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At least 703 records · Page 39

SPRUCE Quantitative PCR (qPCR) of Microbial Gene Copy Numbers, 2021-2022

This dataset provides the results for quantitative polymerase chain reaction (qPCR) of peat samples collected from ambient and experimental plots in the Spruce and Peatland Responses Under Climatic and Environmental Change (SPRUCE) experiment site in June and August of 2021, and June of 2022. SPRUCE is located within the Marcell Experimental Forest in northern Minnesota, USA. The dataset includes bacterial, archaeal, fungal gene copy numbers, along with corresponding logarithmic values, at 11 depth increments of two-meter deep peat cores taken from 12 sampling sites locations inside SPRUCE plots (10 chambered and 2 ambient plots). The sampling, sample prep and analysis followed standard methods outlined in prior publications (Wilson et al. 2016; Kluber et al. 2020) except that a higher yielding Omega Bio-Tek Mag-Bind Environmental DNA 96 Kit was used for extractions and DNA was quantified using Qubit dsDNA High Sensitivity Assay Kit. qPCR subsamples of peat cores from the SPRUCE plots characterize changes in the abundance and composition of microbial communities of peat seasonally showing how composition varies under multiple levels of experimental peat warming and atmospheric CO2 concentrations. This dataset contains one data file in comma-separated values (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma-separated values (.csv) format and a user guide in PDF (*.pdf) format. On 2026-07-07 this dataset was updated to add three columns to the data file: ‘Fungal_copy_dry’, ‘Log_fungal_copy_dry’, ‘Fungal_copy_wet’. No previously released data values were altered. Additionally, the abstract, data dictionary, and user guide were updated, and a file-level metadata file was added.

Archaea↗

Triso Analysis Tool For Predictive Source Terms

Source term modeling for TRi-structural ISOtropic (TRISO) fuel has been performed for previous reactor designs, but few are available in the open literature. Thus, there is a need to develop a simple, versatile, and mechanistic model of fission product release and transport in gas reactor cores that can be applied to a variety of reactors through user inputs and reactor-specific radionuclide inventories. To meet this need, the TRISO Analysis Tool for Predictive Source terms (TRISO-ATOPS) was developed. This model calculates the release of the key safety-important fission products by diffusion through the kernel, silicon carbide and graphite based on fuel and graphite temperatures in the reactor under normal operation. These releases from the fuel enter the coolant where they can plate-out on cooler surfaces. A clean-up model is included for designs with a coolant purification system for removing fission gases. This initial distribution of fission products in the reactor serves as an initial condition for potential releases under postulated accident conditions. From this initial condition, the model calculates the fission product release for any transient temperature profile, and the fission product releases can then be used to assess radiological dose to the workers and the public using conventional radiological dose tools. Data on the diffusion of fission products is based on historic German TRISO experiments and the more current Department of Energy Advanced Gas Reactor TRISO fuel development program. The example cases in this work demonstrate the flexibility of the model

Stoyer, Benjamin [Idaho National Laboratory (INL),↗

ECAR-3386 AS-RUN THERMAL ANALYSIS OF THE AGC-3 EXPERIMENT

The third Advanced Graphite Creep (AGC-3) experiment was designed to irradiate various types of graphite specimens at a temperature of 900°C. The specimens were irradiated in an instrumented leadout capsule experiment in the east flux trap of the ATR during cycles 152B, 154B, 155A, and 155B. Temperature was monitored using twelve thermocouples located at various elevations in the reactor core, and a helium-argon gas mixture was used for gas gap temperature control of the specimens. The purpose of this analysis is to calculate specimen temperature using measured data on reactor power and helium-argon gas flows, and as-run calculations of heating rates and displacement per atom (DPA) in graphite. The accuracy of the model is assessed by comparing measured and calculated thermocouple temperatures. Uncertainty in gas gaps may preclude an accurate temperature calculation. In these cases, adjustments are made to the thermal model in order to reconcile the measured and calculated thermocouple temperature and to ensure the accuracy of the calculated specimen temperature.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The Development of a Generalized Riser Flow Regime Map Based Upon Higher Moment and Chaotic Statistics Using Electrical Capacitance Volume Tomography (ECVT)

