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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Mountainous Floodplain Connectivity in Response to Hydrological Transitions

In mountainous watersheds, floodplain sediments are typically characterized by gravel bed layers capped by an overlying soil unit that serves as a hotspot for biogeochemical reactivity. However, the influence of soil biogeochemistry on gravel bed underflow composition remains unclear, especially during hydrological transitions that alter the vertical connectivity between overlaying soils and the underlying gravel bed. This study investigates these dynamics by measuring hydraulic gradients and water compositions over three hydrological years in a typical mountainous, low-order stream floodplain in the Upper Colorado River Basin. Results indicate that the timing of hydrological conditions strongly influences the vertical exchanges that control water quality. Specifically, during flooding events such as beaver ponding, that induce downward flushing of the soil, anoxic conditions prevalent in the biogeochemically active soil are transferred downstream via gravel bed underflow. Conversely, snowmelt and drought conditions increase oxic conditions in the gravel bed due to diminished hydrological connectivity with the overlying soil. To compare water quality response to hydrological transitions across similar floodplain environments, we propose a conceptual model that quantifies the inundation-induced flushing of soil porewater to measure solute exchange efficiency with the gravel bed solute convergence efficiency (SCE). This model provides a framework for quantifying biogeochemical processes in hydrological underflow systems, which is critical for water and elemental budgets in these globally important mountainous ecosystems.

58 GEOSCIENCES↗
DOE OSTI2026

Small Reservoirs Offer a New Perspective on Flood Reduction in Large Basins

The flood reduction potential of individual reservoirs within a large river network continuum remains poorly understood due to the complex interplay between reservoir characteristics and network properties. Here we investigate whether a collection of relatively small reservoirs can play a significant role in mediating downstream floods and assess how that role may be influenced by reservoir network properties compared to traditionally known reservoir characteristics. Our unique contribution was the simulation of downstream flood inundation maps alongside peak flows for each of the 81 major reservoirs (6 × 104 to 8 × 109 m3) across 15,000 river reach segments, integrated into a process-based hydrologic model covering a 415,000 km2 region in the Texas Gulf Coast, United States. The three key takeaways from our study are as follows. (a) Smaller reservoirs can substantially reduce downstream flooding, suggesting that inclusion of large reservoirs—the traditional approach in flood risk management studies—may present only a partial picture. (b) Flood reduction by smaller reservoirs is more effective upstream, although this phenomenon may be linked with aridity and overall water availability. (c) While reservoir size matters, it is not the primary factor determining its downstream flood reduction potential; the influence of network properties, such as catchment area, the count of upstream reservoirs, the cumulative maximum storage capacity of upstream reservoirs, and Stream Order (i.e., location), is equally and often more important. The broader impact of our findings goes beyond just floods, providing foundational insights for addressing emerging challenges such as aging dams and river connectivity.

Patel, Krutikkumar [University of Texas at Arlingt↗
DOE OSTI2026

Emergent constraints on future methane emissions from global wetlands

Future methane (CH 4 ) emissions from natural wetlands are predicted to increase due to global warming, leading to positive feedback on climate change. However, the magnitude of this increase remains highly uncertain. Here we present novel ensemble simulations of seven state-of-the-art terrestrial biosphere models to estimate wetland CH 4 emissions (eCH 4 ) during the twenty-first century. Our estimates suggest that for every 1 °C increase in global land surface temperature, there is a 24 ± 10 Tg CH 4 yr −1 increase in eCH 4 . We also identify an emergent relationship between contemporary temperature dependence and projected eCH 4 . When constrained by 163 site-year eddy-covariance measurements of eCH 4 , we show that wetland emissions can increase by 50–60% by the 2090s relative to the 2010s under a high-warming scenario. The projected decadal increase in eCH 4 from the 2010–2019 baseline to the 2030s would very likely (90% probability) offset an amount equivalent in scale to 8–10% of anthropogenic eCH 4 at the 2020 level, comparable to the reductions committed under the Global Methane Pledge. However, the constraint is dominated by mid- and high-latitude observations, with limited tropical coverage, and uncertainties in projected wetland inundation contribute substantially to uncertainty in eCH 4 . Our findings reduce the uncertainty in projected wetland methane–climate feedback and highlight its potential impacts on methane mitigation efforts to slow global warming.

