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DOE OSTI2020

Quantifying the drivers and predictability of seasonal changes in African fire

Africa contains some of the most vulnerable ecosystems to fires. Successful seasonal prediction of fire activity over these fire-prone regions remains a challenge and relies heavily on in-depth understanding of various driving mechanisms underlying fire evolution. Here, we assess the seasonal environmental drivers and predictability of African fire using the analytical framework of Stepwise Generalized Equilibrium Feedback Assessment (SGEFA) and machine learning techniques (MLTs). The impacts of sea-surface temperature, soil moisture, and leaf area index are quantified and found to dominate the fire seasonal variability by regulating regional burning condition and fuel supply. Compared with previously-identified atmospheric and socioeconomic predictors, these slowly evolving oceanic and terrestrial predictors are further identified to determine the seasonal predictability of fire activity in Africa. Our combined SGEFA-MLT approach achieves skillful prediction of African fire one month in advance and can be generalized to provide seasonal estimates of regional and global fire risk.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Time-series RNA metabarcoding of the active Populus tremuloides root microbiome reveals hidden temporal dynamics and dormant core members

The rhizosphere is a critical interface between plant roots and soil, harboring diverse microbial communities that are essential to plant and ecosystem health. Although these communities exhibit stark temporal dynamics, their dormancy/activity transitions remain poorly understood. Such transitions may enable microbes to rapidly adjust functional contributions faster than community turnover alone would allow. Here, we used RNA metabarcoding to characterize the active fraction of microbial communities on the roots of quaking aspen (Populus tremuloides) in a time-series study across a natural environmental gradient. We explore cryptic temporal microbial community dynamics of rhizosphere communities at the ecosystem scale. The active rhizosphere bacterial and fungal communities were more temporally dynamic than total communities, while total communities exhibited a stronger response to site-specific conditions. Notably, some core microbiome members were often inactive, yielding a smaller “active core” subset. The fungal endophyte Hyaloscypha finlandica was the only microbe that was both present and active in all plots across all timepoints. Soil temperature strongly influenced both total and active community composition, with the fungal class Eurotiomycetes showing a temperature-dependent seasonal decline in abundance. Together, these results reveal that modulation of microbial activity levels is a key mechanism by which the plant root holobiont responds to environmental variation, and that even dominant symbionts may frequently persist in dormancy within the rhizosphere.

Community Structure and Diversity↗

DOE OSTI2023

Why cutting respiratory CO 2 loss from crops is possible, practicable, and prudential

Abstract Plants release back to the atmosphere about half of the CO 2 they capture by photosynthesis. Decreasing the rate of crop respiration could therefore potentially increase yields, store more carbon in the soil and draw down atmospheric CO 2 . However, decreasing respiration rate has had very little research effort compared to increasing photosynthesis, the historically dominant metabolic paradigm for crop improvement. Conceptual and technical advances, particularly in protein turnover and directed enzyme evolution, have now opened ways to trim the large fraction of respiration that fuels proteome maintenance by lowering the breakdown and resynthesis rates of enzymes and other proteins. In addition to being theoretically possible and practicable, exploring the reduction of respiration is prudential, given that it (i) has barely yet been tried and (ii) could help meet the challenges of sustaining crop productivity and managing atmospheric carbon.

Joshi, Jaya↗

DOE OSTI2025

Historical land management alters new soil carbon inputs by annual and perennial bioenergy crops

Bioenergy and bioproduct markets are expanding to meet demand for climate friendly goods and services. Perennial biomass crops are particularly well suited for this goal because of their high yields, low input requirements, and potential to increase soil carbon (C). However, it is unclear how much C is allocated into belowground pools by perennial bioenergy crops and whether the belowground benefits vary with nitrogen (N) fertilizer inputs. Using in situ 13C pulse-chase labeling, we tested whether the sterile perennial grass Miscanthus × giganteus ( miscanthus ) or annual maize transfers more photosynthetic C to belowground pools. The experiment took place at two sites in Central and Northwest (NW) Iowa with different management histories and two nitrogen (N) fertilizer rates (0 and 224 kg N ha-1 yr-1) to determine if the fate of plant-derived soil C depends on soil fertility and crop type (perennial or annual). Maize allocated a greater percentage of total new 13C to roots than miscanthus, but miscanthus had greater new 13C in total and belowground plant biomass. We found strong interactions between site and most soil measurements – including new 13C in mineral and particulate soil organic matter (SOM) pools –which appear to be driven by differences in historical fertilizer management. The NW Iowa site, with a history of manure inputs, had greater plant-available nutrients (phosphorus, potassium, and ammonium) in soils, and resulted in less 13C from miscanthus in SOM pools compared to maize (approximately 64% less in POM and 70% less in MAOM). In more nutrient-limited soils (Central site), miscanthus transferred 4.5 times more 13C than maize to the more stable mineral-associated SOM pool. Our results suggest that past management, including historical manure inputs that affect a site’s soil fertility, can influence the net C benefits of bioenergy crops.

