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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Model-based real-time surface heat flux and temperature estimation for the DIII-D tokamak

A control-oriented model for monitoring of wall power flux densities on the DIII-D tokamak has been successfully implemented and validated experimentally. Future reactors will have to withstand severe steady state high heat flux loads on plasma-facing components (PFCs). Due to the difficulty of directly-measuring local heat fluxes on these components, monitoring and protection of PFCs during the plasma discharge can benefit from simplified physics-based real-time (RT) functional models to estimate and guide heat load control. As a first step into the development, a control-oriented model for monitoring of wall power flux densities and temperatures on DIII-D tokamak has been successfully implemented. The paper discusses the experimental demonstration and comparison of the 2-D model-based wall heat flux algorithm on the DIII-Dinner wall limiter (IWL) against infra-red camera heat flux measurements for limited plasma configurations. The paper also reports on the benchmarking of the field line tracing environment, SMITER, developed at ITER organization on DIII-D tokamak against experimental IR diagnostic data and the derivation of the component shaping weighting factors for the 2-D model-based approach. Here, the extension of the model-based approach for surface temperature estimation on the DIII-D IWL is also presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A dissolution model of alite coupling surface topography and ions transport under different hydrodynamics conditions at microscale

Portland cement is the most produced material in the world. The hydration process of cement consists of a group of complex chemical reactions. In order to investigate the mechanism of cement hydration, it is vital to study the hydration of each phase separately. An integrated model is proposed in this paper to simulate the dissolution of alite under different hydrodynamic conditions at microscale, coupling Kinetic Monte Carlo model (KMC), Lattice Boltzmann method (LBM) and diffusion boundary layer (DBL). The dissolution of alite is initialised with KMC. Two Multiple-relaxation-time (MRT) LB models are used to simulate the fluid flow and transport of ions, respectively. For solid-liquid interface, DBL is adapted to calculate the concentration gradient and dissolution flux. The model is validated with experiment from literature. The simulation results show good agreements with the results published in the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Global 1km Land Surface Parameters for Kilometer-Scale Earth System Modeling

Earth system models (ESMs) are progressively advancing towards the kilometer scale (k-scale). However, the surface parameters for Land Surface Models (LSMs) within ESMs running at the k-scale are typically derived from coarse resolution and outdated datasets. This study aims to develop a new set of global land surface parameters with a resolution of 1 km for multiple years from 2001 to 2020, utilizing the latest and most accurate available datasets. Specifically, the datasets consist of parameters related to land use and land cover, vegetation, soil, and topography. The new land surface parameters are tailored to meet the emerging needs of k-scale LSMs and ESMs modeling with significant implications for advancing our understanding of water, carbon, and energy cycles under global change. The data is published via PNNL DataHub.

Li, Lingcheng↗
DOE OSTI2024

Elucidating Phosphate and Cadmium Cosorption Mechanisms on Mineral Surfaces with Direct Spectroscopic and Modeling Evidence

The simultaneous sorption of cations and anions at the mineral–water interface can substantially alter their individual sorption characteristics; however, this phenomenon lacks a mechanistic understanding. Our study provides direct spectroscopic and modeling evidence of the molecular cosorption mechanisms of the cadmium ion (Cd 2+ ) and phosphate (P) on goethite and layered manganese (Mn) oxide of birnessite, through in situ attenuated total reflection Fourier-transform infrared (ATR-FTIR), P K-edge X-ray absorption near-edge structure (XANES) spectroscopy, and surface complexation modeling. Phosphate synergistically cosorbed with Cd on goethite predominantly through P-bridged ternary complexes (≡Fe–P–Cd) and electrostatic interactions at wide pH conditions. Likewise, P and Cd exhibited synergistic cosorption on birnessite by forming P-bridged ternary complexes (≡Mn–P–Cd) and weak competitive sorption at the layer edge sites. As pH and Cd loading increased, the surface P species transitioned from a binary complex to a ternary complex and/or Cd 3 (PO 4 ) 2 precipitate for both goethite and birnessite. Compared to that in solution at pH 8, the formation of Cd 3 (PO 4 ) 2 was inhibited by the presence of goethite and birnessite, ascribed to the specific adsorption of P and Cd, more pronounced in birnessite due to the stronger sorption of Cd at its vacant sites. Finally, the discovered cosorption mechanisms of P and Cd have important implications for understanding and predicting their mobility and availability in Cd-contaminated settings.