Dynamic analyses have been applied to the temporal signals from an Electro Capacitance Volume Tomography instrument located near mid-height on the riser of an industrial-scale cold-flow circulating fluidized bed to characterize gas-solids flow behavior in the riser. Twelve capacitance electrodes surround the cylindrical riser over a height of 1.3 m. The instrument used a neural network deconvolution algorithm to determine the spatially resolved solids fraction recorded at 52 Hz. Experiments were carried out over a range of gas and solids flows in the transport regime using a Geldart Group B bed material, high density polyethylene with mean particle size of 880 μm. The radial solids distribution was found to vary from one-time step to the next between profiles typical of laminar and turbulent flow. The duration of time spent in each of these flow profiles depended upon the operating regime – dilute, core-annular, or fast fluidized bed. The chaotic structure of the temporal data was characterized using the three conventional approaches: the first 4 moments from the distribution of signal in time, system memory parameters from the autocorrelation function and the Hurst exponent, and analysis of the correlationentropy and correlation dimension of the attractor. These signal analysis techniques were used to clearly distinguish differences between different transport operating regimes. Specifically, it was experimentally observed that a riser transitions from core annular flow profile to dilute and dense regimes via increasing the frequency of short term transients to either dilute or dense flow profiles, respectively. A regime map was generated based upon these dynamics using solids flux and gas velocity axes. Fast fluidized, core annular, and dilute each exhibited different degree of dynamic characteristics typical of fluid dominated or particle compromising behavior. It should be noted that the magnitude for the different statistics was in the same range regardless of the regime, it was the radial profile for the statistic that changed and subsequently identified that there was a change in the regime. Finally, a reduced regime map was developed consisting of plotting the gas velocity normalized by the upper transport velocity versus the solids flux normalized by the saturation carrying capacity. The use of this reduced plot allowed the data from widely different conditions to be plotted and compared on the same<p>graph. Note that in many instances, some of the statistics identified the operating point as being in one regime while others indicated that it was in another indicating a transition region between dilute or core annular regimes and between the core annular and fast fluidization regimes. This now provides a tool that can be used to optimize process performance, identify changes in operating states, or replicate process dynamics during process scaling or changing operating parameters. </p>

Breault, Ronald↗

Theoretical Prediction and Interpretation of 237 Np Mössbauer Isomer Shifts

Different theoretical approaches for the calculation of 237 Np Mössbauer isomer shifts are investigated. The traditional contact density route is compared to a previously proposed alternative approach that uses energy derivatives with respect to the nuclear radius. Both approaches yield similar results as long as suitable basis sets augmented with large exponents and relativistic methods are used. Density functional theory (DFT) calculations do not show a strong dependency of the 237 Np isomer shift on the chosen functional. Wavefunction calculations show that dynamic electron correlation can be important when covalent bonding influences the isomer shift. Effects from spin–orbit coupling are small. The isomer shifts of ionic solids and Np(III) organometallic complexes are largely governed by the oxidation state of Np. Isomer shifts of organometallic Np(IV) complexes are strongly affected by donation bonding. Furthermore, detailed analysis of the wavefunction results with different active spaces demonstrates that correlation among the outer core Np and occupied ligand frontier orbitals contributes significantly to isomer shifts of Np(IV) compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting the chemical space of fungal polyketides by phylogeny-based bioinformatics analysis of polyketide synthase-nonribosomal peptide synthetase and its modification enzymes

Fungal polyketide synthase (PKS)–nonribosomal peptide synthetase (NRPS) hybrids are key enzymes for synthesizing structurally diverse hybrid natural products (NPs) with characteristic biological activities. Predicting their chemical space is of particular importance in the field of natural product chemistry. However, the unexplored programming rule of the PKS module has prevented prediction of its chemical structure based on amino acid sequences. Here, we conducted a phylogenetic analysis of 884 PKS–NRPS hybrids and a modification enzyme analysis of the corresponding biosynthetic gene cluster, revealing a hidden relationship between its genealogy and core structures. This unexpected result allowed us to predict 18 biosynthetic gene cluster (BGC) groups producing known carbon skeletons (number of BGCs; 489) and 11 uncharacterized BGC groups (171). The limited number of carbon skeletons suggests that fungi tend to select PK skeletons for survival during their evolution. The possible involvement of a horizontal gene transfer event leading to the diverse distribution of PKS–NRPS genes among fungal species is also proposed. This study provides insight into the chemical space of fungal PKs and the distribution of their biosynthetic gene clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards High-Performance AI4NP Applications on Modern GPU Platforms