Keiser, Ashley [Stockbridge School of Agriculture,↗

DOE OSTI2020

Sustainability of soil organic carbon in consolidated gully land in China’s Loess Plateau

Massive gully land consolidation projects, launched in China’s Loess Plateau, aim to restore 2667 km 2 agricultural lands in total by consolidating 2026 highly eroded gullies. This effort represents a social engineering project where the economic development and livelihood of the farming families are closely tied to the ability of these emergent landscapes to provide agricultural services. Whether these ‘time zero’ landscapes have the resilience to provide a sustainable soil condition such as soil organic carbon (SOC) content remains unknown. By studying two watersheds, one of which is a control site, we show that the consolidated gully serves as an enhanced carbon sink, where the magnitude of SOC increase rate (1.0 gC/m 2 /year) is about twice that of the SOC decrease rate (-0.5 gC/m 2 /year) in the surrounding natural watershed. Over a 50-year co-evolution of landscape and SOC turnover, we find that the dominant mechanisms that determine the carbon cycling are different between the consolidated gully and natural watersheds. In natural watersheds, the flux of SOC transformation is mainly driven by the flux of SOC transport; but in the consolidated gully, the transport has little impact on the transformation. Furthermore, we find that extending the surface carbon residence time has the potential to efficiently enhance carbon sequestration from the atmosphere with a rate as high as 8 gC/m 2 /year compared to the current 0.4 gC/m 2 /year. The success for the completion of all gully consolidation would lead to as high as 26.67 GgC/year sequestrated into soils. This work, therefore, not only provides an assessment and guidance of the long-term sustainability of the ‘time zero’ landscapes but also a solution for sequestration CO 2 into soils.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

A genomic catalog of Earth’s microbiomes

Abstract The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2

Abstract. A new weakly coupled land data assimilation (WCLDA) system based on the four-dimensional ensemble variational (4DEnVar) method is developed and applied to the fully coupled Energy Exascale Earth System Model version 2 (E3SMv2). The dimension-reduced projection four-dimensional variational (DRP-4DVar) method is employed to implement 4DVar using the ensemble technique instead of the adjoint technique. With an interest in providing initial conditions for decadal climate predictions, monthly mean anomalies of soil moisture and temperature from the Global Land Data Assimilation System (GLDAS) reanalysis from 1980 to 2016 are assimilated into the land component of E3SMv2 within the coupled modeling framework with a 1-month assimilation window. The coupled assimilation experiment is evaluated using multiple metrics, including the cost function, assimilation efficiency index, correlation, root-mean-square error (RMSE), and bias, and compared with a control simulation without land data assimilation. The WCLDA system yields improved simulation of soil moisture and temperature compared with the control simulation, with improvements found throughout the soil layers and in many regions of the global land. In terms of both soil moisture and temperature, the assimilation experiment outperforms the control simulation with reduced RMSE and higher temporal correlation in many regions, especially in South America, central Africa, Australia, and large parts of Eurasia. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought, highlighting the crucial role of land surface in drought lifecycle. The WCLDA system is intended to be a foundational resource for research to investigate land-derived climate predictability.

58 GEOSCIENCES↗

DOE OSTI2020

A Genomic Catalogue of Earth’s Microbiomes - Introductory KBase Narrative

The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled unprecedented insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this powerful approach to over 10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, human- and animal-host associated microbiomes, engineered environments, and natural and agricultural soils to capture extant microbial metabolic and functional potential. We present a comprehensive catalogue of 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units (OTUs), spanning 135 phyla, which expand the known phylogenetic diversity of Bacteria and Archaea by 44%. We also demonstrate the utility of this collection for secondary metabolite biosynthetic potential and predicting host-virus linkage, which can provide a view into the global distribution of lysogenic viruses. This resource underscores the value of leveraging genome-centric approaches to reveal genomic properties of uncultivated microbes that impact on ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Modeling Efforts to Gain Insight into Historical Leak Events from the Single-Shell Tank A-105 in the Hanford 241-A Tank Farm - 20113