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

Curating Carbon Storage Data for Reuse: Enabling Research and Modeling from Earth’s Surface to Subsurface

The volume of public geologic carbon storage (GCS) data resources has continued to increase in recent years as the result of an increase in funding from government, industry, and academia towards national, basin, regional and field scale studies to ensure carbon capture and storage becomes a commercially viable operation. Despite the increasing volume of data, GCS data applied towards analyses such as geologic, cost, and risk modeling continues to be multi-sourced and often disparate in nature, published across government agencies, websites, data repositories and buried in derivative reports and documents. Much of the time preparing for an analysis and derivative product development is spent collecting, aggregating, transforming and preparing input data. There have been significant efforts within the DOE National Energy Technology Laboratory’s Carbon Storage Program to optimize multi-source, multi-scale subsurface geologic data curation and aggregation to support data discovery, interoperability, and reuse. Methods include the use of artificial intelligence, machine learning, and data science techniques. This talk will discuss the workflows, best practices, and processes developed to support the aggregation and curation of data through the whole system – surface to subsurface data - that support multi-scale, multi-purpose analysis for carbon storage research.

Morkner, Paige↗
DOE OSTI2023

Modeling and Characterization of Surface Discharges in Insulating Material for Spacers: Electrode Shape, Discharge Mode, and Revision of the Creepage Concept

In the design of MV AC and DC spacers, the predominant factors are surface and interface conditions. Design is generally carried out on specifications and standards which are based on long-term experience and lab testing. However, the diffusion of power electronics with a trend to increase electric field, switching frequency, and rise time to achieve higher power density calls for an innovative, global approach to optimized insulation system design. A new methodology, based on field simulation, discharge modeling, and partial discharge inception measurements, called the three-leg approach, can form the basis to optimize insulation design for any type of supply voltage waveform. This paper focuses on the influence of the type of electrode on the inception and phenomenology of surface discharges and, as a consequence, on the interpretation of the results used for application of the three-leg approach. It is demonstrated that a typical electrode system used for insulating material testing can generate both gas and surface discharges at the triple point, when the electrodes have a smooth profile that is used to avoid corona or flashover. Hence, testing partial discharge may not provide a straightforward indication of the surface discharge inception and, thus, be partially misleading for insulation design. Another takeover is that such analysis must benefit from PD testing tools endowed with analytics able to provide automatic identification of the type of defect generating PD, i.e., internal, surface, and corona, since design and remedy actions can be taken, and adequate insulating materials developed, only knowing the type of source generating PD. Hence, testing partial discharge may not provide a straightforward indication of surface discharge inception and, thus, be partially misleading for insulation design. In addition to the importance of the three-leg approach to favor reliable and optimized design of insulation systems, there is a clear need to have a PD testing tool endowed with analytics. It should preferably be able to provide automatic identification of the type of defect generating PD, i.e., internal, surface, and corona.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Growth of Well-Defined Model Catalysts for Electrochemistry: From Surface Science Studies to Electrocatalytic CO2 Conversion

We combined ultrahigh vacuum (UHV) surface science techniques, electrochemical measurements, and computational modeling to investigate electrocatalytic systems that are crucial components of the carbon management effort, including oxygen evolution reactions (OER) and CO2 reduction reactions (CO2RR). Well-defined Model catalysts were grown on substrates in the UHV chamber and characterized with X-ray photoelectron spectroscopy (XPS) and scanning tunneling microscopy (STM). Selected model electrocatalysts were then tested in electrochemical cells to establish the structure-property relationships in OER and CO2RR. Our results showed that the edge sites of Fe2O3 grown on Au(111) were the most active toward OER and incorporation of Ni at the edge sites (NiFeOx) further boosted their OER activity. We also resolved the size-dependent electrocatalytic CO2-to-CO conversion of the Ag nanoparticle electrocatalysts with average particle diameter between 2 to 6 nm: smaller diameter (< 3 nm) particles favored H2 evolution reaction (HER) due to a high population of Ag edge sites, whereas larger diameter particles favored CO2RR as the population of Ag(100) surface sites grew. We further discovered that electronic interactions between small diameter Ag particles and highly defective carbon supports could break the size-dependent CO2RR selectivity, resulting in highly selective (CO Faradaic Efficiency > 90%) and active Ag nanoparticle electrocatalysts with sizes < 2 nm diameter.

