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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Interactions between molecular-scale biogeochemical processes and hyporheic exchange for understanding coupled Fe-S-C cycling in iron-rich riparian wetlands (Final Technical Report)

Riparian wetlands are dynamic interfaces that exert strong control over water quality, contaminant mobility, and greenhouse gas emissions. These systems are characterized by hyporheic exchange between oxic surface water and anoxic groundwater, which generates steep redox gradients and promotes spatially and temporally variable microbial activity. Despite growing recognition of tightly coupled iron (Fe), sulfur (S), and carbon (C) cycling in these environments, the mechanisms governing these interactions—particularly under low-sulfate freshwater conditions—remain poorly constrained. This project developed a mechanistic understanding of how hydrologic variability and microbial processes interact to control Fe–S–C cycling in iron-rich riparian wetlands. Using a multi-scale and multi-method approach integrating field observations, geochemical and spectroscopic analyses, metagenomics, and reactive transport modeling, we demonstrate that “cryptic” sulfur cycling—rapid sulfur transformations involving intermediate-valence species—plays a dominant and previously underrecognized role in freshwater wetlands. These processes persist despite low sulfate concentrations and significantly influence iron reduction, carbon mineralization, and methane dynamics. The results show that cryptic sulfur cycling enhances dissolved Fe 2+ production, regulates methane concentrations, and is strongly controlled by climate-driven hydrologic fluxes. By linking hydroclimate, subsurface flow, and biogeochemical reactions, this work provides a predictive framework for understanding how wetland systems respond to environmental change, with direct implications for water quality and carbon cycling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Changes in inundation drive carbon dioxide and methane fluxes in a temperate wetland

Wetlands cycle carbon by being net sinks for carbon dioxide (CO 2 ) and net sources of methane (CH 4 ). Daily and seasonal temporal patterns, dissolved oxygen (DO) availability, inundation status (flooded or dry/partially flooded), water depth, and vegetation can affect the magnitude of carbon uptake or emissions, but the extent and interactive effects of these variables on carbon gas fluxes are poorly understood. We characterized the linkages between carbon fluxes and these environmental and temporal drivers at the Old Woman Creek National Estuarine Research Reserve (OWC), OH. We measured diurnal gas flux patterns in an upstream side channel (called the cove) using chamber measurements at six sites (three vegetated and three non-vegetated). We sampled hourly from 7 AM to 7 PM and monthly from July to October 2022. DO concentrations and water levels were measured monthly. Water inundation status had the most influential effect on carbon fluxes with flooded conditions supporting higher CH 4 fluxes (0.39 μmol CH 4 m –2 s –1 ; –1.23 μmol CO 2 m –2 s –1 ) and drier conditions supporting higher CO 2 fluxes (0.03 μmol CH 4 m –2 s –1 ; 0.86 μmol CO 2 m –2 s –1 ). When flooded, the wetland was a net CO 2 sink; however, it became a source for both CH 4 and CO 2 when water levels were low. We compared chamber-based gas fluxes from the cove in flooded (July) and dry (August) months to fluxes measured with an eddy covariance tower whose footprint covers flooded portions of the wetland. The diurnal pattern of carbon fluxes at the tower did not vary with changing water levels but remained a CO 2 sink and a CH 4 source even when the cove where we performed the chamber measurements dried out. Furthermore, these results emphasize the role of inundation status on wetland carbon cycling and highlight the importance of fluctuating hydrologic patterns, especially hydrologic drawdowns, under changing climatic conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Deep State Space Model for Rainfall‐Runoff Simulations

