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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Learning perturbation-inducible cell states from observability analysis of transcriptome dynamics

Abstract A major challenge in biotechnology and biomanufacturing is the identification of a set of biomarkers for perturbations and metabolites of interest. Here, we develop a data-driven, transcriptome-wide approach to rank perturbation-inducible genes from time-series RNA sequencing data for the discovery of analyte-responsive promoters. This provides a set of biomarkers that act as a proxy for the transcriptional state referred to as cell state. We construct low-dimensional models of gene expression dynamics and rank genes by their ability to capture the perturbation-specific cell state using a novel observability analysis. Using this ranking, we extract 15 analyte-responsive promoters for the organophosphate malathion in the underutilized host organism Pseudomonas fluorescens SBW25. We develop synthetic genetic reporters from each analyte-responsive promoter and characterize their response to malathion. Furthermore, we enhance malathion reporting through the aggregation of the response of individual reporters with a synthetic consortium approach, and we exemplify the library’s ability to be useful outside the lab by detecting malathion in the environment. The engineered host cell, a living malathion sensor, can be optimized for use in environmental diagnostics while the developed machine learning tool can be applied to discover perturbation-inducible gene expression systems in the compendium of host organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

RefSoil+: a Reference Database for Genes and Traits of Soil Plasmids

Plasmids harbor transferable genes that contribute to the functional repertoire of microbial communities, yet their contributions to metagenomes are often overlooked. Environmental plasmids have the potential to spread antibiotic resistance to clinical microbial strains. In soils, high microbiome diversity and high variability in plasmid characteristics present a challenge for studying plasmids. To improve the understanding of soil plasmids, we present RefSoil+, a database containing plasmid sequences from 922 soil microorganisms. Soil plasmids were larger than other described plasmids, which is a trait associated with plasmid mobility. There was a weak relationship between chromosome size and plasmid size and no relationship between chromosome size and plasmid number, suggesting that these genomic traits are independent in soil. We used RefSoil+ to inform the distributions of antibiotic resistance genes among soil microorganisms compared to those among nonsoil microorganisms. Soil-associated plasmids, but not chromosomes, had fewer antibiotic resistance genes than other microorganisms. These data suggest that soils may offer limited opportunity for plasmid-mediated transfer of described antibiotic resistance genes. RefSoil+ can serve as a reference for the diversity, composition, and host associations of plasmid-borne functional genes in soil, a utility that will be enhanced as the database expands. Our study improves the understanding of soil plasmids and provides a resource for assessing the dynamics of the genes that they carry, especially genes conferring antibiotic resistances.Soil-associated plasmids have the potential to transfer antibiotic resistance genes from environmental to clinical microbial strains, which is a public health concern. A specific resource is needed to aggregate the knowledge of soil plasmid characteristics so that the content, host associations, and dynamics of antibiotic resistance genes can be assessed and then tracked between the environment and the clinic. Here, we present RefSoil+, a database of soil-associated plasmids. RefSoil+ presents a contemporary snapshot of antibiotic resistance genes in soil that can serve as a reference as novel plasmids and transferred antibiotic resistances are discovered. Our study broadens our understanding of plasmids in soil and provides a community resource of important plasmid-associated genes, including antibiotic resistance genes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape: Modeling Archive

This modeling archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025). This archive contains model input files and outputs from landscape-scale simulations conducted using ELM, the land model component of the Department of Energy’s Energy Exascale Earth System Model (E3SM), at the Council NGEE Arctic field site (Council Road mile marker 71) on Alaska’s Seward Peninsula. Input data and model output from two sets of ELM simulations are provided. The first set of simulations were conducted with the two default ELM Arctic plant functional types (PFTs; broadleaf deciduous boreal shrub and a C3 grass) and the second set of simulations were conducted with a set of nine Arctic-specific PFTs including nonvascular mosses and lichens, graminoids, forbs, evergreen dwarf shrubs, three height classes of deciduous shrubs (dwarf, low, and low to tall), and deciduous alder shrubs (Sulman et al., 2021). Parameter names and major parameter changes in the Arctic-specific PFT configuration are described in Sulman et al. (2021) and archived in the Sulman et al. (2021) dataset (see below). Simulations were spatially explicit, covering an approximately 6.4X3.3 km domain at the Council site with a spatial resolution of 100 m for a total of 2,112 simulated grid cells under each ELM PFT configuration. The modeling archive contains meteorological forcing (seven *.nc files and one *.txt file), a domain definition file (one *.nc files), land surface configuration files (two *.nc files), parameter files (two *.nc files), annual ELM output files spanning 1980-2014 (68 *.nc files), and a User’s Guide (*pdf file). Additional information on the provided files is in the “Modeling Archive Contents” section of the User’s Guide. Model outputs are aggregated to the column scale (i.e. PFT-specific outputs are not provided here).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗
DOE OSTI2020

