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

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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Multiplicity scaling of light nuclei production in relativistic heavy-ion collisions

Using the nucleon coalescence model based on kinetic freeze-out nucleons from the 3D MUSIC+UrQMD and the 2D VISHNU hybrid model with a crossover equation of state, we study the multiplicity dependence of deuteron ( d ) and triton ( t ) production from central to peripheral Au+Au collisions at s NN = 7.7, 14.5, 19.6, 27, 39, 62.4 and 200 GeV and Pb+Pb at s NN = 2.76 TeV, respectively. It is found that the ratio N t N p / N d 2 of the proton yield N p , deuteron yield N d and triton yield N t exhibits a scaling behavior in its multiplicity dependence, i.e., decreasing monotonically with increasing charged-particle multiplicity. A similar multiplicity scaling of this ratio is also found in the nucleon coalescence calculation based on kinetic freeze-out nucleons from a multiphase transport (AMPT) model. The scaling behavior of N t N p / N d 2 can be naturally explained by the interplay between the sizes of light nuclei and the nucleon emission source. We further argue that the multiplicity scaling of N t N p / N d 2 can be used to validate the production mechanism of light nuclei, and the collision energy dependence of this yield ratio can further serve as a baseline in the search for the QCD critical point in relativistic heavy-ion collisions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Unsteady aerodynamics of large-scale floating offshore wind turbines in surge motion

Unsteady aerodynamic loads significantly influence the design and wake flow field of floating offshore wind turbines, especially due to wave- or vibration-induced tower top motions triggering various unsteady phenomena. Recent studies show that increasing turbine sizes amplify unsteady aerodynamic effects, as their impact typically grows with rotor diameter. This work combines recent findings from experiments and simulations on model-scale FOWT aerodynamics with new numerical analyses of large-scale rotors, providing a comprehensive understanding of unsteady phenomena occurrence and impact. Numerical analyses of the IEA 15-MW and 22-MW rotors undergoing surge motions characterise the combined influence of motion-induced unsteady phenomena on rotor thrust. Results indicate that unsteady effects can reduce thrust force variations by up to 40% at realistic surge periods. These findings contrast with prior model-scale rotor investigations, attributed to the specialised design of the model rotors. Comparisons between numerical methods - the dynamic blade element momentum method in OpenFAST and free vortex wake modules in panMARE and OpenFAST - reveal persistent differences in thrust predictions under both idealised and realistic conditions. This highlights that classical blade element momentum approaches require enhancement to accurately capture unsteady loads on large-scale floating offshore wind turbines at low wind speeds.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Uncertain quantum computing futures and potential energy and physical resource impacts at scale

Considerable attention has recently focused on the vast energy and water demands of supercomputing, namely large-scale data centers that underpin artificial intelligence (AI), one of the great disruptors of contemporary society. Looking ahead some years from now, quantum computing is poised to disrupt established computing paradigms once again. Scientists and engineers are now working intensely to bring this century-old dream of physicists to fruition. Yet, as quantum computers begin to be integrated with classical supercomputing architectures, the implications for energy and physical resource use also need to be understood, especially how they compare to today’s AI data centers. These impacts have not yet been quantified by the research community – a notable gap in the literature, even if commercial-scale deployment of Quantum-Accelerated Computing Infrastructure (QuACI) is not expected for a few more years. This study is the first to conduct such an assessment. Using publicly available information from academic sources and private industry, we characterize multiple configurations of superconducting qubit-based, fault-tolerant quantum computers (FTQC) that could plausibly be deployed at scale in the 2030s and into the 2040s. By parameterizing these FTQC systems at a process level, we conduct a prospective scenario analysis to quantify their energy and physical resource needs. While these estimates are uncertain, given the current state of quantum technologies and their unknown future trajectories, important insights can already be drawn. One key finding is that while the electricity needs for a fleet of FTQCs are within the bounds of previous modeling studies that have explored high electricity demand futures, the needs for certain physical resources, namely water and helium-3, could pose bottlenecks to QuACI scale-up.