The classical way of studying the rainfall‐runoff processes in the water cycle relies on conceptual or physically‐based hydrologic models. Deep learning (DL) has recently emerged as an alternative and blossomed in the hydrology community for rainfall‐runoff simulations. However, the decades‐old Long Short‐Term Memory (LSTM) network remains the benchmark for this task, outperforming newer architectures like Transformers. In this work, we propose a State Space Model (SSM), specifically the Frequency Tuned Diagonal State Space Sequence (S4D‐FT) model, for rainfall‐runoff simulations. The proposed S4D‐FT is benchmarked against the established LSTM and a physically‐based Sacramento Soil Moisture Accounting model under in‐sample and out‐of‐sample simulation setups across 531 watersheds in the contiguous United States (CONUS). Results show that S4D‐FT is able to outperform the LSTM model across diverse regions under both simulation setups, especially for regions that feature snowmelt‐driven or intermittent flow regimes. In contrast, S4D‐FT tends to underperform in flashier, high‐magnitude flow regimes, likely due to its global state‐space convolution computation that emphasizes slow, storage‐driven dynamics, which makes it less effective at picking up short bursts and noisy spikes in the data. In summary, our pioneering introduction of the S4D‐FT for rainfall‐runoff simulations challenges the dominance of LSTM in the hydrology community and expands the arsenal of DL tools available for hydrological modeling.

Wang, Yihan [Univ. of Oklahoma, Norman, OK (United↗
DOE OSTI2023

Editorial: Advances in observations and modeling of snow, forest-snow processes and snow hydrology

Seasonal snowpack plays a pivotal role in the regional water cycle. In Western mountainous regions, where precipitation predominantly occurs as snow during winter and is limited in the summer months when water demand peaks, snowpack serves as a critical water source essential for sustaining water supply, ecosystems, agriculture, and industries. Additionally, snowpack dynamically influences extreme events, such as floods, droughts, and wildfires, through intricate land-atmosphere feedback. Nevertheless, significant knowledge gaps persist within this field due to data limitations and the complexity of the physics involved in modeling snow and snow hydrology (i.e., snow acts as a critical upstream hydrological process). Here, this research topic presents a collection of manuscripts that address some of these important research gaps.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Vertical Hydrologic Exchange Flows Control Methane Emissions from Riverbed Sediments

CH 4 emissions from inland waters are highly uncertain in the current global CH 4 budget, especially for streams, rivers, and other lotic systems. Previous studies have attributed the strong spatiotemporal heterogeneity of riverine CH 4 to environmental factors such as sediment type, water level, temperature, or particulate organic carbon abundance through correlation analysis. However, a mechanistic understanding of the basis for such heterogeneity is lacking. Here, in this study, we combine sediment CH 4 data from the Hanford reach of the Columbia River with a biogeochemical-transport model to show that vertical hydrologic exchange flows (VHEFs), driven by the difference between river stage and groundwater level, determine CH 4 flux at the sediment–water interface. CH 4 fluxes show a nonlinear relationship with the magnitude of VHEFs, where high VHEFs introduce O 2 into riverbed sediments, which inhibit CH 4 production and induce CH 4 oxidation, and low VHEFs cause transient reduction in CH 4 flux (relative to production) due to reduced advective CH 4 transport. In addition, VHEFs lead to the hysteresis of temperature rise and CH 4 emissions because high river discharge caused by snowmelt in spring leads to strong downwelling flow that offsets increasing CH 4 production with temperature rise. Our findings reveal how the interplay between in-stream hydrologic flux besides fluvial-wetland connectivity and microbial metabolic pathways that compete with methanogenic pathways can produce complex patterns in CH 4 production and emission in riverbed alluvial sediments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Metabolic Constraints of Organic Matter Mineralization and Metal Cycling

Floodplains are poorly understood and dynamic components of the global carbon cycle that not are well represented in Earth system models. Further, they have a dominant influence on the cycling of important metals within critical transport conduits between surface waters and groundwater. The physical characteristics of floodplains make the hydrology and associated coupled biology and geochemistry particularly responsive to ongoing and impending changes in climate, river management, and land development

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Importance of Freeze/Thaw Cycles on Lateral Transport in Ice-Wedge Polygons: Modeling Archive