The 241-A Tank Farm is a single-shell tank (SST) farm constructed to store process waste from Hanford nuclear operations. Millions of gallons of nuclear waste were stored in the 241-A Tank Farm SSTs and some of the SSTs leaked in the past. In addition, spills and pipeline leaks during transfers and storage and intentional discharges to cribs and trenches resulted in releasing waste to the ground. Tank liner leaks are referred to as 'leaks' and all other discharges to the soil are referred to as 'releases.' Liquid waste that could be removed by pumping has been removed from all of the SSTs to reduce the potential for future leaks. The most significant historical leak event in 241-A Tank Farm occurred in 1965 when tank A-105 experienced a pressurized steam event. This event resulted in damage to the inner steel liner flooring of A-105, which was separated from the sidewalls over part of its circumference and buckled up to 2.5 m, vertically. During this event up to 7,570 L of contaminated liquid may have leaked to the adjacent soil. This leak occurred under extreme temperature and pressure conditions. Modeling efforts to better understand the nature and extent of historical leaks from subsurface SSTs that were used to store highly radioactive, self-boiling liquid wastes at 241-A Tank Farm have recently been undertaken. These efforts have compiled the available historical information to support a preliminary non-isothermal, multiphase flow and chemical transport modeling effort to re-create the conditions under which the leaks occurred and to formulate a conceptual model as to the extent and distribution of leaked radioactive contaminants in the adjacent soil material. The focus of this work was on developing an understanding of the key features, processes and bounding conditions related to tank A-105 leak events that occurred in the 1960's. The activities include estimation of leak composition, non-isothermal multiphase flow and transport modeling, and geochemical modeling. The STOMP{sup C} Water-Air-Energy modeling code was utilized to implement the three-dimensional representation of the subsurface tank and the surrounding flow field. Once constructed, the model was used to evaluate the conceptual understanding of leaks originating from different parts of the tank under the elevated temperature boundary conditions that were imposed by surrounding tanks at the time of the historical leaks. The chemical evolution of the liquid waste was also evaluated as it leaked from the tank under transient pressure and temperature gradients. The results of the preliminary evaluation suggested the presence of a heat-pipe effect beneath tank A-105 in which water vapor at an elevated temperature is driven away from the base of the tank to a position where water vapor cools, condenses and is then drawn back toward the tank by the strong capillary attraction of the dry soil. A non-sorbing contaminant (Tc-99) was introduced into this flow field to better understand the potential distribution patterns of leaked contaminants that may have occurred during the historical leak events. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Refining water and carbon fluxes modeling in terrestrial ecosystems via plant hydraulics integration

Plant hydraulics substantially affects terrestrial water and carbon cycles by modulating water transport and carbon assimilation. Despite improved drought simulations in certain ecosystems through their integration into land surface models (LSMs), the broader application of plant hydraulics in diverse ecosystems and hydroclimates is still underexplored. Here, in this study, we implemented the recently developed Noah-Multiparameterization Land Surface Model (Noah-MP LSM) equipped with a plant hydraulics scheme (Noah-MP-PHS) across 40 FLUXNET sites globally. Employing the Shuffled Complex Evolution-University of Arizona (SCE-UA) auto-calibration algorithm, we optimized key plant hydraulics parameters for these sites spanning eight vegetation types in both arid and humid climates. Noah-MP-PHS significantly improves the simulation of evapotranspiration (ET) and gross primary production (GPP) by better representing atmospheric and soil water stress compared to traditional soil hydraulic schemes (SHSs, such as Noah and CLM). The augmented Noah-MP-PHS models reduce surface flux overestimation and underestimation, exhibiting an average increase of 0.14 and 0.15 in Kling-Gupta Efficiency (KGE) compared to Noah and CLM, respectively. The explicit consideration of plant capacitance in PHS reveals substantial deep-layer and nocturnal root water uptake especially under dry conditions. We employed eXplainable Machine learning (XML) to quantify the model’s relative sensitivity to newly introduced leaf-, stem and root-related parameters in PHS. The sensitivity analysis reveals a rise in root parameter importance and a decline in leaf and stem parameters as conditions shift from humid to arid. These findings indicate that as aridity states vary, the most influential parameters affecting surface fluxes variation may change in parameter calibration for PHS applications. Our findings underscore the importance of incorporating plant hydraulics into LSMs to enhance simulations of terrestrial water and carbon dynamics. These findings are crucial for understanding ecosystem responses to global climate changes and guide the broader application of PHS at larger scales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Uncertainty characterization in a coupled human-natural system: Modeling agricultural adaptation in the Great Lakes Region