Development of an In-Situ Leaching Technology for Extracting Residual Uranium from Remediated Soil - 20099

Site-specific chemical solutions for extracting uranium were developed and evaluated for treating previously remediated soil at a former thorium mill tailings site, known as the Former Rare Earths Facility (REF), in West Chicago, Illinois. Prior remediation efforts had resulted in residual sand and gravel aggregate that met the soil cleanup standards. The target soil contains residual levels of uranium, which continues to leach into the site groundwater at levels exceeding groundwater protection standards (GWPS). A series of bench-scale tests were conducted to evaluate the efficacy and viability of in-situ leaching (ISL) technology to treat the target soil for the purposes of attaining uranium GWPS at the REF. Specific objectives of the bench-scale tests entailed identification and selection of optimal leaching, quantification of the extent and rate of uranium released as a function of chemical composition, chemical concentrations, chemical residence times, and obtaining critical data to estimate treatment costs. A combination of sodium bicarbonate and sodium carbonate reagent was the most effective leaching solution. In general, leaching solutions containing a higher concentration of sodium carbonate demonstrated superior uranium leaching capabilities. Removal of 50% of the uranium mass from the soil matrix was adequate for achieving compliance with the site-specific GWPS. After six to seven pore volume flushes (PVFs), the uranium leaching effectiveness of all leaching solutions was similar. The amount of initial uranium removed with each subsequent PVF was minimal, suggesting limited solubility of the remaining mass of uranium. The effects of leaching duration were significant and persisted through at least the first five consecutive PVFs. Leaching of uranium also resulted in leaching of several non-uranium constituents, many of which exceeded applicable National Pollutant Discharge Elimination System (NPDES) standards. Given historical operations and waste disposal practices at the site, leaching of non-uranium constituents was expected. Hydrochloric acid was used to stabilize treated soil. Savings of approximately $148 million in direct and indirect remediation costs are expected with an ISL alternative compared to the excavation and landfill disposal remediation option. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Cost of saving natural gas through efficiency programs funded by utility customers: 2012–2017

This study estimates the cost of saving a therm of natural gas from energy efficiency programs funded by utility customers during the period 2012 to 2017. Berkeley Lab researchers compiled and analyzed efficiency program data reported by investor-owned utilities and other program administrators in a dozen states representative of the four U.S. Census regions — Arkansas, California, Connecticut, Iowa, Massachusetts, Michigan, Minnesota, New Jersey, New York, Oklahoma, Rhode Island and Utah. Depending on the year, the dataset accounts for about 50 percent to 70 percent of annual national spending on natural gas efficiency programs. The estimated cost of saving natural gas during the study period is $0.40 per therm. The analysis also includes estimates of the program administrator cost of saved energy for three core sectors for natural gas: commercial and industrial, residential, and low-income households. It aggregates these sectors to provide regional and national values. Our metrics include savings-weighted averages, unweighted medians, and interquartile ranges (25th and 75th percentiles) of the levelized program administrator cost of saving gas, in constant 2017 dollars. In addition, the study analyzes cost trends during the study period, finding that average program costs trended downward. The U.S. Department of Energy’s Building Technologies Office supported this work.