Zhang, Zhen [Chinese Academy of Sciences (CAS), Be↗
DOE OSTI2021

Uranium carbonate complexes demonstrate drastic decrease in stability at elevated temperatures

Quantitative understanding of uranium transport by high temperature fluids is crucial for confident assessment of its migration in a number of natural and artificially induced contexts, such as hydrothermal uranium ore deposits and nuclear waste stored in geological repositories. An additional recent and atypical context would be the seawater inundated fuel of the Fukushima Daiichi Nuclear Power Plant. Given its wide applicability, understanding uranium transport will be useful regardless of whether nuclear power finds increased or decreased adoption in the future. The amount of uranium that can be carried by geofluids is enhanced by the formation of complexes with inorganic ligands. Carbonate has long been touted as a critical transporting ligand for uranium in both ore deposit and waste repository contexts. However, this paradigm has only been supported by experiments conducted at ambient conditions. We have experimentally evaluated the ability of carbonate-bearing fluids to dissolve (and therefore transport) uranium at high temperature, and discovered that in fact, at temperatures above 100 °C, carbonate becomes almost completely irrelevant as a transporting ligand. This demands a re-evaluation of a number of hydrothermal uranium transport models, as carbonate can no longer be considered key to the formation of uranium ore deposits or as an enabler of uranium transport from nuclear waste repositories at elevated temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Modeling separation of lanthanides via heterogeneous ligand binding

Individual lanthanide elements have physical/electronic/magnetic properties that make each useful for specific applications. Several of the lanthanides cations (Ln 3+ ) naturally occur together in the same ores. They are notoriously difficult to separate from each other due to their chemical similarity. Predicting the Ln 3+ differential binding energies (ΔΔE) or free energies (ΔΔG) at different binding sites, which are key figures of merit for separation applications, will help design of materials with lanthanide selectivity. We apply ab initio molecular dynamics (AIMD) simulations and density functional theory (DFT) to calculate ΔΔG for Ln 3+ coordinated to ligands in water and embedded in metal–organic frameworks (MOFs), and ΔΔE for Ln 3+ bonded to functionalized silica surfaces, thus circumventing the need for the computational costly absolute binding (free) energies ΔG and ΔE. Perturbative AIMD simulations of water-inundated simulation cells are applied to examine the selectivity of ligands towards adjacent Ln 3+ in the periodic table. Static DFT calculations with a full Ln 3+ first coordination shell, while less rigorous, show that all ligands examined with net negative charges are more selective towards the heavier lanthanides than a charge-neutral coordination shell made up of water molecules. Amine groups are predicted to be poor ligands for lanthanide-binding. Finally, we also address cooperative ion binding, i.e., using different ligands in concert to enhance lanthanide selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Scenario Generation for Built Environment Decision Support under Uncertainty: Case Studies of Airflow Modeling and Climate-Resilient Infrastructure System Design

When confronted with unforeseen challenges, practicing informed decision making is crucial for enhancing resilience in the built environment. While scan-to-building information modeling (BIM) is a well-established approach for creating detailed digital representations of physical assets, its application in assessing and improving infrastructure resilience remains underexplored. This study addresses this gap by proposing a novel application of scan-to-BIM, namely, scan-to-BIM-to-digital twin (S-BIM-DT) workflow. By integrating reality capture and digital twin technologies, this workflow creates continuously updated and accurate digital representations of physical assets, enabling the generation of various scenarios. Unlike traditional methods, the S BIM-DT workflow facilitates continuous model refinement, supporting informed resilience strategies. By combining these technologies into a cohesive process, the workflow facilitates decision making under uncertainty, enabling stakeholders to evaluate and respond to various scenarios effectively. We demonstrate the implementation of the S-BIM-DT workflow through two use cases that highlight its capability to enhance resilience at different scales. The first use case involves the Combined Transportation, Emergency, and Communications Center (CTECC) in Austin, Texas. BIM-enriched computational fluid dynamics (CFD) modeling simulates airflow and develops alternative scenarios for optimizing the heating, ventilation, and air conditioning (HVAC) systems. This approach enhances resilience against airborne health threats in a postCOVID context. The second use case focuses on designated areas within Beaumont, Texas, as part of the Southeast Texas Urban Integrated Field Laboratory (SETx-UIFL) research. By developing inundation maps to assess extreme weather events, this modeling aids in preparedness efforts and informs the development of climate-resilient infrastructure in vulnerable neighborhoods. Results indicate that the S-BIM-DT workflow effectively generates scenarios that enhance resilience in the built environment by facilitating informed decision making. Furthermore, this study serves as a bridge between advanced scan-to-BIM methodologies and the practical strategies needed to improve built infrastructure resilience.