This Modeling Archive is in support of an NGEE Arctic publication "The importance of freeze/thaw cycles on lateral transport in ice-wedge polygons". The dataset includes xml input/configuration files. These files are compatible with the ATS version 1.0 and higher. The mesh folder contains mesh files used for high-centered polygon (hcp) and low-centered polygon (lcp). The mesh files represent the transect of the polygonal tundra (Fig 1). Here we used two types of mesh with impermeable layer and without. The mesh with an impermeable layer corresponds to the synthetic permafrost (no freezeup case). The freeze up case uses mesh without impermeable layer to simulated frozen ground start at the same depth where the impermeable layer is for the no freezeup case. The meteorological data used drive the model saved in the "inputs" folder. The processed tracer flow rates are saved in the "tracer-flow-ratesCfolder. To plot figures 1 and 2, we used VisIt software. To plot all the flow rates, we used ipython notebook script. All required inputs are saved in "freezeup" and "no freezeup" folders. Each folder includes the corresponding "lcp" and "hcp" folders. The "freezeup" folder has also flat-centered polygon (fcp) case, low porosity "lpor", and low permeability "lper" cases. Included are *.xml, *.exo, *.h5, *pdf, *.ipynb, *.sh, *.py, and *.out files. NGEE Arctic Project Summary: The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Advected carbon younger than the sediment fuels microbial metabolism in a pumped deep aquifer

Ever deeper wells are drilled worldwide to pump potable groundwater. Recent studies argue that overpumping compresses clays and releases reactive dissolved organic carbon (DOC), which in turn drives a series of microbial reactions that affect groundwater potability including arsenic concentrations. Here, we use a novel method to measure the radiocarbon ages of microbial RNA to determine the source of reactive or metabolizable DOC and argue against the compression of clays as the sole source of carbon. We show that microbial RNA (5,230; 5,550; 6,250 yr; n = 3 wells), DOC (280-10,800 yr; n = 13), and methane (modern to 6,240 yr; n = 3), from an overpumped deep aquifer in Bangladesh are much younger than the overlying clay layers deposited during the Pleistocene over 12,000 years ago. Mass-balance indicates that at least half of the carbon incorporated into RNA has to come from reactive DOC or methane that is advected downward via vertical recharge. This metabolism of advected organic carbon could have implications for the quality of water pumped from deep aquifers.

Biological and medical sciences↗
DOE OSTI2025

Distinct microbiomes underlie divergent responses of methane emissions from diverse wetland soils to oxygen shifts

Abstract Hydrological shifts in wetlands, a globally important methane (CH4) source, are critical constraints on CH4 emissions and carbon-climate feedbacks. A limited understanding of how hydrologically driven oxygen (O2) variability affects microbial CH4 cycling in diverse wetlands makes wetland CH4 emissions uncertain. Transient O2 exposure significantly stimulated anoxic CH4 production in incubations of Sphagnum peat from a temperate bog by enriching for polyphenol oxidizers and polysaccharide degraders, enhancing substrate flow toward methanogenesis under subsequent anoxic conditions. To assess whether shifts in soil microbiome structure and function operate similarly across wetland types, here we examined the sensitivity of different wetland soils to transient oxygenation. In slurry incubations of Sphagnum peat from a minerotrophic fen, and sediments from a freshwater marsh and saltmarsh, we examined temporal shifts in microbiomes coupled with geochemical characterization of slurries and incubation headspaces. Oxygenation did not affect microbiome structure and anoxic CH4 production in mineral-rich fen-origin peat and freshwater marsh soils. Key taxa linked to O2-stimulated CH4 production in the bog-origin peat were notably rare in the fen-origin peat, supporting microbiome structure as a primary determinant of wetland response to O2 shifts. In contrast to freshwater wetland experiments, saltmarsh geochemistry—particularly pH—and microbiome structure were persistently and significantly altered postoxygenation, albeit with no significant impact on greenhouse gas emissions. These divergent responses suggest wetlands may be differentially resistant to O2 fluctuations. With climate change driving greater O2 variability in wetlands, our results inform mechanisms of wetland resistance and highlight microbiome structure as a potential resiliency biomarker.

