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DOE OSTI2025

Controls From Above and Below: Snow, Soil, and Steepness Drive Diverging Trends of Subsurface Water and Streamflow Dynamics

ABSTRACT The importance of subsurface water dynamics, such as water storage and flow partitioning, is well recognised. Yet, our understanding of their drivers and links to streamflow generation has remained elusive, especially in small headwater streams that are often data‐limited but crucial for downstream water quantity and quality. Large‐scale analyses have focused on streamflow characteristics across rivers with varying drainage areas, often overlooking the subsurface water dynamics that shape streamflow behaviour. Here we ask the question: What are the climate and landscape characteristics that regulate subsurface dynamic storage, flow path partitioning, and dynamics of streamflow generation in headwater streams? To answer this question, we used streamflow data and a widely‐used hydrological model (HBV) for 15 headwater catchments across the contiguous United States. Results show that climate characteristics such as aridity and precipitation phase (snow or rain) and land attributes such as topography and soil texture are key drivers of streamflow generation dynamics. In particular, steeper slopes generally promoted more streamflow, regardless of aridity. Streams in flat, rainy sites (< 30% precipitation as snow) with finer soils exhibited flashier regimes than those in snowy sites (> 30% precipitation as snow) or sites with coarse soils and deeper flow paths. In snowy sites, less weathered, thinner soils promoted shallower flow paths such that discharge was more sensitive to changes in storage, but snow dampened streamflow flashiness overall. Results here indicate that land characteristics such as steepness and soil texture modify subsurface water storage and shallow and deep flow partitioning, ultimately regulating streamflow response to climate forcing. As climate change increases uncertainty in water availability, understanding the interacting climate and landscape features that regulate streamflow will be essential to predict hydrological shifts in headwater catchments and improve water resources management.

Kerins, Devon [Department of Civil and Environment↗

DOE OSTI2025

Methods to Observe Tribological Failures in Self-Mated Steel Contacts

Scuffing, a type of wear found in highly stressed or poorly lubricated contacts, is characterized by a rapid increase in friction and severe plastic deformation of the near-surface material. Scuffing has proven difficult to study because it initiates unpredictably, progresses rapidly, and typically develops within an inaccessible contact interface. Although there have been successful in-situ studies of scuffing in real-time, the transparent counter body needed for these studies changes the interactions between the surfaces and the lubricant, which affects the scuffing process in unknown ways. This paper describes the development of X-ray-compatible tribometry to study the scuffing of self-mated steels in-situ and in real-time. The method uses a crossed cylinders configuration with a thin (500 μm thick) stationary component and a small (≈200 μm) contact width to maximize X-ray interactions with atoms within the stress field generated by the contact. The resulting instrument and method are used to benchmark the scuffing response of self-mated 52,100 steel under tribologically challenging ‘oil-off’ lubrication conditions. The results demonstrate reliable scuffing in this configuration despite the relatively small contact areas and loads used. Following scuffing, gross plastic deformation was observed on both surfaces along with significant subsurface grain refinement and flow only on the stationary surface, which experienced constant contact. Interestingly, high friction initiated at specific locations of the migratory surface, which experienced intermittent contact, and then propagated across the track over time, suggesting that local conditions of the migratory surface dominated friction leading into the failure event.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Lithologic controls on microfracturing from legacy underground nuclear explosions

Detection and verification of underground nuclear explosions (UNEs) can be improved with a better understanding of the nature and extent of explosion-induced damage in rock and the effect of this damage on radionuclide migration. Much of the previous work in this area has focused on centimeter- to meter-scale manifestations of damage, but to predict the effect of damage on permeability for radionuclide migration, observations at smaller scales are needed to determine deformation mechanisms. Based on studies of tectonic deformation in tuff, we expected that the heterogeneous tuff layers would manifest explosion-induced damage differently, with welded tuffs showing more fractures and nonwelded tuffs showing more deformation bands. In comparing post-UNE samples with lithologically matched pre-UNE equivalents, we observed damage in multiple lithologies of tuff through quantitative microfracture densities. We find that the texture (e.g., from deposition, welding, alteration, etc.) affects fracture densities, with stronger units fracturing more than weaker units. While we see no evidence of expected deformation bands in the nonwelded tuffs, we do observe, as expected, much larger microfracture densities at close range (<50 m) to the explosive source. We also observe a subtle increase in microfracture densities in post-UNE samples, relative to pre-UNE equivalents, in all lithologies and depths. The fractures that are interpreted to be UNE-induced are primarily transgranular and grain-boundary microfractures, with intragranular microfracture densities being largely similar to those of pre-UNE samples. This work has implications for models of explosion-induced damage and how that damage may affect flow pathways in the subsurface.