Computing↗
DOE OSTI2024

The impact of sampling scale: A comparison of methods for estimating external contaminant exposure in free-ranging wildlife

The impacts of contaminants on wildlife are dose dependent, and thus being able to track or predict exposure following contamination events is important for monitoring ecosystem health. However, the ability to track exposure in free-ranging wildlife is often severely limited. Consequently, researchers have predominantly relied on simple methods for estimating contaminant exposures in wildlife with little regard for spatial contaminant heterogeneity or an animal’s use of diverse habitats. We evaluated the influence sampling scale (i.e., how finely contaminant distribution and organism’s spatial use of the landscape is mapped) has on (1) realism and (2) conservativeness of exposure estimates. To do this, we monitored the actual exposure of wild boar (Sus scrofa) in Fukushima, Japan to radioactive contamination using GPS27 coupled contaminant monitors placed on individual animals. We compared empirical exposures to estimates generated by combining varying amounts of information about an individual boar’s location and/or movement, with the distribution of contamination on the landscape. Here we found that the most realistic exposure estimates were produced when finer-scale contaminant distribution surveys (e.g., airborne surveys) were combined with more accurate estimates of an individual’s space use (e.g., home ranges or core areas). Importantly, estimates of exposure based on single point surveys at a trap site (a simple method commonly used in the literature), did not correlate with actual exposure rates, suggesting dose-effects studies using this method may result in spurious conclusions. These results suggest that researchers seeking realistic estimates of exposure, such as in dose-effect studies, should ensure they have adequately accounted for fine-scale contaminant distribution patterns and areas of higher use by study organisms. However, conservative estimates of exposure i.e., intentionally over-predicting exposure as is done in initial tiers of ecological risk analyses) were not as scale sensitive and could be achieved with a single known location and coarse contaminant distribution maps.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

High-resolution hourly surrogate modeling framework for physics-based large-scale building stock modeling

Surrogate modeling can play a key role in reducing high computational burdens for large-scale physics-based modeling and uncertainty quantification. With the rapid development of large-scale building stock energy modeling, surrogate modeling has also begun to be widely applied in this field; however, most existing surrogate models lack hourly time resolution for regional-scale modeling, which is essential for understanding building demand profiles and grid impacts. Further, there is generally a lack of necessary data and feature engineering frameworks specific to building modeling for efficiently managing large datasets and complex computations. Furthermore, this paper proposes a modeling framework for large-scale (city-/region-scale), high-resolution, high-fidelity surrogate building stock energy models. Our developed framework consists of six modules: (1) building stock energy modeling (ComStock TM and ResStock TM ), (2) data engineering for large simulation data, (3) high performance computing workflow, (4) feature engineering, (5) machine learning model development, and (6) model performance evaluation. Two case studies apply the developed framework in both residential and commercial building stock analysis to demonstrate its computational efficiency and surrogate modeling accuracies. Results show that surrogate models, when efficiently trained using the HPC workflow module, reach a high level of modeling accuracy for two case studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Full-scale validation gaps and opportunities for low-head hydropower: a review and perspective

Hydropower is undergoing technological innovation as future development increasingly targets low-head sites (<10 m), primarily through retrofits, rehabilitation, and upgrades of existing infrastructure. This shift toward smaller systems creates a timely opportunity: unlike conventional large projects, many emerging low-head technologies may be small enough for direct full-scale validation. Full-scale testing is particularly important for environmental mitigation technologies, including fish passage, sediment continuity, and water-quality improvements, whose performance is difficult to assess reliably using reduced-scale models. Yet adoption remains constrained by the limited risk-bearing capacity of small hydropower owners, discouraging manufacturers from bringing unvalidated technologies to market. This review and perspective paper examines hydropower trends driving innovation, selected emerging technologies, conventional testing methods, and current U.S. testing capabilities as a case study. We then evaluate the gap between existing capabilities and the needs of low-head powertrains and environmental mitigation measures. Many technologies exceed existing facility flow capacities; in the U.S., the highest combined head–flow capability is limited to 5.66 m3/s, compared with median and 90th-percentile low-head turbine-unit flows of 14.3 and 60 m3/s. To mitigate this gap, we advocate repurposing large, retired, or underused hydraulic infrastructure as full-scale testing facilities to reduce first-adoption risk and support sustainable low-head hydropower deployment.