Reji, Linta (ORCID:0000000213376782)↗
DOE OSTI2026

Mapping the soil microbiome functions shaping wetland methane emissions

Accounting for only 8% of Earth’s land cover, freshwater wetlands remain the foremost contributors to global methane emissions. Yet the microorganisms and processes underlying methane emissions from wetland soils remain poorly understood. Over a five-year period, we surveyed the microbial membership and in situ methane measurements from over 700 samples in one of the most prolific methane-emitting wetlands in the United States. We constructed a catalog of 2,502 metagenome-assembled genomes (MAGs), with more than half of the 70 bacterial and archaeal phyla sampled containing novel lineages. Integration of these data with 133 soil metatranscriptomes provided a genome-resolved view of the biogeochemical specialization and versatility expressed over wetland soil spatial and temporal gradients. Centimeter-scale depth differences best explained patterns of microbial community structure and transcribed functionalities, even more than land cover or temporal information. Moreover, while extended flooding restructured soil redox, this perturbation failed to reconfigure the transcriptional profiles of methane-cycling microorganisms, contrasting with theoretically expected responses to hydrological perturbations. Co-expression analyses, coupled with depth-resolved methane measurements, revealed the metabolisms and trophic structures most predictive of methane hotspots. Mapping the spatiotemporal transcriptional patterns on this compendium of biogeochemically classified soil-derived genomes begins to untangle the microbial carbon, energy, and nutrient processing contributing to wetland methane production.

MAG↗
DOE OSTI2024

Snow distribution patterns revisited: A physics-based and machine learning hybrid approach to snow distribution mapping in the sub-Arctic Supporting Data

Snow in the Arctic and sub-Arctic is highly variable at fine scales, with deep drifts and shallow scoured areas creating a complex pattern of snow on the landscape. This fine-scale variation in snow is driven primarily by landscape and vegetation properties. Some landscape features, such as river beds, will rapidly fill in with snow during the wintertime due to high winds, while shrubs will trap blowing snow, resulting in drifts. Meanwhile, snow will blow off of exposed areas, resulting in abnormally shallow snow. These complex interactions between wind, vegetation, and terrain are difficult to represent well with physically-based models, but machine learning techniques have shown promise in the past. Here, we propose a hybrid modeling approach, where we use machine learning derived snow pattern maps to inform SnowModel, a physically-based snow process model. We develop and test this technique at the Teller 27 Seward Peninsula NGEE-Arctic study site. This dataset includes 5 *.nc files of model inputs and outputs plus one user guide (*.pdf). We present the data we use to drive SnowModel (vegetation type, digital elevation model), the snow pattern maps used to inform SnowModel (Standardized Depth Values maps, Machine Learning Snow Distribution Pattern), and our machine learning, SnowModel, and Hybrid snow depth and snow water equivalent results. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Deciphering controls on metal migration within floodplains: The critical role of redox environments on metal-organic complexes (Final Technical Report)

Our project elucidates the effect of differing hydrologic regimes on nutrient and contaminant dynamics within floodplains, and we explore the impact of varying sources of hydrologic extremes on nutrient-contaminant fate and transport. We use a combination of field measurements and laboratory experiments to examine the relationships between redox conditions, functionality of dissolved organic matter, metal speciation (specifically examining metal-ligand complexes), and nutrient-contaminant fate, particularly during hydrologic extremes. Floodplain biogeochemical variation through climatic extremes and beaver-induced hydrologic variation provide a unique look at controls on nutrient-contaminant fate and transport. Through our work, we have developed a novel approach that provides an unprecedented ability to resolve aqueous metal-organic complexes that reveals metal binding preferences for natural organic matter based on metal-ligand chemistry. We have developed novel methods to separate, quantify, and characterize organic-metal complexes in natural DOM that pair with field experiments comprising floodplains having systematic variation in biogeochemical conditions. We also developed a comprehensive computational approach for molecular characterization of metal-organic species that merges LC-coupled high resolution (HR) mass spectrometry and ICP-MS analysis. Importantly, we show that beaver dams have an outsized influence on hydrologic extremes, dwarfing the impact of climatic variation, that ultimate control biogeochemical conditions and water quality. Additionally, beaver dams impose a hydrologic driver that leads to improved, river water quality by divert water through soils and the hyporheic zone. We further show that iron(III) minerals have a dominant control on carbon mineralization across floodplains independent of hydrologic conditions, and that iron and aluminum associations with organic matter are a controlling factor in carbon mineralization. Ultimately, our work is helping to advancing a robust predictive understanding of how hydrologic changes in watersheds affect water quality and carbon and metal cycling in riparian zones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Evaluating post-fire watershed response to varying burn severity and precipitation regimes using fully-distributed and integrated hydrologic models