03 NATURAL GAS↗
DOE OSTI2016

Hydrodynamic effects on β-amyloid (16-22) peptide aggregation

Computer simulations based on simplified representations are routinely used to explore the early steps of amyloid aggregation. However, when protein models with implicit solvent are employed, these simulations miss the effect of solvent induced correlations on the aggregation kinetics and lifetimes of metastable states. In this work, we apply the multi-scale Lattice Boltzmann Molecular Dynamics technique (LBMD) to investigate the initial aggregation phases of the amyloid Aβ{sub 16−22} peptide. LBMD includes naturally hydrodynamic interactions (HIs) via a kinetic on-lattice representation of the fluid kinetics. The peptides are represented by the flexible OPEP coarse-grained force field. First, we have tuned the essential parameters that control the coupling between the molecular and fluid evolutions in order to reproduce the experimental diffusivity of elementary species. The method is then deployed to investigate the effect of HIs on the aggregation of 100 and 1000 Aβ{sub 16−22} peptides. We show that HIs clearly impact the aggregation process and the fluctuations of the oligomer sizes by favouring the fusion and exchange dynamics of oligomers between aggregates. HIs also guide the growth of the leading largest cluster. For the 100 Aβ{sub 16−22} peptide system, the simulation of ∼300 ns allowed us to observe the transition from ellipsoidal assemblies to an elongated and slightly twisted aggregate involving almost the totality of the peptides. For the 1000 Aβ{sub 16−22} peptides, a system of unprecedented size at quasi-atomistic resolution, we were able to explore a branched disordered fibril-like structure that has never been described by other computer simulations, but has been observed experimentally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Final Report for contract DE-SC0010151, "A Cost-Effective Oxygen Separation System Based on Open Gradient Magnetic Field by Polymer Beads"

At present much of the oxygen enrichment market is based primarily on cryogenic systems, ion transport membranes made of ceramics, or polymer membranes technologies. All these methods have some positive and some negative attributes, but remain too expensive for the cost effective production of pure oxygen needed for clean renewable energy conversion projects. In a very successful Phase I period, the ITN-TAMU team accomplished the completion of most of the sub-tasks on oxygen separation based on our proposed magnetic field gradients. Theoretical and computer simulation data under different conditions of flow rates, magnetic flux, magnetic beads packing density, pressure and temperature have resulted very valuable observations. Chitosan based polymer magnetic beads showed the best results for uniformity and column packing. Due to limited magnetic force of 1 Tesla, we were restricted to use only single small column of magnetic beads and limited air pressure with controlled flow rate. We also fabricated smaller sized beads column with metal and clear plastic frames to be used for more concentrated packed capacity. Beads made with rare earth Neodymium were not uniform and were quite brittle. Different surfactants have minimized the effect of the de-aggregation of polymer magnetic beads. This Phase I development work also included overcoming key packaging hurdles such as high packing capacity of magnetic polymer beads and formation of consistent batch of magnetic beads. Market and commercialization studies were also initiated to show that there is a growing market for the proposed cost-effective oxygen separation system for energy conversion projects.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Vibro-acoustic modulation and data fusion for localizing alkali–silica reaction–induced damage in concrete

This article investigates the application of vibro-acoustic modulation testing for diagnosing damage in concrete structures. The vibro-acoustic modulation technique employs two excitation frequencies on a structure. The interaction of these excitations in the measured response indicates damage through the presence of sidebands in the frequency spectra. Past studies using this technique have mostly focused on metals and composites (thin plates or laminates). Our research focuses on concrete, which is a highly heterogeneous material susceptible to a variety of chemical, physical, and mechanical damage processes. In particular, this article investigates diagnosing cracking in concrete from an expansive gel produced by an alkali–silica reaction in the presence of moisture. Past studies have been limited to damage detection using vibro-acoustic modulation testing, whereas this article extends the technique to damage localization. A cement slab with pockets of reactive aggregate is used to investigate the diagnosis technique. The effects of different testing parameters, such as locations, magnitudes, and frequencies of the two excitations, are analyzed and incorporated in the damage localization methodology. A Bayesian probabilistic methodology is developed to fuse the information from multiple test configurations in order to construct damage probability maps for the test specimen. The results of vibro-acoustic modulation–based damage localization are validated by petrographic study of cores taken from the slab.

Karve, Pranav↗
DOE OSTI2021

Enhanced Ion Conductivity through Hydrated, Polyelectrolyte-Grafted Cellulose Nanocrystal Films

Here,iIonically conductive, hydrated polyelectrolyte nanocomposites are prepared from iodomethane-treated poly(2-vinylpyridine) (mPV)-grafted cellulose nanocrystals (MxG-CNC-g-mPV). These polyelectrolyte-grafted nanoparticle (PEGN) films exhibit an order-of-magnitude higher iodide ion conductivity relative to mPV films and a high in-plane/through-plane anisotropy. The PEGN architecture prevents CNC aggregation, maximizing the CNC/polyelectrolyte interface. PEGN films were prepared with varying polymer graft density (0.03-0.12 chains/nm 2 ) and molecular weight (7k-30k g/mol). The greatest ion conductivity enhancement is observed with lower molecular weight, higher density grafts: ca. 89 ± 6 mS/cm (140 ±10 mS/cm accounting for the volume of the CNC) versus 3.3 ± 0.4 mS/cm for ungrafted mPV. Poly(styrene-block-2-vinylpyridine)-grafted CNCs were prepared in which the insulating polystyrene block or the conducting mPV block was directly attached to the CNCs; only the films with the mPV block closest to the CNCs exhibited an enhancement in conductivity relative to mPV. Together, these data point to beneficial CNC/polyelectrolyte interfacial effects, resulting in significant ionic conductivity enhancement along the length of the CNCs in these films.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2014