58 GEOSCIENCES↗

DOE OSTI2024

Stanford Thermal Earth Model for the Conterminous United States

Provided here are various forms of the Stanford Thermal Earth Model, as well as the data and methods used for its creation. The predictions produced by this model were visualized in two-dimensional spatial maps across the modeled depths (0-7 km) for the conterminous United States. The thermal earth model is made available as an application programming interface (API) and as feature layers on ArcGIS, which are both provided via links below. A data-driven spatial interpolation algorithm based on physics-informed graph neural networks was used to develop these national temperature-at-depth maps. The model satisfied the three-dimensional heat conduction law by predicting subsurface temperature, surface heat flow, and rock thermal conductivity. Many physical quantities, including bottomhole temperature, depth, geographic coordinates, elevation, sediment thickness, magnetic anomaly, gravity anomaly, gamma-ray flux of radioactive elements, seismicity, and electric conductivity were used as model inputs. Surface heat flow, temperature, and thermal conductivity predictions were constructed for depths of 0-7 km at an interval of 1 km with spatial resolution of 18 km2 per grid cell. The model showed superior temperature, surface heat flow and thermal conductivity mean absolute errors of 4.8C, 8.1 mW/m2 and 0.07 W/(C-m), respectively..

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Scaling hyporheic nitrogen cycling in large river alluvial aquifers

Research Element 1: Denitrification is a difficult flux to measure when fluxes are low and when the ecosystem is difficult to sample. These attributes describe Nyack floodplain, a large gravel-bedded aquifer adjacent to the Middle Fork Flathead River. Given that denitrification is simply respiration with nitrate as a terminal electron acceptor, we reasoned that N 2 production should negatively covary with oxygen respiration so long that oxygen is available. We sampled 16 wells 8 times throughout a year and analyzed these water samples on a membrane-inlet mass spectrometer for N 2 :Ar and O 2 . We fit multilevel models to N 2 :Ar as a function of dissolved oxygen. Within wells, there was no relationship between O 2 and N 2 :Ar. Among wells N 2 :Ar increased as O 2 declined. Based on the slope of this relationship, ~ -0.07, and estimated oxygen respiration in Nyack derived from prior studies, a possible range for denitrification is 0-8 mmol m -2 d -1 corresponding to a turnover rate for nitrate of 0-0.2/d. This estimated turnover rate is in the lower 20% of rates measured in the LINX 2 study, yet shows that even in a low nitrate (0.005 mmol/L) aquifer denitrification can be a substantial sink for dissolved N. Research Element 3 and 4: We developed a new theoretical approach to describe the relationship between water inflow, water outflow, and water age in porous media control volumes under dynamic flow conditions. Our approach had three distinct steps. First we described the application of well-established equations borrowed from Chemical Engineering to describe water age distributions in the hyporheic zone under steady state conditions. We published the associated results in the scientific journal PLOS ONE. Second, we developed a new theory ("flow spans") to describe how predicted steady-state water age distributions will respond to time varying imbalances in hyporheic discharge and recharge. Finally, we developed a proof-of-concept simulation model based on the new theory and used the model to examine the effects of flow regulation on a simulated river with characteristics representative of western U.S. montane rivers with expansive hyporheic zones.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