Deng, Xingyi↗
DOE OSTI2025

Development and transferability of neural-network models for plasma-surface interactions

Plasma-surface interactions are increasingly critical to modern technologies; yet, accurate molecular dynamics simulations remain limited by the capabilities of interatomic potentials. Deep Potentials (DPs) promise to revolutionize the field by providing a systematic method for producing accurate interatomic potentials. The primary challenge of DP development is selecting a dataset, which efficiently spans the set of atomic environments one expects to encounter in the subsequent molecular dynamics simulations. The computational cost of density functional theory calculations, which are the typical basis for DP development, makes it impossible to directly verify the quality of a given DP. To address this challenge, we explore the development of a deep-learned interatomic potential, “DeepREBO,” trained to reproduce the behavior of the REBO2 empirical potential, enabling direct validation of training methodology and transferability. Using an active learning framework, we begin with a minimal dataset and iteratively expand it to train a Deep Potential-Smooth Edition model that faithfully reproduces REBO2 results for 25 eV hydrogen bombardment of diamond (001), a particularly challenging case. We show that small, carefully curated datasets can outperform large, unguided ones, with effective models requiring fewer than 15 000 snapshots. Subsequent transferability tests demonstrate that while DeepREBO generalizes well to diamond (111) surfaces, performance degrades for amorphous carbon or higher-energy impacts, highlighting the need for use-case-specific training data. We also evaluate methods to improve short-range repulsion. This study outlines best practices for training robust deep potentials and underscores the importance of dataset design for predictive plasma simulations.

Ab-initio molecular dynamics↗
DOE OSTI2022

Modeling the role of lateral surface flow in low‐relief polygonal tundra

Abstract Ice‐wedge polygon troughs play an important role in controlling the hydrology of low‐relief polygonal tundra regions. Lateral surface flow is confined to troughs only, but it is often neglected in model projections of permafrost thermal hydrology. Recent field and modeling studies have shown that, after rain events, increases in trough water levels are significantly more than the observed precipitation, highlighting the role of lateral surface flow in the polygonal tundra. Therefore, understanding how trough lateral surface flow can influence polygonal tundra thermal hydrology is important, especially under projected changes in temperatures and rainfall in the Arctic regions. Using an integrated cryohydrology model, this study presents plot‐scale end‐of‐century projections of ice‐wedge polygon water budget components and active layer thickness with and without trough lateral surface flow under the Representative Concentration Pathway 8.5 scenario. Trough lateral surface flow is incorporated through a newly developed empirical model, evaluated against field measurements. The numerical scenario that includes trough lateral surface flow simulates discharge (outflow from a polygon) and recharge (rain‐induced inflow to a polygon trough from upslope areas), while the scenario that does not include trough lateral surface flow ignores recharge. The results show considerable reduction (about 100–150%) in evapotranspiration and discharge in rainy years in the scenarios ignoring trough lateral surface flow, but less effect on soil water storage, in comparison with the scenario with trough lateral surface flow. In addition, the results demonstrate long‐term changes (~10–15 cm increase) in active layer thickness when trough lateral surface flow is modeled. This study highlights the importance of including lateral surface flow processes to better understand the long‐term thermal and hydrological changes in low‐relief polygonal tundra regions under a changing climate.