Surface Condensation of CO2 onto Kaolinite

The fundamental adsorption behavior of gaseous and supercritical carbon dioxide (CO2) onto poorly crystalline kaolinite (KGa-2) at conditions relevant to geologic sequestration has been investigated using a quartz crystal microbalance (QCM) and density functional theory (DFT) methods. The QCM data indicated linear adsorption of CO2 (0-0.3 mmol CO2/g KGa-2) onto the kaolinite surface up through the gaseous state (0.186 g/cm3). However in the supercritical region, CO2 adsorption increases dramatically, reaching a peak (0.9-1.0 mmol CO2/g KGa-2) near 0.43 g/cm3, before declining rapidly to surface adsorption values equivalent or below gaseous CO2. This adsorption profile was not observed with He or N2. Comparative density functional studies of CO2 interactions with kaolinite surface models rule out CO2 intercalation and confirm that surface adsorption is favored up to approximately 0.35 g/cm3 of CO2, showing distorted T-shaped CO2-CO2 clustering, typical of supercritical CO2 aggregation over the surface as the density increases. Beyond this point, the adsorption energy gain for any additional CO2 becomes less than the CO2 interaction energy (~0.2 eV) in the supercritical medium resulting in overall desorption of CO2 from the kaolinite surface.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2015

Pridopidine, a dopamine stabilizer, improves motor performance and shows neuroprotective effects in Huntington disease R6/2 mouse model

Abstract Huntington disease ( HD ) is a neurodegenerative disorder for which new treatments are urgently needed. Pridopidine is a new dopaminergic stabilizer, recently developed for the treatment of motor symptoms associated with HD . The therapeutic effect of pridopidine in patients with HD has been determined in two double‐blind randomized clinical trials, however, whether pridopidine exerts neuroprotection remains to be addressed. The main goal of this study was to define the potential neuroprotective effect of pridopidine, in HD in vivo and in vitro models, thus providing evidence that might support a potential disease‐modifying action of the drug and possibly clarifying other aspects of pridopidine mode‐of‐action. Our data corroborated the hypothesis of neuroprotective action of pridopidine in HD experimental models. Administration of pridopidine protected cells from apoptosis, and resulted in highly improved motor performance in R6/2 mice. The anti‐apoptotic effect observed in the in vitro system highlighted neuroprotective properties of the drug, and advanced the idea of sigma‐1‐receptor as an additional molecular target implicated in the mechanism of action of pridopidine. Coherent with protective effects, pridopidine‐mediated beneficial effects in R6/2 mice were associated with an increased expression of pro‐survival and neurostimulatory molecules, such as brain derived neurotrophic factor and DARPP 32, and with a reduction in the size of mHtt aggregates in striatal tissues. Taken together, these findings support the theory of pridopidine as molecule with disease‐modifying properties in HD and advance the idea of a valuable therapeutic strategy for effectively treating the disease.

Squitieri, Ferdinando↗
DOE OSTI2015

Transcriptional Responses to Sucrose Mimic the Plant-Associated Life Style of the Plant Growth Promoting Endophyte Enterobacter sp. 638

Growth in sucrose medium was previously found to trigger the expression of functions involved in the plant associated life style of the endophytic bacterium Enterobacter sp. 638. Therefore, comparative transcriptome analysis between cultures grown in sucrose or lactate medium was used to gain insights in the expression levels of bacterial functions involved in the endophytic life style of strain 638. Growth on sucrose as a carbon source resulted in major changes in cell physiology, including a shift from a planktonic life style to the formation of bacterial aggregates. This shift was accompanied by a decrease in transcription of genes involved in motility (e.g. flagella biosynthesis) and an increase in the transcription of genes involved in colonization, adhesion and biofilm formation. The transcription levels of functions previously suggested as being involved in endophytic behavior and functions responsible for plant growth promoting properties, including the synthesis of indole-acetic acid, acetoin and 2,3-butanediol, also increased significantly for cultures grown in sucrose medium. Interestingly, despite an abundance of essential nutrients transcription levels of functions related to uptake and processing of nitrogen and iron became increased for cultures grown on sucrose as sole carbon source. Transcriptome data were also used to analyze putative regulatory relationships. In addition to the small RNA csrABCD regulon, which seems to play a role in the physiological adaptation and possibly the shift between free-living and plant-associated endophytic life style of Enterobacter sp. 638, our results also pointed to the involvement of rcsAB in controlling responses by Enterobacter sp. 638 to a plant-associated life style. Lastly, targeted mutagenesis was used to confirm this role and showed that compared to wild-type Enterobacter sp. 638 a ΔrcsB mutant was affected in its plant growth promoting ability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Concrete Structure Health Monitoring Using Vibro-acoustic Testing and Machine Learning