The evolution of modern heterogeneous accelerators, such as GPUs, has significantly advanced the landscape of artificial intelligence (AI). There is a notable surge to adopt AI within the nuclear physics domain (AI4NP). While most AI4NP studies focus on feasibility analysis, our attention is directed towards evaluating their performance on contemporary GPUs that integrate tensor cores. We first benchmark the throughput of hyperparameterized multi-layer perceptron (MLP) models. We then examine the performance of an AI4NP application: Hydra. We assess the performance gain and accuracy loss caused by the tensor cores for low-precision floating-point operations. Our experiments encompass the PyTorch and TensorFlow Keras frameworks on NVIDIA’s T4 and A100 GPUs. We explore the behavior of different GPU hardware platforms and AI software tools. This study can be a valuable resource for guiding the performance optimization of larger-scale deployments of AI4NP applications.

Mei, Xinxin↗

Comparison of plasma start-up with high Z and low Z first wall in WEST

The choice of first wall material is of paramount importance for the plasma start-up conditions in ITER and future fusion power plants. In this context, the present work focuses on the correlations between first wall impurity sources and total radiated power during plasma start-up in the tungsten (W) Environment in Steady-state Tokamak (WEST). The objective is to highlight experimental indications for a preferable combination of start-up plasma scenario and first wall materials. Until 2019, WEST featured a full high Z first wall with all limiters exposing only W surfaces to the plasma. To study the impact of a low Z first wall in WEST, boron nitride tiles were installed in the central part of the inner and outer limiters in 2020. Although visible spectroscopy and bolometry measurements show respectively a strong weakening of the WI line intensity on the limiters and a reduction of radiated power after the changeover, a degradation occurs with the accumulation of plasma exposure. In addition, the different plasma facing elements of the main chamber do not influence equally the radiated power during start-up. In both high Z and low Z environments, a clear non-linear dependence is found between the start-up radiated power and the outer limiter W impurity source. Since W seems to be the main cause for core radiation, correlation between outer limiter W sources and other impurity sources are investigated. Finally, analysis of the legacy of B powder drops on a number of start-up plasmas suggests that it is less effective at reducing radiated power when the first wall is covered with W.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fitness factors impacting survival of a subsurface bacterium in contaminated groundwater

Many factors contribute to the ability of a microbial species to persist when encountering complexly contaminated environments, including time of exposure, the nature and concentration of contaminants, availability of nutritional resources, and possession of a combination of appropriate molecular mechanisms needed for survival. Herein we sought to identify genes that are most important for survival of Gram-negative Enterobacteriaceae in contaminated groundwater environments containing high concentrations of nitrate and metals using the metal-tolerant Oak Ridge Reservation isolate, Pantoea sp. MT58 (MT58). Survival fitness experiments in which a randomly barcoded transposon insertion (RB-TnSeq) library of MT58 was exposed directly to contaminated Oak Ridge Reservation groundwater samples from across a nitrate and mixed metal contamination plume were used to identify genes important for survival with increasing exposure times and concentrations of contaminants, and availability of a carbon source. Genes involved in controlling and using carbon, encoding transcriptional regulators, and related to Gram-negative outer membrane processes were among those found to be important for survival in contaminated Oak Ridge Reservation groundwater. A comparative genomics analysis of 75 Pantoea genus strains allowed us to further separate the survival determinants into core and non-core genes in the Pantoea pangenome, revealing insights into the survival of subsurface microorganisms during contaminant plume intrusion.