SPRUCE Outflow Chemistry Data for Experimental Plots Beginning in 2016

This data set includes the chemistry of outflow waters in the SPRUCE experiment plots located in the S1 bog of the USDA Forest Service Marcell Experimental Forest (MEF) in northern Minnesota, 40 km north of Grand Rapids. These data are post-treatment data from the warming and elevated carbon dioxide (CO2) treatments associated with the SPRUCE experiment. There are ten experimental plots in SPRUCE: five temperature treatments (+0, +2.25, +4.5, +6.75, +9°C) at ambient CO2, and the same five temperature treatments at elevated CO2 (+500 ppm). Sample collection and analyses started in March of 2016 and will continue for the duration of the experiment. Samples were analyzed for pH, specific conductivity, anion concentrations (chloride, sulfate), cation concentrations (calcium, potassium, magnesium, sodium, aluminum, iron, manganese, silicon, strontium), nutrient concentrations (ammonium, nitrate, soluble reactive phosphorus, total nitrogen, total phosphorus), and total organic carbon (TOC) concentrations. Subsets of the samples have been analyzed for natural-abundance stable isotopes of water (δ18O-H2O and δD-H2O), dissolved carbon dioxide (δ13C-CO2), and dissolved methane (δ13C-CH4), and concentrations of total mercury (Thg), methylmercury (MeHg), ferrous iron (Fe2+), ferric iron (Fe3+), dissolved inorganic carbon (DIC), and dissolved methane (CH4).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Understanding the hydrological response of a headwater-dominated catchment by analysis of distributed surface–subsurface interactions

Abstract We computationally explore the relationship between surface–subsurface exchange and hydrological response in a headwater-dominated high elevation, mountainous catchment in East River Watershed, Colorado, USA. In order to isolate the effect of surface–subsurface exchange on the hydrological response, we compare three model variations that differ only in soil permeability. Traditional methods of hydrograph analysis that have been developed for headwater catchments may fail to properly characterize catchments, where catchment response is tightly coupled to headwater inflow. Analyzing the spatially distributed hydrological response of such catchments gives additional information on the catchment functioning. Thus, we compute hydrographs, hydrological indices, and spatio-temporal distributions of hydrological variables. The indices and distributions are then linked to the hydrograph at the outlet of the catchment. Our results show that changes in the surface–subsurface exchange fluxes trigger different flow regimes, connectivity dynamics, and runoff generation mechanisms inside the catchment, and hence, affect the distributed hydrological response. Further, changes in surface–subsurface exchange rates lead to a nonlinear change in the degree of connectivity—quantified through the number of disconnected clusters of ponding water—in the catchment. Although the runoff formation in the catchment changes significantly, these changes do not significantly alter the aggregated streamflow hydrograph. This hints at a crucial gap in our ability to infer catchment function from aggregated signatures. We show that while these changes in distributed hydrological response may not always be observable through aggregated hydrological signatures, they can be quantified through the use of indices of connectivity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Numerical investigation of multiphase flow through self-affine rough fractures

Multiphase flow through fractures has great significance in subsurface energy recovery and gas storage applications. Different fracture and flow properties affect flow through a fracture which is difficult to control in laboratory experiments. Here, we perform lattice Boltzmann simulations in an ensemble of synthetically generated fractures. Drainage simulations are performed at different capillary numbers, wettability, and viscosity ratios. We track the invading front and quantify breakthrough saturations and show that roughness and wettability have a strong effect on fluid invasion through a complex fracture. Invading a more viscous fluid results in more stable displacement regardless of the capillary number while at very low capillary numbers, fluid migration is dependent on the inherent structure of the fracture. We develop a fluid displacement phase diagram in a single rough fracture and compare our results from that in the literature. Finally, we extend the phase diagrams across multiple fractures and demonstrate the importance of natural fracture features of roughness and wettability in identifying stable versus unstable displacement regimes during multiphase flow through rough fractures. Our work presents an end-to-end numerical pathway for testing on experimental data and expanding numerical data sets for testing combinations of different physical phenomenon and make valuable predictions on fluid flow through rough fractures.