Jan, Ahmad↗
DOE OSTI2021

Lagrangian particle model for 3D simulation of pellets and SPI fragments in tokamaks

A 3D numerical model for the ablation of pellets and shattered pellet injection (SPI) fragments in tokamaks in the plasma disruption mitigation and fueling parameter space has been developed based on the Lagrangian particle code [R. Samulyak, X. Wang, H.-S. Chen, Lagrangian Particle Method for Compressible Fluid Dynamics, J. Comput. Phys., 362 (2018), 1-19]. The pellet code implements the low magnetic Reynolds number MHD equations, kinetic models for the electronic heating, a pellet surface ablation model, an equation of state that supports multiple ionization states, radiation, and a model for grad-B drift of the ablated material across the magnetic field. The Lagrangian particle algorithm is highly adaptive, capable of simulating a large number of fragments in 3D while eliminating numerical difficulties of dealing with the tokamak background plasma. The code has achieved good agreement with theory for spherically symmetric ablation flows. Axisymmetric simulations of neon and deuterium pellets in magnetic fields ranging from 1 to 6 Tesla have been compared with previous simulations using the FronTier code, and very good agreement has also been obtained. Furthermore, the main physics contribution of the paper is a detailed study of the influence of 3D effects, in particular grad-B drift, on pellet ablation rates and properties of ablation clouds. Smaller reductions of ablation rates in magnetic fields compared to axially symmetric simulations have been demonstrated because the ablated material is not confined to narrowing channels in the presence of grad-B drift. Contribution of various factors in the grad-B drift model has also been quantified.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Reducing impacts of artificial ponding in modeling salt marshes using a conductivity-formulated subgrid model

The landforms of salt marsh systems are rather complex, with meandering channel networks cutting through low-lying, extensive marsh platforms. Some small-scale topographic details are critical to flooding and draining processes but cannot be reflected in the Digital Elevation Model (DEM) due to limited measurement resolution and vegetation bias. Numerical models need a grid with high enough resolution to capture the small-scale connectivity to correctly model the small-scale flow processes, making the model computationally unaffordable. Here, in this study, we derived a subgrid model, which couples two flow components, one is the regular subgrid model for simulating the subgrid-resolved flows, and the other is a conductivity-formulated porous flow model for modeling small-scale gut flows unresolved at the subgrid level. The model validation was performed using an idealized case with a narrow slot that was unresolved in the coupled flow model. Model results were compared with a slot-resolved regular subgrid model where only surface flows are solved and suggested that, with a proper model parameterization, the coupled flow model is capable of reproducing flooding and draining processes similar to the slot-resolved subgrid model of surface flow. The model was applied to simulating flooding and draining processes in a meso-tidal salt marsh. The model results demonstrate that the coupled subgrid model can be used to reduce the impacts of artificial ponding that usually occur in numerical simulations of salt marshes with numerous narrow gullies and creeks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Permafrost Promotes Shallow Groundwater Flow and Warmer Headwater Streams

Abstract The presence of permafrost influences the flow paths of water through Arctic landscapes and thereby has the potential to impact stream discharge and thermal regimes. Observations from 11 headwater streams in Alaska showed that July water temperatures were higher in catchments with more near‐surface permafrost. We apply a fully coupled cryohydrology model to investigate if the impact of permafrost on flow path depth could cause the same pattern in temperatures of groundwater discharging from hillslopes to streams. The model simulates surface energy and water balances, snow, and subsurface water and energy balances for two‐dimensional hillslope model cases with varying permafrost extent. We find that hillslopes with continuous permafrost have more shallow flow paths and twice as high rates of evapotranspiration, compared to hillslopes with no permafrost. For our simulated cases, 6.7% of the horizontal water flux moves through the top organic soil layers when there is continuous permafrost, while only 0.5% moves through organic layers without permafrost. The deeper flow paths in permafrost‐free simulations buffer seasonal temperature extremes, so that summer groundwater discharge temperatures are highest with continuous permafrost. Our results suggest that permafrost thawing alters groundwater flow paths and can lead to decreases in summer stream temperatures and reductions in evapotranspiration in headwater catchments. These changes are of potential importance for stream biotic components of ecosystems, however, the full impact remains unknown.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Mechanistic insights into carbon–carbon coupling on NiAu and PdAu single-atom alloys