Tseng, Chien-Yung [Colorado State University, Fort↗
DOE OSTI2022

Implications of inertial subrange scaling for stably stratified mixing

In this work, we investigate the effects of the turbulent dynamic range on active scalar mixing in stably stratified turbulence by adapting the theoretical passive scalar modelling and demonstrating their usefulness through consideration of the results of direct numerical simulations of statistically stationary homogeneous stratified and sheared turbulence. By analysis of inertial and inertial–convective subrange scalings, we show that the relationship between the active scalar and turbulence time scales is predicted by the ratio of the Kolmogorov and Obukhov–Corrsin constants, provided mean flow parameters permit the two subrange scalings to be appropriate approximations. We use the resulting relationship between time scales to parameterise an appropriate turbulent mixing coefficient $\varGamma \equiv \chi /\epsilon$, defined here as the ratio of available potential energy ($E_p$) and turbulent kinetic energy ($E_k$) dissipation rates. With the analysis presented here, we show that $\varGamma$ can be estimated by $E_p,E_k$ and a universal constant provided an appropriate Reynolds number is sufficiently high. This large Reynolds number regime appears here to occur at $ {{Re_b}} \equiv \epsilon / \nu N^{2} \gtrapprox 300$ where $\nu$ is the kinematic viscosity and $N$ is the characteristic buoyancy frequency. We propose a model framework for irreversible diapycnal mixing with robust theoretical parametrisation and asymptotic behaviour in this high-$ {{Re_b}}$ limit.

42 ENGINEERING↗
DOE OSTI2026

Modulation induced by very-large-scale motions on the inclination angle of wall-attached eddies: an atmospheric surface layer experiment

The forward leaning inclination angle, 𝛾, of coherent turbulent structures is a well-known feature of wall-bounded turbulent flows. Although invariant across friction Reynolds numbers within the range 𝑅𝑒 𝜏 =10 3 −10 6 , 𝛾 can vary significantly across turbulent scales within a high-Reynolds-number flow. Very-large-scale motions (VLSMs) are known to induce significant changes in the instantaneous shear profile, which is a conditioning event that could trigger variability in the inclination angle of smaller coherent turbulent structures. Although this aspect has been extensively studied via numerical and laboratory experiments, few studies have explored this feature for a very-high-Reynolds-number atmospheric flow. In this work, the inclination angle of turbulent structures within the atmospheric surface layer at a very high Reynolds number (𝑅𝑒 𝜏 =7.9 ×10 5 ) is investigated by deploying a scanning Doppler light detection and ranging and a super large particle image velocimetry (SLPIV) apparatus. The inclination angle of wall-attached eddies is inferred either from the two-point correlation of streamwise velocity (𝛾 =41.1∘) or with a scale-dependent approach through the spectral linear stochastic estimator (SLSE). The SLSE (and, thus, the scale-dependent inclination angle) is conditionally evaluated based on the high- and low-momentum events induced by VLSMs, both in the streamwise (𝑢′𝑉𝐿𝑆𝑀) and in the vertical (𝑤′ 𝑉𝐿𝑆𝑀) velocity components. As a result, lower inclination angles (𝛾 =30° −50°) are found for 𝑢$^{'}_{VLSM}$ >0 (𝑤$^{'}_{VLSM}$ <0), while higher values (50° −85°) are ascribed to 𝑢$^{'}_{VLSM}$ <0 (𝑤$^{'}_{VLSM}$ >0). This result emphasises the primary role that VLSMs play in shaping the wall-attached eddy geometry, which, in turn, is crucial to determine the Reynolds stress balance within the wall-attached eddy range.