59 BASIC BIOLOGICAL SCIENCES↗

The Effect of Pressure on NO x Entitlement and Reaction Timescales in a Premixed Axial Jet-In-Crossflow

This paper investigates the pressure dependency of a lean premixed jet injected into a lean vitiated crossflow with an experimentally verified detailed chemistry computational fluid dynamics (CFD) model and 53 species considered. Experimental data were taken in an axially staged combustor with an optically accessible test section, allowing the use of particle image velocimetry (PIV) and CH* chemiluminescence techniques as well as point measurement of species concentration, temperature, and pressure. The experimental data cases at one, three, and five atmospheres were selected to describe the flame stabilization dependency on pressure and gain the required knowledge for an extrapolation to engine condition. Simulated exit nitrogen oxide levels were validated with experimental emission data, and a global emission trend for the NO reduction at elevated pressure and constant turbine inlet temperature level was defined. The nitrogen oxide benefit at elevated operating pressure was justified with the significantly smaller flame surface area: the analysis of the simulated spanwise and top-view profiles showed a relatively short receded core flame with nitrogen oxide production in the center at high pressure relative to a longer and larger shear layer flame at atmospheric condition that produced NO toward the inner and outer side of the flame. Furthermore, decomposition of the Damköhler number revealed the strong influence of the reaction timescales with higher reaction rates at elevated pressure, along with a moderate influence of the turbulent timescales, showing higher turbulence intensity in the lee-side recirculation zone at lower pressure.

03 NATURAL GAS↗

Duckweed hosts a taxonomically similar bacterial assemblage as the terrestrial leaf microbiome

Culture-independent characterization of microbial communities associated with popular plant model systems have increased our understanding of the plant microbiome. However, the integration of other model systems, such as duckweed, could facilitate our understanding of plant microbiota assembly and evolution. Duckweeds are floating aquatic plants with many characteristics, including small size and reduced plant architecture, that suggest their use as a facile model system for plant microbiome studies. Here, we investigated the structure and assembly of the duckweed bacterial microbiome. First, a culture-independent survey of the duckweed bacterial microbiome from different locations in New Jersey revealed similar phylogenetic profiles. These studies showed that Proteobacteria is a dominant phylum in the duckweed bacterial microbiome. To observe the assembly dynamics of the duckweed bacterial community, we inoculated quasi-gnotobiotic duckweed with wastewater effluent from a municipal wastewater treatment plant. Our results revealed that duckweed strongly shapes its bacterial microbiome and forms distinct associations with bacterial community members from the initial inoculum. Additionally, these inoculation studies showed the bacterial communities of different duckweed species were similar in taxa composition and abundance. Analysis across the different duckweed bacterial communities collected in this study identified a set of “core” bacterial taxa consistently present on duckweed irrespective of the locale and context. Furthermore, comparison of the duckweed bacterial community to that of rice and Arabidopsis revealed a conserved taxonomic structure between the duckweed microbiome and the terrestrial leaf microbiome. Our results suggest that duckweeds utilize similar bacterial community assembly principles as those found in terrestrial plants and indicate a highly conserved structuring effect of leaf tissue on the plant microbiome.

54 ENVIRONMENTAL SCIENCES↗

MTA Removable Beam Absorber

Once commissioned, the secondary production beamline in the MeV Test Area (MTA) will require a removable beam absorber for continuous beam operation. A 4"x 4" x 4" copper core encased within steel will absorb the full 15 Hz 400 MeV Fermilab Linac primary proton beam. However the residual activation will constrain work activities in the hall, so a 6” marble casing is proposed entombing the core. Marble has minimal residual activation. This presentation describes the initial concept and planned ANSYS analysis.

Blas, Efren↗

Assessing High Burnup U-19Pu-10Zr Fuel Performance against Historical and Modeled Behavior