Carbon–carbon coupling is an important step in many catalytic reactions, and performing sp 3 –sp 3 carbon–carbon coupling heterogeneously is particularly challenging. It has been reported that PdAu single-atom alloy (SAA) model catalytic surfaces are able to selectively couple methyl groups, producing ethane from methyl iodide. In this work, we extend this study to NiAu SAAs and find that Ni atoms in Au are active for C–I cleavage and selective sp 3 –sp 3 carbon–carbon coupling to produce ethane. Furthermore, we perform ab initio kinetic Monte Carlo simulations that include the effect of the iodine atom, which was previously considered a bystander species. We find that model NiAu surfaces exhibit a similar chemistry to PdAu, but the reason for the similarity is due to the role the iodine atoms play in terms of blocking the Ni atom active sites. Specifically, on NiAu SAAs, the iodine atoms outcompete the methyl groups for occupancy of the Ni sites leaving the Me groups on Au, while on PdAu SAAs, the binding strengths of methyl groups and iodine atoms at the Pd atom active site are more similar. These simulations shed light on the mechanism of this important sp 3 –sp 3 carbon–carbon coupling chemistry on SAAs. Furthermore, we discuss the effect of the iodine atoms on the reaction energetics and make an analogy between the effect of iodine as an active site blocker on this model heterogeneous catalyst and homogeneous catalysts in which ligands must detach in order for the active site to be accessed by the reactants.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

$\mathrm{IH}$-$\mathrm{GAN}$: A conditional generative model for implicit surface-based inverse design of cellular structures

Variable-density cellular structures can overcome connectivity and manufacturability issues of topologically optimized structures, particularly those represented as discrete density maps. However, the optimization of such cellular structures is challenging due to the multiscale design problem. Past work addressing this problem generally either only optimizes the volume fraction of single-type unit cells but ignoring the effects of unit cell geometry on properties, or considers the geometry–property relation but builds this relation via heuristics. In contrast, we propose a simple yet more principled way to accurately model the property to geometry mapping using a conditional deep generative model, named Inverse Homogenization Generative Adversarial Network (IH-GAN). It learns the conditional distribution of unit cell geometries given properties and can realize the one-to-many mapping from properties to geometries. Here we further reduce the complexity of IH-GAN by using the implicit function parameterization to represent unit cell geometries. Results show that our method can 1) generate various unit cells that satisfy given material properties with high accuracy (R 2 -scores between target properties and properties of generated unit cells >98%) and 2) improve the optimized structural performance over the conventional variable-density single-type structure. In the minimum compliance example, our IH-GAN generated structure achieves a 79.7% reduction in concentrated stress and an extra 3.03% reduction in displacement. In the target deformation examples, our IH-GAN generated structure reduces the target matching error by 86.4% and 79.6% for two test cases, respectively. We also demonstrated that the connectivity issue for multi-type unit cells can be solved by transition layer blending.

42 ENGINEERING↗
DOE OSTI2023

Observations and Machine-Learned Models of Near-Surface Permafrost along the Koyukuk River, Alaska, USA

This dataset contains GeoTIFs (raster) and GeoPackages (vector) that map observations of near-surface permafrost and not-permafrost from a field campaign conducted near the village of Huslia, AK along the Koyukuk River and its floodplain in July 2018. These data were collected as part of a campaign to understand if and how permafrost impacts riverbank erosion. This problem cannot be assessed without knowing where permafrost exists. Permafrost was observed via frost probing (to a maximum depth of one meter), coring (to a maximum depth of two meters) and bank/bar excavations. An additional boat survey was performed wherein expert (Joel Rowland) judgment assessed the presence or absence of distinctive permafrost features (e.g., overhanging tundra mats, thermoerosional niching, ice wedges, active drainage of ice melt from soils). This dataset also contains the input features and results of two machine learning models (random forest and convolutional neural network) that extrapolate the observations to the full floodplain that may be useful for building, testing, or validating other machine-learned permafrost models. Permafrost data are provided as georasters of the same shape and geovectors (polylines/polygons) and are all projected into EPSG:32605. All data can be visualized with a GIS (QGIS, ArcGIS, etc.).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Predictive numerical modeling of plasma-induced surface roughness and wettability evolution in LM-PAEK/CF tape