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on margins of safety in existing codes. Research is required to deploy online monitoring capability to assess the health of concrete structures in nuclear power plants and perform predictive analytics based on heterogeneous measurements, in order to reduce the operation and maintenance costs. The research effort described in this report focuses on the health monitoring of concrete slabs containing reactive aggregates using the vibro-acoustic modulation (VAM) technique and predictive modeling. The research is developing an approach to enable detection, localization, and estimation of the extent of degradation in concrete slabs due to alkali-silica reaction (ASR). The project outcomes are generic and extendable to other degradation modes in concrete. A concrete slab without reinforcements was cast at Vanderbilt University and cured in aggressive conditions to accelerate ASR degradation. In this report, we develop a methodology for the automation of VAM testing, and the construction of machine learning models to facilitate damage localization in concrete structures. We investigate how machine learning models based on physics simulation data can be effectively utilized for damage localization (damage location and depth) and estimation in a concrete slab specimen. Our study indicates that these models could potentially support damage localization and estimation for NPP structures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Mathematical Modelling of Arctic Polygonal Tundra with Ecosys: 2. Microtopography Determines How CO 2 and CH 4 Exchange Responds to Changes in Temperature and Precipitation

Differences of surface elevation in arctic polygonal landforms cause spatial variation in soil water contents (θ), active layer depths (ALD), and thereby in CO 2 and CH 4 exchange. In this paper, we test hypotheses in ecosys for topographic controls on CO 2 and CH 4 exchange in trough, rim, and center features of low- and flat-centered polygons (LCP and FCP) against chamber and eddy covariance (EC) measurements during 2013 at Barrow, Alaska. Larger CO 2 influxes and CH 4 effluxes were measured with chambers and modeled with ecosys in LCPs than in FCPs and in lower features (troughs) than in higher (rims) within LCPs and FCPs. Spatially aggregated CO 2 and CH 4 fluxes from ecosys were significantly correlated with EC flux measurements. Lower features were modeled as C sinks (52–56 g C m -2 yr -1 ) and CH 4 sources (4–6 g C m -2 yr -1 ), and higher features as near C neutral (-2–15 g C m -2 yr -1 ) and CH 4 neutral (0.0–0.1 g C m -2 yr -1 ). Much of the spatial and temporal variations in CO 2 and CH 4 fluxes were modeled from topographic effects on water and snow movement and thereby on θ, ALD, and soil O 2 concentrations. Model results forced with meteorological data from 1981 to 2015 indicated increasing net primary productivity in higher features and CH 4 emissions in some lower and higher features since 2008, attributed mostly to recent rises in precipitation. Finally, small-scale variation in surface elevation causes large spatial variation of greenhouse gas (GHG) exchanges and therefore should be considered in estimates of GHG exchange in polygonal landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Advantage of multi-band solar-induced chlorophyll fluorescence to derive canopy photosynthesis in a temperate forest