Wildfires can cause significant changes in vegetation and soil, which may lead to increased surface runoff and soil erosion, thereby affecting water cycling within ecosystems. This study uses the Advanced Terrestrial Simulator (ATS), an integrated and fully distributed hydrologic model at the watershed scale, to examine post-fire hydrologic responses in selected watersheds with varying burn severities in the Pacific Northwest region of the United States. The model integrates surface overland flow, subsurface flow, and canopy biophysical processes. We have developed a new fire module in ATS to account for changes in soil hydraulic properties caused by fire in the topsoil layer. Modeling results indicate that, in the year following a high-severity burn, watershed-averaged evapotranspiration decreases by 25%. Additionally, post-fire peak flows increase by 18-29% in watersheds burned with medium to high severity due to changes in soil properties. Conversely, a low-severity burn results in less than a 1% increase in post-fire peak flow. Furthermore, a high-severity fire causes a 38% reduction in the infiltration rate within the affected watershed during the first post-fire wet season. Hypothetical numerical experiments with varying precipitation regimes after a high-severity fire show that post-fire peak flows can increase by 1-29% due to fire-induced changes in soil hydraulic properties. This study highlights the importance of using fully distributed hydrologic models to quantify disturbance-feedback loops, which are essential for understanding the complexities brought about by spatial heterogeneity in post-fire landscapes.

ATS↗
DOE OSTI2020

Carbon Dioxide Production in Bedrock Beneath Soils Substantially Contributes to Forest Carbon Cycling

Abstract Soils are widely considered the primary terrestrial organic matter pool mediating carbon transactions with the atmosphere and groundwater. Because soils are both a host and a product of rhizosphere activity, they are thought to mark the location where photosynthetic fixation of carbon dioxide (CO 2 ) is balanced by the oxidation of organic matter. However, in many terrestrial environments, the rhizosphere extends below soils and into fractured bedrock, and it is unknown if the resulting biological and hydrologic dynamics in bedrock have a significant impact on carbon cycling. Here we show substantial production of CO 2 in weathered bedrock at 4–8 m below the thin soils (<0.5 m thick) of a Northern California forest using innovative monitoring technology for sampling gases and water in fractured rock. The deep CO 2 production supports a persistent upward flux of CO 2(g) year‐round from bedrock to soil, constituting between 2% and 29% of the average daily CO 2 efflux from the land surface. When water is rapidly transported across the fractured bedrock vadose zone, nearly 50% of the CO 2 produced in the bedrock dissolves into water, promoting water‐rock interaction and export of dissolved inorganic carbon (DIC) from the unsaturated zone to groundwater, constituting as much as 80% of the DIC exiting the hillslope. Such CO 2 production in weathered bedrock is subject to unique moisture, temperature, biological, and mineralogical conditions which are currently missing from terrestrial carbon models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

High–Resolution Maps of Near–Surface Permafrost for Three Watersheds on the Seward Peninsula, Alaska Derived From Machine Learning

Permafrost soils are a critical component of the global carbon cycle and are locally important because they regulate the hydrologic flux from uplands to rivers. Furthermore, degradation of permafrost soils causes land surface subsidence, damaging infrastructure that is crucial for local communities. Regional and hemispherical maps of permafrost are too coarse to resolve distributions at a scale relevant to assessments of infrastructure stability or to illuminate geomorphic impacts of permafrost thaw. Here we train machine learning models to generate meter–scale maps of near–surface permafrost for three watersheds in the discontinuous permafrost region. The models were trained using ground truth determinations of near–surface permafrost presence from measurements of soil temperature and electrical resistivity. We trained three classifiers: extremely randomized trees (ERTr), support vector machines (SVM), and an artificial neural network (ANN). Model uncertainty was determined using k–fold cross validation, and the modeled extents of near–surface permafrost were compared to the observed extents at each site. At–a–site near–surface permafrost distributions predicted by the ERTr produced the highest accuracy (70%–90%). However, the transferability of the ERTr to the sites outside of the training data set was poor, with accuracies ranging from 50% to 77%. The SVM and ANN models had lower accuracies for at–a–site prediction (70%–83%), yet they had greater accuracy when transferred to the non–training site (62%–78%). These models demonstrate the potential for integrating high–resolution spatial data and machine learning models to develop maps of near–surface permafrost extent at resolutions fine enough to assess infrastructure vulnerability and landscape morphology influenced by permafrost thaw.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The first ensemble of kilometer-scale simulations of a hydrological year over the third pole