The Great Lakes Region's water quality and ecological health are threatened by the export of nutrients from agricultural lands, which causes eutrophication, hypoxia, and destructive algal blooms. The intensification of hydrologic cycles brought about by climate change is expected to exacerbate nutrient loading in the region, and, at the same time, agricultural adaptation to changing conditions is also expected to affect loading through shifting amounts and timing of fertilization. Quantifying these future effects and their interactions necessitates modeling both the human and natural processes as a coupled system, by pairing land use and agricultural management with hydrologic modeling. At the same time, compounding uncertainties arising from the complex interactions in both systems significantly limit our predictive understanding of the region's impacts. This study utilizes the Soil and Water Assessment Tool (SWAT), developed for simulating the impact of various farmer decisions on watershed functions in Western Lake Erie watersheds, and an under-development agent-based model (ABM) for agricultural management decisions. The aim of this study is to use global sensitivity analysis on the coupled ABM and SWAT models to quantify how uncertainty in both models interactively affects nutrient loading. To do so, we will conduct Sobol sensitivity analysis experiments at different levels of coupling assumptions to quantify how various uncertain factors (e.g., soil moisture and crop choice) and their interactions affect our estimates of nutrient loading. The results of this analysis will allow us to quantify how complex interactions and dependencies between both systems amplify the effect of uncertainties. Insights gained from this study will have broader implications for modeling the adaptive co-evolution of human and natural systems under climate change and can inform effective management of nutrient loading in the Great Lakes Region.

Climate Change↗

DOE OSTI2025

Community‐Level Metabolic Shifts Following Land Use Change in the Amazon Rainforest Identified by a Supervised Machine Leaning Approach

ABSTRACT The Amazon rainforest has been subjected to high rates of deforestation, mostly for pasturelands, over the last few decades. This change in plant cover is known to alter the soil microbiome and the functions it mediates, but the genomic changes underlying this response are still unresolved. In this study, we used a combination of deep shotgun metagenomics complemented by a supervised machine learning approach to compare the metabolic strategies of tropical soil microbial communities in pristine forests and long‐term established pastures in the Amazon. Machine learning‐derived metagenome analysis indicated that microbial community structures (bacteria, archaea and viruses) and the composition of protein‐coding genes were distinct in each plant cover type environment. Forest and pasture soils had different genomic diversities for the above three taxonomic groups, characterised by their protein‐coding genes. These differences in metagenome profiles in soils under forests and pastures suggest that metabolic strategies related to carbohydrate and energy metabolisms were altered at community level. Changes were also consistent with known modifications to the C and N cycles caused by long‐term shifts in aboveground vegetation and were also associated with several soil physicochemical properties known to change with land use, such as the C/N ratio, soil temperature and exchangeable acidity. In addition, our analysis reveals that these alterations in land use can also result in changes to the composition and diversity of the soil DNA virome. Collectively, our study indicates that soil microbial communities shift their overall metabolic strategies, driven by genomic alterations observed in pristine forests and long‐term established pastures with implications for the C and N cycles.

carbon and nitrogen cycles↗

DOE OSTI2025

Reviews and syntheses: Variable inundation across Earth's terrestrial ecosystems

Abstract. The structure, function, and dynamics of Earth's terrestrial ecosystems are profoundly influenced by how often (frequency) and how long (duration) they are inundated with water. A diverse array of natural and human-engineered systems experience temporally variable inundation whereby they fluctuate between inundated and non-inundated states. Variable inundation spans extreme events to predictable sub-daily cycles. Variably inundated ecosystems (VIEs) include hillslopes, non-perennial streams, wetlands, floodplains, temporary ponds, tidal systems, storm-impacted coastal zones, and human-engineered systems. VIEs are diverse in terms of inundation regimes, water chemistry and flow velocity, soil and sediment properties, vegetation, and many other properties. The spatial and temporal scales of variable inundation are vast, ranging from sub-meter to whole landscapes and from sub-hourly to multi-decadal. The broad range of system types and scales makes it challenging to predict the hydrology, biogeochemistry, ecology, and physical evolution of VIEs. Despite all experiencing the loss and gain of an overlying water column, VIEs are rarely considered together in conceptual, theoretical, modeling, or measurement frameworks and approaches. Studying VIEs together has the potential to generate mechanistic understanding that is transferable across a much broader range of environmental conditions, relative to knowledge generated by studying any one VIE type. We postulate that enhanced transferability will be important for predicting changes in VIE function in response to global change. Here we aim to catalyze cross-VIE science that studies drivers and impacts of variable inundation across Earth's VIEs. To this end, we complement expert mini-reviews of eight major VIE systems with overviews of VIE-relevant methods and challenges associated with scale. We conclude with perspectives on how cross-VIE science can derive transferable understanding via unifying conceptual models in which the impacts of variable inundation are studied across multi-dimensional environmental space.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Spatial and temporal prediction of radiation dose rates near Fukushima Daiichi Nuclear Power Plant