When solar-induced chlorophyll fluorescence (SIF) is developed as a novel approach to quantify gross primary production (GPP), narrow SIF emission spectrum around the atmospheric oxygen absorption windows (˜ 761 nm and ˜687 nm) has been widely used to represent SIF and to derive GPP. As SIF is a continuous spectrum, deriving the full broadband SIF emission spectrum over 640–850 nm provides an opportunity to fully explore the potential of SIF in estimating GPP. Using high-frequency measurements of canopy carbon flux and SIF emissions at the atmospheric absorption bands, here we reconstruct the full SIF spectrum from SIF signals at the absorption bands, and then analyze correlations between the GPP and the selected single SIF bands and their combinations using both linear regression (LR) and Gaussian processes regression (GPR). Our results indicate that (1) the red SIF bands (640–700 nm) shows low correlation with GPP due to the strong (re)absorption of red SIF emissions by leaf chlorophyll; (2) the individual bands in near-infrared area (at 720 nm, 740 nm, and 761 nm) can determine about 60% and 62% of the variance in GPP with hourly scale by LR and GPR, respectively, and the combination of those SIF bands provide increased predictive power, explaining 66% and 76% variance in GPP with hourly scale by LR and GPR, respectively; (3) the solar radiation saturation, fraction of direct solar radiation, air temperature and leaf area index may have negative impacts on the SIF-GPP correlations when they are beyond optimal thresholds; and (4) the temporal aggregation of SIF-GPP (daily scale) enhances the correlations as compared with the hourly scale: the daily combination of SIF bands (at 687 nm, 720 nm, and 761 nm) can account for 80% and 93% of variance in daily daytime GPP by LR and GPR, respectively, suggesting that the combination of these three bands of SIF on the daily scale is the best proxy for GPP. Our results provide a new approach to analyze the SIF-GPP correlations using the ground-based full broadband SIF emission, suggesting that multi-bands SIF has a stronger capacity in predicting plant GPP than traditionally used signal band SIF data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Maximum likelihood Bayesian model averaging and its predictive analysis for groundwater reactive transport models

While Bayesian model averaging (BMA) has been widely used in groundwater modeling, it is infrequently applied to groundwater reactive transport modeling because of multiple sources of uncertainty in the coupled hydrogeochemical processes and because of the long execution time of each model run. To resolve these problems, this study analyzed different levels of uncertainty in a hierarchical way, and used the maximum likelihood version of BMA, i.e., MLBMA, to improve the computational efficiency. Our study demonstrates the applicability of MLBMA to groundwater reactive transport modeling in a synthetic case in which twenty-seven reactive transport models were designed to predict the reactive transport of hexavalent uranium (U(VI)) based on observations at a former uranium mill site near Naturita, CO. Moreover, these reactive transport models contain three uncertain model components, i.e., parameterization of hydraulic conductivity, configuration of model boundary, and surface complexation reactions that simulate U(VI) adsorption. These uncertain model components were aggregated into the alternative models by integrating a hierarchical structure into MLBMA. The modeling results of the individual models and MLBMA were analyzed to investigate their predictive performance. The predictive logscore results show that MLBMA generally outperforms the best model, suggesting that using MLBMA is a sound strategy to achieve more robust model predictions relative to a single model. MLBMA works best when the alternative models are structurally distinct and have diverse model predictions. When correlation in model structure exists, two strategies were used to improve predictive performance by retaining structurally distinct models or assigning smaller prior model probabilities to correlated models. Since the synthetic models were designed using data from the Naturita site, the results of this study are expected to provide guidance for real-world modeling. Finally, limitations of applying MLBMA to the synthetic study and future real-world modeling are discussed.

58 GEOSCIENCES↗
DOE OSTI2019

Streamflow Reconstruction in the Upper Missouri River Basin Using a Novel Bayesian Network Model

A Bayesian model that uses the spatial dependence induced by the river network topology, and the leading principal components of regional tree ring chronologies for paleo-streamflow reconstruction is presented. In any river basin, a convergent, dendritic network of tributaries come together to form the main stem of a river. Consequently, it is natural to think of a spatial Markov process that recognizes this topological structure to develop a spatially consistent basin-scale streamflow reconstruction model that uses the information in streamflow and tree ring chronology data to inform the reconstructed flows, while maintaining the space-time correlation structure of flows that is critical for water resource assessments and management. Given historical data from multiple streamflow gauges along a river, their tributaries in a watershed, and regional tree ring chronologies, the model is fit and used to simultaneously reconstruct the full network of paleo-streamflow at all gauges in the basin progressing upstream to downstream along the river. Our application to 18 streamflow gauges in the Upper Missouri River Basin shows that the mean adjusted R 2 for the basin is approximately 0.5 with good overall cross-validated skill as measured by five different skill metrics. The spatial network structure produced a substantial reduction in the uncertainty associated with paleo-streamflow as one proceeds downstream in the network aggregating information from upstream gauges and tree ring chronologies. Uncertainty was reduced by more than 50% at six gauges, between 6% and 50% at one gauge, and by less than 5% at the remaining 11 gauges when compared with the traditional principal component regression reconstruction model.

54 ENVIRONMENTAL SCIENCES↗