42 ENGINEERING↗
DOE OSTI2023

Habitat severity characteristics structure soil communities at regional and local spatial scales along the Antarctica Peninsula

Antarctic soils provide an excellent setting to test biogeographical patterns across spatial and environmental scales given their relatively simple communities and the dominance of physical factors that create strong environmental gradients. Additional urgency is given by the fact that their unique terrestrial communities are the subject of conservation efforts in a rapidly changing environment. We investigated relationships of soil community assembly and alpha and beta diversity with climatic and environmental parameters across regional and local scales in Maritime Antarctica. We sampled from a regional gradient of sites that differ in habitat severity, ranging from relatively favourable to harsher physicochemical conditions. At the regional scale, bacterial community characteristics and microarthropod abundance varied along this severity gradient, but most measures of fungal communities did not. Microarthropod and microbial communities differed in which soil and climate parameters were most influential, and the specific parameters that influenced each taxon differed across broad and fine spatial scales. This suggests that conservation efforts will need to focus on a large variety of habitat characteristics to successfully encompass diversity across taxa. Because beta diversity was the result of species turnover, conservation efforts also cannot focus on only the most biodiverse sites to effectively preserve all aspects of biodiversity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Cross-Scale Catalyst Modeling Applied to H 2 Storage and Release via Formic Acid

Here, we propose the Systems-to-Atoms (S2A) modeling framework that integrates the kinetics of reaction chemistry and structural configurations across various length scales with the aim of establishing a versatile template for multiscale modeling of reactive flow problems and to predict the operando activity of catalyst materials. The approach encompasses a microkinetic model to analyze surface reactions on individual facets of catalyst nanoparticles coupled with the computation of average surface reaction rates for catalyst nanoparticles of specific size distributions. Macro-homogeneous surface reaction kinetics are derived as a function of catalyst loading and used as input parameters for the continuum-scale reactor model. The cross-scale framework enables the optimization of catalyst utilization through reactor design and operating strategy. To demonstrate the framework, we studied the storage and release of hydrogen from formic acid, a promising liquid organic hydrogen carrier (LOHC), over Pd, Pt, and Cu catalysts. The framework predicts observed trends in formic acid dehydrogenation activity for catalysts with comparable weight loadings and metal particle diameters, demonstrating satisfactory quantitative alignment. Finally, the seamless transmission of parameter uncertainties between scales is also discussed.

08 HYDROGEN↗
DOE OSTI2024

Tensor Hypercontraction of Cluster Perturbation Theory: Quartic Scaling Perturbation Series for the Coupled Cluster Singles and Doubles Ground-State Energies

Even though Cluster Perturbation has been shown to be a robust non-iterative alternative to Coupled Cluster Theory, it is still plagued by high order polynomial computational scaling and the storage of higher order tensors. Here we present a proof-of-concept strategy for implementing Cluster Perturbation Theory ground state energy series for the coupled cluster singles and doubles energy with N 4 computational scaling using Tensor Hypercontraction (THC). The reduction in computational scaling by two orders is achieved by decomposing two electron repulsion integrals, doubles amplitudes and multipliers, as well as selected doubles intermediates to Tensor Hypercontraction format. Using the outlined strategy, we showcase that the Tensor Hypercontraction pilot implementations retain numerical accuracy to within 1 kcal/mol relative to corresponding conventional and density fitting implementations and we empirically verify the N 4 scaling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Scaling of Shear Rheology of Concentrated Charged Colloidal Suspensions across Glass Transition