In this paper, we have developed a methodology to estimate the spatiotemporal distribution of radiation air dose rates around the Fukushima Daiichi Nuclear Power Plant (FDNPP). In our exploratory data analysis, we found that (1) the temporal evolution of dose rates is composed of a log-linear decay trend and fluctuations of air dose rates that are spatially correlated among adjacent monitoring posts; and (2) the slope of the log-linear environmental decay trend can be represented as a function of the apparent initial dose rates, coordinate position, land-use type, and soil type. From these observations, we first estimated the log-linear decay trend at each location based on these predictors, using the random forest method. We then developed a modified Kalman filter coupled with a Gaussian process model to estimate the dose-rate time series at a given location and time. We applied this method to the Fukushima evacuation zone (as of March 2017), which included 17 monitoring post locations (with monitoring datasets collected between 2014 and 2018) and generated a time series of dose-rate maps. Our results show that this approach allows us to produce accurate spatial and temporal predictions of radiation dose-rate maps using limited spatiotemporal measurements.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2024

Nitrogen Deposition Weakens Soil Carbon Control of Nitrogen Dynamics Across the Contiguous United States

ABSTRACT Anthropogenic nitrogen (N) deposition is unequally distributed across space and time, with inputs to terrestrial ecosystems impacted by industry regulations and variations in human activity. Soil carbon (C) content normally controls the fraction of mineralized N that is nitrified ( ƒ nitrified ), affecting N bioavailability for plants and microbes. However, it is unknown whether N deposition has modified the relationships among soil C, net N mineralization, and net nitrification. To test whether N deposition alters the relationship between soil C and net N transformations, we collected soils from coniferous and deciduous forests, grasslands, and residential yards in 14 regions across the contiguous United States that vary in N deposition rates. We quantified rates of net nitrification and N mineralization, soil chemistry (soil C, N, and pH), and microbial biomass and function (as beta‐glucosidase (BG) and N ‐acetylglucosaminidase (NAG) activity) across these regions. Following expectations, soil C was a driver of ƒ nitrified across regions, whereby increasing soil C resulted in a decline in net nitrification and ƒ nitrified . The ƒ nitrified value increased with lower microbial enzymatic investment in N acquisition (increasing BG:NAG ratio) and lower active microbial biomass, providing some evidence that heterotrophic microbial N demand controls the ammonium pool for nitrifiers. However, higher total N deposition increased ƒ nitrified , including for high soil C sites predicted to have low ƒ nitrified , which decreased the role of soil C as a predictor of ƒ nitrified . Notably, the drop in contemporary atmospheric N deposition rates during the 2020 COVID‐19 pandemic did not weaken the effect of N deposition on relationships between soil C and ƒ nitrified . Our results suggest that N deposition can disrupt the relationship between soil C and net N transformations, with this change potentially explained by weaker microbial competition for N. Therefore, past N inputs and soil C should be used together to predict N dynamics across terrestrial ecosystems.