02 PETROLEUM↗

DOE OSTI2022

FY22 Progress on Multicontinuum Methods in Containment

Estimation of two-phase fluid flow properties is important to understand and predict water and gas movement through the vadose zone for agricultural, hydrogeological, and engineering applications, such as containment transport and/or containment of gases in the subsurface. To estimate rock fluid flow properties and subsequently predict physically realistic processes such as patterns and timing of water, gas, and energy (e.g., heat) movement in the subsurface, laboratory spontaneous water imbibition with simultaneous temperature measurement and numerical modeling methods are presented in the FY22 progress report. A multiple-overlapping-continua conceptual model is used to explain and predict observed complex multi-phenomenological laboratory test behavior during spontaneous imbibition experiments. This report primarily addresses two complexities that arise during the experiments: 1) capturing the late-time behavior of spontaneous imbibition tests with dual porosity; and 2) understanding the thermal perturbation observed at or ahead of the imbibing wetting front, which are associated with adsorption of water in initially dry samples. We use numerical approaches to explore some of these issues, but also lay out a plan for further laboratory experimentation and modeling to best understand and leverage these unique observations.

58 GEOSCIENCES↗

NASA NTRS1988

Observations of photospheric magnetic fields and shear flows in flaring active regions

Horizontal flows in the photosphere and subsurface convection zone move the footpoints of coronal magnetic field lines. Magnetic energy to power flares can be stored in the corona if the flows drive the fields far from the potential configuration. Videodisk movies were shown with 0.5 to 1 arcsecond resolution of the following simultaneous observations: green continuum, longitudinal magnetogram, Fe I 5576 A line center (mid-photosphere), H alpha wings, and H alpha line center. The movies show a 90 x 90 arcsecond field of view of an active region at S29, W11. When viewed at speeds of a few thousand times real-time, the photospheric movies clearly show the active region fields being distorted by a remarkable combination of systematic flows and small eruptions of new flux. Magnetic bipoles are emerging over a large area, and the polarities are systematically flowing apart. The horizontal flows were mapped in detail from the continuum movies, and these may be used to predict the future evolution of the region. The horizontal flows are not discernable in H alpha. The H alpha movies strongly suggest reconnection processes in the fibrils joining opposite polarities. When viewed in combination with the magnetic movies, the cause for this evolution is apparent: opposite polarity fields collide and partially cancel, and the fibrils reconnect above the surface. This type of reconnection, driven by subphotospheric flows, complicates the chromospheric and coronal fields, causing visible braiding and twisting of the fibrils. Some of the transient emission events in the fibrils and adjacent plage may also be related.

Tarbell, T.↗

DOE OSTI2020

Seismic refraction tracks porosity generation and possible CO 2 production at depth under a headwater catchment

Significance To understand groundwater in weathered bedrock aquifers, we explore (bio)geochemical reactions using geophysical measurements. The result leads to a conceptual model for the three-dimensional distribution of geochemical alteration in the subsurface—well beyond the typical approach of inferring (bio)geochemical reactions in the subsurface from pits, boreholes, and outcrops. With this geophysical technique we discovered the prevalence of gas beneath the water table at this site. This geophysical viewing of the subsurface highlights patterns of water movement, reactions of clays, and microbial and abiotic gas-producing reactions recorded in the subsurface and thus illuminates storage, flow, and reactions of groundwater in bedrock systems. Protecting the groundwater resource beneath our feet will rely on such enhanced capacities to see into the subsurface.

58 GEOSCIENCES↗

NASA NTRS2013

Towed Subsurface Optical Communications Buoy

The innovation allows critical, high-bandwidth submarine communications at speed and depth. This reported innovation is a subsurface optical communications buoy, with active neutral buoyancy and streamlined flow surface veins for depth control. This novel subsurface positioning for the towed communications buoy enables substantial reduction in water-absorption and increased optical transmission by eliminating the intervening water absorption and dispersion, as well as by reducing or eliminating the beam spread and the pulse spreading that is associated with submarine-launched optical beams.