Built environment↗
DOE OSTI2025

Short-term experimental flooding impacts soil biogeochemistry but not aboveground vegetation in a coastal forest

Rising sea levels and intensifying storms increase flooding pressure on coastal forests, triggering tree mortality, ecosystem transitions, and changes to the coastal carbon cycle. However, the mechanisms that drive coastal forest mortality remain elusive due to the complex interplay between belowground and aboveground processes during flooding disturbances and limitations of observations typically reported in coastal forest mortality studies. We used an ecosystem-scale manipulation to simulate hurricane-level flooding of a coastal forest and explore the individual and interactive impacts of inundation and salinity. Monitoring real-time soil conditions and tree physiological responses, we observed consistent impacts on soil biogeochemistry aligned with belowground drivers of tree mortality, but no consistent responses in aboveground vegetation immediately following flooding. Our findings provide empirically based insight into the earliest stages of a hypothesized forest mortality spiral and offer critical benchmarks for predicting coastal forest resilience in the face of accelerating climate change.

coastal forests↗
DOE OSTI2025

Advancements and opportunities to improve bottom–up estimates of global wetland methane emissions

Wetlands are the single largest natural source of atmospheric methane (CH 4 ), contributing approximately 30% of total surface CH 4 emissions, and they have been identified as the largest source of uncertainty in the global CH 4 budget based on the most recent Global Carbon Project CH 4 report. High uncertainties in the bottom–up estimates of wetland CH 4 emissions pose significant challenges for accurately understanding their spatiotemporal variations, and for the scientific community to monitor wetland CH 4 emissions from space. In fact, there are large disagreements between bottom–up estimates versus top–down estimates inferred from inversion of atmospheric CH 4 concentrations. To address these critical gaps, we review recent development, validation, and applications of bottom–up estimates of global wetland CH 4 emissions, as well as how they are used in top–down inversions. These bottom–up estimates, using (1) empirical biogeochemical modeling (e.g. WetCHARTs: 125–208 TgCH 4 yr -1 ); (2) process-based biogeochemical modeling (e.g. WETCHIMP: 190 ± 39 TgCH 4 yr -1 ); and (3) data-driven machine learning approach (e.g. UpCH4: 146 ± 43 TgCH 4 yr -1 ). Bottom–up estimates are subject to significant uncertainties (~80 Tg CH 4 yr -1 ), and the ranges of different estimates do not overlap, further amplifying the overall uncertainty when combining multiple data products. These substantial uncertainties highlight gaps in our understanding of wetland CH 4 biogeochemistry and wetland inundation dynamics. Major tropical and arctic wetland complexes are regional hotspots of CH 4 emissions. However, the scarcity of satellite data over the tropics and northern high latitudes offer limited information for top–down inversions to improve bottom–up estimates. Recent advances in surface measurements of CH 4 fluxes (e.g. FLUXNET-CH 4 ) across a wide range of ecosystems including bogs, fens, marshes, and forest swamps provide an unprecedented opportunity to improve existing bottom–up estimates of wetland CH 4 estimates. We suggest that continuous long-term surface measurements at representative wetlands, high fidelity wetland mapping, combined with an appropriate modeling framework, will be needed to significantly improve global estimates of wetland CH 4 emissions. There is also a pressing unmet need for fine-resolution and high-precision satellite CH 4 observations directed at wetlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Projecting U.S. coastal storm surge risks and impacts with deep learning

Storm surge is one of the deadliest hazards posed by tropical cyclones (TCs), yet assessing its current and future risk is difficult due to the phenomenon’s rarity and physical complexity. Recent advances in artificial intelligence applications to natural hazard modeling suggest a new avenue for addressing this problem. We develop a deep learning storm surge model to efficiently estimate coastal surge risk in the United States from 900 000 synthetic TC events, accounting for projected changes in TC behavior and sea levels. The derived historical 100 year surge (the event with a 1% yearly exceedance probability) agrees well with historical observations and other modeling techniques. When coupled with an inundation model, we find that heightened TC intensities and sea levels by the end of the century result in a 50% increase in population at risk. Key findings include markedly heightened risk in Florida, and critical thresholds identified in Georgia and South Carolina.