Electrostatic interparticle interactions are a key component in controlling and designing rheological characteristics of concentrated charged colloidal suspensions. Herein, we investigate electroviscous effects on shear rheology using highly charged silica particles. By fixing the volume fraction but varying the salinity, the system undergoes a glass transition as evidenced by the evolution of the yield stress and zero-shear viscosity. We show that the steady shear viscosities obey a critical scaling relation that scales the flow curves into a super- and a sub-critical branch with glass transition salinity serving as the bifurcation point; we also demonstrate an isoviscosity scaling that collapses all isoviscosity lines into a single master curve that exhibits no singularity. Based on each scaling relation, in conjunction with common modeling equations, the quantitative relationships between the shear viscosity, stress, and salinity are established. This study demonstrates a new framework to model the steady shear rheology of concentrated charged colloids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Microstructure, Transport, and Mechanics of Compacted Clay Simulated at the 0.1 μm Scale (1400 Smectite Clay Particles) Using a Coarse-Grained Model with Explicit Counterions

Clay-rich geomaterials play a critical role in many subsurface systems. The macroscale properties of these materials (low permeability, high ionic conductivity, high swelling pressure, etc.) are sensitive to molecular-level adsorption and hydration interactions at clay−water interfaces. Efforts to develop multiscale simulation approaches to predict these properties reveal a scale gap between atomistic simulations (typically limited to systems smaller than 10 nm) and continuum-scale models (which use computational grid elements with dimensions ≳ 10 μm). In this study, we present a coarse-grained (CG) framework that partly bridges this gap by simulating compacted smectite clay assemblages with dimensions of 0.1 μm containing 1,400 clay particles across a range of dry densities (1,050 to 1,850 kg·m −3 ) and Na/Ca counterion compositions (Na fraction ranging from 0.2 to 1). The simulated systems, along with their reconstructed binary three-dimensional pore networks, are used to evaluate the microstructure, pore size distribution, tortuosity, ion diffusivity, and swelling pressure of compacted smectite clay. Results show that our approach captures important features of the mesoscale heterogeneity of compacted clays, including tactoid formation, hierarchical porosity, and anisotropic pore networks. Results also reveal how compaction and counterion composition govern emergent behaviors, including dominant pore sizes, directional transport, and electrochemical response. This work highlights the potential of CG simulations to bridge molecular and continuum scales and to advance geotechnical and environmental applications involving clay-rich materials as well as related nanoporous media such as geopolymers and calcium-silicate-hydrate. However, the results also suggest that accurate prediction of certain microstructural and mechanical properties (e.g., swelling pressure) may require even larger-scale systems on the order of 1 μm.

02 PETROLEUM↗
DOE OSTI2020

A Mixed Length Scale Model for Migrating Fluvial Bedforms

With the expansion of hydropower, in-stream converters, flood-protection infrastructures, and growing concerns on deltas fragile ecosystems, there is a pressing need to evaluate and monitor bedform sediment mass flux. It is critical to estimate real-time bedform size and migration velocity and provide a theoretical framework to convert easily accessible time histories of bed elevations into spatially evolving patterns. In this study, we collected spatiotemporally resolved bathymetries from laboratory flumes and the Colorado River in statistically steady, homogeneous, subcritical flow conditions. Wave number and frequency spectra of bed elevations show compelling evidence of scale-dependent velocity for the hierarchy of migrating bedforms observed in the laboratory and field. New scaling laws were applied to describe the full range of migration velocities as function of two dimensionless groups based on the bed shear velocity, sediment diameter, and water depth. Further simplification resulted in a mixed length scale model estimating scale-dependent migration velocities, without requiring bedform classification or identification.

