedimentary bedrock during rock weathering. However, the mechanisms and rates remain uncertain, particularly where overlying soils and vegetation drive contemporaneous oxidation of recently fixed organic carbon. Here, in this study, we quantify OC petro weathering across a 16 m shale depth profile in a steep, rapidly eroding forested hillslope in the Northern California Coast Ranges. We report solid and gas phase radiocarbon and stable isotope analyses of samples extracted from specialized in-situ samplers, and a supporting laboratory incubation experiment of the shale regolith. OC petro is removed from the weathered bedrock at a rate of approximately 0.12 gC/m 3 yr, which is orders of magnitude lower than the rate of OC petro oxidation we achieved in the laboratory with crushed samples (557.1 gC/m 3 yr). This disparity occurs despite high O 2(g) content across the depth profile, indicating that physical accessibility of OC petro can regulate oxidative weathering. There is no direct radiocarbon evidence of OC petro oxidation in CO 2(g) across the upper 13 m of the weathering profile during both wet and dry seasons. Instead, vadose zone CO 2(g) production at the site is dominated by respiration of recently fixed carbon associated with deep rooting. OC petro is clearly mobilized across the vadose zone during weathering in this rapidly eroding, oxygen-rich, biologically dynamic hillslope, but at rates far below what can be measured given the contribution of root-derived CO 2(g) .

58 GEOSCIENCES↗

NASA NTRSDate not supplied

Systematic Errors in Simulated L-Band Brightness Temperature in the SMAP Level-4 Soil Moisture Analysis

The NASA Soil Moisture Active Passive (SMAP) mission has been providing L-band (1.4 GHz) brightness temperature (Tb) observations since April 2015. By assimilating the Tb observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter (EnKF), the SMAP Level-4 Soil Moisture (L4_SM) product provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with ~2.5-day latency for use in research and applications. The EnKF-based L4_SM analysis assumes unbiased forecast errors. Consequently, the seasonally varying bias between the model forecast Tb and the observed values is removed prior to the assimilation of the SMAP Tb observations. The L4_SM system is thus designed to only correct errors in synoptic-scale and interannual variations from the long-term mean seasonal cycle while maintaining the model’s (possibly wrong) climatology. In this paper, we examine the Tb observation-minus-forecast (O-F) residuals from the L4_SM Version 7 product (computed after rescaling the Tb observations to the mean seasonal cycle of the simulated Tb). The long-term average of the Tb O-F residuals has a global mean of only 0.13 K and locally small values, ranging from -1 to 3 K. The model forecast Tb, however, still exhibits undesirable systematic errors relative to the (rescaled) Tb observations. At some locations, the time-average Tb O-F values strongly depend on surface soil moisture (SM). At the Yanco SMAP core validation site, for example, the Tb O-F residuals typically range from 5 to 15 K under dry soil moisture conditions (SM < 0.15 m3 m-3) yet are predominantly negative under wet soil moisture conditions (SM > 0.25 m3 m-3), with values ranging from 0 to -40 K. This results in soil moisture analysis increments that persistently make the soil drier under dry SM conditions and persistently make the soil wetter under wet SM conditions, suggesting an error in the dynamic range of the simulated Tb, soil moisture or soil temperature. In this paper, we describe the higher-order systematic Tb forecast errors in more detail, examine their impact on the L4_SM product quality, and explore potential avenues to improve the L4_SM algorithm.

Rolf Reichle↗

NASA NTRS2018

An Assessment of the Differences Between Spatial Resolution and Grid Size for the SMAP Enhanced Soil Moisture Product over Homogeneous Sites

Satellite-based passive microwave remote sensing typically involves a scanning antenna that makes measurements at irregularly spaced locations. These locations can change on a day to day basis. Soil moisture products derived from satellite-based passive microwave remote sensing are usually resampled to a fixed Earth grid that facilitates their use in applications. In many cases the grid size is finer than the actual spatial resolution of the observation, and often this difference is not well understood by the user. Here, this issue was examined for the Soil Moisture Active Passive (SMAP) enhanced version of the passive-based soil moisture product, which has a grid size of 9-km and a nominal spatial resolution of 33-km. In situ observations from core validation sites were used to compute comparison metrics. For sites that satisfied the established reliability and scaling criteria, the impact of validating the 9-km grid product with in situ data collected over a 9-km versus a 33-km domain was very small for the sites studied (0.039 cu. m/cu. m unbiased root mean square difference for the 9-km case versus 0.037 cu. m/cu. m for the 33-km case). This result does not mean that the resolution of the product is 9-km but that for the conditions studied here the soil moisture estimated from in situ observations over 9-km is a close approximation of the soil moisture estimated from in situ observations over the 33-km resolution. The implication is that using the enhanced SMAP product at its grid resolution of 9-km should not introduce large errors in most applications.

Soil moisture↗