An accurate understanding of the current and future water cycle over the Third Pole is of great societal importance, given the role this region plays as a water tower for densely populated areas downstream. An emerging and promising approach for skillful climate assessments over regions of complex terrain is kilometer-scale climate modeling. As a foundational step towards such simulations over the Third Pole, we present a multi-model and multi-physics ensemble of kilometer-scale regional simulations for the hydrological year of October 2019 to September 2020. The ensemble consists of 13 simulations performed by an international consortium of 10 research groups, configured with a horizontal grid spacing ranging from 2.2 to 4 km covering all of the Third Pole region. These simulations are driven by ERA5 and are part of a Coordinated Regional Climate Downscaling EXperiment Flagship Pilot Study on Convection-Permitting Third Pole. The simulations are compared against available gridded and in-situ observations and remote-sensing data, to assess the performance and spread of the model ensemble compared to the driving reanalysis during the cold and warm seasons. Although ensemble evaluation is hindered by large differences between the gridded precipitation datasets used as a reference over this region, we show that the ensemble improves on many warm-season precipitation metrics compared with ERA5, including most wet-day and hour statistics, and also adds value in the representation of wet spells in both seasons. As such, the ensemble will provide an invaluable resource for future improvements in the process understanding of the hydroclimate of this remote but important region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Biogeochemical Cycling of Redox-Sensitive Elements in Permafrost-Affected Ecosystems

Northern high latitudes are experiencing rapid changes in climate that drive permafrost thaw and shifts in hydrology and soil saturation. These factors regulate redox conditions across permafrost-affected landscapes, potentially altering carbon storage in soils and exacerbating climate change through accelerated decomposition of soil organic matter. Redox conditions impact soil carbon storage directly by influencing rates and pathways of organic matter decomposition, and indirectly by moderating the bioavailability of organic molecules and nutrients. Indeed, the ability of increased plant growth to offset C losses in permafrost regions will be regulated by nutrient availability (e.g., N, P) that varies across redox gradients. The purpose of this review is to examine how redox conditions shape biogeochemical cycling of ecologically important elements (P, N, S, Fe) in permafrost-affected ecosystems. Although carbon cycling in these regions continues to be widely studied, relatively little information is available on the elements that regulate C cycling. We discuss the complex feedbacks between climate change, hydrology, and landscape change that control redox conditions, then examine how these factors regulate biogeochemical cycles. We identify key gaps in our understanding of how changing climate may alter biogeochemical cycles and carbon storage in northern high-latitude ecosystems.

Herndon, Elizabeth↗
DOE OSTI2023

Accelerating the Lagrangian Particle Tracking in Hydrologic Modeling to Continental-Scale

Unprecedented climate change and anthropogenic activities have induced increasing ecohydrological problems, which have motivated the development of large-scale modeling for solutions. Water age/quality is as important as water quantity for understanding the water cycle. However, current scientific progress in tracking water parcels at large-scale with high spatiotemporal resolutions is far behind that in water balance/quantity owing to the lack of powerful tools. EcoSLIM is a particle tracking model that works with the hydrologic model ParFlow-CLM, which couples surface-subsurface hydrology with land surface processes. Here, we demonstrate a parallel framework to accelerate EcoSLIM to continental-scale on a distributed, multi-GPU platform with CUDA-Aware MPI. In tests from catchment-, to regional-, and then to continental-scale using 25-million to 1.6-billion particles, EcoSLIM shows significant speedup and excellent parallel performance. The parallel framework is portable to atmospheric and oceanic particle tracking models, where parallelization is inadequate and a standard parallel framework is absent. Parallelized EcoSLIM is a promising tool to accelerate our understanding of the terrestrial water cycle and the upscaling of subsurface hydrology to Earth system models.

54 ENVIRONMENTAL SCIENCES↗