58 GEOSCIENCES↗
DOE OSTI2021

Investigation of Small-Scale Electron Density Irregularities Observed by the Arase and Van Allen Probes Satellites Inside and Outside the Plasmasphere

In situ electron density profiles obtained from Arase in the night magnetic local time (MLT) sector and from RBSP-B covering all MLTs are used to study the small-scale density irregularities present in the plasmasphere and near the plasmapause. Electron density perturbations with amplitudes >10% from background density and with time-scales less than 30-min are investigated here as the small-scale density irregularities. The statistical survey of the density irregularities is carried out using nearly 2 years of density data obtained from RBSP-B and 4 months of data from Arase satellites. The results show that density irregularities are present globally at all MLT sectors and L-shells both inside and outside the plasmapause, with a higher occurrence at L > 4. The occurrence of density irregularities is found to be higher during disturbed geomagnetic and interplanetary conditions. The case studies presented here revealed: (1) The plasmaspheric density irregularities observed during both quiet and disturbed conditions are found to coexist with the hot plasma sheet population. (2) During quiet periods, the plasma waves in the whistler-mode frequency range are found to be modulated by the small-scale density irregularities, with density depletions coinciding well with the decrease in whistler intensity. Our observations suggest that different source mechanisms are responsible for the generation of density structures at different MLTs and geomagnetic conditions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Large-Scale Forcing Impact on the Development of Shallow Convective Clouds Revealed From LASSO Large-Eddy Simulations

Real-world large-eddy simulations (LES) are driven by time-varying large-scale forcings (LSF) - e.g., temperature advection, moisture advection, and subsidence - derived from large-scale weather models. This study investigates the impact of the uncertainty in LSF on real-world LES in terms of the development of shallow convection at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) atmospheric observatory for the 11 June 2016 case using LES provided by the U.S. Department of Energy's LES ARM Symbiotic Simulation and Observation (LASSO) activity. The LASSO dataset provides an ensemble of LES for the selected case, which consists of LES runs that were driven by different LSF. The two contrasting LES runs investigated here generate different types of convective clouds, i.e., nonprecipitating shallow clouds and precipitating cumulus congestus, mainly due to the difference of LSF in temperature advection in the free troposphere. The temperature advection modulates the strength of the capping inversion and therefore the buoyancy of the air parcels rising from the atmospheric boundary layer (ABL). The inversion, together with large-scale updrafts, controls the penetration of the ABL thermals into the free troposphere, leading to cumulus congestus in the case of a weaker inversion. In contrast, clouds remain shallow in the case of a strong inversion. Differences between the two simulations are amplified over time, as mixed-phase clouds are formed near the top of the congestus in the weaker inversion case. Furthermore, this high dependency of LES results to LSF stresses the importance of accurate LSF by large-scale models to real-world LES simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

On the Morphodynamics of a Wide Class of Large‐Scale Meandering Rivers: Insights Gained by Coupling LES With Sediment‐Dynamics

Abstract In meandering rivers, interactions between flow, sediment transport, and bed topography affect diverse processes, including bedform development and channel migration. Predicting how these interactions affect the spatial patterns and magnitudes of bed deformation in meandering rivers is essential for various river engineering and geoscience problems. Computational fluid dynamics simulations can predict river morphodynamics at fine temporal and spatial scales but have traditionally been challenged by the large scale of natural rivers. We conducted coupled large‐eddy simulation and bed morphodynamics simulations to create a unique database of hydro‐morphodynamic data sets for 42 meandering rivers with a variety of planform shapes and large‐scale geometrical features that mimic natural meanders. For each simulated river, the database includes (a) bed morphology, (b) three‐dimensional mean velocity field, and (c) bed shear stress distribution under bankfull flow conditions. The calculated morphodynamics results at dynamic equilibrium revealed the formation of scour and deposition patterns near the outer and inner banks, respectively, while the location of point bars and scour regions around the apexes of the meander bends is found to vary as a function of the radius of curvature of the bends to the width ratio. A new mechanism is proposed that explains this seemingly paradoxical finding. The high‐fidelity simulation results generated in this work provide researchers and scientists with a rich numerical database for morphodynamics and bed shear stress distributions in large‐scale meandering rivers to enable systematic investigation of the underlying phenomena and support a range of river engineering applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

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

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

54 ENVIRONMENTAL SCIENCES↗