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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Short-term warming increased soil heterotrophic respiration due to enhanced active microbial community

Soil microbes, particularly active microbes, play a crucial role in conserving soil carbon under climate change, especially in forest ecosystems, constituting over 50% of global soil organic carbon. Nevertheless, the response mechanisms of active microbial community to climate warming and their subsequent impacts on soil heterotrophic respiration (Rh) remain insufficiently understood. To resolve this mechanistic uncertainty, we implemented a 3-year soil translocation experiment to investigate soil warming effects on active microbial community and Rh. We used 16S rRNA gene amplicon sequencing, Metatranscriptomics sequencing, coupled with correlation analyses to explore the linkages between warming-induced shifts in Rh and the active microbial community. Our results demonstrated that warming of soil induced a 55% enhancement in Rh. Concurrently, the Shannon index and Richness of active microbial community increased by 20% and 117%, respectively. Warming significantly altered active microbial community composition, inducing a compositional shift characterized by 0.5-to 2-fold increases in the abundances of Proteobacteria, Chloroflexi, and Actinobacteria. Our study also revealed 92–100% increases in the abundance of C-degradation functional genes encoding starch, cellulose, and lignin decomposition pathways within active microbial community under warming. Statistical analyses identified significant positive correlations between Rh and the abundance of Proteobacteria and Actinobacteria, as well as expression levels of functional genes associated with lignin and cellulose decomposition pathways. Furthermore, our results suggested that short-term warming increased Rh through altering diversity, species composition, and C degradation functional genes of active microbial community providing insights into the influence of microbial communities on soil C-climate feedbacks under climate warming.

Active microbial community↗
DOE OSTI2023

Derivation of heterogeneous material distributions and their sensitivity to HM-coupled two-phase flow models exemplified with the LASGIT experiment

Abstract Advective gas transport in bentonite, a possible buffer material in repositories for radioactive materials, is difficult to simulate in numerical continuum models, partly due to the complicated microstructure of bentonite. To generate reliable models of repositories nevertheless, spatially distributed heterogeneous material properties can be used to allow localization of gas flow. In this study, a pore-size-dependent stochastic approach of the gas entry pressure is derived from Mercury Intrusion Porosimetry, which is used to replicate measurements from the LASGIT experiment. In addition, three benchmark tests are simulated to investigate the dependence of heterogeneous distributions of material properties on the mesh discretization, the temporal dependence, and the coupling between the processes influenced by the heterogeneous parameters. The numerical modeling results of the LASGIT experiment show that the onset of gas flow into the system and the subsequent increase in pressure and stress can be well reproduced using heterogeneous distributions. Compared to a model with homogeneous material properties, heterogeneous distributions may allow the generation of dilatancy-controlled microfractures—an important feature with regard to the advective gas flow in bentonites. However, it can be observed that the heterogeneous distributions in LASGIT are less significant, as technical gaps or differences in material types could have a greater impact.

Environmental Sciences & Ecology↗
DOE OSTI2020

A mass-transfer particle-tracking method for simulating transport with discontinuous diffusion coefficients

The problem of a spatially discontinuous diffusion coefficient (D(x)) is one that may be encountered in hydrogeologic systems due to natural geological features or as a consequence of numerical discretization of flow properties. To date, mass-transfer particle-tracking (MTPT) methods, a family of Lagrangian methods in which diffusion is jointly simulated by random walk and diffusive mass transfers, have been unable to solve this problem. This manuscript presents a new mass-transfer (MT) algorithm that enables MTPT methods to accurately solve the problem of discontinuous D(x). To achieve this, we derive a semi-analytical solution to the discontinuous D(x) problem by employing a predictor-corrector approach, and we use this semi-analytical solution as the weighting function in a reformulated MT algorithm. Furthermore, this semi-analytical solution is generalized for cases with multiple 1D interfaces as well as for 2D cases, including a 2 × 2 tiling of 4 subdomains that corresponds to a numerically-generated diffusion field. The solutions generated by this new mass-transfer algorithm closely agree with an analytical 1D solution or, in more complicated cases, trusted numerical results, demonstrating the success of our proposed approach.

42 ENGINEERING↗
DOE OSTI2021

Atmospheric humidity deficits tell us how soil moisture deficits down-regulate ecosystem evaporation

Knowing how actual evaporation is down-regulated from potential evaporation during periods with soil moisture deficits is one of the greatest challenges towards computing evaporation everywhere on a regular basis. We propose the hypothesis that vegetated landscapes transmit information on soil moisture deficits through its down-regulation of evaporation, which in turn affects the humidification and growth of the planetary boundary layer. To test this hypothesis, here, we examined how the evaporative fraction, defined as the ratio between actual and potential evaporation, corresponds with the soil moisture stress index, defined as the relative humidity with a power law dependence on vapor pressure deficit times a parameter, β. We tested the parameterized soil moisture stress index with direct eddy covariance measurements of actual evaporation and computations of potential evaporation based on meteorological conditions, averaged on monthly time steps. The analysis was conducted on a dataset obtained from 144 FLUXNET sites. These sites spanned much of the world's climates and biomes and contained over 5900 months of observations. Observations of the evaporative fraction fit the model of the soil moisture stress index best for semi-arid and arid ecosystems, and least for the humid and wet ecosystems. Consequently, a significant relationship between measurements of the evaporative fraction and soil moisture stress index held for about one-half of the population of sites. Under this condition, the median value of the parameter, β, was 1.41. To investigate the mechanism of this empirical soil moisture stress index, we diagnosed it with a coupled evaporation-planetary boundary layer model. The soil moisture stress index is strongly related to surface resistance, as defined by inverting Penman-Monteith equation. Consequently, this index provides an independent estimate of surface resistance based on easy to measure mean monthly weather conditions like relative humidity and temperature. Thereby, this soil moisture stress index has potential to be applied to weather, climate and biogeochemical models and the interpretation of satellite derived evaporation products, like the one provided by the ECOSTRESS mission.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Topographic hydro-conditioning to resolve surface depression storage and ponding in a fully distributed hydrologic model

Land surface depressions play a central role in the transformation of rainfall to ponding, infiltration and runoff, yet digital elevation models (DEMs) used by spatially distributed hydrologic models that resolve land surface processes rarely capture land surface depressions at spatial scales relevant to this transformation. Methods to generate DEMs through processing of remote sensing data, such as optical and light detection and ranging (LiDAR) have favored surfaces without depressions to avoid adverse slopes that are problematic for many hydrologic routing methods. Here, in this study, we present a new topographic conditioning workflow, Depression-Preserved DEM Processing (D2P) algorithm, which is designed to preserve physically meaningful surface depressions for depression-integrated and efficient hydrologic modeling. D2P includes several features: (1) an adaptive screening interval for delineation of depressions, (2) the ability to filter out anthropogenic land surface features (e.g., bridges), (3) the ability to blend river smoothing (e.g., a general downslope profile) and depression resolving functionality. From a case study in the Goodwin Creek Experimental Watershed, D2P successfully resolved 86% of the ponds at a DEM resolution of 10 m. Topographic conditioning was achieved with minimum impact as D2P reduced the number of modified cells from the original DEM by 51% compared to a conventional algorithm. Furthermore, hydrologic simulation using a D2P processed DEM resulted in a more robust characterization on surface water dynamics based on higher surface water storage as well as an attenuated and delayed peak streamflow.

54 ENVIRONMENTAL SCIENCES↗