Stirbl, Robert C.↗

DOE OSTI2025

3013 Baseline Inner Container Report: Description, Imaging, and Analysis

This report presents consolidated findings from three microscopy studies of baseline Bagless Transfer Containers (BTCs), which are the inner containers used in DOE Standard 3013-compliant plutonium storage packages. The studies were conducted by Los Alamos National Laboratory (LANL), Savannah River National Laboratory (SRNL), and DNV, a subcontractor specializing in corrosion science. The baseline BTCs examined had not been exposed to corrosive environments, serving as control samples for comparison with destructively examined (DE) containers. Additionally, the Background section provides an overview of the BTC design, including manufacturing methods, material properties, and container configurations that may influence corrosion behavior. The primary objective of the LANL and SRNL studies was to establish reference characteristics of BTCs to distinguish manufacturing artifacts from corrosion-induced features observed in DE containers. Both laboratories used advanced microscopy techniques, including Wide Area Microscopy (WAMS), Laser Confocal Microscopy (LCM), Scanning Electron Microscopy (SEM), and Focused Ion Beam (FIB), to reveal that most surface anomalies were shallow and attributable to flow-forming processes, not corrosion. Subsurface impurities, identified as non-metallic inclusions, were also observed. DNV’s investigation focused on characterizing the mechanical and chemical properties of the BTC material to support crack growth modeling. Their findings indicate higher hardness and strength but reduced ductility—consistent with flow-formed 304L stainless steel and a higher-than-expected martensite content, in contrast to manufacturer claims. Ongoing and future studies, including Electron Backscatter Diffraction (EBSD), aim to further understand the microstructural factors influencing crack initiation and propagation. The combined studies provide a crucial baseline for distinguishing corrosion effects in DE containers, contributing to the safe and reliable long-term storage of plutonium-bearing materials.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Method of Distributions for Two‐Phase Flow in Heterogeneous Porous Media

Abstract Multiscale heterogeneity and insufficient characterization data for a specific subsurface formation of interest render predictions of multi‐phase fluid flow in geologic formations highly uncertain. Quantification of the uncertainty propagation from the geomodel to the fluid‐flow response is typically done within a probabilistic framework. This task is computationally demanding due to, for example, the slow convergence of Monte Carlo simulations (MCS), especially when computing the tails of a distribution that are necessary for risk assessment and decision‐making under uncertainty. The frozen streamlines method (FROST) accelerates probabilistic predictions of immiscible two‐phase fluid flow problems; however, FROST relies on MCS to compute the travel‐time distribution, which is then used to perform the transport (phase saturation) computations. To alleviate this computational bottleneck, we replace MCS with a deterministic equation for the cumulative distribution function (CDF) of travel time. The resulting CDF‐FROST approach yields the CDF of the saturation field without resorting to sampling‐based strategies. Our numerical experiments demonstrate the high accuracy of CDF‐FROST in computing the CDFs of both saturation and travel time. For the same accuracy, it is about 5 and 10 times faster than FROST and MCS, respectively.

Yang, Hyung Jun↗

DOE OSTI2023

Leveraging Groundwater Dynamics to Improve Predictions of Summer Low-Flow Discharges

Summer streamflow predictions are critical for managing water resources; however, warming-induced shifts from snow to rain regimes impact low-flow predictive models. Additionally, reductions in snowpack drive earlier peak flows and lower summer flows across the western United States increasing reliance on groundwater for maintaining summer streamflow. However, it remains poorly understood how groundwater contributions vary interannually. Here, we quantify recession limb groundwater (RLGW), defined as the proportional groundwater contribution to the stream during the period between peak stream flow and low flow, to predict summer low flows across three diverse western US watersheds. We ask (a) how do snow and rain dynamics influence interannual variations of RLGW contributions and summer low flows?; (b) which watershed attributes impact the effectiveness of RLGW as a predictor of summer low flows? Linear models reveal that RLGW is a strong predictor of low flows across all sites and drastically improves low-flow prediction compared to snow metrics at a rain-dominated site. Results suggest that strength of RLGW control on summer low flows may be mediated by subsurface storage. Subsurface storage can be divided into dynamic (i.e., variability saturated) and deep (i.e., permanently saturated) components, and we hypothesize that interannual variability in dynamic storage contribution to streamflow drives RLGW variability. In systems with a higher proportion of dynamic storage, RLGW is a better predictor of summer low flow because the stream is more responsive to dynamic storage contributions compared to deep-storage-dominated systems. Overall, including RLGW improved low-flow prediction across diverse watersheds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Automated and Accelerated Continuum Model Development for Electrochemical Systems (Abbreviated Report)