Nieland, Matthew A. [Stockbridge School of Agricul↗

DOE OSTI2020

Implications of End Points on Remediation - 20476

The Port Hope Area Initiative (PHAI) is a federal environmental clean-up program. Its mandate is the remediation and local, long-term, safe management of approximately 1.7 million cubic metres of historic low-level radioactive waste in the adjacent communities of Port Hope and Port Granby in Southern Ontario, Canada. The PHAI is being undertaken by Canadian Nuclear Laboratories (CNL), on behalf of Atomic Energy of Canada Limited, a federal Crown corporation. It is currently one of the largest environmental remediation projects in Canada. The safety of workers, the public and the environment while delivering the PHAI compliantly, on time and within budget is CNL's number one priority. The PHAI is being implemented as two projects - the Port Hope Project and the Port Granby Project. The Port Hope Project is the larger of the two and includes the cleanup of approximately 1.2 million cubic metres of historic waste. The Port Hope Project includes a unique and important component - the remediation of approximately 1,200 private residences and businesses to include both interior and exterior verification of soil and surface-contaminated objects. Planning and consultation for the PHAI clean-up criteria and remediation verification standard operating procedures (RVSOP) were initiated in the early 2000's. The criteria were developed through a cooperative effort involving the PHAI, scientific specialists, federal and provincial government agencies, peer reviewers, the municipalities and members of the public. Subsequent verification procedures which detail the unique systematic methods to verify compliance with the clean-up criteria were developed by CNL in consultation with federal regulators and relevant stakeholders. Now, specifically with the Port Hope Small-Scale Sites project having been underway for a year and approximately 38 properties in some stage of remediation, it has become increasingly evident that the practical application of the clean-up criteria and RVSOP methodology is posing unique challenges that are having direct impact on project execution. The current RVSOP approach is based on discrete sample verification not allowing failure of any one sample. When implemented in the field, particularly at the Small-Scale Sites, it leads to a much more extensive excavation than what was accounted for in the original design, the implications of which are substantial delays in project progress and much more significant impact on the individual properties than originally anticipated. This paper will examine the evolution of PHAI clean-up criteria, subsequent RVSOP methodology and its impact on current project execution and the justification for exploring potential revisions to methods of remediation verification. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Coupled THM modeling of bentonite heating and hydration in tank tests with a new temperature-dependent water retention model

This study presents a coupled thermo-hydro-mechanical (THM) model for simulating the heating and hydration behavior of bentonite, a buffer material in deep geological repositories (DGRs). The model incorporates a new temperature-dependent soil water retention curve which captures the thermal-induced shift in water retention behavior. It also distinguishes between liquid and gas permeability, modeling intrinsic gas permeability as a function of accessible porosity to improve vapor transport and desaturation predictions. The model was validated against two large-scale tank tests, demonstrating good agreement with measured temperature, relative humidity, and water inflow data. It revealed a complex porosity evolution driven by thermal expansion, vapor movement, vapor condensation, and hydration-induced swelling during heating and hydration processes. The simulation results also suggest that the permeability of the hydration layer plays a critical role in controlling water intake. Clogging of this layer can significantly reduce the volume of water inflow during the hydration phase. Furthermore, while the model effectively captures key THM behavior, further development of the mechanical constitutive law is required to account for possible thermo-elasto-plastic volume changes and microstructural effects. Overall, the model provides a robust tool for evaluating the evolution of bentonite-based barrier material in DGRs.

Guo, Guanlong [Lawrence Berkeley National Laborato↗

DOE OSTI2022

Multi-modelling predictions show high uncertainty of required carbon input changes to reach a 4‰ target

Soils store vast amounts of carbon (C) on land, and increasing soil organic carbon (SOC) stocks in already managed soils such as croplands may be one way to remove C from the atmosphere, thereby limiting subsequent warming. The main objective of this study was to estimate the amount of additional C input needed to annually increase SOC stocks by 4‰ at 16 long-term agricultural experiments in Europe, including exogenous organic matter (EOM) additions. We used an ensemble of six SOC models and ran them under two configurations: (1) with default parametrization and (2) with parameters calibrated site-by-site to fit the evolution of SOC stocks in the control treatments (without EOM). We compared model simulations and analysed the factors generating variability across models. The calibrated ensemble was able to reproduce the SOC stock evolution in the unfertilised control treatments. We found that, on average, the experimental sites needed an additional 1.5 ± 1.2 Mg C ha -1 year -1 to increase SOC stocks by 4‰ per year over 30 years, compared to the C input in the control treatments (multi-model median ± median standard deviation across sites). That is, a 119% increase compared to the control. While mean annual temperature, initial SOC stocks and initial C input had a significant effect on the variability of the predicted C input in the default configuration (i.e., the relative standard deviation of the predicted C input from the mean), only water-related variables (i.e., mean annual precipitation and potential evapotranspiration) explained the divergence between models when calibrated. Here, our work highlights the challenge of increasing SOC stocks in agriculture and accentuates the need to increasingly lean on multi-model ensembles when predicting SOC stock trends and related processes. To increase the reliability of SOC models under future climate change, we suggest model developers to better constrain the effect of water-related variables on SOC decomposition.

4 per 1000 initiative↗