Advancing the deployment of sodium-cooled fast reactors (SFRs) requires thorough testing of metallic fuel pins under accident conditions to establish safe operational limits of high burnup fuel. To conduct transient testing, a comprehensive understanding of steady-state fuel behavior obtained through both experimental characterization and accurate predictive capabilities is needed. This study comparatively assesses the steady-state irradiation performance of two high burnup U-19Pu-10Zr fuel pins, DP-36 and DP-40, irradiated under prototypic fast reactor conditions in preparation for planned safety testing at the Transient Reactor Test Facility. Since DP-40 was designated for use in the test and DP-36 serves as its sibling pin, non-destructive, engineering-scale post-irradiation examinations (PIE) were conducted on both pins while destructive examinations were performed exclusively on DP-36. The results were then assessed against historical performance data from similar fuel pins irradiated in the Experimental Breeder Reactor-II. Additionally, the steady-state irradiation of each pin was modeled using the BISON fuel performance code to assess the accuracy of current modeling capabilities in predicting the baseline irradiation behavior. Non-destructive examinations included neutron radiography to measure fuel column elongation, gamma scanning to verify pin integrity and fission product migration, and profilometry to assess dimensional changes. Benchmarking against existing PIE data revealed consistent patterns in axial fuel column growth and cladding diametral strain, though both pins exhibited longer low-density “fluff” structures, which can have implications for core reactivity and source term calculations. Destructive examinations on DP-36 included fission gas release analysis and sectioning for optical microscopy, which showed more complex constituent redistribution patterns than the traditionally accepted 3-ring model. The axial evolution of fractional areas and porosities of each of the redistributed zones were quantified and presented. Modeling comparisons showed agreement in fractional fission gas release but consistently overestimated axial and radial swelling and disagreed with measured axial porosity patterns. These conservative overpredictions suggested that the pins would appear closer to failure or operational limits at the start of transient tests, potentially leading to higher strain accumulation during the transient. While conservative estimates provide safety margins, they can negatively impact fuel economics. A review of the swelling models identified areas for improvement in the gaseous swelling, solid swelling, and fuel hot-pressing models when applied to ternary fuel. The results of this study highlight the critical importance of conducting pre-test characterization on both test and sibling pins to accurately capture steady-state fuel behavior, providing a precise baseline for post-test evaluations and essential inputs for transient modeling of the planned experiments. The analysis also revealed significant data gaps that require further investigation to enhance the understanding and prediction of fuel swelling and pore dynamics. Collecting comprehensive data across different irradiation conditions, burnup levels, and fuel compositions are essential for refining existing models and developing mechanistic models for both binary and ternary metallic fuels, ultimately improving the integration of modeling and experimental approaches in accident testing.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

ECAR-2322 As-Run Thermal Analysis Of The AGC-2 Experiment

The second Advanced Graphite Creep (AGC-2) experiment was designed to irradiate various types of graphite specimens at a temperature of 600°C. The specimens were irradiated in an instrumented leadout capsule experiment in the south flux trap of the ATR during cycles 149A, 1498, 1508, 151A, and 1518. Temperature was monitored using twelve thermocouples located at various elevations in the reactor core, and a helium-argon gas mixture was used for gas gap temperature control of the specimens. The purpose of this analysis is to calculate specimen temperature using measured data on reactor power and helium-argon gas flows, and as-run calculations of heating rates and displacement per atom (DPA) in graphite. The accuracy of the model is assessed by comparing measured and calculated thermocouple temperatures. Uncertainty in gas gaps may preclude an accurate temperature calculation. In these cases, adjustments are made to the thermal model in order to reconcile the measured and calculated thermocouple temperature and to ensure the accuracy of the calculated specimen temperature.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Integration of Experimental Hydroprocessing and FCC Data with Process (Aspen Plus) and Refinery Optimization (Aspen PIMS) Models

NREL's Economic, Sustainability, and Market Analysis (ESMA) team develops process models in Aspen Plus to support techno-economic analysis (TEA) and life-cycle assessment (LCA) of conversion pathways from renewable and circular resources to fuels and chemicals. These tools are being applied to assess probable operational constraints or bottlenecks associated with refinery co-processing and repurposing opportunities. The team also utilizes optimizable refinery models to quantify opportunities for biofuel and bioproduct pathways through integration with existing refining infrastructure. The goals of analysis are to model the transition of refineries to renewable and circular feedstocks and quantify the costs production and CO2 abatement through utilization of existing refineries. At the core of the ESMA team's work is the process data derived from conversion experiments on hydroprocessing and fluid catalytic cracking performed at NREL. The objective of this presentation is to highlight new analysis approaches and capabilities in pathway analysis and refinery optimization modeling with specific emphasis on integration of experimental data.