Despite the availability of computational resources and advancements in numerical computing capabilities, the multiscale models core to understanding, predicting the behaviors of, and designing energy and environmental systems involving porous media are still 1.) developed through by-hand derivations and 2.) limited by many methodological assumptions employed during model derivation. As a result, the advancement of effective media models for engineering DOE mission-critical systems (e.g., batteries, flow batteries, electrolyzers, geothermal systems, subsurface chemical storage systems, etc.) is slow (i.e., it takes years for models to traverse from stages of “development” to “practical utilization”), hindering our ability to effectively optimize such systems and stay at the cutting-edge of the energy frontier. In this work, we aimed to address these limitations by 1.) automating and accelerating multiscale model derivation via symbolic computing and 2.) develop a novel multiscale modeling methodology for flow and transport through porous media that avoids the typical assumptions hindering previous models. As a result of our efforts, we 1.) developed a hybrid symbolic-numeric code called Fouriera for fully-automating the implementation of multiphysical and phase-field models via the Fourier spectral method for materials science research, and 2.) advanced a multiscale modeling methodology called The Method of Finite Averages that rigorously predicts the behaviors of flow and transport through heterogeneous porous media under the influence of non-local effects and strong advection. Ultimately, these deliverables provide strong foundations from which further efforts can advance multiscale modeling tools and capabilities that do not intrinsically rely on 1.) the speed and mathematical capabilities of humans, nor 2.) the methodological assumptions limiting current models.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Inertia-induced mixing and reaction maximization in laminar porous media flows

Solute transport and biogeochemical reactions in porous and fractured media flows are controlled by mixing, as are subsurface engineering operations such as contaminant remediation, geothermal energy production, and carbon sequestration. Porous media flows are generally regarded as slow, so the effects of fluid inertia on mixing and reaction are typically ignored. Here, we demonstrate through microfluidic experiments and numerical simulations of mixing-induced reaction that inertial recirculating flows readily emerge in laminar porous media flows and dramatically alter mixing and reaction dynamics. An optimal Reynolds number that maximizes the reaction rate is observed for individual pore throats of different sizes. This reaction maximization is attributed to the effects of recirculation flows on reactant availability, mixing, and reaction completion, which depend on the topology of recirculation relative to the boundary of the reactants or mixing interface. Recirculation enhances mixing and reactant availability, but a further increase in flow velocity reduces the residence time in recirculation, leading to a decrease in reaction rate. The reaction maximization is also confirmed in a flow channel with grain inclusions and randomized porous media. Interestingly, the domain-wide reaction rate shows a dramatic increase with increasing Re in the randomized porous media case. This is because fluid inertia induces complex three-dimensional flows in randomized porous media, which significantly increases transverse spreading and mixing. This study shows how inertial flows control reaction dynamics at the pore scale and beyond, thus having major implications for a wide range of environmental systems.

Chen, Michael A. (ORCID:0000000294614710)↗

DOE OSTI2021

Machine learning to identify geologic factors associated with production in geothermal fields: A casestudy using 3D geologic data, Brady geothermal field, Nevada

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in the Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fluid flow pathways are relatively rare in the subsurface but are critical components of hydrothermal systems like Brady and many other types of fluid flow systems in fractured rock. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of fourteen 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate the macro-scale faults and a local step-over in the fault system preferentially occur along with production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate 1) the specific geologic controls on the Brady hydrothermal system and 2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes.

15 GEOTHERMAL ENERGY↗