Plasma surface modification effectively enhances adhesion in thermoplastic composites, yet its impacts on high-performance polymers like low-melting polyaryletherketone (LM-PAEK) remain inadequately quantified. Here, this study integrates experimental analysis and numerical modeling to characterize surface roughness and wettability changes in LM-PAEK/carbon fiber composites treated with atmospheric plasma. Atomic Force Microscopy quantified surface topography (n = 10 per condition for contact angles), while static contact-angle assessments measured wettability. Roughness rapidly increased from ∼0.2 nm to 1.6 nm, and contact angle reduced from ∼90° to 24°, both stabilizing after 25–30 s of exposure. A semi-empirical, physics-informed framework was calibrated to these data, coupling surface chemistry via the Owens–Wendt decomposition with topography via the Wenzel roughness factor, and evaluated using out-of-sample (cross-validated) tests, while static contact angle assessments measured wettability. Numerical predictions matched experimental results closely (RMSE <5%, R 2 > 0.95). Incorporating material-specific parameters, the calibrated model supports plasma-treatment optimization and provides quantitative guidance for improving interfacial adhesion in thermoplastic composite manufacturing.

Atomic Force Microscopy↗
DOE OSTI2021

Impact of Lateral Flow on Surface Water and Energy Budgets over the Southern Great Plains – A Modeling Study

As we see the horizontal grid spacing decrease, treatment of hydrologic processes in land surface models, such as the lateral flow of surface and subsurface flow, need to be explicitly represented. Unlike previous studies that mainly focused on the mountainous regions, in this study the offline WRF-Hydro model is employed to study the impact of lateral flow on soil moisture and energy fluxes over the relatively flat southern Great Plains (SGP). The vast amount of measurements over the SGP provide an unique opportunity to assess the model behavior. In addition, newly developed land surface properties and input forcing are ingested into the model, in an attempt to reduce uncertainties associated with the initial and boundary forcing and help to identify model deficiencies. Our results show that the more realistic inputs (parameters, soil types, forcing) lead to larger underestimation of latent heat flux and dry bias, indicating the existence of model structural uncertainty (embedded errors) in WRF-Hydro that need to be characterized to inform future model development efforts. Including lateral flow processes partly mitigates the model deficiencies in representing hydrologic processes and alleviates the dry bias. In particular, both surface and subsurface lateral flow increase soil moisture mainly over the lower elevations, except that subsurface flow also affects soil moisture over steeper terrains. Additional simulations are performed to assess the effect of routing resolution on model results. When LSM resolution is high, noticeable differences in soil moisture are produced between different routing resolutions especially over steep terrain. Whereas when LSM resolution is coarse, differences between routing resolutions become negligible, especially over flat terrain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluation of distributed process-based hydrologic model performance using only a priori information to define model inputs

Fully distributed, integrated surface–subsurface hydrological models (ISSHMs) have seen renewed interest due to availability of better software, high performance computing facilities, and high-resolution, spatially extensive data products. ISSHMs are valuable as tools for advancing system understanding as they can resolve multiple processes defined on the plot scale including three-dimensional interaction of surface water and groundwater. Here, we evaluated the performance of an ISSHM, the Advanced Terrestrial Simulator (ATS), on seven diverse catchments across the continental US using widely available data products to define model inputs without calibration. We compare the ATS-simulated streamflow and evapotranspiration with gauge observations and MODIS-derived evapotranspiration, respectively. Using the Kling-Gupta Efficiency (KGE) as metric, ATS with default data products performed reasonably well at 6 of 7 catchments for streamflow. However, in one of those 6 catchments ATS had poor performance on baseflow and ATS’s overall performance was thus judged to be inadequate despite the acceptable KGE. ATS performance for evapotranspiration was good in all 7 catchments using default data products. In the two catchments where ATS streamflow performance using default data products was not acceptable, the performance was significantly improved by using local information on subsurface properties below the soil. We also compare the model-simulated streamflow and evapotranspiration with the Sacramento soil moisture accounting (SAC-SMA) model, a semi-distributed model that was calibrated on a catchment-by-catchment basis. Uncalibrated ATS performance is comparable to the calibrated SAC-SMA model in terms of streamflow while ATS performance is similar to or better (much better in certain catchments) in reproducing MODIS-derived evapotranspiration. Reasonably good performance of ATS without catchment-specific calibration provides new confidence in the ISSHM class of models and community data products as tools for advancing understanding of watershed function in a changing environment.

54 ENVIRONMENTAL SCIENCES↗