BIOMASS FUELS,ENERGY PLANNING, POLICY, AND ECONOMY↗

Feynman-α analysis using BGO gamma-ray detector in UTR-KINKI reactor

In conventional reactor noise measurement based on neutron detection, a neutron detector must be placed as close to a core as possible, to observe a largest possible correlation amplitude. For most of reactors other than critical assemblies, however, the placement is hardly possible. We focused on an alternative reactor noise measurement using prompt gamma-rays having a long flight range, to overcome the above constraint. A Feynman-α analysis using a NaI(Tl) scintillation detector was previously performed in UTR-KINKI, however, white noise originating from radioactivation of the scintillator significantly degraded the correlation amplitude. In this study, another Feynman-α analysis using a BGO gamma-ray detector, which never suffers from any radioactivation, is performed. A series of Feynman-α analyses for a critical state and several subcritical states of UTR-KINKI reactor has been carried out using two BGO detectors and a BF{sub 3} neutron detector to determine prompt-neutron decay constant. In the present analysis, the dead-time effect of these detectors and the delayed-neutron effect are considered. The prompt-neutron decay constant determined from Feynman-α analysis based on gamma-ray detection agrees with that from the analysis based on neutron detection. The Feynman-α analysis based on detecting gamma rays appears to be able to determine prompt-neutron decay constant at least as efficiently as the conventional analysis detecting neutrons.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Comparative Hydrophobic Core Dynamics Between Wild‐Type Amyloid‐β Fibrils, Glutamate‐3 Truncation, and Serine‐8 Phosphorylation

Abstract Post‐translational modifications (PTMs) of amyloid‐β (Aβ) species are implicated in the modulation of overall toxicities and aggregation propensities. We investigated the internal dynamics in the hydrophobic core of the truncated ΔE3 mutant fibrils of Aβ 1–40 and compared them with prior and new data for wild‐type fibrils as well as with phosphorylated S8 fibrils. Deuteron static solid‐state NMR techniques, spanning line‐shape analysis, longitudinal relaxation, and chemical exchange saturation transfer methods, were employed to assess the rotameric jumps of several methyl‐bearing and aromatic groups in the core of the fibrils. Taken together, the results indicate the rather significant influence of the PTMs on the hydrophobic core dynamics, which propagates far beyond the local site of the chemical modification. The phosphorylated S8 fibrils display an overall rigidifying of the core based on the higher activation barriers of motions than the wild‐type fibrils, whereas the ΔE3 fibrils induce a broader variety of changes, some of which are thermodynamic in nature rather than the kinetic ones.

Vugmeyster, Liliya↗

Soil Water Retention and Hydraulic Conductivity Data and Model at Trail Creek in Taylor River Watershed, Colorado 2024-2025