RAFT↗
DOE OSTI2025

Comparing multi-source urban flood indicators: satellite, simulation, and citizen-reported data

Urban flooding arises from complex mechanisms, making it challenging to capture accurately with a single detection method. This study evaluates three complementary approaches to detect flooding across three Chicago neighborhoods: (i) Sentinel-1 synthetic aperture radar (SAR), offering weather-independent, high-resolution (10 m) imagery of surface inundation; (ii) the storm water management model (SWMM), simulating combined sewer overflow and drainage performance; and (iii) citizen-generated 311 service requests, capturing observed flooding impacts. By analyzing six storms ranging from severe to mild, we examine how each source uniquely contributes to identifying urban flood events. SAR imagery effectively identifies standing water but can miss brief flooding due to satellite revisit constraints. SWMM provides detailed insights into system-wide drainage behavior yet may underestimate localized street-level flooding. Meanwhile, 311 calls reflect real-world flooding impacts but are vulnerable to underreporting. Statistical overlap analysis highlights chronic flood hotspots repeatedly identified across multiple detection methods, indicating persistent infrastructure and topographic vulnerabilities. Temporal analysis further reveals that while SWMM flooding aligns closely with rainfall peaks, 311 calls typically precede or persist beyond these peaks. Our findings emphasize the value of using satellite observations, hydrological modeling, and resident-reported data in a complementary manner to better interpret patterns in flood timing, severity, and spatial distribution—providing insights that can inform targeted infrastructure improvements and contribute to urban flood resilience planning.

311↗
DOE OSTI2023

Plants use molecular mechanisms mediated by biomolecular condensates to integrate environmental cues with development

This review highlights recent literature on biomolecular condensates in plant development and discusses challenges for fully dissecting their functional roles. Plant developmental biology has been inundated with descriptive examples of biomolecular condensate formation, but it is only recently that mechanistic understanding has been forthcoming. Here, we discuss recent examples of potential roles biomolecular condensates play at different stages of the plant life cycle. We group these examples based on putative molecular functions, including sequestering interacting components, enhancing dwell time, and interacting with cytoplasmic biophysical properties in response to environmental change. We explore how these mechanisms could modulate plant development in response to environmental inputs and discuss challenges and opportunities for further research into deciphering molecular mechanisms to better understand the diverse roles that biomolecular condensates exert on life.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Variation in Flooding Tolerance in Populus deltoides ‘D-124’ and P. trichocarpa x P. deltoides Hybrid ‘52–225’

Flooding poses a substantial challenge to plant survival and productivity, particularly in riparian genus like Populus. This study examines the physiological, morphological, metabolic, and molecular responses of Populus deltoides ‘D-124’ and P. trichocarpa x P. deltoides hybrid clone ‘52–225’ under control and inundated conditions to identify differences in flooding tolerance. Under flooding conditions, physiological and cellular stress was more pronounced in P. deltoides ‘D-124’ than in the hybrid clone ‘52–225,’ as evidenced by lower transpiration (E), photosynthesis (A), and chlorophyll content. In contrast, ‘52–225’ showed reduced ROS accumulation suggesting better cellular function under stress. Morphologically, ‘52–225’ produced more shoot-born roots, which likely enhance oxygen transport and metabolic activity during flooding. Metabolite profiling revealed both overlapping and distinct patterns of sugar and amino acid accumulation between genotypes. Gene expression analysis revealed that flooding-responsive genes, including ALCOHOL DEHYDROGENASE 1 and HYPOXIA RESPONSIVE ERF 2, were activated in both genotypes, with a more pronounced response noted in ‘52–225.’ These findings extend our understanding of flooding tolerance mechanisms in Populus by connecting physiological traits, stress responses, and genetic regulation. This research contributes to the development of more flooding-resilient poplar varieties, with potential applications in breeding and restoration programs for flooding-prone environments.

Flooding stress↗
DOE OSTI2020

Total ecosystem carbon stocks at the marine-terrestrial interface: Blue carbon of the Pacific Northwest Coast, United States

The coastal ecosystems of temperate North America provide a variety of ecosystem services including high rates of carbon sequestration. Yet, little data exist for the carbon stocks of major tidal wetland types in the Pacific Northwest, United States. We quantified the total ecosystem carbon stocks (TECS) in seagrass, emergent marshes, and forested tidal wetlands, occurring along increasing elevation and decreasing salinity gradients. The TECS included the total aboveground carbon stocks and the entire soil profile (to as deep as 3 m). TECS significantly increased along the elevation and salinity gradients: 217 ± 60 Mg C/ha for seagrass (low elevation/high salinity), 417 ± 70 Mg C/ha for low marsh, 551 ± 47 Mg C/ha for high marsh, and 1,064 ± 38 Mg C/ha for tidal forest (high elevation/low salinity). Soil carbon stocks accounted for >98% of TECS in the seagrass and marsh communities and 78% in the tidal forest. Soils in the 0–100 cm portion of the profile accounted for only 48%–53% of the TECS in seagrasses and marshes and 34% of the TECS in tidal forests. Thus, the commonly applied limit defining TECS to a 100 cm depth would greatly underestimate both carbon stocks and potential greenhouse gas emissions from land-use conversion. The large carbon stocks coupled with other ecosystem services suggest value in the conservation and restoration of temperate zone tidal wetlands through climate change mitigation strategies. However, the findings suggest that long-term sea level rise effects such as tidal inundation and increased porewater salinity will likely decrease ecosystem carbon stocks in the absence of upslope wetland migration buffer zones.

Kauffman, J Boone↗
DOE OSTI2023

Abrupt permafrost thaw drives spatially heterogeneous soil moisture and carbon dioxide fluxes in upland tundra

Permafrost thaw causes the seasonally thawed active layer to deepen, causing the Arctic to shift toward carbon release as soil organic matter becomes susceptible to decomposition. Ground subsidence initiated by ice loss can cause these soils to collapse abruptly, rapidly shifting soil moisture as microtopography changes and also accelerating carbon and nutrient mobilization. The uncertainty of soil moisture trajectories during thaw makes it difficult to predict the role of abrupt thaw in suppressing or exacerbating carbon losses. Here, in this study, we investigated the role of shifting soil moisture conditions on carbon dioxide fluxes during a 13-year permafrost warming experiment that exhibited abrupt thaw. Warming deepened the active layer differentially across treatments, leading to variable rates of subsidence and formation of thermokarst depressions. In turn, differential subsidence caused a gradient of moisture conditions, with some plots becoming consistently inundated with water within thermokarst depressions and others exhibiting generally dry, but more variable soil moisture conditions outside of thermokarst depressions. Experimentally induced permafrost thaw initially drove increasing rates of growing season gross primary productivity (GPP), ecosystem respiration (R eco ), and net ecosystem exchange (NEE) (higher carbon uptake), but the formation of thermokarst depressions began to reverse this trend with a high level of spatial heterogeneity. Plots that subsided at the slowest rate stayed relatively dry and supported higher CO 2 fluxes throughout the 13-year experiment, while plots that subsided very rapidly into the center of a thermokarst feature became consistently wet and experienced a rapid decline in growing season GPP, R eco , and NEE (lower carbon uptake or carbon release). These findings indicate that Earth system models, which do not simulate subsidence and often predict drier active layer conditions, likely overestimate net growing season carbon uptake in abruptly thawing landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Upland forest retreat lags behind sea‐level rise in the mid‐Atlantic coast

Abstract Ghost forests consisting of dead trees adjacent to marshes are striking indicators of climate change, and marsh migration into retreating coastal forests is a primary mechanism for marsh survival in the face of global sea‐level rise. Models of coastal transgression typically assume inundation of a static topography and instantaneous conversion of forest to marsh with rising seas. In contrast, here we use four decades of satellite observations to show that many low‐elevation forests along the US mid‐Atlantic coast have survived despite undergoing relative sea‐level rise rates (RSLRR) that are among the fastest on Earth. Lateral forest retreat rates were strongly mediated by topography and seawater salinity, but not directly explained by spatial variability in RSLRR, climate, or disturbance. The elevation of coastal tree lines shifted upslope at rates correlated with, but far less than, contemporary RSLRR. Together, these findings suggest a multi‐decadal lag between RSLRR and land conversion that implies coastal ecosystem resistance. Predictions based on instantaneous conversion of uplands to wetlands may therefore overestimate future land conversion in ways that challenge the timing of greenhouse gas fluxes and marsh creation, but also imply that the full effects of historical sea‐level rise have yet to be realized.