This data package includes soil water retention and hydraulic conductivity data and model fitting results from measurements of ex-situ soil samples and in-situ soil sensors near Trail Creek. Soil water retention curves (SWRC) characterize soil water content as a function of soil water potential. SWRC depends on soil texture and pore structure and can be used to describe the constraints on biogeochemical processes in terms of soil water availability. In this data package, the sample identification follows the format TR-X-Y, where TR refers to Trail Creek, X is the treatment block identifier, and Y is the location identifier. Specifically, TR-ASCC1 is the control treatment block under the Adaptive Silviculture for Climate Change (ASCC) project, and TR-ASCC2 is the clear-cut treatment block. TR-ASCC-EHSn is associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and TR-ASCC-ERTn (upslope n=1) are ecohydrology sites along the electrical resistivity tomography transects. The sample and location information can be found in metadata.csv, and the data from the soil sensors will be included in a future data version when the observation period becomes sufficiently long for data analysis. Sampling and Measurements Each sample falls into one of the two sampling methods – (1) intact cores or (2) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. The intact cores were measured using the laboratory methods, which include measurements of soil water potential (HYPROP & WP4C, METER), saturated (KSAT, METER) and unsaturated hydraulic conductivity (HYPROP). The in-situ method uses a pair of co-located soil sensors to measure volumetric water content (TEROS12, METER) and soil water potential (TEROS21, METER), and the hydraulic conductivity was not measured. In comparison, the laboratory methods progress from full saturation to dry conditions, and the in-situ method includes both dry-to-wet and wet-to-dry cycles. The sampling and measurement methods for each sample can be found in metadata.csv, and more information about the measurements is detailed in the Methods section below. Models Retention and hydraulic conductivity data were fitted with four van-Genuchten-type models (specified by “model_name” column in the files): (1) traditional constrained van Genuchten model (“vG_constrained”), (2) traditional unconstrained van Genuchten model (“vG_unconstrained”), (3) PDI-variant of the constrained van Genuchten model (“vG_constrained_PDI”), and (4) PDI-variant of the unconstrained van Genuchten model (“vG_unconstrained_PDI”). The difference between the constrained (1: n) and the unconstrained (2: n, m) van Genuchten models is the number of pore-size distribution parameters in the model equations, giving the unconstrained model more degrees of freedom when fitting the data. Between the traditional and the PDI-variant models, model fitting differs the most at the dry end of the measurements. The traditional models allow infinite suction at the residual water content (water content does not drop below residual water content), and the PDI-variant models enforce a soil water potential value of pF=6.8 (~ -630 MPa) at oven-dryness (water content reaches 0). The inclusion of the van-Genuchten-type models is due to their common application. If other retention models are required, users can access the data in data.csv for further data fitting. More information about the models can be found in the Methods section below. Fitting Tasks The model fitting can be categorized into three levels of tasks (specified by “fitting_task” column in the files). Level 1 (“fit_retention”) only includes retention data fitting (the only level available for the in-situ method). Level 2 (“fit_retention_conductivity”) includes both retention and hydraulic conductivity data fitting, and the saturated hydraulic conductivity (Ks, a parameter of the hydraulic conductivity functions) is fixed by the measurements from KSAT. Level 3 (“fit_retention_conductivity_Ks”) also includes both retention and hydraulic conductivity data fitting, but Ks is a fitted parameter without the constraints from KSAT measurements. Among the same retention models (e.g. vG_constrained models of the same sample), level 1 should produce the best retention data fitting. Level 2 should have the highest misfit of the retention and hydraulic conductivity data, because the retention and hydraulic conductivity functions share common model parameters, and the unsaturated hydraulic conductivity (HYPROP) data fitting is subject to Ks measured independently by KSAT. Level 3 should have mid-level misfits of the retention and hydraulic conductivity data. While level 3 fits the hydraulic conductivity data better than level 2, the fitted Ks value might be unreasonable due to the lack of constraints at the wet end of the measurements. General recommendation when using this data package: (1) Choice of sampling methods: Intact cores might suffer from sample gaps that would lead to overestimation of Ks (sample gaps can be inferred from the “soil_sample_volume” column in metadata.csv when the value is < 249). In-situ method has higher uncertainty in characterizing the wet end of the SWRC because of sensor limitations and the difficulty in reaching full saturation under natural conditions. (2) Choice of fitting tasks: When only retention data is needed, level 1 (“fit_retention”) should be prioritized. When both retention and hydraulic conductivity data are needed, level 2 (“fit_retention_conductivity”) could be prioritized. (3) Choice of models: This could depend on what the downstream models call for. If no specific model is required, model misfit could be used as a ranking criterion. Model misfit values in terms of RMSE can be found in model_parameters.csv. The following files are included in this data package: (1) metadata.csv – This file includes the general information of each sample, including location (description, geocoordinates, elevation), sampling and measurements details (method, depth, time or period, volume, instruments), and soil physical properties (bulk density, saturated hydraulic conductivity, only applicable to physical soil samples). (2) data.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity data of each sample. Column “instrument” specifies the instrument (HYPROP, WP4C, or TEROS) used to perform the measurements. (3) model_fit.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity fitted from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the variable does not apply to that fitting task. (4) model_parameters.csv – This file includes the fitted model parameters, model misfits, and conventional water content thresholds (field capacity and wilting point) from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the parameter does not apply to that model and/or that fitting task. (5) data_Ks.csv – This file includes the saturated hydraulic conductivity measurements from KSAT. (6) /figure/*.png – This folder includes three quick visualizations of the data, retention model fitting results and misfits, and hydraulic conductivity model fitting results, misfits, and parameters. The model fitting results are separated by samples and fitting tasks and colored by models. Zoom-in required. (7) /hyprop/*.bdhx – This folder includes proprietary hyprop files that require the free Labros SoilView-Analysis (METER) to open. Users can explore data fitting using other retention models (i.e. Brooks-Corey, Fredlund-Xing, Kosugi, bimodal models). Be aware that Ks value is pre-entered under “Fitting tab, Conductivity functions parameters” for level 2 fitting. If the value is lost, please refer to metadata.csv under “Ks” column. (8) Six file-level metadata that summarize file, header, column, and variable information of all files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > LAND SURFACE > SOILS↗