Biodiversity & Conservation↗
DOE OSTI2024

Methane fluxes in tidal marshes of the conterminous United States

Abstract Methane (CH 4 ) is a potent greenhouse gas (GHG) with atmospheric concentrations that have nearly tripled since pre‐industrial times. Wetlands account for a large share of global CH 4 emissions, yet the magnitude and factors controlling CH 4 fluxes in tidal wetlands remain uncertain. We synthesized CH 4 flux data from 100 chamber and 9 eddy covariance (EC) sites across tidal marshes in the conterminous United States to assess controlling factors and improve predictions of CH 4 emissions. This effort included creating an open‐source database of chamber‐based GHG fluxes ( https://doi.org/10.25573/serc.14227085 ). Annual fluxes across chamber and EC sites averaged 26 ± 53 g CH 4 m −2 year −1 , with a median of 3.9 g CH 4 m −2 year −1 , and only 25% of sites exceeding 18 g CH 4 m −2 year −1 . The highest fluxes were observed at fresh‐oligohaline sites with daily maximum temperature normals (MATmax) above 25.6°C. These were followed by frequently inundated low and mid‐fresh‐oligohaline marshes with MATmax ≤25.6°C, and mesohaline sites with MATmax >19°C. Quantile regressions of paired chamber CH 4 flux and porewater biogeochemistry revealed that the 90th percentile of fluxes fell below 5 ± 3 nmol m −2 s −1 at sulfate concentrations >4.7 ± 0.6 mM, porewater salinity >21 ± 2 psu, or surface water salinity >15 ± 3 psu. Across sites, salinity was the dominant predictor of annual CH 4 fluxes, while within sites, temperature, gross primary productivity (GPP), and tidal height controlled variability at diel and seasonal scales. At the diel scale, GPP preceded temperature in importance for predicting CH 4 flux changes, while the opposite was observed at the seasonal scale. Water levels influenced the timing and pathway of diel CH 4 fluxes, with pulsed releases of stored CH 4 at low to rising tide. This study provides data and methods to improve tidal marsh CH 4 emission estimates, support blue carbon assessments, and refine national and global GHG inventories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Assessing the Role of Hydrodynamics in Enhancing Height-Above-the-Nearest-Drainage Derived Synthetic Rating Curves: A Comparative Study in the Wu River Basin, Taiwan

The conventional approach to generating synthetic rating curves (SRC) using the Height-Above-the-Nearest-Drainage (HAND) method typically relies on the assumption of uniform flow, such as Manning's equation, to establish stage-discharge ratings. The zero-physics application of the uniform flow equation is insufficient for capturing detailed hydraulic features (e.g., backwater effect) and neglects the hydraulic effects from adjacent channels. This lack of hydrodynamic computation can impact the accuracy and effectiveness of riverine flood risk estimation and management. To reduce this foreseeable error, we introduce the HAND-hd workflow, which integrates sophisticated hydrodynamic computations in the production of HAND-based SRC with hydrodynamic features (SRC hd ). The results indicate that SRC hd demonstrates consistent agreement with both gauge observations and benchmark solutions. Additionally, the comparative analysis suggests that SRC hd provides notable improvements in stage-discharge ratings over conventional HAND-based SRCs, particularly in channels with mild bed gradients, where it reduces water stage prediction errors and percent biases. In steeper channel segments, SRC hd maintains comparable accuracy to conventional methods. The comprehensive evaluation in this study emphasizes the potential discrepancies and inaccuracies associated with the adoption of the uniform flow assumption in the conventional HAND-SRCs and addresses the necessity of including hydrodynamic physics in the application of HAND-based SRC (e.g., inundation map) in channels with mild gradients.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Model Organisms To Study Methanogenesis, a Uniquely Archaeal Metabolism

Methanogenic archaea are the only organisms that produce CH 4 as part of their energy-generating metabolism. They are ubiquitous in oxidant-depleted, anoxic environments such as aquatic sediments, anaerobic digesters, inundated agricultural fields, the rumen of cattle, and the hindgut of termites, where they catalyze the terminal reactions in the degradation of organic matter. Methanogenesis is the only metabolism that is restricted to members of the domain Archaea. Here, we discuss the importance of model organisms in the history of methanogen research, including their role in the discovery of the archaea and in the biochemical and genetic characterization of methanogenesis. Finally, we also discuss outstanding questions in the field and newly emerging model systems that will expand our understanding of this uniquely archaeal metabolism.

59 BASIC BIOLOGICAL SCIENCES↗